Reference Template Research Articles

Leveraging Transfer Superposition Theory for StableState Visual Evoked Potential Cross-Subject Frequency Recognition.

In steady-state visual evoked potential (SSVEP)based brain-computer interfaces (BCIs), various spatial filtering methods based on individual calibration data have been proposed to alleviate the interference of spontaneous activities in SSVEP signals for enhancing the SSVEP detection performance. However, the necessary calibration procedures take time, cause visual fatigue and reduce usability. For the calibration-free scenario, we propose a cross-subject frequency identification method based on transfer superimposed theory for SSVEP frequency decoding. First, a multi-channel signal decomposition model was constructed. Next, we used the cross least squares iterative method to create individual specific transfer spatial filters as well as source subject transfer superposition templates in the source subject. Then, we identified common knowledge among source subjects using a prototype spatial filter to make common transfer spatial filters and common impulse responses. Following, we reconstructed a global transfer superimposition template with SSVEP frequency characteristics. Finally, an ensemble cross-subject transfer learning method was proposed for SSVEP frequency recognition by combining the sourcesubject transfer mode, the global transfer mode, and the sinecosine reference template. Offline tests on two public datasets show that the proposed method significantly outperforms the FBCCA, TTCCA, and CSSFT methods. More importantly, the proposed method can be directly used in online SSVEP recognition without calibration. The proposed algorithm was robust, which is important for a practical BCI.

Advanced Object Tracking through Conditional Online Updates and Noise Suppression

Object tracking under complex environmental conditions, such as background clutter, occlusion, and rapid motion, presents significant challenges. This paper addresses these issues by proposing a tracking algorithm integrating background suppression, target region enhancement, and an adaptive online template update mechanism to improve tracking accuracy. The proposed method uses the initial bounding box of the target object as a reference template and selectively updates specific regions online to suppress noise and retain critical features. We evaluated the proposed method using the OTB dataset to validate it. The baseline model without the proposed method showed a success rate of 0.417 and a precision of 0.586, while the algorithm with the proposed method achieved improved values of 0.524 and 0.728, respectively. Qualitative evaluations further confirmed the robustness of the proposed method, demonstrating high performance in scenarios with occlusion and complex backgrounds. Rather than updating all regions indiscriminately, the proposed method selectively updates the template using representative values from the target object's information. This selective update mechanism ensures the incorporation of the most relevant and accurate features, enabling the algorithm to adapt to changes in the target's appearance while minimizing noise integration. Emphasizing the feature regions and suppressing noise are also critical for maintaining a clear and precise representation of the target object, reducing the likelihood of confusion by irrelevant background information. Future research will focus on developing balanced update strategies that integrate new information while maintaining stable and reliable target characteristics.

Stability of the Tyrosyl Radical in the Ribonucleotide Reductase Beta Subunit of Arcobacter bivalviorum

Arcobacter spp., such as Arcobacter bivalviorum (A. bivalviorum), are free-living organisms found in diverse environments and associated with animals. They are considered emerging enteropathogens and potential zoonotic agents. Ribonucleotide reductase (RNR) is the key enzyme that is used to convert ribonucleotides into deoxyribonucleoside triphosphates (dNTPs). This process utilises radical-based chemistry and is crucial for DNA biosynthesis and repair. There are three RNR classes, with class I RNR the most studied, present in A. bivalviorum, eukaryotes, and many prokaryotes. Class I RNRs are further divided into three subclasses: Ia, Ib, and Ic. Class Ib RNRs use a dimanganese-oxo centre, unlike class Ia RNRs, which use a diiron-oxo centre. A. bivalviorum possesses a class Ia enzyme that requires a diferric tyrosyl radical cofactor located within its beta (β) subunit. Indeed, both the efficiency and fidelity of DNA synthesis are influenced by the stability of the tyrosyl radical (Y•) in the RNR, which is a critical aspect of its enzymatic function. This study investigates the stability of the Y-radical (Y•) site within the RNR β subunit of A. bivalviorum and the nature of the neighbouring amino acid residues. To achieve these goals, we developed a model of the RNR β subunit of A. bivalviorum, using the RNR β subunit of Aquifex aeolicus as a reference template (7aik.1. A PDB). The results provide some important details about the radical site and its surrounding residues, highlighting the influence of the protein structure on the stability of the radical. These findings may guide the development of novel inhibitors targeting this enzyme in A. bivalviorum.

A novel speaker verification approach featuring multidomain acoustics based on the weighted city block Minkowski distance

AbstractAccess control is vital in interconnected environments like the Internet of Things, Industry 4.0, and smart connectivity, ensuring authorized access for security. Biometric‐based access, particularly speaker verification (SV), enhances security with unique vocal features, offering nonintrusive authentication with continuous monitoring. Single‐domain features prove insufficient in distinguishing similar traits, prompting latest SV advancements to adopt multidomain‐based speech features. This paradigm addresses the limitations of single‐domain features by amalgamating the merits of individual domains, establishing a cutting‐edge approach. It utilizes cepstral–frequency–time domain feature fusion, achieved via cepstral mean‐variance normalization for generalizability. The weighted city block Minkowski distance is proposed to compare reference and test speech templates. Parameters are computed based on the confusion matrix, template matching distance functions, dynamic acoustic conditions, and additive white Gaussian noise. A deep convolutional neural network classifier is assessed on open‐source LibriSpeech and Speaker in the Wild corpora, surpassing the current methodologies.

De Novo Rational Design of Peptide-Based Protein-Protein Inhibitors (Pep-PPIs) Approach by Mapping the Interaction Motifs of the PP Interface and Physicochemical Filtration: A Case on p25-Cdk5-Mediated Neurodegenerative Diseases.

Protein-protein interactions, or PPIs, are a part of every biological activity and have been linked to a number of diseases, including cancer, infectious diseases, and neurological disorders. As such, targeting PPIs is considered a strategic and vital approach in the development of new medications. Nonetheless, the wide and flat contact interface makes it difficult to find small-molecule PP inhibitors. An alternative strategy would be to use the PPI interaction motifs as building blocks for the design of peptide-based inhibitors. Herein, we designed 12-mer peptide inhibitors to target p25-inducing-cyclin-dependent kinase (Cdk5) hyperregulation, a PPI that has been shown to perpetuate neuroinflammation, which is one of the major causal implications of neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, and frontotemporal dementia. We generated a library of 5 062 500 peptide combination sequences (PCS) derived from the interaction motif of Cdk5/p25 PP interface. The 20 amino acids were differentiated into six groups, namely, hydrophobic (aliphatic), aromatic, basic, acidic, unique, and polar uncharged, on the basis of their physiochemical properties. To preserve the interaction motif necessary for ideal binding, de novo modeling of all possible peptide sequence substitutions was considered. A set of filters, backed by the Support Vector Machine (SVM) algorithm, was then used to create a shortlisted custom peptide library that met specific bioavailability, toxicity, and therapeutic relevance, leading to a refined library of 15 PCS. A greedy algorithm and coarse-grained force field were used to predict peptide structure and folding before subsequent modeling studies. Molecular docking was performed to estimate the relative binding affinities, and out of the top hits, Pep15 was subjected to molecular dynamics simulations and binding free-energy calculations in comparison to a known peptide inhibitor with experimental data (template peptide). Interestingly, the identified peptide through our protocol, Pep15, was found to show a significantly higher binding affinity than the reference template peptide (-48.10 ± 0.23 kcal/moland -17.53 ± 0.27 kcal/mol, respectively). In comparison to the template peptide, Pep15 was found to possess a more compact and buried surface area, tighter binding landscape, and reduced conformational variability, leading to enhanced structural and kinetic stability of the Cdk5/p25 complex. Notably, both peptide inhibitors were found to have a minimal impact on the architectural integrity of the Cdk5/p25 secondary structure. Herein, we propose Pep15 as a novel and potentially disruptive peptide drug for Cdk5/p25-mediated neurodegenerative phenotypes that require further clinical investigation. The systematic protocol and findings of this report would serve as a valuable tool in the identification of critical PPI interface reactive residues, designing of analogs, and identification of more potent peptide-based PPI inhibitors.

Estimation of waveform deformation with the matched filter

In many particle physics experiments the data processing is based on the analysis of the digitized waveforms provided by the detector. While the waveform amplitude is usually correlated to the event energy, the shape may carry useful information for event discrimination. Thanks to the high signal to noise ratio they provide, matched filters are often applied. Their original design is however intended for the estimation of the waveform amplitude only. In this work we introduce an analytical extension of the original matched filter for the estimation of a possible shape deformation with respect to a reference template. The new filter is validated on simulations and, with respect to shape parameters calculated on unfiltered waveforms or derived from the original matched filter, it improves the discrimination capability by at least a factor 2 both at low and high signal to noise ratios, making it applicable to the data of several experiments.

Effect of implantable cardioverter defibrillator intracardiac electrogram morphology changes on hospitalization and life quality

Abstract Background Implantable Cardioverter Defibrillators (ICD) are standard therapy for patients at risk of life-threatening ventricular tachyarrhythmias. ICDs use morphology discrimination to compare ventricular electrogram during tachycardia with reference template during baseline rhythm. Baseline morphology match score (MMS) changes may predict arrhythmic events, but usefulness as a parameter for heart failure (HF) is still unknown. Methods The prospective single-center study included consecutive 88 patients undergoing device control at cardiology department from July 2022 to May 2023. Inclusion criteria were patients implanted with ICD or CRT for at least 3 months; the exclusion criteria were defined as communication barriers (n=1), depleted device battery during checks (n=1), total AV block (n=3), and auto-template activation (n=4). The data were analysed for changes in the baseline (MMS) relationship with demographic, clinical characteristics, quality of life (QOL), and hospitalisation with HF. Results We analyzed 79 patients with a mean age 64,9 13,6 and an average MMS of 98 1,8 morphology. During follow-up there were 12 (15%) patients hospitalized due to HF. ROC curve analysis showed that a MMS ≤ 97% had 73% sensitivity and 59% specificity for hospitalization (p: 0,033 Area 0.695). No significant differences were observed in demographics between the two groups. Although there was no significant difference in EF and BNP levels, patients with MMS <97% had lower QOL scores and more hospitalizations for heart failure (HF). Conclusion EGM baseline MMS changes in ICD were associated with hospitalization for HF and QOL, apart from arrhythmia detection indications. It may be a follow-up parameter for HF, in addition to the current device algorithms.Graphical AbstractTable 1

Monitoring hPSC Genomic Stability in the Chromosome 20q Region by ddPCR

Copy number increases involving chromosome 20q with gain of the gene BCL2L1 are a prevalent form of genomic instability in hPSCs. In addition to large aneuploidies, findings in this region often include microamplifications that are too small to detect by G-banded karyotyping. Gene editing procedures warrant especially close monitoring of 20q genomic stability because they involve p53-activating stressors that select for the survival of BCL2L1-aneuploid cells. Here we describe an optimized strategy for detecting BCL2L1 copy number increases in hPSC cultures using duplexed droplet digital PCR (ddPCR) with genomic DNA or cell lysate as the starting material. The procedure consists of droplet generation, thermocycling, droplet reading and data analysis. The expected result is a copy number estimate derived by comparing the number of droplets positive for BCL2L1 to the number positive for a reference template, PVRL2. This procedure generates same-day screening results for 1 to 96 samples, providing a convenient option for screening hPSC cultures that is easily integrated into a gene editing workflow.

A calibration-free c-VEP based BCI employing narrow-band random sequences

Objective. Code-modulated visual evoked potential (c-VEP) based brain–computer interfaces (BCIs) exhibit high encoding efficiency. Nevertheless, the majority of c-VEP based BCIs necessitate an initial training or calibration session, particularly when the number of targets expands, which impedes the practicality. To address this predicament, this study introduces a calibration-free c-VEP based BCI employing narrow-band random sequences. Approach. For the encoding method, a series of random sequences were generated within a specific frequency band. The c-VEP signals were subsequently elicited through the application of on-type grid flashes that were modulated by these sequences. For the calibration-free decoding algorithm, filter-bank canonical correlation analysis (FBCCA) was utilized with the reference templates generated from the original sequences. Thirty-five subjects participated into an online BCI experiment. The performances of c-VEP based BCIs utilizing narrow-band random sequences with frequency bands of 15–25 Hz (NBRS-15) and 8–16 Hz (NBRS-8) were compared with that of a steady-state visual evoked potential (SSVEP) based BCI within a frequency range of 8–15.8 Hz. Main results. The offline analysis results demonstrated a substantial correlation between the c-VEPs and the original narrow-band random sequences. After parameter optimization, the calibration-free system employing the NBRS-15 frequency band achieved an average information transfer rate (ITR) of 78.56 ± 37.03 bits/min, which exhibited no significant difference compared to the performance of the SSVEP based system when utilizing FBCCA. The proposed system achieved an average ITR of 102.1 ± 57.59 bits/min in a simulation of a 1000-target BCI system. Significance. This study introduces a novel calibration-free c-VEP based BCI system employing narrow-band random sequences and shows great potential of the proposed system in achieving a large number of targets and high ITR.

Towards Conceptualizing a Policy and Promoting Advocacy for People With Color Vision Deficiency: Addressing the Importance of Color Vision Deficiency in India and Creating a Global Reference Template

Color vision is crucial for daily life, and conditions such as color blindness and deficiencies can negatively impact one's quality of life and livelihood. According to a study in India there was an increase in the prevalence of color vision deficiency (CVD) among children and young adult teenagers, who are losing empowering opportunities in education and academics. However, this trend can be managed with evidence-based new interventions and objectives from India's developing nation models. This policy paper mainly highlights the need for effective strategies to address this issue. Early identification of CVD is crucial for effective interventions and rehabilitation to reduce medical, behavioral, and economic burdens on patients, families, and society. Strategies include policy prescriptions, advocacy, public health campaigns, investing in a trained workforce, and using technology to facilitate early screening in educational institutes. These strategies aim to address the growing healthcare crisis of CVD.

Thermal control materials of carbon/SiO2 composites with a honeycomb structure.

Anisotropic composite thermal control materials show efficient thermal management ability, which can not only improve the heat flow in the direction of high thermal conductivity and prevent local overheating, but also reduce the heat flow in the direction of the low thermal conductivity and improve thermal insulation. In this paper, the anisotropic microstructure of natural wood (e.g. poplar) was used as a reference template. The filling of the SiO2 aerogel into the multi-layer pore structure and microtubule structure originally occupied by lignin was controlled by the process of the axial self-adsorption, limited sol-gel and natural drying. The anisotropic composite biomimetic thermal control materials were prepared by high temperature carbonization and the thermal control properties were evaluated. The anisotropic carbon/SiO2 (ACS) composite biomimetic thermal control material obtained after carbonization inherits the anisotropic microstructure. The axial thermal conductivity of the ACS composite biomimetic thermal control material is mainly determined by the thermal conductivity of the carbon composite microtubule structure. The SiO2 aerogel filled between carbon composite microtubules and the abundant axial microcracks endow the ACS composite biomimetic thermal control material with excellent radial thermal insulation performance. The maximum specific surface area of the ACS composite biomimetic thermal control material is 183 m2 g-1, and the maximum density is 517.8 ± 55.9 kg m-3. The maximum axial thermal conductivity of the ACS composite biomimetic thermal control material is 0.73 ± 0.07 W m-1 k-1, and the radial thermal conductivity is 0.28 ± 0.01 W m-1 k-1. The maximum ratio of the axial thermal conductivity to radial thermal conductivity of the ACS composite biomimetic thermal control material is 3.3.

Multi-Stimulus Least-Squares Transformation With Online Adaptation Scheme to Reduce Calibration Effort for SSVEP-Based BCIs.

The proposed ms-LST-OA consists of two parts. Firstly, to improve the precision of the transformation matrices, we propose the multi-stimulus LST (ms-LST) using cross-stimulus learning scheme as the cross-subject data transformation method. The ms-LST uses the data from neighboring stimuli to construct a higher precision transformation matrix for each stimulus to reduce the differences between transformed data and real data. Secondly, to further optimize the constructed spatial filters and reference templates, we use an online adaptation scheme to learn more features of the EEG signals of the target subject through an iterative process trial-by-trial. ms-LST-OA performance was measured for three datasets (Benchmark Dataset, BETA Dataset, and UCSD Dataset). Using few calibration data, the ITR of ms-LST-OA achieved 210.01±10.10 bits/min, 172.31±7.26 bits/min, and 139.04±14.90 bits/min for all three datasets, respectively. Using ms-LST-OA can reduce calibration effort for SSVEP-based BCIs.

Facilitating the use of the target product profile in academic research

AbstractBackgroundTarget product profiles (TPP) were first defined by industry and supported by FDA to address user needs and guide communication in all phases of drug development. However, heterogeneity in practical use hurdles uptake in academic research. Our study aims to facilitate uptake by outlining a reference template to be adapted to dementia research.MethodsWe conducted a systematic review to extract structural characteristics, along with differences and commonalities across TPPs used in different product development (e.g., drugs vs diagnostics). We included data from peer‐reviewed publications on TPPs content (i.e., developing, revising, or mentioning a TPP), product type (drug, diagnostics, vaccine, medical device, other), disease category (infectious, non‐infectious diseases), specific disease , TPP features of the target profile, and levels of compliance for each feature.Results327 of 1297 identified records were eligible for full‐text review. Preliminary data extraction from 20 papers shows that: Content : 45% (n = 9) developed a new TPP, 10% (n = 2) revised a predefined TPP; 45% only mentioned TPPs (n = 9). Product : of the nine papers that developed a new TPP, 77.8% (n = 7) were for drug and 22.2% (n = 2) for diagnostics development. Disease category : 70% (n = 14) used TPPs in infectious diseases while 30% (n = 6) were in non‐infectious diseases. So far, no publication reported using TPPs in dementia. TPP features for different product types from the 11 publications that developed or revised TPPs: 39 features were extracted from TPPs for diagnostic development, 11 of which (28%) were in common. We extracted 35 features from TPPs for drug development, 9 of which (27.5%) were in common. Levels of compliance ranged between one (n = 5, 45.5%) to two (n = 5, 45.5%) levels, corresponding to conservative and optimistic levels. One (9%) did not report targeted levels of compliance.ConclusionTPPs are not frequently used by academic researchers. Despite being a useful tool enhancing product development, its considerable heterogeneity in structure renders its adaptation challenging. Completing data extraction and comparing the outcome with opinion leader’s assessment and formal guidance (e.g., from WHO) will facilitate drawing a comprehensive picture of common TPP features to derive a consistent and comprehensive template and facilitate its use in academic dementia research.

Visual Tooth Color Determination with Different Reference Scales as an Exercise in Dental Students' Education.

Visual color determination (VCD) requires color competence and individual training. The aim of this study was to evaluate the deviations in students' VCD with two different reference scales. The research hypothesis was that none of the color references would provide a better result. Participants evaluated nine templates randomly using two reference scales (VITA-classical (VC) and 3D-Master-Toothguide (3DM_TG)). The color distance to the chosen color (ΔEab) was calculated in the CIELAB 2000. The sum's changes in the parameters (LCh°) represented the target variable. Results were evaluated with non-parametric, rank-scaled methods, utilizing the median with a 25%-75% quartile. The significance level (α = 0.05) is determined using the Student's t-test. The mean ± 95%CI (SD) was -1.27 ± -1.09 (3.18); the median ΔE00 was -1.49 (-1.97; 0.96) for dC3DM_TG. The determination with VC showed noticeable differences (dCVC), with a mean ΔE00 of 0.00 ± 0.00 (2.20) and a median ΔE00 of 0.00 (1.17; 1.71). The standard error was 0.19 for the dCVC and 0.27 for the dC3DM_TG. dC3DM_TG vs. dCVC showed significant differences at p < 0.001. The dental student's VCD resulted in color deviations, regardless of the reference template used. The color deviations in hue and chroma were comparable, regardless of the reference scale. VCD's early implementation in dental education is useful to avoid shade misjudgments and potentially expensive remakes of dentures.

Structure-Based In Silico Screening of Marine Phlorotannins for Potential Walrus Calicivirus Inhibitor.

A new calicivirus isolated from a walrus was reported in 2004. Since unknown marine mammalian zoonotic viruses could pose great risks to human health, this study aimed to develop therapeutic countermeasures to quell any potential outbreak of a pandemic caused by this virus. We first generated a 3D model of the walrus calicivirus capsid protein and identified compounds from marine natural products, especially phlorotannins, as potential walrus calicivirus inhibitors. A 3D model of the target protein was generated using homology modeling based on two publicly available template sequences. The sequence of the capsid protein exhibited 31.3% identity and 42.7% similarity with the reference templates. The accuracy and reliability of the predicted residues were validated via Ramachandran plotting. Molecular docking simulations were performed between the capsid protein 3D model and 17 phlorotannins. Among them, five phlorotannins demonstrated markedly stable docking profiles; in particular, 2,7-phloroglucinol-6,6-bieckol showed favorable structural integrity and stability during molecular dynamics simulations. The results indicate that the phlorotannins are promising walrus calicivirus inhibitors. Overall, the study findings showcase the rapid turnaround of in silico-based drug discovery approaches, providing useful insights for developing potential therapies against novel pathogenic viruses, especially when the 3D structures of the viruses remain experimentally unknown.

Analyzing Thalamocortical Tract-Tracing Experiments in a Common Reference Space

Current mesoscale connectivity atlases provide limited information about the organization of thalamocortical projections in the mouse brain. Labeling the projections of spatially restricted neuron populations in thalamus can provide a functionally relevant level of connectomic analysis, but these need to be integrated within the same common reference space. Here, we present a pipeline for the segmentation, registration, integration and analysis of multiple tract-tracing experiments. The key difference with other workflows is that the data is transformed to fit the reference template. As a test-case, we investigated the axonal projections and intranuclear arrangement of seven neuronal populations of the ventral posteromedial nucleus of the thalamus (VPM), which we labeled with an anterograde tracer. Their soma positions corresponded, from dorsal to ventral, to cortical representations of the whiskers, nose and mouth. They strongly targeted layer 4, with the majority exclusively targeting one cortical area and the ones in ventrolateral VPM branching to multiple somatosensory areas. We found that our experiments were more topographically precise than similar experiments from the Allen Institute and projections to the primary somatosensory area were in agreement with single-neuron morphological reconstructions from publicly available databases. This pilot study sets the basis for a shared virtual connectivity atlas that could be enriched with additional data for studying the topographical organization of different thalamic nuclei. The pipeline is accessible with only minimal programming skills via a Jupyter Notebook, and offers multiple visualization tools such as cortical flatmaps, subcortical plots and 3D renderings and can be used with custom anatomical delineations.

Analysis and Evaluation of Ecotourism Resources in China Based on RIAM Model

Abstract A comprehensive assessment of ecotourism resources is needed for the sustainable development of ecotourism in China. In this paper, based on the scientific classification of ecological resources, the RIAM model for the environmental impact assessment of ecotourism resources is established, and the indicator sets are obtained based on a fast matrix calculation combining semi-quantitative and qualitative. Then, the hierarchical analysis method is used to calculate the weights of different indicators for the established indicator sets. Finally, an empirical analysis of the resources of Huangtengxia Ecotourism Area was conducted based on the comprehensive assessment model. It was found that the bio-ecological impact index of Huangtengxia was [6,8,-2,15,7], and the economic return impact index was [4,7,10,-5,8]. Taken together, the overall evaluation of ecological tourism resources in Huangtengxia has a total score of 72, which belongs to the middle to the upper level of similar tourism resource regions in China. This study establishes a scientific evaluation system of ecotourism resources in Huangtengxia, which provides a valuable reference template for the evaluation of ecotourism resources in China.

Digital Twin Applications in Manufacturing Industry: A Case Study from a German Multi-National

This article examines how digital twins have been used in a multi-national corporation, what technologies have been used, what benefits have been delivered, and the significance of people- and process-related issues in achieving successful implementation. A qualitative, inductive research method is used, based on interviews provided by key personnel involved in three digital twin projects. The article concludes that digital twin projects are likely to involve incremental rather than disruptive change, and that successful implementation is usually underpinned by ensuring technology, people, and process change factors are progressed in a balanced and integrated fashion. Building upon existing frameworks, three “properties” are identified as being of particular value in digital twin projects—workforce adaptability, technology manageability, and process agility—and a related set of steps and actions is put forward as a template and point of reference for future digital twin implementations. The combination of assessing digital properties and following a set of key actions represents a novel approach to digital twin project planning, and overall the findings are a contribution to the developing theory around digital twins and digitalization, in general, and are also of relevance to professionals embarking on DT projects.

First detection and genome analysis of simple nosed bat polyomaviruses in Central Europe.

Polyomaviruses (PyVs) are known to infect a diverse range of vertebrate host species. We report the discovery of PyVs in vesper bats (family Vespertilionidae) from sampling in Central Europe. Seven partial VP1 sequences from different PyVs were detected in samples originating from six distinct vesper bat species. Using a methodology based on conserved segments within the major capsid virus protein 1 (VP1) among known PyVs, the complete genomes of two different novel bat PyVs were determined. The genetic distances of the large T antigen coding sequences from these PyVs compared to previously-described bat PyVs exceeded 15% meriting classification as representatives of two novel PyV species: Alphapolyomavirus epserotinus and Alphapolyomavirus myodaubentonii. Phylogenetic analysis revealed that both belong to the genus Alphapolyomavirus and clustered together with high confidence in clades including other bat alphapolyomaviruses reported from China, South America and Africa. In silico protein modeling of the VP1 subunits and capsid pentamers, and electrostatic surface potential comparison of the pentamers showed significant differences between the reference template (murine polyomavirus) and the novel bat PyVs. An electrostatic potential difference pattern between the two bat VP1 pentamers was also revealed. Disaccharide molecular docking studies showed that the reference template and both bat PyVs possess the typical shallow sialic acid-binding site located between two VP1 subunits, with relevant oligosaccharide-binding affinities. The characterisation of these novel bat PyVs and the reported properties of their capsid proteins will potentially contribute in the elucidation of the conditions creating the host-pathogen restrictions associated with these viruses.

Modified Siamese Network Based on Feature Enhancement and Dynamic Template for Low-Light Object Tracking in UAV Videos

Unmanned aerial vehicles (UAVs) visual object tracking under low-light conditions serves as a crucial component for applications, such as night surveillance, indoor searches, night combat, and all-weather tracking. However, the majority of the existing tracking algorithms are designed for optimal lighting conditions. In low-light environments, images captured by UAV typically exhibit reduced contrast, brightness, and a signal-to-noise ratio, which hampers the extraction of target features. Moreover, the target’s appearance in low-light UAV video sequences often changes rapidly, rendering traditional fixed template tracking mechanisms inadequate, and resulting in poor tracker accuracy and robustness. This study introduces a low-light UAV object tracking algorithm (SiamLT) that leverages image feature enhancement and a dynamic template-updating Siamese network. Initially, the algorithm employs an iterative noise filtering framework-enhanced low-light enhancer to boost the features of low-light images prior to feature extraction. This ensures that the extracted features possess more critical target characteristics and minimal background interference information. Subsequently, the fixed template tracking mechanism, which lacks adaptability, is enhanced by dynamically updating the tracking template through the fusion of the reference and base templates. This improves the algorithm’s capacity to address challenges associated with feature changes. Furthermore, the Average Peak-to-Correlation Energy (APCE) is utilized to filter the templates, mitigating interference from low-quality templates. Performance tests were conducted on various low-light UAV video datasets, including UAVDark135, UAVDark70, DarkTrack2021, NAT2021, and NAT2021L. The experimental outcomes substantiate the efficacy of the proposed algorithm in low-light UAV object-tracking tasks.