A recently developed contactless ultrasonic testing scheme is applied to define the optimal saw-cutting time for concrete pavement. The ultrasonic system is improved using wireless data transfer for field applications, and the signal processing and data analysis are proposed to evaluate the modulus of elasticity of early-age concrete. Numerical simulation of leaky Rayleigh wave in joint-half space including air and concrete is performed to demonstrate the proposed data analysis procedure. The hardware and algorithms developed for the ultrasonic system are experimentally validated with a comparison of saw-cutting procedures. In addition, conventional methods for the characterization of early-age concrete, including pin penetration and maturity methods, are applied. The results demonstrated that the developed wireless system presents identical results to the wired system, and the initiation time of leaky Rayleigh wave possibly represents 5% of raveling damage compared to the optimal saw cutting. Further data analysis implies that saw-cutting would be optimally performed at approximately 11.5 GPa elastic modulus of concrete obtained by the wireless and contactless ultrasonic system. Concrete is one of the most popular materials in civil engineering. Along with the increasing need for structural inspection, ultrasonic methods have been employed to evaluate the quality of materials in situ. Ultrasound is beneficial for characterizing the soundness of materials because the wave parameters such as velocity and amplitude are directly related to the mechanical properties of the materials . HoweverRecent advances in non-contact ultrasonic sensing technology have broadened the scope of nondestructive inspection of various engineering materials including concrete . Zhu et On top of inspection applications , the contactless ultrasonic system enables the provision of practical information on early-age material characteristics, such as the setting time. Conventional methods to determine a setting time are based on pin penetration tests, where a physical pressure load is applied to the surface of a concrete specimen. However, the methods recommend wet sieving to filter out coarse aggregate such as gravel, which is a significantly labor-intensive and time-consuming procedure. Choi et al., 2016) first demonstrated that the initiation of leaky Rayleigh waves is a useful tool to determine the final setting of early-age cementitious materials without physical contact with the specimens . Moreove first deIn the characterization of early-age concrete, the contactless ultra-sonic system showed great potential for field applications. Tran and Roesler 2020) applied the contactless ultrasonic system to the saw-cutting initiation time in concrete pavements and suggested the framework to predict the relationship between the saw-cut initiation time and final setting time . Saw cut20 applieIn this study, the optimal saw-cutting time is investigated using the concept of a contactless ultrasonic scheme. The uniqueness of this study over previous research lies in (1) the improvement of the sensor network of the contactless system using wireless data transfer for possible field applications, and (2) the development of a signal processing and data analysis scheme to determine the optimal saw-cutting time. Moreover, we optimized the critical testing parameters of the contactless ultrasonic system for application to saw-cutting time, such as the incident angle, measurement time intervals, and the number of sensor array elements. The theoretical background of leaky Rayleigh wave propagation in early-age concrete is supported using numerical simulations. Moreover, the developed hardware and signal processing algorithm were experimentally validated and compared to the conventional methods, such as the pin penetration and maturity methods.Rayleigh wave is one of the surface waves, propagating at the surface of a medium. The wave motion is elliptical rotation, which is caused by the surface guidance of body waves. The portions of longitudinal and shear waves generate the unique behavior of wave propagation. The relationship between material properties and Rayleigh wave velocity is given by’s ratio .At the joint-half space of air and concrete, small portions of the Rayleigh wave en0.ergy are leaked into the air . A contactless ultrasonic measurement system measures the leaky Rayleigh wave without a physical coupling procedure to the surface of a concrete element. In non-destructive evaluation, the measurement of leaky Rayleigh waves has the great benefit of non-invasive material characterization.Concrete is the composite material consisting of cement, and fine and coarse aggregate. The early-age concrete mixture is in a liquid state when water is added, and the hydration reaction makes the mixture harden in time. Conventionally, the degree of hardening at the initial stage is defined by the initial and final setting, generally representing the initiation of chemical adhesion and the physical stiffening of the mixture, respectively. The solid-state of concrete is considered as the time after the final setting. Leaky Rayleigh waves are measurable when the medium enables stress transfer, implying the propagation of both longitudinal and shear waves inside the medium. Therefore, the initiation of leaky Rayleigh waves represents the critical phase of shear resistance development in the medium, which is more relevant to the definition of the final setting.The stiffening scenario with respect to leaky Rayleigh wave propagation is numerically demonstrated using the finite element method. The commercially available software, COMSOL Multiphysics, was used to analyze the propagation of the leaky Rayleigh wave at the joint-half space. The Multiphysics model included the air and concrete, where the ultrasonic excitation and sensing locations were positioned in the air. The details of the numerical simulation are described in E = 0.1 GPa) shown in E = 1 GPa), Rayleigh waves propagate at the surface of concrete, and the corresponding leaky waves are observed in the air. In the hardened concrete case (E = 25 GPa) seen in The simulation results presenting wavefield snapshots are shown in Based on the results of numerical simulations, the direct relationship between the leaky Rayleigh wave velocity and elastic modulus of concrete was derived as shown in To measure the leaky Rayleigh wave responses from concrete pavements, a wireless and contactless ultrasonic system was developed. The system includes two printed circuit boards (PCBs) encapsulated by an aluminum frame. Each PCB is designed for sensing and data acquisition parts, respectively. The sensing board consists of 16 MEMS  ultrasonic sensor elements placed with 5 mm spacing. The data acquisition board is composed of several components, including a field-programmable gate array (FPGA), multiplexer, amplifier, and Wi-Fi module. The details of the wireless system are presented in The acoustic pressure is measured using the MEMS sensor array, and the collected analog signals are amplified 2000 times at the center frequency of 50 kHz. Then, the analog signals are converted to digital signals with a sampling rate of 2 MS/s and a dynamic resolution of 14 bits. The data acquisition process is repeated 16 times through each MEMS sensor element of the array, and the acquired data are wirelessly transferred to a personal computer. The stored data can be checked in real-time with programmed software, and measurement parameters such as the number of time-averaging can be set by an operator. The developed system is significantly improved in terms of the overall structure of the sensor network compared to the previously applied wired unit . Second,In addition to the hardware development, we propose a signal processing approach to computing the leaky Rayleigh wave velocity from measured signals. An overview of the proposed signal processing approach is illustrated in t-x) to frequency–wavenumber (f-k) domains, given byf-k domain signal set, and j is the imaginary number. Next, a region of interest in the f-k domain is highlighted by multiplying a filtering mask First, bandpass filtering is applied to the measured signal set f and k values at the maximum amplitude of Note that the filtering operation shown in Equation (3) maintains wave components with the Rayleigh wave velocity of typical concrete while suppressing other unwanted components including noise. Then, peak frequency  was derived from the simulation results shown in To characterize the state of early-age concrete, conventional methods such as maturity and pin penetration methods were also performed. The pin penetration method (ASTM C403) is a standard test method to determine the setting time of concrete mixtures . In thisDespite its wide acceptance as a means to determine the setting time of concrete, the pin penetration method has several limitations. First, performing the pin penetration test is highly labor-intensive. As the pin penetration method is not applicable directly to concrete with coarse aggregate, wet sieving needs to be carried out to extract the mortar fraction of the concrete mixture. Also, the test results can vary depending on the proficiency of the operator. To obtain reliable setting times, the operator needs to be trained for the test procedure. Moreover, the pin penetration test is typically carried out in a controlled laboratory environment that can be different from that of an actual construction site .Q the activation energy divided by the ideal gas constant, and The maturity method (ASTM C1074) is a standard practice to estimate concrete strength using measured temperature data . Two matLike the pin penetration test, the maturity method has its own limitations. First, the laboratory curing temperature may not represent that of the concrete element on the actual construction site. Also, the strength of concrete cannot be estimated directly from the temperature measurement data; a calibration curve needs to be constructed before actual strength estimation is carried out, which is time-consuming. The maturity method does not capture local strength variations within a concrete element.The developed wireless and contactless ultrasonic hardware system and proposed signal processing approach were validated through experiments. All the early-age concrete specimens used in this study were produced with the mixture design proportions summarized in Once the specimens were prepared, contactless ultrasonic tests and maturity tests were carried out. For the contactless ultrasonic measurement tests (both the wireless and wired systems), a contactless air-coupled transmitter  with a center frequency of 48 kHz generated ultrasonic Rayleigh waves in the tested specimens, and the corresponding leaky Rayleigh wave responses were measured using an array of MEMS microphones. Measured analog signals were digitized at a sampling rate of 2 MS/s using a data acquisition device . An incident angle was set to 5° for the air-coupled transmitter. To improve the signal-to-noise level, 50 times time averaging was applied. Leaky Rayleigh wave responses were automatically measured every minute and stored in laptop computers.Pin penetration tests were carried out following ASTM C403. More details about the test method can be found in . For theLeaky Rayleigh wave signals measured using the contactless ultrasonic measurement systems are presented in Despite the good agreement in the leaky Rayleigh wave initiation time and wave-front development, the wired and wireless measurement systems show differences in signal-to-noise level in the B-scan images . The sigThe results from the conventional methods are presented in The equivalent age of the mixture is shown in Raveling damages caused by a saw cut that is too early were observed on the top surface of the slab specimen as shown in The quantified saw-cut areas as a function of elapsed time are presented in Based on the proposed signal processing scheme described in DI values closer to zero represent the smaller extent of raveling damage. To evaluate the degree of raveling damage, a damage index ((1)The wireless and contactless ultrasonic system measures the initiation of leaky Rayleigh waves and their velocity increments during concrete hardening. The performance of the developed hardware was nearly identical to that of the wired system.(2)The proposed signal processing scheme provides the velocity of leaky Rayleigh waves and the corresponding elastic modulus of concrete, which is a conservative prediction compared to theoretical Rayleigh wave velocity.(3)Graphical analysis efficiently shows time-dependent raveling damage, and a damage index is calculated to assess the damage level with respect to the development of elastic modulus.(4)The initiation of leaky Rayleigh wave with a 5° incident angle was observed two hours later than the final setting time defined by the pin penetration test, which represents 5% of raveling damage compared to the optimal saw-cutting time.(5)The correlation between the damage index and elastic modulus implies that the saw cutting would be optimally performed when the elastic modulus of concrete reaches approximately 11.5 GPa.In this study, a wireless and contactless system was applied to evaluate the optimal saw-cutting time based on leaky Rayleigh wave measurements. The development of sensor networks and the proposed signal processing approach were numerically and experimentally validated. Based on the results, the following conclusions were drawn:


Antibiotic resistance is a major human health problem. While health care facilities are main contributors to the emergence, evolution and spread of antibiotic resistance, other ecosystems are involved in such dissemination. Wastewater, farm animals and pets have been considered important contributors to the development of antibiotic resistance. Herein, we review the impact of wildlife in such problem. Current evidence supports that the presence of antibiotic resistance genes and/or antibiotic resistant bacteria in wild animals is a sign of anthropic pollution more than of selection of resistance. However, once antibiotic resistance is present in the wild, wildlife can contribute to its transmission across different ecosystems. Further, the finding that antibiotic resistance genes, currently causing problems at hospitals, might spread through horizontal gene transfer among the bacteria present in the microbiomes of ubiquitous animals as cockroaches, fleas or rats, supports the possibility that these organisms might be bioreactors for the horizontal transfer of antibiotic resistance genes among human pathogens. The contribution of wildlife in the spread of antibiotic resistance among different hosts and ecosystems occurs at two levels. Firstly, in the case of non-migrating animals, the transfer will take place locally; a One Health problem. Paradigmatic examples are the above mentioned animals that cohabit with humans and can be reservoirs and vehicles for antibiotic resistance dissemination. Secondly, migrating animals, such as gulls, fishes or turtles may participate in the dissemination of antibiotic resistance across different geographic areas, even between different continents, which constitutes a Global Health issue. Antibiotic resistance (AR) is nowadays one of the main human health problems . Its devBeing transmission an important element in AR spread, knowing the transmission routes is important to tackle the AR problem. In that sense, it has become evident that nearly every ecosystem in the biosphere can participate, at different degree, in the origin, evolution and spread of AR . UnderstEnterobacteriaceae, including common human commensals/pathogens such as Klebsiella, Citrobacter or Escherichia and that AR was lower in sampling locations further away from urban areas  are found in wild animals -not receiving antibiotics- this should be considered as a marker of AR pollution , more than areas . Further inhabit . Also su inhabit , carry m inhabit . The sam inhabit . This fa animals . Similarollution .To sum up, available information indicates that anthropic pollution by ARB and the ARGs they contain is a main driver for the acquisition of AR by wildlife and that the abundance of ARGs in the microbiomes of these hosts might reflect such pollution. This concept agrees with the finding that the abundance of ARGs in anthropogenically impacted environments correlates with human faecal pollution  .However, these facts do not mean that the situation is not of concern. Although wildlife is not expected to play a fundamental role in the emergence of AR, which mainly occurs in ecosystems containing antibiotics at selective concentrations and human-linked microbiomes -as the treated patients themselves - it can Staphylococcus aureus (MRSA) appeared in hedgehogs in the pre-antibiotic era  - cofinanced by the European Development Regional Fund “A Way to Achieve Europe”, by grant S2017/BMD-3691 InGEMICS-CM, funded by Comunidad de Madrid (Spain) and European Structural and Investment Funds and by MCIN/AEI/10.13039/501100011033 (PID2020-113521RB-I00). PL is recipient of a FPU fellowship and TG-G of a FPI fellowship, both from MINECO. LO-S is supported by a postdoctoral fellowship from Consejo Nacional de Ciencia y Tecnología (CONACyT-México).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.


BCL-2-like molecule, small transcript isoform), a BH3-only proapoptotic BCL-2 family member, mediates apoptosis of postmitotic immature neurons during embryonic cortical development, but its role in the adult brain is unknown. To better understand the physiological role of Blm-s gene in vivo, we generated a Blm-s-knockout (Blm-s−/−) mouse. The Blm-s−/− mice breed normally and exhibit grossly normal development. However, global depletion of Blm-s is highly associated with depression- and anxiety-related behaviors in adult mutant mice with intact learning and memory capacity. Functional magnetic resonance imaging of adult Blm-s−/− mice reveals reduced connectivity mainly in the ventral dentate gyrus (vDG) of the hippocampus with no alteration in the dorsal DG connectivity and in total hippocampal volume. At the cellular level, BLM-s is expressed in DG granule cells (GCs), and Blm-s−/− mice show reduced dendritic complexity and decreased spine density in mature GCs. Electrophysiology study uncovers that mature vGCs in adult Blm-s−/− DG are intrinsically more excitable. Interestingly, certain genetic variants of the human Blm homologue gene (VPS50) are significantly associated with depression traits from publicly resourced UK Biobank data. Taken together, BLM-s is required for the hippocampal mood control function. Loss of BLM-s causes abnormality in the electrophysiology and morphology of GCs and a disrupted vDG neural network, which could underlie Blm-s-null-associated anxiety and depression.Mood disorders are an important public health issue and recent advances in genomic studies have indicated that molecules involved in neurodevelopment are causally related to mood disorders. BLM-s ( Mood disorders such as depression and anxiety are common public health problems with a lifetime prevalence of 4–29%, and both rank among the top ten causes of disability , 2. Mood2) studies [B-Cell Lymphoma 2) family member BLM-s  causes anxiety- and depression-like behavior.Depression and anxiety might share the same etiology since both are marked by impaired cognition and respond to the same treatment. Although multiple neural, cellular, and molecular mechanisms have been proposed to explain mood control, no unified theory that integrates all information from studies of micro-, meso-, and macro-scales could be proposed to explain the pathophysiology of mood disorders . The lac studies , 27 and  studies , 29. In  studies . Here, iBlm-l gene  mouse line. Here, we reported our macro-, meso-, and micro-scale analysis of the Blm-s−/− mice to uncover the link of a proapoptotic molecule- BLM-s with anxiety and depression.BLM-s is a BH3-only apoptosis sensitizer/derepressor of the BCL-2 family, which consists of >40 members harboring the evolutionarily highly conserved BH domain and plays important roles in the regulation of cell death under various physiological or pathological conditions , 31. BLMs mVps50 , SyndetiSyndetin , mVps54L[mVps54L , and CCD[CCDC132 ) via theBlm-s knockout mice were generated from the Transgenic Mouse Models Core  using C57BL/6 J mice (purchased from the Jackson Laboratory). To specifically delete the Blm-s genome, we replaced the whole Blm-s genomic sequence, including the promoter region,  with a Neo gene cassette flanked by Flippase recognition sequence followed by an engineered exon composed of the fused 24–28th exons of the Blm-l gene plus IRES-eGFP. As demonstrated in Fig. Blm-s-specific knockout mice. However, while eGFP proteins could be detected by Western blot in heterozygotic or homozygotic Blm-s mutants, we were, for an unknown reason, unable to detect any fluorescent signals in any tissue sections from mutant mice.All experiments with mice were performed in accordance with the guidelines for the Care and Use of Laboratory Animals and were approved by the National Taiwan University College of Medicine and the College of Public Health Institutional Animal Care and Use Committee (NTUMC IACUC# 20170358). All experimental procedures for these assays, as well as PCR primers and antibodies used, are described in Supplementary Information.All behavioral training and testing were carried out in accordance with the behavioral schemes described . Animals3, 25 glucose, 2.5 KCl, 2 CaCl2, 1.25 NaH2PO4, and 1 MgCl2 at 23 ± 2 °C using a temperature controller . The mature GCs located at the outer 1/3 of the granule cell layer (GCL) were visually selected under an infrared and differential interference contrast (IR-DIC) microscope  equipped with an infrared-sensitive charge-coupled device camera . Whole-cell recordings were performed with a digitizer -equipped amplifier . Recording electrodes were filled with the low Cl- internal solution containing the following (in mM): 136.8 K-gluconate, 10 HEPES, 7.2 KCl, 7 Na2-phosphocreatine, 4 MgATP, 0.5 Na3GTP, 0.2 EGTA, and 0.4 % (w/v) biocytin (pH 7.3 adjusted with KOH). For all the recordings, the pipette capacitance was fully compensated, and series resistance was compensated to ~80% (Bandwidth: 1–2 kHz) in the current-clamp configuration. Signals were low-pass filtered at 2 kHz using a 4-pole Bessel filter and sampled at 10 kHz. Pulse sequences were generated by pClamp 10.2 or 10.3 . Electrophysiological data analysis is described in the Supplementary Information.Male mice with ages from 8 to 10 weeks were used. The hippocampal slices were prepared as described previously . During Blm-s−/− mice were scanned on a 7 T MRI system . Initial anesthesia was carried out using 4% isoflurane mixed with oxygen, followed by 0.5 mL dexmedetomidine  with a dose of 0.2 mg/kg body weight through i.p. injection. Isoflurane was switched off 10 min before the resting-state functional MRI (rs-fMRI) scan to minimize the impact of isoflurane on rs-fMRI data and was turned on before the diffusion tensor imaging (DTI) scan to minimize unwanted head motion during DTI acquisition. Both global and local shim procedures were performed to improve the field homogeneity. T2-weighted structural images were acquired using a fast-spin-echo sequence. For rs-fMRI, 1 or 2 sessions of gradient-echo echo planar imaging (EPI) with 250 repetitions were acquired using the identical geometric position as used for anatomical images. For DTI scan, 5 unweighted diffusion images (b0) and 30 diffusion-weighted images with b = 1000 s/mm2 were acquired. Image pre-processing and analysis were performed by using AFNI toolbox (http://afni.nimh.nih.gov), region of interest (ROI) was manually depicted according to Allen mouse brain atlas (https://mouse.brain-map.org), and resting-state connectivity among these areas was assessed by calculating the correlation coefficients between every 2 regions [Supplementary Information for more explanations).See Supplementary Information for more information. Briefly, a total of 14 WT mice and 12  regions , and the regions  was evalhttps://www.ukbiobank.ac.uk/. The genetic data released contained ~96 million variants using either Affymetrix UK BiLEVE Axiom or the Affymetrix UK Biobank Axiom arrays . Imputation was conducted centrally by UKB using two different reference panels (The Haplotype Reference Consortium (HRC) panel and UK10K + 1000 Genomes panel). We conducted standard quality control procedures for genetic variants and individuals, respectively.The subjects in the UK Biobank were recruited from 22 assessment centers across the United Kingdom, and additional data were collected via online questionnaires. Biological samples were also collected for genotyping. For detailed information on participants, please see p < 1 × 10−4 and r2 < 0.5 within the gene region for significant signals.We used all variables related to five domains, i.e., mood, anxiety, sleep, suicide, and psychosocial and well-being, which were collected at the assessment centers and online questionnaires. For instance, the mood domain contained 82 mood-related traits, which could be subdivided into 54 depressive traits and 28 manic traits. In total, there were 37 anxiety-related traits in the anxiety domain. Before testing genetic association, we evaluated population stratification by using principal component analysis. We performed logistic and linear regression analyses with the additive genetic model, and all models were adjusted for sex, age, and the top 10 principal components. We retained SNPs with association t-test. The sample size was chosen based on the literature in general without arbitrary exclusion of data points from statistical analyses. All experiments were all independently repeated with similar observations and represented either as mean ± s.e.m. or as mean ± s.d.Statistical analyses were performed using SigmaPlot 12 (Systat software). The results from behavioral tests were assayed using one-way, two-way, or two-way repeated measures ANOVAs followed by Tukey post hoc tests. The results from the quantification of TUNEL-positive cells were tested using two-tailed unpaired Blm-s-knockout (Blm-s−/−) mice. Because Blm-s transcript is an isoform of the Blm-l gene and is transcribed via the usage of alternative promoter and TSS located at the 24th intron of the Blm-l genome [Blm-s-specific knockout by removing the Blm-s genome but preserving the transcription of Blm-l gene  mice . Given that Blm-s mRNA is differentially transcribed by alternative usage of promoter and TSS [Blm-s-specific promoter to drive GFP expression in endogenous BLM-s-expressing cells. We found that GFP driven by Blm-s promoter expressed in the granule cells (GCs) of dentate gyrus (DG)  Fig. . BesidesDG) Fig. . We alsoice Fig. . We, theBlm-s−/− mice. First, we tested hippocampus-dependent spatial learning and memory by subjecting the Blm-s−/− mice to the Morris water maze (MWM) with age-matched WT mice as controls. Both Blm-s−/− and WT mice gradually learned relatively direct paths to the goal over the course of days, although the Blm-s−/− showed significant immobility during the initial adaptation period , with no significant difference in path length, swim speed, and latency time to the hidden platform  and remote memory (7 d) tests  and novel-object recognition (NOR) memory tasks on ice Fig. . On the sts Fig. . PuttingBlm-s−/− mice had defects in anxiety-like behavior. There were significant differences in all the parameters of the EPM in the Blm-s−/− mice. The mutant mice significantly reduced open space exploration and spent more time in closed arms  and forced swim test (FST), in which mice show epochs of immobility that are thought to reflect behavioral despair intersected by periods of active escape movement. Blm-s−/− mice showed longer periods of immobility in both tests , open field test , marble rms Fig. . In the rea Fig. . BesidesMBT Fig. . In the ice Fig. . The tot WT Fig. , suggeststs Fig. . TogetheBlm-s−/− mice are likely to be caused by a disrupted neural network. Brain neuroimaging such as rs-fMRI and DTI can be used to identify the brain-wide activity patterns and connectivity maps that underlie behaviors. Blm-s−/− mice (n = 12) and age-matched WT mice (n = 14) were scanned under dexmedetomidine anesthesia (0.2 mg/kg) on a 7 T animal MRI system. Analysis of preprocessed rs-fMRI images among ROIs involved in mood control —left caudate putamen (CPu), left insula—right CPu, left insula—left vDG, and right insula—right vDG  of Blm-s−/− mice when compared to that of the WT mice. Besides, the hippocampal volume of Blm-s−/− mice estimated by MRI was not different from that of WT  synaptic contacts in the DG by transmission electron microscopy and found that the PSD (postsynaptic density) length and area were altered in the asymmetric synapses of Blm-s−/− DG GCs  and spike properties, were compared between WT and Blm-s−/− DG along the dorsal-ventral axis. Blm-s−/− GCs from both dorsal and ventral DG (labeled as KO-dDG and KO-vDG) exhibited more hyperpolarized RMP compared with those from WT-dDG and WT-vDG, respectively  in response to depolarizing currents greater than 80 pA , AP threshold, and AP peak amplitude evoked by rheobase current injection revealed no significant difference between Blm-s−/−- and WT-GCs either from dorsal- or from ventral DG  gene in correlation with any depression-related traits from public assessable UK Biobank data (https://biobank.ndph.ox.ac.uk/showcase/). The genomic locations were based on the human genome GRCh37 assembly and defined from 5’ to 3’ region with an extra 50 kb. A total of 273 variants in VPS50 gene were retained for analysis. We analyzed 5 domains  containing 183 traits in total. After quality control, we used 425,214 individuals with European ethnic backgrounds in the UK Biobank to perform an association analysis. We performed logistic and linear regression models with additive genetic modes for binary continuous traits, respectively. All models were adjusted by sex, age, and the top 10 principal components. Two variants in VPS50 gene were significantly associated, and both associations were only in the mood domain but not in the other four domains. The first one, rs2285505, is located at intron 27 of VPS50 gene, which is equivalent to intron 3 of human homolog of murine Blm-s. It was significantly associated with two specific traits, i.e., longest period of depression  and longest period of unenthusiasm/disinterest . The second one, rs17147430, is located at intron 9 of VPS50 gene. It was also associated with the longest period of depression   variants of the human Blm VPS0 gene inBlm-s−/− mice do not show any obvious developmental defects in the brain, suggesting that either BLM-s acts redundantly with other BCL-2 family members or that multiple strategies are exploited to compensate for the loss of BLM-s for normal development of brain cortices. It has been reported that deficiency of BLM-l (mVPS50), an isoform of BLM-s, in mice causes a cognitive defect, which is attributed to dysfunctional dense core formation in neurons [Blm-s−/− mice exhibit anxiety- and depression-like behaviors while their ability for spatial memory and learning remain intact. Mesoscale analysis of Blm-s−/− mice via rs-fMRI further suggests that the emotional disorders in the Blm-s−/− mice could be related to a defect in the connectivity of vDG, which is critical for emotional control and is functionally segregated from the dDG that controls spatial learning and memory [Blm-s−/− mice are not different from the WT, the Blm-s−/− mature GCs, particularly those in ventral DG, do exhibit morphological and electrophysiological abnormalities, which could underlie the microstructural changes and altered functional connectivity in the vDG. Our results thus support the synaptogenesis hypothesis of depression, which states that dysregulated synaptogenesis leads to abnormal electrophysiology of neurons and aberrant circuit activity that underlies depressive behavior [Blm-s−/− mice exhibit anxiety and depression-like behavior.BLM-s is a BCL-2 family protein that has been shown to promote apoptosis of the migrating immature neurons during murine cortical development . However neurons . By contd memory –44. AlthLM-l mVPS0, an isoVPS50 rs2285505 and rs17147430 variants are statistically significantly associated with increased depression in mood domain. This implies that BLM-s may be one of the contributing factors to human MDD. In addition to BLM-s, other BCL-2 family members have been reported to be involved in mood disorders as exemplified by dysregulated prosurvival BCL-2 and BCL-xL in anxiety, depression, or bipolar disorders in humans [It has been hypothesized that human major depression disorder (MDD) is a polygenetic disorder resulting from accumulative effects of multiple mutated genes with minor effects each , 25. Altn humans –47. Anxin humans . These fBlm-s−/− mice would be expected to exhibit increased BCL-2 activity, which would lead to an antidepressive phenotype as previously reported [Blm-s−/− mice, arguing against such a scenario. Accordingly, BLM-s in the murine hippocampus might play a role in mood control via a nonapoptotic process.Given that dysregulation of either anti- or proapoptotic BCL-2 members is observed in mood disorders and that the hemostasis model among the BCL-2 members operates quite well in explaining their effect on cell survival , 50, it reported  rather treported . HoweverBlm-s−/− mice do imply BLM-s’ nonapoptotic role in mood control. First, recent genetic studies indicate that dysregulated developmental profiles of voltage-gated cation channels are highly associated with psychiatric diseases [Blm-s−/− DG GCs might result from BLM-s-mediated changes in the number, composition, location, or dynamics of ion channels within the membrane [Blm-s−/− DG also exhibit fewer dendritic branches and reduced dendritic spines, which could causally relate to depression behavior in Blm-s−/− mice. BLM-s may have a direct effect on the morphogenesis during the maturation of GCs in DG. Alternatively, the morphological changes of GC dendrites in Blm-s−/− DG might result from synaptic or cellular homeostasis in response to functional alteration related to decreased neuronal connectivity. Third, accumulative data have shown that mitochondrial impairment triggers mood disorders [Our extensive analyses of diseases  and thatdiseases . Therebymembrane . Second,membrane . The GCsisorders –62. A weisorders , 64. Becisorders , depletiisorders .Supplementary materials and methodsSupplementary Figure S1Supplementary Figure S2Supplementary Figure S3Supplementary Figure S4Supplementary Figure S5Supplementary Figure S6Supplementary Figure S7


The aim of this paper is to investigate the flexural performance of a new steel–concrete composite beam system, which is required to carry higher loads when applied in flooring systems with less self-weight and cost compared with conventional composite beams. This new composite member is prepared by filling a single cold-formed steel C-section with concrete material that has varied lightweight-recycled aggregates. In addition, varied stiffening scenarios are suggested to improve the composite behavior of this member, since these cold-formed C-sections are of a slender cross-section and more likely to buckle and twist under high bending loads than those of hot-rolled C-sections. The influence of using four different lightweight-recycled aggregates that combine together in the infill concrete material was investigated. These recycled aggregates are recycled concrete aggregate (RCA), expanded polystyrene (EPS) beads, crumb rubber aggregates (CRA) and fine glass aggregates (FGA). For this purpose, 14 samples of cold-formed galvanized steel C-purlin were filled with concrete material (containing 0 to 100% recycled aggregates) which are experimentally tested under pure bending load, and 1 additional sample was tested without the filling material. Further numerical models were prepared and analyzed using finite element analysis software to investigate the effects of additional parameters that were not experimentally examined. Generally, the results confirm that filling the C-sections with concrete material that contains varied percentages of recycled aggregates offer significantly improved the flexural stiffness, bending capacity, and ductility performances. For example, using infill concrete materials with 0% and 100% recycled aggregate replacement increased the bending capacity of hollow C-section by about 11.4 and 8.6 times, respectively. Furthermore, stiffening of the concrete-filled C-sections with steel strips or screw connectors eventually improved the composite behavior of the specimens which led to an increase in their bending capacities accordingly, and this improvement enhanced more with an increased number of these strips and connectors. In recent years, several comprehensive studies have investigated the performance of composite concrete-filled hollow steel tube members, and have reported significantly improved strength, stiffness, and ductility . For exaThe slender cross-section of steel tube members filled with concrete are usually lighter and cost less than those with non-compact and compact sections, and they are more favorable in construction projects. However, these slender tube sections are more likely to buckle under the compression stress that occurs due to bending load, such as with cold-formed steel tubes filled with normal and recycled concrete , or whenFurthermore, engineers have given significant attention to reducing the cost and self-weight of concrete-filled steel tube members by adding different types of waste materials such as recycled aggregates in concrete mixtures ,28,29,30Based on the above literature, the main aim of this research is to investigate the flexural performance of single C-sections filled with concrete materials. This new composite beam system is suggested to achieve a lighter weight and lower cost than the conventional composite beams system, which is required to be adopted into flooring systems since, to date, cold-formed C-sections are applicable for a roofing system to carry lighter loads compared to those applied on floors. Therefore, 15 specimens were prepared and tested under four-point bending. The specimens were categorized into four groups: Group 1, to study the flexural performances of a cold-formed C-section (C-purlin) filled with concrete material containing different percentages of combined recycled aggregates which are RCA, EPS, FGA, and CRA; Group 2, to investigate the influence of using multi-steel strips for restraining the top and bottom flanges together along the open side of the C-sections to improve the concrete’s confinement behavior; and Groups 3 and 4, to investigate the effects of providing connectors on the top-half of the C-section’s cross-section along varied span lengths. Furthermore, finite element (FE) models were built and analyzed to further investigate the flexural performance of the newly proposed steel C-sections filled with concrete material. The results obtained from the current experimental and numerical works are discussed.Fifteen (15) specimens were prepared in this research by filling single C-sections  with concrete material to investigate their flexural performance. In addition, to improve the behavior of the composite C-sections and core concrete, the top and bottom flanges were stiffened with steel strips by providing multi-screw connectors along the top-half of a C-section’s cross-section, as shown in 3 (replaced raw coarse aggregate), (b) RCA prepared from crushed old concrete elements with 5–19 mm particle sizes and overall density equal to 1278 kg/m3 (replaced raw coarse aggregate), (c) CRA prepared from crumb rubber with density equal to 600 kg/m3 and 2–5 mm particle sizes, and (d) FGA prepared from crushed waste glass material with density equal to 1570 kg/m3 and 1–5 mm particle sizes (both CRA and FGA replaced raw fine aggregate by volume). For each concrete mix designed in this research, 3 cubes (150 mm) were taken during the casting day which were cured and tested at 28 days, according to the standard of BS 1881:1983. cuf, and elastic modulus, cE) of each concrete mixture are shown in the same table.The C-sections used in this research were supplied from the same batch and had been previously tested by Al Zand et al. , with avThe specimens were tested under pure bending load (two-point load), as shown in In this section, we present and discuss the failure modes that were recorded from the experimental testing of the specimens of steel C-sections filled with concrete materials, where all specimens were tested beyond their ultimate capacities in order to further investigate extreme behavior. First, the hollow C-section showed twisting failure for the webs at the supports even before reaching its ultimate bending capacity, as shown in In general, the concrete-filled C-section specimens stiffened with multi steel strips  showed the same behavior as the unstiffened specimen (B-CM0), as shown in eL/300. Then, the load–deflection curves show elastic–plastic behavior up to 80–90% of the specimens’ loading capacities, where steel buckling starts to occur and the width of concrete cracking becomes wider, where after that the load–deflection curves show fully plastic behavior and reduces rapidly till the end of test.The flexural load vs. mid-span deflection relationships of the tested concrete-filled C-sections are shown in The load–deflection curve of concrete filled specimen B-CM0 showed much better stiffness and ductility behavior than that of the hollow specimen B-H, as shown in The load–deflection curves of the specimens stiffened with multi steel strips are stiffer than the control specimen (B-CM0), as shown in The relationships between the load and longitudinal strain of the steel C-sections at the mid-span of the tested specimens are presented in uP) and ultimate moment (uM) for the tested specimens are presented and compared in uP values than that of the control specimen filled with normal concrete. The 50% lightweight, recycled concrete aggregate mixture (B-CM50) achieved a uP value equal to 41.5 kN which was about −18.3% less than that of the B-CM0 specimen (50.8 kN), and then the loading capacity was further reduced, up to 38.3 kN (−24.7%), by using a higher replacement percentage of lightweight, recycled concrete aggregate mixture ; however, the loading capacity was still much higher than the uP value of the hollow specimen B-H . This performance was considered to be reasonable. Although the compressive strength of the concrete mixture was gradually reduced as the percentage of recycled aggregate increased, the recycled aggregate, when used as infill material in single C-sections, still had a significant influence, which was similar to that of double C-section [This section presents and discusses the achieved loading capacities  of the tested C-section specimens that were filled with varied contains of lightweight-recycled concrete materials aggregates, including those stiffened with steel strips and screw connectors. The ultimate load , and this was further improved to 65.5 kN (+28.9 %) when seven steel strips were used, as shown in uP values of specimens B-CM0-20SR and LB-CM0-20R  adopted in this experimental investigation improved the loading capacity of the single steel C-sections filled with concrete material. As highlighted earlier, tightening the top and bottom C-section’s flanges with multi steel strips achieved better concrete confinement behavior. For example, using three steel strips to stiffen the concrete-filled C-section achieved a u) to the deflection value at yielding limit (Δy) [This section presents the ductility index (DI) of the tested specimens. The DI performance of the newly suggested composite members is important to be understand in general. For flexural members, the DI is usually estimated using the ratio of the deflection value at ultimate limit (Δmit (Δy) ,51, as sThe performance of the steel C-sections filled with concrete material is further investigated in this section using a numerical method. The nonlinear finite element software, namely ABAQUS, was used for this purpose. In particular, the tested specimen B-CM0 was simulated, as shown in The components of the FE model are the same as the corresponding tested specimen B-CM0, which had infill concrete and steel C-section. These are equal to 40.1 MPa, 26.6 GPa, 489 MPa, 558 MPa, and 201 GPa of the average cubic concrete compressive strength, concrete elastic modulus, steel yield strength, steel ultimate strength, and steel elastic modulus, respectively. The solid element type C3D8R, available in the ABAQUS software’s library, was selected for the concrete elements, while the shell element type S4R was selected for the C-section elements . Based oThe results of the analyses using the currently developed FE model were verified with the corresponding tested specimen B-CM0, since the same boundary conditions and materials properties were considered. First, a convergence study was performed to select a sufficient mesh size for the elements of the suggested FE model, since increasing the number of elements may not be necessary to achieve accurate results, as shown in D/t values of 94, 75, 60, and 50, respectively. In addition, the C-sections with depths equal to 125, 150, 15, and 200 mm achieved L/D values of 10.8, 9.0, 7.7, and 6.7, respectively. Meanwhile, the rest of the physical properties of the infill concrete and steel C-section remained without change as described earlier in Further parameters were investigated after confirming the validity of the proposed FE model of the C-sections filled with concrete, for example, the effects of varied plate thickness and the depth of the C-sections were investigated. Specifically, C-sections with thicknesses of 1.6, 2.0, 2.5, and 3.0 mm were considered  which achieved D/t ratio occurred at an earlier deflection limit than those with lower ratios (see D/t = 94) achieved 51.2 kN, which occurred at a deflection limit equal to 10 mm, while the same model achieved a higher load capacity of 86.4 kN (+68.7% improvement) when the thickness was increased to 2.5 mm (D/t = 60), as shown in D/t ratio), see The flexural performance of the concrete-filled C-section models changed due to the effects of varied steel thicknesses; the flexural stiffness and strength were both significantly improved with an increase in C-section thickness, as shown in tios see a. For exL/D ratio of the concrete-filled single C-section model led to increases in flexural stiffness and strength accordingly, since reducing the L/D means reducing the slenderness ratio of the beam’s span and becoming closer to the non-compact and/or compact span’s limit [D/t equal to 9.0 (D = 150 mm) was significantly improved by about 22.4% (62.7 kN) when the D/t ratio was reduced to 7.7 (D =175 mm). In general, the loading capacity of models with higher L/D ratio occurred at lower deflection limits than the limit of L/50  models in this group.Furthermore, as shown in ’s limit . For exaL/50 see a. Figure➢The flexural loading capacity of the new composite member  is significantly increased, i.e., more than 8 times, even by using 100% lightweight-recycled aggregates in the concrete mixture, which are a combination of four different waste materials . This is due to the influence of infill concrete material that delayed the buckling/twisting failure of the hollow C-section.➢Unlike a double C-section fabricated with closed tube section that was tested by others, the newly tested single C-section cannot achieve high concrete confinement impact, due to how the top and bottom flanges in the single C-section still has one side open along its span. Thus, concrete cracking that usually occurs under two-point loads rapidly increases and the concrete leaks outside the tube section of single C-section at the high bending loads. However, this failure performance can be significantly improved by stiffening the concrete-filled single C-section with steel strips provided along the open side and/or by providing multi-screw connectors distributed equally along the span on the top-half of beam’s cross-section.➢It is worthwhile to note that using multi steel strips or screw connectors for stiffening the single C-sections filled with concrete incredibly increased the flexural loading capacity. For example, using seven steel strips to stiffen the open side of C-section or providing 20 multi-screw connectors on the top-half of a C-section’s cross-section increased the loading capacity about 28.9% and 13.4%, respectively as compared with the corresponding unstiffened specimens.➢Additionally, the ductility index of the suggested single cold-formed steel C-section beam filled with concrete materials was clearly improved once any of these stiffening scenarios (providing steel strips or screw connectors) was adopted, since bonding behavior between the core concrete and steel C-section parts was significantly enhanced.➢D/t and/or L/D ratios significantly improved the flexural capacity and behavior of C-sections filled with concrete material. For example, using single steel C-section filled with concrete with D/t equal to 75 (2.0 mm tube thickness) instead of 94 (1.6 mm tube thickness) led to an increase in the flexural loading capacity of about 36.1%.Lastly, the numerical model of the specimens of a single C-section filled with concrete material perfectly verified the actual flexural capacity and failure mode of the corresponding tested specimen. The results of the FE analysis confirmed that slightly reducing the In this study, the following conclusions have been established based on the results of the experimental and numerical investigation of concrete-filled C-sections under pure bending load:The conclusions of this investigation are limited to the size and material properties that were adopted in the current experimental and numerical research. Further investigations are required to adopt newly suggested composite members in future modern projects, including stiffening, strengthening, and connection concepts.


To the Editor—We read with interest the recent publication by Brenon et al regarding the overuse of broad-spectrum outpatient parenteral antibiotic therapy (OPAT). As noted by the authors, broad-spectrum antibiotics with once-daily dosing are often chosen for OPAT due to ease of administration despite options with a narrower-spectrum that may require multiple administrations daily. We applaud the authors for highlighting stewardship opportunities in OPAT, which is an underexplored field within antimicrobial stewardship (AMS) practice and research. Most intravenous (IV) antibiotic courses are completed in the outpatient setting, and AMS through OPAT programs is a significant and underserved need. Patient-specific factors, such as indication, allergies, organ function, previous drug intolerances, cost, risk of adverse events, and drug–drug interactions, play a large role. In addition to these factors, discharge location, ease of administration, caregiver or patient time and effort, and drug stability must also be considered before concluding that an OPAT regimen is a suboptimal choice.While spectrum of activity based on culture and susceptibilities is key in determining appropriate antibiotic therapy, considering OPAT regimen selection with a broader stewardship lens is likewise essential. conducted a survey to determine the rate of nonadherence with OPAT regimens and associated factors leading to nonadherence. The survey results revealed that 10% of patients were nonadherent due to younger age, household income <$20,000, or lack of time for administering IV antibiotics. Conversely, less frequent dosing and having the support of a friend or family member during IV antibiotic administration were associated with better adherence. Considering further how ease of administration affects adherence, a meta-analysis comparing compliance with once-, twice-, or thrice-daily administration showed that lower frequency dosing led to higher compliance rates regardless of the study design or treatment duration across 26 randomized controlled studies. Thus, it is essential to consider patient adherence along with the spectrum of activity, especially if “narrowing the spectrum” requires a patient to complete multiple IV antibiotic administrations daily. Hospital readmission and/or infection recurrence arising from nonadherence would incur significant costs and could result in compounding antimicrobial usage. Although converting standard bolus antimicrobials to continuous infusions via a continuous ambulatory delivery device (CADD) might appear to be a ready solution, certain antimicrobials (including ampicillin) cannot readily be given using this method due to drug stability. Also, insurance companies may deny CADD pump coverage. Furthermore, the potential for a patient to need placement in a skilled facility for an OPAT regimen to be administered (due to its frequency) warrants serious consideration in the COVID-19 pandemic era.Within the purview of AMS, one must consider whether the given regimen will be compatible with the patient’s life or whether the complexity of administration could lead to nonadherence. Hamad et al investigated whether inpatient antibiotic stewardship programs (ASPs) reduced infection rates of high-profile drug-resistant organisms. A key program component was restricting use of broad-spectrum antimicrobials, including ceftriaxone. With >765,000 hospitalization episodes included, these researchers detected an overall increase in vancomycin-resistant enterococcal infections after this intervention, and they detected no changes in the rates of extended-spectrum β-lactamase, carbapenem-resistant Enterobacteriaceae, or multidrug-resistant Pseudomonas aeruginosa infections after the intervention. Thus, Tartof et al concluded that ASPs with successful reductions in consumption of targeted antibiotics may not yield changes in antimicrobial resistance patterns in the 2 to 6 years after implementation.Although the threat of antimicrobial resistance is a major incentive to narrow antibiotic therapy, evidence regarding whether more narrow therapy leads to less drug resistance is controversial. A retrospective cohort study by Tartof et al classifies antibiotics based on activity against important pathogens. Similarly, a study by Peryrani et al used the antibiotic intensity score (AIS) calculated as the sum of the number of days of each antibiotic multiplied by the antibiotic spectrum. In their study, Brenon et al extrapolated National Healthcare Safety Network (NHSN) antibiotic use and resistance antimicrobial groupings, classifying agents as class 1 (broad-spectrum) to class 4 (narrow-spectrum). Notably, the adapted NHSN scoring method was not subject to validation. To illustrate the limitations in applying the score, ceftriaxone was deemed to be a “broader-spectrum” agent for gram-positive infections, but for certain gram-negative infections it may be carbapenem (ertapenem) sparing and thus a “narrowing” agent. These scenarios were not equally considered in the scoring system.While the impact of ease of administration on a patient’s life is tangible, the definition of a “broad-spectrum” or “broader-spectrum” antimicrobial is largely a subjective, conceptual matter. Various scoring systems have been developed to define antimicrobial spectrum usage. The antibiotic spectrum index (ASI) developed by Gerber et alTo consider a potential future direction, another AMS approach for OPAT includes IV-to-oral switch therapy (IVOST), which involves safely transitioning patients from IV to oral antibiotic regimens at the optimal time due to clinical improvement and meeting evidence-based and complex outpatient antimicrobial therapy (COpAT) criteria for serious infections. High-quality evidence for IVOST and COpAT is rapidly emerging and may hold the opportunity to avoid the disadvantages of OPAT: using intravenous access and its related complications, weekly or more frequent laboratory monitoring, and home healthcare or infusion center or facility admission requirements.We applaud Brenon et al for bringing attention to the AMS potential in OPAT. It is crucial to derive AMS interventions that are tailored to the broader OPAT context while allowing the patient to successfully complete their OPAT course, treat their infection, and not use additional healthcare resources.


Concrete production by replacing cement with green materials has been conducted in recent years considering the strategy of sustainable development. This study researched the topic of compressive strength regarding one type of green concrete containing blast furnace slag. Although some researchers have proposed using machine learning models to predict the compressive strength of concrete, few researchers have compared the prediction accuracy of different machine learning models on the compressive strength of concrete. Firstly, the hyperparameters of BP neural network (BPNN), support vector machine (SVM), decision tree (DT), random forest (RF), K-nearest neighbor algorithm (KNN), logistic regression (LR), and multiple linear regression (MLR) are tuned by the beetle antennae search algorithm (BAS). Then, the prediction effects of the above seven machine learning models on the compressive strength of concrete are evaluated and compared. The comparison results show that KNN has higher R values and lower RSME values both in the training set and test set; that is, KNN is the best model for predicting the compressive strength of concrete among the seven machine learning models mentioned above. Concrete is a common building material; it has been widely used in industrial and civil buildings and has become one of the world’s most widely used building materials because of its low price, excellent performance, simple production process, and other characteristics ,3,4,5,6.Blast furnace slag is a type of industrial waste slag discharged from the blast furnace when smelting pig iron, and it contains a large amount of active substances ,28,29,30Engineers usually use the laboratory test method to study the performance of concrete. However, the laboratory test method has many disadvantages, such as low efficiency and high cost ,41,42,43Strength is an important index to measure the quality of concrete with blast furnace slag. To ensure the quality of concrete, concrete must reach a certain strength, and the material composition of concrete determines its most critical mechanical index, which is compressive strength. To predict the compressive strength of concrete with blast furnace slag more efficiently and economically, firstly, this study uses the beetle antennae search algorithm (BAS) to adjust the hyperparameters of the BPNN, SVM, DT, RF, KNN, LR, and MLR, considering the simple implementation, fast convergence speed, and low possibility of falling into local optimization by changing the step size strategy . Then, cIn the past, many researchers often only focused on developing new prediction models of the performance of concrete, while ignoring the importance of a reliable database to verify the accuracy of the developed models. In this study, the data set on the compressive strength of concrete is collected from the published articles, and a reliable database is formed . Cement,To prevent the multicollinearity of machine learning models for predicting the compressive strength of concrete, it is necessary to analyze the correlation between input variables before the training of models. The correlation analysis results of cement, water, blast furnace slag, coarse aggregate, superplasticizer, and fine aggregate are shown in (1)Determine the direction of the initial value of each beetle. The direction of the initial value of the beetles is determined by the following formula:K is the spatial dimension.BAS is an efficient intelligent optimization algorithm. Compared with other optimization algorithms, this algorithm can optimize without knowing the specific function and gradient information. Therefore, this algorithm has the advantages of small computation and fast optimization speed. The idea of the BAS algorithm is to realize optimization by simulating the process of beetles looking for food. The BAS algorithm regards the fitness function value as the concentration of food odor, so the function has different function values in different positions. Beetles find the optimal value by comparing the odor concentration received by left and right antennae until they find the location of food; that is, the algorithm finds the optimal function value through multiple iterations and comparisons. The optimization steps of the BAS algorithm are as follows:(2)eta is the decreasing factor, t is the current number of iterations, and n is the total number of iterations.Set the step factor. The step size factor determines the searchability of beetles, so choosing a larger initial step size is helpful to improve the search range of beetles. The calculation formula of the step factor is as follows:t, and The position coordinates of the two whiskers of beetles are updated by the following formula:The fitness function  is expressed by the odor concentration of the left and right whiskers, and the solution formula is as follows ,72:(4)fiComparing the fitness values of the two tentacles, the beetle moves in the direction of a large fitness value, to update the position. The location update formula is as follows:Algorithm 1 The framework of BAS algorithmInput:Output:Optimal solution 1: Initial the initial position of the beetle 2: Initial a random orientation of the beetle 3: Initialization iteration number While Assuming that the size of the training set is N, m training sample sets with retrieval are taken from the training sample set, and m regression trees are constructed using the extracted training sample sets.(2)In the process of constructing a regression tree, no more than the total number of variables are randomly extracted from all independent variables at each node to branch, and each branch is scored to determine the optimal branch.(3)Each regression tree is branched from top to bottom, and parameters such as the number of RF subtrees, the depth of RF subtrees, the maximum number of subtrees, and the minimum number of subtrees are constantly adjusted during the branching process, to optimize the accuracy of the model.(4)Summarizing all the generated regression trees to form the RF model, the prediction effect of the model is determined by evaluating the determination coefficient and root mean square error of the test set. If the prediction effect of the model is not satisfactory, the parameters need to be adjusted continuously in the process of random forest modeling until the expected effect is achieved.RF is an algorithm that integrates multiple trees through the bagging idea of ensemble learning. RF summarizes the classification results of all decision trees on the training sample set by constructing a large number of decision trees. If the problem studied is a classification problem, the result is the prediction category of the classification tree; if the problem studied is a regression problem, the result is the average of all regression trees. Integrated learning is one of the most common machine learning ideas at present. The advantage of integrated learning is to integrate more models and effectively avoid the inherent defects of a single model or a group of models. RF is one of the typical ensemble learning algorithms. RF can solve the problems of low accuracy and over-fitting of a single decision tree by gathering multiple decision trees. The construction process of RF is as follows:The schematic diagram of random forest construction is shown in KNN is one of the most simple machine learning methods. The core idea of KNN is that if k nearest samples of a sample in space belong to the same category, the sample also belongs to this category. That is, the category of a given unknown sample can be determined according to the category of k samples closest to it. In simple terms, the KNN algorithm calculates the distance between the input unknown sample and all sample points and then takes the first K samples with the smallest distance for unified annotation. The graphic description of the KNN algorithm is shown in w is the model weight coefficient, Y is the output variable, b is bias, and LR is a generalized linear regression model with the advantages of strong plasticity, fast calculation speed, and strong generalization ability. The LR algorithm can not only predict the possibility of an event occurring under the action of a variety of different input variables but also analyze two opposing events. LR has many advantages over SVM, ANN, and other self-optimized training learning algorithms in the learning of model training set and the time required for model prediction. The binary classification problem is the most important application field of LR. LR only distinguishes class 0 and class 1 in the classification process of binary classification problems, and its probability distribution formula is as follows:In the case of multiple inputs, the weight vectors and input variables of the model need to be expanded. In this case, the mathematical expression of the LR algorithm is as follows:The regression function is obtained by unifying the above two expressions as follows:Regression analysis is a common statistical analysis method to deal with variable correlation. For the independent variables and dependent variables without a strict deterministic function relation quantity, regression analysis can also better determine the functional relationship between them. The conceptual diagram of the regression model is shown in y is the dependent variable, and Regression analysis problems can usually be divided into unary regression and multiple regression. In real life, a phenomenon is often associated with multiple factors, so it is necessary to generate an optimal combination of multiple independent variables to jointly predict the dependent variable. Therefore, the application scope of multiple linear regression is often wider than that of unary regression. The general form of multiple regression linear problems is as follows:In the actual problem, if there are m groups of data, the multiple linear regression model can be expressed as follows:The above formula can be written as a matrix:To optimize the hyperparameters of the BPNN, SVM, DT, RF, KNN, LR, and MLR models, the BAS algorithm is used in this study to optimize the hyperparameters of the above seven machine learning models, and the optimization results are shown in To further determine the optimal RSME values of the above seven machine learning models, this study further tuned the hyperparameters of the above models through 10-fold cross-validation. The results of the 10-fold cross-validation on the hyperparameter optimization of the above seven models are shown in The box diagram of the prediction error of concrete compressive strength by the BPNN, SVM, DT, RF, KNN, LR, and MLR models optimized by BAS is shown in To select the model with the best prediction effect for the compressive strength of concrete, this study further evaluated the prediction effect of the BPNN, SVM, DT, RF, KNN, LR, and MLR models tuned by BAS on the compressive strength of concrete. The comparison between the predicted values and actual values of the training set and test set of the seven models mentioned above is shown in To further analyze the prediction effect of the training set and test set of seven models on the compressive strength of concrete, a Monte Carlo simulation was conducted on the RSME values of the seven models in this study, and the simulation results are shown in Due to the complexity of the compressive strength of concrete, different admixtures have different effects on the compressive strength of concrete. The importance scores of different input variables to concrete compressive strength are shown in (1)The BAS algorithm showed a small amount of computation, very fast convergence, and global optimization ability in the machine learning model used to adjust and predict the mechanical properties of concrete. By comparison with varying machine learning models, the results showed that BAS has good hyperparameter tuning effects on BPNN, SVM, RF, and KNN models, but poor hyperparameter tuning effects on DT, LR, and MLR models.(2)Among the seven machine learning models, SVM, RF, and KNN have higher prediction accuracy for the compressive strength of concrete, while SVM has an over-fitting phenomenon for the prediction of the compressive strength of concrete. After further comparison, the KNN model is finally confirmed to be the model with the highest prediction accuracy  for the compressive strength of concrete.(3)Among all the design parameters of the concrete with blast furnace slag, the importance score of cement to the compressive strength of concrete is the highest, while the importance score of fine aggregate to the compressive strength of concrete is the lowest, and the importance values of the above five variables to the compressive strength of concrete are all positive. In other words, cement and fine aggregate have the greatest and least influence on the compressive strength of concrete among the five input variables mentioned above, and the compressive strength of concrete is proportional to any one of the five input variables in this study.Concrete is one of the most widely used building materials, and strength is an important index of its comprehensive performance; to ensure that the quality of concrete meets the requirements, concrete must reach a certain compressive strength. To enhance the compressive strength of concrete and ensure the sustainable development of the concrete industry, the use of mineral admixtures to replace part of the cement in concrete has attracted more and more researchers’ attention. In this study, the prediction effect of BPNN, SVM, DT, RF, KNN, LR, and MLR models tuned by BAS on the compressive strength of concrete containing blast furnace slag was studied, and the following conclusions were obtained:In future studies, more data can be collected to improve the reliability of the machine learning model, and the prediction model obtained should be applied to actual production practice, providing some guidance for industrial production. Moreover, the performance of the models optimized with the BAS algorithm can be compared with traditional methods to train each model to verify the effectiveness of hyperparameter tuning. The model combining the linear and nonlinear models using error series or residuals can be proposed in the future to improve the efficiency and reliability of computing.


The low tensile capacity of concrete often results in brittle failure without any warning. One way to cope with this issue is to add fibers and essentially improve the tensile strength (TS) behavior of concrete and offset its undesirable brittle failure. In recent investigations, basalt fibers (BFs), as compared to a variety of other kinds of fiber, have attracted the attention of researchers. In that respect, BFs exhibit several benefits, such as excellent elastic properties, great strength, high elastic modulus, higher thermal stability, and decent chemical stability. Although many researchers have reported that BFs can be embedded in concrete to improve the tensile capacity, a more profound understanding of its contribution is still needed. However, the information is scattered and it is difficult for the reader to identify the benefits of BFs. Therefore, a detailed assessment is essential to summarize all relevant information and provide an easy path for the reader. This review (part Ⅰ) summarizes all the relevant information, including flow properties, strength properties, and failure modes. Results reveal that BFs can greatly enhance the strength properties and change the brittle nature of concrete to one of ductility. However, it unfavorably impacts the flowability of concrete. Furthermore, the optimal proportion is shown to be important as a higher dose can adversely affect the strength of concrete, due to a deficiency of flowability. The typical range of the ideal incorporation of BFs varies from 0.5 to 1.5%. Finally, the review also indicates the research gap for future research studies that must be cautiously explored before being used in the real world. The most widely used building and construction material worldwide is concrete ,2,3. TheBy changing the traditional and energy-intensive techniques of using steel reinforcing bars and wire mesh with fibers, building costs may be reduced overall ,18,19. TThe drawbacks of steel fibers include reduced workability, and corrosion. Although the addition of glass fibers makes concrete more resilient, the alkali assault reduces concrete’s long-term strength. One disadvantage of the more rigid and powerful carbon fibers is their high price. The melting temperature and elastic modulus of nylon and polypropylene fibers are both low . In terms of strength, elasticity, and load transfer associated with surface adhesion qualities, the compatibility of the fiber and matrix has a major impact on the composite’s performance. In several fiber-reinforced composite applications, fibers made of steel, glass, carbon, and polymers are frequently employed. Polymer-based fibers can be used in a variety of ways, and their performance in composites varies greatly . Small rPolymer fibers provide a more desirable material since they are more resistant to alkaline reactions, corrosion, chlorine, and salt . Even atIn recent years, BFs with non-hazardous and ecologically friendly characteristics have been employed in concrete. These fibers are produced by melting volcanic rocks. BFs are produced using the same technology as glass fiber. However, it is less expensive since it doesn’t include any additives and uses less energy than glass or carbon fibers.In contrast to other materials such as fiberglass, BFs are manufactured entirely from basalt rock from a carefully selected excavation supply. All that is done is to wash and melt the basalt. It takes melting the mined basalt rock at a temperature of around 1400 °C to produce BFs. A continuous thread of BFs is created by extruding the molten basalt rock via tiny nozzles called spinnerets. The production of BFs is seen in According to A brand new type of high-performance, environmentally beneficial, and eco-friendly fiber known as BFs performs very well and is employed extensively across a variety of industries . The purAccording to research, BFs may greatly increase the hardness and fracture resistance of concrete and have high alkali resistance . The impAlthough many researchers reported that BFs can be used in concrete to enhance the tensile strain, the information is scattered and it is difficult for a reader to identify the benefits of BFs in concrete. Therefore, a detailed review is required to summarize all the relevant information and provide an easy path for the reader. This review summarized all the relevant information including fresh properties, strength properties, and failure modes. Results suggest that BFs enhanced the strength properties as did the other fibers. In addition, the failure mode of BFs reinforced concrete is ductile which ensures the safety of a structural member by allowing deformation before failure. However, it unfavorably impacts the flow of concrete. Furthermore, the optimum dose is important as the greater quantity unfavorably impacts the strength properties of concrete due to a deficiency of flowability. The typical range of the ideal amount of BFs fluctuates from 0.5 to 1.5%. Finally, the analysis also indicates s research gap for potential research that must be explored before being used practically. 3, with the lengths being 10 mm, 20 mm, and 30 mm. BFs absorb some water, reducing workability and droop. In addition, research [research  investigresearch , fresh cIt was discovered that when the fiber proportion was raised, the slump values of concrete mixtures decreased. When fibers are added at volume fractions of 0.5, 1.0, 1.5, and 2.0 percent, the slump value is reduced to 70 mm, 65 mm, 60 mm, and 55 mm, respectively, from 80 mm for the control mix (BFs 0.0). It may be concluded that fibers added to the concrete mix may be to blame for the decline in workability. The viscosity of concrete may rise as a result of the fiber’s greater surface area needing to absorb much more cement paste . ConcretAccording to research , the fibThere are three different forms of air voids: closed air voids, semi-connected air voids, and linked air voids. According to As a monitoring approach for the volume of the mix, and the air content values, the unit weight of the mixture was used. The air content of the blend, which also impacts the drop of the mix, had an impact on unit weight. The research predicts that when the slump decreases, the air content often rises, which should lower the unit weight value.According to research, the amount of air in a concrete mixture reduced as the quantity of steel fiber in the mixture was boosted, and adding 3 percent of steel fiber resulted in a reduction of entrapped air of between 0.9 percent and 2.4 percent for various water-to-binder ratios. As a result, the effective distribution of short fibers when a greater dose of superplasticizer was applied may explain the lowering impact of entrapped air content in concrete mixes. Other probable factors should be researched in the future . The triThe BFs are added to the concrete in volume fractions of 0.5, 1, 1.5, 2, 2.5, and 3 percent for M-30 grade concrete, which results in seven-day CS that are almost 55 to 64 percent higher than 28-day CS for BFs content of 0 to 3 percent. The CS of ordinary concrete rose by 4.72 percent when BFs were added at a rate of 0.5 percent. The CS rises to 11.45% as compared to reference concrete when BFs are raised to 1%. Because the BFs occupied the concrete pores in a variety of orientations, the strength-improving feature was induced. When BFs concentration is raised further, such as by 1.5 percent, CS decreases to 8.2 percent but increases to 3.45 percent when compared to normal concrete. When BFs concentration exceeds 1.5 percent, the CS gradually decreases, by 16.48 percent, 25.26 percent, and 33.87 percent for BFs contents of 2%, 2.5 percent, and 3%, respectively. This might be the result of the fiber content bunching, problems with compaction, or a lack of bonding between the fibers and concrete elements .According to research , the RCAAccording to research, adding BFs at 0.5 percent resulted in a 3.9 percent decrease in CS after 28 days . There wAn adequate quantity of BFs may be included to increase the CS at various ages, according to research . The CS The compression test failure mode for cubes is shown in A study was conducted by a researcher to investigate the effects on the properties and strength of concrete caused by the addition of BFs of varying lengths. The author carried out research on the effect that employing different BFs lengths of 10, 20, and 30 mm had on the TS of concrete, and he published his findings. According to the findings, the BFs with a diameter of 30 mm have the potential to provide the greatest TS . HoweverWhen compared to plain concrete, the TS of concrete seems to improve with an increase in fiber percentage. This contrasts with the plain concrete. The splitting TS shown by the BF concrete is much greater than that of the concrete reinforced with polypropylene fibers. The TS of concrete reinforced with BFs of12 mm improves by about 14.08–24.34 percent when the fiber content of the concrete is increased. In addition, an increase of around 14.96–25.51 percent may be seen in the splitting TS of BFs (22 mm) reinforced concrete . The TS of high-performance concrete (HPC) reinforced with single BFs increased by 21.90 percent –38.33 percent when compared to the TS of HPC without fiber. Meanwhile, the TS of HPC reinforced with single polypropylene fibers increased by 32.86 percent–44.52 percent. The findings indicate that the incorporation of BFs or polypropylene fiber into concrete results in the formation of a three-dimensional chaotic distribution within the material. This, in turn, can delay the onset of cracking and lead to an increase in the splitting TS of high-performance concrete (HPC). According to the results of the correlation research, polypropylene fibers that have a low elastic modulus have a significant impact on the splitting TS of HPC .According to the findings of the research, the incorporation of polypropylene fiber and carbon fiber into concrete at a volume fraction of 0.5 percent may enhance the splitting TS of the material by 19.5 and 31.6 percent, respectively, after 28 days. This is primarily due to the bridging action of the three oriented dispersed fibers across fractures, which is what successfully restrains the proliferation of micro-cracks in the initial stage. After the specimens have been flexurally cracked, the stress is then transmitted to the bridging fibers. As a result, the formation of macro cracks is slowed down, and the splitting TS is increased .The early splitting TS of concrete is not greatly affected by BFs, however, the later splitting TS is significantly affected. At 28 days, concrete with a 0.05 percent fiber content had the maximum splitting TS (3.74 MPa), 1.36 percent greater than control concrete. The splitting TS of the concrete diminishes as the fiber content rises and falls below that of the control concrete. The splitting TS at 90 days increased by 4.41 percent to 9.35 percent with the addition of 0.05 percent to 0.15 percent BFs to concrete. However, the addition of 0.2 percent BFs reduces the splitting TS by 1.29 percent. The tensile stress of concrete is mostly supported by concrete prior to fracture. Tensile stress is transferred from the matrix to the BFs between cracks once the matrix has cracked. The splitting TS of concrete is enhanced by the redistribution of an internal force, which also decreases the stress concentration factor at the concrete’s microcracks, increases the concrete’s ultimate tensile strain, and prevents crack development and expansion. The overall surface area of the fiber rises, nevertheless, when the fiber content is quite high, necessitating the use of a lot of cement paste. As a result, the binding between the cement paste and the aggregate and the splitting TS are adversely affected .The TS of concrete combined with BFs of 12 mm, 24 mm, and 50 mm in length was examined. The results showed that using 12 mm BFs with a content of 1–2% allowed for the best possible TS of concrete. In addition, BFs reinforced concrete with a content of 1–3 percent has a length of 24 mm and a length of 50 mm, and its TS is significantly boosted by 1.80 times. Although most fiber lengths have excellent TS, there is no difference between employing fiber lengths of 24 mm and 50 mm . The splThroughout the first part of the test, the load continuously increased as the displacement increased. The rising amplitude of the load value showed no evident change when the deformation approached the ultimate displacement. As seen in The best use of the fibers’ bridging function is to stop or slow the spread of fractures in composite materials. Concrete cracking is a multiscale phenomenon that is first manifested as a small microcrack and ultimately grows to a significant macrocrack. According to one study , the preIn comparison to the control mixture, the flexural strengths of the mixes were significantly boosted by the inclusion of BFs. With varying fiber lengths, there was no discernible difference in the seven-day flexural strengths. These findings suggested that BFs efficiently bonded to the cement matrix regardless of fiber length. Additionally, BF-reinforced composites had a greater increase in FS than glass fiber-reinforced composites when compared to plain mortar. In fact, it was discovered that BF composites (20 mm length) with 0.5 and 1 percent fiber had flexural strengths that were 19 and 16 percent greater than those of fiber mixes (20 mm length) with the same fiber content. In applications requiring reinforcement, BFs seem to be more advantageous than glass fiber. Furthermore, it is evident from comparing the flexural data that the peak load of BF composites occurred at a much greater deflection compared to that of glass fiber composites. This is explained by the fact that BFs have more TS and elongation than glass fibers .Increases in the volume percentage of BFs make the gain in FS more noticeable. As opposed to fiber-reinforced concrete with a fiber volume fraction of 0.3 percent, however, FS shows a modest decrease at 0.5 percent. This might be because high-volume fiber dispersion with a 0.5 percent fraction has proved challenging. It follows that 0.3 percent of the total volume of concrete is the appropriate amount of BFs to admix. Furthermore, FRC with 22 mm BFs has greater FS than fiber-reinforced concrete with 12 mm BFs. The anchoring and bridging effects are greater in longer fibers. In addition, the connection between the fiber and the concrete matrix strengthens, which will aid in the growth of flexural strength. Additionally, it has been shown that plain concrete exhibits brittle behavior. The specimen of plain concrete will split in two when subjected to flexural pressure after a bending fracture appears. However, the fiber actually slows down the crack’s spread, improving the specimen’s mechanical behavior and toughness .The flexure and serviceability behavior of concrete reinforced with ribbed basalt rebars were described by research. Rebars with diameters 8, 12, and 16 mm were used. The four-point bending test was used to evaluate the beams. Due to the axial stiffness of the flexural reinforcement being comparable to that of other bars, rebar with smaller diameters had better bonding with the concrete with respect to bar diameter and spacing. As a result, its behavior was determined to be better under cracking . AccordiThe poor post-crack performance of BFs was not unexpected considering the absence of discernible fibers in the cracked cross-section, as illustrated in In contrast, basalt FRC prisms demonstrated ductile failure upon crack development, as seen in In contrast, an experiment using different ratios of 0.1–0.3% BFs was claimed to considerably boost the MOE. It was discovered that fibers addition 23% increase elastic modulus of concrete compared to the reference concrete . The effThe ductility index is crucial to the safety of concrete buildings because it measures the energy consumption and deformation capability of concrete when its matrix splits. The ductility index of BF-reinforced concrete rises by a factor of 24 as indicated in Ordinary concrete cracks when subjected to impact loads, while BF-reinforced concrete is slightly fractured but not broken, demonstrating an adequate level of durability. Concrete deterioration is a process in which fractures progressively widen and grow. The fiber number per unit volume in concrete is high after the addition of fiber, which is fine and greater than the surface area, and a homogeneous network system with a three-dimensional disorderly distribution of fiber is produced. This method efficiently slows down the crack’s quick growth and effectively minimizes the damage to the concrete by absorbing kinetic energy while the concrete is being struck. This system does this by reducing the stress concentration of the fracture tip within the concrete. Therefore, an increase in toughness under impact loads is the most important effect of BFs on the concrete matrix.According to Manibalan and Baskar , the eneThe fracture extension in the BF-reinforced concrete is delayed by the bridging action in the crack between the fibers, which starts after the cracks develop. In comparison to the standard concrete test blocks, the BFs, which are removed to use a particular amount of energy, result in various alterations in the form of destruction. After cleft, the failure pattern of BF-reinforced concrete is destroyed without pieces. Only many fractures and molting are visible, while the original concrete’s integrity is still intact. As a result, the mixed fiber transforms the brittle failure pattern of concrete into a ductile failure pattern. The impacting behavior and damage progression of BF-reinforced concrete were presented in According to research , adding According to research, regardless of testing age, it is clear from comparing the toughness data that both peak load toughness and toughness at deflection of 2.5 mm rose exponentially as BFs content climbed from 0 to 1.5 percent. To be more specific, adding 0.5 percent, 1 percent, and 1.5 percent BFs to plain mortar increased its 28-day toughness at a deflection of 2.5 mm by 4, 13, and 33 times, respectively (0.176 KN.mm) . As prevA comprehensive summary and analysis of recent research that is relevant to the mechanical characteristics and failure mechanisms of basalt-fiber-reinforced concrete is given in this paper. The following findings are reached, in consideration of the in-depth discussions presented above.The flowability of concrete declined with the addition of BFs due to the increased surface area, which required more water and pastes for lubrication. With the inclusion of BFs, a decrease in unit weight and an increase in air content were also seen. As with other forms of fiber, the inclusion of BFs boosted the strength qualities of concrete up to a certain level. However, the ideal BF concentrations are crucial since a greater dosage has a negative impact on strength qualities. Nevertheless, based on factors such as mix design and fiber length, many studies suggest varying ideal BF percentages. However, the normal range of ideal BF percentages is from 0.5 to 1.5 percent. In addition, it can be shown that BFs have a less increased compressive capacity than flexural or tensile capacity. The inclusion of BFs also transforms the brittle character of concrete into a ductile failure, which ensures safety by delivering deformation (warning) prior to failure, according to research on failure modes.Research suggests that BFs have not significantly increased the compressive strength of concrete. To enhance the compressive capacity of basalt-fiber-reinforced concrete, further research adding pozzolanic materials to basalt-fiber-reinforced concrete is required. The data on MOE of concrete with the addition of BFs is unclear since some publications claimed that BFs have no effect on MOE while others claimed that MOE has significantly improved. Consequently, a detailed assessment is needed in this area. Due to a lack of flowability, greater dosages of BFs result in lower strength properties. This study, therefore, recommends a thorough examination of various doses of plasticizers at a higher dosage of BFs. Finally, this study compiles data on the fresh characteristics, strengths, and failure mechanisms of basalt-fiber-reinforced concrete. The review also recommends a compressive review of durability aspects, thermal properties, and microstructure analysis of basalt-fiber-reinforced concrete.