bluuebunny/crossref_metadata_2025 huggingface dataset:
Diversified Cropping of Grains and Atractylodes lancea (Thunb.) DC. Enhances Ecological Benefits of Agroecosystems
Authors: Wang Enze , Sun Yu , Li Ming , Ye Libo , Yu Xinyi , Yao Zongmu , Tian Chunjie
Published: December 2024

Crop diversification is pivotal in sustainable agriculture, influencing soil microbial communities and soil nutrient cycling functions. Yet, the impacts of incorporating medicinal plants into crop diversification strategies on the functional characteristics of these microbial communities remain understudied. This research elucidates the benefits of diversified cropping systems by assessing soil nutrient content, diversity and composition of soil microorganisms, the abundance of functional genes involved in carbon (C), nitrogen (N) and phosphorus (P) cycling, and overall agricultural productivity; collectively referred to as ecological benefits. The experimental design included four treatment groups: (1) continuous maize (Zea mays L.) cultivation (MC); (2) maize–A. lancea (Atractylodes lancea Thunb.) intercropping (MA); (3) maize–sorghum (Sorghum bicolor L.) rotation (MS); and (4) maize–A. lancea intercropping combined with sorghum rotation (MSA). Findings indicate that diversified cropping treatments significantly enhance the alpha diversity of soil bacterial communities over fungal communities. NH4+ and NO3− predominantly influence the composition of soil bacterial communities, with a notable increase in the relative abundance of Acidobacteriota, Gemmatimonadota, and Chloroflexi. Compared to MC treatment, the MA and MSA treatments significantly increased the abundance of C (121.44%, 294.26%), N (206.57%, 294.26%), and P (112.02%, 225.84%) cycling genes. The inverse variance weighting evaluation demonstrates that, compared to the MC treatment, the MS (5.34) and MSA (8.15) treatments significantly boost soil ecological benefits. Overall, diversifying the cultivation of A. lancea with grains can enhance the ecological benefits of the soil. This study offers new perspectives on diversified planting, particularly in terms of species selection and practical combinations on farmland.
Trends and Applications of Computed Tomography in Agricultural Non-Destructive Testing
Authors: Wang Qi , Xue Hui , John Martin Jerome Jeyakumar , Hou Mingming , Cao Hongxing , Dong Zhiguo , Li Jianshe , Sun Chengxu
Published: December 2024

With the continuous progress of technology, computed tomography (CT) technology has expanded from medicine to agriculture and other industries. With the advantages of non-destructiveness, high resolution, and high precision, CT technology shows great application potential in the agricultural field. However, there are still some problems with this technology that need to be solved. This paper aims to show the application of CT technology in the agricultural field, find technical challenges, and put forward specific countermeasures, so that CT technology can be better applied in the agricultural field. This paper summarizes the application of CT technology in the quality detection of agricultural products, disease and insect pest identification, seed screening, soil analysis, and precision agriculture management, and focuses on the current challenges and the countermeasures, and looks into the role of this technology in promoting agricultural development in the future. Despite various challenges, CT technology has far more advantages than disadvantages, and it is expected to become an indispensable part of all the links of agricultural production and promote the development of precision agriculture and smart agriculture.
A Comparative Study of Agroecological Intensification Across Diverse European Agricultural Systems to Assess Soil Structure and Carbon Dynamics
Authors: Doyeni Modupe Olufemi , Kadziene Grazina , Pranaitiene Simona , Slepetiene Alvyra , Skersiene Aida , Shamshitov Arman , Trinchera Alessandra , Warren Raffa Dylan , Testani Elena , Fontaine Sebastien , Rodriguez-Hernandez Antonio , Rasmussen Jim , Sánchez-Moreno Sara , Hanegraaf Marjoleine , Un Akin , Sail Simon , Suproniene Skaidre
Published: December 2024

Continuous agricultural activities lead to soil organic carbon (SOC) depletion, and agroecological intensification practices (i.e., reduced soil disturbance and crop diversification) have been suggested as strategies to increase SOC storage. The study aims to assess the effect of agroecological intensification levels (lower (T1) and highest (T2)) on the soil C pool and aggregate stability and validate the correlation between different variables compared to the control (lowest/none (T3), where agroecological intensification was not applied. The C-stock, soil microbial biomass carbon (SMB-C), SOC, water extractable organic carbon (WEOC) in bulk soil, fine and coarse soil aggregates, and water-stable aggregates (WSA) were measured during maximum nutrient uptake in plants under diversified agroecological practices across different environmental conditions (core sites: Italy (CS1), France (CS2), Denmark (CS4), Spain (CS5), Netherlands (CS6), Lithuania (CS7), Turkey (CS8), and Belgium (CS9)). The soil aggregate stability varied among the CSs and treatments. At sites CS7 and CS9, WSA was higher in T1 and T2 compared to the control; a similar trend was observed at other sites, except CS1. SMB-C differed among the core sites, with the lowest value obtained in CS5 (52.3 μg g−1) and the highest in CS6 (455.1 μg g−1). The highest average contents of SOC and WEOC were obtained in bulk soil at CS2 (3.1 % and 0.3 g kg−1 respectively). Positive and statistically significant (p < 0.001) correlations were detected among all variables tested with SOC in bulk soil and WSA. This study demonstrates the significance of agroecological practices in improving soil carbon stock and optimizing plant–soil–microbe interactions.
Different Types of Co-Infection by Contagious Ecthyma Virus, Enteropathogenic Escherichia coli, Mycoplasma conjunctivae, Ecto- and Endo-Parasites in Four Young Alpine Ibex (Capra ibex)
Authors: Domenis Lorenzo , Spedicato Raffaella , Guidetti Cristina , Carella Emanuele , Robetto Serena
Published: December 2024

The research aimed to investigate the perinatal pathology of Alpine ibex (Capra ibex) through the study of four young subjects (at the age of 3 to 4 months) found dead in Valle d’Aosta, a region of northwestern Italy. The carcasses were submitted to necropsy followed by an examination of ecto- and endoparasites (ECP and ENP); samples from the gross lesions (in summary, cutaneous papilloma and crusts, ocular discharge, lobular haemorrhagic areas in the lungs, catarrhal–haemorrhagic enterocolitis) were analysed by bacteriological, histopathological, and biomolecular methods to define the etiological agent. The subjects, with various co-infection patterns, were affected by contagious ecthyma virus (ORFV) (agent of a highly diffusive pustular dermatitis transmissible to small ruminants and humans), Enteropathogenic Escherichia coli (EPEC) (major etiological agent of infantile diarrhoea especially in developing countries), Mycoplasma conjunctivae (MC) (cause of an ocular infection common to goats and sheep), various ECP (ticks and keds) and ENP (lung and intestinal nematodes, and coccidia). This study emphasises the potential role of the Alpine ibex in the transmission of infectious diseases to other animals such as to humans and, secondly, the need to apply diversified analytical approaches, with the commitment of various specialistic skills, in order to define, in detail, the various and frequently overlapping causes that led a free-ranging animal to the death.
A Real-Time Lightweight Behavior Recognition Model for Multiple Dairy Goats
Authors: Wang Xiaobo , Hu Yufan , Wang Meili , Li Mei , Zhao Wenxiao , Mao Rui
Published: December 2024

Livestock behavior serves as a crucial indicator of physiological health. Leveraging deep learning techniques to automatically recognize dairy goat behaviors, particularly abnormal ones, enables early detection of potential health and environmental issues. To address the challenges of recognizing small-target behaviors in complex environments, a multi-scale and lightweight behavior recognition model for dairy goats called GSCW-YOLO was proposed. The model integrates Gaussian Context Transformation (GCT) and the Content-Aware Reassembly of Features (CARAFE) upsampling operator, enhancing the YOLOv8n framework’s attention to behavioral features, reducing interferences from complex backgrounds, and improving the ability to distinguish subtle behavior differences. Additionally, GSCW-YOLO incorporates a small-target detection layer and optimizes the Wise-IoU loss function, increasing its effectiveness in detecting distant small-target behaviors and transient abnormal behaviors in surveillance videos. Data for this study were collected via video surveillance under varying lighting conditions and evaluated on a self-constructed dataset comprising 9213 images. Experimental results demonstrated that the GSCW-YOLO model achieved a precision of 93.5%, a recall of 94.1%, and a mean Average Precision (mAP) of 97.5%, representing improvements of 3, 3.1, and 2 percentage points, respectively, compared to the YOLOv8n model. Furthermore, GSCW-YOLO is highly efficient, with a model size of just 5.9 MB and a frame per second (FPS) of 175. It outperforms popular models such as CenterNet, EfficientDet, and other YOLO-series networks, providing significant technical support for the intelligent management and welfare-focused breeding of dairy goats, thus advancing the modernization of the dairy goat industry.
The Influence of Berry-Derived Polyphenol Supplementation on Exercise-Induced Oxidative Stress and Cardiovascular Health in Physically Active Individuals
Authors: Ruszkowska Joanna , Drygas Wojciech , Kwaśniewska Magdalena
Published: December 2024

Numerous studies have documented that high-intensity or prolonged exercise is associated with increased oxidative stress and modification of antioxidant status. Polyphenol-rich dietary supplements seem to be the compounds that can upregulate the endogenous antioxidant defense system and consequently prevent muscle damage, support recovery. As berry fruits are at the top of the list of the richest polyphenol food sources, supplements containing berries have become the subject of interest in the context of counteracting exercise-induced oxidative stress and the development of cardiovascular diseases. The purpose of this review is to summarize current knowledge on the effects of berry-derived polyphenol supplementation on exercise-induced oxidative stress and cardiovascular health in physically active individuals. Based on the available literature, blackcurrant supplementation, with its richest version being New Zealand blackcurrant extract, is the most commonly explored berry fruit, followed by chokeberries and blueberries. Although several studies have documented the significant and beneficial influence of berry-derived supplements on redox status and cardiovascular response, some inconsistencies remain. The presented findings should be interpreted with caution due the limited number of available studies, particularly with the participation of physically active individuals. Further research is needed to reveal more comprehensive and accurate data concerning the impact of berry-derived supplements on exercise-induced outcomes taking into account the type of supplement, time of administration, and dosage.
Vitamins, Coenzyme Q10, and Antioxidant Strategies to Improve Oocyte Quality in Women with Gynecological Cancers: A Comprehensive Review
Authors: Alexandru Isaic , Nistor Daciana , Motofelea Alexandru Catalin , Cadar (Andone) Bianca-Astrid , Crintea Andreea , Tatu Carmen , Pop Gheorghe Nicusor , Csep Andrei Nicolae
Published: December 2024

Background: Gynecological cancers, including ovarian, cervical, and endometrial cancers, significantly affect both survival and reproductive health in women. Cancer treatments such as chemotherapy and radiotherapy can impair ovarian function, reducing oocyte quality and fertility potential. Objective: This review aims to evaluate how vitamins and antioxidants can enhance fertility and fertility preservation outcomes for women diagnosed with gynecological cancers, particularly in the context of assisted reproductive technologies (ART). Standard treatments for these cancers, including hysterectomy, bilateral salpingo-oophorectomy, radiation, and chemotherapy, often compromise ovarian function and oocyte quality. This review focuses on the potential role of these interventions in improving oocyte quality, thereby supporting successful fertility preservation and ART outcomes. Methods: A comprehensive narrative review of the current literature was conducted, examining the effects of vitamins A, C, D3, E, and Coenzyme Q10 on oocyte quality, particularly in the context of oxidative stress and inflammation induced by cancer and its treatments. Results: The evidence suggests that certain vitamins and antioxidants may mitigate oxidative damage and enhance oocyte quality. Vitamin A supports cumulus–oocyte complex integrity, while vitamins C and E act as potent antioxidants, reducing oxidative stress in ovarian tissues. Vitamin D3 enhances ovarian reserve markers and modulates inflammatory cytokines. Coenzyme Q10 improves mitochondrial function and reduces DNA damage, increasing oocyte viability and fertilization potential. Conclusions: The incorporation of specific vitamins and antioxidants into fertility preservation strategies may enhance oocyte quality in women with gynecological cancers. Although the preliminary findings are promising, further research is needed to determine optimal dosages and establish standardized protocols for clinical use.
Sedimentary Record of the Bio-Geological Events in Tethys: Insight from the Permian Yangtze Block Breakup in the Sichuan Basin
Authors: Liu Xuanwei , Jiang Fujie , Zheng Xiaowei , Gao Yang , Zhou Siyu
Published: December 2024

At the end of the Middle Permian Guadeloupe series, the Chinese region recorded the only internationally recognized large igneous provincial eruption event, known as the Emeishan LIP. The Yangtze region of South China records a series of short and almost synchronous geological events that accompanied the development of bio-geological events such as large-scale magmatic intrusion, plate rupture, magnetic pole anomalies, and ecological collapse. These events ultimately triggered the extinction of living organisms. However, the current study leaves several questions unanswered. What was the sequence of geological events? Are the global records of these events synchronized? What is the causal relationship between these events? This study discusses the sedimentary responses to various geological events using biofossils, fluid inclusion, carbon isotopic analysis, and astrochronological analysis. The results reflect the following: (i) Mantle plumes: Mantle plumes act as pathways for heated fluids to ascend from the Earth’s interior. The mantle plume reached the Moho surface in the mid-Wordian and affected the magnetic field at the Earth’s surface; (ii) Magnetic pole anomalies: The anomaly of the Earth’s magnetic poles appeared in the mid-Wordian stage, causing the originally stable plates to begin to split. The sea level changes dramatically, and the ancient landform pattern changes dramatically; (iii) Plate rupture: The rifting of plates accelerated the activity of deep hydrothermal fluids; the hydrothermal fluid gradually infiltrated the paleo-ocean after the J. altudaensis zone; (iv) Emeishan LIP: The volcano erupted at 260 Ma, and eventually led to the mass extinction. We aim to identify the initial triggers of various geological events by analyzing the sedimentary record.
Bayesian Optimization for Instruction Generation
Authors: Sabbatella Antonio , Archetti Francesco , Ponti Andrea , Giordani Ilaria , Candelieri Antonio
Published: December 2024

The performance of Large Language Models (LLMs) strongly depends on the selection of the best instructions for different downstream tasks, especially in the case of black-box LLMs. This study introduces BOInG (Bayesian Optimization for Instruction Generation), a method leveraging Bayesian Optimization (BO) to efficiently generate instructions while addressing the combinatorial nature of instruction search. Over the last decade, BO has emerged as a highly effective optimization method in various domains due to its flexibility and sample efficiency. At its core, BOInG employs Bayesian search in a low-dimensional continuous space, projecting solutions into a high-dimensional token embedding space to retrieve discrete tokens. These tokens act as seeds for the generation of human-readable, task-relevant instructions. Experimental results demonstrate that BOInG achieves comparable or superior performance to state-of-the-art methods, such as InstructZero and Instinct, with substantially lower resource requirements while also enabling the use of both white-box and black-box models. This approach offers both theoretical and practical benefits without requiring specialized hardware.
Elemental Composition and Dentin Bioactivity at the Interface with AH Plus Bioceramic Sealer: An Energy-Dispersive X-Ray Spectroscopy Study
Authors: Marta Maria-Monica , Chivu Oana Roxana , Marian Diana , Enache Ioana-Catalina , Veja (Ilyes) Ioana , Pitic (Cot) Dana Emanuela , Flueras Razvan , Popovici Ramona Amina , Stana Ademir Horia , Cojocariu Carolina , Vasca Elisabeta , Olariu Iustin
Published: December 2024

In recent decades, there has been significant growth in research focused on biocompatible materials, particularly in the field of materials science and engineering. The primary advantages of these materials are their biocompatibility, bioactivity, and antibacterial properties. Consequently, there has been a growing utilization of bioceramic sealers in the field of endodontics. This study investigated the amounts of bioactive elements in dentin in contact with the AH Plus® Bioceramic Sealer (Dentsply, Konstanz, Germany). The results were qualitatively evaluated by examining scanning electron microscopy (SEM) images and elemental mapping and quantitatively by determining element weight (wt%) and atomic (at%) percentages obtained from EDX analysis. The AH Plus® Bioceramic Sealer demonstrated notable bioactivity through its dynamic contact with dentin at the root level.
Study on the Structural Instability Characteristics of Interlayer Rock Strata During Mining Under Interval Goaf in Shallow Coal Seams
Authors: Wang Bin , Zhang Jie , Lin Haifei , Liu Dong , Yang Tao
Published: December 2024

In order to study the instability characteristics of interlayer rock strata (IRS) in shallow buried close-distance coal seams under insufficient mining areas, based on the background of interval mining under goaf in Nanliang Coal Mine, this paper studies the instability characteristics of interlayer strata in interval mining under goaf by means of similar simulation, numerical simulation, and field measurement. The results indicated that the first weighting interval of the main roof during mining in the lower coal seam was 49 m, while small and large periodic weightings with intervals of 10–14 m and 15–19 m were identified. During periodic weighting, the support resistance ranged from 6813 to 10,935 kN, with a dynamic load factor of 1.07–1.74, and the peak abutment pressure in front of the working face was 5.85–9.85 MPa. The mining under the interval coal pillar (ICP) was the ‘stress increase zone’, and the mining under the temporary coal pillars (TCPs) and the interval goaf was the ‘stress release zone’. During the working face mining out of the ICP, the support resistance reached 10,934 kN, the dynamic load factor reached 1.74, and the abutment pressure (AP) reached 9.85 MPa, which was 60% higher than the AP mining under the “stress release zone”. Analysis suggests that the cutting instability of the IRS was the root cause of the increased AP in the working face of the lower coal seam. A numerical simulation was performed to verify the instability characteristics of the IRS in the interval goaf. The relationship between support strength and roof subsidence during the period of the working face leaving the coal pillar was established. A dynamic pressure prevention method involving pre-splitting and pressure relief of the ICP was proposed and yields superior field application performance. The findings of the study provide a reference for rock strata control during mining under the subcritical mining area in shallow and closely spaced coal seams.
An Innovative Gradual De-Noising Method for Ground-Based Synthetic Aperture Radar Bridge Deflection Measurement
Authors: Wang Runjie , Wu Haiqian , Zhao Songxue
Published: December 2024

Effective noise reduction strategies are crucial for improving the precision of Ground-Based Synthetic Aperture Radar (GB-SAR) technology in bridge deflection measurement, particularly in mitigating the signal noise introduced by complex environmental factors, and thereby ensuring reliable structural health assessments. This study presents an innovative gradual de-noising method that integrates an Improved Second-Order Blind Identification (I-SOBI) algorithm with Fast Fourier Transform (FFT) featuring Adaptive Cutoff Frequency Selection (A-CFS) for reducing the complex environmental noises. The novel method is a two-stage process. The first stage employs the proposed I-SOBI to preserve the contribution of effective information in separated signals as much as possible and to recover pure signals from noisy ones that have nonlinear characteristics or are non-Gaussian in distribution. The second stage utilizes the FFT with the A-CFS method to further deal with the residual high-frequency noises still within the signals, which is conducted under a proper cutoff frequency to ensure the quality of de-noised outputs. Through meticulous simulation and practical experiments, the effectiveness of the proposed de-noising method has been comprehensively validated. The experimental results state that the method performs better than the traditional Second-Order Blind Identification (SOBI) method in terms of noises reduction capabilities, achieving a higher accuracy of bridge deflection measurement using GB-SAR. Additionally, the method is particularly effective for de-noising nonlinear time-series signals, making it well-suited for handling complex signal characteristics. It significantly contributes to the provision of reliable bridge dynamic-behavior information for infrastructure assessment.
Heart Rate Measurement Accuracy During Intermittent Efforts Under Laboratory Conditions: A Comparative Analysis Between Chest Straps and Armband
Authors: Marzano-Felisatti Joaquín Martín , De Lucca Leonardo , Priego-Quesada José Ignacio , Pino-Ortega José
Published: December 2024

Heart rate (HR) is the most frequently used variable to monitor athletes’ internal load during training and competition. High-intensity effort and abrupt HR changes during exercise have presented measurement accuracy issues depending on the chosen device. Therefore, this study aimed to compare two chest straps (Garmin HRM-Dual and Coospo H6) and one armband (Coospo HW807) during intermittent exercise under controlled laboratory conditions. Thirty active young men performed an indoor cycling protocol consisting of seven intermittent efforts with a 2 min effort stage followed by a 2 min recovery stage. The results show no difference between the chest straps (Garmin vs. Coospo), with a high level of agreement between the two devices (Bias = −0.2 bpm, LoAup = +2.5 bpm, LoAlow = −2.9 bpm, ICC = 0.6–1.0). Differences were found between the chest straps and the armband during effort stages (±5 bpm, p < 0.05), with similar bias and LoA values in the Garmin Strap vs. Coospo Armband (Bias = −0.5 bpm, LoAup = 8.3 bpm, LoAlow = −9.3 bpm) and Coospo Strap vs. Coospo Armband (Bias = −0.4 bpm, LoAup = 8.3 bpm, LoAlow = −9.0 bpm) comparison. Chest straps (Garmin HRM-Dual and Coospo H6) accurately measure HR during intermittent exercise with abrupt HR changes. However, caution should be taken when using armbands (Coospo HW807) to monitor intermittent and high-intensity effort.
Evaluating the Efficacy of Cosmetic Textiles in Skin Hydration and Cellulite Management Through Wear Trials
Authors: Kurtoğlu Necef Özlem , Öndoğan Ziynet , Tama Birkocak Derya , Boz Serkan , Şen Kılıç Arzu , Boyacı Bekir , Ertam Sağduyu İlgen
Published: December 2024

This study aimed to develop and evaluate cosmetic textiles integrated into sportswear to enhance skin hydration and reduce the appearance of cellulite. The research involved the creation of leggings and long-sleeve shirts treated with microencapsulated natural extracts targeting moisture and anti-cellulite effects. A total of 18 healthy female volunteers participated in the wear trials with a control group and an experimental group wearing the microencapsulated garments. The participants underwent a standardized training procedure, and their skin’s moisture level and cellulite (orange peel) appearance were assessed using Tewameter measurements and thermal imaging. Additionally, dermatological clinical evaluations were performed. The results demonstrated that the microencapsulated products significantly improved skin hydration and reduced cellulite grades compared to the control group. All nine participants in the microencapsulated group displayed negative values for the appearance of orange peel skin, whereas two of the nine participants in the control group exhibited negative cellulite levels, one showed a positive value, and six showed no change at all. Statistical analyses also confirmed the efficacy of the microencapsulated garments. The study highlights the potential of cosmetic textiles in providing added value to sportswear by offering functional skin benefits during physical activity.
Can Digital Activism Change Sustainable Supply Chain Practices in the Agricultural Bioeconomy? Evidence from #Buttergate
Authors: van der Ven Hamish
Published: December 2024

Under what conditions will digital activism elicit a response from industry? What is the nature of that response and how does it impact sustainable supply chain practices? I develop three hypotheses in response to these questions by examining a recent case of digital activism targeted at the use of a controversial bioproduct in the Canadian dairy industry. Drawing on 14 key informant interviews as well as a novel Twitter dataset, I hypothesize that digital activism can elicit a response from industry when it originates with a small number of activists, provided that it also spreads to traditional media. I further hypothesize that industry’s response will be superficial and result in only token changes to sustainable supply chain practices due to the ephemerality and lack of cohesion inherent in some forms of digital activism. These hypotheses lay a foundation for broader cross-sectoral research on how industries respond to digital activism directed at their supply chains and add nuance to ongoing debates about the efficacy of digital activism as a means of changing industry practices.
Nonconvex Nonlinear Transformation of Low-Rank Approximation for Tensor Completion
Authors: Mei Yifan , Su Xinhua , Lin Huixiang , Ge Huanmin
Published: December 2024

Recovering incomplete high-dimensional data to create complete and valuable datasets is the main focus of tensor completion research, which lies at the intersection of mathematics and information science. Researchers typically apply various linear and nonlinear transformations to the original tensor, using regularization terms like the nuclear norm for low-rank approximation. However, relying solely on the tensor nuclear norm can lead to suboptimal solutions because of the convex relaxation of tensor rank, which strays from the original outcomes. To tackle these issues, we introduce the low-rank approximation nonconvex nonlinear transformation (LRANNT) method. By employing nonconvex norms and nonlinear transformations, we can more accurately capture the intrinsic structure of tensors, providing a more effective solution to the tensor completion problem. Additionally, we propose the proximal alternating minimization (PAM) algorithm to solve the model, demonstrating its convergence. Tests on publicly available datasets demonstrate that our method outperforms the current state-of-the-art approaches, even under extreme conditions with a high missing rate of up to 97.5%.
Seismic Response Analysis of Concrete Box-Type Subgrade in High-Speed Railways
Authors: Chen Ying-Ying , Xiao Hong , Song Xu-Guo , Guo Shuai-Jie , Luo Bei-Er , Nadakatti Mahantesh M.
Published: December 2024

China is prone to frequent earthquakes, impacting both the construction and operation of high-speed railways. The seismic response analysis is essential for the promotion and structural optimization of novel box-type subgrade structures. This paper develops a nonlinear integrated spatial dynamic model of a ballastless track and box-type subgrade, investigating structural vibrations under multi-dimensional seismic actions using the time–frequency domain method. A seismic performance analysis of the structure is conducted to examine the influence of seismic intensity on its seismic response. Results indicate that the box-type subgrades exhibit good integrity under seismic actions, primarily undergoing rigid body motion, with forces in all components well below design strength, meeting the Chinese seismic fortification requirements. Compared to traditional simply supported beams, box-type subgrades show better adaptability to earthquakes. As seismic intensity increases, vibrations and deformations of box-type subgrades change linearly, while vibrating forces increase nonlinearly.
Improving Hard Rock Materials Cuttability by Hydraulic Fracturing at Mining Working Face
Authors: Li Haojie , Liu Benben , He Qingyuan , Gao Yanan , Ma Dan , Yang Haiyan , Cheng Jingyi , Ye Jiqing , Liu Guoqiang
Published: December 2024

During advancing the working face at Guojiawan Coal Mine, hard rock faults are encountered, which hinder the normal cutting of the shearer. Hydraulic fracturing is applied to pretreat the hard rock materials. Un-directional hydraulic fracturing experiments in transparent gelatin samples are carried out. The influence of the differential stress, the borehole dip angle on the initiation and propagation of un-directional hydraulic fractures (HFs) are investigated. Three field test schemes of hydraulic fracturing are proposed and implemented at the 51207 working face of Guojiawan Coal Mine. Compared with the results of different test schemes, the cutting current ratio of the shearer is reduced by 51.70% and the cutting efficiency is increased by 89.93%. Therefore, the feasibility of hydraulic fracturing to improve the cuttability of the hard rock materials is verified, which provides a theoretical basis and field guidance for hydraulic fracturing pretreatment of the hard rock materials at a coal mining working face.
Compressive Behavior of Inconel 625 and Ti-6Al-4V Strut Lattices Fabricated by LPBF
Authors: Condruz Mihaela Raluca , Badea Teodor Adrian , Paraschiv Alexandru
Published: December 2024

The present study assessed the compression performance of four strut lattices manufactured via laser powder bed fusion (LPBF), namely selective laser melting (SLM) from Inconel 625 and Ti-6Al-4V. Static finite element analysis and mechanical testing were performed, and it was concluded that the experimentally determined performance trend was in good agreement with that obtained by numerical methods. The cell type greatly influences the compressive performance of the lattices, regardless of the material used for manufacturing. The best compressive performances were recorded for the octet lattice, followed by the truncated octahedron, Kelvin, and re-entrant lattices. Regarding material performance, for the first maximum compressive strength, similar results were recorded for both materials; a difference was recorded in the case of yield strength, with higher values were recorded for Ti-6Al-4V compared to Inconel 625. The average first maximum compressive strength for the Ti-6Al-4V lattice was between 30.39 and 290.17 MPa, and it was within a range of 16.22–258.71 MPa for Inconel 625. The elastic modulus was between 1.74 and 4.72 GPa for Ti-6Al-4V, and 1.13 and 4.46 GPa for Inconel 625. A more ductile behavior was registered for the nickel-based superalloy than for the titanium alloy; the Inconel 625 specimens were characterized by a bending-dominant damage mode, and Ti-6Al-4V specimens were characterized more by a stretch-dominant damage mode.
A Lightweight Kernel Density Estimation and Adaptive Synthetic Sampling Method for Fault Diagnosis of Rotating Machinery with Imbalanced Data
Authors: Lu Wenhao , Wang Wei , Qin Xuefei , Cai Zhiqiang
Published: December 2024

Rotating machinery is widely used across various industries, making its reliable operation crucial for industrial production. However, in real-world settings, intelligent fault diagnosis faces challenges due to imbalanced fault data and the complexity of neural network models. These challenges are particularly pronounced when defining decision boundaries accurately and managing limited computational resources in real-time machine monitoring. To address these issues, this study presents KDE-ADASYN-based MobileNet with SENet (KAMS), a lightweight convolutional neural network designed for fault diagnosis in rotating machinery. KAMS effectively handles data imbalances commonly found in industrial applications and is optimized for real-time monitoring. The model employs the Kernel Density Estimation Adaptive Synthetic Sampling (KDE-ADASYN) algorithm for oversampling to balance the data, applies fast Fourier transform (FFT) to convert time-domain signals into frequency-domain signals, and utilizes a 1D-MobileNet network enhanced with a Squeeze-and-Excitation (SE) block for feature extraction and fault diagnosis. Experimental results across datasets with varying imbalance ratios demonstrate that KAMS achieves excellent performance, maintaining nearly 90% accuracy even on highly imbalanced datasets. Comparative experiments further demonstrate that KAMS not only delivers exceptional diagnostic performance but also significantly reduces network parameters and computational resource requirements.
TurboPixels: A Superpixel Segmentation Algorithm Suitable for Real-Time Embedded Applications
Authors: Aguilar-González Abiel , Medina Santiago Alejandro , Orozco Torres Jorge Antonio , Osuna-Coutiño J. A. de Jesús , Pérez Patricio Madaín , Morales-Navarro Néstor A.
Published: December 2024

Superpixel segmentation aims to produce a consistent grouping of pixels. In recent years, the importance of superpixel segmentation has increased in computer vision since it offers useful primitives for extracting image features and simplifies the complexity of other image processing steps. In this work, we propose the TurboPixels algorithm, whose main contribution is a hardware architecture for superpixel segmentation. Compared with previous approaches, our superpixels are computed without the need for iterative loops. This makes it possible to reduce algorithmic complexity and increases processing speed. The experimental results indicate that our approach enables a small-scale FPGA-based implementation suitable for embedded applications. In addition, the results demonstrate that robust superpixel segmentation can be achieved with processing speeds up to 86 times faster than in previous works in the current literature.
On the Convergence of a Kurchatov-Type Method for Solving Nonlinear Equations and Its Applications
Authors: Argyros Ioannis K. , Shakhno Stepan , Yarmola Halyna
Published: December 2024

A local and a semi-local convergence analysis are presented for the Kurchatov-type method to solve numerically nonlinear equations in a Banach space. The method depends on a real parameter. By specializing the parameter, we obtain methods already studied in the literature under different types of conditions, such us Newton’s, and Steffensen’s, and Kurchatov’s methods, the Secant method, and other methods. This study is carried out under generalized conditions for first-order divided differences, as well as first-order derivatives. Both in the local case and in the semi-local case, the error estimates, the radii of the region of convergence, and the regions of the solution’s uniqueness are determined. A numerical majorizing sequence is constructed for studying semi-local convergence. The approach of restricted convergence regions is used to develop a convergence analysis of the considered method. The new approach allows a comparison of the convergence of different methods under a uniform set of conditions. In particular, the assumption of generalized continuity used to control the divided difference provides more precise knowledge on the location of the solution as well as tighter error estimates. Moreover, the generality of the approach makes it useful for studying other methods in an analogous way. Numerical examples demonstrate the applicability of our theoretical results.
On a Schrödinger Equation in the Complex Space Variable
Authors: Esquível Manuel L. , Krasii Nadezhda P. , Didier Philippe L.
Published: December 2024

We study a separable Hilbert space of smooth curves taking values in the Segal–Bergmann space of analytic functions in the complex plane, and two of its subspaces that are the domains of unbounded non self-adjoint linear partial differential operators of the first and second order. We show how to build a Hilbert basis for this space. We study these first- and second-order partial derivation non-self-adjoint operators defined on this space, showing that these operators are defined on dense subspaces of the initial space of smooth curves; we determine their respective adjoints, compute their respective commutators, determine their eigenvalues and, under some normalisation conditions on the eigenvectors, we present examples of a discrete set of eigenvalues. Using these derivation operators, we study a Schrödinger-type equation, building particular solutions given by their representation as smooth curves on the Segal–Bergmann space, and we show the existence of general solutions using an Fourier–Hilbert base of the space of smooth curves. We point out the existence of self-adjoint operators in the space of smooth curves that are obtained by the composition of the partial derivation operators with multiplication operators, showing that these operators admit simple sequences of eigenvalues and eigenvectors. We present two applications of the Schrödinger-type equation studied. In the first one, we consider a wave associated with an object having the mass of an electron, showing that two waves, when considered as having only a free real space variable, are entangled, in the sense that the probability densities in the real variable are almost perfectly correlated. In the second application, after postulating that a usual package of information may have a mass of the order of magnitude of the neutron’s mass attributed to it—and so well into the domain of possible quantisation—we explore some consequences of the model.
GCBAM-UNet: Sun Glare Segmentation Using Convolutional Block Attention Module
Authors: Zrira Nabila , Jimi Anwar , Di Nardo Mario , Elafi Issam , Gallab Maryam , Chahdi El Ouazzani Redouan
Published: December 2024

Sun glare poses a significant challenge in Advanced Driver Assistance Systems (ADAS) due to its potential to obscure important visual information, reducing accuracy in detecting road signs, obstacles, and lane markings. Effective sun glare mitigation and segmentation are crucial for enhancing the reliability and safety of ADAS. In this paper, we propose a new approach called “GCBAM-UNet” for sun glare segmentation using deep learning. We employ a pre-trained U-Net model VGG19-UNet with weights initialized from an ImageNet. To further enhance the segmentation performance, we integrated a Convolutional Block Attention Module (CBAM), enabling the model to focus on important features in both spatial and channel dimensions. Experimental results show that GCBAM-UNet is considerably better than other state-of-the-art methods, which will undoubtedly guarantee the safety of ADAS.
Geo-Statistical Characterization of Annual Maximum Daily Rainfall Variability in Semi-Arid Regions
Authors: Achite Mohammed , Caloiero Tommaso , Jehanzaib Muhammad , Wałęga Andrzej , Kuriqi Alban , Pellicone Gaetano
Published: December 2024

In the Wadi Cheliff basin (Algeria), a 48-year (1971–2018) time series of annual maximum daily rainfall was studied to identify and quantify trends observed at 150 rain gauges. Initial trends in annual maximum daily rainfall were determined using the Mann–Kendall test, with a significance level of 95%. The slope or increase/decrease in the annual maximum daily precipitation was assessed using the Theil–Sen estimator. A running trend analysis was then performed to quantify the effects of different time windows on trend detection. Finally, to assess the different spatial distribution of annual maximum daily precipitation during the observation period, spatial analysis was performed using a geo-statistical approach for the whole observation period and at different decades. The results showed a predominant negative trend in annual maximum daily rainfall (about 11% of rain gauges at a 95% significance level), mainly affecting the north-eastern area of the catchment. The spatial distribution of annual maximum daily rainfall showed high rainfall variability in the period of 1970–1980, with a decrease in the decades of 1980–1990 and 2010–2017 when the maximum values were more evenly distributed across the region.
Effectiveness and Mechanism of Resibufogenin on Human Renal Cancer Cell Caki-1
Authors: Wu Yuqi , Yang Yue , Huang Run , Li Tao , Wan Chunlei , Zhang Lei
Published: December 2024

In this study, we investigated the effect and mechanism of Resibufogenin on renal cell carcinoma based on network pharmacology, molecular docking, and in vitro experiments. The results showed that there were 35 cross-targets between Resibufogenin and renal cell carcinoma. GO and KEGG pathway analyses indicated that Resibufogenin inhibited renal cancer cells through the vascular smooth muscle contraction signalling pathway and EGFR tyrosine kinase inhibitor resistance signaling pathway, and MAPK1, PRKCB, and Resibufogenin had strong associative activities. After different concentrations of Resibufogenin were applied to human renal cancer cells, it was found that the IC50 value was 408.2 nM, 10 nM resibufogenin could significantly inhibit cell migration (p < 0.0001), the percentage of apoptosis and necrosis increased dose-dependently, and the expression of genes of MAPK1 and PRKCB in the cells was significantly reduced (p < 0.001) in a dose-dependent manner. The above results indicate that Resibufogenin can inhibit human renal cell carcinoma through multi-targets and multi-methods, which provides a theoretical basis for the application of Resibufogenin in the treatment of renal cell carcinoma and the development of novel drugs in the future.
Biological Implications of the Intrinsic Deformability of Human Acetylcholinesterase Induced by Diverse Compounds: A Computational Study
Authors: Alvarado Ysaías J. , González-Paz Lenin , Paz José L. , Loroño-González Marcos A. , Santiago Contreras Julio , Lossada Carla , Vivas Alejandro , Marrero-Ponce Yovani , Martinez-Rios Felix , Rodriguez-Lugo Patricia , Balladores Yanpiero , Vera-Villalobos Joan
Published: December 2024

The enzyme acetylcholinesterase (AChE) plays a crucial role in the termination of nerve impulses by hydrolyzing the neurotransmitter acetylcholine (ACh). The inhibition of AChE has emerged as a promising therapeutic approach for the management of neurological disorders such as Lewy body dementia and Alzheimer’s disease. The potential of various compounds as AChE inhibitors was investigated. In this study, we evaluated the impact of natural compounds of interest on the intrinsic deformability of human AChE using computational biophysical analysis. Our approach incorporates classical dynamics, elastic networks (ENM and NMA), statistical potentials (CUPSAT and SWOTein), energy frustration (Frustratometer), and volumetric cavity analyses (MOLE and PockDrug). The results revealed that cyanidin induced significant changes in the flexibility and rigidity of AChE, especially in the distribution and volume of internal cavities, compared to model inhibitors such as TZ2PA6, and through a distinct biophysical-molecular mechanism from the other inhibitors considered. These findings suggest that cyanidin could offer potential mechanistic pathways for future research and applications in the development of new treatments for neurodegenerative diseases.
Treatment Strategies for Painful Pelvic Floor Conditions: A Focus on the Potential Benefits of Cannabidiol
Authors: Bonanni Roberto , Ratano Patrizia , Cariati Ida , Tancredi Virginia , Cifelli Pierangelo
Published: December 2024

Painful conditions of the pelvic floor include a set of disorders of the pelvic region, discreetly prevalent in the female population, in which pain emerges as the predominant symptom. Such disorders have a significant impact on quality of life as they impair couple relationships and promote states of anxiety and irascibility in affected individuals. Although numerous treatment approaches have been proposed for the management of such disorders, there is a need to identify strategies to promote muscle relaxation, counter pelvic pain, and reduce inflammation. The endocannabinoid system (ECS) represents a complex system spread throughout the body and is involved in the regulation of numerous physiological processes representing a potential therapeutic target for mood and anxiety disorders as well as pain management. Cannabidiol (CBD), acting on the ECS, can promote relief from hyperalgesia and allodynia typical of disorders affecting the pelvic floor and promote muscle relaxation by restoring balance to this delicate anatomical region. However, its use is currently limited due to a lack of evidence supporting its efficacy and harmlessness, and the mechanism of action on the ECS remains partially unexplored to this day. This comprehensive review of the literature examines the impact of pain disorders affecting the pelvic floor and major treatment approaches and brings together the main evidence supporting CBD in the management of such disorders.
The Influence of Bariatric Surgery on Matrix Metalloproteinase Plasma Levels in Patients with Type 2 Diabetes Mellitus
Authors: Gentile João Kleber de Almeida , Migliore Renato , Waisberg Jaques , Ribeiro Junior Marcelo Augusto Fontenelle
Published: December 2024

Background: Bariatric surgery is a safe and effective procedure for treating obesity and metabolic conditions such as type 2 diabetes mellitus (T2DM). Remodeling of the extracellular matrix (ECM) supports adipose tissue expansion and its metabolic activity, where matrix metalloproteinases (MMPs) play a key role in ECM regulation. The MMPs, particularly MMP-2 and MMP-9, are elevated in patients with morbid obesity, metabolic syndrome, and T2DM. Objectives: To evaluate the effect of weight loss in bariatric surgery patients using oxidative stress markers and to compare MMP levels in patients undergoing bariatric surgery. Methods: This was a prospective, controlled study including 45 morbidly obese patients with T2DM (BMI > 35 kg/m2) who underwent RYGB (n = 24) or VG (n = 21). Weight loss was assessed through anthropometric measurements (weight, height, BMI). MMP-2 and MMP-9 levels were measured preoperatively and at 3 and 12 months postoperatively. Results: Significant and sustained weight loss was observed after surgery in both groups, with reductions in BMI. MMP-2 and MMP-9 levels decreased significantly after one year of follow-up. Conclusions: Bariatric surgery is an effective long-term intervention for weight loss and associated comorbidities, including T2DM. MMP-2 and MMP-9 proved to be effective markers of extracellular matrix remodeling, with significant reductions following surgery.