Methodologically robust clinical trials are required to improve neonatal care and reduce unwanted variations in practice. Previous neonatal research prioritisation processes have identified important research themes rather than specific research questions amenable to clinical trials. Practice-changing trials require well-defined research questions, commonly organised using the Population, Intervention, Comparison, Outcome (PICO) structure. By narrowing the scope of research priorities to those which can be answered in clinical trials and by involving a wide range of different stakeholders, we aim to provide a robust and transparent process to identify and prioritise research questions answerable within the National Healthcare System to inform future practice-changing clinical trials.A steering group comprising parents, doctors, nurses, allied health professionals, researchers and representatives from key organisations  was identified to oversee this project. We will invite submissions of research questions formatted using the PICO structure from the following stakeholder groups using an online questionnaire: parents, patients, healthcare professionals and academic researchers. Unanswered, non-duplicate research questions will be entered into a three-round eDelphi survey of all stakeholder groups. Research questions will be ranked by mean aggregate scores.The final list of prioritised research questions will be disseminated through traditional academic channels, directly to key stakeholder groups through representative organisations and on social media. The outcome of the project will be shared with key research organisations such as the National Institute for Health Research. Research ethics committee approval is not required. By involving parents and former patients alongside a wide range of healthcare professionals, we will ensure that research questions are important to all key stakeholder groups.We will use established strategies (three-round eDelphi process) to rank research questions based on mean scores.The study will rank research questions based on subjective input from a large number of key stakeholders; however, questions may need further work prior to being addressed in a clinical trial.The final list of prioritised questions will be disseminated widely to inform neonatal clinical research.The importance of involving different stakeholders including parents, patients, healthcare professionals and researchers to identify and prioritise research is well recognised.10There is wide variation in neonatal careThe aim of this project is to identify and prioritise neonatal research questions in PICO format, suitable for high-quality interventional studies, using a robust, transparent and inclusive methodology. The results of this identification and prioritisation process will inform the development and design of neonatal interventional studies in high-income settings, including the National Healthcare System in the United Kingdom.A steering group was formed in September 2021 to agree the scope and facilitate the process of identifying and prioritising research questions. The following key stakeholders are represented on the steering group: the Neonatal Society (NS), British Association of Perinatal Medicine (BAPM), Neonatal Nurses Association (NA), Royal College of Paediatrics and Child Health, neonatal allied health professionals (AHPs), neonatal clinical trial methodologists, neonatal trainees and parents with experience of neonatal care. The steering group is cochaired by representatives of the NS and BAPM and has an allocated project co-ordinator responsible for agenda, minuting, role allocation and participant support. Details of the steering group members and their affiliations are found in The roles of the steering group are as follows:Agreeing the scope of the process.Disseminating details of the process.Engaging with clinical stakeholders to take part in identifying and prioritising research questions.Review of submitted research questions to identify duplicate questions, questions that have already been answered and questions outside the scope.Disseminating the final ranked list of research questions.The utility and validity of this project will depend on ensuring that representative questions are generated and prioritised by a wide group of neonatal stakeholders including:Clinicians involved in neonatal care: neonatologists, paediatricians, neonatal nurses, advanced neonatal nurse practitioners (ANNPs) working in paediatrics or neonatal medicine. Recruitment will be through advertisements on the RCPCH website and through other relevant professional organisations including BAPM, the Neonatal Nurses Association and the NS. Trainee doctors and nurses will be additionally contacted through local training schools and use of communication methods such as regional teaching and social media channels.AHPs: occupational therapists, physiotherapists, dieticians, speech and language therapists and clinical psychologists working in neonatal care: advertisements will be placed through professional websites and organisations and co-ordinated by the AHP steering group representative.Academics and researchers working within neonatology: recruitment will be targeted through academic organisations, existing research networks, national meetings and through clinical trial units with a neonatal interest.Parents and former neonatal patients: these groups will be contacted through the national care coordinator group, maternity voices partnerships, charity websites and through social media platforms.To ensure maximal engagement across all stakeholder groups, various communication strategies will be employing including email contact, professional websites and social media routes.Parents and patients have been involved in this work from its inception. A parent representative sits on the steering group to plan the project and optimise parent and patient involvement. Communication to parents and former neonatal patients will be through parent and patient network charities, regional support networks and social media groups. We recognise the importance of hearing from minority ethnic communities and those from low socioeconomic backgrounds, particularly in view of their greater risks of pregnancy complications that may lead to experience of neonatal care.Parents and former neonatal patients will be involved in identifying neonatal research questions through the online identification process. We acknowledge that there will need to be extensive support for non-academic participants to ensure they are not dissuaded by the PICO structure. To further facilitate the identification of research questions from parents and former neonatal patients, we will develop targeted online support resources and run several online workshops focused on developing questions using a PICO format. We will develop a training video targeted specifically towards parents and former patients and develop our resource page on the BAPM website with further written information about formatting a PICO question. In addition, our question building software will be designed specifically to walk participants through the PICO process, with preformatted options for populations and outcomes to make it more accessible.Parents and former neonatal patients will then be invited to participate in the prioritisation of research questions through the eDelphi process. Due to the nature of the study, some questions may require a high level of medical understanding, and so there will be the option for ‘unable to rank’ if a participant feels that they cannot make a meaningful judgement on assessing its importance. Throughout the eDelphi, we will seek feedback from parents and former patients regarding its accessibility. Balancing meaningful parental involvement with the specificity required for questions to be answered in interventional trials may be challenging. Therefore, with the results of the final eDelphi survey, we will carry out a specific targeted prioritisation process with parents, families and former patients, with support from Bliss, to ensure that this important group of voices is heard.The scope of the prioritisation process has been agreed by the steering group as follows:Limited to research questions relevant to high-income neonatal care settings.Limited to research questions related to care provided by neonatal teams:On neonatal units, transitional care units or as part of neonatal transport.On postnatal wards .In the community after receiving neonatal care as an inpatient .This study will be divided into four stages, which will commence in January 2022 and complete by September 2022 :Identification of neonatal research questions suitable for analysis in RCTs (1 month).Review of submitted neonatal research questions to remove duplicate questions and previously answered questions (1 month).Prioritisation of neonatal research questions by all relevant stakeholders using a three-round eDelphi process (3 months).Dissemination of ranked list of PICO questions.We will identify neonatal research questions suitable for evaluation in practice-changing RCTs through an open process. Individual stakeholders  will be contacted via professional organisations, social media platforms, networks and organisational mailing lists. The process for identifying research questions will also be openly publicised on organisational websites seeking submission of research questions from stakeholders. Publicity will precede and continue throughout a 4-week submission periodStakeholders will be invited to submit as many questions as they would like using an online system that facilitates submission using the PICO structure:Populations will be able to be selected from a predefined selection of gestations and clinical cohorts or specified by the submitter.Intervention and comparisons will take the form of free text to allow full descriptions.Outcomes will be able to be selected from Core Outcomes in Neonatology,Support in structuring research questions using PICO will be facilitated by the steering group members and organisations using techniques such as short videos and webinars. Contact details and basic demographic data will be requested from individuals who submit questions to monitor the representativeness of stakeholder involvement and to invite participation in the subsequent prioritisation process.Submission of relevant PICOs from previous priority setting workSubmitted research questions will be reviewed by the steering group to remove duplicate, already answered and out of scope questions, and to refine those not consistent with the PICO structure. Each question will be independently reviewed by two separate members of the steering group to ensure a transparent and reproducible process. It is recognised that there can be widely variable views on whether a clinical question has been adequately ‘answered’ by existing research and in view of this any questions excluded on this rationale will have to receive consensus view from all members of the steering group. Prior to exclusion, questions will be independently reviewed by two members of the steering group. A final long list of research questions will be taken forward for prioritisation.All research questions included in the long list will be entered into a three-round eDelphi prioritisation process. Involvement of stakeholders in the prioritisation process will be facilitated as follows:All stakeholders who submitted questions will be contacted by email and asked to take part.Invitations to take part will be circulated by professional organisations and open links will be made available on professional organisational websites and social media accounts.Parents and previous neonatal patients will be contacted through professional and charitable organisations and networks and through social media.All research questions will be ranked using a 9-point Likert scale. After the first round, there will be the opportunity to submit new PICO questions. These additional questions will pass through the same two stage review process, co-ordinated by the steering group as the original questions. Prior to opening the second round of the Delphi survey, a steering group meeting will define the threshold for questions to take part in this round. During the second round, participants will be provided with information on how individual research questions were prioritised by each stakeholder group during the first round. Participants will then be able to amend or confirm their original ratings, taking into consideration other stakeholder group opinions. Prior to the third round, the steering group will convene a meeting and review the preliminary results to decide the threshold of questions to enter the third round. A shorter list of questions in the third round will help to improve retention of participants by facilitating a shorter time commitment.After completion of the third round of ranking, all research questions entered into the Delphi will be collated into a ranked list of research priorities for the UK neonatal community. Ranking will be ordered based on mean score. Results will also be presented by mean score within each stakeholder group. All questions not excluded in the initial review process will be included in the final list.Research Ethics Committee approval is not required for this work.The ranked list of defined neonatal research questions will be disseminated as follows:We will share results directly with the NIHR prioritisation panel and other funders of neonatal trials.We will circulate the list to stakeholder organisations and their members.Individuals who participated in question setting or the prioritisation process will be emailed directly with the finalised rankings and named as group authors in any published work.Results will be disseminated among the scientific community through a publication and presented at relevant neonatal meetings.More than 1 in 10 babies in many high-income settings will receive neonatal care. Neonatal conditions are important, contributing to almost half of all child deaths in the UK and to many long-term health conditions. Despite this importance, much neonatal care is not based on high-quality research evidence. Historically, the perinatal research environment has fostered collaborative working, demonstrated by studies such as EPICure.


The samples were characterised using FESEM, HRTEM, XRD, Raman, XPS, and Hall effect measurements for their structural and electrical properties. Compared to the undoped sample, the rutile-phased TAFM sample had finer nanorods with an average 42 nm diameter assembled to form microsphere-like structures. It also had higher oxygen vacancy sites, electron concentration, and mobility. In addition, a reversed double-beam photoacoustic spectroscopy measurement was performed for TAFM, revealing that the sample had a high electron trap density of up to 2.5 μmolg−1. The TAFM showed promising results when employed as the resistive-type sensing film for a humidity sensor, with the highest sensor response of 53,909% obtained at 3 at.% Ta doping. Adding rGO to 3 at.% TAFM further improved the sensor response to 232,152%.This study fabricated tantalum (Ta)-doped titanium dioxide with a unique nanorod-assembled actinomorphic-flower-like microsphere structured film. The Ta-doped TiO Lan et al. [2 microspheres through a pressure-driven hydrothermal method using an autoclave. However, their method required an amphiphilic triblock copolymer to produce the unique structure and the growth time was up to 24 h. Arjunkumar et al. [2 microspheres, hydrothermally synthesised on a fluorine-doped tin oxide (FTO)-coated substrate. Their method also relied on an autoclave to generate pressure to form of 10 µm–sized TiO2 microspheres in 8 h of growth duration. Meanwhile, Ren et al. [2 microsphere using the hydrothermal method at a deposition time of 24 h. They utilised SiO2 as the template to form TiO2 hollow microspheres.Three-dimensional (3D) structures such as microspheres have been reported to provide a high surface area for zinc oxide (ZnO) , tin oxi2) , magnesi2) , and nic2) ,13. Howen et al.  producedr et al.  presenten et al.  produced2 actinomorphic-flower-like microsphere (TAFM) using a simple solution immersion without an autoclave. Furthermore, the use of TAFM structures as sensing films for humidity-sensing applications has not been reported. This research discovered that this structure type could be formed by adding TaCl5. The advantage of using TaCl5 is that it can serve bifunctionally as both a Ta dopant source and a catalyst for the formation of microspheres. Pentavalent dopants, such as Ta, enhance the optical and electrical characteristics of TiO2 [Based on the literature review, there is no report on the formation of nanorod-assembled Ta-doped TiO of TiO2 ,18. This2 microspheres, and this work aimed to fulfil that gap. The properties of the TAFM, including structural, surface, electrical, and humidity responses, were investigated. This research also explored the humidity response of TAFM/reduced graphene oxide (rGO) nanocomposite film.This research included results from reversed double-beam photoacoustic spectroscopy (RDB-PAS) for TAFM, which has rarely been reported in the literature. Ohtani et al. introduced RDB-PAS, a novel method characterising a material’s electron trap density . This te2 and rGO were chosen for humidity sensor application in this study because these two materials possess excellent characteristics for water detection. TiO2 has a hydrophilic nature and chemical robustness, making it suitable for humidity detection. Meanwhile, rGO has been reported to improve the humidity detection of other metal oxide-based humidity sensors. In addition, carbon nanostructures can be prepared using abundant organic precursor materials, including waste materials [2 nanostructures with a high surface area exhibit excellent humidity-sensing ability. Jeong et al. [2 nanostructure. The 3D architecture was prepared via hydrothermal processing and deposited on a flexible polyimide substrate using the drop-casting method. They reported that the highest sensitivity obtained was attributed to the immense surface area of TiO2.TiOaterials ,22. TiO2g et al.  reported2/rGO [2/GO [Researchers have also combined metal oxide with graphene to enhance humidity sensors’ performance further. Saqib et al.  used a c2/rGO , and MoSGO [2/GO  compositGO [2/GO  demonstrGO [2/GO , a graph2 was sputtered evenly on a 2.5 × 2.5 cm2 microscope glass slide using radio frequency (RF) magnetron sputtering (SNTEK) by bombarding plasma ions on a pure TiO2 target. The RF power was set at 200 W for 6 h under 20 sccm argon and 5 sccm oxygen. A solution containing 0.07 M of titanium butoxide (Ti(C4H9O)4, Purity: 97%, Sigma-Aldrich, USA) was prepared in a Schott bottle with a solvent-acid mixture of deionised (DI) water and hydrochloric acid. A small amount of tantalum pentachloride  was added to the solution to achieve 1 at.%, 3 at.%, 5 at.%, 7 at.%, and 9 at.% Ta doping. An undoped solution was also prepared for comparison. After 1 h of rigorous stirring, a substrate was arranged into the immersion bottle with the TiO2-seed-layer-coated surface facing upwards. A unique, high-heat resistance cap was used to tightly seal the bottle to ensure pressure built up inside the bottle. The bottle was then clamped with a homemade clamp , high-resolution transmission electron microscopy , and energy-dispersive X-ray spectroscopy  examined the morphology, atomic structure, and elemental mappings of the prepared films, respectively. X-ray diffraction  and Raman spectroscopy  determined the structural characteristics of the thin film. An X-ray photoelectron spectroscopy  analysis of the samples was also performed to ascertain the samples’ chemical states. The survey and narrow scan were conducted using pass energies of 280 eV and 112 eV, respectively. RDB-PAS analysis was done using the method used by Nitta et al. . Hall ef2 losing its microsphere structure and ending up with aggregated particles, as shown in The 10,000× magnified images of the prepared samples were taken by FESEM a–f. The 5 up to 5 at.% reduced the diameter of the nanorods and caused the nanorods to be aggregated to form actinomorphic flower-like structures.Higher magnification images of UTD and TAFM-3 showed that the microsphere of TAFM-3 consisted of assembled nanorods with a diameter of around 42 nm . The mic2 nanorod constructed from a 5 nm-diameter nanorod assembly. The EDX elemental mappings , (101), (111), (211), (200), (002), and (301) planes. For samples with Ta doping concentrations of 3 at.% and above, peaks were observed at 2θ of 24.9° and 24.6° ascribed to Ta2O5. The interplanar spacing of hkld and lattice constants, a, of both the undoped (UTD) and Ta-doped (TAFM) samples were determined by Equations (1) and (2) [a is the lattice constant, θ is the diffraction angle, n is the diffraction order , and λ is the X-ray wavelength (1.54 Å). Using the XRD peak of the (110) crystalline plane, the interplanar distance (hkld) and lattice parameter (a) for UTD, TAFM-1, TAFM-3, TAFM-5, TAFM-7, and TAFM-9 were calculated to be 3.32 Å/4.691 Å, 3.31 Å/4.688 Å, 3.32 Å/4.692 Å, 3.31 Å/4.676 Å, 3.28 Å/4.638 Å, and 3.32 Å/4.695 Å, respectively, as shown in The XRD result of the prepared samples a specifi02), and 1 planes. and (2) .(1)1dhkD) (Equation (3)) [λ, β, and θ represent the X-ray wavelength (1.54 Å), full width at half maximum (FWHM) of the (110) plane, and peak angle of the (110) plane, respectively. The crystallite size decreased as a higher concentration of Ta was added to TiO2. It is a common doping effect since foreign elements often disrupt the crystal growth of the parent material [ε, was calculated using Equation (4) [β is the full width at half maxima (FWHM) of the (110) peak. The detailed analysis of XRD data revealed that TAFM samples had a higher microstrain than that of UTD. When examining the ionic radius, there was a slight mismatch in the sizes of Ti4+ (0.605 Å) and Ta5+ (0.640 Å), which could have promoted the defects. Other possible reasons are the electron density around Ta and the doping-induced oxygen vacancies, which could cause the rearrangement of nearby atoms and disrupt the crystal growth [Scherrer’s equation was used to determine the crystallite size (ion (3)) :(3)D=0.9material . Meanwhition (4) :(4)ε=β4tl growth ,36.−1, 235 cm−1, 447 cm−1, and 612 cm−1, which correspond to 1gB and two-phonon bands (marked with*), gE and 1Ag, respectively. Conforming with the XRD results, this pattern indicated TiO2 with a rutile polymorph [gE peak was ascribed to the mode of the Ti–O vibration, whereas the vibration mode of the oxygen atoms along the c-axis was associated with the 1gA peak. The broadening of the gE peak of the Ta-doped sample indicated the incorporation of Ta5+ into Ti4+ sites [gE shifted slightly to the lower wavenumber, indicating the increased oxygen vacancy [The raman spectroscopy results in olymorph . The Eg 4+ sites . In addi vacancy ,40.2. The core-level scan of Ti for UTD  plane while advancing the anisotropic growth in the (001) direction.The growth mechanism of TAFM’s microsphere  was initic state . Adding 2 increased with Ta doping. Works by previous researchers [The results for RDB-PAS measurements  showed tearchers ,49 have earchers .18 cm−3. UTD and TAFM samples exhibited n-type semiconducting characteristics as observed through the Hall effect measurement results. It was expected that pentavalent dopants, such as Ta, would donate extra electrons, increasing the electron concentration in the film, consistent with previous research [3 cm2/V·s compared to 6.35 × 102 cm2/V·s for the undoped sample.The Hall effect measurement results of the samples  revealedresearch . The carHumidity sensors were fabricated using the prepared samples by depositing Ag metal contacts, and the photo images are depicted in S) of the sensors was assessed using Equation (5) [R40 is the resistance at 40% RH and R90 is the resistance at 90% RH.The humidity-sensing capabilities of all sensors are shown in tion (5) :(5)S=R40RH–R40)/R40) of UTD and TAFM-3 samples over five cycles at various relative humidity levels from 50% RH to 90% RH are shown in The humidity-sensing responses  and trapped the surface’s electrons in the process [2. The Ta-doped samples could attract more oxygen from the environment because of an excess of electrons in the lattice. Upon exposure to the environment that had a higher humidity level , the adsorbed oxygen species reacted with water molecules on the sensing surface to release the electrons and neutralise the depletion layer. Subsequently, this process restored the electron concentration in the lattice and the film’s conductivity. This process was reversible when the humidity level was reduced to 40% RH. The electron movement was very rapid, which enhanced the response and recovery times of the sensors for the Ta-doped samples compared to their undoped counterparts. The response/recovery times were also affected by the morphology and porosity of the sample, the presence of the active sites on the sample’s surface, the accessibility of hydrophilic functional groups on the sample’s surface, and the ability of the sample to absorb water molecules [The static humidity response plots of humidity sensors based on UTD, TAFM-1, TAFM-3, and TAFM-7 at different humidity levels from 40% RH to 90% RH are shown in  process . Those aolecules ,55.2 sensor recorded the lowest response of 11,525%. An improvement was observed as the Ta doping percentage increased, with sample TAFM-3 showing the highest response of 53,909%. The sensing performance was superior or comparable to those reported in other works  ion movement, as shown in Equation (6):The proposed humidity detection mechanisms of UTD and TAFM are illustrated in s to hop ,61. The A few layers of physiosorbed material formed on the TAFM surface when the humidity increased. The electrostatic force then produced hydronium ions, and the electrical resistance of the sample was governed by ion conduction (Equation (7)):These ions hopped from one hydrogen bond to another in a Grotthuss chain reaction, increasing the sensor’s electrical conductivity . The mec2 microsphere and rGO sheet structures (2 microsphere.A nanocomposite of TAFM-3 and reduced graphene oxide (rGO) was synthesised to explore the possibility of further improvement to the performance of the TFAM-based humidity sensor. The FESEM image of the prepared nanocomposite showed both the TiOructures a,b. The 2 microsphere structure increased the adsorption surface area, adding rGO enabled efficient electron transportation between the TiO2 microspheres, owing to the excellent electron mobility property of rGO [2 microspheres and rGO subsequently enhanced the humidity response of the film. Moreover, the rGO also contained a large number of active sites and hydrophilic functional groups [The humidity sensor was fabricated using the nanocomposite and the sensor response was observed c. The hiy of rGO . The rGOl groups ,67, whic2 nanorod-assembled actinomorphic flower-like microsphere structures through Ta doping using a simple solution immersion method and proposed their growth mechanism. The TAFM contained 42-nm nanorod-assembled microspheres with a rutile phase polycrystalline and highly porous structure. The TAFM had higher oxygen vacancy sites, electron trap densities (up to 2.5 μmolg−1), electron concentrations (9.98 × 1018 cm−3), and electron mobilities (1.92 × 103 cm2/V·s) as compared to its undoped counterpart. The sensor made from TAFM doped at 3 at.% showed the highest humidity-sensing sensitivity of 53,909%. The formation of a nanocomposite between TAFM-3 and rGO increased the sensor response to 232,152% because of the combined effect of increased surface area and efficient electron transportation.This study synthesised TiO


In conversation, people are able to listen to an utterance and respond within only a few hundred milliseconds. It takes substantially longer to prepare even a simple utterance, suggesting that interlocutors may make use of predictions about when the talker is about to end. But it is not only the upcoming talker that needs to anticipate the prior talker ending—listeners that are simply following the conversation could also benefit from predicting the turn end in order to shift attention appropriately with the turn switch. In this paper, we examined whether people predict upcoming turn ends when watching conversational turns switch between others by analysing natural conversations. These conversations were between triads of older adults in different levels and types of noise. The analysis focused on the observer during turn switches between the other two parties using head orientation  to identify when their focus moved from one talker to the next. For non-overlapping utterances, observers started to turn to the upcoming talker before the prior talker had finished speaking in 17% of turn switches (going up to 26% when accounting for motor-planning time). For overlapping utterances, observers started to turn towards the interrupter before they interrupted in 18% of turn switches (going up to 33% when accounting for motor-planning time). The timing of head turns was more precise at lower than higher noise levels, and was not affected by noise type. These findings demonstrate that listeners in natural group conversation situations often exhibit head movements that anticipate the end of one conversational turn and the beginning of another. Furthermore, this work demonstrates the value of analysing head movement as a cue to social attention, which could be relevant for advancing communication technology such as hearing devices. One of the most impressive feats of human cognition is our ability to converse, spontaneously and easily, with familiar and unfamiliar interlocutors alike. In a conversation, individuals alternate between listening to speech: comprehending the intended message and monitoring for appropriate times to respond, and taking on the role of talker: producing a message while concurrently monitoring the listener’s understanding. The ability to coordinate utterances with others on the fly is a striking skill that even young children are able to grasp , in spitOf particular note in conversation is the apparent seamlessness of turn taking, with the average gap between one talker ending and another beginning being <250 ms in English . Given tRecently, there has been some criticism of the idea that short turn-taking gaps in conversation imply prediction, since in real conversation interlocutors may not always be directly responding to a prior turn, but instead continuing their point from several turns ago . In suchImportantly, listeners that are simply following the conversation could also benefit from predicting the turn switch , in order to shift attention in time to follow the conversational flow. This situation allows the listener to use cues from the current talker, signalling that they are about to end, as well as cues from the upcoming talker, that they are about to start. Hence this provides a range of additional information to typical studies of prediction during speech listening. In a group conversation, there are multiple possible targets when a floor change occurs, and a variety of cues indicate who is going to be the one to take the floor  before the prior turn ends, (2) during the gap between the prior and upcoming turns or (3) after the upcoming turn has begun. Turns at different times may be driven by different processes. The simplest situation is (1) when the head turn occurs before the prior spoken turn ends. This provides clear evidence of the listener predicting the end of the talker’s turn and an imminent change of floor. The case of (2) is more complicated, and may or may not be considered evidence of prediction. If a listener turns their head during the time between the prior talker and the upcoming talker, i.e. during the gap, it could either indicate a prediction of the upcoming talker starting their turn: i.e. the listener using cues given by the person about to take the floor that signal they are about to begin, or it could be a simple reaction to the end of the prior talker’s turn: i.e. the listener using turn end cues to recognise that a talker is done. Yet even in this reactive case, turning towards the ‘correct’ upcoming talker may nonetheless still be considered to demonstrate the use of predictive cues to correctly identify who is going to start next . Finally, situation (3) does not provide evidence for prediction, as it could be explained as a reactive response to the latter talker’s speech.When there is an overlap between the speech of the prior and the upcoming talker, the behaviour indicating prediction would differ from the non-overlapping case discussed above. In this case, a second talker ‘interrupts’, and prediction would be demonstrated specifically by head turns towards the interrupter prior to them starting to talk. Such head turns would suggest that the listener is using cues given by the interrupter that signal they are about to begin, even though the prior talker has not finished. Any head turns occurring after the interrupter had begun could be a simple reaction to the new talker speaking.Given prior evidence of prediction of speech, and the speed of conversational turn taking, interlocutors listening to a turn exchange may predictively orient to an upcoming talker to facilitate processing of their speech and thus more efficiently follow the conversation. In this study, we therefore investigate when unaddressed interlocutors shift their attention from one talker to another during a conversational turn switch. Since most prior work has focused exclusively on non-overlapping utterances and reported gaze switches typically occurring during the gap, with the only study demonstrating predictive gaze switches focusing exclusively on the more predictive question-answer pairings, there is currently no clear evidence regarding the use of prediction across general conversational turn switches. We specifically analyse the unaddressed participant across a large number of triadic conversation turn switches to assess evidence for whether and how often unaddressed interlocutors predict the end of the prior talker’s turn (in the case of non-overlapping speech), or the start of an interrupter’s turn (in the case of overlapping speech).Furthermore, we analyse how background noise level affects predictive looks. Based on the recent work of As there are some inherent differences when watching a turn switch in a videoed conversation, and watching a turn switch between members of one’s own conversational group, we re-analyse the data of Ntriads = 11, Mage = 61, SDage = 11). Triads each engaged in four conversations lasting 12–16 min each: two in speech-shaped noise, and two in multi-talker babble noise. Noise level varied every 15–30 s between 54, 60, 66, 72, and 78 dB, as the original study was already designed to address coping strategies when communication varied from easy to challenging. Participants were unfamiliar. Data were collected from all three participants concurrently using a level threshold to automatically record the voice activity and an infra-red motion tracking system to record the head movement. In total, this dataset included 43 conversation recordings ; 22 in babble and 21 in speech-shaped noise with triads doing two sessions in each type of noise. With all three participants analysed of each triad, there are over 29 h of data in all.We extracted head movements consistent with turn-switch following from both datasets. An automatic algorithm developed in MATLAB applied the following processing stages. Note that separate analyses were run on non-overlapping speech  and overlapping speech .The voice-activity detection (VAD) data were based on sampled data from a close microphone. The data were pre-processed so that relatively clean exchanges of the conversational floor could be detected. The pre-processing was done in two stages. First, uninterrupted pauses in voice activity from a particular talker were closed up so that they were recorded as talking continuously. Second, any remaining voice activity whose duration was <0.5 s was deleted as representing only momentary isolated vocalisation  or perhaps mechanical noise on the microphone rather than full possession of the conversational floor. Speech onset and offset detection was then taken from the start and end points of each period of VAD.Head movement (HM) saccades were detected as movements of the head that exceeded 10° within a 400-ms window (i.e. a rate of movement averaging at least 25°/s over at least 10°). Having detected the presence of a saccade, the initiation and termination were defined as the points in time where the rate of movement fell to <5°/s over a 40-ms window.Pairings between saccades between saccades and exchanges of conversational floor were also identified automatically. A ± 4-s interval preceding and following a saccade initiation was scanned for the nearest VAD onsets and offsets by the other two participants that were consistent with the direction of head movement.The algorithm and its parameters were assessed for reliability by visual inspection of an automatically annotated visualisation. An example of such a visualisation is shown in in response to the exchange of floor between Blue and Green, starting at 53.7 s. Blue makes a movement in anticipation of an exchange from Green to Red at 58.7 s. The algorithm also detects Green moving between Blue and Red at 56.6 s. It is less clear that this is a true exchange of floor, because Green speaks during the gap between the other two voices. The algorithm accepts it, but the time intervals between the saccade and the associated offset and onset are both around 3 s, a time interval that tended to be classified as “coincidental” in the statistical analysis (see below).In To determine whether HMs were more frequent in time bins around the exchanges of floor than would occur by chance, the numbers of detected HMs were compared with mismatched VAD and HM data. Mismatched VAD and HM data were produced by pairing VAD and HM data from different sessions using all possible combinations with the same background noise type. The red lines in p < 0.05 (one-tailed) in each time bin.To determine whether the excess of associated HMs was statistically significant within each time bin, the null hypothesis was adopted that HMs are randomly distributed in time, with equal probability at a given time unit. However, the probability of a coincidental HM varies with respect to the timing of VAD onsets and offsets see  due to tt-tests.The number of associated HMs in each time bin was estimated by subtracting the expected number of coincidental HMs (red lines) from the observed number of HMs (blue lines). These numbers were used to calculate the distribution in time of associated HMs. Negative values were discarded, because these may reflect a genuine suppression of movements prior to or following an onset or offset. In the figures presented below, data from all participants are pooled. To conduct the inferential statistics, data from each triad were pooled, because data from one individual were too sparse to generate a histogram. Mean and standard deviations of the associated saccade timings with respect to a VAD onset or offset were reconstructed from the difference between the expected coincidental HMs and the observed numbers for each triad in each condition. Two four-way repeated-measures ANOVAs were conducted: one addressed the mean timing of the HMs and one addressed the standard deviation of their timing. The first was intended to detect whether any factor influenced how promptly an HM was made, while the second was intended to detect whether any factor made listeners less precise in the timing of their movements. Both ANOVAs examined the factors of noise level, noise type (babble vs. speech-shaped noise), type of exchange (overlapping/non-overlapping) and event type (voice onset or voice offset). Follow-up statistics include simple main effects and Holm-corrected In exchanges with non-overlapping speech, the median duration of silence between talkers was 0.64 s for speech-shaped noise and 0.68 s for babble. It is noticeable that the red curves for the coincidental rate of HM detection are not flat, but peak near to zero lag and are also skewed differently for the onsets and offsets. These effects are to be expected from the HM-detection algorithm. The distribution has a peak near zero delay, because only the HMs closest to zero delay are associated with a given onset or offset; if there is a second-nearest HM, it will be ignored. The different skews for association with onsets and offsets are caused by the rejection of overlapping dialogue; because the 4-s analysis window is centred on the saccade under examination and the onset must always follow offset, the eligible onsets are necessarily later in time that eligible offsets.F = 10.2, p = 0.01], wherein the standard deviation is smaller (the timing is more precise) for onsets than offsets in non-overlapping dialogue (t(10) = 3.25, p < 0.05), but not in overlapping dialogue.The associated HM lags are predominantly positive for VAD offsets, suggesting that they are largely reactive or timed to occur at the moment a talker finishes saying something. The saccade lags are more evenly and precisely distributed around zero delay with respect to the VAD onsets, suggesting that they may be timed to coincide with the onset. The ANOVA of standard deviation confirmed an interaction between type of exchange and event type , reaching 10% larger at 78 dB. The only effect involving noise type was a four-way interaction on the mean timing of HMs , but the nature of this interaction is unclear.There is no obvious difference in the pattern of results as a function of noise level or noise type, but the ANOVA for the standard deviation of the HM timing (covering both overlapping and non-overlapping speech) revealed a small effect of noise level in which the timing was most precisely timed  at 60 dB (SPL) and became progressively less precise at higher noise levels . In the interaction, simple main effects confirmed that head turns occurred earlier in relation to speech onset than offset for non-overlapping speech  = 362, p < 0.001), and earlier in relation to offset than onset for overlapping speech  = 488, p < 0.001). No other effects were statistically significant.Compared to the data for non-overlapping dialogue in By analysing real triadic conversations between unfamiliar older adult participants, we demonstrated that a substantial proportion of head saccades from the unaddressed interlocutor around a turn switch occurred predictively. When conversational turns did not overlap, an average of 17% of the listener’s head turns to the upcoming talker occurred before the prior spoken turn ended, increasing to 26% when motor-planning time was taken into account. When conversational turns did overlap, an average of 18% of the listener’s head turns to the interrupter occurred before the interrupter interrupted, increasing to 33% when motor-planning time was taken into account. This is strong evidence for prediction of the turn end and the turn start, respectively.It is important to acknowledge that whereas most work using videoed conversation shows reactive orientations to an upcoming talker , we and Interestingly, while prior work using videoed conversation demonstrated that more degraded audio led to more delayed orientation to the upcoming talker , we did However, while we did not see a slowing of head turns in noise, we did see an increase of variability; head movements had a 10% larger standard deviation at 78 dB than at 60 dB, meaning they were more spread around speech onsets/offsets when the noise level was higher. This distinction between the mean and the standard deviation of orientation timing could reflect that while predictions were made in a similar manner regardless of noise, the temporal precision of these predictions may have been reduced for degraded speech. Interestingly, this complements recent work demonstrating not only slower but also more variable timing of spoken turns in noise , as well as more variable timing of spoken turns for people with hearing loss , but in the latter case, this was a result of ‘floor request’ signals from a listener. Such a communication feedback loop  makes itIn conclusion, this paper re-analysed an existing dataset of older adults engaged in triadic conversation to provide evidence that listeners can anticipate when a speaker will finish a conversational turn. This work demonstrates the value of head movements in assessing interlocutors’ focus of attention around a conversational turn switch, and indicates the propensity of listeners to orient towards an upcoming talker before they start talking. Such findings could be highly relevant for hearing technology. Hearing devices use beamformers to amplify specific regions around the wearer’s head while dampening others, and currently have a wide beam to amplify most of what is in front of the user. Recent work, however, has begun to explore the potential benefits of narrower beamformers , increasosf.io/w6t3y.Publicly available datasets were analysed in this study. This data can be found at: Ethics approval was obtained from the West of Scotland Research Ethics Committee (09/S0704/12). The patients/participants provided their written informed consent to participate in this study.LH and JC contributed to the conception and design of the paper. JC performed the statistical analysis, wrote sections of the manuscript, contributed to the manuscript revision, and read and approved the submitted version. LH wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.LH is supported by a UKRI Future Leaders Fellowship [grant number MR/T041471/1]; and the Medical Research Council [grant number MR/X003620/1]. JC is supported by the Engineering and Physical Sciences Research Council [grant number EP/S030298/1]. Funders did not play a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The University of Nottingham provided open access publication fees.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


On the interaction between the clusters and graphene with defects, the charge was transferred from the clusters to the modified graphene, and it was observed that the binding energy between them was substantially higher than that previously reported for Pd-based clusters supported on pristine graphene. The vertical ionization potential calculated for the clusters supported on modified graphene decreased compared with that calculated for free clusters. In contrast, vertical electron affinity values for the clusters supported on graphene with defects increased compared with those calculated for free clusters. In addition, the chemical hardness calculated for the clusters supported on modified graphene was decreased compared with free clusters, suggesting that the former may exhibit higher reactivity than the latter. Therefore, it could be inferred that graphene with defects is a good support material because it enhances the stability and reactivity of the Pd-based alloy clusters supported on PNG.Graphene with defects is a vital support material since it improves the catalytic activity and stability of nanoparticles. Here, a density functional theory study was conducted to investigate the stability, energy, and reactivity properties of Ni Moreoveorous Pd . In addireaction . Among tNevertheless, clusters or nanoparticles tend to agglomerate, which can affect their catalytic activities and stabilities ,22. Cons12  nanoparticles deposited on graphene with a vacancy was investigated employing the density functional theory (DFT). It was shown that the defective graphene can provide anchoring sites for these nanoparticles by forming a strong metal−graphene interaction [6Ni4 and Pd4Ni6 clusters supported on defective graphene have been investigated using the DFT and shown to have good stability [12  core-shell nanoparticles supported on PNG using the DFT [nPdn (n = 1−3) clusters supported on graphene with a vacancy and on PNG with one, two, and three N atoms is developed.There are many theoretical studies on the electronic and energetic properties of monometallic clusters supported on modified graphene ,35,36,37eraction . In anottability . Recentl the DFT , demonst−6 Eh, max. gradient = 3 × 10−4 Eh/Bohr, rms gradient = 1 × 10−4 Eh/Bohr, max. displacement = 4 × 10−3 Bohr, and rms displacement = 2 × 10−3 Bohr. To investigate the stability of NinPdn (n = 1−3) clusters on PNG, most stable structures for the clusters were obtained from a previous study [All electronic structure calculations were conducted with the DFT as implemented in the ORCA package . The revnPdn (n = 1−3) clusters deposited on graphene with different defects, circumcoronene (C54H18) was used as the graphene model. To obtain graphene with a vacancy, a C atom was removed from graphene (b) between the bimetallic cluster and the modified graphene was calculated by the following equations:To investigate the stability, energy, and reactivity properties of Nigraphene a. To obtgraphene b–d. The nPdn (n = 1−3) clusters and PNG were investigated using the quantum theory of atoms in molecules implemented in the Multiwfn 3.8 program [Finally, the intermolecular interactions between the Ni program .nPdn (n = 1−3) clusters are illustrated in 2Pd2 cluster was a triplet with a tetrahedral shape. Finally, the most stable structure of the Ni3Pd3 cluster was an incomplete pentagonal bi-pyramid with a spin multiplicity of five.The ground-state structures of the NinPdn (n = 1−3) clusters, 2Pd2 cluster had the lowest value. The η was calculated from the VIP and VEA. As the cluster size increased, the η tended to decrease, which suggested that the larger clusters presented greater reactivity. The calculated properties were similar to those previously reported for these systems [Different properties, e.g., the binding energy per atom (BE/n), vertical ionization potential (VIP), vertical electron affinity (VEA), and chemical hardness (η), were calculated for the ground-state cluster structures of the NinPdn (n = 1−3) clusters and graphene with different defects was obtained using many initial interactions. 2Pd2 cluster deposited on the graphene with defects, the most stable interaction was with two Ni atoms joined with the graphene substrates, whereby one of the atoms was anchored in the vacancy  clusters and graphene with defects was also computed  clusters deposited on graphene with a vacancy was higher compared with that calculated for the same clusters supported on PNG with a different number of N atoms. These results are similar to those reported in the literature, where it was observed that the Eb of Nin (n = 1−4) clusters supported on graphene with a vacancy was higher than that computed for the same clusters supported on PNG with a different number of N atoms [nPdn (n = 1−3) clusters and modified graphene was also calculated  clusters supported on graphene with defects . The computed properties for the clusters were similar to those reported in the literature, demonstrating the reliability of the method used in this study. Regarding the stability of the NinPdn (n = 1−3) clusters supported on modified graphene, the charge was transferred from the clusters to graphene, and the Eb between them was substantially higher than that previously reported for Pd-based clusters supported on pristine graphene. The VIP calculated for the clusters supported on modified graphene decreased compared with that calculated for free clusters. The computed VEA for the clusters supported on modified graphene increased compared with those calculated for free clusters. The η computed for the clusters supported on modified graphene decreased compared with that calculated for free clusters, suggesting that the clusters supported on modified graphene can present greater reactivity than free clusters as a small η implies an increase in the reactivity. Therefore, it could be inferred that graphene with defects is a good support material because it enhances the stability and reactivity of the Pd-based alloy clusters supported on PNG.A DFT study was conducted to investigate the stability, energy, and reactivity properties of Ni


Hyalomma ticks. The present study investigated the acaricidal activity of neem seed extracts at different concentrations against developmental stages of the camel tick Hyalomma dromedarii in comparison to Butox and diazinon. The acaricidal activity of three extracts, namely, hexane extract (HE), methyl chloride extract (MCE), and methanol extract (ME), of neem seeds (Azadirachta indica) were tested at varying concentrations of 5, 10, 15, and 20% on engorged H. dromedarii female ticks at days 1, 3, 5, 7, 12, 16, 20, 28, 37, and 43 after treatment (DPT). Interestingly, results of applying different neem seed extracts to engorged H. dromedarii female ticks showed that the most effective extract was hexane at concentration 20%, causing 100% mortality at 1st day post-application, while methanol extract at 20% and dichloromethane extract at 20% caused the death of all ticks at 28th day posttreatment as compared to Butox® 5.0 and Diazinon-60, which resulted in mortality of all ticks at 3 and 5 DPT, respectively. In addition, no mortality was reported with the application of aqueous extract (AE), which served as the control group. Furthermore, the neem hexane extract exhibited high efficacy against reproductive performance of female ticks, whereas no fertility or oviposition was reported at all of their concentrations. Additionally, no hatchability occurred using all neem extracts, except the aqueous extract, which showing no effect. In the present study, larvae responded more rapidly to the plant extracts, whereas mortality of all larvae was recorded at 24 h after treatment with 5% hexane. Taken together, this study pointed out that the acaricidal effect of hexane extract of neem seeds was more effective and could be economically used for controlling H. dromedarii ticks.Tick infestation remains one of the major health problems that affect the productivity and comfort of camels. The control of ticks mainly relies on using chemical acaracides. Limited information is available on the potential benefits and activity of various neem extracts on  Hyalomma dromedarii is considered the most reported Hyalomma spp. parasitizing camels in Egypt  extracts against H. dromedarii. A previous study  using the immersion method and in mortality rates of engorged ticks from 1st to 15th DPT (up to 100%), with some changes in morphology. Also, there was a potent activity of the methanolic extract of neem leaves on hatchability of H. dromedarii eggs (100%) from 1st to 15th DPT, and it induced 100% mortality on the newly hatched larvae of H. dromedarii ticks. Agreed with the aforementioned information, this study aimed to investigate the effect of neem extract application on ticks infesting one-humped camels in Aswan Governorate, Egypt, which might provide new insights into the control of hard ticks in camels.Revising the available literature, limited information is available about the use of us study  showed tThe ethical approval of the present study was obtained from the Research, Publication, and Ethics Committee of the Faculty of Veterinary Medicine, Aswan University, Egypt, and the Institutional Review Approval Board Number is 2020/5.Engorged adult, larvae, and nymphs of hard ticks were collected from naturally infested camels (5- to 15-year-olds) from Daraw market, Daraw city, Aswan Governorate, Egypt. In order to minimize damage to the mouthparts and cuticle, the ticks were manipulated by rotating for easy removal with a pair of soft forceps. The collected ticks were then placed in a clean plastic container with perforated lids to allow ventilation, then immediately transported to the laboratory at the Department of Parasitology, Faculty of Veterinary Medicine, Aswan University, for identification using standardized international keys and bioassays, as described elsewhere , 42, 43.Hexane, diethyl ether, dichloromethane, and methanol solvents, Tween 20, Tween 80, TLC plates 20 × 20 cm, and vanillin spray reagent were purchased from Sigma Chemical Company, Cairo, Egypt. Synthetic chemical acaricides such as deltamethrin (Butox 5%) and Diazinon-60 were purchased from Arab Chemical Industrial Company, Cairo, Egypt.Neem seeds were collected from an old neem tree located at Aswan University during July 2020 at 10 a.m. and identified and authenticated by Department of Botany, College of Science, Aswan University. The collected seeds were then transported to the Laboratory of Parasitology, Faculty of Veterinary Medicine, Aswan University, Egypt, and stored at 4°C until analysis.The seeds were cleaned to remove any sticks, unwanted leaves, bad seeds, sand and dirt in order to ensure the oil produced is not contaminated and of high quality. The cleaned neem seeds were dried at 55°C for 72 h until constant weight and moisture content determined, as described elsewhere  using Eqwhere W1 is the weight of neem seeds before drying and W2 is the weight of neem seeds after drying.The dried clean neem seeds were roasted about 5 min to enhance extraction of oil, then crushed in a blender, and sieved to obtain particles ranging from 425 to 710 μm in size. The sieved neem powder was then stored under vacuum in an airtight container at 4°C prior to use .To obtain extracts from the neem seeds, about 9,000 ml of hexane was added to 3,000 g of the dried grounded neem seeds in a conical flask, which is then allowed to stand at room temperature for a period of 3 days with intermittent agitation (stirring) until the soluble matter dissolved. This mixture was filtered by gravity filtration, producing a hexane extract mixture as the filtrate, which was then concentrated using a rotary evaporator and stored at 4°C until further use . For thewhere M1 is the mass of the neem seed before extraction and M2 is the mass of the neem seed after extraction.The emulsion was prepared by mixing neem oil and two different non-ionic surfactants (Tween 20 and Tween 80) using each emulsifier separately, at rates of 1:5 and 1:3, respectively. Surfactants and deionized water were first mixed using a stirrer, and then neem oil was added. This step was followed by preparation of the different concentrations  from each extracts as described elsewhere  with sliIn this step, the plant extract was spotted on the plate with the aid of a capillary tube. The spot was applied 1 cm upward from the lower end of the TLC plate, then placed in a beaker consisting hexane:ether  with drops of methanol and dichloromethane:methanol (7:1/4) as the mobile phase. Run spots were performed to separate the compounds. Later on, when the mobile phase reached the upper end of the TLC plate, it was removed from a beaker and was air dried. The TLC run plates were observed by using a UV spectrophotometer, and the separated spots were marked. Then, the spots were visualized by vanillin spray reagent. After spraying, the plates were immediately placed in the oven maintained at 1,100°C for 5–10 min . A prepaFour concentrations  of neem extract emulsions were used, while in case of aqueous emulsion, only two concentrations of 5 and 10% were tested. Also, 5% deltamethrin (Butox 5%) and Diazinon-60 were applied. The tested groups included 15 adult female ticks (three replicates for each concentration) that were weighed and immersed in their respective dilutions for 5 min. The adult immersion test was then performed by placing each group of ticks in separate petri dishes, and all plates were incubated at 27–30°C and 70%−80% relative humidity (RH). A negative control composed of the surfactant and distilled deionized water was included along the study. The number of live and dead ticks was counted during the period of 43 days (posttreatment period). The mortality rate of adult female ticks was calculated according to the following equation (Equation 3):The acaricidal efficacy was calculated using the following equation , and theThe eggs were weighted and then incubated in test tubes at 27–30 °C and 70–80% RH. Later on, the percentage inhibition of egg laying was calculated after hatching 21 days by using the following formula (Equation 5):The neem extract emulsions with the different concentrations  were applied to its corresponding group of eggs, which were laid by a control group. The eggs (5-day-old eggs) were immersed in neem seed extract emulsions for 5 min and then were placed in open test tubes until drying emulsions, and then the test tubes were closed with cotton plugs to avoid contamination. All tubes were also incubated at 27–30°C and RH of 70%−80%. The control group eggs consisted of filter paper envelops immersed in the surfactant, and distilled deionized water was also used. After 21 days, all tubes were incubated at 40°C for counting, and hatchability was determined, as described elsewhere .The eggs of the adult control group were placed in test tubes and incubated at 27–30°C and 70%−80% RH until they hatched into larvae. The larval packet test was performed using about 300–400 larvae (at 10-day-old larvae) which were then placed in filter paper envelopes immersed in neem seed extract emulsions with the different concentrations  . All envThis step involved collection of nymphs from camel tail and ears. Each group of 15 nymphs was immersed in the various concentrations  of neem extract emulsions for 5 min. Then, the nymphs were placed in separate petri dishes, and all plates were incubated at 27–30°C and 70%−80% RH. A negative control consisted of the surfactant, and distilled deionized water was also included. The number of live and dead nymphs of ticks was counted posttreatment during the whole time of the test, and the acaricidal efficacy was determined , using tp < 0.05. Curves and the lethal concentrations (LC50 and LC90) were obtained at 95% using probit analysis with LDP line software  and non-hatching eggs and antifeedant activity of the ticks were analyzed by one-way ANOVA. This was followed by using of Duncan multiple range tests  to detersoftware .H. dromedarii infestation in camels. As shown, the 5% hexane extract was the most effective extract, which showed evident changes and caused death of Hyalomma ticks from the first day of application with a percentage of 46.7%, and caused complete mortality of ticks at day 20. The methanol extract (ME) followed HE in its efficacy since and caused 100% mortality at day 37. On the other hand, little effect was obtained by uding dichloromethane, compared to that recorded with Butox® 5.0 and Diazinon-60, which caused mortality of all ticks at day 3 and day 5, respectively. By contrast, no mortality was recorded among control groups and following treatment with aqueous extracts. The data presented in Data presented in H. dromedarii engorged female ticks exposed to the effect of various concentrations of neem seed extracts. The results indicated that there was no oviposition with all concentrations of hexane extract, while oviposition percentages with application of methanol extract at concentrations of 5, 10, 15, and 20% were 18.8, 12.5, 7.5, and 2.5%, respectively. Furthermore, a little effect was obtained with the application of dichloromethane as the oviposition percentages were 87.5, 81.3, 75, and 68.8% at concentrations of 5, 10, 15, and 20%. The results also indicated that there was a significant effect for hexane extract on the fertility of H. dromedarii at all concentrations. In this regard, the fertility rates were 100, 95, 91.6, and 75%, and their corresponding concentrations of methanol extract concentrations were 5, 10, 15, and 20%, respectively. On the other hand, no effect was obtained upon application of aqueous extracts on oviposition and fertility of ticks. Data presented in H. dromedarii nymphs. In this regard, hexane extract at a concentration of 5% induced a mortality rate of nymphs reaching 80 and 100% at the first day posttreatment and 3rd day posttreatment, respectively. Furthermore, the mortality rate of nymphs reached 100% at concentrations of 10 and 15% of hexane extract at first day posttreatment. In the case of methanol extracts, the mortality of nymphs reached to 40 and 100% at the first day posttreatment and 3rd day posttreatment, respectively, while the mortality reached 100% at concentrations of 10 and 15% using the same extract on the first day posttreatment. On the other hand, the lowest effect was observed with dichloromethane, and no effect gained using the aqueous extract.Data presented in H. dromedarii collected from camels, and their activity seem to depend on the used concentration. As shown in ® 5.0 and Diazinon-60 induced in mortality of all ticks at 3 and 5 DPT, respectively. Furthermore, application of the aqueous extract (AE) of neem seeds caused the mortality of adult ticks 43 DPT, which also occurred in the control groups. The same effect was also observed in previous studies on Rhipicephalus microplus  of neem seed oil were able to kill all Boophilus decoloratus larvae in cattle after a period of 24–27 h , as well as between 10% hexane extract and Butox (5%) and diazinon (p > 0.05), while there is no significant relationship between Butox 5% and diazinon (p > 0.05). The tabulated data concluded that the efficiency of Butox 5% and diazinon was more than that of 10% hexane extract against infested ticks. Despite the fact that the data of our current study indicated that synthetic chemical insecticides were more efficient in controlling ticks than neem extract oil, the application of neem at higher doses on affected animals might offer many advantages for the control of ectoparasites without the risk of toxicity to them (Regarding the effect of methanol extract (ME) of neem seeds on ticks, which is shown in ing rate . Our resing rate , 60, 70.ing rate , 7, whicing rate . Importaing rate , 5–7 hadt et al. . This pot et al. . In the  to them .in vitro application of neem extracts showed high efficacy against camel ticks. More importantly, the hexane extract exhibited a highly acaricidal effect on adult ticks of camels from the first day of application and continued up to 20 days after treatment, resulting in 100% mortality. The present data provide a platform for the development of environment-friendly, non-toxic, non-accumulating medicines against ectoparasites, which could be carried out in a large scale in animal farms.The study concluded that the The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.The animal study was reviewed and approved by Ethics Committee of the Faculty of Veterinary Medicine, Aswan University, Egypt, and the Institutional Review approval Board Number is 2020/5.AG, DH, AE, SK, MK, and AM designed the idea of the conception, performed the methodology, formal analysis, data curation and supervision, and revised the manuscript. AA, EE, NE, EH, ML, FE-G, and EKE participated in the methodology, formal analysis, data curation, and scientific advice. AG, AE, SK, EE, and EKE drafted the manuscript, prepared the manuscript for publication, and revised the manuscript. All authors have read and agreed to the published version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The measurement and control of humidity is a major challenge that affects the sensing properties of sensors used in high-precision equipment manufacturing industries. Graphene Oxide(GO)-based materials have been extensively explored in humidity sensing applications because of their high surface area and functional groups. However, there is a lack of effective bulk-manufacturing processes for the synthesis of 2D-based nanocomposites with comb electrodes. Moreover, water intercalation within the layers of 2D materials increases recovery time. This work demonstrates the enhanced sensing characteristics of a capacitive/resistive GO-MnZnO nanocomposite humidity sensor produced using a cost-effective single-pot synthesis process. The in-plane sensing layer consistently improves sensitivity and reduces response time for a wide range of relative humidity measurements (10% to 90%). Interdigitated gold electrodes with varying numbers of fingers and spacing were fabricated using photolithography on a Si/SiO₂ for a consistent sensor device platform. The choice of nanomaterials, dimension of the sensor, and fabrication method influence the performance of the humidity sensor in a controlled environment. GO nanocomposites show significant improvement in response time (82.67 times greater at 40% RH) and sensitivity (95.7 times more at 60% RH). The response time of 4.5 s and recovery time of 21 s was significantly better for a wider range of relative humidity compared to the reduced GO-sensing layer and ZnMnO. An optimized 6 mm × 3 mm dimension sensor with a 28-fingers comb was fabricated with a metal-etching process. This is one of the most effective methods for bulk manufacturing. The performance of the sensing layer is comparable to established sensing nanomaterials that are currently used in humidity sensors, and hence can be extended for optimal bulk manufacturing with minimum electrochemical treatments. The research and development of 2D materials in humidity sensing are progressing at such a rapid pace that the limitations in the technology for measuring minute changes in electrical parameters are becoming more significant. Manufacturing more sophisticated, high-precision equipment drastically increases the cost of synthesizing, characterizing, and testing the materials. Even though there are advancements in material science, the challenge to thrive effectively with the established materials is an ever-growing subject of research. One such material to be considered in humidity sensing is graphene, which is very much compared with recently developing Mxene. The need for more precise humidity sensing and control is a rising challenge in most industrial applications. Optimized control of humidity requires versatile sensing characteristics of the humidity-sensing device. The measurement of water vapor in gas, i.e., hygrometry, is comparatively more complex than measuring the temperature of the same environment, though both parameters are related to each other . For exaHygrometry is in fact “a branch of applied physics in which the multitude of techniques is an indication of the complexity of the problem, and of the fact that no one solution will meet all requirements at all times and in all places” . Fast re2, NH3, and so on. This may affect the overall single-molecule sensitivity of the sensing layer. There are metals such as Zn, Cu, Sn, Au, and Pt that can be added to GO to modify the conductivity and consequently the selectivity of gases [2/GO interface in an interdigitated electrode capacitive/resistive sensor is affected, when relative humidity is increased. Hence, the lifetime stability of sensing material is very much limited. It is observed from the literature that ZnO is one of the preferred materials because it exhibits superior electrical conductivity, high thermal, chemical stability, mechanical stability, and low cost due to its abundance in nature [2+ ion being 74 pm and that of Mn2+ being 70 pm, the overall size of the MnxZn1−xO samples decreases with increasing Mn doping concentration. Moreover, the doping of ZnO with transition elements leads to weak structural disorder, which is due to mass and size asymmetries of dopants into the host lattice. Hence, nanosynthesis materials still have challenges to improve long-term stability and effective bulk production. The overall efficiency of humidity sensing could be enhanced by synthesizing nanocomposites. The selection of nanocomposites of GO may significantly increase the performance of the sensor, as GO nanosheets contain rich oxygen groups for good adsorption of water molecules. To avoid the swelling of the sensing layer at higher humidity levels, the in-plane capacitive type sensor is preferred over the sandwich-structured capacitive sensor. It is observed that the time taken for complete desorption of the water molecules in the sandwich structure is more because of top electrode placing. Hence, it is more effective to cast the sensing material on the electrode surface as an in-plane capacitive/resistive type humidity sensor. MnxZn1−xO would form cross-linking between layers of GO to prevent water intercalation and swelling which is detailed in the final session. Moreover, the conduction of GO at low relative humidity (RH%) levels shall be improved, with ZnO and Mn doping in the composite for linear response. This further increases the consistent slope of sensitivity of the sensor for a wider sensing range of RH% levels.In general, two-dimensional (2D) materials are recognized as promising sensors with advantages such as high surface area and surface functionality. Ultra-thin materials such as palladium nanosheets (PdNS) and MXene  are trending nanocomposite materials for many types of gas and humidity sensing ,16,17. Hof gases ,29. Few of gases . In highn nature . Few evan nature . It has xZn1−xO nanocomposite structures, with relatively facile technology, is developed through freestanding chemical synthesis. Reduced GO nanoparticles and MnxZn1−xO nanoparticles were also synthesized for comparison of performances. All three materials  were coated on five customized different configurations of interdigitated comb electrodes (IDE), with a fixed 6 mm × 3 mm area  to choose optimized performance characteristics. The GO-MnxZn1−xO nanocomposite sensing layer is also tested for different humidity levels and characterized using various characterization techniques. The enhanced performance of the sensing device is predicated due to the peculiar characteristic of GO-MnxZn1−xO nanocomposites.In this work, a highly stable and sensitive in-plane capacitive/resistive humidity sensor based on GO-MnInitially, an extensive analysis is carried out to synthesize nanocomposite-containing GO as an essential compound. Hence, the whole synthesis process is performed at relatively low-temperature levels (less than 600 °C) compared to ceramic metal oxides, which usually can withstand temperatures above 800 °C .Graphene Oxide (GO) is prepared by oxidizing graphite powder using the well-established modified Hummer’s method.3CO2)2·2H₂O) and Manganese acetate ((CH3CO2)2Mn) were taken as precursors in the sol-gel process in a 1:1 mole ratio. Each precursor is dissolved in 50 mL of deionized water. These solutions are further dissolved in 30 mL of dimethylformamide at room temperature and mixed to a clear solution under vigorous stirring. The clear solution is further stirred for 24 h, maintaining the temperature between 60 °C to 70 °C. The gel formation is observed after vaporizing. The gel product is then dehydrated at 150 °C for 3 h. Final nanopowder MnxZn1−xO is obtained after thermal decomposition of the dehydrated gel at a calcination temperature of 350 °C for 4 h. The concentration of Mn in the final product is 37%.Zinc acetate  were dissolved in GO  by adding anhydrous ethanol solution (0.6 g/L). The mixture is stirred and sonicated for about 30 min, after which the solution contains oxalic acid to metal ion molar ratio of 1:1. This solution with 55 mL of anhydrous ethanol is slowly dropped into the graphene oxide solution at 50 °C, producing a precursor. Finally, the precursor is annealed in argon gas starting from room temperature to 600 °C at the rate of 5 °C/min and held for 2 h. The ground finished end product is a dark grey GO-Mn2 layer is grown carefully using thermal oxidation technique at 1000 °C for 4 h including different stages of dry and wet oxidation. The wafer is cleaned with trichloroethylene and isopropyl alcohol followed by acid cleaning with nitric acid and hydrofluoric acid to remove the oxide layer formed in atmospheric conditions. Then, gold (100 nm thick) is deposited using thermal evaporation and its thickness is measured to be an average of 98 nm with roughness less than 2 nm. An effective photomask pattern is designed with different numbers of fingers, finger widths, and different spatial wavelengths (λ), as listed in xZn1−xO, and GO-MnxZn1−xO nanocomposite is individually mixed with deionized water and drop cast on fabricated sensors. The required electrical connections are taken out by using silver conductive paste and the sensor devices are mounted on copper-toned FR-4 board. Fabrication of IDE with the variation of finger width and distance between fingers is done by a conventional photolithography technique. A silicon (100) substrate of 4-inch diameter is used on which a 1 µm-thick SiOThe fabricated humidity sensor is characterized by setting up an in-house controlled environment of a 1-L volume chamber maintained at a constant temperature of 25 °C, with the reliable data recording. The schematic diagram of the test set-up is presented in TM 3100 Atomic Force Microscope is used for high-resolution height profiling of the comb electrode; (v) Agilent BA1500 parameter analyzer is used for current measurement.The following tools are used to characterize the nanomaterials: (i) Scanning Electron Microscope with EDS MA15/ EVO 18  is used to investigate the surface morphology of the nanostructure; (ii) PANalytical X’Pert Powder X-Ray Diffractometer System  is used to obtain XRD patterns; (iii) Scanning Electron Microscope NanoAnalysis INCA Energy 250 Microanalysis System -EDS  is used for quantitative analysis of synthesized nanomaterials; (iv) Digital Instruments DimensionThe sensor fabrication process is done with the following equipment: (i) oxidation of p-type(100) silicon wafer was done in the Tempress Omega three heating zone chamber; (ii) Mask Writer Heidelberg—DWL 66  is used to prepare positive and negative masks for the lift-off and metal etching processes, respectively; (iii) Photolithography Mask Aligner Model 5000  was used for lithographing; (iv) E-beam Evaporation BOC Edwards Auto 306  is used to pattern gold for electrodes; (v) 7100-Provectvs  is used for precise dicing of multiple sensors of 6 mm × 3 mm each from a 4-inch × 4-inch wafer; (vi) detailed patterns of different dimensions of comb electrodes are studied using Confocal Microscope Olympus LEXT 3D Measuring Laser Microscope OLS4000 ; (vii) thickness of oxide layer and gold electrode layers are measured using Woollam Spectroscopic Ellipsometer M-2000VI EC-400  focusing beam angle kept at <70°.xZn1−xO and GO-MnxZn1−xO powders, as shown in xZn1−xO has 37.7% of Mn. In GO-MnxZn1−xO nanocomposite, the Mn and Zn constituted 2.23% and 26.39% respectively. In xZn1−xO and GO-MnxZn1−xO peaks. The broadening of the peak near 2θ = 24.5° shows a reduction of GO, hence forming a composite. The peaks are sharper at (100), (002), (101), (102), (110), and (201) planes. It is found that the samples exhibiting the diffraction peaks of ZnO and Mn3O4 are in good agreement with JCPDS no.050664 and JCPDS no.080017.The Energy Dispersive X-ray Spectrometry (EDS) data reveal the concentration of MnxZn1−xO, and GO-MnxZn1−xO nanocomposite, SEM images are studied. The sheet structure of reduced GO is seen in xZn1−xO in To analyze the morphological structure of GO, MnxZn1−xO in xZn1−xO in GO sheets, with particle sizes ranging between 120 nm–140 nm. MnxZn1−xO nanoparticles are tightly adsorbed on GO sheets.The SEM image of nanocomposite GO-MnSince the sensing layer is in-plane with the interdigital electrode, the fringing electric field penetration in the sensing material plays an important role in measuring capacitance change with relative humidity, which is proportional to comb electrode dimensions ,34. HencIn this work, a capacitive/resistive humidity sensing device is designed by drop-casting the sensing material on a custom-designed IDE. Though the comb electrodes are designed in five different combinations of numbers of fingers, the spatial wavelength of less than 0.6 mm gives better performance; hence 28, 20, and 16 finger combs are taken for further detailed testing. This is because the spatial wavelength is proportional to the penetration depth of fringing electric fields above IDE . The detbaseI corresponds to current at 15%RH, while RHI is the current at respective measured RH%. It is observed that the response for 28 fingers GO-MnxZn1−xO  nanocomposite is much higher than GO and MnxZn1−xO . The overall response comparison with corresponding RH% change is shown in xZn1−xO nanocomposite enhanced the response 82.67 times more than GO, and 61.28 times more than MnxZn1−xO .Sensitivity is a critical parameter in choosing any sensor. This fabricated sensor sensitivity is tested for two parameters, namely capacitance and resistance, relative to the change in RH%. Initially, sensitivity is studied in terms of capacitance for various ranges of RH%. The variation of capacitance for 28, 20, and 16 finger combs at 100 kHz frequency and 1 V AC input signal are taken separately for GO-Mnacitance , the forxZn1−xO shows a wide change in resistance, ranging from 2.6 MΩ to 1.4 kΩ at 10%RH to 90%RH, respectively. This proves the enhanced performance of the nanocomposite is 94.5 times higher than MnxZn1−xO and 97 times greater than the conventional GO.As depicted in sensitivity  for wide range of change in RH% . Moreover, the new nanocomposite depicts a 10.74-times enhancement of sensitivity than MnxZn1−xO and 15.5 times more than that of the GO material.As per the IUPAC definition, the humidity . Figure xZn1−xO nanocomposite, MnxZn1−xO, and GO for 16-, 20-, and 28-finger comb electrodes in terms of capacitance is shown in In this research work, the comb electrode dimensional parameters and sensing layer properties significantly affect response and recovery times. Both response and recovery times are defined with RH% ranging from 20% to 85% while increasing as well as decreasing RH%. A detailed comparison of response times and recovery times for GO-MnxZn1−xO nanocomposite performed better for further analysis of the response and recovery times.The spacing of the electrodes is inversely proportional to the capacitance, while the sensing material dielectric properties and the number of fingers in the comb electrode are directly proportional to the capacitance of the humidity sensor . This shxZn1−xO nanocomposite with 28 fingers. This is a reliable improvement, compared with conventional GO (response time ~10.5 s and recovery time ~41 s) and MnxZn1−xO (response time ~6 s and recovery time of ~25 s) [xZn1−xO are used to detect other gases such as NO2, CO2, etc., but the responses for gas detection are comparatively lower than humidity sensing [xZn1−xO nanocomposite.As per recorder plots, demonstrated in f ~25 s) ,32. HencxZn1−xO nanocomposite-based humidity sensor is illustrated in The transient response of the GO-MnxZn1−xO nanocomposite is aged for more than 5 months and tested repeatedly under different humidity levels  for 30 consecutive days. The impedance is recorded at 100 kHz frequency and shows variations of less than 4% as seen in The stability of the sensor is one of the most important parameters in analyzing humidity sensing for a long period. When nanomaterials play the sensing role, their agglomeration is removed by simple mortar and pestle grinding. Considering the stability, the GO-MnxZn1−xO nanocomposite as demonstrated in xZn1−xO has a hysteresis error of maximum of 0.12 at 40%RH and minimum of 0.06 at 90%RH. Similarly, the maximum error in impedance for GO-MnxZn1−xO nanocomposite is 0.105 at 50%RH and a minimum of 0.062 at 90%RH in impedance as shown in xZn1−xO shows a maximum hysteresis error of 0.25 at 40%RH and minimum of 0.09 at 90%RH. The hysteresis error plays a very important role in the humidity-sensing property of the sensor as it defines the adaptability of humidity sensors for various environments. Since GO is hydrophilic, the synthesized GO nanocomposite shows less hysteresis error, as given in xZn1−xO nanocomposite sensing layer. The probable reasons behind the performance analysis in sensing the humidity sensor are the doping of nanocomposite, and the effects of choosing the dimensions of comb electrode (IDE) for optimizing the measuring parameters, which are thereby discussed analytically.These experimental results demonstrate the excellent performance of an in-plane capacitive/resistive humidity sensor, coated with an effectively synthesized GO-Mne (me is free electron mass), when doped causes a large carrier and injected spins. xZn1−xO nanocomposite.GO produced through Hummer’s method accounts for a hydrophilic character with a high density of oxygen functional groups. GO opens the bandgap of graphene which is done through versatile defect engineering. On reducing the GO, some oxygen groups are removed and thus the energy band gap is adjusted by managing the oxygen groups present ,39. The 1−xMnxO nanoparticles, a higher concentration of Mn(37 w%) increased the agglomeration, because of the kinetic equilibrium process. The high concentration of Mn dopants might be nucleated with oxygen ions by itself and formed bigger particles as illustrated in 1−xMnxO compound [In the case of synthesized Zncompound .GO is widely known for high electrical resistance, especially at lower values of RH%. During the first layer of physisorption of water molecules and double hydrogen bonding, it requires high energy for conduction through proton hopping transfer below 20%RH as visualized in xZn1−xO nanocomposite. The synthesizing is done at low temperature and the process is a wet chemical method which, on the formation of MnO2, would eventually lower the effective bandgap [The concentration of Mn in the newly synthesized nanocomposite is taken to less than 2% mol to tune the energy bandgap in the GO-Mn bandgap ,46. Mn d1−xMnxO compound, and the newly synthesized GO-MnxZn1−xO nanocomposite, the added dopants crosslinked GO with silicon substrate even at high RH%(>85%), thus improving the stability. It further enhanced the electrical conductivity at low values of RH%(<20%). The ease of measurement for a wide range of RH% increased, and the longevity of the sensing layer for continuous monitoring. In addition, it reduces recovery time to nearly half (21 s) compared to pristine GO (41 s) [With the comparison of reduced GO nanoparticles, ZnO (41 s) .The major advantages of interdigital electrodes are fast measurement, being non-destructive, non-intrusive, and possessing compatibility for continuous measurements ,49. At ccellK) is taken into consideration for comparing the electrode dimensions that are given by Equation (4) to Equation (10):L is the length of an electrode (mm), N is the number of the electrodes of the sensor, W is the width of an electrode (μm), cellK is the factor of the cell (m−1) [The reduction of interface impedance between the sensing layer and electrodes improves the applied frequency bandwidth for measurement ,51. Hencll (m−1) .K(k) is then given by,sR) of the sensing layer given by Equation (7) is inversely proportional to the cell factor cellK.σs is the electric conductivity of the sensing medium (S/m).The resistivity (t), at the interface of the surface of sensor electrodes, and sensing layer is given by Equation (8),0 is the capacitance per unit area (pF/μm2) given by Equation (9),The total capacitance (CThe impedance of polarization which appears at the contact surface between electrodes and sensing layer is determined by the following Equation (10):t (1932 pF and 1995 pF) for 10 and 14 fingers (W = 0.2 mm), while compared to 16 fingers with width W = 0.1 mm, having a capacitance of 1607 pF. Moreover, optimizing the in-plane area, with the number of fingers (N) as 28, shows enhanced overall comb dimensions for effective bulk production methods  of sensor electrodes. According to Equation (10), the interface capacitance Ct is inversely proportional to polarization impedance (Zp). From the above demonstrations, interface capacitance (Ct) is 2901 pF for 28 finger electrodes, which reduces the polarization impedance more than 1/1000 times, and confirms the enhanced sensitivity at an operating frequency of 100 kHz.Hence, to choose an effective comb electrode, the effect of various dimensions are studied and tabulated in 1, p2, and p3 is illustrated in As far as in-plane sensing is considered, the fringing capacitance is an important parameter to measure, which is very much dependent on the number of comb fingers and spatial wavelength ,47. The 1−xMnxO nanocomposite with facile, single-pot processing procedure and excellent electrical properties for humidity-sensing applications are demonstrated. The functionality of nanocomposite sensing material and sensing platform are orchestrated by theoretical studies and practical experimentation, comparing three materials GO, Zn1−xMnxO, and GO-Zn1−xMnxO with five different dimensions of comb electrode. An optimized dimension of 6 mm × 3 mm, with 28 fingers, 0.1 mm width, and 0.1 mm spacing reveals the best performance result for simple photolithographic methods . The electrode deposition layer is far clear and has fewer defects in the metal etching process. GO-Zn1−xMnxO nanocomposite exhibited 82.67 times greater response at 40%RH and 95.7 times more sensitivity at 60%RH. The capacitance as well as resistance sensitivity show excellent consistency and are linear for a wide sensing range of humidity (10%RH–90%RH). GO-Zn1−xMnxO nanocomposite also inhibits very high stability, even after months of aging. The response time and recovery time are found to be 4.5 s and 21 s respectively. The device is even tested for hysteresis errors. With these characteristics, the newly developed humidity sensing device exhibited excellent performance in overall aspects. Thus, the GO-based nanocomposite has wonderful potential for future bulk production as an in-plane capacitive as well as resistive humidity sensor for high-precision industries.GO-Zn