Multiple sequence alignments and phylogenetic trees are rich in biological information and are fundamental to research in biology. PhyKIT is a tool for processing and analyzing the information content of multiple sequence alignments and phylogenetic trees. Here, we describe how to use PhyKIT for diverse analyses, including (i) constructing a phylogenomic supermatrix, (ii) detecting errors in orthology inference, (iii) quantifying biases in phylogenomic data sets, (iv) identifying radiation events or lack of resolution using gene support frequencies, and (v) conducting evolution-based screens to facilitate gene function prediction. Several PhyKIT functions that streamline multiple sequence alignment and phylogenetic processing—such as renaming FASTA entries or tree tips—are also discussed. These protocols demonstrate how simple command-line operations in the unified framework of PhyKIT facilitate diverse phylogenomic data analysis and processing, from supermatrix construction and diagnosis to gene function prediction.

This paper proposed emotion recognition methods for consecutive facial images, and implements the inference of neural network model on a field-programmable gate array (FPGA). The proposed emotion recognition methods are based on a neural network model architecture that combines convolution neural networks (CNNs), long short-term memory (LSTM), and fully connected neural networks (FCNNs), called CLDNN or ConvLSTM-FCN. This type of neural network mod-el can analyze the local feature sequences obtained through convolution of data, making it suita-ble for processing time-series data such as consecutive facial images. In this paper, sequences of facial images are sampled from videos corresponding to various emotional state of subjects. The sampled images are then pre-processed with the processes includes facial detection, greyscale conversion, resize, and data augmentation if necessary. The 2-D CNN in ConvLSTM-FCN is used for feature extraction for these pre-processed facial images. These sequences of facial im-age features are time sequences with dependent properties between the elements within them. The LSTM is then used to model these time sequences followed by fully connected neural net-works (FCNNs) for classification. The proposed consecutive facial emotion recognition method achieves an average recognition rate of 99.51% on RAVDESS dataset, 87.80% on BAUM-1s dataset and 96.82% on eNTERFACE’05 data set, using 10-fold cross-validation on the PC. Some com-parisons of recognition accuracies between the proposed method and the other existing related works are conducted in this paper. According to the comparisons, the proposed emotion recog-nition methods outperform the existing related researches. The proposed emotion recognition methods are then implemented on an FPGA chip using the neural network model inference algo-rithms in this paper, and the accuracies of the experiments conducted on the FPGA chip are iden-tical to those obtained on the PC. This verifies that the proposed neural network model imple-mented on the FPGA chip performs well.

This paper introduces a novel architecture—bidirectional optical neural network (BONN)—for providing backward connections alongside forward connections in artificial neural networks (ANNs). BONN incorporates laser diodes and photodiodes and exploits the properties of Köhler illumination to establish optical channels for backward directions. Thus, it has bidirectional functionality that is crucial for algorithms such as the backpropagation algorithm. BONN has a scaling limit of 96 × 96 for input and output arrays, and a throughput of 8.5 × 1015 MAC/s. While BONN's throughput may rise with additional layers for continuous input, limitations emerge in the backpropagation algorithm as its throughput doesn't scale with layer count. Successful BONN-based implementation of the backpropagation algorithm requires the development of fast spatial light modulator to accommodate frequent data flow changes. A two-mirror-like BONN and its cascaded extension are alternatives for multilayer emulation, and they help save hardware space and increase the parallel throughput for inference. An investigation into the application of the clustering technique to BONN revealed its potential to help overcome scaling limits and to provide full interconnections for backward directions between doubled input and output ports. BONN's bidirectional nature holds promise for enhancing supervised learning in ANNs and increasing hardware compactness.

Abstract: Development of the fast neutron radiography with higher penetration capability in Non-Destructive Testing (NDT) techniques is rapidly. The detection efficiency and the imaging spatial resolution are the main problem of the radiography detector for many fast neutron imaging systems. In this paper, a detector composed of pixelated EJ200 scintillator array，an 16 × 16 silicon-photomultipliers (SiPM) array, and a capacitive multiplexing network readout electronics is designed. Using Monte-Carlo simulations，the main parameters of the detector was optimization. Then the detector prototype was fabricated and tested at a 14 MeV D-T neutron source. The preliminary test results showed that the prototype has spatial resolution of 1.26 mm. Using pixelated scintillator structure，the conflict between spatial resolution and detect efficiency could improved. Moreover, SiPMs offer a flexibility for the expansion of application field of the imaging system due to their excellent photon detection performance, relatively low price and joint possibility for large area.

This paper introduces a rigorous and comprehensive approach for the assessment of marine shafting systems through the utilization of an advanced Pi-Theorem based scaling methodology. Integrating journal bearing similarity assessment and shaft-line scaling methodology with advanced dimensional analysis, the study aims to provide a methodology foundation for systematic replication and analysis of marine shafting systems through scaled models. The proposed scaling methodology ensures geometric and mechanical similarity in terms of shaft-line deflection, considering key scaling parameters such as shaft length, diameter, weight, loads, rotational speed, material properties, bearing locations, and offsets. The advanced dimensional analysis computes specific non-dimensional ratios to guarantee a close resemblance between a real-size system and a scaled lab model, enabling meaningful experimentation. The methodology is analytically derived and validated with numerical simulations for a case study, conducting comparative analysis, evaluating discrepancies, and utilizing the integrated framework for experimentation.

HIV-associated neurocognitive disorders (HAND) persist under antiretroviral therapy as a complex pathology that has been difficult to study in cellular and animal models. Therefore, we generated an ex vivo human brain slice model of HIV-1 infection from surgically resected adult brain tissue. Brain slice cultures processed for flow cytometry showed >90% viability of dissoci-ated cells within the first three weeks in vitro, with parallel detection of astrocyte, myeloid, and neuronal populations. Neurons within brain slices showed stable dendritic spine density and mature spine morphologies in the first weeks in culture, and they generated detectable activity in multi-electrode arrays. We infected cultured brain slices using patient-matched CD4+ T-cells or monocyte-derived macrophages (MDMs) that were exposed to a GFP-expressing R5-tropic HIV-1 in vitro. Infected slice cultures expressed viral RNA and developed a spreading infection up to 9-days post-infection, which were significantly decreased by antiretrovirals. We also detected infected myeloid cells and astrocytes within slices and observed minimal effect on cellular via-bility over time. Overall, this human-centered model offers a promising resource to study the cel-lular mechanisms contributing to HAND (including antiretroviral toxicity, substance use, and aging), infection of resident brain cells, and new neuroprotective therapeutics.

Global navigation satellite system (GNSS) array antenna receivers are widely used to suppress wideband interference in navigation countermeasures. However, existing array antenna receivers all adopt digital array structure and digital beamforming technique, and it has limited analog-front-end (AFE) dynamic range. In strong interference scenarios, AFE saturation will occur, which limits the maximum interference suppression ability of the array receiver. Aiming at this issue, this paper proposes a robust wideband interference suppression method for GNSS array antenna receivers based on hybrid beamforming technique. Firstly, a novel fully connected hybrid array receiver structure is proposed; Secondly, the corresponding hybrid beamforming method is proposed at the same time, and it realizes the complete elimination of strong interference by jointly suppression in analog domain and digital domain. After mathematical simulation experiments, it is verified that compared to the digital beamforming-based anti-jamming technique, the proposed method can effectively suppress strong wideband interference, and the maximum interference suppression ability is improved by 36 dB.

The article presents an innovative method for synthesizing radiation patterns efficiently by 1 combining the Taguchi method and neural networks, while validating the results on a 10-element 2 antenna array. The Taguchi method aims to minimize product and process variability, while neural 3 networks are used to model the relationship between antenna design parameters and radiation 4 pattern characteristics. This approach utilizes Taguchi parameters as inputs for the neural network, 5 which is then trained on a dataset generated by the Taguchi method. After training, the network is 6 validated using a real 10-element antenna array. Analytical results demonstrate that this method 7 enables efficient synthesis of radiation patterns with a significant reduction in computation time 8 compared to traditional approaches. Furthermore, validation on the antenna array confirms the 9 accuracy and robustness of the approach, showing a high correlation between predicted performances 10 by the neural network model and actual measurements on the antenna array.In summary, our article 11 highlights that the combined use of the Taguchi method and neural networks, with validation on a 12 real antenna array, offers a promising approach for efficient synthesis of antenna radiation patterns. 13 This approach combines speed, accuracy, and reliability in antenna system design.

In reinforced concrete (RC) structures, splicing is required owing to the length limitations of rebars, insufficient lengths, and transportation issues. In particular, splices connect the rebar of RC structures such as walls, columns, beams, slabs, and joints. Lap splices are the most commonly used method worldwide because they do not require specific equipment or skilled workers. However, lap splices incur high construction costs because of the long splice lengths required for large-diameter rebars in megastructures, as well as issues pertaining to material supply, labor costs, constructability, and project duration. Additionally, approximately 15% more rebar is required because of the overlap. Energy saving for a sustainable built environment is possible if the disadvantage of lap splices, which generate high CO2 emissions due to the excessive use of rebar, are resolved. Hence, mechanical rebar couplers (MRCs) have been developed. However, despite their advantages, they have not been widely applied in construction sites owing to concerns regarding safety, quality, and constructability. Although various MRCs have been developed, most studies focus only on their structural performance. Therefore, a data-driven approach for selecting MRCs based on the reinforcing bar shape and structural characteristics is proposed in this study. Using a data-driven MRC selection algorithm, using the T-threaded coupler for one rebar over two floors resulted in 56% more efficient labor productivity, 15% shorter assembly time, 17% lower costs, and 26% lower CO2 emission. Using a developed algorithm, the appropriate MRC can easily and rapidly be selected for frequent design changes.

The penetrability and directivity of ultrasound in different media is of interest in engineering and medical applications (imaging, nondestructive testing, sonochemistry, among others). The nonlinearity of a liquid can be used in the parametric antenna framework to generate low-frequency components with particular features from several ultrasonic signals at the source. Bubbly liquids are dispersive liquids in which a small amount of tiny gas bubbles leads to the increase of the nonlinear parameter of the media over certain frequency ranges. Parametric antenna applied to this huge nonlinear media gives rise to low-frequency components with relatively small intensity at the source. The evolution of a low-frequency component (difference-frequency component obtained from two primary signals) during its propagation in a bubbly liquid is somehow unknown. It is thus interesting to analyse its characteristics to establish whether this component can benefit from the quality of its own frequency and from the primary frequencies in terms of directivity and penetrability into the medium. It must be noted that no such study in bubbly liquids exists in the litterature, but only for homogeneous media. To this end, several numerical models developed previously are used here to analyse the difference-frequency component obtained from a parametric antenna emitting from two ultrasonic signals at the source in one and two-dimensional domains. These models allow us to observe the behavior of this frequency component. An angle that measures the directivity of a beam is also defined. Our results show a point hardly found in the literature: the high directivity and the huge penetrability of the secondary beam associated to the difference-frequency component into the bubbly liquid, compared to the same frequency signal excited directly from the source in the bubbly liquid and to the parametric acoustic array in homogeneous fluids.

Wavelength selective switches (WSSs) are essential elements for wavelength division multiplexing (WDM) optical networks, as they offer cost-effective, high port-count and flexible spectral channel switching. This work proposes a new hybrid WSS architecture that leverages the beam shaping and steering features of uniform silicon nitride (SiN) based end-fire optical phased arrays (OPAs). By introducing beamforming to a WSS system, the spectral channels on the liquid crystal on silicon (LCoS) panel can be tailored and arranged properly, depending on the optical configuration, using the beam control capabilities of OPAs. Combining 3D-FDTD and ray tracing simulations, the study shows that by reducing the input beam dimensions with proper sizing of the OPAs, the WSS design with the null-steering OPAs layout and 4×No switch size features increased spectral resolution. This extensive beamforming study on the steering-enabled layout reveals the acquirement of an even higher input channel number, achieving up to the 8×No WSS scheme with flexible channel routing on the LCoS panel. Such implementation of beamsteerers can unlock an extra degree of freedom for the switching capabilities of hybrid WSS devices. The results show great promise for the introduction of OPAs in WSS systems and provide valuable insight for the design of future wireless communication links and WDM systems.

The independence of commercial law and the independence of commercial trial are the key issues in the development of China's market economy, which is of great significance for maintaining the market order and protecting the rights and interests of consumers. With the development of China's market economy, the independence of commercial law and commercial trial has gradually become the focus of social attention. On the one hand, the independence of commercial law refers to the effective distinction between commercial law as a normative system and other laws, which has an independent social and economic basis and a unique role. On the other hand, the independence of commercial trial means that commercial trial has relatively independent space and procedures, which can effectively guarantee the fair settlement of commercial disputes.The independence of commercial law is reflected in many aspects, including commercial law ontology, normative structure and content, external relations and so on. Commercial law has the independent social and economic foundation and the unique role, and is the foundation of the development of market economy. The basic principles, adjustment objects, and system design of commercial law are independent, which makes commercial law play its unique role in social life. There are differences between commercial laws and other laws, such as civil law and economic law, in essence and in expression form, which makes commercial law irreplaceable.

Understanding the factors which control endothelial cell (EC) function and angiogenesis is crucial for developing the horse as a disease model, but equine ECs remain poorly studied. In this study we have optimised methods for the isolation and culture of equine aortic endothelial cells (EA-oECs) and characterised their angiogenic functions in vitro. Mechanical dissociation, followed by magnetic purification using an anti-VE-cadherin antibody, resulted in EC-enriched cultures suitable for further study. Fibroblast growth factor 2 (FGF2) increased EAoEC proliferation rate and stimulated scratch wound closure and tube formation by EAoECs on extracellular matrix. Pharmacological inhibitors of FGFR1 (SU5402) or MEK (PD184352) blocked FGF2-induced ERK1/2 phosphorylation and functional responses, suggesting that these are dependent on FGFR1/MEK-ERK signalling. In marked contrast, VEGF-A had no effect on EAoEC proliferation, migration or tubulogenesis and did not promote ERK1/2 phosphorylation, indicating a lack of sensitivity to this classical pro-angiogenic growth factor. Gene expression analysis showed that, unlike human ECs, FGFR1 is expressed by EAoECs at a much higher level than both VEGFR1 and VEGFR2. These results suggest a predominant role for FGF2 versus VEGF-A in controlling the angiogenic functions of equine ECs. Collectively, our novel data provide a sound basis for stud-ying angiogenic processes in the horse and lay the foundations for comparative studies of EC biology in horses versus humans.

Bacteriophages (phages) are potential alternatives to chemical antimicrobials against pathogens of public health significance. Understanding the diversity and host specificity of phages is important for developing effective phage biocontrol approaches. Here, we assessed the host range, morphology, and genetic diversity of eight Salmonella enterica phages isolated from a wastewater treatment plant. The host range analysis revealed that six out of eight phages lysed more than 81% of the 43 Salmonella enterica isolates tested. The genomic sequences of all phages were determined. Whole genome sequencing data (WGS) data revealed that phage genome sizes ranged from 41 to 114 kb with GC contents be-tween 39.9 and 50.0 %. Two of the phages SB13 and SB28 represent new species Epsep-timavirus SB13 and genera Macdonaldcampvirus, respectively as designated by the In-ternational Committee for the Taxonomy of Viruses (ICTV) as per genome based taxonomic classification. One phage (SB18) belonged to the Myoviridae morphotype while the re-maining phages belonged to the Siphoviridae morphotype. The gene content analyses showed that none of the phages possessed virulence, toxin, antibiotic resistance, type I-VI toxin-antitoxin modules or lysogeny genes. Three (SB3, SB15 and SB18) out of the eight phages possessed tailspike proteins. Whole genome-based phylogeny of the eight phages with their 113 homologs revealed three clusters A, B, C and seven subclusters (A1, A2, A3, B1, B2, C1 and C2). While cluster C1 phages were predominantly isolated from animal sources, cluster B contained phages from both wastewater and animal sources. The broad host range of these phages highlights their potential use to control the presence of S. enterica in foods.

Nowadays, unmanned vehicles are widely used in various fields. However, the safety of unmanned vehicles is directly determined by the autopilot systems, and sensor faults are a very critical factor that affects the normal operation of the autopilot systems. To efficiently and comprehensively test unmanned systems for sensor faults, this paper proposes a chip-level testing platform for unmanned vehicle autopilot systems based on FPGA hardware-in-the-loop simulation. Unlike existing testing platforms, the introduction of FPGA technology allows us to achieve nanosecond real-time simulation frequency, thus realizing chip-level simulation of sensors and black-box automated testing. Firstly, we propose a set of general platform and modeling methods, and the paper presents a detailed application of the four most common necessary sensors in autopilot systems as examples. Secondly, we propose for the first time a chip-level fault testing method for unmanned systems, and build a test platform with a quadrotor vehicle, the PX4 software platform, and the Pixhawk4 hardware platform as examples. Finally, the experimental results verify that the testing platform proposed in this paper can adapt to various autopilot systems and has high simulation test reliability.

Focused microwave breast hyperthermia (FMBH) employs a phased antenna array to perform beamforming that can focus microwave energy at targeted breast tumors. Selective heating of the tumor endows the hyperthermia treatment with high accuracy and low side effects. The effect of FMBH is highly dependent on the applied phased antenna array. This work investigates the effect of polarizations of antenna elements on the microwave focusing results by simulations. We explore two kinds of antenna arrays with the same number of elements using different digital realistic human breast phantoms. The first array has all the elements’ polarization in the vertical plane of the breast while the second array has half elements’ polarization in the vertical plane and the other half in the transverse plane, i.e., cross polarization. In total 96 sets of different simulations are performed, and the results show that the second array leads to a better focusing effect in dense breasts than the first array. This work is very meaningful for the potential improvement of the antenna array for FMBH, which is of great significance for the future clinical applications of FMBH. The antenna array with cross polarization can also be applied in micro-wave imaging and sensing for biomedical applications.

Simple Summary: The distribution of typical bacterial redox enzymes such as pyruvate-ferredoxin oxidoreductase (PFOR) in protozoa remains interestingly puzzling. Previous studies have demonstrated diverse cellular localizations of PFOR in some amitochondriate anaerobic protozoa. PFOR is of particular pharmacological importance because it catalyzes the reductive bio-activation of nitro-based prodrugs to cytotoxic radical metabolites. Metronidazole was developed primarily as an antiprotozoal agent against infections caused by Trichomonas vaginalis. However, its antimicrobial spectrum was subsequently expanded to cover anaerobic bacterial infections. It has been shown that mutations in the genes encoding PFOR result in inherent resistance of PFOR-possessing anaerobic protozoa and bacteria to nitro-based prodrugs. Deciphering the evolutionary history of PFOR is crucial in deepening our understanding of the evolution of anaerobic pathogens and unfold new approaches for drug discovery and targeting in pathogen chemotherapy. Abstract: The present frontrunners in the chemotherapy of infections caused by protozoa are nitro-based prodrugs that are selectively activated by PFOR-mediated redox reactions. This study seeks to analyze the distribution of PFOR in selected protozoa and bacteria by applying comparative bioinformatics approaches to test the hypothesis that PFOR was most likely acquired through horizontal gene transfer (HGT) from bacteria. Furthermore, to identify other genes that were putatively acquired using proteome-wide and gene expression analyses. A plausible explanation for the patchy occurrence of PFOR in protozoa is based on the hypothesis that bacteria are potential sources of genes that enhance optimal adaptation of protozoa in hostile environments. The exclusively expressed proteins obtained from Entamoeba histolytica and the putative gene donor, Desulfovibrio vulgaris, showed an over-expression of eleven genes involved in intermediary metabolism. If these results can be reproduced in other PFOR-possessing protozoa, it would provide a more validated evidence to support the horizontal transfer of pfor from bacteria.

Currently, the textile industry is a poorly automated sector, due in part to problems in the handling of deformable leather and textile parts during production operations. In this work, several problems in the handling process of leather and textile parts are addressed, introducing methods to increase the automation of the process. A pneumatic actuator designed to pick up textile or leather parts avoiding their deformation during transport has been developed. This actuator maximizes the number of gripping points to improve handling, making it more stable and efficient. Additionally, a vision system has been implemented in the part picking task which, in conjunction with the CAD information of the part, sends the modified gripping position of the part to the robot. This allows customized handling of each textile or leather part. Finally, validation tests have been carried out on this development, both in simulations and in laboratory conditions, demonstrating its viability and direct applicability in the production line.

This work introduces a new architecture for a time-domain feedback-based beamformer designed to meet real-time processing demands. The primary goal of this design is to locate reflective sources by estimating their direction of arrival (DOA) and signal range. Incorporating a feedback mechanism in this architecture is a unique aspect that refines localization precision. We conduct an in-depth analysis highlighting their respective benefits and limitations to compare the effectiveness of time-domain feedback beamforming against conventional time-domain methods. Our evaluation of the proposed architecture, based on critical performance indicators such as peak-to-sidelobe ratio, mainlobe width, and directivity factor, demonstrates its ability to improve beamformer effectiveness significantly.

Humans have a unique cognitive ability known as relational abstraction, which allows us to identify logical rules and patterns beyond basic perceptual characteristics. This ability represents a key difference between how humans and other animals learn and interact with the world. With current large language models rivaling human intelligence in many regards, we investigated whether relational abstraction was an emergent chat completion capacity in various models. We find that despite their impressive language processing skills, all tested language models failed the relational match-to-sample (RMTS) test, a benchmark for assessing relational abstraction. These results challenge the assumption that advanced language skills inherently confer the capacity for complex relational reasoning. The paper highlights the need for a broader evaluation of AI cognitive abilities, emphasizing that language proficiency alone may not be indicative of certain higher-order cognitive processes thought to be supported by language.

The exceptional performance of graphene has driven the advancement of its preparation technique and application. Laser-induced graphene (LIG), as a novel graphene preparation technique, has been applied in various fields. Graphene periodic structures created by LIG technique exhibit superhydrophobic characteristics and can be used for deicing and anti-icing applications, which are significantly influenced by the laser parameters. The laser surface treatment process was simulated by a finite element software analysis (COMSOL Multiphysics) to optimize the scanning parameter range, and the linear array surface structure were subsequently fabricated by the LIG technique. The generation of graphene was confirmed by Raman spectroscopy, and energy-dispersive X-ray spectroscopy. The periodic linear array structure were observed by Scanning electron microscopy (SEM) and confocal laser imaging (CLSM). In addition, CLSM testings, contact angle measurements, and delayed icing experiments were systematically performed to investigate the effect of scanning speed on surface hydrophobicity. The results show that the high quality and uniform graphene can be achieved using the laser scanning speed of 125 mm/s. The periodic linear array structures can obviously increase the contact angle and suppress delayed icing. Furthermore, these structures have the enhanced ability of the electric heating deicing, which can reach 100°C and 240°C within 15 s and within 60 s under the DC voltage power supply ranging from 3 to 7 V, respectively. These results indicate that the LIG technique can be developed to provide an efficient, economical, and convenient approach for preparing graphene and the hydrophobic surface array structure based on LIG has considerable potential for deicing and anti-icing applications.

Time-modulated sparse circular array (TMSCA) with elements uniformly excited is designed and synthesized in this paper. By utilizing rotationally symmetric structure, the array geometry and the time modulation of the TMSCA is presented, and the radiation patterns in frequency domain are formulated. In order to achieve the desired radiation pattern at the operating frequency and suppress the sideband radiation, the synthesis problem is established and solved by the proposed harmony search-convex programming (HS-CP) algorithm in two dependent optimizations. Two designs are presented, and the numerical results indicate that the TMSCA with rotationally symmetric structure has the advantages of designing time-modulated sparse arrays with superior performance.

This paper investigates the critical factors for balancing environmental sustainability and economic development through the lens of New Structural Economics. Specifically, we utilize the congruence index to access the alignment between local factor endowment structure and firm production input structure. Using a comprehensive manufacturing firm-level pollutant emissions dataset from the Yangtze River Economic Belt (YEB) region in China, we find that firms demonstrating higher congruence exhibit improved economic performance and alignment with comparative advantages. This not only contributes to increased economic efficiency for these firms but also leads to a reduction in pollutant emissions, including wastewater discharge and Chemical Oxygen Demand (COD) emissions. Our study provides valuable insights into achieving mutually beneficial environmental and economic outcomes.

The present study provides a detailed analysis of the chloroplast genome of Microula sikkimensis. The genome was consisted of altogether 149,428bp and distinct regions, including large single-copy (81329bp), small single-copy (17261bp), and inverted repeat (25419bp). The genome contained 112 genes, including 78 protein-coding genes, 30 tRNA genes, and 4 rRNA genes, some exhibited duplication in the IR region. The chloroplast genome displayed different GC content across regions, with the IR region exhibiting the highest. Codon usage analysis and the identification of simple sequence repeats (SSRs) offer valuable genetic markers. Comparative analysis with other Boraginaceae species highlighted conservation and diversity in coding and noncoding regions. Phylogenetic analysis placed M. sikkimensis within the Boraginaceae family, revealing its distinct relationship with specific species.

CdZnTe (CZT) is a new type of compound semiconductor that has emerged in recent years. Compared to other semiconductor materials, it possesses an ideal bandgap, high density, and high electron mobility, rendering it an excellent room-temperature composite semiconductor material for X-ray and γ-ray detectors. Due to the exceptional performance of CZT material, detectors manufactured using it exhibit high energy resolution, spatial resolution, and detection efficiency. They also have the advantage of operating at room temperature. CZT array detectors, furthermore, demonstrate outstanding spatial detection and three-dimensional imaging capabilities. Researchers worldwide have conducted extensive studies on this subject. This paper, building upon this foundation, provides a comprehensive analysis of CZT crystals and CZT array detectors, summarizes existing research to offer valuable insights for envisioning new detector methodologies.

Malaxidinae is one of the confusing groups with classification in Orchidaceae. Previous phylogenetic analysis reveals that the relationships among the taxa in Malaxidinae have not yet been reliably established using a few plastome regions or nuclear ribosomal internal transcribed spacer (nrITS). In the present study, the complete plastomes of Oberonia integerrima and Crepidium purpureum were assembled using high-throughput sequencing. Combined with publicly available complete plastome data, this resulted in a data set of 19 plastomes, including 17 species of Malaxidinae. The plastome feature and phylogenetic relationship were compared and analyzed. The results showed that: (1) The plastomes of Malaxidinae species possessed the quadripartite structure of typical angiosperms, with sizes ranging from 142,996 bp to 158,787 bp and encoding from 125 to 133 genes. The ndh genes were lost or pseudogenized with varying degrees in six species. An unusal inversion was detected in the Large Single-Copy region (LSC) of Oberonioides microtatantha. (2) A total of 8 regions, including ycf1, matK, rps16, rpl32, ccsA-ndhD, clpP-psbB, trn-FGAA-ndhJ, and trnSGCU-trnGUCC, were identified as mutational hotspots. (3) Based on complete plastomes, 68 protein-coding genes and 51 intergenic regions, respectively, the phylogenetic analyses resolved genera-level relationships in this subtribe with strong support. The Liparis was supported as polyphyletic.

We are introducing a highly efficient 48-channel ultrasound beamforming system ideal for ultrasound endoscopy applications. The system includes a transmitter and a receiver, which allow for low-area, high-resolution imaging acquisition. The transmitter uses a charge redistribution HV (high voltage) scheme to generate three-level pulses that actuate the transducer, implemented with the standard CMOS process for optimal cost and power savings. Meanwhile, the receiver features a sub-array structure and a delay generator that reduces area usage. To achieve high-resolution ultrasound imaging acquisition with low computational power, we developed the Shift Coherence Factor (SCF) algorithm, which is hardware-friendly. This approach delivers a lateral resolution over 20% better than the conventional delay and sum (DAS) algorithm, with a contrast ratio of over 30 dB. The system was implemented in a 180 nm standard CMOS process with an area of 24.98 mm2, power consumption of 8.23 mW per channel, achieving a delay resolution of 8.33 ns, and a low-area implementation of 0.52 mm2 per channel. The system offers high-quality imaging acquisition with minimal additional area and power consumption, which has great potential for 3D imaging or catheterized ultrasound systems.

A novel quasi-twisted miniaturized wideband Branch Line Coupler (BLC) is proposed. The design is based on bisecting the conventional microstrip line BLC transversely and folding bisected sections on double-layered substrates with a common ground plane in between. The pair of quarter wavelength horizontal parallel arms is converted to a Z-shape meandered microstrip line in the designed structure. On the other hand, the pair of quarter wavelength vertical arms are cut by half into two lines and converted to a periodically loaded slow wave structure. The bisected parts of BLC are placed on the opposite side of the doubled-layer substrate and connected through four vias passing through the common ground plane. This technique enabled a compact BLC size of 6.4×18 mm2, which corresponds to a surface area miniaturization by ~50% as compared to the classical BLC size of 10×23 mm2 at 6GHz, Moreover, the attained relative bandwidth is 73.9% (4.6-10 GHz) for S11, and 75.8% (4.5-10 GHz) for S33 as compared to 41% for the ordinary BLC at the same resonant frequency. The circuit is constructed on a double-layered low-cost FR4 substrate with a relative permittivity of 4.3, and a loss tangent of 0.025. An isolation of -13dB was realized in both S13 and S31 demonstrating an excellent performance. The transmission coefficients between input/output ports S21, S41, S23, and S43 are between -3.1dB to -3.5dB at the frequency of 6GHz. Finally, the proposed BLC provides phase differences between output ports of 90.5o and 94.8o at the frequency of 6GHz when the input ports 1 and 3 are excited, respectively. The presented design offers the potential of being utilized as a unit cell for building a Butler-matrix (BM) for sub-6GHz 5G beamforming networks.

The World Health Organization (WHO) has released reports indicating that heart disorders hold the unfortunate distinction of being the primary cause of death worldwide. Shockingly, an astonishing estimated 17.9 million lives are claimed by heart diseases annually, accounting for an alarming 31% of all global deaths. With all the flaws in the clinical situation, it is frequently challenging to assess the severity of cardiac disease and forecast its course of progression due to heterogeneity and complex interplay of factors. Therefore, early heart disease detection is essential for effective therapy. To address these challenges, Machine Learning (ML) boosting algorithms play a pivotal role as the main components of predictive analytics required to do this. The main objective of this study is to develop a comprehensive comparative framework to predict heart diseases using state-of-the-art machine learning with boosting techniques such as Decision Tree, Random Forest, Gradient Boosting, Catboost, XGboost, Light GBM, and Adaboost. To evaluate the performance of the models, a large heart disorders dataset is used from the UCI machine learning repository, comprised of 26 feature-based numerical and categorical attributes with 8763 samples from all over the globe. The Experimental results reveal that AdaBoost attained the highest accuracy of 95% and outperforms other algorithms concerning various performance measures like precision= 0.98, recall= 0.95, specificity= 0.95, f1-score=0.01, Negative predicted value= 0.83, False positive rate= 0.04, False negative rate= 0.04 and False Development rate= 0.01.

Terahertz tomography is a promising method among non-destructive inspection techniques to detect faults and defects in dielectric samples. Image quality recently significantly improved through the incorporation of a priori information and off-axis data. However, this improvement has come at the cost of increased measurement time. To aim toward industrial applications, it is therefore necessary to speed up the measurement by parallelizing the data acquisition employing multi-channel setups. In this work, we present two tomographic frequency-modulated continuous wave (FMCW) systems working at a bandwidth of 230-320 GHz, equipped with an eight-channel detector array, and compare their imaging results with a single-pixel setup. While in the first system, the additional channels are used exclusively to detect radiation refracted by the sample, the second system features an f-θ lens, focusing the beam at different positions on its flat focal plane, and thus utilizing the whole detector array directly. The usage of the f-θ lens in combination with a scanning mirror eliminates the necessity of the formerly used slow translation of a single-pixel transmitter. This opens up the potential for a significant increase in acquisition speed, in our case by a factor of four to five, respectively.

We present a surface acoustic wave (SAW) sensor array for microRNA (miRNA) detection that utilizes photocatalytic silver staining on titanium dioxide (TiO2) nanoparticles as a signal enhancement technique for high sensitivity with an internal reference sensor for high reproducibility. A sandwich hybridization was performed on working sensors of the SAW sensor array that could simultaneously capture and detect three miRNAs (miRNA-21, miRNA-106b, and miRNA-155) known to be upregulated in cancer. Sensor responses due to signal amplification varied depending on the concentration of synthetic miRNAs. It was confirmed that normalization (a ratio of working sensor response to reference sensor response) screened out background interferences by manipulating data and minimized non-uniformity in the photocatalytic silver staining step by suppressing disturbances to both working sensor signal and reference sensor signal. Finally, we were able to successfully detect target miRNAs in cancer cell-derived exosomal miRNAs with performance comparable to the detection of synthetic miRNAs.

This paper considers the direction of arrival (DOA) estimation problem of phase ambiguity for unfolded coprime linear array (UCLA). The existing most common stacking subarray-based method can tackle the phase ambiguity problem. However, the method is not always true. For a given DOA, it has its corresponding steering vector, but if there are two DOAs which have the same steering vectors with the given DOA for different subarrays, the phase ambiguity problem still arises. A modified method, which defines a decision variable and uses the classic beamforming technique to estimate the DOAs is proposed. However, this method needs additional algorithm to distinguish the true DOAs besides multiple signal classification (MUSIC) spectrum. And sometimes this method is not reliable if the decision variable is not chosen appropriately. Therefore, based on the UCLA, we reconstruct the array to design an improved UCLA called IUCLA. With moving the reference element, the linear relationship among the directional vectors can be broken. In this way, we can directly utilize the MUSIC algorithm to estimate with no additional algorithm. The proposed method can solve the phase ambiguity problem and it does not demand other technique to decrease the complexity. Moreover, the Cramer-Rao Bound (CRB), as the lower bound of the unbiased estimation, is provided and numerical simulations are given to demonstrate the effectiveness and superiority of the proposed method.

Real-time multi-axis distributed tactile sensing is a critical capability if robots are to perform stable gripping and dexterous manipulation, as it provides crucial information about the sensor-object interface. In this paper, we present an optical-based 6-axis tactile sensor designed in a fingertip shape for robotic dexterous manipulation. The distributed sensor can precisely estimate local XYZ force and displacement at ten distinct locations, and provide global XYZ force and torque measurements. Its compact size, comparable to that of a human thumb, and minimal thickness allow seamless integration onto existing robotic fingers, eliminating the need for complex modifications to the gripper. The proposed sensor design uses a simple, low-cost fabrication method. Moreover, the optical transduction approach uses light angle and intensity sensing to infer force and displacement from deformations of individual sensing units that form the overall sensor, providing distributed 6-axis sensing. The local force precision at each sensing unit in the X, Y, and Z axes is 20.89 mN, 19.19 mN, and 43.22 mN, respectively, over an local force range of approximately ±1.5 N in X and Y and 0 to -2 N in Z. The local displacement precision in the X, Y and Z axes is 56.70 μm, 50.18 μm and 13.83 μm, respectively, over a local displacement range of ±2 mm in the XY directions and 0 to -1.5mm in Z (i.e., compression). Additionally, the sensor can measure global torques, Tx, Ty and Tz, with a precision of of 1.90 N-mm, 1.54 N-mm and 1.26 N-mm, respectively. The fabricated design is showcased by integrating it with an OnRobot RG2 gripper and illustrating real-time measurements during in simple demonstration task which generate changing global forces and torques.

The article explores Qualitative Comparative Analysis (QCA), an approach for establishing causal relationships between conditions and outcomes. QCA, applied in case studies and empirical analyses, facilitates generalizations for future research and addresses causal complexity by identifying various causal "recipes" leading to the same outcome. Three widely used QCA variants are Crisp-Set QCA (csQCA), Multi-value QCA (mvQCA), and Fuzzy-Set QCA (fsQCA), each with unique approaches. The article emphasizes the significance of bibliometric analysis in mapping a research field's intellectual structure, revealing key contributions and trends. In QCA, bibliometric analysis identifies leading researchers, affiliations, and influential countries. Results show QCA's widespread adoption across disciplines, with continuous growth in article production since 2013. The favored variant is fsQCA, followed by csQCA, and China notably contributes to QCA-related research. In conclusion, QCA proves a potent tool for discerning complex causal relationships in empirical studies, with its increasing interdisciplinary use indicating substantial potential for advancing scientific knowledge.

Primulina serrulata is a valuable ornamental herb with rosette leaves and vibrant flowers. Some leaves exhibit a bright and distinct white color along the upper veins, enhancing their ornamental value, while others are less white or entirely green. This variation is observed among adult leaves in natural habitats and among young leaves from seedlings grown in the laboratory. TMT-labeled proteomic technology was employed to study the protein-level biogenesis of white-veined (WV) leaves of P. serrulata. The chlorophyll (Chl) content was significantly lower in the WV group than in the control group. A total of 6,261 proteins were identified, revealing 69 differentially expressed proteins (DEPs), with 44 down-regulated and 25 up-regulated in WV plants. Some DEPs associated with chloroplasts and Chl biosynthesis were down-regulated, leading to the absence of green coloration. Concurrently, gene ontology enrichment analysis further underscored an insufficiency of magnesium , the key element in Chl biosynthesis. Many DEPs associated with abiotic or biotic stresses were down-regulated, suggesting an overall weakening of stress resistance with certain compensatory mechanisms in place. Similarly, many DEPs related to biomacromolecule modification were down-regulated, possibly influenced by the decrease in proteins involved in photosynthesis and stress resistance. Some DEPs containing iron were up-regulated, indicating that iron was mainly used to synthesize heme and ferritin instead of Chl. Additionally, several DEPs related to sulfur or sulfate were up-regulated, implying strengthened respiration. Expansin-A4 and pectinesterase displayed up-regulation, coinciding with the emergence of a rough and bright surface in the white area, indicative of the elongation and gelation processes in cell walls. These findings provide new insights that could be utilized by future studies to explore the mechanism of color formation in WV leaves.

China Xihu Longjing tea famous for its good flavor and quality. However, the related metabolites information except flavonoids is largely deficient. Different processing methods of China Xihu Longjing tea fixing both by machine at first and second step(A1), first step by machine and second step by hand(A2), first step by hand and second step by machine(A3), both by hand at first and second step (A4) were compared using a UHPLC-QE-MS-based metabolomics approach. Liquid chromatography-mass spectrometry was used to analyze the metabolic profiles of the processed samples. A total of 490 metabolites (3 alkaloids, 3 anthracenes, 15 benzene and substituted derivatives, 2 benzopyrans, 13 coumarins and derivatives, 128 flavonoids, 4 furanoid lignans, 16 glycosides and derivatives, 5 indoles and derivatives, 18 isocoumarins and derivatives, 4 chalcones and dihydrochalcones, 4 naphthopyrans, 3 nucleosides, 78 organic acids and derivatives, 55 organooxygen compounds, 5 phenols, 109 prenol lipids, 3 saccharolipids, 3 steroids and steroid derivatives, 17 tannins) were identified. The different metabolism profiles were distinguished using PCA and OPLS-DA. There were differences in the types and contents of metabolites, especially flavonoids, furanoid lignans, glycosides and derivatives, organic acids and derivatives and organooxygen compounds. There was a positive correlation between flavonoid metabolism and amino acid metabolism. However, there was a negative correlation between flavonoid metabolism and amino acid metabolism, which had the same trend as prenol lipids metabolism, tannin.This study provides new valuable information for regarding differences in the metabolite profile of China Xihu Longjing tea processed based on machine fixing and manual fixing methods.

The limitations of conventional sensors have made phased array antennas increasingly crucial for gathering information and communication applications in intelligent transportation systems. Compact cylindrical arrays, in particular, are favored for their ability to achieve azimuth angle scan. However, the substantial mutual coupling effect between elements on curved surfaces and its implication in these arrays remains unclear, which is a crucial factor to consider when such arrays are used for multibeam applications. This study investigated the effect of mutual coupling in a dual-slant-polarized cylindrical array. The results showed that mutual coupling is essential for achieving an ultra-wide bandwidth. Mutual coupling is predominantly observed among elements that are closely positioned. The study also analyzes the impact of mutual coupling on scan impedance and radiation characteristics for multibeam applications and reveals that these arrays exhibit robust multibeam capability, hence having great potential for use in intelligent transportation systems.

In our article in Genome Biology Ecology six years ago, one complete plastid genome of Belian was assembled for comparative analyses of the plastomes in Lauraceae. However, Ariati et al. (2023) concluded that our sequenced Belian individual could be located in the clade of Myristicaceae instead of that of Lauraceae. Here, we performed re-analyses of additional two Belian plastomes, along with 42 plastomes from plants spanning ten families of the Magnoliids. The plastomes of the three Belian individuals range from 157,535 to 157,577 bp in length. Comparative genomic analysis revealed 170 mutation sites in their plastomes, which include 111 substitutions, 53 indels, and six microinversions. Phylogeny was reconstructed using maximum likelihood and Bayesian approaches for 44 magnoliids species indicated that our three Belian individuals are nested among the species in the family Lauraceae rather than Myristicaceae.

Based on the multiple coordination framework of “promising government-effective market-ordered society”, this paper takes 68 cases of adding elevators to old buildings as samples, and selects six conditional variables: approval optimization, financial subsidies, financing innovation, technological innovation, capable people leading and neighborhood committee guidance. Using Crisp-Set Qualitative Comparative Analysis (csQCA), this paper discusses the combination of conditions that affect the success or failure. It is found that: approval optimization and neighborhood committee guidance are sufficient conditions for the success; successful cases can be divided into three types: “political and social dual-drive type”, “market and social dual-drive type” and “ternary co-drive type”; lack of approval optimization, lack of financing innovation, and the existence of capable people leading are necessary conditions for the failure. The failure cases can be divided into “government and market double failure type” and “market failure type”.

Iterative Stochastic decoding is an alternative to standard fixed-point decoding of Low-density parity check codes (LDPC) to reduce inter-node routing. In this paper, we propose a Flexible Field-Programmable Gate Array (FPGA)-Based Stochastic decoding (SD) hardware architecture for LDPC codes in the Fifth-Generation (5G) New Radio (NR) Standard that supports decoding of set of various code rates. This decoder’s runtime flexibility is desirable to switch a better performing code rate automatically based on the channel conditions without the extra time needed for reprogramming of FPGA. An offline design method is implemented to generate the hardware description language (HDL) code description of the decoder for the required code-rate set, which is further synthesized and integrated into the Xilinx Kintex-7 series FPGA board to determine the hardware resource utilisation and processing throughput. The Synopsys design tools were employed during both the simulation and synthesis stages, in combination with TSMC 65-nm CMOS standard cell technology, to facilitate comparative analysis. Compared with state-of-the-art designs, the proposed architecture reduces hardware utilization by up to 26% and achieved energy efficiency by 52%.

This study addresses the pressing energy constraints in nations like Bangladesh by proposing the implementation of photovoltaic (PV) microgrids. Given concerns about environmental degrada-tion, limited fossil fuel reserves, and volatile product costs, renewable energy sources are gaining momentum globally. Our research focuses on a grid-connected solar PV system model at Char Jazira, Lalpur, Natore, Rajshahi, Bangladesh. Through PVsyst simulation software, we assess the performance ratio (PR) and system losses, revealing an annual solar energy potential of 3375 MWh at Standard Test Condition (STC) efficiency. After considering losses, the system generates 2815 MWh annually, with 2774 MWh exported to the grid. We analyze an average PR of 78.63% and calculate a levelized cost of energy (LCOE) of 2.82 BDT/kWh [1 USD = 110 BDT]. The financial assessment indicates a cost-effective LCOE for the grid-connected PV system, with an annual gross income of 27744 BDT from selling energy to the grid and operating costs of 64060.60 BDT/year. Remarkably, this initiative can prevent 33074.061 tCO2 emissions over the project’s 25-year lifespan.

The utilization of dual-potential mode of integrated array (IDA) electrodes and other two-electrode systems has revolutionized electrochemical detection by enabling the simultaneous and independent detection of two species, accompanied by the exhibition of unique characteristics. In contrast to conventional dual-potential electrodes, the rotating ring disk electrodes (RRDE), IDA electrodes demonstrate analogous yet vastly improved performance metrics, characterized by remarkable collection efficiency and sensitivity. Notably, due to the distinctive microscale structure of IDA electrode, the special “feedback” effect makes IDA a unique signal amplifier. In recent decades, the research surrounding IDA electrodes has garnered escalating interest due to their attractive attributes. This review centers its focus on the fabrication and applications of IDA electrodes. In the realm of fabrication, two critical breakthroughs are poised for realization: the achievement of reduced dimensions and the diversification of materials. Established fabrication methods for IDA electrodes encompass photolithography, inkjet printing, and direct laser writing, each affording distinct advantages in terms of size and precision in IDA construction. Predominantly employed materials for IDA electrodes include gold, platinum, and carbon, with the selection of fabrication methods guided by considerations such as material properties, desired dimensions, cost-efficiency, and specific application requisites. Within the domain of applications, IDA electrodes, capitalizing on their distinctive attributes, have found utility in diverse fields. This review summarizes the applications of IDA electrodes based on their fundamental working principles, encompassing redox cycling, resistance modulation, capacitance variations, and more. The potential for further development of this specialized tool to exhibit enhanced properties holds substantial promise.

The liver is not only a digestive gland, but also an immune tissue that receives a double infusion from the hepatic artery and the hepatic portal vein. Receiving 80% of its blood supply from the intestine through the hepatic portal vein system, the liver is enriched with a large number of innate immune cells, which carry out the process of immune response by detecting pathogens entering the organism through the intestine. The intestine and liver communicate extensively through the bile ducts, portal vein and the somatic circulation, a bidirectional communication known as the intestinal-liver axis. The mammalian gut is considered an important microbial ecosystem. The interplay between the natural immune system and microbes coordinates the physiology of the whole organism, and in specific mammalian lineages, there is a dependency between the host and its associated microbes. To this end, we explored the regulatory mechanisms of natural immunity genes at the genome-wide level. Based on comparative genomics, 1473 bovine natural immunity genes were obtained by collecting the latest reports of human natural immunity genes and updated bovine genomic data for comparison, and a bovine natural immunity gene database was initially constructed to screen and match calf liver natural immunity differential genes mainly affected by the phylum Mimosoidea and the phylum Thick-walled Bacteria, and 16 differentially expressed natural immunity genes were obtained. In addition, the results of IPA analysis indicated that the upstream factor IL-2 initiated the PI3K/AKt/mTOR, mitogen-activated protein kinase (MAPK) pathway and JAK/STAT5 pathway, leading to the liver's involvement in gut microbial immune regulation.

5G low-earth orbit satellite communications offer enhanced wireless coverage beyond the reach of 5G terrestrial networks, with important implications, particularly for automated and connected vehicles. Such wireless automotive mass-market applications demand well-designed compact user equipment antenna terminals offering non-terrestrial jointly with terrestrial communications. The antenna should be low-profile, conformal, and meet specific parameter values for gain and operational frequency bandwidth, tailored to the intended applications, in line with the aesthetic design requirements of passenger cars. This work presents an original concept for a dual-band nested circularly polarized automotive user terminal that operates at the S-band frequencies around 3.5 GHz and Ka-band frequencies around 28 GHz, namely within the 5G new-radio bands n78 and n257, respectively. The proposed terminal is designed to be integrated into the plastic components of a passenger vehicle. The arrays consist of 2×2 aperture-coupled corner-truncated microstrip slot patch antenna elements for the n78 band and of 4×4 single-layer edge-truncated microstrip circular slot patch antenna elements for the n257 band. The embedded arrays offer, across the two bands, respectively 9.9 and 13.7 dBi measured realized gain and 3-dB axial ratio bandwidths of 100 and 1500 MHz for the n78 and n257 bands along the broadside direction. Detailed link budget calculations anticipate uplink data rates of 21 and 6 Mbit/s, respectively, deeming it suitable for various automotive mobility and internet-of-things applications.

Criminal investigations aimed to track the route walked by Missing Persons and Fugitives (MPFs) usually involve Intelligence analysts, military planners, experts in mobile forensics, traditional investigative methods, and sniffer dog handlers. Notwithstanding, when MPFs are devoid of any technological device and move in uninhabited rural areas devoid of tele cameras and densely covered by vegetation, tracking backwards the route walked by MPFs may be a much more arduous task. In such complex cases, a very efficient approach may consist in comparing the geological traces found on the MPFs with soils and plants exposed in the event scenes. In particular, the search for peculiar or rare particles and aggregates may strengthen the weight of the geological evidence comparisons. A match of mineralogical, textural, and botanical data may demonstrate the provenance of the traces from the soil of a specific site, linking in this way the MPFs to the scene of events. Based on the above, the present paper reports geological and botanical determinations accomplished for a “mediatic” casework. Results allowed to ascertain a general high degree of compatibility among traces collected on the MPFs and on the soil from the scene of events. The most significant positive matches, based on the finding of a ten of peculiar and rare particles and assemblages, allowed reconstructing a route about 1.1 km long, as the crow flies, on the event site. Notwithstanding this procedure was extremely time consuming and available only in a backwards reconstruction linked to the MPFs’ findings, it was of uttermost importance in strengthen the inferences proposed, where other methods could not provide any information.

This research, which focuses on wave energy generating technology, suggests a brand-new oscillating float-type wave energy conversion system that is appropriate for the offshore wave environment. To accurately model the device, a three-dimensional viscous numerical pool is created based on STAR-CCM+. The array-type power generation device is numerically simulated using theoretical analysis and numerical simulation, and the wave energy power generation device is arranged as double floats in the front and rear rows, representing triangular array type and rectangular array type, respectively. The triangular array type is a superior layout and can make greater use of marine resources, according to this paper's analysis of the hydrodynamic and power generation impacts of the three array types. The findings are meant to serve as a guide for engineering practice.

Qualitative comparative analysis (QCA) was developed by Charles Ragin in 1987 for the comparative analysis of small data sets. The method has become widespread in sociological and economic research. There are examples of successful use of QCA in the field of medicine and epidemiology. The purpose of this review is to describe the key stages of QCA with a discussion the application of this method to the analysis of medical and epidemiological data.

The Korean water deer (WD), the dominant wildlife species in South Korea, is classified as vul-nerable on the IUCN Red List. Beside their several unique characteristics, they have a lower in-cidence of tick bites compared to other Cervidae species, particularly roe deer (RD). In natural environments, ticks exhibit questing behavior by waiting on grasses to climb onto host's hair coat. They use sensory organs to detect signals such as body temperature and chemicals from the host's skin, then move to preferred feeding location. Therefore, we conducted a comparative analysis of the skin tissue and hair features of both species to compare the factors leading to lower incidence of tick bites in WD. Notably, WD had significantly larger blood vessels, sebaceous glands, and sweat glands which maintain the barrier functions of the skin (p≤0.004), irregular scale surfaces in hair cuticles, and stiff and 2.83-times thicker primary hair diameter (p<0.001). Each parameters made the ticks difficult to move onto the epidermis of WD. To our knowledge, this is the first report which is focused on the comparative analysis for skin and hair feature in WD and RD. We suggest that these differences may attribute to evade tick bites in WD.

Cochlear implantation (CI) allows rehabilitation for patients with severe to profound hearing impairment. Although the use of a robotic assistant provides technical assistance to the surgeon, the assessment of the impact of its use on auditory outcomes remains uncertain. We aim to com-pare the hearing results of patients who underwent bilateral cochlear implantation, one side was performed with manual insertion and the other side with robot-assisted insertion. The electrode array intrascalar positioning and the surgery duration were also studied. This retrospective intra-individual study involved 10 patients who underwent bilateral cochlear implantation. The study included 2 infants and 8 adults. The unique composition of this cohort enabled us to utilize each patient as their own control. Regarding speech disyllabic recognition, pure tone average, ECAP, ratio of array translocation, basilar membrane rupture, percentage of translocated electrodes there was no difference between manual and robot-assisted CI groups. This study is the first to compare intra-individual hearing performance after cochlear implantation either manually or robot-assisted. The number of patients and the time delay between manual and robotic implantation may have led to a lack of power, but there was no apparent difference in hearing performance between manual and robotic implantation.

The Savu Sea holds significant importance as a conservation area in Indonesia, providing sustenance and livelihoods for local communities. It is situated within the Coral Triangle, a critical hotspot for marine biodiversity worldwide. However, the Savu Sea is currently facing various threats, including overfishing, pollution, and the impacts of climate change. Effective management of this conservation area relies heavily on the active participation of local communities. Therefore, this study aims to address this issue by analyzing how factors within these communities, such as the socio-economic condition of coastal households, environmental awareness, the existence of community-based conservation areas, attitudes towards activities within the conservation area, and participation in multistakeholder institutions, contribute to a positive perception of the benefits provided by the Savu conservation area. To determine the complex causal conditions that influence the outcome of perception, the study employs the Qualitative Comparative Analysis (QCA) method, specifically using crisp set QCA (csQCA). A survey was conducted among 22 coastal villages surrounding the Savu Sea, resulting in the identification of 14 different combinations of pathways that contribute to varying levels of perception regarding conservation. Valuable lessons can be drawn from this study to enhance the design of policies aimed at effectively managing the Savu conservation area.

This paper proposes a position recognition method for the receiver coil by the secondary coil current. Based on the practical value of the current of the receiver coil, the position recognition of the receiver coil in the WPT system is realized. This paper proposes a 3×3 array multi-transmitter coil grouping and control logic. The mathematical model of mutual inductance between the receiver and transmitter coil at different positions on the X-Y plane is established. A method for identifying the position of the receiver coil according to the current of the receiver coil is proposed. Compared with the traditional position recognition method of the receiver coil, this method does not need to add a detection coil and position sensor and can realize the position recognition of the receiver coil on the 2D plane.

The availability of multiple sequenced genomes from a single species made it possible to explore intra- and inter-specific genomic comparisons at higher resolution and build clade-specific pangenomes of several crops. The pan-genomes of crops constructed from various cultivars/accessions, landraces, and wild ancestral species represent a compendium of genes and structural variations and allow researchers to search for the novel genes and alleles that were inadvertently lost in domesticated crops during the historical process of crop domestication or in the process of extensive plant breeding. Fortunately, many valuable genes and alleles associated with desirable traits like disease resistance, abiotic stress tolerance, plant architecture, and nutrition qualities exist in landraces, ancestral species, and crop wild relatives. The novels genes from the wild ancestors and landraces can be introduced back to high-yielding varieties of modern crops by implementing classical plant breeding, genomic selection, and transgenic/gene editing approaches. Thus, pan-genomic represents a great leap in plant research and offers new avenues for targeted breeding for mitigating the impact of global climate change. Here we summarize the tools used for pangenome assembly and annotations, web-portals hosting plant pangenomes. Furthermore, we highlight a few discoveries made in crops using the pan-genomic approach and its future potential.

This research paper presents an enhanced economic load dispatch (ELD) approach using the Teaching-Learning-Based Optimization (TLBO) algorithm for 10 thermal units, examining the impact of Plug-in Electric Vehicles (PEVs) in different charging scenarios. The TLBO algorithm is utilized to optimize the ELD problem, considering the complexities associated with thermal units. The integration of PEVs in the load dispatch optimization is investigated, and different charging profiles and probability distributions are defined for PEVs in various scenarios, including overall charging profile, off-peak charging, peak charging, and stochastic charging. These tables allow for the modeling and analysis of PEV charging behavior and power requirements within the power system. By incorporating PEVs, additional controllable resources are introduced, enabling more effective load management and grid stability. The comparative analysis showcases the advantages of the TLBO-based ELD model with PEVs, demonstrating the potential of coordinated dispatch strategies leveraging PEV storage and controllability. This paper emphasizes the importance of integrating PEVs into the load dispatch optimization process, utilizing the TLBO algorithm, to achieve economic and reliable power system operation while considering different PEV charging scenarios.

In the modern world, stress has become a pervasive concern that affects individuals' physical and mental well-being. To address this issue, many wearable devices have emerged as potential tools for stress detection and management, by measuring heart rate, heart rate variability (HRV), and various matrices related to it. This literature review aims to provide a comprehensive analysis of existing research on HRV tracking and Biofeedback using smartwatches and finger monitor/sensor pairing with reliable 3rd party mobile apps like Elite HRV, Welltory, and HRV4Training specifically designed for stress detection and management. we apply various algorithms and methodologies employed for HRV analysis and stress detection is discussed, including time-domain, frequency-domain, and non-linear analysis techniques. Prominent smartwatches, such as Apple Watch, Garmin, Fitbit, Polar, and Samsung Galaxy Watch, are evaluated based on their HRV measurement accuracy, data quality, sensor technology, and integration with stress management features. We describe the efficacy of smartwatches in providing real-time stress feedback, personalized stress management interventions, and promoting overall well-being. To assist researchers, doctors, and developers use smartwatch technology to address stress and promote holistic well-being, we discuss the data's advantages and limitations, future developments, and the significance of user-centered design and personalized interventions. Keywords: smartwatch; stress; wearable device; heart rate variability; comparative analysis

Vasculogenic mimicry (VM), a process in which aggressive cancer cells form tube-like structures, plays a crucial role in providing nutrients and escape routes. Highly plastic tumor cells, such as those with triple-negative breast cancer (TNBC) phenotype, can develop VM. However, little is known about the interplay between cellular components of the tumor microenvironment upon TNBC cells VM-capacity. In this study, we analyzed the ability of endothelial and stromal cells to induce VM when interacting with TNBC cells, and analyzed the involvement of the FGFR/PI3K/Akt pathway in this process. VM was corroborated using fluorescently‐labeled TNBC cells. Only endothelial cells triggered VM formation, suggesting a predominant role of paracrine/ juxtacrine factors from an endothelial origin in VM development. By immunocytochemistry, qPCR and secretome analyses, we determined increased expression of proangiogenic factors as well as stemness markers in VM-forming cancer cells. Similarly, endothelial cells primed by TNBC cells showed upregulation of proangiogenic molecules, including FGF, VEGFA, and several inflammatory cytokines. The endothelium-dependent TNBC-VM formation was prevented by AZD4547 or LY294002, strongly suggesting the involvement of the FGFR/PI3K/Akt axis in this process. Given that VM is associated with poor clinical prognosis, targeting FGFR/PI3K/Akt pharmacologically may hold promise for treating and preventing VM in TNBC tumors.

Near-infrared (NIR) photodetectors (PDs) have attracted much attention in noninvasive medical diagnosis and treatment. Especially, the self-filtered NIR PDs are highly demandable for tremendous biomedical application due to their strong ability in wavelength discrimination. In this work, we designed and then fabricated a Si micro-holes array/Graphene (Si MHA/Gr) van der Waals (vdW) Schottky NIR photodiode by using PbS quantum dots (QDs) coating. The device exhibits a unique self-filtered NIR response with a responsivity of 0.7 A/W at -1 V and a response time of 61 μs, which are higher than that without PbS QDs coating and even most of previous Si/Gr Schottky photodiodes. The light trapping of the Si MHA and the PbS QDs coating can be attributed to the high responsivity of the vdW photodiode. Furthermore, the presented NIR photodiode can also be integrated in photoplethysmography (PPG) for real-time heart-rate (HR) monitoring. The extracted HR is in great accord with the value measured with the patient monitor by analyzing the Fourier transform of the stable and reliable fingertip PPG waveform, suggesting its potential for practical applications.

Gold- and MnO₂- nanozymes are well-known for their enzyme-like activity. In this regard, initially, gold- and MnO₂- nanozymes were synthesized by simple and green methods. Afterward, the kinetic studies were performed using the Michaelis–Menten model for both gold- and MnO₂- nanozymes. The kinetic parameters including K_m and V_max were calculated via the construction of the linear plot of Lineweaver–Burk for both nanozymes. The results showed a V_max and K_m of 185 nM sec^-1 and 47 nM sec^-1 for the gold- and MnO₂- nanozymes, in order. The ratio of V_max(gold)/V_max(MnO₂) was found to be about 4.0 which pointed that the catalytic efficiency of gold-nanozymes is 4.0-fold higher than the catalytic efficiency of MnO₂- nanozymes. The K_m value was found to be 0.72 mM and 1.6 mM for the as-prepared gold- and MnO₂- nanozymes, respectively, and the K_m of MnO₂-nanozymes is 2.2-fold higher than that of gold nanozymes. Since the Km shows the affinity of substrate for binding to nanozyme active nodes (lower K_m=higher affinity), it is consultable that the substrate affinity toward MnO₂-nanozymes is 2.2-fold lower than that of the gold-nanozymes. Considering the above results, the as-prepared gold nanozymes are very stronger peroxidase-like mimics than the metal oxide MnO₂-nanozymes.

Petrochemical plants use on-stream inspection more often to detect and monitor the corrosion on the equipment and piping system. Compared to ultrasonic thickness gauging and pulse-echo A-scan, phased array corrosion mapping has better coverability and can scan a large area to detect general and localized corrosion. This paper's objective is to obtain documentary evidence on the accuracy of corrosion detection from 30°C to 250°C on A36 low-carbon steel by carrying out simulation experiments every 10°C steps. A minimum of three sets of phased array corrosion mapping data in each temperature were collected to study and evaluate the detectability. The data evidence could enhance the confidence level of the plant's end users to use the phased array mapping in the future during an inspection. The experiments were found to be insufficiently thorough despite addressing the initial concerns, leaving more area for discussion in further studies, such as expanding the investigation to thicker carbon steel, stainless steel, and wedge materials.

Light Detection and Ranging (LiDAR) technology, a cutting-edge advancement in mobile applications, presents a myriad of compelling use cases, including enhancing low-light photography, capturing and sharing 3D images of fascinating objects, and elevating the overall augmented reality (AR) experience. However, its widespread adoption has been hindered by the prohibitive costs and substantial power consumption associated with its implementation. To surmount these obstacles, this paper proposes a low-power, low-cost, SPAD-based system-on-chip (SoC) which packages the microlens arrays (MLA) and incorporates with a light-weight RGB-guided sparse depth imaging completion neural network for 3D LiDAR imaging. The proposed SoC integrates an 8x8 Single-Photon Avalanche Detectors (SPADs) macro pixel array with time-to-digital converters (TDC) and charge pump, fabricated using a 180nm bipolar-CMOS-DMOS (BCD) process. A random MLA-based homogenizing diffuser efficiently transforms Gaussian beams into flat-topped beams with a 45° field of view (FOV), enabling flash projection at the transmitter. To further enhance resolution and broaden application possibilities, a lightweight neural network employing RGB-guided sparse depth complementation is proposed, enabling a substantial expansion of image resolution from 8x8 to quarter video graphics array level (QVGA; 256x256). Experimental results demonstrate the effectiveness and stability of the hardware encompassing the SoC and optical system, as well as the lightweight features and accuracy of the algorithmic neural network. This integrated state-of-the-art hardware-software solution offers a promising and inspiring foundation for developing consumer-level 3D imaging applications.

In recent years, the number of mole species for which the species status has been confirmed using genetic methods has been continuously increasing. Unfortunately, cytogenetic analysis is not available for all species. Here, for the first time, a GTG-banded karyotype of the small-toothed mole from Vietnam, Euroscaptor parvidens, a representative of the eastern clade of the genus Euroscaptor, was described. Through comparative analysis of available Euroscaptor (E. parvidens, E. klossi, and E. malayana) and Oreoscaptor (O.mizura) karyotypes we find cytogenetic signatures. Zoo-FISH with sorted chromosomes of the Siberian mole Talpa altaica on chromosome sets of the small-toothed mole E. parvidens, the small Japanese mole M. imaizumii from the close genus Mogera and the Japanese shrew mole Urotrichus talpoides from the tribe Urotrichini made it possible to identify syntenic regions between species that diverged about 35 million years ago. The low rate of chromosomal changes within the species of the genus Talpa - T.altaica and T.europaea - and the high rate of karyotypic reshuffling within the Asian genera of the tribe were confirmed. The pericentric inversions on four pairs of autosomes are shared between the closely related genera Euroscaptor, Oreoscaptor, and Mogera, while many more apomorphic rearrangements have occurred in each lineage additionally. The highest rate of chromosomal changes was recorded in the lineage of the small-toothed mole.

Detecting, tracking, and classifying unmanned aerial vehicles (UAVs) in a swarm presents significant challenges due to their small and diverse radar cross-sections, multiple flight altitudes, velocities, and close trajectories. To overcome these challenges, adjustments of the radar parameters and/or position of the radar (for airborne platforms) are often required during runtime. The runtime adjustments help to overcome the anomalies in the detection, tracking, and classification of UAVs. The runtime adjustments are performed either manually or through fixed algorithms, each of which can have its limitations for complex and dynamic scenarios. In this work, we propose the use of multi-agent reinforcement learning (RL) to carry out the runtime adjustment of the radar parameters and position of the radar platform. The radar used in our work is a multibeam multifunction phased array radar (MMPAR) placed onboard UAVs. The simulations show the cognitive adjustment of the MMPAR parameters and position of the airborne platform using RL helps to overcome anomalies in the detection, tracking, and classification of UAVs in a swarm. A comparison with other artificial intelligence (AI) algorithms shows that RL performs better due to runtime learning of the environment through rewards.

Due to the accelerated development of the offshore method of oil production in recent decades, especially in the Arctic region, the risks of crude oil pollution of the waters of the World Ocean are inevitably increasing. These oil spills during the exploitation of shelf deposits, transportation of oil from production sites and other anthropogenic impacts have a devastating impact on the marine biosphere, economy and life of coastal regions. For operative monitoring of water surface and fixation of oil spills it is necessary to use modern, effective and reliable methods, remote monitoring tools. One of such methods is radar. This article deals with increasing the efficiency of the radar method of water surface monitoring by means of constructive modification of the radar antenna array and changing the shape of the radio signal. As a result of the literature review, theoretical analysis of radar and conducted mathematical modeling it is substantiated the increase of radar monitoring efficiency by using phased active antenna array and construction of the cosecant-squared pattern diagram of the radio signal.

For the water bodies of the Lena Delta Nature Reserve, 413 taxa were known. In 14 small tundra reservoirs in its vicinity, we identified 385 taxa, which in the compilatory list made up a significant diversity (666 taxa including definitions to the genus level) of diatoms. Thus, the species composition of diatoms in the reserve and adjacent territories was replenished by 278 species. The predominance of species of the genera Pinnularia (57) and Eunotia (51) at the family and generic levels was revealed. Index of intraspecific variability Ssp./Sp. for the lakes of the reserve was 1.11, and for the lakes of the Tiksi region 1.14, which is typical for high-latitude and high-mountain communities. The number of rare or endangered species varied in different lakes within 1-10, totaling 42 species for the entire study area. Bioindication has shown that potentially threatened species prefer moderate temperatures, slightly acidic or neutral environments free from organic pollution. A comparative analysis of the species composition of diatoms in the vicinity of the Lena Delta and other northern water bodies of Yakutia and the Arctic Islands showed that the species composition of each lake in the Arctic is strictly individual. The indicator characteristics show a certain response of the species composition of diatoms to changes in salinity, pH, and organic pollution. A number of regularities in the spatial distribution of diatoms in the study area were found in connection with the physicochemical parameters of their habitat, height above sea level, and relation to a particular catchment basin. Statistical mapping of indicators of community and habitat diversity revealed a strong reaction to point one-time pollution and made it possible to assume the influence of summer northeast winds on the species composition. We suggest that the high diversity inherent in the diatom lakes of the Tiksi coastal zone, which can even be replenished in further studies, can be considered as a property of coastal biota inherent in ecotones. Since it is in the coastal Tiksi region that a surge in the number of species is observed, this region can be considered not only an ecotone, but also a hotspot of diatom diversity. The results of the study are important for developing the basis for monitoring biodiversity under the conditions of anthropogenic and climatic changes in the Arctic.

According to data from the U.S FDA, the likelihood of a new drug progressing from Phase I clinical trials to market approval is only 8% (DiMasi et al., 2016). Furthermore, a significant attrition rate of 35% occurs during Phase II studies due to the failure to demonstrate clinical efficacy (Arrowsmith, 2011). These statistics underscore the urgent need to reassess the current research and development (R&D) paradigm. To address this challenge, a promising approach called reverse translational pharmacology (RTP) has emerged, aiming to enhance the predictive value of preclinical models used in biomedical research by leveraging animal models that spontaneously develop analogous diseases to humans (Schneider et al., 2018). The rationale behind RTP is that knowledge gained from clinical trials in canines can subsequently inform and guide human clinical trials, leading to improved outcomes for both species. Additionally, this approach capitalizes on the opportunity to stimulate veterinary drug development by leveraging pharmacokinetic (PK), efficacy, and safety data obtained from human clinical studies (Schneider et al., 2018). The application of reverse translational pharmacology holds immense potential for expediting drug development and advancing medical knowledge. By employing animal models that naturally develop diseases akin to those found in humans, researchers can enhance the predictive capacity of preclinical models, thereby mitigating the high attrition rates encountered in later stages of clinical trials. Moreover, the exchange of knowledge and data between human and veterinary medicine engenders a synergistic relationship, fostering progress in both domains (Schneider et al., 2018). As this innovative approach gains momentum, fostering collaborations between basic and clinician scientists, pharmaceutical companies, and veterinary professionals becomes increasingly imperative. By sharing resources, expertise, and findings, we can pave the way for groundbreaking discoveries and the development of safe and efficacious treatments for diverse diseases. Embracing reverse translational pharmacology offers an avenue to redefine the R&D paradigm, bringing us closer to a future where a higher proportion of drugs successfully traverse the arduous path from the laboratory to market approval, ultimately benefiting patients across species. In this brief commentary, we highlight four examples of diseases where reverse translational modeling has been used to support pharmaceutical research, including some applications developed in our research laboratory (SMART Pharmacology) at the Iowa State University College of Veterinary Medicine. In doing so, this report also seeks to provide a brief overview of the heuristic value of computational approaches in comparative research. To further illustrate the value of these in silico approaches, we deliberately chose to employ some features of ChatGPT to produce the present summary (OpenAI. (2023). GPT-3.5 [ChatGPT]. Retrieved from https://openai.com).

Among the five human senses, light, sound, and force perceived by eye, ear, and skin, respectively are physical actions, and therefore can be easily measured and expressed as objective, univocal, and simple digital data with physical quantity. However, taste and odor molecules perceived by tongue and nose are chemical actions, it has been difficult to express them as objective and univocal digital data, since no reference chemicals can be defined. Therefore, while the recording, saving, transmitting to remote locations, and replaying human visual, auditory, and tactile information as digital data in digital devices has been realized (this series of data flow is defined as DX (digital transformation) in this review), the DX of human taste and odor information is not yet in the realization stage. Particularly, since there are at least 400,000 types of odor molecules and an infinite number of complex odors that are mixtures of these molecules, it has been considered extremely difficult to realize "human olfactory DX" by converting all odors perceived by the human olfaction into digital data. In this review, we discuss the current status and future prospects of the development of "human olfactory DX," which we believe can be realized by utilizing odor sensors that employ the olfactory receptors (ORs) that support human olfaction as sensing molecules (i.e., human OR sensor).

The environment is seldom optimal for plant growth and changes in abiotic and biotic signals, including temperature, water availability, radiation and pests, induce plant responses to optimise survival. The New Zealand native plant species and close relative to Arabidopsis thaliana, Pachycladon cheesemanii grows under environmental conditions that are unsustainable for many plant species. Here we compare the responses of both plant species to different stressors (low temperature, salt and UV-B radiation) to help understand how P. cheesemanii can grow in such harsh environments. The stress transcriptomes were then determined and comparative transcriptome and network analyses discovered similar and unique responses within species between different stresses, and between the two plant species. A number of widely studied plant stress processes were highly conserved in A. thaliana and P. cheesemanii. However, in response to cold stress, Gene Ontology terms related to glycosinolate metabolism were only enriched in P. cheesemanii. Salt stress was associated with alteration of the cuticle and proline biosynthesis in A. thaliana and P. cheesemanii, respectively. Anthocyanin production may be a strategy to cope with UV-B radiation stress in P. cheesemanii only. These results allowed us to construct broad stress response pathways in A. thaliana and P. cheesemanii and identify possible novel plant strategies that help mitigate environmental stress.

Loss of photoreceptors in retinal degenerative diseases also impacts the inner retina: bipolar cell dendrites retract, neurons rewire and protein expression changes. ON-bipolar cells represent an attractive target for optogenetic vision restoration. However, above-described maladaptations may negatively impact the quality of restored vision. To investigate this question, we employed human post-mortem retinas and transgenic rd1_Opto-mGluR6 mice expressing the optogenetic construct Opto-mGluR6 in ON-bipolar cells and carrying the retinal degeneration rd1 mutation. We found significant changes in delayed rectifier potassium channel expression in ON-bipolar cells of degenerative retinas. In particular, we found an increase in Kv1.3 expression already in early stages of degeneration. Immunohistochemistry localized Kv1.3 channels specifically to OBC axons. In whole-cell patch-clamp experiments, ON-bipolar cells in the degenerated murine retina were less responsive, which could be reversed by application of the specific Kv1.3 antagonist Psora-4. Notably, Kv1.3 block significantly increased the amplitude and kinetics of Opto-mGluR6-mediated light responses in ON-bipolar cells of the blind retina and increased the signal-to-noise ratio of light-triggered responses in retinal ganglion cells. We propose that reduction of Kv1.3 activity in the degenerated retina, either by pharmacological block or by KCNA3 gene silencing, could improve the quality of restored vision.

Video behavior recognition often needs to focus on object motion processes. In this work, a self-organizing computational system oriented to behavioral clustering recognition is proposed, which achieves the extraction of motion change patterns by binary encoding and completes motion pattern summarization using a similarity comparison algorithm. And in the face of unknown behavioral video data, a self-organizing structure with layer-by-layer accuracy progression is used to achieve motion law summarization by using a multi-layer agent design approach. Finally, the real-time feasibility is verified in the prototype system using real scenes to provide a new feasible solution for unsupervised behavior recognition and space-time scenes.

Amphetamine is a psychostimulant drug with a high risk of toxicity and death when misused. Abuse of amphetamines is associated with an altered organic profile, which includes omega fatty acids. Low omega fatty acid levels are linked to mental disorders. Using the Comparative Toxicogenomic Database (CTD), we investigated the chemical profile of the brain in amphetamine-related fatalities and the possibility of neurotoxicity. We classified amphetamine cases as low (0-0.5 g/ml), medium (&gt;0.5 to 1.5 g/ml), and high (&gt;1.5 g/ml) based on amphetamine levels in brain samples. All three groups shared 1-octadecene, 1-tridecene, 2,4-di-tert-butylphenol, arachidonic acid, docosahexaenoic acid (DHA), eicosane, and oleylamide. We identified chemical-disease associations using the CTD tools and predict an association between docosahexaenoic and arachidonic acids and curated conditions like autistic disorder, disorders related to cocaine, Alzheimer's disease, and cognitive dysfunction. An amphetamine challenge may cause neurotoxicity in the human brain due to a decrease in omega-3 fatty acids and an increase in oxidative products. Therefore, in cases of amphetamine toxicity, supplement therapy may necessitate preventing omega-3 fatty acid deficiency.

X-band dual-polarization phased array radar (XPAR-D) possesses high temporal-spatial resolutions and plays a significant role in detecting meso- and micro-scale convective systems. However, the precipitation attenuation it endures necessitates an effective correction method. This study selected radar data from XPAR-D at the peak of Maofeng Mountain in Guangzhou during May 16-17, 2020 from three precipitation stages after quality control. Attenuation coefficients are calculated for different precipitation types through scattering simulations of raindrop size distribution (RSD) data. Drawing upon this, an attenuation correction algorithm (MZH-KDP method) is proposed for radar reflectivity factor (ZH) according to different raindrop types, and is compared to the ZH-KDP method currently in use. The results indicate that the attenuation amount of XPAR-D echoes depends on the attenuation path and echo intensity. When the attenuation path is shorter and the echo intensity is weaker, the amount of attenuation and correction is smaller. Difficulties arise when there are noticeable deviations in such a situation, which are challenging to solve via attenuation correction methods. Longer attenuation paths and stronger echoes highlight the advantages of the MZH-KDP method, while the ZH-KDP method tends to overcorrect the bias. The MZH-KDP method outperforms the ZH-KDP method for different precipitation types. The superior correction capability of the MZH-KDP method provides a significant advantage in improving the performance of XPAR-D for the detection of extreme weather.

Urban vitality, understood as a key factor for the achievement of cities’ sustainability, shows a strong relationship with urban morphology. The city theorist Jane Jacobs suggested morphologi-cal aspects to promote vital cities already in the 1960s, which remain valid in the present. How-ever, few studies in the Andean region quantitatively exemplify this. This paper aims to test the measurement of urban vitality in a neighborhood of Quito, Ecuador, called La Mariscal, inte-grating Jacobs’ approach. In particular, three urban vitality indexes are evaluated with the appli-cation of GIS software using cadastral data obtained from the municipality and field data col-lection. Results show that the context-based previous knowledge and the scale of analysis are es-sential factors in the configuration of dimensions, indicators, and spatial representation of any urban vitality index. In the study area land use mixture, contact opportunity, and accessibility dimensions are fundamental. Regarding indicators, the incorporation of the informal small-scale commerce, the quality of sidewalks, the street slope, and the good-conditioned street furniture is recommended. Finally, a hybrid representation (raster and vectorial) is suggested to precisely measure urban vitality at a block scale. Altogether, by providing a comparative approach, we in-tend to bring a useful framework for researchers and planners to study urban vitality in Andean cities.

The shortwave infrared Ge-Si photodetector will become the core device of the LiDAR optical receiver. In order to meet the urgent demand for photodetectors in the LiDAR field, we have designed and produced a 32×32 pixel Ge-Si photodetector array proposed and developed to meet the performance requirements of the detector array. A dark current detection system for fast scanning and detecting large-scale Ge-Si detector arrays is proposed and developed to achieve rapid detection of dark current in each pixel of the detector. The system was used to validate the main performance indicators of the detector array we designed, achieving rapid discrimination of array performance and rapid localization of damaged pixels. The scanning test results show that the average dark current of the detector array chip we designed is at the nano ampere level, and the proportion of bad points is less than 1%. The consistency of the array chip is high, which can meet the requirements of light detection at the receiving end of the LiDAR. This work laid the foundation for our subsequent development of a LiDAR prototype system.

Aluminum alloy (Al6061) sheet micro-hole processing is extensively used in smartphones, tablet PC, and smart wearable devices. The micro-hole processing is commonly performed using laser, micro drilling, microstamping, micro discharge, and chemical etching technologies. Micro-stamping technology is characterized by precision and rapid processing, but the precision positioning of the punch head and lower die is one of the major difficulties in micro-hole stamping, especially in manufacturing array micro-holes. This study used stamping without die technology. This technology uses an array punch head to punch the lower die holes on the base, then performs array micro-hole stamping. The experimental results show that a micro-hole array with 37 micro-holes were successfully manufactured and can be reproduced many times. Tapered array micro-holes with a high aspect ratio can be manufactured using this stamping without die technology; the micro-hole depth can be 260μm, the inlet diameter is 116μm, and the outlet diameter is 25μm. This study has successfully developed the feasibility of array micro-hole stamping technology.

The intense emergence of mucilage in the Marmara Sea in 2021 has raised concerns due to its potential impact on the global marine system. Considering the potential of mucilage threatening the diverse ecosystems, it is important to define the mucilage microbiome. However, studies dedicated to exploring the biodiversity of mucilage are limited and de novo approaches are needed to understand unexplored biodiversity of mucilage microenvironment. This study aimed to investigate mucilage and water samples from certain stations in Marmara Sea. For this reason, 11 mucilage, 2 pre-mucilage water and 3 clean sea water were collected from 16 stations. DNA isolation, shotgun metagenome sequencing and bioinformatics analysis were performed. It was revealed that the mucilage microbiome and the clean water microbiome were different from each other, and the reads that could not be assigned to any taxon (dark matter) accounted for 58% (p=0.014) of the mucilage metagenome. The clean water had a higher presence of Euryarchaeota (p=0.014), Proteobacteria (p=0.019) and Rhodothermaeota (p=0.034), while Chlamydiae (p=0.014) and Fusobacteria (p=0.034) were found in excess in the mucilage. The study produced the first comparative data on clean sea water and the mucilage microbiome using shotgun metagenomics approaches.

Microlens arrays (MLAs) which are increasingly popular micro-optical elements in compact integrated optical systems were fabricated by femtosecond direct laser write (fs-DLW) technique in the low-shrinkage SZ2080TM photoresist. High fidelity definition of 3D surfaces on IR transparent CaF2 substrates allowed to achieve ∼ 50% transmittance at chemical fingerprinting spectral region 2-5 μm wavelengths since MLAs were only ∼ 10 μm high corresponding to the numerical aperture of 0.3 (the lens height is comparable with the IR wavelength). To combine diffractive and refractive capabilities in miniaturised optical setup, a graphene oxide (GO) grating acting as a linear polariser was also fabricated by fs-DLW by ablation of a 1 μm-thick GO thin film. Such an ultra-thin GO polariser can be integrated with the fabricated MLA to add dispersion control at the focal plane. Pairs of MLAs and GO polarisers were characterised throughout visible-IR spectral window and numerical modeling was used to simulate their performance. Good match between experimental results of MLA focusing and simulations was achieved.

The aim of Predictive Maintenance, within the field of Prognostics and Health Management (PHM), is to identify and anticipate potential issues in the equipment before these become critical. The main challenge to be addressed is to assess the amount of time a piece of equipment will function effectively before it fails, which is known as Remaining Useful Life (RUL). Deep Learning (DL) models, such as Deep Convolutional Neural Networks (DCNN) and Long Short-Term Memory (LSTM) networks, have been widely adopted to address the task, with great success. However, it is well known that this kind of black box models are opaque decision systems, and it may be hard to explain its outputs to stakeholders (experts in the industrial equipment). Due to the large number of parameters that determine the behavior of these complex models, understanding the reasoning behind the predictions is challenging. This work presents a critical and comparative revision on a number of XAI methods applied on time series regression model for PM. The aim is to explore XAI methods within time series regression, which have been less studied than those for time series classification. The model used during the experimentation is a DCNN trained to predict the RUL of an aircraft engine. The methods are reviewed and compared using a set of metrics that quantifies a number of desirable properties that any XAI method should fulfill. The results show that GRAD-CAM is the most robust method, and that the best layer is not the bottom one, as is commonly seen within the context of Image Processing.

Manipulation of radiation pattern control is challenging, especially at low frequencies. In this paper, we demonstrate that acoustic metamaterials as an effective array of quadrupoles can remarkably improve the directionality of acoustic radiation at low frequencies, compared with previous metamaterials as monopole and dipole structures. The directivity of the acoustic radiation can be adjusted by changing the characteristic parameter and the symmetry of the structure, which provide a flexible method of adjustable radiation di-rections. The directionality can be further improved by constructing linear array of structure. Our work opens an approach of acoustic radiation control via quadrupolar metamaterials.

Microgrids offer flexibility in power generation in a way of using multiple renewable energy sources. In the past few years, microgrids become a very active research area in terms of design and control strategies. Most of the microgrids use DC/DC converters to connect renewable energy sources to the load. In this paper, the simulation model of a DC microgrid with three different energy sources (Lithium-ion battery (LIB), photovoltaic (PV) array, and fuel cell) and external variant power load is built with MATLAB/Simulink and the simulative results show that the stability of DC microgrid can be guaranteed by the proposed maximum power point controller MPPT. The three energy sources are connected to the load through DC/DC converters, one for each. This type of topology ensures protection for each energy source as well as optimum stability at the load.

We analyze the information that can be retrieved from the tracking parameters produced by an innovative wearable eye tracker. The latter is based on a permanent-magnet marked corneal lens and by an array of magnetoresistive detectors that measure the magnetostatic field in several positions in the eye proximity. We demonstrate that, despite missing information due to the axial symmetry of the measured field, physiological constraints or measurement conditions make possible to infer complete eye-pose data. Angular precision and accuracy achieved with the current prototypical device are also assessed and briefly discussed. The results show that the instrumentation considered is suitable as a new, moderately invasive medical diagnostics for the characterization of ocular movements and associated disorders.

Epichloë species form bioprotective endophytic symbioses with many cool-season grasses, including agriculturally important forage grasses. Despite its importance, relatively little is known about the molecular details of the interaction and the regulatory genes involved. VelA is a key global regulator in fungal secondary metabolism and development. In previous studies, we showed the requirement of velA for E. festucae to form a mutualistic interaction with Lolium perenne. We showed that VelA regulates the expression of genes encoding proteins involved in membrane transport, fungal cell wall biosynthesis, host cell wall degradation and secondary metabolism, along with several small-secreted proteins in Epichloë festucae. Here, by a comparative transcriptomics analysis on perennial ryegrass seedlings and mature plants, which are endophyte free or infected with wild type (mutualistic interaction) or mutant ∆velA E. festucae (antagonistic or incompatible interaction), regulatory effects of the endophytic interaction on perennial ryegrass development was studied. We show that ∆velA mutant associations influence the expression of genes involved in primary metabolism, secondary metabolism and response to biotic and abiotic stresses compared to wild type associations, providing an insight into processes defining mutualistic versus antagonistic interactions.

The article proposes to use a radio holography for the detection and identification of unmanned aerial vehicles (UAVs).

While low serotonergic activity is often associated with psychological disorders like depression, anxiety, mood and personality disorders, variations in serotonin also contribute to normal personality differences. Here we investigate the role of blood DNA methylation levels at individual CpG sites of two key serotonergic genes (serotonin receptor gene 1A, HTR1A; serotonin transporter gene, SLC6A4) in predicting personality of captive chimpanzees. We find associations between methylation at 9/48 CpG sites with four personality dimensions: Dominance, Reactivity/Dependability, Agreeableness and Openness. Directionality of effects were CpG location-dependent and confirmed a role of serotonergic methylation in reducing anxiety (Dominance) and aggression related personality (Reactivity/Undependability) while simultaneously promoting prosocial (Agreeableness) and exploratory personality (Openness). While early-life adversity has been shown to impact serotonergic methylation patterns in other species, here, atypical early social rearing experiences only had a modest impact on CpG methylation levels in this chimpanzee sample. While the precise environmental factors impacting serotonergic methylation in chimpanzees thus remain to be identified, our study suggests a role in shaping natural variation in animal personality. The results of this study offer a basis for future hypothesis driven testing in additional populations and species to better understand the impact of ecology and evolution on complex behavioral traits.

The number of animals bred, raised, and slaughtered each year is on the rise, resulting in increasing impacts to welfare. Farmed animals are also becoming more diverse, ranging from pigs to bees. The diversity and number of species farmed invites questions about how best to allocate currently limited resources towards safeguarding and improving welfare. This is of the utmost concern to animal welfare funders and effective altruism advocates, who are responsible for targeting the areas most likely to cause harm. For example, is tail docking worse for pigs than beak trimming is for chickens in terms of their pain, suffering, and general experience? Or are the welfare impacts equal? Answering these questions requires making an interspecies welfare comparison; a judgment about how good or bad different species fare relative to one another. Here, we outline and discuss an empirically-based methodology that aims to improve our ability to make interspecies welfare comparisons by investigating welfare range, which refers to how good or bad animals can fare. We begin our proposal with a theory of welfare. We operationalize that theory of welfare by identifying metrics that are defensible proxies for measuring welfare, including cognitive, affective, behavioral, and neuro-biological measures. We assign differential weights to those proxies that reflect their evidential value for the determinants of welfare, such as the “Delphi'' structured deliberation method with a panel of experts. Then we review the evidence and score its quality to ascertain whether a particular taxa may possess the proxies in question to construct a taxa-level welfare range profile. Finally, we use a Monte Carlo simulation to generate an overall estimate of comparative welfare range relative to our hypothetical index species - humans. Interspecies welfare comparisons will help facilitate empirically informed decision-making to streamline the allocation of resources and to ultimately better prioritize and improve animal welfare.

In this paper, a study of modeling PV cell (solar cell), PV module (solar modules) and PV array solar array) using Matlab/Simulink software is presented. This study is focused on the study to design photovoltaic cell, photovoltaic modules, photovoltaic panels and PV array (solar array) and to analyze the change in PV performance according to changes in different parameters such temperature, solar irradiation, reverse saturation current, series resistance and shunt resistance. This study shows the PV and IV characteristics curve for each model from which MPP (maximum power point) is determined. In this study, different PV and IV characteristic curves are gained for varying temperatures with specified solar irradiation conditions,s and then the MPP is tracked. The highest power output is also compared between the designed PV module and the selected PV module (MX Solar USA MX60-245)

In order to enhance the gain of antenna suitable for the airplane mounted platform, a conformal tightly coupled antenna array is investigated in this paper. Especially, three-dimensional (3-D) inkjet printing technique is used to implement the conformal property. The printing of antenna substrate and radiation layer is implemented by combining the fused deposition modelling and microdroplet injection molding technologies based on the existing 3-D printer. Here, through a unique combination of 3-D and 2-D inkjet printing of dielectric material and metallic ink, respectively, we demonstrate a monolithically integrated to a nonplanar antenna for the first time. Antenna measurements show that the complete characterization of this new process in terms of minimum feature sizes and achievable conductivities. This antenna configuration offers a high-gain performance with low-cost and rapid fabrication technique by using 3-D printing. The voltage standing wave ratio and radiation patterns are tested after adding the newly designed feed structure. Results shown the design process much efficient. Both antenna element and the array with good properties, which are in very good agreement with the specially mounted platform.

A modern definition of “deep sleep” is elusive despite being ubiquitously appreciated as an important physiological state supporting health and homeostasis. In modern times, human deep sleep is identified by specific bioelectric signatures in the electroencephalogram (EEG) emerging somewhere between periods of wakefulness. However, deep sleep has been used to describe states of quiescence well before the first electrical brain recordings in the late 1800s, highlighting its own evolution in both lay and medical literature. Furthermore, EEG states are not only ill-defined in most mammals outside of humans and laboratory rodents, but non-existent in some invertebrates. Given that all organisms rest and do so with seemingly well-defined utility, it remains a challenge linguistically, scientifically, and comparatively define what “deep sleep” means—or what it should—in a research context. Here, I explore standard definitions of deep sleep from a modern, comparative perspective, and discuss potential problems of using a strict and narrow definition of such a fleeting concept that has historically undergone significant updates. Finally, I suggest a path towards resolving inconsistencies around the meaning of “deep sleep” and consider whether it is truly reflected by any one measure.

The Fusarium fujikuroi species complex (FFSC) includes socioeconomically important pathogens that cause disease and/or mycotoxin contamination on numerous crops. Here, we used comparative genomics to elucidate processes underlying the ability of pine-associated and grass-associated FFSC species to colonize tissues of their respective plant hosts. We characterized the identity, possible functions, evolutionary origins, and chromosomal positions of the host-range-associated genes encoded by the two groups of fungi. The 72 and 47 genes identified as unique to the respective genome groups were potentially involved in diverse processes, ranging from transcription, regulation, and substrate transport, through to virulence/pathogenicity. Most emerged early during the evolution of Fusarium/FFSC and were subsequently retained only in some lineages, while some had origins outside Fusarium. Although differences in the densities of these genes were especially noticeable on the conditionally dispensable chromosome of F. temperatum (representing the grass-associates) and F. circinatum (representing the pine-associates), the host-range-associated genes tended to be located towards the subtelomeric regions of chromosomes. Taken together, these results demonstrate that multiple mechanisms drive the emergence of genes in grass- and pine-associated FFSC taxa examined and highlighted the diversity of molecular processes potentially underlying niche-specificity in these and other Fusarium species.

Synechococcus sp. PCC 11901 reportedly demonstrates the highest, sustained growth of any known cyanobacterium under optimized conditions. Due to its recent discovery our knowledge of its biology, including the factors underlying sustained, fast growth, is limited. Furthermore, tools specific for genetic manipulation of PCC 11901 are not established. Here, we demonstrate that PCC 11901 shows faster growth than other model cyanobacteria, including the fast-growing species Synechococcus elongatus UTEX 2973, under optimal growth conditions for UTEX 2973. Comparative genomics between PCC 11901 and Synechocystis sp. PCC 6803 reveal conservation of most metabolic pathways but PCC 11901 has a simplified electron transport chain and reduced light-harvesting complex. This may underlie its superior light utilization, reduced photoinhibition and higher photosynthetic and respiratory rates. To aid biotechnology applications we developed a vitamin B12 auxotrophic mutant but were unable to generate unmarked knockouts using two negative selectable markers, suggesting that recombinase- or CRISPR-based approaches may be required for repeated genetic manipulation. Overall, this study establishes PCC 11901 as one of the most promising species currently available for cyanobacterial biotechnology and provides a useful set of bioinformatics tools and strains for advancing this field, in addition to insights into the factors underlying its fast growth phenotype.

Rhodovulum spp. are anoxygenic photosynthetic purple bacteria with versatile metabolisms, including the ability to obtain electrons from minerals in their environment to drive photosynthesis, a relatively novel process called phototrophic extracellular electron uptake (pEEU). Recently, our group isolated 15 strains of R. sulfidophilum to observe this metabolism in marine phototrophs. Our group previously observed carbon dioxide fixation coupled to phototrophic iron oxidation (photoferrotrophy) and pEEU in AB26 and identified a novel di-heme c¬-type cytochrome EeuP important for pEEU but not photoferrotrophy. Taxonomic re-evaluation based on 16S and pufM phylogenetic analyses led us to re-classify two isolates, AB26 and AB19, as Rhodovulum visakhapatnamense. The AB26 genome consists of 4,380,746 base-pairs, including two plasmids, and encodes 4,296 predicted protein-coding genes. AB26 contains 22 histidine kinases, 20 response regulators, and dedicates ~16% of its genome to transport. Transcriptomic data under aerobic, photoheterotrophy, photoautotrophy, and pEEU reveals how gene expression varies between metabolisms. Lastly, we use transcriptomic data for a comparative genomic analysis of potential pEEU-relevant genes between all 15 isolates. With these data we identify potential pEEU capable phototrophs within these isolates, and likely molecular mechanisms of pEEU.

Wireless power transfer promises to revolutionize the way we use and power mobile devices. However, low transfer efficiencies prevent this technology from seeing wide scale real-world adoption. The aim of this work is to use quasioptics to develop a system composed of a dielectric lens fed by a phased array to reduce spillover losses, increasing the beam efficiency, while working on the antenna system’s Fresnel zone. The DC-RF electronics, digital beamforming and beam-steering by an FPGA, and radiating 4x4 microstrip patch phased array have been developed and experimented upon, while the lens has been designed and simulated. This paper details these preliminary results, where the phased array radiation pattern was measured, showing that the beam is being generated and steered as expected, prompting the lens construction for the complete system experimentation.

Since the 1970s, researchers in international relations have asserted that the enhancement of interdependence between nations can reduce conflicts among them (Keohane and Nye 1973). Thus, interdependency between nations is regarded as desirable for the stability of the countries' networks. On the other hand, there has been no confirmation of empirical data on the benevolent effects of interdependency on the nations' networks. This article aims to analyze the concept of interdependence into reciprocity and dependence, leading to quantifying both of them. To assess the usefulness of this approach, the empirical analysis of trade relations among five countries, namely, THE U.S.., China, Germany, Japan, and Korea from 1992 to 2020 was empirically analyzed with the aid of reciprocity index (R) and dependency index (D).

As commonly used chemical plasticizers in plastic products, phthalate esters had become a serious ubiquitous environmental pollutant, such as in soil of plastic film mulch culture. Microbial degradation or transformation was regarded as a suitable strategy to solve the phthalate esters pollution. Thus, a new phthalate esters degrading strain Gordonia sp. GZ-YC7 was isolated in this study, which exhibited the highest di-(2-ethylhexyl) phthalate degradation efficiency under 1000 mg/L and the strongest tolerance to 4000 mg/L. The comparative genomic analysis showed that there exist diverse degradation pathways for various phthalate esters such as di-(2-ethylhexyl) phthalate and dibutyl phthalate in Gordonia sp. GZ-YC7, which possibly contributes to its broad substrate spectrum, high degrading efficiency and high tolerance to phthalate esters. Gordonia sp. GZ-YC7 is potential for bioremediation of phthalate esters in polluted soil environments.

The emergence of the COVID-19 pandemics prompted a fast development of novel diagnostic methods of the etiologic virus SARS-CoV-2. Methods based on CRISPR-Cas systems have been particularly promising because they can achieve a similar sensitivity and specificity to the golden standard RT-qPCR, especially when coupled to an isothermal pre-amplification step. Furthermore, they have also solved inherent limitations of RT-qPCR that impede its decentralized use and deployment in the field, such as the need for expensive equipment, high cost per reaction, and delivery of results in hours, among others. In this review, we evaluate publicly available methods to detect SARS-CoV-2 that are based on CRISPR-Cas and isothermal amplification. We critically analyze the steps required to obtain a successful result from clinical samples and pinpoint key experimental conditions and parameters that could be optimized or modified to improve clinical and analytical outputs. The COVID outbreak has propelled intensive research in a short time, which is paving the way to develop effective and very promising CRISPR-Cas systems for the precise detection of SARS-CoV-2. This review could also serve as an introductory guide to new labs delving into this technology.

The literature on substance use usually extracts conclusions from data with correlational methods. Our study shows the usefulness of complementing ordered logistic regression (OLR) and fuzzy set qualitative comparative analysis (fsQCA) to assess factors inducing cannabis consumption in a sample of 1,935 teenagers. OLR showed a significant influence of gender (odd ratio (OR) =0.383, p<0.0001), parental monitoring (OR=0.587, p=0.0201); religiousness (OR=0.476, p=0.006); parental tolerance to substance use (OR=42.01, p<0.0001) and having close peers that consume substances (OR=5.60, p<0.0001). FsQCA has allowed fitting linkages between factors from a complementary perspective. (1) Coverage (cov) and consistency (cons) attained by solutions explaining use (cons=0.808, cov=0.357) are clearly lower than by recipes of non-use (cons=0.952, cov=0.869) (2) The interaction of gender, a tolerant family to use and the attitude toward substances by peers is very consistent to explain cannabis use. (3) The most important recipe explaining resistance to cannabis is simply parental disagreement with substance consumption (cons=0.956, cov=0.861) (4) Factors as gender, religiosity, parental monitoring and age show also a relevant impact on attitude toward cannabis use. However, whereas some of them impact symmetrically on use and non-use this does not follow in factors such as parental monitoring or age.

With the current technological transformation in the automotive industry, autonomous vehicles are getting closer to the Society of Automative Engineers (SAE) automation level 5. This level corresponds to the full vehicle automation, where the driving system autonomously monitors and navigates the environment. With SAE-level 5, the concept of a Shared Autonomous Vehicle (SAV) will soon become a reality and mainstream. The main purpose of an SAV is to allow unrelated passengers to share an autonomous vehicle without a driver/moderator inside the shared space. However, to ensure their safety and well-being until they reach their final destination, it is required an active monitoring of all passengers. In this context, this article presents a microphone-based sensor system that is able to localize sound events inside an SAV. The solution is composed of a Micro-Electro-Mechanical System (MEMS) microphone array with a circular geometry connected to an embedded processing platform that resorts to Field-Programmable Gate Array (FPGA) technology to successfully process in hardware the sound localization algorithms.

Antibiotics are in excessive use that has extensively increased antimicrobial resistance worldwide which has become the major public concern among the countries. To control this threat proper monitoring of the antimicrobial usage along with the increasing rate of antimicrobial resistance (AMR) is required. Further, surveillance of both the parameters is highly recommended for comparing the differences in distinct countries. Moreover, alternatives for antibiotics are also surveyed and are being researched for quick use in the near future. AMR is an issue that needs immense attention from various sectors. Thus, intervention of multisector is highly encouraged for better outcomes. One Health is one of the approaches that play a vital role in resolving this issue. In this research paper, six different European countries are discussed in terms of antimicrobial usage and AMR in the human and livestock sectors with the help of literature study and various reports published by different organizations. Data study has been conducted to collect the data for comparison study. Data sources of AMR and antimicrobial usage are analyzed and a thorough comparison of both antimicrobial use and AMR are conducted. Also, the application of One Health is studied for a balanced system. This article provides about various surveillance systems that are formed only to keep a track on the upcoming situation of AMR and the consumption of antimicrobials by the humans as well as animals. The article does not provide about all the details required to monitor the AMR issue but firmly allow the readers to get acknowledged with the broad information about the antimicrobial resistance across the six countries of Europe. The regular data collected by the different organizations play a vital role in monitoring the status of AMR and antimicrobial usage by humans and in live stocks. These annual reports have highly helped the government to decide for alternatives and have focused in many training activities to combat the AMR situation globally. AMR prevention is linked to the One Health concept. As antibiotic resistance genes persist on an interface between environment and animal and animal health, an approach is required in all three areas that stress the concept of 'One Approach to Health.'

Ultrasound based haptic feedback is a potential technology for human-computer interaction (HCI) with the advantages of low cost, low power consumption and controlled force. In this paper, the phase optimization for multipoint haptic feedback based on ultrasound array is investigated and the corresponding experimental verification is provided. A mathematical model of acoustic pressure is established for the ultrasound array and then a phase optimization model for an ultrasound transducer is constructed. We propose a pseudo-inverse (PINV) algorithm to accurately determine the phase contribution of each transducer in the ultrasound array. By controlling the phase difference of the ultrasound array, the multipoint focusing forces are formed leading to various shapes such as geometries and letters that can be visualized. Because the unconstrained PINV solution results in unequal amplitudes for each transducer, a weighted amplitude iterative optimization is deployed to further optimize the phase solution, by which the uniform amplitude distributions of each transducer are obtained. For the purpose of experimental verifications, a platform of ultrasound haptic feedback consisting of a Field Programmable Gate Array (FPGA), an electrical circuit and an ultrasound transducer array is prototyped. The haptic performances of single point, multiple points and dynamic trajectory were verified by controlling the ultrasound force exerted on the liquid surface. The experimental results demonstrate that the proposed phase optimization model and theoretical results are effective and feasible, and the acoustic pressure distribution is consistent with the simulation results.

Avian mutations in vaccine strains obtained from embryonated eggs could impair vaccine effec-tiveness. We performed a systematic review and meta-analysis of the adjusted relative vaccine effectiveness (arVE) of seed cell-cultured influenza vaccines (ccIV) compared to egg-based influ-enza vaccines (eIV) in preventing laboratory-confirmed influenza related outcomes (IRO) or IRO by clinical codes, in subjects 18 and over. We completed the literature search in January 2021; ap-plied exclusion criteria, evaluated risk of bias of the evidence, and performed heterogeneity, pub-lication bias, qualitative, quantitative and sensitivity analyses. All estimates were computed us-ing a random approach. International Prospective Register of Systematic Reviews, CRD42021228290. We identified 12 publications that reported 26 adjusted arVE results. Five publications reported 13 laboratory confirmed arVE and seven reported 13 code-ascertained arVE. Nine publications with 22 results were at low risk of bias. Heterogeneity was explained by season and risk of bias. We found a significant 11% (8 to 14%) adjusted arVE favoring ccIV in preventing any IRO in the 2017-2018 influenza season. The arVE was 3% (-01 to 7%) in the 2018-2019 influenza season. We found moderate evidence of a significant advantage of the ccIV in preventing IRO, compared to eIV, in a well-matched A(H3N2) predominant season.

The testing requirements of the active phased array antennas are very different from those of traditional passive antennas, due to its beam steering capability. Usually, each beam profile of the active phased array needs a separate radiation pattern test, which makes the overall testing time extremely long. Thus the traditional antenna test method can no longer meet the efficiency and cost requirements of new active phased array antennas test. In this paper, a fast test method tailored for phased array antennas is proposed that offers significantly reduced testing time at the expense of slight sacrifice of the accuracy. Using the simulated element pattern in array and ideal port excitation, the beam profile in any direction can be predicted by testing only a certain beam profile. Through theoretical derivation and experiments, the effectiveness of the method is verified, and the testing efficiency of the phased array antenna is demonstrated to be improved by ten times or even more.

With the increased use of simulation based training using animal models for the education of surgical and anaesthetic techniques, an increased understanding of the anatomy of such models and how they compare to humans is required. The transversus abdominis plane block is a regional anaesthetic technique that requires an understanding of the abdominal wall anatomy along with proficient ultrasound use. The current review aims to compare the anatomy of the abdominal wall across species, particularly focussing on the pertinent differences within the class of mammals, and secondarily, it aims to address the implications of these differences for simulation based training of the transversus abdominis plane block. To achieve this, the PubMed, Web of Science and Google Scholar databases were searched for relevant literature. The mammalian abdominal wall differs in its musculature, vasculature or innervation from that of amphibians, birds or reptiles, however, among species of mammals, the structure of the abdominal wall follows a similar framework. Particular differences among mammals include the additional muscular layer of the panniculus carnosus found in most mammals other than humans, the variable arterial origins and dominant vascular supply of the abdominal wall and the number of thoracolumbar nerves innervating the abdominal wall. When using animal models for simulation based training, the pig is recommended for the transversus abdominis plane block given its closely homologous abdominal wall structure, availability and larger comparative size.