bluuebunny/crossref_metadata_2025 huggingface dataset:
A Neglected Part of Bovine Genital Leptospirosis: Bulls
Authors: Pedrosa Juliana , Ezepha Camila , Carvalho‐Costa Felipe Anibal , Di Azevedo Maria Isabel Nogueira , Lilenbaum Walter
Published: November 2024

Bovine leptospirosis is a worldwide disease that causes reproductive issues, including early embryonic death, stillbirths and infertility, which result in significant economic losses. Although bovine leptospirosis is well‐documented in cows, the role of bulls in harbouring and potentially transmitting genital leptospirosis has been largely neglected. We examined genital and blood samples from 16 slaughtered bulls using microscopic agglutination testing (MAT), polymerase chain reaction (PCR) and sequencing of amplicons. Our results showed that 81.2% of bulls were seroreactive, and 75% were genitally infected. The amplicons displayed an identity greater than 99% with Leptospira interrogans strains from the Sejroe serogroup, specifically serovar Hardjoprajitno. This study demonstrates that bulls can harbour in their genital tract the same leptospires associated with reproductive syndromes in cows from the same geographic region, highlighting the importance of bulls in maintaining and transmitting Sejroe serogroup strains associated with reproductive disease.
NKG2C Sequence Polymorphism Modulates the Expansion of Adaptive NK Cells in Response to Human CMV
Authors: Asenjo Judit , Moraru Manuela , Al‐Akioui‐Sanz Karima , Altadill Mireia , Muntasell Aura , López‐Botet Miguel , Vilches Carlos
Published: November 2024

A subpopulation of NK cells with distinctive phenotype and function differentiates and expands specifically in response to infection by human cytomegalovirus (HCMV). A hallmark of these adaptive NK cells is their increased expression levels of the activating CD94/NKG2C receptor for HLA‐E, and lack of expression of its inhibitory homologue CD94/NKG2A. Their frequency is highly variable in HCMV+ individuals, and the basis for such differences is only partially understood. Here, we explore the possible influence of sequence polymorphism of the NKG2C (or KLRC2) gene on the expansion of NKG2C+NKG2A− NK cells in healthy HCMV‐seropositive donors. Our results show a significant association of greater proportions of adaptive NK cells with allele NKG2C*02. This is defined by two amino acid substitutions in comparison with the most prevalent allele, NKG2C*01, and associates with additional sequence polymorphisms in noncoding regions. Furthermore, we demonstrate consistently higher mRNA levels of NKG2C*02 in heterozygous individuals co‐expressing this allele in combination with NKG2C*01 or *03. This predominance is independent of polymorphisms in the promoter and 3′ UTRs and is appreciated also in HCMV‐seronegative donors. In summary, although additional factors are most likely implicated in the variable expansion of NKG2C+NKG2A− NK cells in response to HCMV, our results demonstrate that host immunogenetics, in particular NKG2C diversity, influences the magnitude of such response.
High‐Resolution Sequencing Identifies a Novel HLA Allele: HLA‐B*35:20:03
Authors: Molinari Isabella Fantini , Cita Rafael Formenton , Massi Fernanda Pelisson , Pinto Larissa Danielle Bahls , de Lima Neto Quirino Alves
Published: November 2024

The novel HLA‐B*35:20:03 allele differs from B*35:20:01 by a change of C→A in exon 4.
A Component-based Systematic Review of Pool-based Active Learning for 2D Object Detection
Authors: Yasin Mohammed , Hj Salam Md Sah , Adam Tarmizi
Published: November 2024

Active learning can help reduce the labeling burden in training deep object detection models by strategically selecting the most informative data points for labeling from unlabeled data. Different approaches to this task have been proposed in recent years, with differences often found in their approaches to the specific components. Consequently, this study breaks down active learning methods into their individual components and examines the diverse strategies associated with each intending to shed light on areas that have not yet been explored in depth. Doing so, the study offers valuable insights into potential research directions in this area.
Quantification of Facial Geometrical Dimension for Student Attendance Tracking
Authors: Yakhub Shaik
Published: November 2024

The traditional method of manual attendance-taking has been used in educational institutions for decades which have consumed one-sixth amount of class time for attendance marking. Great research on attendance systems has come up with techniques like biometrics, NFC’s and QR codes. Moreover, with advancements in technology, this research project can provide a more efficient and effective solution. This research project utilizes image processing, computer vision and facial recognition technology to mark the attendance of the students in class. The objectives of the system are registration of facial image, perform landmarking of the facial image and develop automated attendance system. As a result, this project works by installing a camera on top of the board which detects the student faces and performs attendance marking. Now is the time to implement this system in schools, institutions, colleges, and universities to streamline the attendance-taking process. This automated system will not only save time and effort but will also provide accurate attendance records, which will benefit both management and students.
Comparative Study on Encryption Algorithms for Autism MRI Scan Images
Authors: Sivakumar Pavunraj , Yusoff Yusliza
Published: November 2024

Healthcare centre is the most susceptible sctor. Cyber-attack on medical institutions, such as hospitals and health care centre have increased year after year. Autism health care centre is one of the victims. Autism MRI scan images include sensitive and confidential information about a patient's health and other personal information. Therefore, image encryption is a fundamental aspect of information security, especially in today's digital era where the proliferation of images and the need to protect sensitive visual content are of paramount importance. In order to protect the confidentiality and integrity of images, image encryption techniques work to make sure that only authorised users can view and understand the visual data while prohibiting unauthorised access and modification. The pixel values and spatial properties of the image are hidden using a variety of cryptographic methods and key-based actions. Symmetric encryption algorithm, like Advanced Encryption Standard (AES), which use the same key for encryption and decryption operations, are among the famous image encryption techniques. After that, asymmetric encryption algorithm like Rivest-Shamir-Adleman (RSA), which employ two distinct keys for both encryption and decryption. Next, the research includes a hybridization method of Elliptic Curve Cryptography (ECC) with the Hill Cypher (HC) for image encryption and decryption. There are five different Autism MRI Scan images selected to be used as the input image for encryption process. Then, each image will have two different file format which is PNG and BMP and two different file size which is 256*256px and 512*512px. This research's goal is to compare how well symmetric encryption, asymmetric encryption and hybrid encryption work as three separate image encryption techniques. This can help users rapidly and efficiently speed up the encryption and decryption of images and enhance the security of MRI scan images. By applying differential analysis parameters like Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI) and statistical analysis parameters like Histogram Analysis (HA), the characteristics of the image encryption approach are examined. At the end of the experiment, AES encryption proves to be the best among the three types of encryption with better performance in terms of security with NPCR percentage of 99.72%, UACI percentage of 32.68% and has a higher speed of encryption which only takes 0.0238s but has the second-best distribution in HA of pixel value to frequency compares to ECC with HC.
UTMSPACE Research Grant Management System
Authors: Surati Nazihah , Yusoff Yusliza , Ramali Nor Azliana
Published: November 2024

The "UTMSPACE Research Grant Management System" is a web application designed to improve the efficiency and accessibility of managing grants for both administrators and applicants. The current manual process, involving paper forms and departmental submissions, leads to delays, tracking difficulties, and increased administrative workload due to human errors and misfiling. The new online platform addresses these issues by enabling seamless submission and management of applications, budget matters, and other grant-related information. The system aims to streamline the application process, enhance user-friendliness, and replace traditional methods. It will be developed using HTML, CSS, PHP, MySQL, and JavaScript, following an Agile methodology to ensure continuous collaboration between developers and stakeholders. The ultimate goal is to enhance the management of research grants, promoting efficiency, accessibility, and user satisfaction, and contributing to the advancement of research endeavors. By transitioning to this digital system, we anticipate a significant reduction in processing times, with the potential to decrease the time spent on application processing by 50-70%. Additionally, the system is expected to reduce human errors by 60-80%, leading to more accurate and reliable grant management. These improvements will not only enhance the overall user experience but also contribute to more effective and streamlined research grant administration.
Enhancing Transcriptomic Analysis by Influencing De Novo Assembly Using Parallel Computing
Authors: Zaideen Nur Hafizah , Mohamed Muhammad Azman Habeeb , Abdul Hamid Nor Asilah Wati , Ariffin Norazrin , Laham Mohamed Faris , Ismail Zurita
Published: November 2024

The efficient and accurate assembly of genomic data is a computationally intensive process that demands significant computational resources. Traditional sequential approaches often struggle to handle genomic data sets increasing volume and complexity, leading to prolonged execution times and suboptimal results. The study aims to leverage parallel computing capabilities by employing the ABySS and Velvet Assembler tools on the MD2 Pineapple dataset hosted on the Quanta server. By systematically evaluating the performance of these tools across varying thread counts, the study seeks to identify optimal configurations that can enhance the efficiency and accuracy of the de novo assembly process, ultimately enabling more rapid and precise genomic analysis. The study found that for the ABySS assembler, an 8-core and 8-thread configuration exhibited the shortest execution time and greatest speedup, while an 8-core and 12-thread setup produced similar outcomes, demonstrating ABySS's flexibility to adjust to various thread configurations. Velvet assembler demonstrated exceptional performance by utilizing 8 cores and 16 threads for the velvetg command, and 8 cores and 8 threads for the velveth command. Significantly, this study provided implications for advancing genomic analysis methodologies by providing valuable guidance on optimizing the efficiency and accuracy of de novo assembly processes through careful selection of parallelization configurations, paving the way for future studies and applications in genetic data analysis.
Multidimensional Context Clustering to Analyse Student Engagement in Online Learning Environment
Authors: Ke Ting Chong , Ibrahim Noraini , Huspi Sharin Hazlin , Wan Kadir Wan Mohd Nasir
Published: November 2024

Educational data mining is the application of data mining technology in an educational environment to indicate and resolve various types of issues faced in education. COVID-19 pandemic in 2020 accelerated the shift to emergency remote learning and online learning, which has continued to grow due to its flexibility and cost-effectiveness. However, several challenges exist when adopting the online learning, and which include the access to technology, technology attitude, psychological questions, teacher contact, and quality of assessment. Thus, it becomes important to focus on student engagement as a determinant of success during online learning. Student engagement is a complex construct which is comprised of four aspects which are behavioural, cognitive, emotional and social. In this study, the K-Means clustering approach is chosen to categorise students into clusters according to their active participation in the online learning process. The experiment used produces a silhouette coefficient of 0.71 clustering the datasets into three clusters. Cluster 0 are the disengaged learners who were observed to be least active across all the dimensions, while cluster 1 is composed of passive learners. The cluster 2 comprises the most engaged students with the high level of time management. These results provide information regarding the distinct engagement profiles that may be helpful when the lecturers attempt at student’s interventions.
Large Scale Contractor Management Dashboard
Authors: Nasiruddin Alya Nasuha Mohammad , Wan Kadir Wan Mohammad Nasir , Khairuddin Alif Ridzuan
Published: November 2024

Advancements in digital technology have considerably boosted productivity and economic growth over time. Numerous businesses and organizations use a variety of software to organize their work efficiently. This system's main objective is to convert from a manual to an automated method for more effective management. An Employee Management System is one of the systems that contribute significantly to the management of a business. However, this article highlights the deployment of an automated system to replace the paper-based approach that general contractor companies have been using for decades. Laravel is one of the most popular framework technologies for system development among developers. Laravel enables developers to concentrate on the design architecture and functionality of an online application, making it easier for other developers to manage their tasks. Furthermore, role-based access control (RBAC) in Contractor Management System (CMS) has increased the system's security by granting users access depending on their jobs. On-site users will be able to access the system with the tip of their fingers. This development aims to simplify the organization's staff management and will elaborate further on the technologies employed in the proposed system.
Three new species of Pergalumna (Acari, Oribatida, Galumnidae) from Venezuela, with an updated identification key to known species of the genus from the Neotropical region
Authors: Ermilov Sergey G.
Published: November 2024

Three new species of the subgenus Pergalumna (Pergalumna)—P. (P.) chamaensis sp. nov., P. (P.) henriensis sp. nov. and P. (P.) parabifissurata sp. nov.—are described, based on adults collected from northern, northwestern and western Venezuela. Pergalumna (P.) chamaensis differs from its related species P. (P.) andicola and P. (P.) anellata by the morphology of the rostrum and the length of the lamellar seta. Pergalumna (P.) henriensis differs from its related species P. (P.) hypergranulosa and P. (P.) obsidiana by the larger body size, the morphology of the rostral region, and the body sculpturing. Pergalumna (P.) parabifissurata differs from the related species P. (P.) bifissurata by the morphology of the rostral region and the size of the notogastral porose areas. An identification key to the known species of Pergalumna from the Neotropical region is presented.
Following the propagation of erroneous x-ray photoelectron spectroscopy peak fitting through the literature. A genealogical approach
Authors: Clark B. Maxwell , Major George H. , Pinder Joshua W. , Austin Daniel E. , Baer Donald R. , Biesinger Mark C. , Easton Christopher D. , Harmer Sarah L. , Herrera-Gomez Alberto , Hughes Anthony E. , Skinner William M. , Linford Matthew R.
Published: November 2024

This study considers how poor x-ray photoelectron spectroscopy (XPS) peak fitting in the scientific literature is both affected by previous precedent and affects future published work. It focuses on a highly cited paper (the “Subject” paper) from a respected journal that contains incorrect S 2p peak fits. This paper was studied in a genealogical fashion vis-à-vis the XPS peak fitting in its “child,” “parent,” “grandparent,” and “great-grandparent” papers. Interestingly, precedents were not followed to a high degree between parent and child papers. However, in many cases, even when the authors of a study did not follow the incorrect precedent that they cited, they still incorrectly fit their data. Thus, not necessarily for good reasons, the effects of poor XPS peak fits on future generations of papers may be less than some experts had expected or feared. In many cases, older papers appear to contain better XPS peak fitting than newer ones.
Unveiling the spatial-temporal dynamics: Diffusion-based learning of conditional distribution for range-dependent ocean sound speed field forecasting
Authors: Gao Ce , Cheng Lei , Zhang Ting , Li Jianlong
Published: November 2024

Environment-aware underwater acoustic detection and communications demand precise forecasting of the sound speed field (SSF) both temporally and spatially. Toward this goal, recent machine learning models, such as recurrent neural networks and Gaussian process regressions, have outperformed classical autoregressive models. However, from the unified theoretical perspective of conditional distribution learning, there is still significant room for improvement, as existing works have not fully learned the conditional distribution of future SSFs given past SSFs. To address these limitations, in this paper, we leverage the use of diffusion models, the foundation of recent successful deep generative models, such as DALL-E 2 and SORA, to learn the conditional distribution even under limited training data, through careful neural architecture and training strategy design. Our experiments, conducted on real-life South China Sea datasets, confirm that our proposed model outperforms the state-of-the-art baselines in forecasting range-dependent SSFs and the associated underwater transmission losses. Additionally, our model provides reliable confidence intervals that quantify the uncertainties of predictions.
Pleural space infection microbiology as assessed using a clinical sequencing-based assay:
Fusobacterium nucleatum
group,
Streptococcus intermedius,
and other oral normal microbiota are the most common bacteria identified in community-acquired pleural space infections
Authors: Alvarez Otero Judith , Mandrekar Jay , Wolf Matt J. , Starkey Jordan C. , Carmona Eva M. , Dyrhovden Ruben , Kommedal Øyvind , Patel Robin
Published: November 2024

The definition of the microbiology of pleural space infection has been challenging due to the poor yield of conventional culture. Here, the results of a 16S ribosomal RNA gene PCR/sequencing assay performed on pleural fluid in routine clinical practice between August 2020 and January 2023 were evaluated. Amplified 16S rRNA gene DNA was submitted to Sanger sequencing and/or next-generation sequencing or results were reported as negative, depending on PCR crossing threshold value. In all, 496 pleural fluids were tested at Mayo Clinic Laboratories, with 227 positive results, including 57 from Mayo Clinic patients. Among the 57 Mayo Clinic patients, pleural space infection was community acquired in 48 (84%);
Fusobacterium nucleatum
group and/or
Streptococcus intermedius
were detected in 31/57 (54%) cases [including 28/48 (58%) community-acquired cases], with additional facultative and/or anaerobic species also found in various combinations in 17/31 (55%). Results of this study suggest that the most frequent microorganism profile involved in community-acquired pleural space infection may be a combination of
F. nucleatum
group and/or
S. intermedius
, with or without other normal microbiota.

IMPORTANCE

We describe here the most frequent microorganisms detected in community-acquired pleural space infection using a clinically performed sequencing-based assay. We found that the most common detection was the
Fusobacterium nucleatum
group and/or
Streptococcus intermedius
, with or without other normal microbiota. We propose the term e-FuSion (effusion with
Fusobacterium nucleatum
group,
Streptococcus intermedius
, and other oral normal microbiota) for this entity.
Bacterial community function increases leaf growth in a pitcher plant experimental system
Authors: Bernardin Jessica R. , Young Erica B. , Gray Sarah M. , Bittleston Leonora S.
Published: November 2024

Across diverse ecosystems, bacteria and their hosts engage in complex relationships having negative, neutral, or positive interactions. However, the specific effects of leaf-associated bacterial community functions on plant growth are poorly understood. Although microbes can promote plant growth through various biochemical mechanisms, investigating the community’s functional contributions to plant growth remains to be explored. To address this gap, we characterized the relationships between bacterial community function and host plant growth in the purple pitcher plant (
Sarracenia purpurea
). The main aim of our research was to investigate how different bacterial community functions affect the growth and nutrient content in the plant. Previous research has suggested that microbial communities aid in prey decomposition and subsequent nutrient acquisition in carnivorous plants, including
S. purpurea
. However, the specific functional roles of bacterial communities in plant growth and nutrient uptake are not well known. In this study, sterile, freshly opened pitchers were inoculated with three functionally distinct, pre-assembled bacterial communities. Bacterial community composition and function were measured over 8 weeks using physiological assays, metagenomics, and metatranscriptomics. Distinct community functions affected plant traits; a bacterial community enriched in decomposition was associated with larger leaves with almost double the biomass of control pitchers. Physiological differences in bacterial communities were supported by metatranscriptomics; for example, the bacterial community with the highest chitinase activity had greater expression of transcripts associated with chitinase enzymes. The relationship between bacterial community function and plant growth observed here indicates potential mechanisms, such as chitinase activity, for host-associated bacterial functions to support pitcher plant growth.

IMPORTANCE

This study addresses a gap in understanding the relationships between bacterial community function and plant growth. We inoculated sterile, freshly opened pitcher plant leaves with three functionally distinct bacterial communities to uncover potential mechanisms through which bacterial functions support plant health and growth. Our findings demonstrate that distinct community functions significantly influence plant traits, with some bacterial communities supporting more plant growth than in control pitchers. These results highlight the ecological roles of microbial communities in plants and thus ecosystems and suggest that nutrient cycling is an important pathway through which microbes support host plant health. This research provides valuable insights into plant-microbe interactions and the effects of diverse microbial community functions.
Overflying nilpotent horizons
Authors: Figueroa José , Giribet Gaston , Neira-Gallegos Anibal , Oliva Julio , Oyarzo Marcelo
Published: November 2024

We study solutions of Einstein equations with negative cosmological constant in five dimensions that describe black holes whose event horizons are homogeneous, anisotropic spaces. We focus on the case where the constant-time slices of the horizon are the Nil geometry, the Thurston geometry associated to the Heisenberg group. For such spaces, we analyze the symmetries both in the asymptotic region and in the near horizon region. We compute the associated conserved charges, which turn out to be finite and admit a sensible physical interpretation. We analyze the thermodynamics of the Nil black hole, and we present a stationary spinning generalization of it in the slowly rotating approximation.
The geodesic structure of BPS one-branes in five dimensions
Authors: Dabash Tahia F , Emam Moataz H
Published: November 2024

In this paper, we continue previous work where one-brane spacetimes coupled to the $${\mathcal {N}}=2$$

N
=
2

ungauged five dimensional hypermultiplets were found. We explore their symmetries as well as study their full geodesic structure. The one-branes are characterized by a coupling constant that distinguishes the behavior of the geodesics from smooth and causally connected in the positive case to singular and repulsive in the negative case.
An Accurate Construction Method of E-commerce User Profile Based on Artificial Intelligence Algorithm and Big Data Analysis
Authors: Li Xiaolei
Published: November 2024

User’s basic attributes, behavior characteristics, value attributes, social attributes, interest attributes, psychological attributes, and other factors will lead to poor user experience, information overload, interference, and other negative effects. In order to develop more accurate marketing strategies, optimize user experience, and improve the conversion rate and user satisfaction of e-commerce platforms, an accurate construction method of e-commerce user profile based on artificial intelligence algorithm and big data analysis is proposed. Based on big data analysis technology, the basic attributes, behavior characteristics, value attributes, social attributes, interest attributes, and psychological attributes of e-commerce users are collected and integrated from multiple dimensions. The improved sequential pattern mining algorithm (PBWL) is applied to mine the frequent sequential pattern in the e-commerce user behavior, and to reveal the user’s behavior habit. The comprehensive attribute representation of e-commerce users is obtained by combining the LINE network model and the convolutional neural network. The firefly K-means clustering algorithm is used to cluster the e-commerce users, group the users based on the similarity of user attribute information, create different types of user clusters, and achieve the accurate construction of an e-commerce user profile. The experimental results show that this method can build an accurate e-commerce user profile and provide strong support for personalized recommendation and precision marketing of e-commerce platforms. This method can dig deeply into the behavior habits of e-commerce users and accurately reflect their interest preferences and consumption characteristics. This method can quickly and stably cluster e-commerce users, and the clustering effect of user profiles is optimal. This method can also divide the data into meaningful groups according to the user’s consumption behavior, and reveal the characteristics and values of different groups.
Furniture Form Innovation and Human–Machine Comfort Evaluation Model Based on Genetic Algorithm
Authors: Bai Yifan , Kamarudin Khairul Manami , Alli Hassan
Published: November 2024

Mechanization, specialization, and shrewd steering have been regularly added to indoor fixtures commercial enterprises due to their ever-growing clinical and technological capacities. Competing in a marketplace in which technical layout competencies are required, the capability to think creatively and create novel shapes is what makes a product stand out and provides cost. Customers are no longer content material to buy fixtures in bulk, preferring as an alternative to choose pieces that are extra suitable to their own necessities and people in their homes, to higher fulfill primary demands and cope with problems like cramped quarters. The user’s needs for domestic product ergonomics inform the established order of a standards layer, which is then weighted to get its corresponding cost. In situations wherein competing gadgets provide similar features and overall performance, the aesthetics of the product grow to be more critical. This research explores the Pareto-primarily based Genetic Algorithm (PGA) inside this framework, with the goal of fostering innovation in product layout and the generation of novel ideas. Using more suitable [Formula: see text]-means clustering and the Enhanced Least Squares Support Vector Machine (ELSSVM), this study gives a prediction technique for objectively assessing furniture comfort. Designers might be capable of focusing on aesthetics by using the findings as a springboard to research new shapes, way to the fact that the proposed version investigates several alternatives in pursuit of nice purposeful forms. Afterward, a mathematical version is used to symbolize the layout preference problems, and the layout scheme selection method is simulated. In the give-up, the advised model’s viability is checked by means of looking at how fixtures from the product’s layout picks had been carried out to assist designers give us fresh thoughts.
Acupuncture and Moxibustion for Inflammatory Bowel Disease: Regulatory Mechanisms Revealed by Microbiome and Metabolomic Analysis
Authors: Yang Xinyue , He Min , Cao Jiazhen , Tang Qingqing , Yang Bo , Li Tie , Sun Mengmeng
Published: November 2024

Acupuncture and moxibustion are widely acknowledged as effective complementary therapies for managing inflammatory bowel disease (IBD) in traditional Chinese medicine. However, the regulatory mechanisms by which these two therapies exert their therapeutic effects in IBD are yet to be fully elucidated. The objective of this study was to investigate the mechanisms of action underlying acupuncture and moxibustion and the regulative differences between them as therapeutic interventions for IBD. Using a dextran sodium sulfate-induced IBD mice model, the effects of the two treatments were evaluated by examination of body weight, stool samples, colon morphology, inflammatory factors, gut microbiota, and metabolites. The results indicated that both acupuncture and moxibustion mitigated body weight reduction; improved the structural characteristics of intestinal tissues; increased levels of anti-inflammatory cytokines including interleukin (IL)-10; and decreased levels of pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-[Formula: see text]), nuclear factor kappa B (NF-[Formula: see text]B), IL-6, IL-1[Formula: see text], and IL-17. Acupuncture and moxibustion had distinct effects on the regulation of the intestinal microbiota and metabolic pathways in IBD mice. Moxibustion regulated a greater number of metabolic pathways than acupuncture, the majority of which were associated with amino acid metabolism, brain signal transmission, energy metabolism, and anti-inflammatory pathways. These findings provide a scientific basis for the differential applications of acupuncture and moxibustion in clinical practice.
A study on solutions of fractional order equal-width equation using novel approach
Authors: Naveen K. , Prakasha D. G. , Mofarreh F. , Haseeb A.
Published: November 2024

The time-fractional equal-width equation plays a vital role in plasma physics, serving as an essential tool for elucidating the dynamics of hydromagnetic waves in cold plasma, a critical component for the comprehensive understanding of plasma-related phenomena. Furthermore, this equation finds application in fluid mechanics, which models the transmission of nonlinear waves across shallow waters. In this study, we employ an innovative technique to solve time-fractional equal-width equation, demonstrating the q-homotopy analysis transform technique. This considered technique was implemented to find the effective approximated solution of the considered equations. The obtained results are discussed through the 3D plots and graphs that express the physical representation. The results derived from the q-homotopy analysis transform method are presented in a series form, exhibiting swift convergence and capturing the behavior of the equal-width equation’s solution with minimal error, and the convergence analysis and uniqueness of the solution using the projected method have been secured using the fixed-point theory. The projected method we used does not require linearization, perturbations, or discretization, which significantly reduces computations. The results disclose that the proposed technique is highly effective, methodical, and easy to apply for complex and nonlinear systems, helping us to capture the associated behavior of diverse classes of phenomena. The numerical simulations presented ensure higher accuracy and are compared with other techniques to evaluate approximate errors. In comparison with other techniques, the considered method is a competent tool to get an analytical solution of an considered equation and the methodology employed herein for the considered equation is demonstrated to be both efficient and dependable, marking a significant advancement in the field.
Nonlinear effects in quantum field theory: Applications of the Pochhammer–Chree equation
Authors: Khater Mostafa M. A.
Published: November 2024

This study aims to solve the nonlinear Pochhammer–Chree ([Formula: see text]) equation to understand its physical implications and establish connections with other nonlinear evolution equations, particularly in plasma dynamics. By using the Khater II ([Formula: see text]hat. II) method for analytical solutions and validating these solutions numerically with the variational iteration method, this study offers a detailed understanding of the equation’s behavior. The results demonstrate the effectiveness of these methods in accurately modeling the system, highlighting the importance of combining analytical and numerical approaches for reliable solutions. This research significantly advances the field of nonlinear dynamics, especially in plasma physics, by employing multidisciplinary methods to tackle complex physical processes. Moreover, the [Formula: see text] equation is relevant in various physical contexts beyond plasma dynamics such as optical and quantum fields. In optics, it models the propagation of nonlinear waves in fiber optics, where similar nonlinear evolution equations describe wave interactions. In quantum field theory, the [Formula: see text] equation helps in understanding the behavior of quantum particles and fields under nonlinear effects, making it a versatile tool for studying complex phenomena across different domains of physics.
Swin-Caption: Swin Transformer-Based Image Captioning with Feature Enhancement and Multi-Stage Fusion
Authors: liu Lei , Jiao Yidi , Li Xiaoran , Li Jing , Wang Haitao , Cao Xinyu
Published: November 2024

The objective of image captioning is to empower computers to generate human-like sentences autonomously, describing a provided image. To tackle the challenges of insufficient accuracy in image feature extraction and underutilization of visual information, we present a Swin Transformer-based model for image captioning with feature enhancement and multi-stage fusion (Swin-Caption). Initially, the Swin Transformer is employed in the capacity of an encoder for extracting images, while feature enhancement is adopted to gather additional image feature information. Subsequently, a multi-stage image and semantic fusion module is constructed to utilize the semantic information from past time steps. Lastly, a two-layer LSTM is utilized to decode semantic and image data, generating captions. The proposed model outperforms the baseline model in experimental tests and instance analysis on the public datasets Flickr8K, Flickr30K, and MS-COCO.
FormA11y - A tool for remediating PDF forms for accessibility
Authors: Paliwal Sparsh , Hoeflich Joshua , Jordan J Bern , Jain Rajiv , Morariu Vlad I , Siu Alexa , Lazar Jonathan
Published: November 2024

PDF documents are usually not born-accessible, and so document authors need to put in additional work (remediation) to make them accessible for people with disabilities. Unfortunately, this step is often overlooked and hard to execute, resulting in a large number of inaccessible PDF documents on the internet. Previously, there have been research efforts to investigate potential solutions for remediating PDF documents for accessibility. However, most of the existing research focuses on accessibility of long or scientific PDF documents meant for passive reading. PDF documents come in different types, and this research project focuses on a distinct type of PDF document—forms—where the user is required to interact with the PDF document and enter data. Through our research work we identified that the PDF form remediation process is non-intuitive, repetitive, and overwhelming due to the high-information density of PDF forms, and existing research and tools do not yet address the challenges. Our research work culminated in the creation of a tool – FormA11y – that addresses these challenges by making the repetitive and painstaking process of form remediation easier. To evaluate the effectiveness and efficiency of FormA11y against the industry standard tool – Adobe Acrobat – for PDF form remediation, we performed a within-subject user study with 20 participants. With FormA11y, users remediated forms 2.8 times faster while creating more accurately accessible PDF forms.
A Caching-based Framework for Scalable Temporal Graph Neural Network Training
Authors: Li Yiming , Shen Yanyan , Chen Lei , Yuan Mingxuan
Published: November 2024

Representation learning over dynamic graphs is critical for many real-world applications such as social network services and recommender systems. Temporal graph neural networks (T-GNNs) are powerful representation learning methods and have demonstrated remarkable effectiveness on continuous-time dynamic graphs. However, T-GNNs still suffer from high time complexity, which increases linearly with the number of timestamps and grows exponentially with the model depth, making them not scalable to large dynamic graphs. To address the limitations, we propose
Orca
, a novel framework that accelerates T-GNN training by caching and reusing intermediate embeddings. We design an optimal caching policy, named
MRD
, for the uniform cache replacement problem, where embeddings at different intermediate layers have identical dimensions and recomputation costs.
MRD
not only improves the efficiency of training T-GNNs by maximizing the number of cache hits but also reduces the approximation errors by avoiding keeping and reusing extremely stale embeddings. For the general cache replacement problem, where embeddings at different intermediate layers can have different dimensions and recomputation costs, we solve this NP-hard problem by presenting a novel two-stage framework with approximation guarantees on the achieved benefit of caching. Furthermore, we have developed profound theoretical analyses of the approximation errors introduced by reusing intermediate embeddings, providing a thorough understanding of the impact of our caching and reuse schemes on model outputs. We also offer rigorous convergence guarantees for model training, adding to the reliability and validity of our
Orca
framework. Extensive experiments have validated that
Orca
can obtain two orders of magnitude speedup over state-of-the-art T-GNNs while achieving higher precision on various dynamic graphs.
Reversible Degradation Phenomenon in PEMWE Cells: An Experimental and Modeling Study
Authors: Krenz Tobias , Rex Alexander , Helmers Lennard , Trinke Patrick , Bensmann Boris , Hanke-Rauschenbach Richard
Published: November 2024

In proton exchange membrane water electrolysis (PEMWE) systems, voltage cycles dropping below a threshold are associated with reversible performance improvements, which remain poorly understood despite being documented in literature. The distinction between reversible and irreversible performance changes is crucial for accurate degradation assessments. One approach in literature to explain this behavior is the oxidation and reduction of iridium. Iridium-based electrocatalyst activity and stability in PEMWE hinge on their oxidation state, influenced by the applied voltage. Yet, full-cell PEMWE dynamic performance remains underexplored, with a focus typically on stability rather than activity. This study systematically investigates reversible performance behavior in PEMWE cells using Ir-black as an anodic catalyst. Results reveal a recovery effect when the low voltage level drops below 1.5 V, with further enhancements observed as the voltage decreases, even with a short holding time of 0.1 s. This reversible recovery is primarily driven by improved anode reaction kinetics, likely due to changing iridium oxidation states, and is supported by alignment between the experimental data and a dynamic model that links iridium oxidation/reduction processes to performance metrics. This model allows distinguishing between reversible and irreversible effects and enables the derivation of optimized operation schemes utilizing the recovery effect.
Effect of insulin on indices of cerebral blood flow and cerebrovascular compliance in young adults
Authors: Shariffi Brian , Harper Jennifer L. , McMillan Neil J. , Gonsalves Anna M. , Bond Braden J. , Pipkins Aubrey M. , Shoemaker Leena N. , Manrique-Acevedo Camila , Padilla Jaume , Limberg Jacqueline K.
Published: November 2024

Insulin has important vasodilatory effects in the peripheral circulation, but less is known about the role of insulin in cerebrovascular control. Contrary to our hypothesis, there was no effect of systemic (intravenous) nor local (intranasal) insulin administration on middle cerebral artery blood velocity; however, both systemic and local insulin administration reduced cerebrovascular compliance. Our findings advance our understanding of the cerebrovascular response to insulin and may have implications in the context of known metabolic disturbances.
PDGFRα-positive cell-derived TIMP-1 modulates adaptive immune responses to influenza A viral infection
Authors: Dutta Saugata , Zhu Yin , Almuntashiri Sultan , Peh Hong Yong , Zuñiga Joaquin , Zhang Duo , Somanath Payaningal R. , Ramírez Gustavo , Irineo-Moreno Valeria , Jiménez-Juárez Fabiola , López-Salinas Karen , Regino Nora , Campero Paloma , Crocker Stephen J. , Owen Caroline A. , Wang Xiaoyun
Published: November 2024

Our data strongly link tissue inhibitor of metalloproteinases-1 (TIMP-1) to influenza A virus (IAV) pathogenesis. TIMP-1 is highly increased in PDGFRα-lineage cells during IAV infection. Transforming growth factor-β (TGF-β) induces TIMP-1 during lipofibroblast (lipoFB)-to- myofibroblast (myoFB) transdifferentiation. Timp-1 deficiency protects mice from H1N1 IAV-induced weight loss, mortality, and lung injury. TIMP-1 may be a novel therapeutic target for IAV infection.
Impact of glucagon-like peptide-1 receptor agonists on axonal function in diabetic peripheral neuropathy
Authors: Dhanapalaratnam Roshan , Issar Tushar , Poynten Ann M. , Milner Kerry-Lee , Kwai Natalie C. G. , Krishnan Arun V.
Published: November 2024

Diabetic peripheral neuropathy is known to be relentlessly progressive and irreversible. Prospective studies in 24 participants with diabetic peripheral neuropathy (DPN) treated with glucagon-like peptide-1 receptor agonists (GLP-1RA) demonstrated improvements in clinical neuropathy scores, nerve conduction studies, and axonal excitability recordings. Analysis of axonal excitability recordings revealed the mechanism for GLP-1RA improvement in DPN were changed consistent with improvements in Na+/K+–ATPase pump function, and this was supported by mathematical modeling.
Neural integration of egocentric and allocentric visual cues in the gaze system
Authors: Bharmauria Vishal , Seo Serah , Crawford J. Douglas
Published: November 2024

A fundamental question in neuroscience is how the brain integrates egocentric (body-centered) and allocentric (landmark-centered) visual cues, but for many years this question was ignored in sensorimotor studies. This changed in recent behavioral experiments, but the underlying physiology of ego/allocentric integration remained largely unstudied. The specific goal of this review is to explain how prefrontal neurons integrate eye-centered and landmark-centered visual codes for optimal gaze behavior. First, we briefly review the whole brain/behavioral mechanisms for ego/allocentric integration in the human and summarize egocentric coding mechanisms in the primate gaze system. We then focus in more depth on cellular mechanisms for ego/allocentric coding in the frontal and supplementary eye fields. We first explain how prefrontal visual responses integrate eye-centered target and landmark codes to produce a transformation toward landmark-centered coordinates. Next, we describe what happens when a landmark shifts during the delay between seeing and acquiring a remembered target, initially resulting in independently coexisting ego/allocentric memory codes. We then describe how these codes are reintegrated in the motor burst for the gaze shift. Deep network simulations suggest that these properties emerge spontaneously for optimal gaze behavior. Finally, we synthesize these observations and relate them to normal brain function through a simplified conceptual model. Together, these results show that integration of visuospatial features continues well beyond visual cortex and suggest a general cellular mechanism for goal-directed visual behavior.
The High‐Quality Genome Sequencing and Analysis of Red Raspberry (Rubus idaeus L.)
Authors: Zhang Haopeng , Li Weihua , Li Guodong , Liu Jiaren , Chen Hongsheng , Zhang Chunpeng , Zhao Jinlu , Zhang Zhicheng , Lv Qiang , Zhang Yan , Yang Guohui , Liu Ming
Published: November 2024

Red raspberry (Rubus idaeus L.), which is an important nutritional source for human health, belongs to fruit crops of the Rosaceae family. Here, we used Pacific Biosciences single‐molecule real‐time (SMRT) sequencing and high‐throughput chromosome conformation capture (Hi‐C) sequencing technologies to assemble genomes and reported a high‐quality Rubus idaeus L. (DNS‐1) genome with 321.29 Mb assembled into seven chromosomes. The LAI score of the DNS‐1 genome assembly was 21.32, belonging to gold quality. Approximately 52.3% of the assembly sequences were annotated as repetitive sequences, and 24.15% were composed of long terminal repeat elements. A total of 29,814 protein‐coding genes and 2474 pseudogenes were predicted in DNS‐1. We characterized the complete genomes of DNS‐1 and compared them to those of seven other species. We found that 652 gene families were unique to DNS‐1 and they were shaped from an ancestor. There were 1000 and 5193 gene families that expanded and contracted in the DNS‐1 genome. The Rubus idaeus L. genome can be used to understand the structure and evolution of Rosaceae genomes and can be developed to identify genes controlling important traits and improve breeding work.
Clay‐Loaded Starch‐Grafted Chitosan as Environmentally Controlled Release Material for Atrazine
Authors: Jindor Norbert J. , Amenorfe Leticia P. , Kangmennaa Ahmed , Forkuo Richard B. , Okyere Harry , Boadi Nathaniel O. , Opoku Francis , Adimado Anthony A. , Agorku Eric S.
Published: November 2024

Herein, controlled‐release material for atrazine (ATZ) herbicide was formulated using different ratios of kaoline (Kao) clay‐loaded starch (ST)‐grafted chitosan (CHT). The materials were characterized by FTIR, SEM and EDX. The ATZ‐release kinetics were studied using the zero‐order, first‐order and Korsmeyer–Peppas models. The percentage release of the active ATZ in the ST‐g‐CHT/Kao/ATZ, Kao/ATZ and bare ATZ were 9, 57 and 99 within 96 h, respectively. The Korsmeyer–Peppas model better described the release of active ATZ from the ST‐g‐CHT/Kao/ATZ system (R2 = 0.999), which delineates a non‐Fickian diffusion mechanism that the release was controlled by diffusion and dissolution.
An Interesting Case of Hemophagocytic Lymphohistiocytosis in a Postpartum Female With Recent COVID‐19 Vaccination
Authors: Patresan John , Kalsi Amardeep , Cook Perry
Published: November 2024

Hemophagocytic lymphohistiocytosis is a life‐threatening cryptogenic inflammatory process. In some cases, the etiology is obscure, while in others multiple potential etiologies may be present. Diagnosis relies on observed findings rather than context.