bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel and Recurrent Copy Number Variants in ABCA4-Associated Retinopathy
Authors: Corradi Zelia , Dhaenens Claire-Marie , Grunewald Olivier , Kocabaş Ipek Selen , Meunier Isabelle , Banfi Sandro , Karali Marianthi , Cremers Frans P. M. , Hitti-Malin Rebekkah J.
Published: May 2024

ABCA4 is the most frequently mutated gene leading to inherited retinal disease (IRD) with over 2200 pathogenic variants reported to date. Of these, ~1% are copy number variants (CNVs) involving the deletion or duplication of genomic regions, typically >50 nucleotides in length. An in-depth assessment of the current literature based on the public database LOVD, regarding the presence of known CNVs and structural variants in ABCA4, and additional sequencing analysis of ABCA4 using single-molecule Molecular Inversion Probes (smMIPs) for 148 probands highlighted recurrent and novel CNVs associated with ABCA4-associated retinopathies. An analysis of the coverage depth in the sequencing data led to the identification of eleven deletions (six novel and five recurrent), three duplications (one novel and two recurrent) and one complex CNV. Of particular interest was the identification of a complex defect, i.e., a 15.3 kb duplicated segment encompassing exon 31 through intron 41 that was inserted at the junction of a downstream 2.7 kb deletion encompassing intron 44 through intron 47. In addition, we identified a 7.0 kb tandem duplication of intron 1 in three cases. The identification of CNVs in ABCA4 can provide patients and their families with a genetic diagnosis whilst expanding our understanding of the complexity of diseases caused by ABCA4 variants.
Multimodal Biosensing of Foodborne Pathogens
Authors: Ullah Najeeb , Bruce-Tagoe Tracy Ann , Asamoah George Adu , Danquah Michael K.
Published: May 2024

Microbial foodborne pathogens present significant challenges to public health and the food industry, requiring rapid and accurate detection methods to prevent infections and ensure food safety. Conventional single biosensing techniques often exhibit limitations in terms of sensitivity, specificity, and rapidity. In response, there has been a growing interest in multimodal biosensing approaches that combine multiple sensing techniques to enhance the efficacy, accuracy, and precision in detecting these pathogens. This review investigates the current state of multimodal biosensing technologies and their potential applications within the food industry. Various multimodal biosensing platforms, such as opto-electrochemical, optical nanomaterial, multiple nanomaterial-based systems, hybrid biosensing microfluidics, and microfabrication techniques are discussed. The review provides an in-depth analysis of the advantages, challenges, and future prospects of multimodal biosensing for foodborne pathogens, emphasizing its transformative potential for food safety and public health. This comprehensive analysis aims to contribute to the development of innovative strategies for combating foodborne infections and ensuring the reliability of the global food supply chain.
Mesenchymal Stem Cells from Mouse Hair Follicles Inhibit the Development of Type 1 Diabetes
Authors: Mićanović Dragica , Stanisavljević Suzana , Li Hanluo , Koprivica Ivan , Jonić Natalija , Stojanović Ivana , Savković Vuk , Saksida Tamara
Published: May 2024

Mesenchymal stem cells (MSCs) are known for their immunosuppressive properties. Based on the demonstrated anti-inflammatory effect of mouse MSCs from hair follicles (moMSCORS) in a murine wound closure model, this study evaluates their potential for preventing type 1 diabetes (T1D) in C57BL/6 mice. T1D was induced in C57BL/6 mice by repeated low doses of streptozotocin. moMSCORS were injected intravenously on weekly basis. moMSCORS reduced T1D incidence, the insulitis stage, and preserved insulin production in treated animals. moMSCORS primarily exerted immunomodulatory effects by inhibiting CD4+ T cell proliferation and activation. Ex vivo analysis indicated that moMSCORS modified the cellular immune profile within pancreatic lymph nodes and pancreatic infiltrates by reducing the numbers of M1 pro-inflammatory macrophages and T helper 17 cells and upscaling the immunosuppressive T regulatory cells. The proportion of pathogenic insulin-specific CD4+ T cells was down-scaled in the lymph nodes, likely via soluble factors. The moMSCORS detected in the pancreatic infiltrates of treated mice presumably exerted the observed suppressive effect on CD4+ through direct contact. moMSCORS alleviated T1D symptoms in the mouse, qualifying as a candidate for therapeutic products by multiple advantages: non-invasive sampling by epilation, easy access, permanent availability, scalability, and benefits of auto-transplantation.
scZAG: Integrating ZINB-Based Autoencoder with Adaptive Data Augmentation Graph Contrastive Learning for scRNA-seq Clustering
Authors: Zhang Tianjiao , Ren Jixiang , Li Liangyu , Wu Zhenao , Zhang Ziheng , Dong Guanghui , Wang Guohua
Published: May 2024

Single-cell RNA sequencing (scRNA-seq) is widely used to interpret cellular states, detect cell subpopulations, and study disease mechanisms. In scRNA-seq data analysis, cell clustering is a key step that can identify cell types. However, scRNA-seq data are characterized by high dimensionality and significant sparsity, presenting considerable challenges for clustering. In the high-dimensional gene expression space, cells may form complex topological structures. Many conventional scRNA-seq data analysis methods focus on identifying cell subgroups rather than exploring these potential high-dimensional structures in detail. Although some methods have begun to consider the topological structures within the data, many still overlook the continuity and complex topology present in single-cell data. We propose a deep learning framework that begins by employing a zero-inflated negative binomial (ZINB) model to denoise the highly sparse and over-dispersed scRNA-seq data. Next, scZAG uses an adaptive graph contrastive representation learning approach that combines approximate personalized propagation of neural predictions graph convolution (APPNPGCN) with graph contrastive learning methods. By using APPNPGCN as the encoder for graph contrastive learning, we ensure that each cell’s representation reflects not only its own features but also its position in the graph and its relationships with other cells. Graph contrastive learning exploits the relationships between nodes to capture the similarity among cells, better representing the data’s underlying continuity and complex topology. Finally, the learned low-dimensional latent representations are clustered using Kullback–Leibler divergence. We validated the superior clustering performance of scZAG on 10 common scRNA-seq datasets in comparison to existing state-of-the-art clustering methods.
Identification of a Novel miR-195-5p/PNN Axis in Colorectal Cancer
Authors: Piccinno Emanuele , Scalavino Viviana , Labarile Nicoletta , De Marinis Lucia , Armentano Raffaele , Giannelli Gianluigi , Serino Grazia
Published: May 2024

Pinin (PNN) is a desmosome-associated protein that reinforces the organization of keratin intermediate filaments and stabilizes the anchoring of the cytoskeleton network to the lateral surface of the plasma membrane. The aberrant expression of PNN affects the strength of cell adhesion as well as modifies the intracellular signal transduction pathways leading to the onset of CRC. In our previous studies, we characterized the role of miR-195-5p in the regulation of desmosome junctions and in CRC progression. Here, with the aim of investigating additional mechanisms related to the desmosome complex, we identified PNN as a miR-195-5p putative target. Using a public data repository, we found that PNN was a negative prognostic factor and was overexpressed in colon cancer tissues from stage 1 of the disease. Then, we assessed PNN expression in CRC tissue specimens, confirming the overexpression of PNN in tumor sections. The increase in intracellular levels of miR-195-5p revealed a significant decrease in PNN at the mRNA and protein levels. As a consequence of PNN regulation by miR-195-5p, the expression of KRT8 and KRT19, closely connected to PNN, was affected. Finally, we investigated the in vivo effect of miR-195-5p on PNN expression in the colon of AOM/DSS-treated mice. In conclusion, we have revealed a new mechanism driven by miR-195-5p in the regulation of desmosome components, suggesting a potential pharmacological target for CRC therapy.
Deleting Mitochondrial Superoxide Dismutase 2 in Salivary Gland Ductal Epithelial Cells Recapitulates Non-Sjögren’s Sicca Syndrome
Authors: Papinska Joanna A. , Durślewicz Justyna , Bagavant Harini , Deshmukh Umesh S.
Published: May 2024

Elevated oxidative stress can play a pivotal role in autoimmune diseases by exacerbating inflammatory responses and tissue damage. In Sjögren’s disease (SjD), the contribution of oxidative stress in the disease pathogenesis remains unclear. To address this question, we created mice with a tamoxifen-inducible conditional knockout (KO) of a critical antioxidant enzyme, superoxide dismutase 2 (Sod2), in the salivary glands (i-sg-Sod2 KO mice). Following tamoxifen treatment, Sod2 deletion occurred primarily in the ductal epithelium, and the salivary glands showed a significant downregulation of Sod2 expression. At twelve weeks post-treatment, salivary glands from the i-sg-Sod2 KO mice exhibited increased 3-Nitrotyrosine staining. Bulk RNA-seq revealed alterations in gene expression pathways related to ribosome biogenesis, mitochondrial function, and oxidative phosphorylation. Significant changes were noted in genes characteristic of salivary gland ionocytes. The i-sg-Sod2 KO mice developed reversible glandular hypofunction. However, this functional loss was not accompanied by glandular lymphocytic foci or circulating anti-nuclear antibodies. These data demonstrate that although localized oxidative stress in salivary gland ductal cells was insufficient for SjD development, it induced glandular dysfunction. The i-sg-Sod2 KO mouse resembles patients classified as non-Sjögren’s sicca and will be a valuable model for deciphering oxidative-stress-mediated glandular dysfunction and recovery mechanisms.
High-Yield α-Synuclein Purification and Ionic Strength Modification Pivotal to Seed Amplification Assay Performance and Reproducibility
Authors: Janarthanam Chelva , Clabaugh Griffin , Wang Zerui , Melvin Bradley R. , Scheibe Ileia , Jin Huajun , Anantharam Vellareddy , Urbauer Ramona J. B. , Urbauer Jeffrey L. , Ma Jiyan , Kanthasamy Arthi , Huang Xuemei , Donadio Vincenzo , Zou Wenquan , Kanthasamy Anumantha G.
Published: May 2024

Alpha-synuclein seed amplification assays (αSyn-SAAs) have emerged as promising diagnostic tools for Parkinson’s disease (PD) by detecting misfolded αSyn and amplifying the signal through cyclic shaking and resting in vitro. Recently, our group and others have shown that multiple biospecimens, including CSF, skin, and submandibular glands (SMGs), can be used to seed the aggregation reaction and robustly distinguish between patients with PD and non-disease controls. The ultrasensitivity of the assay affords the ability to detect minute quantities of αSyn in peripheral tissues, but it also produces various technical challenges of variability. To address the problem of variability, we present a high-yield αSyn protein purification protocol for the efficient production of monomers with a low propensity for self-aggregation. We expressed wild-type αSyn in BL21 Escherichia coli, lysed the cells using osmotic shock, and isolated αSyn using acid precipitation and fast protein liquid chromatography (FPLC). Following purification, we optimized the ionic strength of the reaction buffer to distinguish the fluorescence maximum (Fmax) separation between disease and healthy control tissues for enhanced assay performance. Our protein purification protocol yielded high quantities of αSyn (average: 68.7 mg/mL per 1 L of culture) and showed highly precise and robust αSyn-SAA results using brain, skin, and SMGs with inter-lab validation.
A Comparative Study of Different Milling Strategies on Productivity, Tool Wear, Surface Roughness, and Vibration
Authors: Silva Francisco J. G. , Martinho Rui P. , Magalhães Luís L. , Fernandes Filipe , Sales-Contini Rita C. M. , Durão Luís M. , Casais Rafaela C. B. , Sousa Vitor F. C.
Published: May 2024

Strategies for obtaining deep slots in soft materials can vary significantly. Conventionally, the tool travels along the slot, removing material mainly with the side cutting edges. However, a “plunge milling” strategy is also possible, performing the cut vertically, taking advantage of the tip cutting edges that almost reach the center of the tool. Although both strategies are already commonly used, there is a clear gap in the literature in studies that compare tool wear, surface roughness, and productivity in each case. This paper describes an experimental study comparing the milling of deep slots in AA7050-T7451 aluminum alloy, coated with a novel DLCSiO500W3.5O2 layer to minimize the aluminum adhesion to the tool, using conventional and plunge milling strategies. The main novelty of this paper is to present a broad study regarding different factors involved in machining operations and comparing two distinct strategies using a novel tool coating in the milling of aeronautical aluminum alloy. Tool wear is correlated with the vibrations of the tools in each situation, the cycle time is compared between the cases studied, and the surface roughness of the machined surfaces is analyzed. This study concludes that the cycle time of plunge milling can be about 20% less than that of conventional milling procedures, favoring economic sustainability and modifying the wear observed on the tools. Plunge milling can increase productivity, does not increase tool tip wear, and avoids damaging the side edges of the tool, which can eventually be used for final finishing operations. Therefore, it can be said that the plunge milling strategy improves economic and environmental sustainability as it uses all the cutting edges of the tools in a more balanced way, with less global wear.
Achieving Equiaxed Transition and Excellent Mechanical Properties in a Novel Near-β Titanium Alloy by Regulating the Volume Energy Density of Selective Laser Melting
Authors: Li Xiaofei , Cheng Huanhuan , Shi Chengcheng , Liu Rui , Wang Ruyue , Yang Chuan
Published: May 2024

This research investigated the relationship between volume energy density and the microstructure, density, and mechanical properties of the Ti-5Al-5Mo-3V-1Cr-1Fe alloy fabricated via the SLM process. The results indicate that an increase in volume energy density can promote a transition from a columnar to an equiaxed grain structure and suppress the anisotropy of mechanical properties. Specifically, at a volume energy density of 83.33 J/mm3, the average aspect ratio of β grains reached 0.77, accompanied by the formation of numerous nano-precipitated phases. Furthermore, the relative density of the alloy initially increased and then decreased as the volume energy density increased. At a volume energy density of 83.33 J/mm3, the relative density reached 99.6%. It is noteworthy that an increase in volume energy density increases the β grain size. Consequently, with a volume energy density of 83.33 J/mm3, the alloy exhibited an average grain size of 63.92 μm, demonstrating optimal performance with a yield strength of 1003.06 MPa and an elongation of 18.16%. This is mainly attributable to the fact that an increase in volume energy density enhances thermal convection within the molten pool, leading to alterations in molten pool morphology and a reduction in temperature gradients within the alloy. The reduction in temperature gradients promotes equiaxed grain transformation and grain refinement by increasing constitutive supercooling at the leading edge of the solid–liquid interface. The evolution of molten pool morphology mainly inhibits columnar grain growth and refines grain by changing the grain growth direction. This study provided a straightforward method for inhibiting anisotropy and enhancing mechanical properties.
The Different Properties of Geopolymer Composites Reinforced with Flax Fibers and Carbon Fibers
Authors: Brugaletta Francesca , Becher Anton Frederik , Rostagno Danilo Laurent , Kim JeongHye , Fresneda Medina José Ignacio , Ziejewska Celina , Marczyk Joanna , Korniejenko Kinga
Published: May 2024

The main motivation for this research was to improve the properties of geopolymers by reinforcement using synthetic and natural fibers, and to gain new knowledge regarding how the nature and/or the quantity of reinforcement fibers influences the properties of the final geopolymers. The main objective was to investigate the effects of different types of reinforcement fibers on the properties of the geopolymers. These reinforcement fibers were mainly environmentally friendly materials that can be used as alternatives to ordinary Portland cement. The authors used fly ash and river sand as the raw materials for the matrix, and added carbon fibers (CF), flax fibers (FF), or a hybrid of both (CFM) as reinforcements. The samples were prepared by mixing, casting, and curing, and then subjected to various tests. The main research methods used were compressive strength (CS), flexural strength (FS), water absorption (WA), abrasion resistance (Böhme’s disk method), microstructure analysis (SEM), chemical composition (XRF), and crystal structure analysis (XRD). The results showed that the addition of fibers partially improved the mechanical properties of the geopolymers, as well as reducing microcracks. The CF-reinforced geopolymers exhibited the highest compressive strength, while the FF-reinforced geopolymers showed the lowest water absorption. The authors, based on previous research, also discussed the factors that influence fiber-matrix adhesion, and the optimal fiber content for geopolymers.
Effects of Misalignment of c-axis on the Properties of Hydrogenation–Disproportionation–Desorption–Recombination Particles
Authors: Wang Xuhua , Wang Zilong , Yang Yuanfei , Quan Ningtao , Wang Zhongkai , Peng Haijun , Zhang Hongbin , Sun Xiaojun , Cui Shuai , Yu Dunbo , Luo Yang
Published: May 2024

Hydrogenation–Disproportionation–Desorption–Recombination (HDDR) Nd2Fe14B particles have excellent magnetic properties, but the magnetic properties of powder are not uniform across different particle sizes. The remanence and maximum magnetic energy products of samples with a particle size of 120 μm are 14.0 kGs and 41.35 MGOe, while the products of samples with a particle size of 60 μm are only 13.3 kGs and 36.31 MGOe. The macroscopic morphology of HDDR Nd2Fe14B particles and the gradient distribution of microstructures in different micro-regions were observed. By modifying the macroscopic morphology of the particles, the poorly oriented clusters on the surface of the particles were precisely eliminated, and the remanence and maximum magnetic energy products of the particles increased to 14.5 kGs and 45 MGOe, respectively. Compared with the original particles, the samples after mechanical grinding had better grain arrangement. The effects of the nanocrystalline c-axis and field misalignment angle θ on the magnetic properties of HDDR Nd2Fe14B particles were investigated through micromagnetic simulation. The targeted removal of macroscopic defects on the particle surface contributed to a 3.6% increase in remanence and an 8.8% increase in the maximum magnetic energy product, offering a promising approach to enhance the microstructure of high-performance HDDR Nd2Fe14B particles.
Effects of Mixing Techniques and Material Compositions on the Compressive Strength and Thermal Conductivity of Ultra-Lightweight Foam Concrete
Authors: Xu Tongyu , Garrecht Harald
Published: May 2024

The research focuses on ultra-lightweight foam concrete with a dry density below 200 kg/m3, primarily used as insulation material. Factors that may affect material properties are categorized into mixing techniques and material composition, and experimental investigations were conducted on the impact of these factors on the rheological properties of cement slurry, density at different time intervals, compressive strength, and thermal conductivity of foam concrete samples. The experimental results indicate the influence of mixing speed and mixing duration on the instrument during the cement slurry production and mixing process with foam. Additionally, variations in foam concrete sample properties are observed due to the water-to-cement ratio, foam content, and foam density in the selected material compositions. By analyzing the material density at different time intervals, the relationship between the ambient air trapped during the mixing process and the viscosity of the material can be indirectly observed. This analysis can also reveal the correlation between the unplanned air content and the properties of the material.
Enhancing Mesopore Volume and Thermal Insulation of Silica Aerogel via Ambient Pressure Drying-Assisted Foaming Method
Authors: Guo Jinjing , Luo Kaiqiang , Zou Wenqi , Xu Jun , Guo Baohua
Published: May 2024

Ambient pressure drying (APD) of silica aerogels has emerged as an attractive method adapting to large-scale production. Spring-back is a unique phenomenon during APD of silica aerogels with volume expansion after its shrinkage under capillary force. We attribute the intense spring-back at elevated drying temperatures to a dense structure formed on the surface and the formation of positive internal pressure. Furthermore, an APD-assisted foaming method with an in situ introduction of NH4HCO3 was proposed. NH4HCO3 decomposing at drying temperatures hastened the emergence of positive pressure, thereby increasing the expansion volume. Compared to the previous method, the porosity of silica aerogel increased from 82.2% to 92.6%, and mesopore volume from 1.79 cm3 g−1 to 4.54 cm3 g−1. By adjusting the amount of the silicon source, silica aerogels prepared by the APD-assisted foaming method generated higher volume expansion and lower thermal conductivity. After calcination to remove undecomposed ammonium salts, the hydrophobic silica aerogel with a density of 0.112 g cm−3 reached a mesopore volume of 5.07 cm3 g−1 and a thermal conductivity of 18.9 mW m−1·K−1. This strategy not only improves the thermal insulation properties, but also offers a significant advancement in tailoring silica aerogels with specific porosity and mesopore volume for various applications.
An FTwNB Shield: A Credit Risk Assessment Model for Data Uncertainty and Privacy Protection
Authors: Hua Shaona , Zhang Chunying , Yang Guanghui , Fu Jinghong , Yang Zhiwei , Wang Liya , Ren Jing
Published: May 2024

Credit risk assessment is an important process in bank financial risk management. Traditional machine-learning methods cannot solve the problem of data islands and the high error rate of two-way decisions, which is not conducive to banks’ accurate credit risk assessment of users. To this end, this paper establishes a federated three-way decision incremental naive Bayes bank user credit risk assessment model (FTwNB) that supports asymmetric encryption, uses federated learning to break down data barriers between banks, and uses asymmetric encryption to protect data security for federated processes. At the same time, the model combines the three-way decision methods to realize the three-way classification of user credit (good, bad and delayed judgment), so as to avoid the loss of bank interests caused by the forced division of uncertain users. In addition, the model also incorporates incremental learning steps to eliminate training samples with poor data quality to further improve the model performance. This paper takes German Credit data and Default of Credit Card Clients data as examples to conduct simulation experiments. The result shows that the performance of the FTwNB model has been greatly improved, which verifies that it has good credit risk assessment capabilities.
A Study on Caregiver Activity Recognition for the Elderly at Home Based on the XGBoost Model
Authors: Liu Zhonghua , Zhang Shuang , Zhang Huihui , Li Xiuxiu
Published: May 2024

This paper aims to discuss the implementation of data analysis and information management for elderly nursing care from a data-driven perspective. It addresses the current challenges of in-home caregivers, providing a basis for decision making in analyzing nursing service content and evaluating job performance. The characteristics of caregivers’ activities were analyzed during the design of a wearable device-wearing scheme and a sensor data collection system. XGBoost, SVM, and Random Forest models were used in the experiments, with the Cuckoo search algorithm employed to optimize the XGBoost model parameters. Based on the control group experiment, it was confirmed that the XGBoost model, after adjusting the parameters using the Cuckoo search algorithm, exhibited better recognition performance than the SVM and RandomForest models, and the accuracy reached 0.9438. Wearable devices present high recognition accuracy in caregiver activity recognition research, which greatly improves the inspection of caregivers’ work and further promotes the completion of services. This study actively explores the applications of information technology and artificial intelligence theory to address practical problems and effectively promote the digitalization and intelligent development of the elderly nursing care industry.
Solving the Vehicle Routing Problem with Time Windows Using Modified Rat Swarm Optimization Algorithm Based on Large Neighborhood Search
Authors: Wei Xiaoxu , Xiao Zhouru , Wang Yongsheng
Published: May 2024

The vehicle routing problem with time windows (VRPTW) remains a formidable challenge, due to the intricate constraints of vehicle capacity and time windows. As a result, an algorithm tailored for this problem must demonstrate robust search capabilities and profound exploration abilities. Traditional methods often struggle to balance global search capabilities with computational efficiency, thus limiting their practical applicability. To address these limitations, this paper introduces a novel hybrid algorithm known as large neighborhood search with modified rat swarm optimization (LNS-MRSO). Modified rat swarm optimization (MRSO) is inspired by the foraging behavior of rat swarms and simulates the search process for optimization problems. Meanwhile, large neighborhood search (LNS) generates potential new solutions by removing and reinserting operators, incorporating a mechanism to embrace suboptimal solutions and strengthening the algorithm’s prowess in global optimization. Initial solutions are greedily generated, and five operators are devised to mimic the position updates of the rat swarm, providing rich population feedback to LNS and further enhancing algorithm performance. To validate the effectiveness of LNS-MRSO, experiments were conducted using the Solomon VRPTW benchmark test set. The results unequivocally demonstrate that LNS-MRSO achieves optimal solutions for all 39 test instances, particularly excelling on the R2 and RC2 datasets with percentage deviations improved by 5.1% and 8.8%, respectively, when compared to the best-known solutions (BKSs). Furthermore, when compared to state-of-the-art algorithms, LNS-MRSO exhibits remarkable advantages in addressing VRPTW problems with high loading capacities and lenient time windows. Additionally, applying LNS-MRSO to an unmanned concrete-mixing station further validates its practical utility and scalability.
Imbalanced Data Classification Based on Improved Random-SMOTE and Feature Standard Deviation
Authors: Zhang Ying , Deng Li , Wei Bo
Published: May 2024

Oversampling techniques are widely used to rebalance imbalanced datasets. However, most of the oversampling methods may introduce noise and fuzzy boundaries for dataset classification, leading to the overfitting phenomenon. To solve this problem, we propose a new method (FSDR-SMOTE) based on Random-SMOTE and Feature Standard Deviation for rebalancing imbalanced datasets. The method first removes noisy samples based on the Tukey criterion and then calculates the feature standard deviation reflecting the degree of data discretization to detect the sample location, and classifies the samples into boundary samples and safety samples. Secondly, the K-means clustering algorithm is employed to partition the minority class samples into several sub-clusters. Within each sub-cluster, new samples are generated based on random samples, boundary samples, and the corresponding sub-cluster center. The experimental results show that the average evaluation value obtained by FSDR-SMOTE is 93.31% (93.16%, and 86.53%) in terms of the F-measure (G-mean, and MCC) on the 20 benchmark datasets selected from the UCI machine learning library.
Stem-Cell-Regenerative and Protective Effects of Squid (Symplectoteuthis oualaniensis) Skin Collagen Peptides against H2O2-Induced Fibroblast Injury
Authors: Wei Mingjun , Jeevithan Lakshmi , Li Na , Liu Lixin , Xu Jiren , Wu Wenhui , Elango Jeevithan
Published: May 2024

Recently, there has been a growing interest in collagen peptides derived from marine sources for their notable ability to protect skin cells against apoptosis induced by oxidants. Therefore, the current study aimed to investigate the fundamental properties of collagen peptides, including their physicochemical, thermal, structural, stem-cell-regenerative, and skin-cell-protective effects, in comparison to commercial collagen peptides. The acid-soluble (ASC) and pepsin-soluble (PSC) collagens exhibited three distinct bands on SDS-PAGE, namely α (α1 and α2), β, and γ chains, confirming a type I pattern. The thermal profiles obtained from TG and DSC analyses confirmed the denaturation of PSC and ASC at temperatures ranging from 51.94 to 56.4 °C and from 52.07 to 56.53 °C, respectively. The purified collagen peptides were analyzed using SDS-PAGE and MALDI-TOF mass spectrometry, revealing a mass range of 900–15,000 Da. Furthermore, the de novo peptide sequence analysis confirmed the presence of the Gly-X-Y repeating sequence in collagen peptides. Collagen peptide treatments significantly enhanced HFF-1 cell proliferation and migration compared to the control group. ELISA results confirmed the potential interactions between collagen peptides and HFF-1 cells through α2β1, α10β1, and α11β1 integrin receptors. Notably, collagen peptide treatment effectively restored the proliferation of HFF-1 cells damaged by H2O2. Consequently, the advantageous characteristics of squid skin collagen peptides highlight their promising role in regenerative medicine.
Simulation of Bubble Behavior Characteristics in a Rolling Fluidized Bed with the Addition of Longitudinal Internal Members
Authors: Xu Rongsheng , Wang Ruojin , Wu Banghua , Yuan Xiaopei , Wang Dewu , Liu Yan , Zhang Shaofeng
Published: May 2024

To address the effect of a ship’s rolling on the fluidization quality of fluidized beds, in this study, a simulation of a rolling fluidized bed with longitudinal internal members added (R-FBLIM) was carried out and compared with that of a rolling fluidized bed without internal members added (R-FBWIM). The transient motion, as well as the behavioral characteristics of the bubbles within the R-FBLIM, was analyzed; the variation patterns of the number of bubbles, as well as the equivalent diameter of the bubbles, were compared for different apparent gas velocities, oscillation periods, and amplitudes; and the mechanism of the action of the longitudinal internal members was investigated. The results show that the structural design of the longitudinal internal members can effectively improve the gas–solid fluidization quality of the rolling fluidized bed. The horizontal support plate and the cap hole structure can effectively break the air bubbles, the cap hole structure promotes the radial mixing of the gas–solid fluid, and the internal and outer rings of the curved surface plate roll in rows, which inhibit the aggregation behavior of the gas–solid fluid to the two sides of the oscillating planes, respectively, by cooperating with the cap hole structure. Compared with R-FBWIM, the gas–solid phase within R-FBLIM is more spatially distributed, with the number of bubbles increasing by about 2–4 times and the mean diameter decreasing by about 50–60%. The number of bubbles increases with the gas velocity but decreases with the rolling amplitude; the mean diameter decreases with the gas velocity but responds less to the rolling amplitude change.
Semantic Aware Stitching for Panorama
Authors: Jia Yuan , Li Zhongyao , Zhang Lei , Song Bin , Song Rui
Published: May 2024

The most critical aspect of panorama generation is maintaining local semantic consistency. Objects may be projected from different depths in the captured image. When warping the image to a unified canvas, pixels at the semantic boundaries of the different views are significantly misaligned. We propose two lightweight strategies to address this challenge efficiently. First, the original image is segmented as superpixels rather than regular grids to preserve the structure of each cell. We propose effective cost functions to generate the warp matrix for each superpixel. The warp matrix varies progressively for smooth projection, which contributes to a more faithful reconstruction of object structures. Second, to deal with artifacts introduced by stitching, we use a seam line method tailored to superpixels. The algorithm takes into account the feature similarity of neighborhood superpixels, including color difference, structure and entropy. We also consider the semantic information to avoid semantic misalignment. The optimal solution constrained by the cost functions is obtained under a graph model. The resulting stitched images exhibit improved naturalness. Extensive testing on common panorama stitching datasets is performed on the algorithm. Experimental results show that the proposed algorithm effectively mitigates artifacts, preserves the completeness of semantics and produces panoramic images with a subjective quality that is superior to that of alternative methods.
A CMOS Current-Mode Vertical-Cavity-Semiconductor-Emitting-Laser Diode Driver for Short-Range LiDAR Sensors
Authors: Zhang Xinyue , Choi Shinhae , Chon Yeojin , Park Sung-Min
Published: May 2024

This paper presents a current-mode VCSEL driver (CMVD) implemented using 180 nm CMOS technology for application in short-range LiDAR sensors, in which current-steering logic is suggested to deliver modulation currents from 0.1 to 10 mApp and a bias current of 0.1 mA simultaneously to the VCSEL diode. For the simulations, the VCSEL diode is modeled with a 1.6 V forward-bias voltage and a 50 Ω series resistor. The post-layout simulations of the proposed CMVD clearly demonstrate large output pulses and eye-diagrams. Measurements of the CMVD demonstrate large output pulses, confirming the simulation results. The chip consumes a maximum of 11 mW from a 3.3 V supply, and the core occupies an area of 0.1 mm2.
Planning Socially Expressive Mobile Robot Trajectories
Authors: Scales Philip , Aycard Olivier , Aubergé Véronique
Published: May 2024

Many mobile robotics applications require robots to navigate around humans who may interpret the robot’s motion in terms of social attitudes and intentions. It is essential to understand which aspects of the robot’s motion are related to such perceptions so that we may design appropriate navigation algorithms. Current works in social navigation tend to strive towards a single ideal style of motion defined with respect to concepts such as comfort, naturalness, or legibility. These algorithms cannot be configured to alter trajectory features to control the social interpretations made by humans. In this work, we firstly present logistic regression models based on perception experiments linking human perceptions to a corpus of linear velocity profiles, establishing that various trajectory features impact human social perception of the robot. Secondly, we formulate a trajectory planning problem in the form of a constrained optimization, using novel constraints that can be selectively applied to shape the trajectory such that it generates the desired social perception. We demonstrate the ability of the proposed algorithm to accurately change each of the features of the generated trajectories based on the selected constraints, enabling subtle variations in the robot’s motion to be consistently applied. By controlling the trajectories to induce different social perceptions, we provide a tool to better tailor the robot’s actions to its role and deployment context to enhance acceptability.
Antecedents and Context of Chinese Firms’ Foreign Exit
Authors: Ding Sasa , Liu Yajun
Published: May 2024

This paper examines the outward foreign direct investment events of Chinese manufacturing firms from 2008 to 2022. It explores how sunk cost and performance feedback drive firms’ foreign exit strategies based on the behavioral theory of the firm. Additionally, it also examines the contextual factor that may affect the focal relationship. We adopt a panel logistic estimation to test the hypotheses. The conclusions show that firms are more likely to exit overseas markets when faced with sunk costs and negative performance feedback. Conversely, positive performance feedback significantly decreases the probability of firms exiting foreign markets. Additionally, environmental munificence and complexity can weaken the strength of the focal nexus to some extent. These findings hold both theoretical and practical significance for multinational enterprises and the government in the context of the ‘dual-circulation strategy’.
Noroviruses: Evolutionary Dynamics, Epidemiology, Pathogenesis, and Vaccine Advances—A Comprehensive Review
Authors: Omatola Cornelius Arome , Mshelbwala Philip Paul , Okolo Martin-Luther Oseni , Onoja Anyebe Bernard , Abraham Joseph Oyiguh , Adaji David Moses , Samson Sunday Ocholi , Okeme Therisa Ojomideju , Aminu Ruth Foluke , Akor Monday Eneojo , Ayeni Gideon , Muhammed Danjuma , Akoh Phoebe Queen , Ibrahim Danjuma Salisu , Edegbo Emmanuel , Yusuf Lamidi , Ocean Helen Ojomachenwu , Akpala Sumaila Ndah , Musa Oiza Aishat , Adamu Andrew Musa
Published: May 2024

Noroviruses constitute a significant aetiology of sporadic and epidemic gastroenteritis in human hosts worldwide, especially among young children, the elderly, and immunocompromised patients. The low infectious dose of the virus, protracted shedding in faeces, and the ability to persist in the environment promote viral transmission in different socioeconomic settings. Considering the substantial disease burden across healthcare and community settings and the difficulty in controlling the disease, we review aspects related to current knowledge about norovirus biology, mechanisms driving the evolutionary trends, epidemiology and molecular diversity, pathogenic mechanism, and immunity to viral infection. Additionally, we discuss the reservoir hosts, intra–inter host dynamics, and potential eco-evolutionary significance. Finally, we review norovirus vaccines in the development pipeline and further discuss the various host and pathogen factors that may complicate vaccine development.
Changes in the Transcriptome Profile in Young Chickens after Infection with LaSota Newcastle Disease Virus
Authors: Lopes Taina S. B. , Nankemann Jannis , Breedlove Cassandra , Pietruska Andrea , Espejo Raimundo , Cuadrado Camila , Hauck Ruediger
Published: May 2024

Understanding gene expression changes in chicks after vaccination against Newcastle Disease (ND) can reveal vaccine biomarkers. There are limited data on chicks’ early immune response after ND vaccination. Two trials focused on this knowledge gap. In experiment one, 42 13-day-old specific-pathogen-free (SPF) chicks were used. Harderian glands (Hgs) and tracheas (Tcs) from five birds per group were sampled at 12, 24, and 48 h post-vaccination (hpv) to evaluate the gene transcription levels by RNA sequencing (RNA-seq) and RT-qPCR. The results of RNA-seq were compared by glmFTest, while results of RT-qPCR were compared by t-test. With RNA-seq, a significant up-regulation of interferon-related genes along with JAK-STAT signaling pathway regulation was observed in the Hgs at 24 hpv. None of the differentially expressed genes (DEGs) identified by RNA-seq were positive for RT-qPCR. Experiment 2 used 112 SPF and commercial chickens that were 1 day old and 14 days old. Only the commercial birds had maternal antibodies for Newcastle Disease virus (NDV). By RNA-seq, 20 core DEGs associated with innate immunity and viral genome replication inhibition were identified. Genes previously unlinked to NDV response, such as USP41, were identified. This research present genes with potential as immunity biomarkers for vaccines, yet further investigation is needed to correlate the core gene expression with viral shedding post-vaccination.
Pregnancy Rates of Holstein Friesian Cows with Cavitary or Compact Corpus Luteum
Authors: Vincze Boglárka , Kátai Levente , Deák Kamilla , Nagy Krisztina , Cseh Sándor , Kovács Levente
Published: May 2024

Cavitary corpora lutea are commonly observed during the estrous cycle in bovines. Since the quality of the corpus luteum (CL) is extremely important during embryo transfer when embryos are implanted into the recipient, the ultrasonographic examination of the CL is becoming more and more important in terms of the outcome of the procedure. In the present study, a total of 2477 ultrasonographic transrectal diagnoses were performed, and data were collected between the years of 2018 and 2020 in a large-scale Holstein Friesian dairy farm in Hungary. In 91.1% (n = 2257) and in 8.9% (n = 220) of the cases, compact CLs and cavitary CLs, respectively, were diagnosed at pregnancy diagnosis. The presence of a cavitary CL on the ovary at pregnancy diagnosis increased the odds of remaining open after pregnancy by 21 times compared to the presence of a compact CL (OR = 21.0, p < 0.001) in the cows. The presence of cavitary CL was not influenced either by month or season. Ovarian cysts were detected in 196 cases (8.0%) in the examined animals. The presence of a cavitary CL decreased by 9 times when an ovarian cyst was also diagnosed (OR = 9.0, 1.6% vs. 9.5%, p < 0.001). The presence of an ovarian cyst decreased the odds of established pregnancy by 81 times (OR = 81.1, p < 0.001). Based on our results, the presence of a cavitary CL between days 31 and 42 after artificial insemination is associated with a smaller chance of conception in Holstein Friesian cows. The presence of an ovarian cyst decreases the occurrence of cavitary CL and the chance of conception.
Hábitos en el matrimonio mixto de los creyentes Adventista del Séptimo Día en una localidad peruana
Authors: Vaca Espino Jaim , Martinez Tejada Victoria , Balabarca Cárdenas Yván
Published: May 2024

Este estudio explora las experiencias de matrimonios mixtos en la Iglesia Adventista del Séptimo Día de Chosica, Lima, 2022. El objetivo es identificar las experiencias que impactan en el acoplamiento de pareja. Utilizando un enfoque cualitativo y un diseño fenomenológico, se entrevistaron 9 personas con experiencia en matrimonios mixtos. Los hallazgos revelan que las prácticas religiosas, los valores y las creencias religiosas influyen significativamente en estos matrimonios, generando conflictos y momentos de crisis. Se identificaron 7 experiencias causales, 14 experiencias resultantes y 7 momentos de crisis. Además, se encontraron 10 diferencias en prácticas religiosas, 4 en valores y 9 en creencias religiosas, todas impactando en el acoplamiento de pareja. Estas conclusiones subrayan la complejidad y los desafíos enfrentados por los matrimonios mixtos en esta comunidad religiosa.
MR-COV 19: ANDROID-BASED COVID-19 RISK PREDICTION APPLICATION WITH SENSITIVITY AND SPECIFICITY TESTS
Authors: Riviwanto Muchsin , Muslim Burhan , Wijayantono Wijayantono
Published: May 2024

Background. Therefore, the development and use of accurate predictors of susceptibility for COVID-19 prognosis will be beneficial for COVID-19 risk management, and will help reduce case and mortality rates. The aim of this researcher is to build an Android-based MR-Cov-19 application in order to reduce the impact of the spread of disease and increase community resilience against COVID-19.
Method. This study uses the prototype method in designing and building applications. To test this application, researchers conducted an android-based MR-Cov-19 screening test on 30 communities for self-assessment and 30 for institutional assessment in Padang City from July to August 2022, whose data were then tested for validity and reliability. This method is a 2x2 tabulation diagnostic confirmation tool that produces sensitivity, specificity, predictive value, and prevalence
Result. The MR-Cov19 application can determine the risk of covid-19. The MR-Cov19 application has been tested for validity and reliability using the android-based MR-Cov 19 test with 77.8% and 71.4% results. Based on the Positive Predictive Value (NPP) test, the results show 53.8% and the Negative Predictive Value (NPN) 88.2%, meaning that the NPP value is lower than the NPN
 
Conclusion. This MR-Cov19 application was built using android studio programming which can detect an individual at risk of covid-19. This android-based EPDS design has a home screen form design, a questionnaire form design and a result form design. This application displays results based on the multiplication of weights and scores for vulnerability, exposure, sensitivity and adaptive capacity.
ANALISIS PENERIMAAN PAJAK REKLAME TERHADAP PENINGKATKAN PENDAPATAN ASLI DAERAH (PAD) KOTA MEDAN
Authors: Ginting Felik ginitng
Published: May 2024

This research was conducted at the Regional Tax and Levy Management Agency of Medan City, North Sumatra. The aim of this research is to analyze the effectiveness of the advertising tax revenue budget and the realization of advertising tax budget revenues. Apart from that, it also analyzes the contribution of advertising tax to local revenue (PAD) in Medan City. So from this analysis it can be seen whether the advertising tax has been effective in achieving the predetermined budget and has made a good contribution to Medan City's PAD. The research method used in this research is descriptive, namely the results of interviews. Interviews were conducted to find out data on the advertising tax revenue budget and the realization of the advertising tax budget from 2010 to 2015. The data analysis technique used was a survey to the research location, namely the Medan City Revenue Service office. Realization of advertising tax revenue in 2010 was 92.98% (very effective). Realization of advertising tax revenue in 2011 was 55.55% (not effective). Realization of advertising tax revenue in 2012 was 40.45% (not effective). Realization of advertising tax revenue in 2013 was 35.32% (not effective). Realization of advertising tax revenue in 2014 was 19.49% (not effective). Realization of advertising tax revenue in 2014 was 7.23% (not effective).