bluuebunny/crossref_metadata_2025 huggingface dataset:
Terahertz CMOS High-Sensitivity Sensor Based on Hybridized Spoof Surface Plasmon Resonator
Authors: Wan Ming , Li Chenchen , Bao Di , Wang Jiangpeng , Lu Kai , Qu Zhenyu , Gao Hao
Published: January 2025

In recent years, spoof localized surface plasmon (SLSP) have gained increasing attention due to their strong electromagnetic wave confinements. Based on the multipole resonance of SLSP, a high-Q-factor terahertz resonator based on CMOS technology is proposed. Specifically, a quadrilateral hybridized SLSP structure, composed of a core and a cavity SLSP resonator, is designed to reduce electric dimension and improve the Q-factor. The experimentally measured Q-factor reached 56.7 at 194 GHz, which is quite a high value within the terahertz frequency band, particularly given the compact electrical dimension of 0.081λ × 0.081λ. Moreover, pharmaceutical testing in the terahertz frequency range was successfully conducted, including glucose and two traditional Chinese medicines: Chuanbei and Sanqi. And three frequency shifts (4 GHz, 3.2 GHz, and 1.4 GHz) were observed. Thus, the SLSP resonator holds great potential for high-performance terahertz applications.
Exploring the Biocontrol Potential of Fungus Alternaria gaisen GD-011 in the Tibetan Plateau
Authors: Zhu Haixia , Li Huan , Ma Yongqiang
Published: January 2025

In screening for biocontrol strains with broad-spectrum and efficient herbicidal activity, strain GD-011 isolated from naturally susceptible M. sativa (Medicago sativa L.) roots was selected as a promising candidate. The control effects of strain GD-011 on nine weeds of Qinghai farmland were evaluated in vitro and in vivo, and its safety to five local crops was tested. The in vivo spray inoculation test showed that strain GD-011 had a strong pathogenic effect on the weeds M. verticillata (Malva verticillata L.), E. densa (Elsholtzia densa Benth), and A. fatua (Avena fatua L.), with incidence rates of more than 80.87% and fresh weight control effects of more than 71.8%. Crop safety tests showed that the B. napus (Brassica napus L.) crop is moderately susceptible to strain GD-011, with slight reactions in H. vulgare (Hordeum vulgare L.), but strain GD-011 is safe for T. aestivum (Triticum aestivum L.), P. sativum (Pisum sativum L.), and V. faba (Vicia faba L.) Observations on the morphological characteristics combined with a sequence analysis of the ribose rDNA internal transcribed spacer (rDNA ITS), the Elongation factor (EF-1α) gene, and the antigen-related protein gene (Alt a1) identified strain GD-011 as Alternaria gaisen. Scanning electron microscopy observations showed that the mycelia of strain GD-011 invaded the leaf tissue through the stomata on the surface, with the formation of a parasitic mycelium network on the surface of the tissue, the metabolism of E. densa leaf tissues was disturbed, and leaf tissues appeared to be broken. From the perspective of its herbicidal potential, the metabolites of strain GD-011 have good control effects on most weeds and are relatively safe for crops.
Investigation of a Rare Occurrence of a Diatomaceous Coating of the Cotswold Weir Wall on the Condamine River, Australia
Authors: Thompson John P. , Standley John , Hancock Rachel C.
Published: January 2025

A white encrustation of the Cotswold Weir wall in the lower reaches of the Condamine River, a tributary of the Murray–Darling River system in semi-arid Australia, was investigated following community concern that it indicated health risks from an unknown substance in the water resulting from mining and agricultural enterprises in the catchment. The vitreous white surface consisted of closely packed frustules of diatoms, observed by scanning electron microscopy, with an underlying layer of clay particles and dried filamentous green algae. Pennate diatoms identified in the white encrustation were the benthic species Nitzschia palea (predominant), Eolimna subminiscula, Craticula aff. cuspidata, Navicula viridula var. rostellata, and Luticola mutica. The centric diatom species Melosira varians was also present as filamentous chains of cylindrical frustules among the aggregated pennate diatom frustules. The encrustation was the remains of a periphyton (biofilm) of diatoms and green algae that had developed during protracted stream flow over the weir wall following record flooding. A dry period had resulted in the death of the diatoms and exposure of their aggregated siliceous frustules as a vitreous white coating. All diatom species identified are considered tolerant of eutrophic and mildly saline conditions. Chemical analyses of water from the Cotswold Weir, compared to long-term records, revealed higher salinity, with changes from March when the river was flowing to September when the white coating was noted, in electrical conductivity (299 to 461 µS/cm), and in sodium (26 to 43 mg/L) and chloride (26 to 75 mg/L) concentrations, respectively. Total nitrogen (0.82 to 1.6 mg/L) and total phosphorus (0.24 to 0.094 mg/L) were at mesotrophic and eutrophic concentrations, respectively, together with substantial dissolved silica concentrations (18 to 11 mg/L). Atomic ratios for total nitrogen/total phosphorus (7.6 to 37.6), nitrate-nitrogen/orthophosphate-phosphorus (2.3 to 274), and dissolved silica–silicon:orthophosphate-phosphorus (81.7 to 749) probably favoured diatoms over other photoautotrophs. While the diatomaceous encrustation indicated no health risks from the weir water, continued watch is required to avoid eutrophication and salinization of the river.
Effect of Ultraviolet Aging on Properties of Epoxy Resin and Its Pultruded Fiber-Reinforced Composite
Authors: Ci Shengzong , Wang Baoming , Di Chengrui , Wang Mingyu , Zhu Bo , Qiao Kun
Published: January 2025

Polymer matrix composites (PMCs) often undergo aging as a result of ultraviolet (UV) radiation, which significantly impacts their performance and durability. This paper investigated the alterations in the microstructure and macroscopic properties of epoxy resin and its composite used in overhead wires during UV aging. Furthermore, the mechanism of UV aging for both resin and composite was revealed. The results showed that UV aging predominantly affected the properties of the surface layer resin. UV aging can induce molecular chain scission, which leads to resin weight change, color deepening, microcrack formation, a decline in mechanical properties, and other performance degradation behaviors under the combined action of many factors. With the increase in aging time, the weight change rate and hardness of the resin increased first and then decreased, while the mechanical properties of the composite decreased rapidly first and gradually tended to be constant. The bending strength and impact strength of the composite decreased by 6.0% and 12.8%, respectively, compared with the initial values. The purpose of this study is to comprehensively understand the UV aging behaviors of epoxy resins and their composites employed in overhead wires, and it also provides essential data for advancing the utilization and durability of epoxy resins and composites across aerospace, marine, and other outdoor applications.
Thermal Decomposition of Date Seed/Polypropylene Homopolymer: Machine Learning CDNN, Kinetics, and Thermodynamics
Authors: Albin Zaid Zaid Abdulhamid Alhulaybi , Otaru Abdulrazak Jinadu
Published: January 2025

The buildup of abandoned plastics in the environment and the need to optimize agricultural waste utilization have garnered scrutiny from environmental organizations and policymakers globally. This study presents an assessment of the thermal decomposition of date seeds (DS), polypropylene homopolymer (PP), and their composites (DS/PP) through experimental measurements, machine learning convolutional deep neural networks (CDNN), and kinetic and thermodynamic analyses. The experimental measurements involved the pyrolysis and co-pyrolysis of these materials in a nitrogen-filled thermogravimetric analyzer (TGA), investigating degradation temperatures between 25 and 600 °C with heating rates of 10, 20, and 40 °C.min−1. These measurements revealed a two-stage process for the bio-composites and a decrease in the thermal stability of pure PP due to the moisture, hemicellulose, and cellulose content of the DS material. By utilizing machine learning CDNN, algorithms and frameworks were developed, providing responses that closely matched (R2~0.942) the experimental data. After various modelling modifications, adjustments, and regularization techniques, a framework comprising four hidden neurons was determined to be most effective. Furthermore, the analysis revealed that temperature was the most influential parameter affecting the thermal decomposition process. Kinetic and thermodynamic analyses were performed using the Coats–Redfern and general Arrhenius model-fitting methods, as well as the Flynn–Wall–Ozawa and Kissinger–Akahira–Sunose model-free approaches. The first-order reaction mechanism was identified as the most appropriate compared to the second and third order F-Series solid-state reaction mechanisms. The overall activation energy values were estimated at 51.471, 51.221, 156.080, and 153.767 kJ·mol−1 for the respective kinetic models. Additionally, the kinetic compensation effect showed an exponential increase in the pre-exponential factor with increasing activation energy values, and the estimated thermodynamic parameters indicated that the process is endothermic, non-spontaneous, and less disordered.
A Rescheduling Strategy for Multipurpose Batch Processes with Processing Time Variation and Demand Uncertainty
Authors: Zheng Taicheng , Li Dan , Li Jie
Published: January 2025

In this paper, we address the problem of dynamic scheduling of a multipurpose batch process subject to two types of disturbances, namely, processing time variation and demand uncertainty. We propose a rescheduling strategy that combines several ideas. First, when we generate a new schedule, we simultaneously construct a Directed Acyclic Graph (DAG) to represent this new schedule. While each node in the DAG represents an operation, each arc represents the dependency of an operation on another. Based on this DAG, we then use a simple procedure to determine how long an operation is allowed to be delayed without affecting the current makespan. After that, when the new schedule is used for online execution, we trigger a rescheduling procedure only when (1) we infer from the predetermined delayable time information that the current makespan will be extended, or (2) we observe new demands, or (3) the current schedule is not guaranteed to be feasible. In the rescheduling procedure, only the affected operations are allowed to be revised, while those unaffected operations are fixed. By doing this, we can reduce system nervousness and improve computational efficiency. The computational results demonstrate that our method can achieve an order of magnitude of reduction in both the number of operation changes and the computational time with a slightly better long-term makespan, compared to the widely used periodically–completely rescheduling strategy.
CO2 to Methanol Conversion: A Bibliometric Analysis with Insights into Reaction Mechanisms, and Recent Advances in Catalytic Conversion
Authors: Sajnani Shahdev , Memon Mazhar Ahmed , Memon Shabir Ahmed , Kumar Akash , Mehvish Darakhshan , Ameen Somavia , Mukarama  , Zhou Wei , Liu Yuan
Published: January 2025

The rising levels of atmospheric carbon dioxide (CO2) necessitate urgent and effective strategies for its capture and utilization. Among the various CO2 valorization pathways, the conversion of CO2 into methanol has gained considerable attention due to its dual role in reducing greenhouse gas emissions and serving as a renewable fuel and chemical feedstock. This review uniquely combines bibliometric analysis of 13,289 peer-reviewed publications (2012–2023) with an evaluation of Cu-based catalyst advancements, addressing critical gaps in the literature. A bibliometric analysis highlights the key trends, collaborations, and research gaps in the field. Among the catalytic systems, noble metals, though highly active, are uneconomical for large-scale applications, while non-noble metals, such as nickel, exhibit limited activity due to undesired reaction pathways. In comparison, Cu-based catalysts overcome these challenges by offering a balance of activity, selectivity, and cost-effectiveness. Special emphasis is placed on the CO2 to methanol conversion pathways, with insights into thermodynamic constraints, emerging solutions, and potential directions for future research. By consolidating the current state of knowledge, this review identifies significant opportunities for advancing CO2 conversion technologies, particularly in methanol synthesis, positioning it as a promising strategy for sustainable carbon management and energy production.
An Improved Mask2Former-HRNet Method for Insulator Defect Detection
Authors: Huo Yaoran , Xiao Lan , Tang Zhenyu , Zhou Jian , Dai Xu , Xiao Yuhao , Fang Xia
Published: January 2025

To solve the problem of scale variation in insulator images captured by drones, caused by the lack of control over angle and distance, which makes it hard to detect subtle defects, this paper proposes an instance segmentation method based on an improved Mask2Former-HRNet model for precise localization and defect detection of transmission line insulators. First, a mask-guided and matching component is added to Mask2Former to reduce the misjudgment rate of insulator defects by including noisy label masks. Second, the HRNet backbone network is used to better capture the spatial and shape information of insulators, as it has a stronger feature transfer ability. Deformable convolutions are introduced to handle deformation issues caused by varying angles in insulator images. Then, an attention mechanism is added to focus on key content, improving the network’s attention to crucial information. Finally, experimental results on defect detection of transmission line insulator images captured by drones show that the proposed method increases the detection accuracy by 8.41% and reduces the misjudgment rate by 4.11%. Comparative experiments indicate that the proposed method outperforms existing methods in several evaluation metrics.
Navigating Burnout: The Mediating Role of Mindfulness and the Mediterranean Lifestyle in Fostering Job Satisfaction and Well-Being
Authors: Christodoulou Efstratios , Dimitriadou Maroula-Eleni , Mpali Tsambika , Koutelidakis Antonios E.
Published: January 2025

This study delves into the intricate interplay between mindfulness, the Mediterranean lifestyle, burnout, job satisfaction, and well-being among employees, offering compelling insights for workplace interventions. Through a cross-sectional survey comprising 407 employees in Greece, we unravel the profound associations among these variables, shedding light on novel pathways to mitigate burnout and enhance overall employee satisfaction and health. Our findings unveil not only the negative associations between mindfulness, the Mediterranean lifestyle, and burnout but also the pivotal role of mindfulness as a predicting factor of burnout. Moreover, our research underscores the significant impact of burnout on job satisfaction, emphasizing the need for organizational strategies to address employee well-being. Notably, our mediation analyses illuminate the potential benefits of mindfulness and the Mediterranean lifestyle on burnout, accentuating the importance of fostering a workplace culture that embraces holistic well-being practices. With practical implications for designing evidence-based workplace wellness programs, our study advocates for the integration of mindfulness techniques and the adoption of Mediterranean lifestyle principles to cultivate resilient, engaged employees, and foster thriving organizational cultures. By delving into these dynamic relationships, our research not only advances theoretical frameworks but also offers actionable strategies to navigate burnout and promote flourishing in the modern workplace.
Differential Code Bias Estimation and Accuracy Analysis Based on CSES Onboard GPS and BDS Observations
Authors: Pang Jiawen , Zhu Fuying , Wu Shang
Published: January 2025

An accurate estimation of Differential Code Bias (DCB) is essential for high-precision applications of the Global Navigation Satellite System (GNSS) and for the precise determination of GNSS-derived total electron content (TEC). This study leverages BeiDou Navigation Satellite System (BDS) and Global Positioning System (GPS) dual-frequency observations of the China Seismo-electromagnetic Satellite (CSES) from day of the year (DOY) 201 to DOY 232 in 2018, we evaluate the quality of CSES onboard GNSS observations, improve the data preprocessing method, and use the least-squares to estimate DCBs for both GNSS satellites and CSES receivers. A comprehensive analysis of the estimation accuracy is presented, revealing that DCBs for BDS satellites, derived from joint BDS and GPS observations, exhibit superior consistency compared to those from single BDS observations. Notably, the stability of DCBs for the CSES BDS receiver as well as for BDS GEO, IGSO, and MEO satellites has been significantly enhanced by 70%, 14%, 22%, and 23%, respectively. Conversely, the consistency of GPS satellite DCBs estimated from joint observations shows a decline when compared to the DCB products from the Center for Orbit Determination in Europe (CODE) and the Chinese Academy of Sciences (CAS). When fewer than nine satellites are tracked daily and nighttime observations are under 25%, estimation errors increase. The optimal DCB estimation is achieved with a cutoff elevation angle set at 10°, with monthly mean DCB values for CSES GPS and BDS receivers determined to be −2.193 ns and −1.099 ns, respectively, accompanied by root mean square errors (RMSEs) of 0.10 ns and 0.31 ns. The highest accuracy of DCBs estimated by the single-GPS scheme is corroborated by examining the occurrence of negative vertical total electron content (VTEC) percentages.
Modeling Forest Carbon Stock Based on Sample Plots and UAV Lidar Data from Multiple Sites and Examining Its Vertical Characteristics in Wuyishan National Park
Authors: Jian Kai , Lu Dengsheng , Li Guiying
Published: January 2025

The accurate estimation of forest carbon stocks with remote sensing technologies helps reveal the spatial patterns of forest carbon stocks within national parks, but the limited number of sample plots in one site often results in difficulty in developing robust estimation models. This study employed a Bayesian hierarchical model to estimate forest carbon stock based on data from 193 sample plots collected across 37 UAV (unmanned aerial vehicle) Lidar sites. The developed model was employed to predict the carbon stock distribution in 17 Lidar sites within Wuyishan National Park (WNP). Then, the carbon stock characteristics along vertical zones of vegetation distribution (VZsVD) were examined. The results showed an overall coefficient of determination (R2) of 0.84 for forest carbon stock estimation across four regions, with a root mean square error (RMSE) of 12.09 t/ha. Within WNP, the overall R2 was 0.73, with specific values of 0.83 for broadleaf forests, 0.61 for mixed forests, 0.53 for Masson pine forests, and 0.46 for Chinese fir forests. Despite variations in R2, the relative RMSE (rRMSE) averaged 20.15%, ranging from 10.83% to 23.57%. The average carbon stock was 52.15 t/ha. Forest diversity and structural complexity emerged as key factors influencing the vertical distribution of carbon stocks. Regions with complex and diverse forest types exhibited higher and more evenly distributed carbon stocks. Chinese fir and Masson pine showed higher carbon stocks in low-altitude regions (350–850 m) than other vegetation types. In medium- to high-elevation regions (1350–1600 m), the carbon stocks of mixed forest and broadleaf forests remained relatively stable. Conversely, coniferous forests at high altitudes (above 1600 m) had lower carbon stocks due to extreme climatic and terrain conditions. This study provided a comprehensive analysis of carbon stock distribution across different VZsVD in WNP, offering valuable insights for enhancing the management of national parks.
Compensation of Temperature-Induced Errors in Quartz Flexible Accelerometers Using a Polynomial-Based Non-Uniform Mutation Genetic Algorithm Framework
Authors: Zhao Jinyue , He Kunpeng , Le Kang , Tu Yongqiang
Published: January 2025

The quartz flexible accelerometer (QFA) is a critical component in navigation-grade strapdown inertial navigation systems (SINS) due to its bias error, which significantly impacts the overall navigation accuracy of SINS. Temperature variations induce dynamic changes in the bias and scale factor of QFA, leading to a degradation of the navigation accuracy of SINS. To address this issue, this paper proposes a temperature error compensation method based on a non-uniform mutation strategy genetic algorithm (NUMGA) and a polynomial curve model (PCF). Firstly, the temperature bias mechanism of QFA output is analyzed, and a polynomial temperature error model is established. Then, the NUMGA is utilized to identify the model parameters using the −20–40 °C test data, seeking the optimal parameters for the polynomial. Finally, the compensation parameters are used for cold start static test verification. The results demonstrate that the temperature compensation model based on NUMGA-PCF can automatically select the optimal parameters, which enable the model to exhibit a stable decreasing trend on the adaptation curve without multiple fluctuations. Compared to the traditional GA temperature compensation model, the compensation errors in the three axes of QFA in SINS are reduced by 612.24 μg, 60.82 μg, and 875.82 μg, respectively. Before the 20th generation, there are no decrease in convergence speed observed with the in-crease of population diversity. Within the −20–40 °C temperature range, the average values and standard deviations of QFA for the three optimized axes can be maintained below 0.1 μg by using this compensation model.
Pd-Decorated SnO2 Nanofilm Integrated on Silicon Nanowires for Enhanced Hydrogen Sensing
Authors: Fang Tiejun , Mo Tianyang , Xu Xianwu , Tao Hongwei , Wang Hongbo , Yu Bingjun , Zhao Zhi-Jun
Published: January 2025

The development of reliable, highly sensitive hydrogen sensors is crucial for the safe implementation of hydrogen-based energy systems. This paper proposes a novel way to enhance the performance of hydrogen sensors through integrating Pd-SnO2 nanofilms on the substrate with silicon nanowires (SiNWs). The samples were fabricated via a simple and cost-effective process, mainly consisting of metal-assisted chemical etching (MaCE) and electron beam evaporation. Structural and morphological characterizations were conducted using scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). The experimental results showed that, compared to those without SiNW structure or decorative Pd nanoparticles, the Pd-decorated SnO2 nanofilm integrated on the SiNW substrates exhibited significantly improved hydrogen sensing performance, achieving a response time of 9 s at 300 °C to 1.5% H2 and a detection limit of 1 ppm. The enhanced performance can be primarily attributed to the large surface area provided by SiNWs, the efficient hydrogen spillover effect facilitated by Pd nanoparticles, and the abundant oxygen vacancies present on the surface of the SnO2 nanofilm, as well as the Schottky barrier formed at the heterojunction interface between Pd and SnO2. This study demonstrates a promising approach for developing high-performance H2 sensors characterized by ultrafast response times and ultralow detection limits.
CR-Mask RCNN: An Improved Mask RCNN Method for Airport Runway Detection and Segmentation in Remote Sensing Images
Authors: Wan Meng , Zhong Guannan , Wu Qingshuang , Zhao Xin , Lin Yuqin , Lu Yida
Published: January 2025

Airport runways, as the core part of airports, belong to vital national infrastructure, and the target detection and segmentation of airport runways in remote sensing images using deep learning methods have significant research value. Most of the existing airport target detection methods based on deep learning rely on horizontal bounding boxes for localization, which often contain irrelevant background information. Moreover, when detecting multiple intersecting airport runways in a single remote sensing image, issues such as false positives and false negatives are apt to occur. To address these challenges, this study proposes an end-to-end remote sensing image airport runway detection and segmentation method based on an improved Mask RCNN (CR-Mask RCNN). The proposed method uses a rotated region generation network instead of a non-rotated region generation network, allowing it to generate rotated bounding boxes that fit the shape of the airport runway more closely, thus avoiding the interference of a large amount of invalid background information brought about by horizontal bounding boxes. Furthermore, the method incorporates an attention mechanism into the backbone feature extraction network to allocate attention to different airport runway feature map scales, which enhances the extraction of local feature information, captures detailed information more effectively, and reduces issues of false positives and false negatives when detecting airport runway targets. The results indicate that, when comparing horizontal bounding boxes with rotated bounding boxes for detecting and segmenting airport runways, the latter are more precise for complex backgrounds. Furthermore, incorporating an attention mechanism enhances the accuracy of airport runway recognition, making it highly effective and practical.
Deep Learning Tool Wear State Identification Method Based on Cutting Force Signal
Authors: Li Shuhang , Li Meiqiu , Gao Yingning
Published: January 2025

The objective of this study is to accurately, expeditiously, and efficiently identify the wear state of milling cutters. To this end, a state identification method is proposed that combines continuous wavelet transform and an improved MobileViT lightweight network. The methodology involves the transformation of the cutting force signal during the milling cutter cutting process into a time–frequency image by continuous wavelet transform. This is followed by the introduction of a Contextual Transformer module after layer 1 and the embedding of a Global Attention Mechanism module after layer 2 of the MobileViT network structure. These modifications are intended to enhance visual representation capability, reduce information loss, and improve the interaction between global features. The result is an improvement in the overall performance of the model. The improved MobileViT network model was shown to enhance accuracy, precision, recall, and F1 score by 1.58%, 1.23%, 1.92%, and 1.57%, respectively, in comparison with the original MobileViT. The experimental results demonstrate that the proposed model in this study exhibits a substantial advantage in terms of memory occupation and prediction accuracy in comparison to models such as VGG16, ResNet18, and Pool Former. This study proposes an efficient identification method for milling cutter wear state identification, which can identify the tool wear state in near real-time. The proposed method has potential applications in the field of industrial production.
Graph Neural Network and LSTM Integration for Enhanced Multi-Label Style Classification of Piano Sonatas
Authors: Zhang Sibo , Liu Yang , Zhou Mengjie
Published: January 2025

In the field of musicology, the automatic style classification of compositions such as piano sonatas presents significant challenges because of their intricate structural and temporal characteristics. Traditional approaches often fail to capture the nuanced relationships inherent in musical works. This paper addresses the limitations of traditional neural networks in piano sonata style classification and feature extraction by proposing a novel integration of graph convolutional neural networks (GCNs), graph attention networks (GATs), and Long Short-Term Memory (LSTM) networks to conduct the automatic multi-label classification of piano sonatas. Specifically, the method combines the graph convolution operations of GCNs, the attention mechanism of GATs, and the gating mechanism of LSTMs to perform the graph structure representation, feature extraction, allocation weighting, and coding of time-dependent features of music data layer by layer. The aim is to optimize the representation of the structural and temporal features of musical elements, as well as the dependence between discovery features, so as to improve classification performance. In addition, we utilize MIDI files of several piano sonatas to construct a dataset, spanning the 17th to the 19th centuries (i.e., the late Baroque, Classical, and Romantic periods). The experimental results demonstrate that the proposed method effectively improves the accuracy of style classification by 15% over baseline schemes.
Adaptive Kalman Filter Fusion Positioning Based on Wi-Fi and Vision
Authors: Zhong Shuxin , Cheng Li , Yuan Haiwen , Li Xuan
Published: January 2025

The fusion of multiple sensor data to improve positioning accuracy and robustness is an important research direction in indoor positioning systems. In this paper, a Wi-Fi- and vision-based Fusion Adaptive Kalman Filter (FAKF) method is proposed for improving the accuracy of indoor positioning. To improve the accuracy of Wi-Fi positioning, a random forest algorithm with added region restriction is proposed. For visual positioning, YOLOv7 target detection and Deep SORT target tracking algorithms are combined in order to improve the stability of visual positioning. The fusion positioning method proposed in this study uses Kalman filtering for state estimation and updating by combining measurements from camera and Wi-Fi sensors, and it adaptively adjusts the parameters and weights of the filters by monitoring the residuals of the camera and Wi-Fi measurements in real time in order to optimize the accuracy and stability of the position estimation. In the experimental section, the real trajectory data and the predicted trajectory data generated using different positioning methods are compared. The experimental results show that the fused positioning method can significantly reduce positioning errors and the fused data can more accurately reflect the actual position of a target compared with single-sensor data.
Assessing the Impacts of Mulching on Vegetable Production Under Drip Irrigation in Burkina Faso
Authors: Masasi Blessing , Aryal Niroj , Millogo Vinsoun , Masasi Jonathan , Srivastava Ajit , Kalita Prasanta K.
Published: January 2025

Burkina Faso faces chronic food insecurity because of adverse agroclimatic conditions and significant soil degradation. Mulching, the practice of applying organic or synthetic materials to the soil surface, offers a promising avenue for enhancing agricultural production in this challenging agroecological setting. This study utilized the Sustainable Intensification Assessment Framework (SIAF) to evaluate the ecological, economic, and social impacts of mulching on vegetable production in Burkina Faso. Experimental and survey data collected from Sonsongona village in Bobo-Dioulasso were used to compare the production of mulched and non-mulched vegetables (tomato, cabbage, and onion) across the five SIAF domains. A calibrated AquaCrop crop model was also applied with 30-year historical weather data to simulate mulched and non-mulched cabbages for the study site. Our results reveal that mulching conserves soil moisture, suppresses weed growth, and enhances soil fertility, contributing to enhanced vegetable production and long-term sustainability. Economically, adopting mulching positively influences vegetable yields, reduces labor requirements, and increases income for smallholder farmers. These mulching benefits lead to community empowerment, particularly among women farmers. Our findings highlight the multifaceted benefits of mulching, suggesting that it holds promise for increasing agricultural productivity and improving economic stability, ecological sustainability, and social well-being in Burkina Faso. These insights contribute to developing context-specific strategies for sustainable intensification, with applicability across similar agroecological contexts in sub-Saharan Africa and beyond.
The Network Evolution and Influencing Factors of the Global Cultural Printed Material Trade
Authors: Wang Li , Ding Fang , Liu Tao , Zheng Qingqing
Published: January 2025

Understanding the global trade network in the printing industry is crucial for promoting sustainable development and cultural exchange and knowledge dissemination. However, the extant literature does not reveal the contours of the global cultural printed material trade network. This paper uses a social network analysis and QAP analysis to explore the global printing industry trade network pattern. The aim of this paper is to discern the core and emerging nodes and explore the evolutional characteristics on the network spatial linkage and country role. The results show the following: ① The printing industry’s global trade network is growing increasingly intricate, with trade links between nations (regions) becoming closer, the network’s connectivity steadily improving, and the hierarchical structure becoming more apparent. ② Germany, France, and Belgium are important intermediary bridges. The “circle of friends” in the trade of cultural products has a growing effect, and China can more easily establish close ties with Southeast Asia, Northern Europe, and Central and Eastern Europe. ③ The industrial chain and geographical proximity are the primary factors in the formation of the trade network. Economic proximity and political proximity significantly and positively contribute to the formation of the trade network, while institutional stability gradually plays a weaker role. As for cultural proximity, a common language and colonial relationship will positively contribute to the formation of a network, while immigrants have no obvious impact. Digital technology is becoming an “emerging force”. Additionally, this paper extends sustainable policies and recommendations for the global cultural trade.
Continuum Effect on Mirror Symmetry Breaking Within the Gamow Frameworks
Authors: Zhang Shuang , Xu Zhicheng , Wang Simin
Published: January 2025

Nuclear physics provides a natural laboratory for studying two kinds of fermions: protons and neutrons. These particles share similarities in mass and strong nuclear interactions, which are often described by isospin symmetry. However, isospin is not a good quantum number due to the differences between protons and neutrons in charge and quark mass. These differences become more pronounced as we approach or move beyond the dripline, affecting the structures and decay properties of mirror nuclei. To explore these intriguing phenomena, researchers have developed novel theoretical frameworks. In this article, we review the results from the Gamow shell model and Gamow coupled-channel, which account for the mirror symmetry breaking influenced by nuclear forces and continuum effects. Specifically, we discuss the recently observed mirror asymmetries in nuclei at the boundaries of the nuclide landscape and their theoretical explanations. We examine the breaking of mirror symmetry in the spectra of N=8 isotones versus Z=8 isotopes, as well as the decay properties of the 22Al-22F mirror pair. Such studies enhance our understanding of strong interactions and the behavior of open quantum systems.
Symmetry in Genetic Distance Metrics: Quantifying Variability in Neurological Disorders for Personalized Treatment of Alzheimer’s and Dementia
Authors: Ruiz-Vanoye Jorge A. , Díaz-Parra Ocotlán , Márquez-Vera Marco Antonio , Barrera-Cámara Ricardo A. , Fuentes-Penna Alejandro , Simancas-Acevedo Eric , Ruiz-Jaimes Miguel A. , Xicoténcatl-Pérez Juan M. , Ramos-Fernández Julio Cesar
Published: January 2025

This paper aims to adapt and apply genetic distance metrics in biomedical signal processing to improve the classification and monitoring of neurological disorders, specifically Alzheimer’s disease and frontotemporal dementia. The primary objectives are: (1) to quantify the variability in EEG signal patterns among the distinct subtypes of neurodegenerative disorders and healthy individuals, and (2) to explore the potential of a novel genetic similarity metric in establishing correlations between brain signal dynamics and clinical progression. Using a dataset of resting-state EEG recordings (eyes closed) from 88 subjects (36 with Alzheimer’s disease, 23 with frontotemporal dementia, and 29 healthy individuals), a comparative analysis of brain activity patterns was conducted. Symmetry plays a critical role in the proposed genetic similarity metric, as it captures the balanced relationships between intra- and inter-group EEG signal patterns. Our findings demonstrate that this approach significantly improves disease subtype identification and highlights the potential of the genetic similarity metric to optimize the predictive models. Furthermore, this methodology supports the development of personalized therapeutic interventions tailored to individual patient profiles, making a novel contribution to the field of neurological signal analysis and advancing the application of EEG in personalized medicine.
Identification of Benzothiophene-Derived Inhibitors of Flaviviruses by Targeting RNA-Dependent RNA Polymerase
Authors: Wang Leah Liu , Karim Shazeed-Ul , Hand Aidan , Brunkhorst Ryan , Petersen Mackenna , Altman Sarah , Liu Yi , Zhang Luwen , Bai Fengwei , Xiang Shi-Hua
Published: January 2025

Flaviviruses such as Dengue, West Nile, and Zika viruses are mosquito-borne RNA viruses that can cause serious diseases in humans. To develop effective drugs for treating these viruses’ infections, we create a new approach for developing common or shared drugs that may work for several different viral species of flaviviruses. It is based on the conserved RNA-dependent RNA polymerase (RdRp), which is the key enzyme for viral replication. We built up a common structure of RdRps (POLcon) from their consensus sequence. A conserved Triple-D structural motif was identified at the active site of POLcon that has been used for virtual compound screening. We have identified three inhibitors that have potent activities against Dengue, West Nile, and Zika viruses. All these three inhibitors are Benzothiophene derivatives. This is the first report of Benzothiophene-derived compounds as inhibitors for flaviviruses. Furthermore, our approach has provided a proof-of-concept that it is feasible to identify shared drugs for several different viral species of flaviviruses.
Primordial Biochemicals Within Coacervate-Like Droplets and the Origins of Life
Authors: Stefano George B. , Kream Richard M.
Published: January 2025

An organism is considered “alive” if it can grow, reproduce, respond to external stimuli, metabolize nutrients, and maintain stability. By this definition, both mitochondria and viruses exhibit the key characteristics of independent life. In addition to their capacity for self-replication under specifically defined conditions, both mitochondria and viruses can communicate via shared biochemical elements, alter cellular energy metabolism, and adapt to their local environment. To explain this phenomenon, we hypothesize that early viral prototype species evolved from ubiquitous environmental DNA and gained the capacity for self-replication within coacervate-like liquid droplets. The high mutation rates experienced in this environment streamlined their acquisition of standard genetic codes and adaptation to a diverse set of host environments. Similarly, mitochondria, eukaryotic intracellular organelles that generate energy and resolve oxygen toxicity, originally evolved from an infectious bacterial species and maintain their capacity for active functionality within the extracellular space. Thus, while mitochondria contribute profoundly to eukaryotic cellular homeostasis, their capacity for freestanding existence may lead to functional disruptions over time, notably, the overproduction of reactive oxygen species, a phenomenon strongly linked to aging-related disorders. Overall, a more in-depth understanding of the full extent of the evolution of both viruses and mitochondria from primordial precursors may lead to novel insights and therapeutic strategies to address neurodegenerative processes and promote healthy aging.
A Single Water Pipeline Design Considering Pressure-Dependent Consumptions: A New Perspective
Authors: Puerta-Zurita Mariangel , Villero-Guerra Juan J. , Coronado-Hernández Oscar E. , Fuertes-Miquel Vicente S. , Saba Manuel
Published: January 2025

Current design techniques for water installations are based on pressure-independent consumption. However, certain types of consumption depend on pressure, most notably water leakages, which occur in all water distribution systems. All water installations are prone to water leakages. To mitigate this issue during the design stage of water pipelines, manuals and local regulations recommend a percentage of water losses for sizing pipelines and using them with pressure-independent consumption. This research develops a practical procedure for sizing single water pipelines by considering the effect of pressure-dependent consumption, as in actual pipelines. The findings of this research offer water utilities a new perspective on pipeline design, which is essential for developing new tools to create digital twins. A new methodology for designing pipe diameters is developed in this research. A single pipeline, 2000 m long, is used for the analysis with an emitter coefficient of 0.00829 m3/s/m0.5. The proposed methodology focuses on calculating energy losses to maintain the required minimum pressure in the system. A sensitivity analysis is conducted on key parameters such as the emitter coefficient, absolute roughness, and the resistance coefficient of a regulating valve. The results of the proposed methodology are compared with the current design (using pressure-independent consumption), revealing differences of up to 28% in calculating water losses.
Study on Sand Wear Testing and Numerical Simulation of a 500 MW Class Pelton Turbine
Authors: Li Jialing , Pang Jiayang , Qin Mengjun , Liu Xiaobing , Hua Hong , Wu Baofu , Zhang Haiku , Liu Jitao , Yu Zhishun , Zeng Yongzhong
Published: January 2025

Pelton turbines frequently encounter significant sediment wear when operating in sandy river environments. The runner bucket of these turbines is particularly prone to wear, which results in considerable reductions in turbine efficiency and operational stability. This research focused on a large-scale Pelton turbine with a 500 MW standalone capacity in a sandy river setting. Numerical simulations of sand–water flow within the runner bucket were conducted using the volume of fluid (VOF) model, shear stress transport (SST) k-ω model, and the discrete phase model (DPM). Additionally, a sediment wear prediction model, based on wear tests conducted on a model turbine, was utilized to estimate sediment wear within the Pelton turbine bucket. The results indicated a maximum bucket wear rate of 2.61 × 10−7 mm/s. Specifically, the 04Cr13Ni5Mo runner bucket, typically made from stainless-steel wear-resistant material, is expected to experience over 5.62 mm of wear after one year of operation under rated conditions, emphasizing the severity of sediment wear. To prolong the operational life of the unit, further investigations into surface wear resistance treatments for the runner water buckets are recommended.
Schiffsbautermini aus der Handschrift von Chylińskis NOVUM TESTAMENTUM
Authors: Hock Wolfgang , Hornecker Henrik
Published: January 2025

The article discusses thirteen entries in the manuscript of Chyliński’s translation of the New Testament that can be attributed to shipbuilding terminology: arklinas, bartos, krywułey, paras, Reanes, rudelis, rupa, ſelewiney, sparey, stoba, styrbarkey, trielbanga and zieza. The majority of these words is glossed in Polish, one in Latin (krywułey), and three (Reanes, sparey, trielbanga) have no indication of meaning. Most of the lemmas have not yet been recorded lexicographically or only in meanings other than those used here. The study analyses the word forms morphologically and aims at a better understanding of their meaning. It investigates their etymology and word history against the background of shipbuilding terminology in the Baltic Sea region of the 17th century. Even though many of the terms are words borrowed from Polish or Germanic, possibly through the mediation of Polish, it turns out that hardly any of the word forms are linguistically unambiguous and that hybrid formations, crossbreeding and etymological folk reinterpretations must be taken in consideration.
The concept of a new premises block for national and reference standards in the context of the creation of the National Metrology Institute of Ukraine
Authors: Potokin Yurii , Kuzmenko Yurii , Samoilenko Oleksandr , Borodiy Davyd
Published: January 2025

The need for designing and building new premises block for national and reference standards as part of the measures to create the National Metrological Institute of Ukraine based on the State Enterprise «Ukrmetrteststandart» in Kyiv is substantiated. The presented project considers the difficult geopolitical realities in Ukraine, which may persist for many more years. Nevertheless, the project is aimed to be included in the strategic post-war reconstruction plan of Ukraine in terms of sustainable development of the national quality infrastructure as part of the European community. The conceptual design of a new building for the preservation and operation of the National Standards of Ukraine presented in the publication leaves room for proposals from interested parties (on the pages of this and other editions) for improvement and innovation.
The premises block of the new building will meet the requirements for the preservation and operation of standards in the current geopolitical situation and after its changes. The main conceptual solution is that the building for national and reference standards consists of an external and internal structure, separated by a temperature joint 1,5 meters wide along the perimeter of the internal structure and on top. The standards are supposed to be stored in the internal structure. The external structure protects the internal structure from all negative factors and houses the infrastructure necessary for the storage and operation of the standards.
Fortune, Long Life, and Luck in Battle: The Cult of the Three Devas and Worldly Rituals in Medieval Japan
Authors: Rappo Gaétan
Published: January 2025

Dans le panthéon des divinités japonaises, il existe plusieurs figures auxquelles on attribue une efficacité particulière pour l’obtention de bienfaits concrets, dans la vie présente. Cet article analyse une triade de divinités, les trois Devas (santen) : Shōten (ou Kangiten), Benzaiten et surtout Dakiniten. Leur culte s’est développé à partir du Moyen Âge au sein du bouddhisme ésotérique Shingon, mais aussi Tendai, avant de se diffuser plus largement dans les textes shinto, notamment ceux qui concernaient la figure du dieu Inari, le Shugendō ou encore les pratiques religieuses des guerriers, ainsi que les rites martiaux destinés à soumettre ses ennemis. Après avoir examiné les origines de cette triade et analysé une série de rituels combinant des tables de divination de la voie du yin et du yang et des pratiques du bouddhisme ésotérique, cet article montre aussi la continuité de l’espace symbolique mis à contribution dans ces rites, ainsi que la constance – qui se retrouve même dans le vocabulaire – de leurs objectifs de richesse, de longévité, et surtout de chance sur le champ de bataille. Ainsi se dégagera une vue d’ensemble de l’évolution historique de cette constellation de rites, mythes et symboles, que l’on peut considérer comme un exemple particulièrement vivace d’une religiosité vécue.