Accelerated by the coronavirus pandemic, the healthcare landscape is rapidly evolving, with a shift towards hybrid care models combining in-person and online care. To support this shift, the Radboudumc, an academic hospital in the Netherlands, decided to redesign an existing space facilitating the conduction of video consultations.The design process involved participation of end-users to ensure that the physical space met their needs. The look and feel of the area was based on evidence-based design guidelines. Two prototype setups were built and tested, and the feedback informed the final design of the Garden Room.Identified end-user needs were divided into 3 major categories entailing consultation room setup, optimal use of technology and practical issues involving room availability. Combined with the look and feel of the hospital, final design requirements were developed. The Garden Room consists of 18 video consultation rooms, 4 shared workspaces, relaxation area with kitchen, and meeting rooms. Specific attention is given to the ergonomics, technology and privacy in the rooms to facilitate optimal video conversations between patients and healthcare providers. In the Garden Room, natural elements and an open design supports working in a healing environment.Next challenge will be optimizing the use of the Garden Room, which may be hindered by various barriers like resistance to change, existing work processes, and lack of skills training. To address these barriers and support use of the Garden Room, the hospital should focus on the implementation of education, changes in work processes, and the presence of advocates for telehealth. One aspWith these developments, also hospitals are increasingly applying video consultations in their current environment. Incorporating in-person and online care into a single healthcare facility requires rethinking and redesigning the physical environment, meeting the needs arising from the application of video consultations of both patients and healthcare professionals. This may, for example, include the implementation of quiet rooms for video consultations within the existing facility to minimize hindering back ground noises during the conversation between the patient and healthcare professional. In addition, designing a video consulting experience requires attention for the virtual experience. The online background should, for example, be free from distractions and provide facility identification for an optimal focus on the conversation.In the design of the built and online environment, it is important to consider “human factors” by tailoring the environment to the needs, both physical and cognitive, of the end-users . For thaTuinzaal), was designated as a central area for video consultations. Here, we discuss the process of redesigning this area, considering needs of both patients and healthcare professionals such as control of environmental distractions and adjustment of audio and video facilities, and the look and feel of the Radboudumc as an input for the evidence-based design process. We conclude with a discussion on how to optimize the use of the video consultation area in the future.In this article, we describe the evidence-based design process of a video consultation area at the Radboudumc, an academic hospital in The Netherlands, Nijmegen. The Radboudumc is increasingly supporting hybrid care, including video consultations. The hospital foresees that healthcare delivery in the future will be largely remote. To support this shift, the built environment of the hospital is based on the vision of “less bricks, more bytes, different behavior” . Designi2.The design processes of the Garden Room were supported by the Hospitality Group, a design consultancy group in Amersfoort. To ensure that the design of the video consultation area was tailored to the needs of the end-users—healthcare professionals providing remote care—interviews were conducted, design requirements developed, and mock-up prototypes tested. Healthcare professionals for the interviews were selected by purposive sampling. Four medical professionals who frequently use video consultations and one member of support staff involved in the implementation of video consultations were asked to reflect on their work and needs. These professionals included a medical oncologist, a surgeon, a plastic surgeon, a pediatric pulmonologist and administrative planner . The interviews were conducted at the beginning of the design process by members of the design consultancy group. Questions revolved around the setup of equipment in the pod, the interior of the pod, technical requirements and requirements for conducting multidisciplinary consultations, optimization of the use of the pods ad a reservation system, important ergonomic conditions and any other essential facilities that should be considered in the Garden Room.All interviews lasted approximately 1 h and provided insights into the needs and preferences of the end-users. The collected information was presented to 11 end-users with varying specialties during two brainstorm sessions. Expressed needs were explained and additional questions were asked until a complete overview of the end-user's needs had been established. In addition to these user needs, also the need to align the design of the video consultation area with the look and feel of the Radboudumc was considered. Together, this resulted in a list of design requirements for the video consultation area.ad hoc developed evaluation form addressing (1) IT; (2) Acoustics; (3) Indoor climate; (4) Light; (5) Ergonomics; (6) Ambience; (7) Background view. The feedback from these evaluations informed the final design of the Garden Room.Based on this list of design requirements, we built and tested two prototype setups. Five end-users tested the prototypes using an 3.The end-user needs retrieved from the interviews and brainstorm sessions, combined with the look and feel of the hospital, eventually resulted in a list of design requirements which were the guiding principle for the design of the Garden Room. The video consultation area was designed and built between December 2020 and June 2022. 3.1.The identified needs from the end-users were categorized in three domains; consultation room set-up, technology, and room availability. The first category entailed requirements for a comfortable working space and efficient set-up to optimize the conversation. The second involved communication and electrical technology, the latter mainly practical conditions for scheduling a video consultation. An overview of the needs is given in 3.2.The Garden Room consists of a large space that has been divided into several sections: video consultation rooms, shared workspaces, a kitchen and relaxation area, and meeting rooms. A total of 18 video consultation rooms were installed using modular boxes, each of which can accommodate one or two healthcare providers -this latter is meant to supervise students. Each box is designed to be acoustically sealed for privacy of healthcare providers and patients during the consultation. Each box is further equipped with a desk with adjustable height, an ergonomic office chair, a dual screen display for showing both the video consult and the patient's electronic health record, a camera that can be adjusted to eye level of speaker, and sufficient charging outlets. These amenities are intended to facilitate efficient remote care consultations. The Garden Room is located in the center of the academic hospital. Healthcare providers can reserve the consultation rooms during the day via a reservation system, and presence sensors above the rooms indicate which rooms are occupied.The four shared workspaces offer healthcare providers a place to do administrative work and are located near the video consultation rooms to prevent unnecessary occupation of these rooms for non-video activities. The kitchen and relaxation area offer healthcare providers the opportunity to take breaks between video meetings and, when desired, accessing the hospital garden. The Garden Room also includes several meeting rooms for private meetings between healthcare providers, such as preparing for a video consultation.3.3.The design of the Garden Room follows the look and feel of the Radboudumc, adhering to six design guidelines: connection to nature, healthy living, innovation, openness and transparency, personalization, and professionalism. To foster a connection to nature, the Garden Room is not only providing direct access to a garden, but also incorporates many green and natural elements through the area, such as wood and greenery, combined with the use of a natural color scheme. Furniture is in most parts manufactured from recycled or recyclable material. The natural environment is intended to support relaxation and reduce stress, providing a healthy and healing environment for both patients and healthcare professionals. Additionally, to promote a healthy workspace, special attention has been given to the installation of a comfortable relaxation space and kitchen within the Garden Room, shown in Within the modular video consultation boxes, the look and feel is well considered; patients virtually see their healthcare provider in the center of their screen, surrounded by the hospital's logo, warm and natural colors and plants. Adequate lighting creates a professional appearance. Out of the patient's view, a small window gives the healthcare provider an open and transparent appearance and allows others to quickly check if the box is occupied or not. A script, outside of the patient's view, is also provided to support the healthcare provider during the video consult. 4.By considering the needs of end-users and the look and feel of the academic hospital, the Garden Room has become an open and natural space supporting hybrid care delivery. The room was put into service on July 1st 2022. Here we discuss how the design of the room is evidence-based and how use of the room can be scaled-up towards the future.4.1.Where possible, the Garden Room is based on best available scientific evidence for aligning physical and online space to the needs of end-users. The 2022 Guidelines for Design and Construction of Hospitals and Outpatient Facilities, for example, addresses design requirements for spaces used for telemedicine . One impFurthermore, previous EBD research has shown that natural elements in the environment, such as plants and a view on trees, improve healthcare outcomes of patients and the overall mental well-being and cognitive functioning of the healthcare professional –21. For In addition to visual comfort, the right technology and audio quality are crucial to facilitate effective and trustworthy communication. In case of technical failure, it is recommended to have alternative forms of communication available (such as a phone) .Finally, privacy is a major concern in video consultations. The Garden Room takes measures to ensure privacy through the use of acoustic sealing, opaque windows and the placement of normal windows only out of the patient's view .4.2.The Garden Room has recently been opened for use. In order to optimize the use of the Garden Room, there are several challenges that need to be addressed. The Garden Room is located centrally in the hospital in close in close proximity to the daily workplace of the healthcare professional as pointed out as relevant by the end-users . HoweverAnother barrier to the adoption of video consulting is resistance to change . Many heSo far, research mostly focused on the design of the physical space. Further research should consider the behaviour and work processes within the Garden Room to optimize adoption of video consulting. This could be achieved through post-occupancy evaluation by, for example, combining a satisfaction survey with interviews and quantitative field data collection. The survey and interview should comprise questions about how the formerly end-users’ needs are met and about their experience with other technical and functional aspects of the consultation room area, such as privacy and comfort . SubsequFinally, to further facilitate the adoption of video consulting, there may be a need to encourage and give audience to advocates for telehealth within the organization .4.3.The Garden Room is a unique area for video consultations within the built hospital environment. It shows that an existing space can successfully be transformed into a hybrid care environment. Part of the successful design of the Garden Room is that end-users were involved in the design process and human factors were closely taken into consideration. However, only few end-users were interviewed, as only those who already advocated the use of telehealth were included. It would have been valuable to also include the perspectives of those healthcare professionals who may resist the implementation of telehealth to increase the adoption towards the future.When successfully combining the post-occupancy evaluation results with the incorporation of behavioural and organizational improvements, the Garden Room will not only facilitate its function towards video consultation but also has the potential to be expanded in the future to include other forms of telehealth, such as remote monitoring of hospital and home-based patients.5.The Garden Room exemplifies how the built environment can facilitate new models of care delivery. By being situated in the center of an academic hospital that primarily provides in-person care, the Garden Room makes video consulting easily accessible to healthcare providers. The involvement of end-users in the design process and consideration of human factors in the design enables the Garden Room to meet the needs of healthcare providers. The incorporation of natural elements, comfortable workspaces, and appropriate technologies in the physical space can create a positive environment for both healthcare providers and patients. However, the adoption and effectiveness of the Garden Room will also depend on the behavior and work processes of the healthcare professionals using it. Post-occupancy evaluation, behavioral and organizational measures are now needed to understand and further promote the adoption of video consulting among hospital caregivers. Finally, as the healthcare landscape continues to evolve, it is essential to continuously explore the potential for incorporating other telehealth solutions and to adapt the design of physical space accordingly to promote scalability and sustainability of the Garden Room.


S. tuberosum) and Chrysanthemum morifolium (C. morifolium) to obtain greater yield and quality. However, pesticide use carries the potential for residues to remain and be detected on harvested crops. Therefore, the aim of this study was to estimate pesticide residues in S. tuberosum and C. morifolium products that are commercially available for human consumption and to assess the associated dietary risks. For this study, a total of 340 samples (200 S. tuberosum samples and 140 C. morifolium samples) were collected randomly from supermarkets and farmer’s markets. Residues of pymetrozine in S. tuberosum and C. morifolium were detected by using an established and validated QuECHERS-HPLC-MS / MS method, while a dietary risk assessment of pymetrozine in S. tuberosum and C. morifolium was performed using these data. The detection rates of pymetrozine in S. tuberosum and C. morifolium samples were 92.31% and 98.17%, respectively, with residues not more than 0.036 and 0.024 mg/kg, respectively. Based on these results, the dietary risk assessment indicated that the intake of pymetrozine residues in S. tuberosum and C. morifolium does not pose a health risk. This work improved our understanding of the potential exposure risk of pymetrozine in S. tuberosum and C. morifolium.Pymetrozine is used on potato ( S. tuberosum) is the fourth largest food crop after maize, wheat and rice [S. tuberosum cultivation area in the world. China is the fourth largest potato exporter in the world; its potato exports account for 6% of the world’s S. tuberosum exports. From 2011 to 2021, the output of S. tuberosum increased from 18.309 million tons to 21.055 million tons in China [C. morifolium is an important cultivar of medicinal and edible chrysanthemum floss, which is widely planted in different regions of China [S. tuberosum and C. morifolium have suffered from increased pests and diseases during the planting process, such as late blight, root rot, aphids and litura [S. tuberosum and C. morifolium in cultivation. According to the investigation from 2008 to 2017 on the national plant protection statistical data, the yield loss due to grubs and aphids was 11.65–18.60% in the two cropping areas of the central plains for China’s four major S. tuberosum growing regions, with a yield loss of 10.14% due to damage by aphids in the southern winter cropping area [C. morifolium is frequently attacked by various types of pests, including aphids, gall midges, leafhoppers and other pests, with aphid infestation covering more than 80% of the area [S. tuberosum and C. morifolium may suffer from various types of pest damage during the planting process, various pesticides are usually applied to control the above damage for better yield and quality.Potato  to determine residual pymetrozine levels in actual samples collected from different regions and (3) to assess dietary risk based on the residue data.Therefore, the purpose of this study is (1) to establish a method for the analysis of pymetrozine residues by using HPLC-MS/MS in 18), anhydrous magnesium sulfate (MgSO4) and primary secondary amines (PSA) were purchased from Tianjin Bonna-Agela Phenomenex Technologies . Water was purchased from Watsons . The pesticides were prepared as stock solutions using methanol at a concentration of 1000 mg L−1 and stored at −18 °C (replaced after three months).The standard for pymetrozine (purity > 97.7%) was obtained from Ehrenstorfer GmbH . Acetonitrile and methanol (chromatographic grade) were purchased from Merck . Absolute alcohol and acetonitrile  were supplied by Shanghai Lin-feng Chemistry Reagent Co. Ltd. . Sodium chloride (NaCl) and ammonia water (Mass fraction: 28%) were obtained from Sinopharm Co. Ltd. . Octadecyl silica  of China [S. tuberosum and C. morifolium samples for a total of 200 S. tuberosum samples and 140 C. morifolium samples. In 2022, 340 samples of of China . In eachC. morifolium samples were ground using dry ice and an electric grinder. The homogenizing machine was thoroughly cleaned with water and absolute alcohol to avoid cross-contamination in the next sample. The samples were frozen at −20 °C until extraction for analysis. All samples were collected and placed in black plastic bags to prevent contamination and spoilage, labeled and brought to the lab. S. tuberosum samples were chopped into small pieces and fully blended using the homogenizing machine. S. tuberosum and powdery C. morifolium samples was added in a 50 mL centrifuge tube, after which 10 mL of 0.1% ammonia-acetonitrile solution was added and samples were extracted by shaking for 15 min. The shaken samples were mixed with 1 g NaCl and 4 g MgSO4 and then centrifuged for 5 min at 4000 rpm. For extraction, 5 g of homogenized 4, 50 mg PSA and 50 mg C18 were added to the supernatant of S. tuberosum, and 150 mg MgSO4 and 50 mg PSA were added to the supernatant of C. morifolium). Then, we vortexed the sample for 1 min, followed by centrifugation at 8000 rpm for 5 min. We used a 0.22 μm filter to filter the extract before HPLC-MS/MS analysis.After centrifugation, 1.6 ml of the supernatant was purified in a QuECHERS tube (150 mg MgSO−1 and with a sample injection volume of 2 µL at 40 °C. The mobile phase was formed by using solvent A (acetonitrile) and solvent B (pure water). The elution program of the chromatographic gradient was carried out as follows: 0~2.5 min, 10% A; 2.5~3.5 min, 10~30% A; and 3.5~6.0 min, 30~10% A. The total separation time was 6.0 minutes.The pesticide was analyzed on a Waters ultra-high performance liquid chromatography triple quadrupole mass spectrometer (HPLC-MS/MS). Pymetrozine was separated using a Waters Acquity HPLC HSS T3 analytical column  at a flow rate of 0.2 mL minm/z 218.03→104.85  and m/z 218.03→78.39 , respectively. As for other parameters, the ion source temperature was set to 115 °C, the desolvation temperature was set to 450 °C, and the desolvation gas flow rate was set to 600 L h−1.Electrospray ionization (ESI+) was used for the mass spectrometric analysis of pymetrozin. The capillary voltage was set at 1.5 kV and the extractor voltage at 4 V. Multiple reaction monitoring (MRM) mode was performed to detect pymetrozine, and the quantification transition and qualitative transition values were −1, for which correlation coefficients (R2) were obtained according to the linear regression equation. Recovery experiments were performed on five replicate samples at three different levels to verify the accuracy of the method, expressed as the RSD (relative standard deviation) between parallel samples . The LOQ shows the lowest detectable concentration of pymetrozine in the sample. For the improvement of the analysis for the accuracy of pymetrozine, we performed an evaluation of the matrix effect. The matrix effect calculation was as follows (1) [m and SS are the slopes of the calibration curves for the matrix and the solvent, respectively. Matrix effects (MEs) were defined as the total influence of components in the sample other than pymetrozine on the measurement, which may inhibit or enhance the analyte signal. MEs ranging from −20% to 20% were considered low, those from −50% to 50% were considered moderate, and those <−50% or >50% were considered strong [Linearity, the limit of detection (LOD), the limit of quantification (LOQ), accuracy, precision and the method matrix effect were evaluated in different matrices to validate the proposed QuEChERS-HPLC-MS/MS method. Analytical curves were established to determine the linearity of the method at different levels of concentration of pymetrozine: 0.001, 0.01, 0.02, 0.05, 0.1 and 0.2 mg·Llows (1) :(1)ME%=Sd strong .S. tuberosum and C. morifolium. The chronic risk quotient (HQc) and acute risk quotient (HQa) were used to assess long-term and short-term dietary risk, respectively.A dietary risk assessment of pesticides derives dietary exposure estimates from calculated food consumption data and chemical concentrations in food for the target population to achieve risk characterization . The Chic) assessment for pymetrozine was conducted using Equations (2) and (3) [−1). Fi is the average daily consumption of agricultural products (kg day−1). The ADI of pymetrozine represents its acceptable daily intake (mg kg−1 bw). A chronic intake risk (HQ and (3) ,29:(2)NEa [S. tuberosum and C. morifolium (mg kg−1). LP represents the largest portion (97.5th percentile) of food consumed by individuals in a day (kg day−1). bw is the average weight of a Chinese adult, which is 63 kg. ARfD is the acute reference dose (mg k) of pymetrozine. The following formula is used to calculate NESTI and HQa ,31:(4)IEc or HQa is less than 100%, the risk is considered acceptable and to not pose a long-term health or acute intake risk, whereas when HQc or HQa is greater than or equal to 100%, it is considered to pose an unacceptable long-term or acute intake risk to consumer health.When HQ−1), which showed good linear relationships in all matrices (R2 > 0.99). The LOD for pymetrozine was 0.001 mg kg−1, while the LOQ was 0.01 mg kg−1 in the matrices  of pymetrozine in blank S. tuberosum and C. morifolium, respectively. The S. tuberosum ranged from 89.19 to 103.57%, with an RSD of 3.02~4.27%. The average recoveries of pymetrozine in C. morifolium ranged from 77.26 to 106.85%, with an RSD of 2.82~4.91%. The average recovery rates for different matrices varied from 70 to 110%, with a coefficient of variation less than 5%. Overall, the recovery and RSD of the method were in line with pesticide residue analysis standards. The method validation for pymetrozine determination in S. tuberosum and C. morifolium showed that pymetrozine could be determined.To evaluate the accuracy and precision of the established method for the determination of pymetrozine residues in S. tuberosum and 140 C. morifolium samples. As shown in S. tuberosum and C. morifolium samples were over 90%. The results showed that pymetrozine residues were relatively common in S. tuberosum and C. morifolium samples, suggesting that growers, consumers and government regulators should pay more attention to these issues. The detection range for S. tuberosum was <LOQ (0.01 mg kg−1) to 0.036 mg kg−1, and that of C. morifolium was <LOQ (0.01 mg kg−1) to 0.024 mg kg−1. According to the registration information, the recommended dose of pymetrozine in S. tuberosum  is higher than that in C. morifolium ; moreover, pymetrozine in S. tuberosum is used twice a season, and C. morifolium is used once a season [S. tuberosum (0.028 mg kg−1) and C. morifolium (0.019 mg kg−1), which may be due to different pymetrozine absorption and metabolism rates in different crops [S. tuberosum; 92.31% C. morifolium) was significantly higher than that not detected . Furthermore, S. tuberosum are tuber crops. Pesticides are partially dropped after spraying. Plants absorb pesticides from the soil and transport them, which partially enriches the stems to produce residues that may have caused the high detection rate of S. tuberosum. Another reason for the higher detection rate may be the widespread application of pymetrozine to protect crops.The validated method was used to detect pymetrozine residues in 340 commercially available samples, including 200 a season . Howevernt crops . In addiS. tuberosum and C. morifolium with pymetrozine residues to human health should be considered. The human health effects of pymetrozine were quantified as the risks of acute and chronic dietary intake. Pymetrozine assessment was defined in the Joint FAO-WHO Meeting of Pesticide Residues [Pymetrozine was detected in market samples, and the risk of eating Residues . TherefoResidues . In ChinS. tuberosum and C. morifolium was conducted next for Chinese people (S) and MRLs. The STMRs of S. tuberosum and C. morifolium were 0.02 and 0.017 mg kg−1 from the supervised test, respectively. The ADI for pymetrozine was 0.03 mg kg−1 day. [c value of S. tuberosum and C. morifolium was 86.71% (less than 100%) in Chinese people, indicating that the chronic dietary risk of pymetrozine in S. tuberosum and C. morifolium was acceptable.A chronic intake risk assessment for pymetrozine residues in e people . The totg−1 day. . ConsequS. tuberosum and C. morifolium was assessed next for Chinese people . The results showed that pymetrozine residues were relatively common in S. tuberosum and C. morifolium samples, suggesting that growers, consumers and government regulators should pay more attention to these issues. Moreover, we conducted a dietary risk analysis to determine the consumer safety of pymetrozine residues in S. tuberosum and C. morifolium. The results showed that the dietary risk of pymetrozine in both matrices was less than 100% and that the overall risk was acceptable. Together, these results provide an important data reference into the current prevalence of pymetrozine residues in S. tuberosum and C. morifolium in the Chinese market while also providing a useful tool for the analysis of pymetrozine residues in other media.In this study, the establishment of a method involving the QuEChERS-HPLC-MS/MS procedure and an analysis of samples with pretreatment achieved satisfactory results in terms of linearity, analytical limits, accuracy and precision. Furthermore, the method was utilized to detect pymetrozine residues in


The Coronavirus disease-2019 (COVID-19) outbreak has deprived simulation-based medical education for health care workers. Attendees are strictly prohibited to converge at a simulation training venue because of the COVID-19 outbreaks. To address this issue, we developed a web-conference-style remote simulation program using demonstration video clips. This report introduced the method and described participants’ satisfaction.This preliminary survey study evaluated learners’ satisfaction in multiple institutions. The Satisfaction Scale Questionnaire with High-Fidelity Clinical Simulation (SSHF) by a 5-degree scale was used to evaluate participants’ satisfaction. The survey was conducted immediately after completing the simulation sessions.P=0.005).Ten (100%) participants  from nine institutions responded to the survey. All median values of the satisfaction scores were ≥4.0, whereas the median values of scores for environmental fidelity and psychological insecurity were 3.5 and 3.0, respectively (A web-conference-style remote simulation using demonstration video clips is a feasible method for conducting simulation-based medical education under COVID-19 that showed high satisfaction scores. Further, additional studies are required to explore the internal and external validity and the effectiveness of mastery learning. Thus, a new SBME technique that does not require learners to congregate in one place is desired.Simulation-based medical education (SBME) is commonly performed as an effective training method to enhance individual clinical skills, judgment, team dynamics and resource management.2 However, a remote simulation was originally designed to remotely provide facilitation from the outside of the simulation site for the learners gathered at the simulation venue to perform a hands-on training. Therefore, the proposed method for remote simulation is not ideal to conduct SBME owing to the potential risks of COVID-19 outbreaks.Even under the COVID-19 outbreaks, remote simulation using telecommunication technologies can be a viable method in providing SBME since the learners can remotely participate in the simulation sessions via the internet.To address this issue, we modified the structure to prevent learners from gathering at the simulation venue, and they, along with the facilitators, participated in the SBME sessions remotely via the internet. The learners were unable to practice on-site simulation scenarios. Thus, we created demonstration video clips that were used as materials for discussion-based learning.This report presents the web-conference-style remote simulation using demonstration video clips and the survey results of participants’ perceptions.This was a preliminary survey study on anaesthesia providers, who participated in a web-conference-style remote simulation programme in October, 2021. This study obtained the approval of the Local Institutional Ethics Committee of Aichi Children’s Health and Medical Center .in situ anaesthesia simulation separately conducted each simulation session. After a brief explanation of the cases in each scenario, the learners watched a video clip of an unsuccessful demonstration. Further, the participants analysed the actions of the actors in the video clip in terms of teamwork/communication and medical expertise along with the prepared questions that were created based on the pre-determined checklists (Learners and facilitators remotely participated in the online conference sessions. The remote simulation was structured into a 50 min simulation session each for two scenarios (i.e. cardiac arrest and difficult airway). Two facilitators experienced in ecklists . Betweenecklists . Regardi4 The learners were expected to perform all of the pre-determined tasks in the checklists.Two distinct paediatric critical scenarios during general anaesthesia (i.e. cardiac arrest and difficult airway) were created. These simulation scenarios were designed to cover the pre-determined checklists of the learners’ expected actions for effective management in each critical event, and their expected actions were classified into two major categories: teamwork/communication and medical knowledge. The teamwork/communication checklists included team dynamics and interpersonal communication skills , whereas, medical knowledge checklists were developed based on the critical event checklists of SPA and PALS.5 This tool has four major categories  with three to four subcategories rated from 1 to 4. We selected most components from the tool based on the capability to learn them in discussion-style, knowledge-based learning.Two types of demonstration video clips were developed for successful and unsuccessful instances for each scenario  . For suc®, Wondershare, Shenzhen, China) (The demonstration video clips show: 1) the scene of implementing the pre-determined tasks by anaesthesiologists and operating room nurses, 2) the monitor displaying vital signs of the manikin and 3) subtitles describing the conversation among actors in the demonstration scenes. In advance, to create demonstration video clips for successful and unsuccessful instances, the demonstration scenes by actors in the operating rooms and the monitor of manikin’s vital signs were recorded simultaneously using video cameras. The recorded video files (i.e. MP4 format) of demonstration scenes were edited into the final demonstration video clips with subtitles of actors’ conversation using a video editing software  .The duration of both final video clips was ~7 min, which is divided into two parts because of the progression of each scenario. The first half focused on the situation awareness regarding the patient’s sudden deterioration and the team dynamics for early transition to initial treatments . In the second half, the patient’s condition deteriorated more, such that individual clinical skills, judgement, team dynamics and resource management were focused on situations requiring advanced medical management .6 SSHF is a validated evaluation tool of simulation sessions that originally comprised 38 closed questions evaluated by a 5-degree Likert scale, integrating into eight domains: 1) simulation utility, 2) scenario cases and applications, 3) team communication, 4) self-reflection on performance, 5) increase in self-confidence, 6) connection between theory and practice, 7) facilities and equipment and 8) negative aspects of the simulation session.6 The two questions in the original SSHF: 1) were removed because of their irrelevance to the simulation scenarios in the current study since learners did not have the opportunities to improve their communication skills with the patient and family members during general anaesthesia in the operating room.Anonymous survey forms were distributed to learners after completing the simulation sessions. The data regarding the characteristics of learners, including age, sex, post-graduate year and simulation experience  were collected. The Satisfaction Scale Questionnaire with High-Fidelity Clinical Simulation (SSHF) was used to determine the participants’ satisfaction with the remote simulation sessions.The primary investigator collected the survey forms and summarised the descriptive statistics of the results. The summary statistics were described in median [interquartile range (IQR)] or number (%). The median values of the score in each questionnaire item were compared using the Kruskal-Wallis test. All summary statistics were calculated using STATA 17.0 .The simulation sessions involved 10 learners  from nine institutions. The response rate was 100%.The following are the learner’s characteristics: age, median (IQR), 30 (27-33); female, 5/10 (50%); previous experiences of manikin-based simulation, none 4/10 (40%); limited 4/10 (40%); moderate 2/10 (20%).P=0.005).The median values of the scores of learners’ satisfaction for the remote simulation were ≥4.0, except for the median values for the two items “the reality of facilities and equipment” (3.5) and “I was thrown off balance during some of the cases” (3.0) . There wThis was the preliminary survey study to conduct a web-conference-style remote simulation using demonstration video clips and evaluate the perceptions of the learners. The overall satisfaction scores of the learners were generally high, whereas the scores for environmental fidelity and psychological safety were relatively lower compared with the other items.in situ simulation training for anaesthesia providers to avoid participants from different sites assembling in a single venue. In the remote simulation, two potential methods exist: 1) trainees assemble in the operating room to begin a simulation scenario as a resuscitation team and the facilitator remotely teaches learners via the internet and 2) faculty members assemble in the operating room to proceed with a simulation scenario as a resuscitation team and learners remotely lead the team via the internet, However, proceeding a simulation scenario requires several participants (learners or faculty members), in both methods, to conduct the simulation scenario in each simulation training session. Therefore, we developed a web-conference-style remote simulation technique using video clip materials that allow all participants  to independently participate in the simulation sessions.The COVID-19 outbreaks have enforced medical educators to conduct SBME using virtual platforms. A remote simulation in operating rooms can now be a solution to provide The present study showed high learners’ satisfaction despite a lack of opportunities for learners to physically conduct the simulation scenario in the operating room. However, scores for environmental fidelity and psychological safety were relatively lower than that for other domains. These results are attributed to several explanations. First, learners participated in the simulation session to engage in the discussion for improving situation awareness, team dynamics, medical knowledge and clinical judgement from clinical scenes in the video clip materials that they watched on their computer screens. The absence of in-situ training in the operating room might have unsatisfied learners regarding environmental fidelity. Advanced virtual technologies  providing realistic remote simulation are considered a solution for providing sufficient environmental fidelity to learners participating in the remote simulation via the internet. Second, our simulation programme was developed as a practical session at an academic conference. Therefore, the simulation sessions that can endanger the learners’ psychological safety because these simulation sessions were watched by other audiences via the online video-sharing platform. Our web-conference-style remote simulation can be performed within a closed community enabling facilitators to provide a psychologically safe environment for learners.There are several strengths in our web-conference-style remote simulation technique, except for minimising the risk of COVID-19 outbreaks. First, compared with the conventional manikin-based simulation, this web-conference style simulation can accommodate more participants. Despite the number of roles in a simulation scenario being limited , the current new remote simulation is performed in a discussion-based style, which allows numerous individuals to participate simultaneously via the internet. Second, the participants can repeatedly review the performance of the actors by comparing successful and unsuccessful instances. Comparisons of failed and ideal instances can clarify issues happening in real-life critical situations and provide solutions in that clinical context.7There are several significant limitations in this study. First, a small sample size was used in this preliminary survey study. However, this new method can accommodate more people compared with conventional in-situ manikin-based simulation. Thus, further prospective studies with larger sample sizes are considered feasible. Second, most participants were unfamiliar with all components  due to a lack of knowledge and skills. The unfamiliarity with the simulation training could result in high satisfaction scores for the current simulation program. However, our simulation program did not provide opportunities for skill training. This simulation program mainly focused on learning the knowledge aspects of the major components  for successful resuscitation because a COVID-19 surge eliminated learning opportunities for novice trainees regarding team resuscitation. Third, the mastery of learning teamwork/communication and medical knowledge was not evaluated. Fourth, this remote simulation was performed in paediatric anaesthesia scenarios, which require further validation assessment in other clinical scenarios . Finally, this study does not dismiss the significance of manikin-based simulation procedures. However, in critical situations, the currently modified remote simulation cannot substitute manikin-based simulation practices to improve situation awareness and review the local response systems. Further, this new method is situated between the knowledge and practice levels in Miller’s pyramid, which facilitates learners to develop a realistic image of appropriate actions to maximise the team dynamics during critical events.Under the COVID-19 outbreaks, a web-conference-styled remote simulation, which uses demonstration video clips can be a feasible approach for simulation-based education. Further additional prospective investigations that evaluate the effectiveness of mastery learning and validation study are required.


This study aimed to explore the risk factors of malnutrition in patients with heart failure and construct a novel nomogram model.A cross-sectional study based on the STROBE checklist. Patients with heart failure from July 2020 to August 2021 were included. Patients were divided into a malnutrition group and a normal nutrition group based on the Society's recommended AND-ASPEN standard. Logistic regression was used to analyze the independent risk factors for malnutrition. A new prediction model of nomogram was constructed based on the risk factors, and its fit and prediction performance were evaluated. Of 433 patients, 66 (15.2%) had malnutrition and 367 (84.8%) had normal nutrition, Logistic regression analyses showed that the risk factors for malnutrition were total protein, hemoglobin, triglyceride, and glucose levels. The regression model based on the above four variables showed an area under the curve of 0.858. The novel nomogram model had a sensitivity of 78.5% and a specificity of 77.3%. After 2000 bootstrap resampling iterations, AUC was 0.852.The novel nomogram model can predict the odds of malnutrition in patients with heart failure at the early stage of admission, and can provide a reference for nursing staff to optimize nutritional care for inpatient with heart failure and to develop a discharge nutritional care plan. The preMalnutrition is a disease in which the intake of various nutrients is insufficient or imbalanced, leading to a decrease in body function and a deterioration in clinical outcomes . MalnutrDisease-related malnutrition significantly increases medical costs, and its importance in the course of the disease remains underappreciated . The malMalnutrition is a modifiable risk factor that clinicians and caregivers can act on . As the Nutritional assessment to determine the nutritional status or nutritional risk of patients with heart failure is the first step in nutritional management. Current guidelines recommend timely assessment of the nutritional status of patients with HF . This stMedical nomogram prediction models are used to describe a statistical prognostic model using biological and clinical variables, which allow the model to be presented in a graphical manner . The nomThe study was a single-center cross-sectional study. Our cases were from patients who admitted to the department of cardiology in a hospital in Shandong, China from July 2020 to August 2021.The inclusion criteria were as follows: (1) being older than 18 years, (2) HF was diagnosed according to the recommendations of the Chinese guidelines for the diagnosis and treatment of HF , (3) PatIn this study, the purpose of the study and informed consent were explained to patients at the time of admission, and basic patient information was collected by questionnaire within 24 h after admission, while the first clinical laboratory indexes were collected in the hospital electronic case system, including (1) basic conditions: age, gender, New York Heart Association (NYHA), BMI; (2) disease conditions: heart rate, etiology of HF, the Charlson comorbidity index (CCI); (3) laboratory tests: serum albumin, glucose, NT-proBNP, serum sodium, hemoglobin, cholesterol, lymphocyte count, etc.; (4) ancillary tests: electrocardiogram, echocardiogram. All data were entered by 2 researchers, and the data set was validated and cleaned to prevent any further changes before statistical analysis was performed.This study complied with the Declaration of Helsinki and was approved by the research ethics committee of hospital. Informed consent was obtained from all the participants prior to any study-related activities.Body mass index (BMI) was calculated for all patients, defined as the body mass (in kilograms) divided by the square of the body height (in meters) .Charlson Comorbidity Index (CCI), a weighted index that explains the presence of 17 co-morbidities .This study identifies malnutrition patients based on the AND-ASPEN criteria recommended by the Society, which include energy intake, weight loss, and physical findings from a nutrition focused physical examination (NFPE). We defined nutritionally normal as patients who did not meet the criteria for moderate or severe malnutrition, and malnutrition patients as those who met the criteria for moderate or severe malnutrition.U test was used for comparison between groups; categorical data are expressed as [n (%)], The chi-square test was used to compare proportions between groups.All the statistical analyses were performed using IBM SPSS/WIN version 26.0 and R 4.1.1. Measures conforming to a normal distribution were expressed as [mean ± SD], and group comparisons were made using Independent Student's t-test; Measures that did not conform to a normal distribution were expressed as median [M ], and the Mann-Whitney P values were two sided, and values <0.05 were considered significant.The tolerance and variance inflation factor (VIF) were used to analyze the multicollinearity of the samples, and all the variables in this study had VIF <5, which is considered to indicate a lack of collinearity problem between the variables. Univariate logistic regression was used to examine the relationship between each risk factor and the nutritional normal group and the malnutrition group. Variables that were significant in the univariate analysis were included in the multifactorial logistic regression model. Models were constructed based on the results of multifactorial logistic regression to facilitate the use of the nomogram in clinical practice. The nomogram-based risk prediction model was established using R4.1.1 software. Model performance was validated by the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow statistic, sensitivity, and specificity. The closer these metrics are to 1, the better is the model performance. A 2000-fold bootstrap resampling method was used for internal validation of results. The AUC was used to test the performance of the prediction model. The model was assessed for clinical utility using decision curve analysis (DCA). All P < 0.05). The differences in age, gender, sedentary hours, smoking history, drinking history, and NHYA classification were not statistically significant   ng/L. More than 70% of patients had severe symptoms (NYHA class III/IV). 66 (15.2%) of the 433 patients had malnutrition and 367 (84.8%) were nutritionally normal. There was a statistically significant difference between the malnutrition group and the normal nutrition group in terms of etiology of HF, CCI, and type of admission ( > 0.05) .P = 0.044), HGB (P < 0.001), LYM (P < 0.001), BUN (P = 0.001), TP (P < 0.001), TG (P < 0.001), HDL (P = 0.020), GLU (P = 0.026), NA (P = 0.011), NT-proBNP (P < 0.001) may be associated with increased the odds of malnutrition. In addition, there was no statistically significant difference between the two groups for BMI, RDW, BUN, LVEF, and CTNI (P > 0.05)  .P < 0.05 in the univariate analysis were included in the multivariate analysis, including etiology of HF, CCI, type of admission, admission heart rate, HGB, LYM, BUN, TP, TG, HDL, GLU, NA, and NT-proBNP. A stepwise method was used to select variables. The results of the multifactorial analysis showed that TP , TG , HGB , GLU  were an independent risk factor  = e(17.429 + −0.268 × TP + −0.022 × HGB + −0.676 × TG + 0.161 ×  GLU)/ (1 + e(17.429 + −0.268 × TP + −0.022 × HGB + −0.676 × TG + 0.161 × GLU)).The risk prediction model equation is as follows, P < 0.001]. The results showed that the Hosmer-Lemeshow test P = 0.098, and the optimal cut-off value of AUC was 0.174 based on the maximum principle of Youden index, where it yielded an accuracy of 77.3%, a sensitivity of 78.5%. This indicates that the model fits better and performs better with the data of this study  for the model revealed that when the threshold probability of an individual was between 20% and 95%, application of this model to predict the odds of malnutrition would add net benefit than applying either the treat-all or treat-none strategies .In this study, the general demographic data, and clinical laboratory biochemical indices of 433 hospitalized patients with HF were analyzed. Malnutrition and normal nutrition patients for this study were identified according to the AND-ASPEN criteria recommended by the Society. In our study, the prevalence of malnutrition was as high as 15.2%. After logistic regression analyses, total protein, hemoglobin, triglyceride, and glucose levels were found to be independent risk factors for malnutrition in patients with HF. A risk prediction model for malnutrition in patients with HF based on risk factors was constructed and presented in the form of a line graph . The nomThis study found that for each unit of elevation in total protein, hemoglobin, and triglyceride, there was a corresponding decrease in the odds of malnutrition in patients with HF. In clinical practice, clinicians prefer the advantages provided by blood metabolic indicators in patients with HF who are malnutrition or at a the odds for malnutrition. Zhang et al.  conducteThe normal range of serum total protein is usually between 6.0–8.3 g/dl, and studies have found that serum total protein levels <6 g/dl serve as a useful biomarker for malnutrition in adults . We did Normal hemoglobin range is generally defined as 13.5–17.5 g/dl for men and 12.0–15.5 g/dl for women , The WorAnother finding of our study was that each unit increase in glucose resulted in a 0.177-fold increase in the odds of malnutrition. There is often a relationship between glucose levels and malnutrition. Poor glucose tolerance is a feature of protein-energy malnutrition, and the prevalence of malnutrition-related gestational diabetes syndrome was found to be high in several hypothetical studies of pregnant women in the prenatal and postnatal periods. In addition to these prenatal effects, postnatal malnutrition may lead to sustained impairment of insulin secretion and glucose tolerance, leading to an increased chance of diabetes prevalence later in life –43. ElevThe traditional logistic prediction model is an equation that requires formula conversion to obtain predictive values, and nurses using such a tool in a tedious clinical environment may often miss the best time to intervene. Nomogram prediction models, which are visual presentations, allow nurses to screen patients with HF who are at a high odds of malnutrition, more easily and quickly and is more suitable in a clinical setting. For patients who are judged to be at an increased odds for malnutrition by this approach, nursing staff should develop detailed, individualized care plans to ensure that the patients receive the necessary nutrients in a timely manner to avoid causing malnutrition. In addition, although age and other variables may not be a factor in the nomogram prediction model in this study, we believe that these variables are also clinically important. We tried to include these variables, which were not statistically significant in the univariate analysis but were considered clinically significant, in the final model and found no significant increase in the predictive efficacy of the model. To present a fast and efficient tool, we decided to only include four variables. We believe that in addition to applying the model to identify patients with HF with malnutrition in a clinical setting, nurses should also pay some attention to factors such as age and co-morbidities in actual clinical work, which can provide more information for the overall health management of patients and reduce the occurrence of malnutrition in patients with HF, thus reducing the occurrence of poor prognostic outcomes.The conditions of data collection in this study led to a relatively homogeneous perspective of the prediction model. However, we believe that including serum biochemicals as a part of routine blood tests to identify patients with HF at the odds for malnutrition is a quicker and more convenient means for carrying out predictions. This study was a single-center study with a limited sample size, and only internal validation of the nomogram model was needed for external validation. We will expand the sample size in future studies and prospectively explore changes in malnutrition over time in patients with HF to assess the predictive validity of the model.Total protein, hemoglobin, triglyceride, and glucose levels are independent risk factors for malnutrition in patients with HF; based on the four risk factors, a new nomogram model was constructed to predict the odds of malnutrition in patients with HF. The model demonstrated good fitting effect and discriminatory ability. The model can help clinicians and nurses to complete the screening for nutritional risk at an early stage of patient admission and predict the odds of malnutrition in patients with HF. Moreover, with our findings nursing staff can implement early interventions and precise management strategies based on these risk factors, and provide a basis for optimizing effective nursing strategy.


K ~ ω/c were dominant in the scattered waves near the SPhP wavelength. In addition to the conventional passive detection mechanisms for metals, the proposed detection scheme will be a versatile passive detection model in the near future.In this study, we passively analyzed the near-field characteristics of thermally excited evanescent waves, which are radiation waves generated by the local dynamics of materials, including electron motions and lattice vibrations. The thermally excited evanescent waves on aluminium nitride (AlN) and gallium nitride (GaN) were measured using passive spectroscopic scattering-type scanning near-field optical microscopy (s-SNOM) in the wavelength ranges of 10.5–12.2 μm and 14.0–15.0 μm, which include the surface phonon-polariton (SPhP) wavelength of the studied dielectrics. We determined the unique decay characteristics of AlN and GaN, indicating a ten-fold increase in the probe area contributing to the scattering of waves near the SPhP wavelength compared to that in other wavelength ranges. The extended probe area correlated with the polariton decay lengths, indicating that the non-enhanced polaritons around  By detecting these thermally excited evanescent waves, local information on the material’s dynamic properties can be obtained.All matter radiates heat unless it is at an absolute zero temperature. Randomly changing charge distributions owing to local fluctuations, including electron motions and lattice vibrations, can generate strong localized electromagnetic (EM) waves on a material surface—that is, thermally excited evanescent waves (wavelength range: 8–20 μm)2. In most conventional s-SNOM techniques, excited waves induced by external illuminations are detected to obtain a localized optical response5. s-SNOM with external illumination is called active-type s-SNOM and can be used to analyze excited waves—including light-plasmon coupling6, light-phonon coupling7, and molecular fluorescence resonance8. However, thermally excited evanescent waves cannot be detected using active-type s-SNOM because strong external illumination disturbs the local dynamics—that is, an s-SNOM technique without external illumination (passive type) is required to analyze local dynamics9.Scattering-type scanning near-field optical microscopy (s-SNOM) is one of the most widely used nanoscale measurement tools for analyzing local material properties. The scanning probe scatters localized waves below the probe apex and provides information on the near-field EM waves induced by localized physical or chemical phenomena10. It comprises a charge-sensitive infrared phototransistor (CSIP)11, confocal optics, and a shear-force-based atomic force microscope (AFM). The noise equivalent power of the CSIP is ~ 7 × 10−20 W/Hz1/212, making possible the detection of thermally excited evanescent waves without the use of external illumination. The passive s-SNOM technique has been applied to the nanoscale measurement of lattice (Joule heating) and electron  temperatures14. Moreover, a principle for the passive near-field detection of metals has been developed, and used to demonstrate that only the forefront of the probe apex was dominant in the scattering of evanescent waves15.Over the last decade, passive-type s-SNOM in the long-wavelength infrared (LWIR) range has been developed7. SPhPs are excited in the absorption band called the Reststrahlen band that is an energy band between the transverse-optic (TO) and longitudinal-optic (LO) phonon frequencies16. The Reststrahlen band exhibits high reflectivity as waves cannot propagate within the medium. The SPhPs have been analyzed using active-type s-SNOM; however, the localization characteristics of the thermally excited evanescent waves in the Reststrahlen band without light exposure have not been discussed owing to the lack of an ultra-sensitive passive detection technique. To clarify the passive detection characteristics, a thorough passive analysis near the surface phonon-polariton (SPhP) wavelength—that is a wavelength around K ~ 17. We performed passive near-field measurements of aluminum nitride (AlN) and gallium nitride (GaN), in which their SPhP wavelengths were 11.8 and 14.1 μm, respectively. We compared the characteristics of the passively detected near-field signals of Au, AlN, and GaN and examined the differences in the scattering mechanism of the evanescent waves.In the active s-SNOM measurements in the LWIR range, optical phonons and phonons are coupled in a specific condition, and the surface phonon polaritons (SPhP) emerge for many materialsK ~ The principal aim of this study is to clarify the characteristics of thermally excited evanescent waves of dielectric materials in the Reststrahlen band and develop a principle for the passive near-field detection of dielectric materials. We performed a near-field decay analysis—measuring changes in the near-field signal using different probe heights—and calculated the probe area that contributed to the scattering of the evanescent waves. We demonstrated that the polarized area of the probe apex contributing to wave scattering extended only in the Reststrahlen band. The tip-polarized area in the Reststrahlen band had correlation with the polariton decay length, in which local minimum was found at the SPhP wavelength. The extended polarized area demonstrated that the characteristics of the detected near-field signals were determined primarily by waves with lower fluctuation modes, that is non-enhanced polaritons around 17. The thermally excited evanescent waves are scattered using the AFM scanning probe, and the scattered waves are collected by means of a Ge objective lens. The waves collected by the Ge objective lens pass through a pinhole of diameter 250 μm; waves outside of the focus position are removed. The spatial resolution is 50–150 nm, depending on the apex radius of the scanning probe. A specific wavelength can be selected by rotating the diffraction grating using a piezoelectric stage. Waves reflected at 30° from the incident light are detected at the CSIP. The diffraction grating is a blazed-type grating with a rectangular apex—the grating pitch and the blazed angle being 15.5 μm and 17°, respectively—as shown in Fig. 18. The first-order diffraction light being detected primarily at the CSIP19.Figure m, λ, θi, and 20. Figure 17. A strong signal owing to the zeroth-order diffracted light (m = 0) is evident at λ = 0 μm. The FWHM of the zeroth-order peak is ~ 150 nm, indicative of the wavelength resolution of the passive LWIR spectroscopic s-SNOM mechanism. A smaller peak in the wavelength range of 13.8–15.2 μm is a detection peak of the first-order diffracted light (m = 1), the detection range depending on the optical response of the CSIP.With passive LWIR spectroscopic s-SNOM, two different diffraction lights can be detected—namely, the zeroth- and first-order diffracted light. The detection wavelength can be calculated using the grating equation, entclass1pt{minimaz, ω,  T denote the sample-probe distance  was 14 Hz and the amplitude 100–900 nm, depending on the sample material.During near-field measurements, the CSIP senses signals owing to background radiation in addition to near-field signals. To extract the near-field signal, the CSIP signal can be modulated by vertically vibrating the scanning probe on the sample. The probe vibration frequency . During passive near-field measurements on a metal in which external illumination is not used, only the forefront of the scanning probe contributes to the scattering of the evanescent waves because the scattered waves are primarily due to the evanescent field on the material surface, as shown in Fig. 15. However, in conventional active near-field measurements with external illumination, a larger area of the probe apex contributes to the scattering of EM waves because the external illumination generates a larger spot size, including the probe shaft 15. Conversely, the decay length of the near-field signals obtained with active s-SNOM  is larger than 1 μm with a modulating frequency of Ω and it decreases to several tens of nanometers with higher harmonics (2Ω or 3Ω)24. The shorter decay length (< 100 nm) with Ω proves that the near-field signal does not include signals due to background radiation.Figure ncy Ω = 1 Hz. Durincy Ω = 1 Hz. Duri23:r denote the dielectric constant of the probe and sample materials and the effective radius of the probe apex, respectively. In Eq. , as shown in Fig. 15. Therefore, the effective radius (r) of the probe apex can be calculated using the actual tip radius (a)—that is, The near-field signals obtained at the CSIP are the interaction waves between the probe and the thermally excited evanescent waves. The probe apex is polarized by thermally excited evanescent waves, the probe-apex polarization enhancing the local EM waves. The tip-scattered near-field signals can be described using the Mie theory as follows15. The polarized dipoles induced with different phases are cancelled out in the probe apex if the wavelength is smaller than the apex size. Figure m = 0) and calculated near-field signals using Eq. (hp) can be determined by curve fitting using the near-field decay curve—that is, In the near-field measurement, the detectable wavenumber is restricted by the radius of the probe apex—that is, entclass1pt{minima25. The −1 and 891 cm−1 for AlN, and 532 cm−1 and 734 cm−1 for GaN, respectively27. The Reststrahlen bands of AlN and GaN are 11.2–16.4 μm and 13.6–18.8 μm, as shown by the dot- and line-filled area in Fig. z = 10 nm. AlN and GaN exhibit their maximum EM-LDOS at the SPhP wavelengths which are 11.8 μm and 14.1 μm, respectively, these wavelengths (frequencies) being located between In the passive near-field measurement of metal, the intensity of the near-field signal decreases exponentially, as shown in Fig. 12. By using these two CSIPs, we could clarify the characteristics of the passively detected near-field signals near the SPhP wavelength of AlN (11.8 μm) and GaN (14.1 μm). We obtained the AlN and GaN decay curves and clarified the differences in the decay characteristics at each wavelength. As shown in Fig. In this study, we used two CSIPs capable of different color detection—that is, the 14.5-μm CSIP (detection wavelength range: 13.8–15.2 μm) and the 11.3-μm CSIP (detection wavelength range: 10.5–12.2 μm)d = 100 nm) at wavelengths of 14.2, 14.5, and 14.8 μm. The radius of the probe’s apex (a) used for measurements was ~ 100 nm. These wavelengths are longer than the SPhP wavelength but still within the Reststrahlen band. The near-field signals decrease exponentially with a decay length of ~ 50 nm. The decay characteristics are similar to those of Au, as shown in Fig. Figure z =  ~ 50 nm, which gradually decays with a decay length of 180 nm.Figures d) of 330 nm.The highest SNR in a range of z = 120 nm and the decay length being ~ 250 nm , as shown in Fig. hp is sufficiently shorter than the actual tip radius (a)15. The longer decay length observed near the SPhP wavelength indicates that the polarized sphere in the probe apex is potentially larger than that used in the conventional model. Here, we assume The near-field decay curves of AlN and GaN at the SPhP wavelength show that the decay length is greatly extended, the signal strength being 10r) by taking the geometric average of a and hp (hp) can be calculated via curve-fitting analysis using the experimentally obtained near-field decay curves at each wavelength. An example of the curve fitting of the AlN decay curve at a wavelength of 11.8 μm is shown in Fig. We can describe the effective radius  at hp (200–400 nm) at hp (80–100 nm) at 1—which is given by The calculated polarized areas of the probe apex in the W-AlN and W-GaN probing systems in the Reststrahlen band exhibit the following characteristics  because the detection wavelengths are limited by the optical property of the CSIP. A more detailed analysis would be possible using a CSIP with an extended detection range. Recently, a multicolor CSIP with a two- or three-fold detection wavelength range was developedIn this study, we conducted a passive decay analysis of thermally excited evanescent waves using passive LWIR spectroscopic s-SNOM. The unique near-field decay characteristics of AlN and GaN were observed near the SPhP wavelengths and were attributed to the extended vertical axis of the polarized sphere in the probe apex, which contributed to the scattering of thermally excited evanescent waves. In the conventional passive detection model applied to the measurement of a metal surface, it is assumed that only the forefront of the probe tip contributes to the scattering of evanescent waves; thus, fluctuation modes with higher wavenumbers are included in the scattered waves. In this study, we proposed a passive detection scheme near the SPhP wavelength with an extended polarized area. The vertical axis of the polarized sphere in the Reststrahlen band correlated with the polariton decay length, indicating that the polariton components with lower fluctuation modes were more dominant in the scattered near-field signals. This finding provides a basic model for detecting dielectric materials. In addition to the conventional passive detection mechanisms for metals, a more versatile detection model will be developed in the near future. Passive LWIR spectroscopic s-SNOM with a versatile detection model will be a powerful tool for analyzing the local dynamics.The scanning probe was fabricated by electrochemical etching of a tungsten (W) wire of diameter 50 μm. The tungsten wire was dipped into the electrolyte (33% KOH solution) and 950 mV AC voltage was applied. The etching was automatically stopped when the current reached 0.02 mA to prevent the over-etching.20. We machine the grating  by Ultra Precision Machine, ROBONANO  with the cutting accuracy of 0.3%. The rotation angle of the grating was measured using a capacitance encoder (UNISOKU corp.).The confocal pinhole, diffraction grating, and CSIP were placed in a cryostat to maintain a temperature of ~ 4.2 K to operate the CSIP properly and remove any environmental noise owing to these optical components. The sample, probe, and Ge objective lens were kept at room temperature. The diffraction grating was designed to have more than 60% first-order diffraction efficiency and less than 8% second-order diffraction efficiency using the scalar theory of diffraction29. The probe was attached to the quartz tuning fork and oscillated horizontally at the resonant frequency of the tuning fork (~ 31 kHz). The conductance of the tuning fork decreases when the probe-sample distance is less than 30 nm. The conductance of the tuning fork was monitored and kept constant using a feedback loop. The probe was also vertically vibrated at a frequency of 14 Hz to eliminate signals induced by background radiations. The change in the CSIP signals owing to the vertical vibration was regarded as the near-field signals. The near-field signals were obtained using a lock-in amplifier with a reference frequency of 14 Hz.The probe height was precisely controlled using a shear-force-mode AFM system and maintained at 5–10 nm above the sample surface during the near-field measurementsAll samples have an Au strip with a thickness and width of 100 nm and 25 μm, respectively. The Au strip was fabricated by the thermal deposition method. The substrates are AlN or GaN crystals with thicknesses of 350 ± 15 μm on sapphire. All samples were cleaned with acetone and isopropyl alcohol (IPA) before the experiments.Supplementary Information.


Paenibacillus polymyxa complex have broad-spectrum activities against fungi and bacteria. Their antibacterial activities against soft rot Dickeya and Pectobacterium phytopathogens containing multiple polymyxin-resistant genes were not clear. Here, we selected nine strains within the P. polymyxa complex having broad-spectrum antagonistic activities against phytopathogenic fungi and a polymyxin-resistant D. dadantii strain causing stem and root rot disease of sweet potato and did antagonistic assays on nutrient agar and sweet potato tuber slices. These strains within the P. polymyxa complex showed clear antagonistic activities against D. dadantii in vitro and in vivo. The most effective antagonistic strain P. polymyxa ShX301 showed broad-spectrum antagonistic activities against all the test Dickeya and Pectobacterium strains, completely eliminated D. dadantii from sweet potato seed tubers, and promoted the growth of sweet potato seedlings. Cell-free culture filtrate of P. polymyxa ShX301 inhibited D. dadantii growth, swimming motility, and biofilm formation and disrupted D. dadantii plasma membranes, releasing nucleic acids and proteins. Multiple lipopeptides produced by P. polymyxa ShX301 may play a major role in the bactericidal and bacteriostatic actions. This study clarifies that the antimicrobial spectrum of polymyxin-producing bacteria within the P. polymyxa complex includes the polymyxin-resistant Dickeya and Pectobacterium phytopathogens and strengthens the fact that bacteria within the P. polymyxa complex have high probability of being effective biocontrol agents and plant growth promoters.Polymyxin-producing bacteria within the  Pectobacterium and Dickeya bacteria produce multiple pectinases and cause destructive soft rot diseases of numerous crops and ornamental plants and great economic losses worldwide  × 100. The in vivo inhibition rate (%) was calculated by [1-(diameter of maceration zone by D. dadantii with Paenibacillus/diameter of maceration zone by D. dadantii without Paenibacillus] × 100. strains  using thP. polymyxa stain ShX301 was determined using the in vivo assay with sweet potato seed tubers as previously described + and [M+K]+. Fusaricidins also appeared as open-chain products [M+H+H2O]+ [m/z 802–865, m/z 904–946, m/z 984–1052, m/z 1101, m/z 1122, m/z 1144–1225, m/z 1542–1559 and m/z 1753) in the range of m/z 800–1800 from CFCS of P. polymyxa ShX301  to resist polymyxins [Pectobacterium carotovorum (formerly Erwinia carotovora) [D. dadantii CZ1501 resists 2 μg·mL−1 of polymyxin B, multiple polymyxins produced by P. polymyxa ShX301 may accumulate to a locally high concentration, contributing to the cytotoxic action on the damage of D. dadantii plasma membrane and the inhibition of D. dadantii growth in vitro, in vivo, and in planta. Pelgipeptins produced by Paenibacillus have broad-spectrum activities against Gram-positive and Gram-negative bacteria and fungi, including phytopathogens [Bacillus and have potent antifungal activity and limited antibacterial activity [P. carotovorum [P. polymyxa ShX301 may also contribute to the cytotoxic action on D. dadantii.MALDI-TOF-MS revealed that bacteria ,31 and tbacteria , while Dlymyxins . Howeverotovora) . Here, aathogens ,29,33,34activity , have alotovorum . The pelD. dadantii to colonize plant surface, intercellular spaces, and xylem vessels and complete disease cycles [P. polymyxa ShX301 inhibited D. dadantii swimming motility and biofilm formation. Fusaricidins and polymyxins from P. polymyxa may not play a major role in cytotoxic action on D. dadantii but may act as biosurfactants to inhibit surface attachment and biofilm formation [D. dadantii infection and increasing D. dadantii susceptibility to cytotoxic lipopeptides. Multiple lipopeptides produced by P. polymyxa ShX301 play a major role in bactericidal and bacteriostatic actions on the phytopathogens.Flagella-mediated motility and biofilm formation facilitate e cycles ,37,38,39ormation , thus reP. polymyxa [P. polymyxa ShX301 completely eliminated D. dadantii from sweet potato seed tubers at 21 d after the equivalent inoculation of the two bacteria. Bactericidal and bacteriostatic actions and induced plant systemic resistance mediated by multiple lipopeptides may play together to eliminate D. dadantii. The latent infection of seed tubers by Dickeya and Pectobacterium is a major source of the soft rot diseases of potato and sweet potato plants [P. polymyxa ShX301 has shown the potential to control soft rot diseases from seed tuber-borne pathogens. Moreover, inoculating P. polymyxa ShX301 alone to sweet potato seed tubers promoted the growth of sweet potato seedlings. Likewise, P. polymyxa ShX301 promoted the growth of cotton seedlings and suppressed the soil-borne fungal pathogen Verticillium dahlia and the Verticillium wilt disease of cotton seedlings [P. polymyxa ShX301 is a promising biocontrol agent and plant growth promoter for future application in fields and study of the underlying mechanisms of the broad-spectrum antagonism and mutually beneficial interactions with plants.From the view of plant-microbe interactions, plants can induce the expression of polymyxin and fusaricidin biosynthesis genes in polymyxa , while lpolymyxa ,43. Notao plants . P. polyeedlings . TherefoP. polymyxa complex includes the polymyxin-resistant soft rot Dickeya and Pectobacterium pathogens and strengthens the fact that bacteria within the P. polymyxa complex have high probability of being effective biocontrol agents and plant growth promoters. P. polymyxa ShX301 will be used to clarify the biocontrol mechanism of the P. polymyxa complex against broad-spectrum phytopathogens, including polymyxin-resistant Dickeya and Pectobacterium and to control plant diseases in fields.This study clarifies that the antimicrobial spectrum of polymyxin-producing bacteria within the


Accurately estimating the pose of a vehicle is important for autonomous parking. The study of around view monitor (AVM)-based visual Simultaneous Localization and Mapping (SLAM) has gained attention due to its affordability, commercial availability, and suitability for parking scenarios characterized by rapid rotations and back-and-forth movements of the vehicle. In real-world environments, however, the performance of AVM-based visual SLAM is degraded by AVM distortion errors resulting from an inaccurate camera calibration. Therefore, this paper presents an AVM-based visual SLAM for autonomous parking which is robust against AVM distortion errors. A deep learning network is employed to assign weights to parking line features based on the extent of the AVM distortion error. To obtain training data while minimizing human effort, three-dimensional (3D) Light Detection and Ranging (LiDAR) data and official parking lot guidelines are utilized. The output of the trained network model is incorporated into weighted Generalized Iterative Closest Point (GICP) for vehicle localization under distortion error conditions. The experimental results demonstrate that the proposed method reduces localization errors by an average of 39% compared with previous AVM-based visual SLAM approaches. One of the important technologies for the commercialization of fully autonomous parking is to accurately estimate the pose of the vehicle. Simultaneous Localization and Mapping (SLAM) technology has been developed for localizing the vehicle . RecentlInstead of a front camera, an around view monitor (AVM) has been also investigated for its application to autonomous parking in visual SLAM. AVM provides a bird’s eye view image using cameras facing in four different directions. Many studies ,6,7 haveDespite the fact that numerous approaches ,10,11,12This paper proposes an accurate AVM-based visual SLAM against AVM distortion errors caused by an inaccurate calibration without using supplementary information. The main contributions are as follows. First, a novel weighting method is proposed, utilizing a deep learning network, to assign weights to the pixels along the parking lines in the AVM based on the degree of distortion error. Second, a data creation framework is established to minimize the human effort for training the weighting network. Through these two contributions, the shape and magnitude of AVM distortion resulting from inaccurate calibration are readily predicted. In contrast to conventional data creation methods which entail human effort in manually annotating ground truth data for each raw data, the proposed data creation framework automatically generates data by utilizing three-dimensional (3D) Light Detection and Ranging (LiDAR) SLAM. By employing parking line points with varying weights based on the degree of distortion error, the proposed SLAM has shown an improved localization performance with an average reduction of 39% in error compared with the modified approach of Hybrid Bird’s-Eye Edge-Based Semantic Visual SLAM  when impThe rest of the paper is organized as follows. In the next section, the background of this paper, including related work and the limitations of Hybrid Bird’s-Eye Edge-Based Semantic Visual SLAM , is presIn the field of visual SLAM, there are various methods using a front camera as the main sensor. These can be broadly categorized into direct and feature-based methods. Direct methods use the raw image, while feature-based methods use only features in the image. Representative direct methods of visual SLAM include Direct Sparse Odometry (DSO), which estimates camera pose by minimizing the pixel intensity difference between two images . ORB-SLAVarious SLAM studies have proposed utilizing AVM as the main sensor for autonomous parking. Autonomous valet parking-SLAM (AVP-SLAM)  estimateSeveral methods have been proposed for the automatic calibration of AVM images, utilizing extracted feature shapes to achieve accurate bird’s eye views. In , a methoIn recent years, there has been a shift towards deep learning-based AVM image generation methods that use Neural Networks (NN) as viewpoint transformation functions, instead of using homography geometric information. HDMapNet  uses a MTo estimate the vehicle pose without the need for pre-map construction or additional sensors, the algorithm of the Hybrid Bird’s-Eye Edge-Based Semantic Visual SLAM  is selecTo assess the AVM distortion error caused by inaccurate AVM calibration, a comparison between the parking line information extracted from the 3D LiDAR and the parking line information of the AVM image (represented as color points and white parking line pixels, respectively, in To assess the impact of AVM distortion errors on SLAM performance, experiments were conducted using the aforementioned modified Hybrid Bird’s-Eye Edge-Based Semantic Visual SLAM  in both The feature weighting network receives the parking line information detected from LaneNet  as the iT represents the transformation matrix used for pose estimation. The pointclouds w is derived from the weight map and is associated with each point i. C represents the covariance matrices of the points. The term For pose estimation, the parking line pointcloud converted from parking line information, corresponding to the predicted weight map and wheel odometry information, are used as the input to the weighted GICP, which is an optimization method that minimizes the weighted sum of distance considering the distribution of each point in an associated pair, as shown in Equation . In the distance , which qThe pose update takes into account the relative pose from trajectory between the newly created local map and the global map using weighted GICP. Both the local map and the global map use a grid map representation, where each grid accumulates the weights of the included points. This indicates that grids containing larger values included a greater number of points with less AVM distortion. Additionally, points with weights lower than the heuristic threshold were removed. As a result, the vehicle pose is accurately updated through matching between grid cells with low distortion errors.There are two stages to assigning weights to each pixel of the parking line based on the AVM distortion error. The first stage involves creating ideal parking line images using LiDAR data and measurement information see . The secIn The detected parking line information from the AVM image is compared with the ideal parking line image, and a weight is assigned based on the position difference between the detected parking line pixels and the ideal parking line pixels as shown in As shown in https://github.com/ywlee0305/Accurate-Visual-SLAM-against-AVM-Distortion-Error-using-Weighted-GICP-Dataset/tree/master/Training_Data, accessed on 20 August 2023. The file encompasses raw AVM images, parking line data detected by LaneNet [The training data were collected from Parking Lot 1, as shown in  LaneNet , and theN is the total number of poses, i, and i. The symbol To evaluate the performance of the proposed method, experiments were conducted in three different parking lots, as shown in The comparison experiments between the Particle-Filter-based Semantic Visual SLAM , the modIn This paper proposed an AVM-based visual SLAM framework for autonomous parking that addresses the challenge of AVM distortion errors. By incorporating a feature weighting network, weights are assigned to parking line features based on the degree of distortion. A novel dataset creation method that minimizes human intervention was proposed, and the ideal parking line map constructed using this method was validated by comparing it with the actual parking lot. Through experiments, the proposed method reduced the error by an average of 39% compared with the modified Hybrid Bird’s-Eye Edge-Based Semantic Visual SLAM. The proposed method also enhances the accuracy of the estimated vehicle pose after parking.However, the proposed method showed less improvement in environments where features are sparsely detected due to walls and parked vehicles, compared with environments with more detected features. Additional data training specific to environments with different shapes, such as diagonal parking lots, is required to effectively apply the proposed method. To overcome these limitations, exploring different features that can be utilized with parking lines is needed. Further evaluations in various parking scenarios are required to generalize the proposed method. Conducting experiments in scenarios including dynamic obstacles and partially occluded parking lines is also essential. Moreover, performance evaluations in environments with distortion errors caused by uneven ground are also necessary.


Such approaches are often problematic because probes can perturb the near-field itself. Here we show that information encoded in evanescent waves can be probed further than previously thought, by reconstructing truthful images of the near-field through selective amplification of evanescent waves, akin to a virtual superlens that images the near field without perturbing it. We quantify trade-offs between noise and measurement distance, experimentally demonstrating reconstruction of complex images with subwavelength features down to a resolution of λ/7 and amplitude signal-to-noise ratios < 25dB between 0.18–1.5 THz. Our procedure can be implemented with any near-field probe, greatly relaxes experimental requirements for subwavelength imaging at sub-optical frequencies and opens the door to non-invasive near-field scanning.Imaging with resolutions much below the wavelength  The authors develop a method for sub-diffraction near-field imaging using measurements taken relatively far from an object, amplifying evanescent waves that encode the highest resolution. The increased distance greatly reduces the perturbation of the fields by the imaging device itself. Conventional imaging techniques that collect light far from an object are typically bound by this limit, and much effort has been invested in developing ways to overcome it. Many techniques now provide resolutions well below the diffraction limit3, relying either on near-field probing through a scanning tip5, stochastic sets of scatterers or fluorophores in the immediate vicinity of the object to be imaged7, or nonlinear effects allowing sub-diffraction imaging in the far field9, many of which have yet to be demonstrated outside the optical spectrum. Methods to reconstruct sub-diffraction details from linear far fields also exist, but typically require some prior knowledge or assumptions on the nature of the object10.The diffraction limit prohibits resolving features smaller than half a wavelength, as a consequence of the evanescent decay of high spatial frequencies in standard materials13. Imaging at terahertz frequencies (0.1–10 THz) would particularly benefit from any improvement in the ability to image below the diffraction limit14, due to its many applications in biomedicine18, which is hindered by established experimental challenges19. We refer the reader to refs. 20 for a review on recent developments in terahertz imaging techniques.Lower frequency sub-wavelength imaging techniques  typically rely on scanning antennas in an object’s near field22, using a sophisticated technique in which an atomic force microscope tip is used to scatter THz radiation. It is ideal for probing local THz material properties, but can only access small-area planar surfaces and has limited signal-to-noise ratio. Information on polarization can in principle be retrieved, but requires careful interpretation23. Recent developments in the combined use of non-linearity and local optical excitation near s-SNOM tips could provide even further improvement in resolution25. THz s-SNOM approaches are powerful for probing THz properties locally, but are less suited to probe full 3D polarization-resolved fields, especially over larger areas such as that of dielectric or photonic crystal resonators due to the limited spatial range of atomic force microscopes.There are two main techniques for sub-wavelength THz imaging: scattering-type scanning near-field optical microscopy (s-SNOM) and near-field photoconductive antennas (NFPA), with very different strengths and drawbacks: THz s-SNOM offer the state-of-the art in terms of resolution ( < 100 nm)λ/2π, that is in the reactive near-field26, where evanescent waves corresponding to high spatial frequencies haven’t decayed much yet26. This is ideal to achieve high spatial resolution, but the proximity of the tips can also affect the fields to be measured. In simple cases the tip’s polarizability is small enough compared to that of the object to be imaged, so that perturbations are of first order and can readily be compensated for23. However for some sample geometries, the tip can cause stronger perturbations (from multiple scattering between tip and object) which require corrections beyond first order27, and cannot simply be corrected by a deconvolution28. Indeed some s-SNOM techniques rely on generating a THz hot spot29, which is an extreme perturbation of the local field distribution. Such hot-spots are beneficial to probe local THz material properties, but make measuring unperturbed fields of waveguides or resonators difficult.Tips of s-SNOMs oscillate within nanometers of the object, a distance well below 30 are a practical alternative to s-SNOMS that are more suitable for probing fields than for probing nm-scale local material properties. Such NFPAs can be incorporated into any commercial THz time domain spectroscopy setup31, and can directly probe both amplitude and phase over centimeter-squared areas with resolutions of order 10 μm at the site of the antenna. Through the orientation of the dipole antenna, polarization can be resolved directly20, making the method well suited to probe the full three-dimensional field of existing structured materials, waveguides or resonators. However, under standard laboratory conditions, it is common for NFPAs to be hundreds of micrometers away from the object to be imaged33, due to practical alignment difficulties combined with the fact such antennas are expensive and delicate, making near-contact scans a risky proposition. At THz frequencies, distances that are hundreds of micrometers from an object are associated with its radiating near-field region, corresponding to distances between λ/2π and λ26 for sub-wavelength objects. The radiating near-field is characterized by fields that are dominated by radiating rather than evanescent waves. In this region, the fields don’t decay as 1/r yet as they do once in the far field, while high spatial frequencies decay significantly, preventing genuine sub-wavelength imaging1. Such increased measurement distances, while leading to a loss in resolution, have the benefit of reducing perturbations to the fields due to the probe itself, which can be important given NFPAs and their substrate are considerably larger than s-SNOM tips.In contrast, near-field photoconductive detector antennas (NFPAs)35 and hyperlenses (HL)36, which respectively amplify or propagate the evanescent fields, and which have been demonstrated over much of the electromagnetic spectrum41. An ideal superlens with unlimited evanescent gain would allow imaging at any distance without loss of resolution, and thus enable non-invasive imaging of the near-field. In contrast, a hyperlens needs to be placed in the reactive near-field to resolve high spatial frequencies, and thus a priori does not help with non-invasive near-field imaging. Both approaches still carry two challenges: (i) the resolution of the highest spatial frequencies is adversely affected by even modest material losses42; (ii) most geometries transfer the near-field information without spatial magnification which converts evanescent waves into propagating waves43: fields must still be measured in the near field of the SL or HL44, shifting the problem rather than solving it. At THz frequencies, anisotropic metamaterials have been used for sub-wavelength propagation of near-field information across finite slabs46 using Fabry-Perot resonance-induced evanescent amplification48, but a THz SL which truly amplifies decayed evanescent fields has so far been beyond reach.Be it with s-SNOMs or NFPAs, if one wants to resolve the near-field of existing structures, ideally one would image far away enough to avoid probe- object interactions, but close enough to avoid decay of evanescent waves. This seeming contradiction could be achieved by imaging in the radiating near-field if one had a way to reverse, or avoid, the exponential decay of the evanescent field. This can be achieved with so-called superlenses (SL)In principle, in the absence of noise, one could imagine reversing the evanescent decay of high spatial frequencies without physical devices, using numerical amplification and phase reversal instead: evanescent waves contribute to the field measured at any distance, superimposing high spatial frequency fluctuations on top of low spatial frequency radiating fields. If these minute amplitude and phase fluctuations can be resolved, they can also be amplified to regain the original field. To our knowledge, such a scheme has not been considered, presumably because high spatial frequencies rapidly decay well below instrument noise.λ/7 taken from a distance greatly reducing field perturbation by the probe. Our approach is general, provided that low-noise, phase-resolved fields can be measured. This demonstrates the possibility of measuring near fields without perturbing them – which would be particularly useful when imaging fields in structures that are sensitive to perturbations, e.g., high-Q/topological resonances50, photonic crystal defects51 and nanoresonators52.Here we show that practical noise levels allow for a useful extraction of decayed information in the radiating near-field region, also providing a way for increasing the resolution in the reactive near-field region. In effect, we experimentally demonstrate a virtual superlens through post-processing, reconstructing previously indiscernible sub-wavelength spatial features contained within complex images, with demonstrated resolution down to Eobj. The total field at r =  is given by a Fourier expansion34σ sums over polarizations, k = ,Eobj, and k0 = 2π/λ is the free space wavenumber. Propagating waves  →  over a subsequent length L, by numerically reversing the phase accumulated by the propagating waves and amplifying the evanescent waves . Starting from Fourier components of the measured field kz is imaginary and leads to exponential amplification 34, achieving the same effect .Figure entclass1pt{minimay, with TM polarized fields (non-zero magnetic field in y). Figure Ex∣ emerging from two perfectly conducting apertures with width- and edge-to-edge- separation of d = λ/5. At a distance z = λ/20 in the reactive near-field region, the two apertures can be distinguishe  this is no longer the case. Figure kx required in order to resolve d is given by kx/k0 = λ/2d = 2.5. While the source’s spatial Fourier spectrum extends beyond kx = 10k0, at z = λ/2  most field components with spatial frequencies inside kx/k0 values. Using this noise level compared to the maximum signal, the amplitude signal-to-noise (SNR) is~30 dB.In Eq.  higher srum Fig. , blue isrum Fig. , red prez = λ/2, thus taking L = λ/2. The result is shown as a black dotted line in Fig. kx/k0 ≲ 2.5, where the signal in the evanescent spectrum was originally above the noise level  as a function of normalized propagation length z/λ for the double aperture case of Fig. π)−1 < z/λ < 1, i.e., in the radiating near field, the two apertures are not resolved. On the right of Fig. z/λ. The blue line in Fig. z/L = 0.5, as per Fig. z, always adding white noise such that SNR = 30 dB before amplification. The resulting z/λ, the procedure yields the required high spatial frequency components. For increasingly long propagation lengths however, the amplitude of amplified noise of evanescent waves becomes greater than those of the propagating waves . Equation (SNR as labeled. For ΔSNR = SNR = 30 dB (dark blue), where the ΔSNR value used in Eq. . The transmitted field amplitude is sampled as a function of the time delay of a probe pulse on a photoconductive antenna (Protemics TD-1550-X-HR-WT-XR) which probes the radiating near field. The electric field is polarized in x, using the reference frame shown in Fig. λ/2 = d, i.e., frequencies of 0.75 − 1 THz. See Supplementary Fig. Figures Ex∣2 emerging from two apertures (diameter and separation: 200 μm) at a frequency of 1.5 THz and 0.38 THz respectively, as well as the associated spatial Fourier transform magnitude y = 0 ± 100 μm as a function of x and frequency, and highlights that apertures cannot be discerned directly: at higher frequencies, what would be measured by a scanning antenna or tip is a diffraction pattern that includes additional features, requiring phase reversal  to reconstruct an accurate image. At lower frequencies the evanescent decay blurs out the features of the double aperture.Figure L by considering the complex field at a frequency above the diffraction limit (here: 1.5 THz), and adjusting L in Eq.  and SNR = 4 − 14 dB between 0.38–1.5 THz, resulting in We calibrate the probe-to-sample distance L in Eq.  to maxim via Eq. . For theres Fig. , shows td = 150 μm). In this case, the calibration yields L = 440 μm, SNR = 15–25 dB, and Ex∣2 at different frequencies as labeled. Figure Ex through, because the slits forming the letters act as parallel plate waveguides with width smaller than half a wavelength, in which solely the TEM mode polarized perpendicularly to the thinnest features can propagate. Therefore, thin features in y (x) only appear for the Ex (Ey) field. As a result, for x − polarized fields the letters’ vertical (y-oriented) features are clearest, and clearly show different numbers of nodes and anti-nodes for different frequencies, revealing the frequency-dependent modal field structure inside each letter in excellent agreement with simulations 53.In this paper, we have presented a superlensing approach which numerically amplifies measured evanescent fields. Spatial resolution is then limited by a trade-off between measurement distance and signal-to-noise ratio, rather than by distance alone. We presented experiments illustrating the process at THz frequencies using commercially available facilities. Compared to previous superlens incarnationsx, using the sample orientation and reference frame shown in Fig. x-polarized electric field at the output of the laser-machined samples. The near-field is spatio-temporally resolved at every point via a raster scan (step size: 25–50 μm). Fast Fourier transforms of the temporal response at each pixel position provide the spectral information, including amplitude and phase . Further details of the experimental setup are described in ref. 33. The phase fluctuation, obtained from the standard deviation of the phase of the Fourier transform of 850 consecutive measurements, is between 0.05–0.35 rad between 0.2–1.5 THz, as shown in Supplementary Fig. A summary of samples and photographs of the experimental setup is shown in Supplementary Fig. Supplementary InformationPeer Review File