bluuebunny/crossref_metadata_2025_split huggingface dataset:
MA-GeSAN: Motion-Appearance Stream-Based Generative Self-Annotation Network Guided Self-Supervised Abnormal Event Detection in Videos
Authors: Chouhan Santosh Prakash , Bhattacharya Mahua , Sharma Gopal Krishna 
Published: June 2024

Abstract

In the recent one-class classification (OCC) approach for detecting abnormal events in surveillance videos, deep generative models (DGM) are specifically trained to learn regular hidden patterns in normal videos. These models assume that unusual events result in significant errors in their generated outputs. However, shared features related to both normal and abnormal events are often captured by DGM, resulting in similar generative errors at the output. Nevertheless, these models do not consider learning crucial domain-specific and distinguishable features, which limits their performance in complex and varying situations. In this paper, we present our model of motion and appearance stream-based generative self-annotation network (MA-GeSAN) guided distinguishable learning based on the conjunction of a generative-discriminative learning network to address the above challenge. The proposed model is established to learn the discriminative boundary of self-annotated video samples generated by the self-annotation network. The MA-GeSAN comprises two parts: (i) generative self-annotation network (GeSAN) for generating the critical frame level annotation based on the joint appearance anomaly score (AAS) and motion anomaly score (MAS), and (ii) deep 3D convolutional network (D3D-CNN) which is trained discriminatively on annotated video snippets \(v{s}_{0}\) (normal) and \(v{s}_{1}\)(abnormal) for identifying normal or abnormal video sequences. The GeSAN consists of a pipeline of spatial adversarial autoencoder (S-AAE) for generating the AAS based on appearance information and a temporal information module (TIM) for generating MAS based on motion information. Finally, the trained D3D-CNN is employed to classify the input video sequence into normal and abnormal classes. Our model performance is evaluated on three publicly available standard datasets, achieving 97.7% on UCSD Ped2, 87.9% on CHUK Avenue, and 99.5% on the UMN dataset in terms of AUC scores. These experimental results verify that our model offers excellent performance compared with other state-of-the-art models.
Multimodal Query Enhancement for Image Retrieval using Transformer Networks - MQIRT
Authors: Hosseini Seyed Mohammad Bagher , Bakhshandeh Soodeh 
Published: June 2024

Abstract

In today's world, with the dramatic increase of digital data and the variety of information, image recovery plays a very vital role in people's lives. For example, imagine a person in an online store looking for a dress similar to a friend's dress, but with distinct criteria such as blue flowers and red flags. The main challenge in this field is the existence of a semantic gap between the user's intention and the machine's understanding. The goal of image retrieval using multivariate (image-text) queries is to reduce this gap. An effective retrieval searches for images matching specific variations specified in a text expression related to the image. Existing methods use Convolutional Neural Networks (CNNs) and recurrent neural networks (LSTM) to extract image and text features that do not express the semantic relationships between the image and text well. In this regard, in order to improve these profiles, a transformer-based architecture is presented. In this research, Vision Transformer (ViT) is used to extract image features and Bidirectional Encoder (BERT) is used to extract text features. After combining the image and text features and applying the attention mechanism on images and text to enhance visual and text understanding. The proposed model of this research is inspired by deep metric learning and seeks to reduce the distance between the image and the input text with the searched images and the user's intent. In addition, a symmetric constraint has been used to improve the model indices. The evaluation results show that the proposed approach from the base model provides better performance in multimodal query-based image retrieval. To reproduce the results of this research, our source code is available at: https://github.com/smb-h/mqirtn
The response of human PMN zeta potential to selected ligands of the cAMP signal pathway under low-dose β-radiation
Authors: Zhirnov Victor , Iakovenko Igor 
Published: June 2024

Abstract

The objective of this study was to examine the zeta potential (ZP) response of human neutrophils to selected ligands of the cAMP signalling pathway under low-dose β-radiation (LDBR). ZP was calculated from the electrophoretic mobility (EPM) of the cells. Cells were irradiated at a dose rate of 10 µGy/hour for one hour. Irradiation of cell suspensions was conducted by adding appropriate aliquots of 14C-leucine to the incubation medium. EPM measurements were carried out in a radiation field. It was demonstrated that the LDBR and agonists of the AC system are capable of increasing the negative surface charge of human neutrophils. Conversely, the antagonist propranolol has been shown to reduce it. Furthermore, it has been demonstrated that radiation affects the response of the membrane ZP to some ligands of the AC pathway and vice versa. Therefore, LDBR can significantly alter the sensitivity of cells to drugs acting on the targets of these ligands. These results do not permit the conclusion that the effect of LDBR on ZP is mediated through the targets with which the studied ligands interact, since any of its components may undergo structural rearrangement, thereby altering the structural organisation of neutrophil membranes in the LDBR field.
Epidemiological Association in Asthma Rhinitis Overlap: Unveiling Key Hematological Markers Using Machine Learning
Authors: Li Haiyang , Yang Jing , Liao Ronghua , Wang Fei 
Published: June 2024

Abstract

Allergic rhinitis (AR) has been rising globally in recent years, now affecting between 10-30% of the population. The condition frequently coexists with asthma, with up to 40% of AR patients experiencing asthma symptoms and 80% of asthmatics reporting symptomatic AR. The presence of co-occurring AR exacerbates asthma, leading to increased risks of asthma attacks, emergency visits, and hospitalizations. This study aims to identify key biomarkers for assessing AR comorbidities in asthmatic patients to improve treatment and management strategies. We categorized subjects into three groups: healthy controls (n=4,032), asthma patients (n=21,506), and asthma patients with rhinitis (n=3,881). We applied a naive Bayesian machine learning algorithm to evaluate routine blood examinations and specific indicators. The ROC curve analysis was conducted to distinguish between normal, asthma, and asthma with AR states, revealing BAS%, ALB, NEUT%, and HB as key biomarkers with high diagnostic accuracy (AUCs of 0.722, 0.712, 0.680, and 0.711, respectively). Our findings indicate significant correlations between these biomarkers and disease states. In asthma with AR patients, lower levels of NEUT% and EOS% were observed compared to healthy and asthma-only groups. Gender differences were also noted, with a higher prevalence of asthma combined with AR in males. The analysis underscores the utility of BAS%, ALB, NEUT%, and HB in predictive modeling, providing a more accurate and early diagnosis crucial for effective disease management. This study highlights the potential of integrating biochemical indicators into advanced predictive models to enhance diagnostic precision and treatment outcomes for asthma and AR. Future research should validate these findings in larger cohorts and explore the integration of these biomarkers into clinical practice for better disease management and patient care.
Versatile Microwave Photonic Filter based on 100-Channel Brillouin Raman Fiber Laser
Authors: Yau Zhi-Yong , Shee Yu-Gang , Lim Eng-Hock , Zhang Zuxing , Mahdi Mohd Adzir 
Published: June 2024

Abstract

Microwave photonic filters (MPF) are among the most crucial components required for meeting the demands of high-speed and high-frequency signal processing of modern telecommunication systems. For the first time, here, we propose an MPF based on a double wavelength spacing Brillouin-Raman fiber laser (BRFL) to realize a versatile bandpass filter. The proposed setup generated 100 optical taps output with ~ 20 GHz spacings as the light source of the MPF. A dispersive medium of 5 km single mode fiber and 3.46 km dispersion compensating fiber (DCF) were used to characterize the effect of the time delay on the central frequency of the MPF passband. A reconfigurable 3-dB bandwidth from 150 MHz to 1.12 GHz centered around 10.3 GHz is achievable by varying the BRFL optical channel numbers using 10 to 100 optical taps with 20 GHz spacing in a 3.46 km DCF. The 3-dB bandwidth and Q-factor of the proposed MPF were investigated experimentally and found to be in good agreement with simulation, demonstrating the potential of the BRFL as a laser source for the realization of flexible and versatile RF transversal filters with potentially reduced cost and complexity.
Fast Best Viewpoint Selection with Geometry-Enhanced Multiple Views and Cross-Modal Distillation
Authors: Cao Zidi , Han Jiayi , Yang Sipeng , Jin Xiaogang 
Published: June 2024

Abstract

Despite significant progress on the mesh-based Best Viewpoint Selection (BVS) problem using multi-views, the current state-of-the-art BVS method requires 20-30 rendering views and is limited to selecting from a predefined sequence of viewpoint samples, which may miss optimal viewpoints and precludes its use in situations where response time is critical. To address the limitations, we present a new dual-branch fast best viewpoint selection regression model that significantly reduces reliance on a large number of input views, enables continuous perspective prediction, and enhances interactive response speeds. Our approach incorporates a geometry-enhanced multi-view feature extractor paired with a learnable token and utilizes a cross-modal distillation method to enrich the model’s understanding of 3D structures. Specifically, by embedding view features into a dimensionally matched learnable token and processing it through three cascaded self-attention layers, the resulting token effectively encapsulates fused features that are better suited to the viewpoint selection task.In addition, to reduce the number of views required, we incorporate cross-modal distillation into the BVS solution by imposing alignment constraints between 3D geometry descriptors and fused multi-view expressions, effectively avoiding the computational requirements of dozens of rendering views. Our experimental results on public benchmarks show that our method is approximately 35 times faster than the SOTA method when only six views are adopted, while also achieving the best quantitative metrics.
Research on High-Speed Drag Torque Characteristics of Wet Clutches Based on Mechanism and Data-Driven Approach
Authors: Zhang LIN , Zhou Haoyu , Zhang Peng , Wei Chao , Ma Ning , Yan Yunbing 
Published: June 2024

Abstract

The traditional drag torque model can accurately predict the drag torque in the low rotation speed stage, but cannot predict the drag torque rebound change in the high rotation speed stage. Therefore, a hybrid model based on the traditional wet clutch drag torque model and Particle Swarm Optimization-Back Propagation (PS0-BP) neural network is proposed in this paper, and the accuracy of the model is improved by the test data. The results show that the error of this hybrid model is 14.45%, which is better than the traditional drag torque model, and the stability and reliability are significantly improved compared with the other neural network models. The effects of oil temperature, the clearance of the friction pair, and the flow rate of lubricant on the drag torque are investigated. It was found that, with the increase of oil temperature and clearance of the friction pair, the rotational speed corresponding to the rebound change of drag torque decreases, and drag torque decreases. With the increase of the flow rate of lubricant, the rotational speed corresponding to the rebound change of drag torque rises, and drag torque increases.
Impact of Thermal Reservoir on Entanglement and Squeezing Characteristics of a Three-Level Laser Driven by Coherent Light in an Open Cavity
Authors: Adem Aliyyi 
Published: June 2024

Abstract

This research aims to study the squeezingand entanglement features of light in three-level atomsunder an open cavity with coherent light excitation.Using an approximation scheme for large timescales,we obtained the steady-state solutions of the evolutionequations for the atomic operators’ expectation valuesand the quantum Langevin equation for the cavity modeoperators. We employed these steady-state solutions todepict the squeezing characteristics, magnification ofentanglement, and normalized second-order correlationof the cavity radiation.The results of our researchshow that the light produced by the three-level lasergets squeezed, mainly in the minus quadrature. Themaximum quadrature squeezing for the light in thetwo-mode cavity is obtained as 37.9% at hni th = 0,and 37.5% at hni th = 0.02, and 37.2% at hni th = 0.03below the vacuum-state level. We demonstrated thatthe average and the variance of the number of photonsdecrease under the influence of spontaneous emission.Moreover, we determined that both the average andthe variance of the photon number are amplified bythe thermal reservoir effect. Additionally, we foundthat quadrature squeezing is enhanced by spontaneousemission, and some entanglement is created. In two-mode light, squeezing and entanglement are directlyrelated, such that an increase in squeezing producesmore entanglement and vice versa.
Transcriptional activation domains interact with ATPase subunits of yeast chromatin remodelling complexes SWI/SNF, RSC and INO80
Authors: Wendegatz Eva-Carina , Engelhardt Maike , Schüller Hans-Joachim 
Published: June 2024

Abstract

Chromatin remodelling complexes (CRC) are ATP-dependent molecular machines important for the dynamic organization of nucleosomes along eukaryotic DNA. CRCs SWI/SNF, RSC and INO80 can move positioned nucleosomes in promoter DNA, leading to nucleosome-depleted regions which facilitate access of general transcription factors. This function is strongly supported by transcriptional activators being able to interact with subunits of various CRCs. In this work we show that SWI/SNF subunits Swi1, Swi2, Snf5 and Snf6 can bind to activation domains of Ino2 required for expression of phospholipid biosynthetic genes in yeast. We identify an activator binding domain (ABD) of ATPase Swi2 and show that this ABD is functionally dispensable, presumably because ABDs of other SWI/SNF subunits can compensate for the loss. In contrast, mutational characterization of the ABD of the Swi2-related ATPase Sth1 revealed that some conserved basic and hydrophobic amino acids within this domain are essential for the function of Sth1. While ABDs of Swi2 and Sth1 define separate functional protein domains, mapping of an ABD within ATPase Ino80 showed co-localization with its HSA domain also required for binding actin-related proteins. Comparative interaction studies finally demonstrated that several unrelated activators each exhibit a specific binding pattern with ABDs of Swi2, Sth1 and Ino80.
Highly Sensitive Silver/Tin Selenide/Graphene Multilayer SPR Sensor for Hemoglobin and Glucose Levels Monitoring in Biological Fluids
Authors: Alsaad Ahmad M. , Al-Hmoud M. , Marashdeh M. W. , Tolstik Elen , Houshmand Milad , Telfah Ahmad 
Published: June 2024

Abstract

This work presents the simulation of a novel surface plasmon resonance (SPR) biosensor composed of silver/tin-selenide/graphene. The designed sensor aims to detect biological constituents in various chemical and biological solutions. While simulation packages based on finite element methods (FEM) are typically utilized in engineering and physics for structural and fluid dynamics analyses, their application in medical diagnostics is less common. In this study, we employed a simple FEM simulation method for medical diagnostics. The functionality of the proposed FEM-based simulated biosensor is examined by testing it on hemoglobin and glucose samples of a diabetic person. In the blood samples analyzed, a 6.1025 g/l increase in hemoglobin (HB) level corresponded to a 0.001 refractive index unit (RIU) increment. The SPR sensor design presented in this work demonstrated a novel capability to detect such minute changes using a simple and cost-effective setup, achieving an angular sensitivity of 158 deg/RIU. Additionally, the SPR sensor was employed for detecting glucose concentrations in urine samples, offering a potential indicator for diabetes diagnosis. The novelty of this SPR sensor lies in its simple schematic design, enabling precise detection of both hemoglobin and glucose levels.
Quantifying suitable low-impact development practices in mitigating runoff floods for the Kinyerezi River catchment in Dar es Salaam, Tanzania
Authors: Swilla Livingstone , Katambara Zacharia , Lingwanda Mwajuma 
Published: June 2024

ABSTRACT

As cities expand, changes in land use increase the runoff quantities. Impermeable catchment areas contribute to peak flows, causing floods in insufficiently capacity river reaches. The rate of urbanization witnessed in the Kinyerezi River catchment in Dar es Salaam has contributed to floods in the Msimbazi River. The low-impact development (LID) practices that include bioretention (BR) ponds, rain barrels (RBs), rain gardens (RGs), vegetative swales (VSs), constructed wetlands (CWs), etc., can be utilized to mitigate a portion of the surface runoff. This study aims to quantify the suitable LID practices for the Kinyerezi River catchment in mitigating a portion of runoff floods. The sub-catchment physical characteristics and soil infiltration rates (Ks) were matched with each LID sitting requirements and later by multi-criteria decision-making (MCDM). The results on matching sub-catchment characteristics and LID sitting requirements indicated that BRs, RBs, VSs, RGs, and CWs were the preferable LIDs while MCDM analysis indicated the BRs, RGs, and RBs more appropriate. The BRs, RGs, and RBs were quantified to be 101, 3,698, and 3,698, respectively, within the catchment. BRs are recommended for catchment use while RBs and RGs are recommended for residential buildings. The RBs have the advantage of promoting water-demanding economic activities.
Online Assessments in Medical Education: Identified Challenges and PotentialSolutions
Authors: Shrivastava Saurabh RamBihariLal , Bobhate Prateek Sudhakar , Mishra Vaishnavi 
Published: June 2024

:
The scope of online assessment in the field of medical education is extensive and varied, encompassing a wide range of types of assessments and
purposes. For the assessment of the cognitive domain, online assessment can be carried out with the help of a number of assessment methods. As is
the case with any potential tool, even online assessments have their share of limitations, and we must be aware of this as it can help us to make a
systematic and evidence-based decision about when to use online assessments and when to combine them with traditional assessments. In order to
enhance the acceptability and use of online assessments in medical education, it is crucial to overcome the identified limitations. The primary
strategy is to clearly communicate the format, the instructions, and the expectations from both teachers and students to avoid all kinds of confusion.
In conclusion, online assessments have immense scope in the field of medical education. However, considering the fact that the successful
implementation of these assessments depends on multiple factors, it becomes essential that we take appropriate measures to overcome the potential
challenges and adopt a concerted and collaborative approach.
Decoding the Expressions, Immune Relevance, and Prognostic Values of Ferroptosis Gene TMEM189: A Pan-cancer Analysis
Authors: Qiu Guanzhong , Song Chaoli , Lou Meiqing , Lin Jing 
Published: June 2024

Background:
TMEM189 is a recently discovered transmembrane protein involved in
ether glycerophospholipid synthesis and ferroptosis regulation. However, its role in tumors is not
well understood.

Objective:
This study aimed to elucidate the oncogenic effects and prognostic values of
TMEM189 in tumors.

Methods:
We performed a pan-cancer analysis of TMEM189 using various databases, bioinformatics
and statistical tools, and tissue microarray analysis.

Results:
TMEM189 was upregulated in tumors compared to normal tissues. High TMEM189 expression
was found to be linked to reduced promoter methylation. Moreover, TMEM189 exhibited
a negative correlation with immunogenic markers, immune cell infiltration, and expression of
Immune Checkpoint Genes (ICGs) in most cancers, implicating its immunosuppressive role in tumor
microenvironments (TME). The genes that interact and are similar to TMEM189 were involved
in hotspot signaling pathways in pan-cancer. TMEM189 overexpression was found to be
usually associated with poor prognosis, especially an independent prognostic risk factor for BLCA,
BRCA, LUAD, MESO, LIHC, and SKCM.

Conclusion:
TMEM189 is overexpressed and exerts immunosuppressive effects in many tumors
with a significant association with poor prognosis, suggesting its potential as a therapeutic target
in cancer treatment.Keywords: TMEM189, ferroptosis, pan-cancer analysis, prognosis, immune
microenvironment.
Physochlainae Radix: A Review of Ethnobotany, Phytochemistry, Pharmacology, Q-marker Prediction, and Future Directions
Authors: Zhang Xin-bo , Zhao Peiyuan , Wang Yunlan , Zhang Ying , Lei Xuan , Song Xiao 
Published: June 2024

Background:
Upon the release of the selection results of “Qin Medicine,” numerous
Chinese herbal medicines and proprietary Chinese medicines have regained attention. Physochlainae Radix (Huashanshen), a herbal medicine named after Mount Hua, the prominent peak in the
Qinling Mountains, has garnered particular interest. Despite this, the impact of Physochlainae Radix and Qin medicines as a whole remains significantly overshadowed by the renown of Mount
Hua.

Methods:
Search on Using “Physochlainae Radix” as the keyword; searches were conducted
across China National Knowledge Infrastructure (CNKI), Wanfang Data, WIP Database, PubMed,
Web of Science, and the National Library of China databases

Results:
This study presents an overview of Physochlainae Radix by reviewing its history, chemical composition, preparation methods, planting and cultivation practices, concoctions, alkaloid detection, contraindications for use, resource recycling, and predicting quality markers.

Conclusion:
To facilitate the further application and development of Physochlainae Radix, this
study also addresses the challenges in the development of Qin medicines and proposes potential
solutions.