bluuebunny/crossref_metadata_2025 huggingface dataset:
Current Trends and Application of Endovascular Thrombectomy in Patients with Acute Ischemic Stroke and Coexisting Cardiac Thrombus
Authors: Ali Zafar , Shatla Islam , Mufarrih Sayyeda Aleena , Khan Abdul Wali , Talluri Rithvik , Asif Talal
Published: May 2024

Cardiac embolism plays a very significant role in acute ischemic strokes (AIS), constituting approximately one-third of cases. The origin of these emboli often stems from intracardiac thrombi in the left atrium or left ventricle. Utilizing the National Readmission Database from 2016 to 2019, we investigate the prevalence of cardiac thrombi in AIS patients and explore their potential correlation with stroke severity, EVT utilization, and mortality rates. Among 1,272,456 AIS patients, 0.58% had concurrent cardiac thrombus, with an increasing trend observed over the study period (P value < 0.001). The cardiac thrombus cohort showed a higher prevalence of comorbidities such as congestive heart failure and atrial fibrillation. After propensity-score matching, groups were well-balanced in terms of baseline characteristics. Patients within the cardiac thrombus cohort experienced a longer hospital stay (median 5 days vs. 3 days), but no significant difference in mortality was noted. Importantly, the cardiac thrombus cohort demonstrated a higher frequency of EVT utilization, suggesting a link to larger vessel occlusions. Despite matching based on atrial fibrillation, the EVT utilization in the cardiac thrombus cohort remained high, highlighting a significant association. While 30-day readmission rates were comparable, cardiac thrombus patients faced a higher risk of gastrointestinal bleeding and hemorrhagic stroke, likely attributed to anticoagulation use. Limitations include potential miscoding in the administrative database and a lack of detailed imaging findings. In conclusion, this study highlights the increased likelihood of EVT in AIS patients with cardiac thrombus, possibly indicative of larger strokes. The observed rise in cardiac thrombus prevalence may stem from improved coding and increased utilization of cardiac MRI.
Relationships among Vitamin D Insufficiency, Health belief, Quality of Life and Metabolic Syndrome in Northeastern Taiwanese Adults: A Cross-sectional Community-based Cohort Study
Authors: Chen Sue-Hsien , Chen Shu-Ching , Lai Yo-Ping , Yeh Kun-Yun
Published: May 2024

Background
The association between vitamin D insufficiency (VDI) and metabolic syndrome (MetS) remains unclear. Little information is available regarding the association between the VDI and health-related quality of life (HRQoL) in the health belief model (HBM). This study aimed to investigate the association between the VDI, HBM, HRQoL, and MetS in community-based Taiwanese adults.
Methods
This cross-sectional study recruited 1015 Taiwanese patients aged ≥ 30 years between August 2019 and December 2021. Sociodemographic data, anthropometric variables, and vitamin D levels, defined as 25 (OH) D concentrations, were acquired from medical records and physical examinations. Data regarding health beliefs and HRQoL were obtained using a questionnaire.
Results
The mean 25(OH)D concentration was 29.59 ± 10.80 ng/mL and the overall prevalence of VDI was MetS was 54.9%. There was no significant difference in the incidence of MetS between the VDI and sufficiency groups. Multivariate analysis revealed that the risk factors associated with VDI development were female sex, age < 65 years, college and above education attainment, high LDL concentration, no alcohol use, and low scores on the emotional role item of HRQoL. There was no association between the VDI and HBM. In people with VDI, age, smoking, education level, blood pressure, perceived barriers, and self-efficacy in the HBM were correlated with HRQoL.
Conclusions
The VDI was not correlated with MetS incidence or HBM. Risk factors including age, female sex, education level, serum LDL concentration, alcohol use, and role-emotional items of HRQoL could be integrated into health initiative programs to reduce the risk of VDI.
Dual-layer Label Perception Algorithm for POI data with long-tailed distribution
Authors: TAN SHUTAO , WANG ZHEN
Published: May 2024

Authentic POI datasets often exhibit a long-tailed distribution, wherein instances vary significantly across labels, rendering conventional training methods ill-equipped to handle such real-world scenarios. This paper introduces a Dual-layer Label Perception Algorithm for POI Data, which pioneers the utilization of prevalent two-layer data labels to formulate a label feature cloud, subsequently enhancing classification accuracy by broadening and refining the distribution of label features. To assess the algorithm's efficacy, extensive experimentation is conducted on genuine urban POI datasets, resulting in a notable 5% enhancement in the comprehensive F1-Score, reaching 79.41%. The experimental findings affirm the algorithm model's efficacy in enhancing its detection performance across various advanced text classification algorithms.
Multi-objective optimization design of low-power-driven, large-flux, and fast-response three-stage valve
Authors: Ma Aixiang , Xiao Heruizhi , Hao Yue , Yan Xihao , Zhao Sihai
Published: May 2024

Solenoid valves in coal mining equipment are driven by intrinsically safe solenoids. The low power consumption of these solenoids limits the response time of the solenoid valves. Additionally, the low viscosity and high susceptibility to dust contamination of the emulsion fluid often leads to leakage and sticking of hydraulic valves. To address these issues, this study proposes a low-power-driven, large-flux, fast-response three-stage valve structure with an internal displacement feedback device. The driving power of this structure is less than 1.2 W. The key parameters of the valve were optimized using a novel multi-objective optimization algorithm. A prototype was manufactured based on the obtained parameters and subjected to simulation and experimental verification. The results demonstrate that the valve has an opening time of 21ms, a closing time of 12ms, and a maximum flow rate of approximately 225L/min. By utilizing this valve for hydraulic cylinder control, a positioning accuracy of ±0.15mm was achieved.
The L-shaped Relationship Between Composite Dietary Antioxidant Index and Cognitive Impairment in the American Elderly: A Cross-Sectional Study (NHANES 2011-2014)
Authors: Yang Hang , Wang Xiaoying , Zhou Ye , Zhang Shenyingjie , Gao Zhenzhen
Published: May 2024

Background
Oxidative stress is involved in the development and progression of cognitive impairment. However, the association between composite dietary antioxidant index (CDAI) and cognitive impairment remains unknown.
Objective
This cross-sectional study investigated the non-linear relationship between CDAI and cognitive impairment among the American elderly.
Methods
The public data was available from the United States National Health and Nutrition Examination Survey from 2011 to 2014. Participants aged ≥ 60 years were eligible for cognitive function, including word learning and recall modules from the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), the animal fluency test (AFT), and the digit symbol substitution test (DSST). A composite cognition score was created to evaluate global cognition. The univariate and multivariate logistic regression analysis, restricted cubic spline, stratified and sensitivity analysis were conducted.
Results
CDAI was negatively associated with cognitive impairment. For each standard deviation increase in CDAI, the risk of cognitive impairment decreased by 6% for DSST (OR = 0.94, 95% CI: 0.9, 0.97), 7% for AFT (OR = 0.93, 95% CI: 0.9, 0.96), 4% for CERAD (OR = 0.96, 95% CI: 0.93, 0.99), and 7% for global cognition (OR = 0.93, 95% CI: 0.9, 0.96) after adjusting for multiple potential confounders. This significant negative relationship remained consistent when comparing individuals in the highest CDAI tertile with those in the lowest CDAI tertile. Furthermore, a non-linear relationship was observed between CDAI and cognitive impairment on AFT (P for non-linearity = 0.009) and global cognition (P for non-linearity = 0.006).These negative correlations between CDAI and cognitive impairment were observed across the stratified age, gender, poverty-to-income ratio, body mass index, hypertension, and diabetes. However, the interaction test revealed significance for education on DSST (P for interaction = 0.04). Moreover, vitamin E, zinc, selenium, and carotenoids were independently associated with cognitive impairment in this study. The sensitivity analysis for participants with complete covariates yielded a similar finding.
Conclusion
These findings suggested a negative and L-shaped association between the CDAI and the risk of cognitive impairment among the American elderly. The results have significant implications for public health initiatives to prevent and limit the progression of cognitive impairment through dietary interventions.
CRP and IHF act as host regulators in Royal Jelly's antibacterial activity
Authors: Xia Zhenyu , Li Yunchang , Liu Jinhao , Chen Yanping , Liu Chenguang , Hao Yue
Published: May 2024

Royal Jelly (RJ) is a natural substance produced by honeybees, serving not only as nutrition for bee brood and queens but also as a functional food due to its health-promoting properties. Despite its well-known broad-spectrum antibacterial activity, the precise molecular mechanism underlying its antibacterial action has remained elusive. In this study, we investigated the impact of RJ on the bacteria model MG1655 at its half maximal inhibitory concentration, employing LC-MS/MS to analyze proteomic changes. The differentially expressed proteins were found to primarily contribute to suppressing gene expression processes, specifically transcription and translation, disrupting nutrition and energy metabolism, and inducing oxidative stress. Notably, RJ treatment led to a marked inhibition of superoxide dismutase and catalase activities, resulting in heightened oxidative damage and lipid peroxidation. Furthermore, through a protein-protein interaction network analysis using the STRING database, we identified identified CRP and IHF as crucial host regulators responsive to RJ. These regulators were found to play a pivotal role in suppressing essential hub genes associated with energy production and antioxidant capabilities. Our findings significantly contribute to the understanding of RJ's antibacterial mechanism, highlighting its potential as a natural alternative to conventional antibiotics.
Construction of a new prognosis prediction model and immune infiltration analysis of bladder urothelial cancer based on disulfidptosis-related immune genes
Authors: Cen Kenan , Zhou Jingyao , Lv Guangjia , Zhu Hengyue , Guo Yangyang , Zhang Hewei
Published: May 2024

Introduction:
The intricate nature and varied forms of bladder urothelial carcinoma (BLCA) highlight the need for new signals to define tumor prognosis. Disulfidptosis, a novel cell death form, is closely linked to BLCA progression, prognosis, and treatment outcomes. Our current goal is to develop a novel disulfidptosis-related immune prognostic model to enhance BLCA treatment strategies.
Methods
RNA-seq data from TCGA included 419 patients, with clinical details and prognostic data (19 normal, 400 tumor samples). Weighted gene co-expression network analysis (WGCNA) identified disulfidptosis-related immune genes. Univariate, multivariate Cox, and LASSO regression established a disulfidptosis-related immune risk score. A nomogram combining risk score and clinical features predicted prognosis. Model performance was validated through curve analysis and independent prediction. Immune checkpoints, cell infiltration, and tumor mutation load were assessed. Differential gene enrichment analysis was conducted. Prognostic genes were validated via in vitro experiments.
Results
Eight immune genes related to disulfidptosis were identified and verified in BLCA prognosis. A prognostic model outperformed previous ones in predicting overall survival (OS) for high- and low-risk groups. Patients with low risk-scores had higher OS rates and mutation load expression compared to high risk-score patients. CD4 memory T cells, CD8 T cells, M1 macrophages, and resting NK cells were higher in the low-risk group. ICIS treatment may be more effective for the low risk-score group. High risk-score group exhibited stronger correlation with cancer malignant pathways. Knocking out TNFRSF12A inhibits BLAC cell proliferation and invasion, while overexpressing it has the opposite effect.
Conclusions
We constructed a novel risk score model combining disulfidptosis and immune genes with good prognostic prediction performance. We discovered and verified that the TNFRSF12A gene is an oncogene in BLAC, which may help provide personalized guidance for individualized treatment and immunotherapy selection for BLCA patients to a certain extent.
Using Hybrid Mountain Gazelle Optimization and Particle Swarm Optimization Algorithms to Improve Clustering
Authors: Mosavi Esra , Fazeli Seyed Abolfazl Shahzadeh , Abbasi Elham , Kaveh-yazdy Fatemeh
Published: May 2024

Clustering plays a crucial role in data mining and machine learning, with the primary objective being the identification of cohesive and distinct data groups, enabling the extraction of valuable information. However, clustering algorithms often encounter the challenge of getting trapped in local optima, hindering their ability to achieve optimal results. To address this issue, researchers have turned to using meta-heuristic algorithms. This article proposes an enhanced approach for clustering by combining the particle swarm optimization algorithm and the mountain gazelle algorithm. The utilization of this combined algorithm has shown superior performance compared to relying solely on the particle swarm algorithm. By using the strengths of both algorithms, our method overcomes the limitations posed by local optima, leading to more accurate and robust clustering results. The proposed algorithm utilizes the minimum fitness measure to locate the optimal centroid, which is determined based on three constraints: intra-cluster distance, inter-cluster distance, and cluster density. The data is then clustered using the optimal centroid corresponding to the minimal value of the fitness. The performance of our proposed approach has been evaluated on real-world datasets such as Iris, Wine, and Vowel. Our method and PSO and MGO algorithms have been compared on these datasets. The results of the experiments indicate that our proposed method outperforms the PSO and MGO algorithms in terms of clustering quality and convergence speed.
Targeting Metabotropic Glutamate Receptor 7 Promotes Neurogenesis
Authors: Zhao Jian , Wang Ying , Fang Jing , Hu Ganlu , Tang Kailin , Zeng Xianglu , Wang Changzheng , Yu Yong-Chun , Cao Zhiwei , Zeng Tao , Fan Guoping
Published: May 2024

Human neural progenitor cells (hNPCs) have been reported to exist in various regions of the central nervous system (CNS) throughout the lifespan and to maintain homeostasis of the CNS. The endogenous NPC pools as well as their function decline during aging, neurodegeneration, or brain damage; therefore, supplementation with hNPCs or enhancement of the potency of endogenous NPCs could lead to potential treatments for these diseases. Here, we showed that 2-phospho-L-ascorbic acid (Asc-2P) promoted hNPC proliferation and differentiation by maintaining mitochondrial glycolysis under growth factor-lacking conditions. Upregulation of metabotropic glutamate receptor 7 (mGluR7) expression by Asc-2P treatment and retention of mGluR7 on the plasma membrane by the specific group III mGluR antagonist alpha-methylserine-O-phosphate (MSOP) promoted the formation of fibroblast growth factor receptor 1 (FGFR1) and mGluR7 complex on the cytomembrane, thereby enhanced the phosphorylation and activation of cyclic adenosine monophosphate (cAMP) response element-binding protein (CREB), maintained mitochondrial glycolysis, thus enhanced hNPC proliferation and differentiation in vitro and in vivo. Furthermore, Asc-2P treatment alleviated pathogenesis and related cognitive decline in an Alzheimer’s disease mouse model. Taken together, our findings indicated that modulation of mGluR7 by Asc-2P and/or its antagonists could be promising pharmaceutical and therapeutic options against neurodegeneration and related diseases.
The mortar performance research with the addition of silica fume, glass powder, Amazon chestnut, and biopolymer additive
Authors: COSTA Mayara Carelli Paula , BARBOSA Maria Teresa Gomes , SÁ Renato Ribeiro Corrêa , SOUSA Clarissa Dias , SOUZA Nelson Luis Gonçalves Dias , RIVELLI Laura Infante
Published: May 2024

Waste reuse in buildings has proven to be an interesting alternative and more and more research is making it possible to it from many industrial sectors as raw material for making products, reducing the disposal and exploitation of natural resources. Associated with the above, the lime-based mortars in the restoration of historic buildings are since the material provides “breathability” to the substrate, facilitating the exchange of vapors due to its porosity, preventing condensation inside the masonry in addition to the low thermal conductivity, also the ability to accommodate the movements that the building may undergo over time. In this context, the objective of this work is to evaluate the physical, mechanical, chemical properties, and durability of mortars made with binder: sand: biopolymer, in the proportion 1: 3: 0.06 (by weight) where waste was added: silica fume and/or glass powder and/or crushed Amazon chestnuts. To this end, Portland cement or hydrated lime was used as a binder to provide a more in-depth analysis, also allowing the influence of this to be assessed. Mechanical tests (compressive strength and diametral compression strength), durability (immersion absorption, capillarity absorption), and ultrasonic pulse were carried out at 28 days of age. Finally, the benefits of inserting waste in the performance of the mortar were verified, mainly from Amazon chestnuts, which provided significant gains in tensile strength.
Sequencing by Binding rivals error-corrected Sequencing by Synthesis technology for accurate detection and quantification of minor (<0.1%) subpopulation variants
Authors: Allender Christopher J. , Wike Candice , Ellis Dean , Lemmer Darrin , Porter Tanner , Pond Stephanie J.K. , Engelthaler David M.
Published: May 2024

Detecting very minor (< 1%) subpopulations using next-generation sequencing is a critical need for multiple applications including detection of drug resistant pathogens and somatic variant detection in oncology. To enable these applications, wet lab enhancements and bioinformatic error correction methods have been developed for ‘sequencing by synthesis’ technology to reduce its inherent sequencing error rate. A recently available sequencing approach termed ‘sequencing by binding’ claims to have higher base calling accuracy data “out of the box.” This paper evaluates the utility of using ‘sequencing by binding’ for the detection of ultra-rare subpopulations down to 0.001%.
Drug-likeness analysis, in silico admet profiling of selected compounds in Kedrostis fetidissima, and anti-bacterial activity of the plant extract.
Authors: Kommidi Saritha , Alivelu Munagala , Mohammad Mustafa
Published: May 2024

Plants are a treasure trove of bioactive compounds. One such plant is Kedrostis foetidissima, which belongs to the Cucurbitaceae family. It has very important phytoconstituents like cucurbitacins, rutin, quercetin, and other compounds. These compounds are responsible for various biological activities like anti-microbial, anti-diabetic, anti-cancer, anti-oxidant, anti-anemic, and wound healing properties. Quercetin-3-O- Rhamnoside (1), Rutin (2), 7, 10 - Hexa decadienoic acid methyl ester (3), Docosanoic acid (4), 3,7,11,15-Tetra methyl hexa decan-1-ol (5), and Cucurbitacin-B (6) compounds from this plant were tested for in silico ADMET profiling and drug likeness properties using the Swiss ADME online webserver and the pkCSM server. All the studied compounds are obeying Lipinski's rule of five except compounds 1 and 2, with two and three violations each. The entire selected of compounds has a good bioavailability score in the recommended range of 0 to 1. Compound 4 has high (0.85) and compound 1 and 2 have low (0.17) oral bioavailability scores. All the selected compounds from Kedrostis foetidissima have strong pharmacological activities. Supporting this, the selected plant methanol extracts of leaf, stem callus, and tuber have shown good in vitro antibacterial activity against Bacillus subtilis, Escherishia coli, and Proteus vulgaris.
Humidity and Oxygen Effects on Photochromic Properties of MTO/ITO Thin Films
Authors: Inoue Shuhei , Matsuo Ippei , Matsumura Yukihiko
Published: May 2024

The study investigates the photochromic properties of magnesium tin oxide (MTO) films deposited on indium tin oxide (ITO) substrates under various environmental conditions. The photochromic behavior involves the transition of the material to a black state upon ultraviolet (UV) irradiation and its return to transparency upon heating. MTO films deposited on ITO substrates exhibited significant coloration upon UV exposure, with a notable decrease in visible light transmittance. Structural analysis revealed the formation of metallic indium at the MTO/ITO interface during UV irradiation, suggesting a complex reaction mechanism involving oxygen and hydrogen radicals. Investigations into the effects of atmospheric gases and humidity on UV-induced coloration indicated that moisture plays a crucial role in promoting photochromism, while the presence of oxygen influences the degree of coloration. The study provides insights into the underlying processes driving the photochromic phenomenon in MTO/ITO systems and underscores the importance of environmental factors in modulating their optical properties. Further research is warranted to fully elucidate the role of oxygen and its derivatives in the photochromic mechanism of MTO films for potential applications in energy storage devices.
Analysis and circuit implementation of fractional-order memristive hyperchaotic system with enhanced memory
Authors: Ding Zhixia , Qiu Le , Li Sai , Yang Le , Wang Liheng
Published: May 2024

In this paper, based on the memory characteristics of fractional calculus, a new fractional-order memristor is proposed, which not only retain the basic characteristics of memristor, but also expand the influence of control parameters on system performance. Which has a stronger memorizability compared to other fractional-order memristor by analyzing the pinched hysteresis loop area. Based on the above fractional-order memristor, a fractional-order memristive hyperchaotic circuit is designed, such system is analyzed by using the Lyapunov Exponents and the bifurcation diagrams. It is found that the phase trajectory of the system expands and narrows under different parameters. In addition, there are two coexisting hyperchaotic attractors at different initial values. The SE complexity and C0 complexity of the system parameters are also given by the complexity algorithm. Finally, the fractional-order memristor and fractional-order memristive hyperchaotic circuits are realized through analog circuits.
Diagnostic value of magnification optical enhancement by experts and ResNet for detecting diminutive colorectal polyps: A retrospective study
Authors: Wan Xiaohan , Zhang Yan , Yang Huawei , Li Yanqing
Published: May 2024

Background
Deep learning models, such as narrow band imaging, are useful for identifying colorectal polyp pathological types using electronic chromoendoscopy. However, such findings remain unreported for i-scan optical enhancement (OE). Thus, this study proposes a ResNet-based model to distinguish between colorectal polyp types.
Methods
Endoscopic videos of 58 patients with colorectal polyps were collected, and their pathological types were determined by pathological examination. An experienced endoscopist was asked to predict the polyp pathological types shown in the videos to evaluate the diagnostic accuracy of the endoscopists. The same videos were extracted as images to train the ResNet model and evaluate its effectiveness. Finally, 100 endoscopic images were randomly selected for human–machine comparisons to examine the consistency between machine learning and endoscopist diagnoses.
Results
An accuracy of 89.77% was obtained by experienced endoscopists in distinguishing colorectal polyp types based on the entire video; the accuracy of the ResNet model based on video-extracted images was approximately 95%. Therefore, the ability of the ResNet model to classify colorectal polyps matched that of an experienced endoscopist.
Conclusions
I-scan OE provides a powerful tool for experienced endoscopists to differentiate between colorectal polyp pathological types; the ResNet model can help endoscopists achieve high diagnostic accuracy and reduce unnecessary invasive examinations.
Image Filtering to Increase the Efficiency in the Construction of Underwater Photomosaics
Authors: Castelló Pol Baños , Bonin-Font Francisco , Codina Gabriel Oliver
Published: May 2024

This paper describes an innovative methodology designed to filter out images with redundant information, initially selected to form photo-mosaics of the seabed. Collecting visual data of the sea bottom using underwater robots usually entails hundreds or even thousands of images if missions are performed in large areas and/or have long durations. All these images usually present multiple overlapping parts that need to be filtered out wisely in order to avoid useless repetitive information, questionable pixel aggregations, unreal colour blends, or the collapse of the computational resources dedicated to the mosaic building process. Experiments have been done with datasets grabbed from an Autonomous Underwater Vehicle while observing marine habitats of special ecological interest. Results show important reductions of visual data destined to the mosaics without significant loss of relevant information to be included in them, saving, drastically, time and data processing efforts.
Interplay of Aurora kinase A functional residues and Epstein-Barr Nuclear Antigen 1 in Epstein-Barr Virus associated Gastric cancer
Authors: Varshney Nidhi , Singh Siddharth , Kandpal Meenakshi , Saini Vaishali , Roberston Erle S. , Jha Hem Chandra
Published: May 2024

Background
Epstein-Barr virus (EBV), an oncogenic gamma-herpesvirus, belongs to group 1 carcinogen and is implicated in various cancers, including gastric cancer. Aurora Kinase A is a major mitotic protein kinase that regulates mitotic progression; overexpression and hyperactivation of AURKA commonly promote genomic instability in many tumours. However, the relationship of functional residues of AURKA and EBV in gastric cancer progression remains unknown.
Results
We reveal that AURKA overexpression and EBV infection induce aneuploidy in gastric epithelial cells. The AURKA (S89) N-terminal residue is critical for the centrosome maturation process in EBV-infected gastric epithelial cells. The kinase domain residues T287 and T288 of AURKA are essential for centrosome maturation and bipolar spindle formation in EBV-infected gastric cancer cells. We also show that AURKA 287/288 dm reduces the transcript expression of cell cycle markers involved in mitotic entry in EBV infection. This mutant also enhanced the protein expression of p53 and Rb, which was reduced in EBV infection and decreased the Survivin expression. Further, EBNA1, the latent gene of EBV, stabilises the AURKA in its wild-type form when it was mutated at the 89th position but unable to stabilise it when mutated at 287/288 position. These mutants also induce mitotic catastrophe by regulating the apoptosis and autophagy pathway in EBV infection. AURKA287/288 dm also promotes autophagosome formation even in EBV infection.
Conclusion
Thus, this study demonstrates that the AURKA kinase domain is essential for its functioning and progression of oncogenesis of EBV-infected gastric epithelial cells.
ML-Based Adaptive MAC Protocol for Real Time Data Transmission in Wireless Sensor Networks
Authors: Kakade Archana R Raut Archana
Published: May 2024

Wireless Sensor Networks (WSNs) are expressively utilized in various real-time control and monitoring applications. WSNs have been expanded considering the necessities in industrial time-bounded applications to support the dependable, time-bound delivery of data. Recently, Machine Learning (ML) algorithms have been used to address various WSN-related issues. The use of machine learning techniques supports dynamically modifying MAC settings based on traffic patterns and network conditions. In WSNs to control the communication between a large number of tiny, low-power sensor nodes while preserving energy and reducing latency, effective MAC protocols are essential. This paper addresses the ML-based Adaptive MAC (ML-MAC) protocol to provide a priority-based transmission system. In this research, depending upon the predictions of the machine learning model, the MAC parameters are dynamically adjusted to find priority-based channel access and the optimal routing path to meet the deadline of critical data packets. From the result analysis, the average throughput and delay of the proposed ML-MAC algorithm is improved as compared to the existing I-MAC protocol.
© 2017 Elsevier Inc. All rights reserved.
Pocket Convolution Mamba for Brain Tumor Segmentation
Authors: Zhang Hao , Zhao Yunhao , Wang Lianjie , Wang Jiashu , Zhang Wenyin , Chen Yeh-Cheng , Xiong Neal
Published: May 2024

In the field of brain tumor segmentation, models based on CNNs and Transformer have received a lot of attention. However, CNNs have limitations in long-range modeling, and although Transformers can model at long distances, they have quadratic computational complexity. Recently, State Space Models (SSM), exemplified by the Mamba model, can achieve linear computational complexity and are adept at long-distance interactions. In this paper, we propose Pocket Convolution Mamba (P-BTS), which utilizes the PocketNet paradigm, SSM, and patch contrastive learning to achieve an efficient segmentation model. Specifically, the encoder follows the PocketNet paradigm, the SSM is used at the highest level of the model encoder to capture rich semantic information, and patch contrastive learning is achieved through the results of dual-stream data. Meanwhile, we designed a Spatial Channel Attention (SCA) module to enhance control over spatial channels, and a Feature Complement Module (FCM) to facilitate the interaction between low-level features and high-level semantic information. We conducted comprehensive experiments on the BraTS2018 and BraTS2019 datasets, and the results show that P-BTS has excellent segmentation performance.
Predictive Analysis of Geomagnetic Disturbance Using Satellite Solar Wind Measurements
Authors: Salloum Said A.
Published: May 2024

Geomagnetic storms pose a significant risk to our increasingly technology-dependent society, with the potential to disrupt power grids, satellite operations, and global communication systems. These disturbances are primarily driven by solar wind, a stream of charged particles emitted by the Sun, which interacts with the Earth's magnetosphere. The dynamic nature of solar activity, notably characterized by the solar cycle's periodicity of approximately 11 years, further complicates the prediction and understanding of such events. A critical challenge in space weather forecasting is the development of reliable models that can accurately predict geomagnetic disturbances in a timely manner. Traditional modeling approaches often struggle to capture the complex temporal dependencies and the multivariate nature of solar wind data. To address this challenge, we developed a Long Short-Term Memory (LSTM) neural network model designed to harness the sequential nature of solar wind measurements. This study leverages LSTM's capability to retain long-term temporal relationships, utilizing a dataset composed of various solar wind parameters collected from NASA's ACE and NOAA's DSCOVR satellites. The model was trained to predict the disturbance storm time (Dst) index, a measure of geomagnetic activity, using a feature set that included interplanetary magnetic field components, solar wind proton density, speed, and ion temperature. The LSTM model demonstrated a substantial learning capacity, evidenced by a Root Mean Squared Error (RMSE) of 14.25, indicating strong predictive performance. In a binary classification setup, the model achieved an accuracy of approximately 80.35% with an Area Under the Curve (AUC) score of 0.818, signifying its effective discrimination between high and low geomagnetic disturbance events. These results underscore the potential of utilizing LSTM models for space weather forecasting, which could significantly enhance our ability to mitigate the risks associated with geomagnetic storms. The incorporation of sunspot data could allow for calibration to the solar cycle, further refining model predictions. This study lays the groundwork for future research aimed at integrating more diverse data sources and applying advanced machine learning techniques to improve the accuracy and reliability of geomagnetic disturbance forecasts.
CSFN-YOLOv5s: A Rapid Apple Detection Algorithm in the Natural Environment
Authors: Hui Yongyong , Zhao Chunyu , Song Zhaoyang , Zhao Xiaoqiang
Published: May 2024

In the natural environment, the rapid detection of apples is of great importance for picking robots. However, the complex growth conditions of apples, the occlusion of leaves and branches, and the distance can cause the problem of missed apple detection. To address this problem, an algorithm called CSFN-YOLOv5s for accurate and efficient apple detection in complex natural environments was developed. Firstly, the Context Augmentation Module - Spatial Pyramid Pooling with Feature Concatenation and Spatial Channel wise Pooling （CAM-SPPFCSPC ）framework is constructed to introduce additional background and context information, enhance the use of context information of the model, and help the model better understand the image information, so as to improve the robustness and generalization ability of the model. Secondly, with the application of four detection layers to obtain finer granular feature expression and a smaller receptive field, improve the accuracy of small target detection by finely capturing its detailed information. Thirdly, the Normalized Wasserstein Distance (NWD) was used to improve the sensitivity of IoU to the position deviation of small objects. Finally, a large number of experimental results show that CSFN-YOLOv5s has certain advantages for rapid identification of apples in natural and complex environments.
Enhancing Solar-to-Chemical Conversion through Tailoring Dimensions of Semiconductors in Biohybrid Systems
Authors: Guo* Mingming , Kong* Xinke , Cheng Wenbo , Yang Wenjun , Pi Shanshan , Wang Xin , Wang Xueyun , Xiang Yang , Duan Fangfang , Yang Chen , Wang Yuanyuan , Gao Xiang
Published: May 2024

Integrating light-harvesting semiconductor materials with biocatalysts offers a promising approach for solar-power production of fuels and fine chemicals. Despite significant advances, the influence of materials’ dimensions on energy utilization efficiency and the involved photoelectron transfer pathways remains largely to be explored. Here, we investigated the effect of dimensionality on the energy conversion efficiency in semiconductor nanomaterial-based biohybrid systems. We found that the intracellularly localized 2D nanoplatelets, particularly with core-crown heterostructures, were more efficient in supplying energy for microbial chemical production than the lower-dimensional nanomaterials. The biohybrids possessing the 2D nanoplatelets exhibited a 2.69-fold increase in 2,3-butanediol (BDO) production yield and achieved 2.35% solar-to-chemical conversion efficiency. Based on metabolomic and transcriptomic analyses, we identified a novel thiamine pyrophosphate (TPP)-mediated pathway of energy generation from photoexcited electrons. Furthermore, the addition of TPP enhanced the BDO production of the biohybrids under illumination. Our results demonstrate the potential to increase the solar-to-chemical conversion efficiency of semiconductor biohybrids by tailoring the dimension of semiconductor nanomaterials and engineering the intracellular electron transfer and energy generation pathways.

*Mingming Guo and Xinke Kong contributed equally to this work.
Nexus between Fair Pay and Say on Pay Votes
Authors: Arslan Muhammad
Published: May 2024

This study explores the magnitude of shareholders' say on pay votes and its impact on future CEO compensation. This study draws its sample from US Russell 3000 companies, consisting largest US companies, from 2011 to 2019. By creating a dummy variable, we further divided our sample into Russell 3000 and S&P 500 for peer comparison. The study employs descriptive statistics, correlation analysis, and pooled OLS regression and finds that future CEO compensation is significantly negatively associated with pay gap opposition. The coefficient and t-stat were higher for S&P 500 than for the Russell group. The study also finds that the CEO-to-Employee pay ratio positively correlates with shareholder dissent votes. The coefficient and t-stat were higher for the Russell group than for the S&P 500. Each additional point of CTE increases the shareholder dissent votes increases by 1.4% for the Russell 3,000 companies. The study has important implications for corporate directors, investors, and policymakers. The study contributes to corporate governance literature, particularly on executive compensation. Our findings supported the view of social comparison theory and contented that shareholders view CEO compensation as a biased evaluation of his contribution to the firm. We have developed a unique measure of the CEO-to-Employee pay ratio, which is based on SEC methodology. Our findings provide empirical evidence to investors and policymakers in the United States and other jurisdictions.
Healthcare Workers' Attitude Towards People Living With HIV
Authors: Saricicek Mehmet Sinan , Tuncer Ozge , Saricicek Ali Taylan
Published: May 2024

Background: HIV-related stigmatization among healthcare workers is still high. The aim of that research was to determine attitudes and behaviors towards people living with HIV (PLWH) to determine the ratio of stigmatization and prejudice towards PLWH among healthcare workers.
Methods: This was a single-center, national, cross-sectional, prospective, analytical survey study. Doctors and nurses at Izmir Bozyaka Training and Research Hospital were included in this study. The study was performed as a face-to-face and online survey. The sociodemographic data form and AIDS Attitude Scale (AAS) were administered to the participants. The results were analysed with the IBM SPSS 24.0 program. The significance level was accepted as p<0.05.
Results: A total of 404 people were included in our study.A total of 301 (74, 5%) of the participants were female, and 13 (25, 5%) were male. The average age of the participants was 33.25 ± 8.22 years. Most of the participants were aged 24-30 years (55, 9%), and the attitudes of healthcare workers towards PLWH increased with age. Compared with assistant doctors and nurses, specialist doctors have more positive and empathetic attitudes and less avoidance.
Conclusion: Participant attitudes towards PLWH are generally mild-high positive, but negative attitudes towards PLWH are common among healthcare workers. Regular education is needed for nurses and assistant doctors to increase confidence in HIV and reduce negative attitudes towards PLWH. However, additional quantitative studies are needed to identify interventionable points to increase empathy toward PLWH.
RETRACTED: Mathematics in Early Childhood From the Perspectives of Children And Teachers
Authors: KARAKUŞ Hilal , AKMAN Berrin
Published: May 2024

The authors have requested that this preprint be removed from Research Square.
From the XXZ chain to the integrable Rydberg-blockade ladder via non-invertible duality defects
Authors: Eck Luisa , Fendley Paul
Published: May 2024

Strongly interacting models often possess “dualities” subtler than a one-to-one mapping of energy levels. The maps can be non-invertible, as apparent in the canonical example of Kramers and Wannier. We analyse an algebraic structure common to the XXZ spin chain and three other models: Rydberg-blockade bosons with one particle per square of a ladder, a three-state antiferromagnet, and two Ising chains coupled in a zigzag fashion. The structure yields non-invertible maps between the four models while also guaranteeing all are integrable. We construct these maps explicitly utilising topological defects coming from fusion categories and the lattice version of the orbifold construction, and use them to give explicit conformal-field-theory partition functions describing their critical regions. The Rydberg and Ising ladders also possess interesting non-invertible symmetries, with the spontaneous breaking of one in the former resulting in an unusual ground-state degeneracy.
Topological aspects of brane fields: Solitons and higher-form symmetries
Authors: Pace Salvatore D. , Liu Yu Leon
Published: May 2024

In this note, we classify topological solitons of nn-brane fields, which are nonlocal fields that describe nn-dimensional extended objects. We consider a class of nn-brane fields that formally define a homomorphism from the nn-fold loop space \Omega^n X_DΩnXD of spacetime X_DXD to a space \mathcal{E}_nℰn. Examples of such nn-brane fields are Wilson operators in nn-form gauge theories. The solitons are singularities of the nn-brane field, and we classify them using the homotopy theory of {\mathbb{E}_n}𝔼n-algebras. We find that the classification of codimension {k+1}k+1 topological solitons with {k≥ n}k≥n can be understood using homotopy groups of \mathcal{E}_nℰn. In particular, they are classified by {\pi_{k-n}(\mathcal{E}_n)}πk−n(ℰn) when {n>1}n>1 and by {\pi_{k-n}(\mathcal{E}_n)}πk−n(ℰn) modulo a {\pi_{1-n}(\mathcal{E}_n)}π1−n(ℰn) action when {n=0}n=0 or {1}1. However, for {n>2}n>2, their classification goes beyond the homotopy groups of \mathcal{E}_nℰn when {k< n}k<n, which we explore through examples. We compare this classification to nn-form \mathcal{E}_nℰn gauge theory. We then apply this classification and consider an {n}n-form symmetry described by the abelian group {G^{(n)}}G(n) that is spontaneously broken to {H^{(n)}\subset G^{(n)}}H(n)⊂G(n), for which the order parameter characterizing this symmetry breaking pattern is an {n}n-brane field with target space {\mathcal{E}_n = G^{(n)}/H^{(n)}}ℰn=G(n)/H(n). We discuss this classification in the context of many examples, both with and without ’t Hooft anomalies.
Factors and mechanisms influencing seasonal disorders in pig reproduction
Authors: WOJTCZAK JANUSZ , POROWSKI MATEUSZ , PIETSCH-FULBISZEWSKA AGNIESZKA , PEJSAK ZYGMUNT
Published: May 2024

The problem of unsatisfactory reproductive results in pigs is visible in a significant percentage of herds, especially during summer months and early autumn (seasonal summer infertility). This is reflected mainly in the reduced percentage of sows entering estrus after weaning and the effectiveness of mating/insemination. The consequence is a significantly lower number of births in November, December and sometimes even in January, compared to other seasons. There are many causes of seasonal summer infertility. The first things mentioned are usually the length of the light day and the high temperature in the pigs environment. An important reason that is not often discussed is the daily temperature fluctuations which usually occur at the end of summer and the beginning of autumn. Persistent unfavorable conditions are responsible for long-term stress. Hormonal disorders related to stress, leading to reproductive disorders, result from connections taking place in the hypothalamus between the hypothalamus-pituitary-gonadal axis (HPG), which regulates, among others, the reproductive functions of the ovaries, and the hypothalamus – pituitary – adrenal axis – HPA which governs organism reaction to stress. Under stressful conditions, glucocorticoids (cortisol, corticosterone) secreted in large amounts by the adrenal glands, as well as adrenaline, norepinephrine and, in small amounts, dopamine, may inhibit reproductive functions at the level of the hypothalamus, reducing the secretion of GnRH. At the same time, by reaching the pituitary gland, these hormones limit the sensitivity of the cells of this endocrine gland to GnRH. As a consequence, the maturation of follicles slows down, the number of ovulating and rupturing follicles decreases, and the secretion of estrogen is reduced. The consequence is the absence of heat or, more often, the so-called “silent heat”. Another problem is the uneven maturation of the follicles, which leads to a delayed appearance of estrus and its longer duration: 3-4 days. The final effect of these is a decrease in the rate of females presenting heat after weaning of piglets, a deterioration in the mating/insemination success rate, an increase in the rate of early abortions and percentage of litters with a small number of piglets in a litter. The summary stated that despite the identification of various seasonal causes of reproductive disorders in pigs, depending on both sows and boars, and the availability of various “tools” to reduce phenomenon of seasonal infertility, the presented problem has not been solved in a large percentage of swine farms. Its intensity varies and depends primarily on awareness, knowledge of ways to eliminate unfavorable conditions and determination in this regard. The first step, as always, is to objectively assess the situation. The assessment can be made through a detailed analysis of production data.
Effect of Bakofix® Treatment Prior to Estrus Synchronization on Some Fertility Parameters in Anatolian Merino Ewes During the Non-Breeding Season
Authors: KURU BUKET BOĞA , ÖLMEZ VELI , KURU MUSHAP
Published: May 2024

This study investigated the effect of Bakofix® (a supplement consisting of vitamin E, copper, zinc, manganese, cobalt, selenium, and calcium) on the reproductive performance of Anatolian Merino sheep. A total of 80 clinically healthy sheep were used in the study. They were synchronized with a progesterone-containing sponge outside the breeding season and divided into three groups. The first group (G1, n = 25) was administered Bakofix® treatment 7 days before estrus synchronization, the second group (G2, n = 25) was administered Bakofix® treatment when estrus synchronization began, and the third group served as the control (G3, n = 30). G1 showed a higher estrus response, conception rate, and pregnancy rate compared to the other groups. Particularly remarkable was the 84% pregnancy rate obtained in G1. The fecundity and litter size in G1 were 2.4 and 2.8, respectively, which were higher than those in the other groups. The multiple birth rate in G1 was significantly higher than that in G3, and Bakofix® treatment seven days before synchronization had a positive effect on the multiple birth rate, with a statistically significant difference between the two groups (P < 0.05). Although the multiple birth rate was high in G1, the birth weights of the lambs were not negatively affected. In conclusion, vitamin, mineral, and trace element supplementation can be applied to increase the reproductive performance of Anatolian Merino ewes, especially outside the breeding season and before estrus synchronization, which can lead to increased economic gain.