bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Cu2+/Ce3+ substituted on synthesis, structural, morphological, magnetic, DC electrical resistivity and dielectric properties of Cobalt nano ferrites
Authors: Suryanarayana B. , Nagasree K. L. V. , Shanmukhi P. S. V. , Kiran M. Gnana , Murali N. , Mammo Tulu Wegayehu , Parajuli D. , Batoo Khalid Mujasam , Hussain Sajjad , Samatha K. 
Published: September 2023

Abstract
The sol-gel auto-combustion method was used to synthesize the nano ferrite compounds Co1 − xCuxFe2−yCeyO4 (x = 0.0, 0.25, 0.5, and 0.75; y = 0.0, 0.03, 0.06, and 0.09). Synthesized nano ferrites with appropriate characteristics sintered at 1150°C for 2h in the transition metals (Cu2+) and rare earth (Ce3+) were used to customise the spinel ferrites' properties. FTIR, FESEM, XRD, VSM, DC electrical resistivity, and dielectric properties examined the spinel nano ferrites' vibrational bands, phase, morphology, structure, and magnetic and electrical characteristics. XRD data was used to analyze the average crystallite size, x-ray density and lattice constant, confirming the formation of the cubic spinel structure of the prepared samples. The grain size values in the FESEM pictures range from 41.07 to 156 nm. An increase in lattice parameter suggests the occupancy of substituted Cu2+/Ce3+ ions in the tetrahedral site, further supported by the FTIR spectra between 415 cm− 1 to 430 cm− 1. It has been measured magnetic properties, such as the magnetic moment, anisotropy constant, saturation magnetization, coercivity, and remanence ratio, were examined. With increasing concentrations of Cu2+/Ce3+ ions, the saturation magnetization (Ms), coercivity (Hc), and remanence (Mr) exhibit a strikingly declining trend. The activation energy varies from 0.52 eV to 0.62 eV, and the increased DC resistivity with increasing Cu2+/Ce3+ content shows their semiconducting nature. Koop's theory describes the dielectric properties, including the dielectric constant, tangent loss, and AC impedance, which are calculated as functions of the frequency of the applied field. All of these factors are seen to decline as frequency increases and become frequency-independent above 1 MHz. Due to their dielectric characteristics, synthetic spinel ferrites are potential candidates for use in the high-frequency region.
Centrosymmetric Constrained Convolutional Neural Networks
Authors: Zheng Keyin , Qian Yuhua , Yuan Zhian , Peng Furong 
Published: September 2023

Abstract
Complex signals can be viewed as compositions of numerous sine waves with different frequencies and amplitudes. As the fundamental unit of perceiving image features, traditional convolutional neural networks (CNNs) typically employ convolutional kernels without direct constraints. However, human perception of the world is inherently structured, relevant studies have indicated that considering the potential underlying correlation structures among data features or variables holds significant value, with particular emphasis on symmetric transformations in representation learning gaining attention in the field of neuroscience. Inspired by the process of human visual concept perception and classic image feature detection operators, when the convolution kernels have a similar scale to the objects, they produce larger responses. This paper introduces constraints on model parameters using centrosymmetric convolutional kernels. Under the influence of nonlinear combinations and local connections in neural networks, these kernels can diversely represent or perceive local image features. Experimental comparisons are conducted, and it is observed that the approach proposed in this paper not only enhances the convergence and accuracy of model, but also reduces the model solution space, resulting in an interpretable perception of local concepts. Furthermore, comparative experiments with classic deep CNNs have demonstrated comparable performance.
Construct Validity of the Japanese Version of the Reynolds Empathy Scale for Patients to Assess Nurses’ Empathy: A Cross-sectional Research Study
Authors: Aoki Yoshimi , Himichi Toshiyuki , Katayama Harumi 
Published: September 2023

Abstract

Background
Empathy education for the nursing profession is needed. The evaluation of empathy education requires not only self-evaluation but also evaluation by patients and third parties. The Reynolds Empathy Scale is a 12-item scale that was developed to allow not only self-assessment of empathy by healthcare professionals but also patient and peer assessment. The purpose of this study was to verify the construct validity of the Japanese version of the Reynolds Empathy Scale for patient assessment. The scale was translated into Japanese by the principal investigators to make it easier to understand.
Methods
This study used a cross-sectional design. Patients eligible for nursing care. Individuals registered with a research company and who have been hospitalized. To test content validity, a preliminary expert meeting was held. For hypothesis testing, three patterns of cartoons with different empathy behaviors and attitudes were used. The three cartoons were the high empathy nurse, the low empathy nurse, and the self-centered nurse. The target population consisted of those who had been hospitalized and were registered with a research company, taking into account the age of Japanese patients in general. The analyses were item analysis, exploratory factor analysis, confirmatory factor analysis, and the t test. SPSS and R were used for analysis. Hypothesis testing using cartoons resulted in higher scores for the high empathy nurse than for the low empathy nurse and self-centered nurse. Data were collected on the subject’s age, gender, and three cartoons related to nurses’ behaviors and attitudes as assessed using the Reynolds Empathy Scale.
Results
Data from 1004 participants were used in the analysis. Factor analysis resulted in a one-factor model with a reverse item factor structure. The hypothesis was supported.
Conclusions
The Reynolds Empathy Scale is a one-factor construct, and the measurements were hypothesis-directed. Construct validity was generally confirmed statistically.
Trial registration:
This study was conducted in compliance with the Declaration of Helsinki, the Ethical Guidelines for Life Sciences and Medical Research Involving Human Subjects, and other relevant regulations and was approved by the Ethics Committee for Life Science and Medical Research at Hamamatsu University School of Medicine (No. 22–050).
Fractional Differentiation Based Image Enhancement for Automatic Detection of Malignant Melanoma
Authors: Anber Basmah , Yurtkan Kamil 
Published: September 2023

Abstract
Recent improvements in artificial intelligence and computer vision make it possible to automatically detect some of the abnormalities in medical images. Skin lesion is one of them and the treatments are greatly aided by the quick and precise diagnosis of these conditions. The identification and delineation of boundaries inside skin lesions has showed promise when using the basic image processing approach of edge detection, to be used in automatic detection. We investigate the use of fractional differentiation in this work to improve edge-detection in order to enhance the images. We propose a framework based on fractional differential filters for edge detection in skin lesion images. The derived images are then used to enhance the original images. Obtained images then undergo a classification process based on deep learning models. A well-studied dataset of HAM10000 is used in the experiments. The results show that these filters are effective in avoiding noise and detecting intricate edge details that can be informative during the recognition processes.
Application of response surface methodology in optimizing simultaneous extraction of multiple mycotoxins in maize via QuEChERS
Authors: Mbisana Mesha , Mogopodi Dikabo , Tshepho Rebagamang , Chibua Inonge , Nkoane Bonang 
Published: September 2023

Abstract
Several methods have been developed for the analysis and detection of mycotoxins in food; however, they do not make use of critical statistics and mathematical tools for precise optimization. The goal of this study was to use a central composite design (CCD) to find the true optimum values for acetonitrile percentage MeCN (%), formic acid percentage FA (%), extraction time, and salt addition in the QuEChERS-LC-MS/MS method for extracting certain mycotoxins. Data analysis of full factorial screening experiments revealed that MeCN (%), FA (%), and extraction time significantly affected the analyte recovery. Analysis of variance, coefficient tables, and surface plots from CCD showed the relative interactions of factors and the statistical significance of the model. The P values from the lack of fit test ranged from 0.137 to 0.467, which indicated an insignificant lack of fit. A composite desirability function of 0.91 was found for the method, and the optimum conditions were found to be 0.1% (v/v) FA in 80.2% MeCN for 74 minutes. To demonstrate applicability, method validation was carried out according to Commission Implementing Regulation 2021/808. Recoveries ranging from 85.45–113.70% and CVs below 15% were obtained. All R2 values were above 0.98, and LOQs ranging from 0.33 to 60.45 µg/Kg were recorded. This method was tested on twenty maize samples collected from markets in Botswana. Thirteen samples had detectable mycotoxins, and two had levels of AFB1 above the maximum permitted level by the European Union (EU). This indicates the possibility of exposure for Botswana to high levels of AFB1, the most toxic of mycotoxins.
Machine learning-based integration identifies ferroptosis hub genes in nonalcoholic steatohepatitis
Authors: Dai Longfei , Yuan Wenkang , Jiang Renao , Zhan Zhicheng , Zhang Liangliang , Xu Xinjian , Qian Yuyang , Yang Wenqi , Zhang Zhen 
Published: September 2023

Abstract
Background
Ferroptosis, an iron-dependent mode of cellular demise, precipitates the accumulation of lipid peroxides and perturbation of vital metabolic routes, culminating in hepatic impairment. However, the pivotal genes governing the contribution of ferroptosis to the pathogenesis of nonalcoholic steatohepatitis (NASH) remain elusive, necessitating a thorough and profound investigation.
Methods
Employing sophisticated machine learning techniques, pivotal ferroptosis hub genes were meticulously identified, culminating in the formulation of a comprehensive ferroptosis-related score (FeRS) model. Sequentially, correlation analyses were harnessed to unravel intricate associations linking the ferroptosis hub genes with immune function scores, as well as distinct immune cell subpopulations.
Results
An FeRS model, encompassing a set of eight central ferroptosis hub genes, was meticulously fashioned, exhibiting profound diagnostic efficacy within the training dataset and across seven independent testing datasets. Among these genes, ZFP36 emerged as a key hub within the FeRS. Moreover, ZFP36 and IL6 revealed substantial positive correlations with immune function scores and various subsets of immune cells. In contrast, GRIA3 and FADS2 exhibit the opposite pattern.
Conclusions
The pivotal role of the ferroptosis-related gene ZFP36 in the context of NASH comes to the fore, as its diminished expression serves to propel the trajectory of restrain the infiltration of immune components within the NASH milieu.
Mathematical Model For Determining The Influence Of Treatment And Vaccination On Measles
Authors: Adedayo Olufemi Adesola , Otaru Martins . O , Adekunle Temitope Samson , Ugwu Clement U , Akande Skirulai Abolaji , Muhammed Ismaili , Job Oloruntoba Samuel , Musa Innocent .O , Tiamyu Abd'gafar Tunde 
Published: September 2023

Abstract

In this paper work, a mathematical modeling of the influence of treatment and vaccination on measles control was developed using a system of ordinary differential equations. Local stability analysis on the disease-free equilibrium was done using the Jacobian matrix approach. The semi-analytical solutions of the model were obtained using the Differential Transformation method and the solutions were plotted using Maple. The result of the findings shows that the Disease Free Equilibrium State (DFE) of the model is stable if R0˂1. The result of the numerical simulation shows that a reduction in the contact rate with infectious individuals reduces the transmission rate of the disease. The simulation also reveals that at high vaccination rate for the infected individuals, the number of recovered individual’s increases. Hence, the combination of treatment and sanitizer at 75% will curb measles to the barest minimum in less than one year, also effective vaccination will help in preventing those who are susceptible from contacting the disease.

Keyword: Mathematical model, Measles, Simulation, Treatment and vaccination.
Feather keratin-functionalized nanomesoporous silica enhances the control effect of indoxacarb on Solenopsis invicta
Authors: Huang Su-qing , Xie Xiao-feng , Ding Jiao , Huang Nanhe 
Published: September 2023

Abstract
Herein, a pesticide-controlled release system (IDC-loaded FK-HMS) with pH and reduced glutathione (GSH) response characteristics was designed and prepared, in which the carboxyl group of feather keratin (FK) was coupled with aminated hollow mesoporous silica (HMS), and indoxacarb (IDC) was loaded into HMS. The composite system was characterized by scanning electron microscopy, Fourier transform spectroscopy, X-ray diffraction, and high-performance liquid chromatography. FK-HMS showed a high loading ratio (23.22%, w/w) on IDC while exhibiting dual sensitivity to pH value and reduction response. Compared with the same dose of the original IDC drug, IDC-loaded FK-HMS showed better killing activity against invasive species of Solenopsis invicta, which was because nanoscale FK-HMS was easily absorbed by Solenopsis invicta and entered midgut cells, reducing the effect of detoxification enzymes. Furthermore, low-dose IDC@FK-HMS effectively inhibited the actions of Solenopsis invicta, indicating that the insecticide-controlled release system based on FK-modified HMS nanoparticles is capable of sustained and long-term control of Solenopsis invicta.
Immune profiling of age and adjuvant-specific activation of human blood mononuclear cells in vitro
Authors: Dowling David , Schüller Simone , Barman Soumik , Mendez-Giraldez Raul , Soni Dheeraj , Daley John , Baden Lindsey (R) , Levy Ofer 
Published: September 2023

Abstract

Vaccination reduces morbidity and mortality due to infections, but efficacy may be limited due to distinct immunogenicity at the extremes of age. This raises the possibility of employing adjuvants to enhance immunogenicity and protection. Early IFNγ production is a hallmark of effective vaccine immunogenicity in adults serving as a biomarker that may predict effective adjuvanticity. We utilized mass cytometry (CyTOF) to dissect the source of adjuvant-induced cytokine production in human blood mononuclear cells (BMCs) from newborns (~39-week-gestation), adults (~18-63 years old) and elders (>65 years of age) after stimulation with pattern recognition receptors agonist (PRRa) adjuvants. Dimensionality reduction analysis of CyTOF data mapped the BMC compartment, elucidated age-specific immune responses and profiled PRR-mediated activation of monocytes and DCs upon adjuvant stimulation. Furthermore, we demonstrated PRRa adjuvants mediated innate IFNγ induction and mapped NK cells as the key source of TLR7/8 agonist (TLR7/8a) specific innate IFNγ responses. Hierarchical clustering analysis revealed age and TLR7/8a-specific accumulation of innate IFNγ producing γδ T cells. Our study demonstrates the application of mass cytometry and cutting-edge computational approaches to characterize immune responses across immunologically distinct age groups and may inform identification of the bespoke adjuvantation systems tailored to enhance immunity in distinct vulnerable populations.
PUF-Sec: A Secure and Efficient Mutual Authentication Protocol for Multi-UAV Networks in Disaster Monitoring Applications
Authors: Chandran Indu , Vipin  
Published: September 2023

Abstract
Drones or Unmanned aerial vehicles have had a profound effect on how we perceive and interact with the world. These remotely piloted or autonomous aircraft have surpassed their military origins and found diverse applications in fields such as agriculture, infrastructure inspection, disaster management, delivery services, and recreational activities. Their ability to swiftly navigate the skies, capture high resolution aerial images, and execute precise tasks has made them indispensable tools in time critical applications like disaster monitoring and search-and-rescue missions. However, their increased usage has raised concerns regarding security issues including unauthorized access, data breaches, cyber-attacks, and physical threats. The UAV network being highly dynamic, the adversaries may exploit drone failures to intrude into the network and pose serious data breaches. It is, therefore, essential to employ robust security measures, such as authentication, encryption, physical security measures, and proactive monitoring, to mitigate the risks associated with drone operations. However, limited resource constraints can make it challenging to implement heavy encryption and cryptographic algorithms on drones. In this paper, we have proposed a lightweight mutual authentication and key agreement protocol for disaster management applications, incorporating physically unclonable technology to secure communication. Additionally, the protocol is enhanced to manage security risks during UAV failures. The protocol has been validated using the Scyther simulation tool, and an informal security analysis has been presented to verify that all security requirements have been met. Additionally, the performance of the protocol has been compared with state-of-the-art approaches by calculating the network latency in terms of computational and communication costs. The analysis shows that the protocol is effective and practical in time-bound scenarios.
Beyond Log-Concavity: Theory and Algorithm for Sum-Log-Concave Optimization
Authors: Achab Mastane 
Published: September 2023

Abstract
This paper extends the classic theory of convex optimization to the minimization of functions that are equal to the negated logarithm of what we term as a sum-log-concave function, i.e., a sum of log-concave functions. In particular, we show that such functions are in general not convex but still satisfy generalized convexity inequalities. These inequalities unveil the key importance of a certain vector that we call the cross-gradient and that is, in general, distinct from the usual gradient. Thus, we propose the Cross Gradient Descent (XGD) algorithm moving in the opposite direction of the cross-gradient and derive a convergence analysis. As an application of our sum-log-concave framework, we introduce the so-called checkered regression method relying on a sum-log-concave function. This classifier extends (multiclass) logistic regression to non-linearly separable problems since it is capable of tessellating the feature space by using any given number of hyperplanes, creating a checkerboard-like pattern of decision regions.
Genomic landscape reveals evolutionary footprints of adaptability in Indian hill cattle
Authors: Ahmad S.F. 
Published: September 2023

Abstract
The present study is aimed to assess the population structure of hill cattle and analyze the genomic footprints of selection and adaptation. The population structure and signatures of selection were analyzed in hill cattle in comparison to Indian milch, non-milch and exotic cattle populations, using Illumina high-density genotyping data. The present study used high-density SNP genotyping data generated on Illumina BovineHD SNP BeadChip on a total of 299 individuals representing 14 bovine populations across three groups i.e., Hill cattle (Ladakhi and Siri), Indian milch cattle (Sahiwal, Gir, Tharparkar), Indian non-milch cattle (Hariana, Hallikar, Kankrej, Ongole, and Vecheur) and exotic group (Holstein-Friesian, Jersey, Brown Swiss and Guernsey). The grouping of populations was based on utility, inheritance and characteristics related to the terrain of breeding tract. The final merged dataset included coverage on 4,68,671 common autosomal SNP markers after quality pruning using different thresholds. The population structure was assessed using principal component analysis and maximum likelihood-based TreeMix analysis while twin methods (iHS, and XP-EHH) were used to scan the whole genome for haplotype homozygosity statistics. Multiple chromosomes were observed to harbour SNPs under selective sweeps in different comparisons. TRIM44, SLC5A12, MYO1D and NAPB were important genes that showed overlap with SNP markers whose frequency was significantly different than overall hill cattle genome under selection. Various genes were found as part of selection footprints along multiple comparisons including U6, ADGRL3, RELN, DAP3, STO1, DNAJA2. A functional analysis of the genes harbouring SNPs under evolutionary pressure (as part of selection sweeps) was undertaken to gain deeper insights into the biological relevance of selection footprints. The genes as part of selection sweeps were mainly involved in important adaptation traits including cell-cell signalling, neuronal development, mitochondrial functioning, hyaluronidase functioning, ion-channel transport of solute and nutrients, and response to reactive oxygen species and other stressors. The present study provides detailed insights into the genomic landscape changes that are result of adaptation of hill cattle to agro-climatic conditions under which they are reared.
Geospatial ecological economic planning based on water-energy-agritourism nexus, a case study of Jilin Province, China
Authors: Guo Yongjia 
Published: September 2023

Abstract
How to use geospatial technology to plan the ecological economy reasonably and promote the sustainable development of regional ecotourism has become an important issue faced by the current society. On the basis of the relationship between water and energy, this article took tourist areas as an example to analyze the geographical and spatial distribution characteristics of ecotourism attractions. A comparative analysis was conducted between the experimental group's tourist areas planned using GIS (geographic information system) and the control group's tourist areas planned using traditional planning. It was found that the average ecological and economic income of the experimental group within 1 year was about 1.2661 million yuan, which was higher than the average ecological and economic income of the control group within 1 year. This indicated that using GIS geospatial technology for reasonable planning of tourist areas is important for improving the overall ecological and economic income of tourist areas. This article used this research to explore the importance of rational planning of the ecological economy. Building a good ecological economic structure in tourism development plays an important role in reducing water and energy consumption to promote sustainable development of the tourism industry.