bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Salp Swarm Algorithm and Extended Repository Feature Selection Method in Bearing Fault Diagnosis
Authors: Lee Chun-Yao , Le Truong-An , Chen Yung-Chi , Hsu Shih-Che
Published: May 2024

Motor fault diagnosis is an important task in the operational monitoring of electrical machines in manufacturing. This study proposes an effective bearing fault diagnosis model for electrical machinery based on machine learning techniques. The proposed model is a combination of three processes: feature extraction of signals collected from the motor based on multi-resolution analysis, fast Fourier transform, and envelope analysis. Next, redundant or irrelevant features are removed using the feature selection technique. A binary salps swarm algorithm combined with an extended repository is the proposed method to remove unnecessary features. As a result, an optimal feature subset is obtained to improve the performance of the classification model. Finally, two classifiers, k-nearest neighbor and support vector machine, are used to classify the fault of the electric motor. There are four input datasets used to evaluate the model performance, and UCI is the benchmark dataset to verify the effectiveness of the proposed feature selection technique. The remaining three datasets include the bearing dataset collected from experiments, with an average classification accuracy of 99.9%, as well as Case Western Reserve University (CWRU) and Machinery Failure Prevention Technology (MFPT), which are public datasets with average classification accuracies of 99.6% and 98.98%, respectively. The experimental results show that this method is more effective in diagnosing bearing faults than other traditional methods and prove its robustness.
Importance of Changes in the Copper Production Process through Mining and Metallurgical Activities on the Surface Water Quality in the Bor Area, Serbia
Authors: Marković Radmila , Marjanović Vesna M. , Stevanović Zoran , Gardić Vojka , Petrović Jelena , Kovačević Renata , Štirbanović Zoran , Friedrich Bernd
Published: May 2024

This paper considers the impact of copper mining-influenced water and metallurgical wastewater on the surface water in the Bor area, Serbia. Sampling, realized through the four campaigns (2020–2021), confirmed that both types of water, discharged without appropriate treatment in the Bor River, had a signific impact on the concentration of metal ions, pH and electrical conductivity on the watercourse in the Bor area. The highest concentrations of the following metal ions, Cu—271 mg/L, As—25,991 μg/L, Ni—13,856 μg/L, Cd—2627 μg/L, and Pb—2855 μg/L, were registered in the metallurgical wastewater samples. After changes occurred in the copper production process by stopping the discharge of untreated wastewater into the Bor River, the concentrations of monitored elements were drastically decreased. In the period 2022–2024, the concentration values for Cu, As and Pb ions were below the maximum allowable value, and the concentration values of Ni and Cd ions were also decreased. The values for pH and electrical conductivity were in the maximum allowable range. The return of wastewater to the copper production process would lead to both a reduction in the primary water consumption and reduction in the negative impact on the environment.
Candida spp. in Cetaceans: Neglected Emerging Challenges in Marine Ecosystems
Authors: Garcia-Bustos Victor , Rosario Medina Inmaculada , Cabañero Navalón Marta Dafne , Ruiz Gaitán Alba Cecilia , Pemán Javier , Acosta-Hernández Begoña
Published: May 2024

Cetaceans, which are crucial in marine ecosystems, act as sentinels for ecosystem and human–environmental health. However, emerging fungal infections, particularly by Candida spp., pose a growing concern in these marine mammals. This review consolidates current knowledge on the prevalence, clinical manifestations, species distribution, and antifungal resistance of Candida infections in cetaceans. We detail the diverse pathogenic impacts of Candida, including respiratory, dermal, and systemic afflictions, underscoring diagnostic and treatment challenges amid rising antifungal resistance. Our analysis extends beyond health concerns in captive cetaceans, where confinement stress heightens vulnerability, to encompass substantial ecological risks in wild populations. The review emphasizes the One Health perspective, linking cetacean health with broader environmental and human public health issues. We particularly focus on the potential zoonotic transmission of emerging fungal pathogens such as Candida auris and the role of environmental changes in fostering antifungal resistance. The study underscores the need for concerted, interdisciplinary efforts in veterinary, medical, and environmental sciences to enhance understanding and management of Candida infections in cetaceans. We advocate for comprehensive monitoring and collaborative research initiatives to mitigate the rising challenge of these infections. Addressing Candida spp. in cetaceans is not just a conservation priority but a critical step in safeguarding overall marine health and, by extension, human health in the context of evolving infectious diseases.
Petrogenesis and Geodynamic Evolution of A-Type Granite Bearing Rare Metals Mineralization in Egypt: Insights from Geochemistry and Mineral Chemistry
Authors: Ghoneim Mohamed M. , Abdel Gawad Ahmed E. , El-Dokouny Hanaa A. , Dawoud Maher , Panova Elena G. , El-Lithy Mai A. , Mahmoud Abdelhalim S.
Published: May 2024

During the Late Precambrian, the North Eastern Desert of Egypt underwent significant crustal evolution in a tectonic environment characterized by strong extension. The Neoproterozoic alkali feldspar granite found in the Homret El Gergab area is a part of the Arabian Nubian Shield and hosts significant rare metal mineralization, including thorite, uranothorite, columbite, zircon, monazite, and xenotime, as well as pyrite, rutile, and ilmenite. The geochemical characteristics of the investigated granite reveal highly fractionated peraluminous, calc–alkaline affinity, A-type granite, and post-collision geochemical signatures, which are emplaced under an extensional regime of within-plate environments. It has elevated concentrations of Rb, Zr, Ba, Y, Nb, Th, and U. The zircon saturation temperature ranges from 753 °C to 766 °C. The formation of alkali feldspar rare metal granite was affected by extreme fractionation and fluid interactions at shallow crustal levels. The continental crust underwent extension, causing the mantle and crust to rise, stretch, and become thinner. This process allows basaltic magma from the mantle to be injected into the continental crust. Heat and volatiles were transferred from these basaltic bodies to the lower continental crust. This process enriched and partially melted the materials in the lower crust. The intrusion of basaltic magma from the mantle into the lower crust led to the formation of A-type granite.
Research Progress of Molecular Simulation in Acrylamide Polymers with High Degree of Polymerization
Authors: Liu Zhenye , Feng Qi , Xu Zhuangzhuang , Yang Shuangchun
Published: May 2024

Acrylamide polymers with a high degree of polymerization are widely used in petroleum production. It is of great significance to study the oil displacement mechanism of acrylamide polymers with a high degree of polymerization from the micro level. In recent years, the rapid development of computer molecular simulation technology has filed the gaps in macroscopic experiments and theories. This technology has been highly valued in the study of the molecular behaviour of polymer systems. In this paper, the research progress of molecular simulation applied to high-polymerization-degree acrylamide polymer is summarized. The application status of acrylamide polymer flooding, the analysis of polymer flooding mechanisms, and the research progress of molecular simulation in acrylamide linear and crosslinked polymers are expounded. Finally, the development prospect of acrylamide polymer research is given, and suggestions are put forward in terms of simulation direction and simulation tools.
Changes of Active Substances in Ganoderma lucidum during Different Growth Periods and Analysis of Their Molecular Mechanism
Authors: Gao Xusheng , Huo Huimin , Bao Haiying , Wang Jialu , Gao Dan
Published: May 2024

Ganoderma lucidum, renowned as an essential edible and medicinal mushroom in China, remains shrouded in limited understanding concerning the intrinsic mechanisms governing the accumulation of active components and potential protein expression across its diverse developmental stages. Accordingly, this study employed a meticulous integration of metabolomics and proteomics techniques to scrutinize the dynamic alterations in metabolite accumulation and protein expression in G. lucidum throughout its growth phases. The metabolomics analysis unveiled elevated levels of triterpenoids, steroids, and polyphenolic compounds during the budding stage (BS) of mushroom growth, with prominent compounds including Diplazium and Ganoderenic acids E, H, and I, alongside key steroids such as cholesterol and 4,4-dimethyl-5alpha-cholesta-8,14,24-trien-3beta-ol. Additionally, nutrients such as polysaccharides, flavonoids, and purines exhibited heightened presence during the maturation stage (FS) of ascospores. Proteomic scrutiny demonstrated the modulation of triterpenoid synthesis by the CYP450, HMGR, HMGS, and ERG protein families, all exhibiting a decline as G. lucidum progressed, except for the ARE family, which displayed an upward trajectory. Therefore, BS is recommended as the best harvesting period for G. lucidum. This investigation contributes novel insights into the holistic exploitation of G. lucidum.
Response Surface Methodology (RSM) for Optimizing Protein Extraction from Housefly (Musca domestica) Larvae Fed with Toad and Its Structural Characterization
Authors: Miao Jingnan , Yu Chenglu , Cheng Xianhe , Qiu Junqiang , Liu Shumin
Published: May 2024

With the global population on the rise, an escalating interest exists in environmentally sustainable and friendly protein sources. Insects have emerged as multifaceted resources, viewed not only as potential food items, but also as sources of traditional medicines and proteins. This study utilized response surface methodology (RSM) to ascertain the optimal extraction conditions for proteins from Musca domestica used in toad feeding, denoted as MDPs-T. The yield of MDPs-T was elevated to 18.3% ± 0.2% under these optimized conditions. Subsequently, the particle size, ζ-potentials, and structures of MDPs-T were analyzed and compared with the proteins derived from Musca domestica fed on a normal diet (MDPs-ND). This comparative analysis utilized a range of advanced techniques, involving UV spectroscopy, Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), high-performance gel permeation chromatography (HPGPC), and scanning electron microscopy (SEM). The outcomes have revealed a marginal disparity in the physical and chemical properties between MDPs-T and MDPs-ND. Derosination led to a reduction in the particle size of the MDPs by 10.98% to 62.81%. MDPs-T exhibited a higher proportion of low-molecular-weight components relative to MDPs-ND. Additionally, in a comparative analysis of amino acids, MDPs-T displayed a greater abundance of essential and total amino acids relative to MDPs-ND. Consequently, MDPs-T holds potential as a valuable food supplement for human consumption or as a nutrient-rich feed supplement for animals.
Examining the Direct and Indirect Effects of Postprandial Amino Acid Responses on Markers of Satiety following the Acute Consumption of Lean Beef-Rich Meals in Healthy Women with Overweight
Authors: Braden Morgan L. , Gwin Jess A. , Leidy Heather J.
Published: May 2024

The consumption of protein-rich foods stimulates satiety more than other macronutrient-rich foods; however, the underlying mechanisms-of-action are not well-characterized. The objective of this study was to identify the direct and indirect effects of postprandial amino acid (AA) responses on satiety. Seventeen women (mean ± SEM, age: 33 ± 1 year; BMI: 27.8 ± 0.1 kg/m2) consumed a eucaloric, plant-based diet containing two servings of lean beef/day (i.e., 7.5 oz (207 g)) for 7 days. During day 6, the participants completed a 12 h controlled-feeding, clinical testing day including repeated satiety questionnaires and blood sampling to assess pre- and postprandial plasma AAs, PYY, and GLP-1. Regression and mediation analyses were completed to assess AA predictors and hormonal mediators. Total plasma AAs explained 41.1% of the variance in perceived daily fullness (p < 0.001), 61.0% in PYY (p < 0.001), and 66.1% in GLP-1 (p < 0.001) concentrations, respectively. Several individual AAs significantly predicted fluctuations in daily fullness, PYY, and GLP-1. In completing mediation analyses, the effect of plasma leucine on daily fullness was fully mediated by circulating PYY concentrations (indirect effect = B: 0.09 [Boot 95% CI: 0.032, 0.17]) as no leucine-fullness direct effect was observed. No other mediators were identified. Although a number of circulating AAs predict satiety, leucine was found to do so through changes in PYY concentrations in middle-aged women.
Effects of Early and Late Time-Restricted Feeding on Parameters of Metabolic Health: An Explorative Literature Assessment
Authors: Petridi Froso , Geurts Jan M. W. , Nyakayiru Jean , Schaafsma Anne , Schaafsma Dedmer , Meex Ruth C. R. , Singh-Povel Cécile M.
Published: May 2024

Chrono-nutrition (meal timing) aligns food consumption with one’s circadian rhythm. The first meal (e.g., breakfast) likely promotes synchronization of peripheral circadian clocks, thereby supporting metabolic health. Time-restricted feeding (TRF) has been shown to reduce body weight (BW) and/or improve cardiovascular biomarkers. In this explorative literature assessment, 13 TRF randomized controlled trials (RCTs) were selected from PubMed and Scopus to evaluate the effects of early (eTRF: first meal before 10:30 a.m.) and late TRF (lTRF: first meal after 11:30 a.m.) on parameters of metabolic health. Although distinct variations in study design were evident between reports, TRF consistently decreased energy intake (EI) and BW, and improved insulin resistance as well as systolic blood pressure. eTRF seemed to have a greater beneficial effect than lTRF on insulin resistance (HOMA-IR). Importantly, most studies did not appear to consider chronotype in their evaluation, which may have underestimated TRF effects. TRF intervention may be a promising approach for risk reduction of human metabolic diseases. To conclusively determine benefits of TRF and identify clear differences between eTRF and lTRF, future studies should be longer-term (≥8 weeks) with well-defined (differences in) feeding windows, include participants chronotypically matching the intervention, and compare outcomes to those of control groups without any dietary limitations.
Design of a Mobile App Interface That Engages Community Members in a Food System Pilot Study
Authors: Lewis Emma C. , Williamson Stacey , Xie Yutong , Poirier Lisa , Oladimeji Ayoyemi T. , Igusa Takeru , Gittelsohn Joel
Published: May 2024

Supermarkets are scarce in many under-resourced urban communities, and small independently owned retail stores often carry few fresh or healthy items. The Baltimore Urban food Distribution (BUD) mobile application (app) was previously developed to address supply-side challenges in moving healthy foods from local suppliers to retailers. In-app opportunities for consumers to indicate demand for these foods are crucial, but remain absent. We sought to understand community members’ perspectives on the overall role, function and features of a proposed consumer-engagement module (BUDConnect) to expand the BUD app. A series of initial high-fidelity wireframe mockups were developed based on formative research. In-depth interviews (n = 20) were conducted and thematically analyzed using ATLAS.ti Web. Participants revealed a desire for real-time crowd-sourced information to navigate their food environments safely and effectively, functionality to help build community and social networks among store owners and their customers, opportunities to share positive reviews and ratings of store quality and offerings, and interoperability with existing apps. Rewards and referral systems resulting in the discounted purchasing of promoted healthy items were suggested to increase adoption and sustained app use. Wireframe mockups were further refined for future development and integration into the BUD app, the program and policy implications of which are discussed.
The Effects of Different Durations of Night-Time Supplementary Lighting on the Growth, Yield, Quality and Economic Returns of Tomato
Authors: Yu Hongjun , Liu Peng , Xu Jingcheng , Wang Tanyu , Lu Tao , Gao Jie , Li Qiang , Jiang Weijie
Published: May 2024

To achieve higher economic returns, we employ inexpensive valley electricity for night-time supplementary lighting (NSL) of tomato plants, investigating the effects of various durations of NSL on the growth, yield, and quality of tomato. Tomato plants were treated with supplementary light for a period of 0 h, 3 h, 4 h, and 5 h during the autumn–winter season. The findings revealed superior growth and yield of tomato plants exposed to 3 h, 4 h, and 5 h of NSL compared to their untreated counterparts. Notably, providing lighting for 3 h demonstrated greater yields per plant and per trough than 5 h exposure. To investigate if a reduced duration of NSL would display similar effects on the growth and yield of tomato plants, tomato plants received supplementary light for 0 h, 1 h, 2 h, and 3 h at night during the early spring season. Compared to the control group, the stem diameter, chlorophyll content, photosynthesis rate, and yield of tomatoes significantly increased upon supplementation with lighting. Furthermore, the input–output ratios of 1 h, 2 h, and 3 h NSL were calculated as 1:10.11, 1:4.38, and 1:3.92, respectively. Nonetheless, there was no detectable difference in yield between the 1 h, 2 h, and 3 h NSL groups. These findings imply that supplemental LED lighting at night affects tomato growth in the form of light signals. Night-time supplemental lighting duration of 1 h is beneficial to plant growth and yield, and its input–output ratio is the lowest, which is an appropriate NSL mode for tomato cultivation.
Responses of Soil C, N, P and Enzyme Activities to Biological Soil Crusts in China: A Meta-Analysis
Authors: Yang Zhi , Yuan Yong , Guo Jinjin , Li Jinxi , Li Jianhua , Yu Hu , Zeng Wen , Huang Yinhong , Yin Liyun , Li Fulian
Published: May 2024

Biological soil crusts (BSCs) are often referred to as the “living skin” of arid regions worldwide. Yet, the combined impact of BSCs on soil carbon (C), nitrogen (N), phosphorus (P), and enzyme activities remains not fully understood. This study identified, screened and reviewed 71 out of 2856 literature sources to assess the responses of soil C, N, P and enzyme activity to BSCs through a meta-analysis. The results indicated that BSC presence significantly increased soil C, N, P and soil enzyme activity, and this increasing effect was significantly influenced by the types of BSCs. Results from the overall effect showed that soil organic carbon (SOC), total nitrogen (TN), available nitrogen (AN), total phosphorus (TP), and available phosphorus (AP) increased by 107.88%, 84.52%, 45.43%, 27.46%, and 54.71%, respectively, and four soil enzyme activities (Alkaline Phosphatase, Cellulase, Sucrase, and Urease) increased by 93.65–229.27%. The highest increases in SOC, TN and AN content occurred in the soil covered with lichen crusts and moss crusts, and significant increases in Alkaline Phosphatase and Cellulase were observed in the soil covered with moss crusts and mixed crusts, suggesting that moss crusts can synergistically enhance soil C and N pool and enzyme activity. Additionally, variations in soil C, N, P content, and enzyme activity were observed under different environmental settings, with more pronounced improvements seen in coarse and medium-textured soils compared to fine-textured soils, particularly at a depth of 5 cm from the soil surface. BSCs in desert ecosystems showed more significant increases in SOC, TN, AN, and Alkaline Phosphatase compared to forest and grassland ecosystems. Specifically, BSCs at low altitude (≤500 m) with an annual average rainfall of 0–400 mm and an annual average temperature ≤ 10 °C were the most conducive to improving soil C, N, and P levels. Our results highlight the role of BSCs and their type in increasing soil C, N, P and enzyme activities, with these effects significantly impacted by soil texture, ecosystem type, and climatic conditions. The implications of these findings are crucial for soil enhancement, ecosystem revitalization, windbreak, and sand stabilization efforts in the drylands of China.
Gelatin and Collagen from Sheepskin
Authors: Matinong Andrea Marie E. , Pickering Kim L. , Waterland Mark R. , Chisti Yusuf , Haverkamp Richard G.
Published: May 2024

Abattoirs dispose of sheepskins as solid waste due to low price and poor demand for sheepskin leather. In principle, as an alternative to being disposed of in landfill, sheepskins can serve as a source of the protein collagen or the hydrolysis product, gelatin. In this research, sheepskins collected from abattoirs were used as a source of collagen. Three extraction methods were compared: acid extraction, acid with enzymes, and alkali extraction. The extracted material was characterized using scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR), small angle X-ray scattering (SAXS), and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The collagen and gelatin extraction yield ranged from 3.1% to 4.8% with the product purity determined by hydroxyproline, ranging from 7.8% for the alkali process to 59% and 68% for the acid and acid-enzyme processes. SDS PAGE showed that the acid process produced fragments with molecular weights in the range 100 to >250 kDa, while acid–enzyme resulted in smaller fragments, below 30 kDa. The FTIR region of the amide I band at 1800–1550 cm−1, which was used as an indicator of the collagen and gelatin content, showed that the gelatin dominated in the acid extracts, and the alkaline extract contained a large portion of keratin. SAXS was found to be a sensitive method for showing the presence of intact collagen fibrils in materials from all of the extraction methods, albeit at low concentrations. Herein, sheepskin is shown to be a useful source for collagen–gelatin material of varying molecular weights.
Towards Reliable Prediction of Performance for Polymer Electrolyte Membrane Fuel Cells via Machine Learning-Integrated Hybrid Numerical Simulations
Authors: Kaiser Rashed , Ahn Chi-Yeong , Kim Yun-Ho , Park Jong-Chun
Published: May 2024

For mitigating global warming, polymer electrolyte membrane fuel cells have become promising, clean, and sustainable alternatives to existing energy sources. To increase the energy density and efficiency of polymer electrolyte membrane fuel cells (PEMFC), a comprehensive numerical modeling approach that can adequately predict the multiphysics and performance relative to the actual test such as an acceptable depiction of the electrochemistry, mass/species transfer, thermal management, and water generation/transportation is required. However, existing models suffer from reliability issues due to their dependency on several assumptions made for the sake of modeling simplification, as well as poor choices and approximations in material characterization and electrochemical parameters. In this regard, data-driven machine learning models could provide the missing and more appropriate parameters in conventional computational fluid dynamics models. The purpose of the present overview is to explore the state of the art in computational fluid dynamics of individual components of the modeling of PEMFC, their issues and limitations, and how they can be significantly improved by hybrid modeling techniques integrating with machine learning approaches. Furthermore, a detailed future direction of the proposed solution related to PEMFC and its impact on the transportation sector is discussed.
Combined Geophysical Methods in Extreme Environments—An Example from the Dead Sea
Authors: Lazar Michael , Cheng Linjing , Basson Uri
Published: May 2024

The application of geophysical methods in saline environments is limited in their ability to discern shallow subsurface geology and tectonics due to the high subsurface conductivity, which can play havoc with the geophysical signal. Recent changes in the hypersaline Dead Sea provided the opportunity to demonstrate the effectiveness and adequacy of the terrestrial frequency domain electromagnetic (henceforth FDEM) method in such settings. Since the International Continental Drilling Program (ICDP) 5017-3-C borehole was cored in 2011 in a water depth of ~2.1 m, the lake level has dropped by almost 15 m, exposing some 320 m of a new, salt-encrusted shore. An FDEM survey was carried out on what is now land across the borehole. The results of the survey were compared to downhole gamma ray logging data. Three lithologies were found based on gamma-ray cutoff values, and they are in agreement with changes in apparent electric conductivity. The FDEM survey supplied additional spatial information on the subsurface geology, highlighting areas of fluid flow and fracturing, which were found to be aligned with the trend of small strike-slip faults and earthquake clusters from previous studies. The FDEM method is a reliable way of discerning shallow subsurface geology, even in harsh conditions where other geophysical methods are limited.
Spatiotemporal Variability of Gross Primary Productivity in Türkiye: A Multi-Source and Multi-Method Assessment
Authors: Başakın Eyyup Ensar , Stoy Paul C. , Demirel Mehmet Cüneyd , Pham Quoc Bao
Published: May 2024

We investigated the spatiotemporal variability of remotely sensed gross primary productivity (GPP) over Türkiye based on MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2 GPP products. The differences in various GPP products were assessed using Kruskal–Wallis and Mann–Whitney U methods, and long-term trends were analyzed using Modified Mann–Kendall (MMK), innovative trend analysis (ITA), and empirical mode decomposition (EMD). Our results show that at least one GPP product significantly differs from the others over the seven geographic regions of Türkiye (χ2 values of 50.8, 21.9, 76.9, 42.6, 149, 34.5, and 168; p < 0.05), and trend analyses reveal a significant increase in GPP from all satellite-based products over the latter half of the study period. Throughout the year, the average number of months in which each dataset showed significant increases across all study regions are 6.7, 8.1, 5.9, 9.6, and 8.7 for MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2, respectively. The ITA and EMD methods provided additional insight into the MMK test in both visualizing and detecting trends due to their graphical techniques. Overall, the GPP products investigated here suggest ‘greening’ for Türkiye, consistent with the findings from global studies, but the use of different statistical approaches and satellite-based GPP estimates creates different interpretations of how these trends have emerged. Ground stations, such as eddy covariance towers, can help further improve our understanding of the carbon cycle across the diverse ecosystem of Türkiye.
CIRF: Coupled Image Reconstruction and Fusion Strategy for Deep Learning Based Multi-Modal Image Fusion
Authors: Zheng Junze , Xiao Junyan , Wang Yaowei , Zhang Xuming
Published: May 2024

Multi-modal medical image fusion (MMIF) is crucial for disease diagnosis and treatment because the images reconstructed from signals collected by different sensors can provide complementary information. In recent years, deep learning (DL) based methods have been widely used in MMIF. However, these methods often adopt a serial fusion strategy without feature decomposition, causing error accumulation and confusion of characteristics across different scales. To address these issues, we have proposed the Coupled Image Reconstruction and Fusion (CIRF) strategy. Our method parallels the image fusion and reconstruction branches which are linked by a common encoder. Firstly, CIRF uses the lightweight encoder to extract base and detail features, respectively, through the Vision Transformer (ViT) and the Convolutional Neural Network (CNN) branches, where the two branches interact to supplement information. Then, two types of features are fused separately via different blocks and finally decoded into fusion results. In the loss function, both the supervised loss from the reconstruction branch and the unsupervised loss from the fusion branch are included. As a whole, CIRF increases its expressivity by adding multi-task learning and feature decomposition. Additionally, we have also explored the impact of image masking on the network’s feature extraction ability and validated the generalization capability of the model. Through experiments on three datasets, it has been demonstrated both subjectively and objectively, that the images fused by CIRF exhibit appropriate brightness and smooth edge transition with more competitive evaluation metrics than those fused by several other traditional and DL-based methods.
Technological Features of Immersive Virtual Reality Systems for Upper Limb Stroke Rehabilitation: A Systematic Review
Authors: Diriba Kenea Chala , Gemechu Abessa Teklu , Lamba Dheeraj , Bonnechère Bruno
Published: May 2024

Stroke is the second most common cause of death worldwide, and it greatly impacts the quality of life for survivors by causing impairments in their upper limbs. Due to the difficulties in accessing rehabilitation services, immersive virtual reality (IVR) is an interesting approach to improve the availability of rehabilitation services. This systematic review evaluates the technological characteristics of IVR systems used in the rehabilitation of upper limb stroke patients. Twenty-five publications were included. Various technical aspects such as game engines, programming languages, headsets, platforms, game genres, and technical evaluation were extracted from these papers. Unity 3D and C# are the primary tools for creating IVR apps, while the Oculus Quest (Meta Platforms Technologies, Menlo Park, CA, USA) is the most often used headset. The majority of systems are created specifically for rehabilitation purposes rather than being readily available for purchase (i.e., commercial games). The analysis also highlights key areas for future research, such as game assessment, the combination of hardware and software, and the potential integration incorporation of biofeedback sensors. The study highlights the significance of technological progress in improving the effectiveness and user-friendliness of IVR. It calls for additional research to fully exploit IVR’s potential in enhancing stroke rehabilitation results.
Firefighting Water Jet Trajectory Detection from Unmanned Aerial Vehicle Imagery Using Learnable Prompt Vectors
Authors: Cheng Hengyu , Zhu Jinsong , Wang Sining , Yan Ke , Wang Haojie
Published: May 2024

This research presents an innovative methodology aimed at monitoring jet trajectory during the jetting process using imagery captured by unmanned aerial vehicles (UAVs). This approach seamlessly integrates UAV imagery with an offline learnable prompt vector module (OPVM) to enhance trajectory monitoring accuracy and stability. By leveraging a high-resolution camera mounted on a UAV, image enhancement is proposed to solve the problem of geometric and photometric distortion in jet trajectory images, and the Faster R-CNN network is deployed to detect objects within the images and precisely identify the jet trajectory within the video stream. Subsequently, the offline learnable prompt vector module is incorporated to further refine trajectory predictions, thereby improving monitoring accuracy and stability. In particular, the offline learnable prompt vector module not only learns the visual characteristics of jet trajectory but also incorporates their textual features, thus adopting a bimodal approach to trajectory analysis. Additionally, OPVM is trained offline, thereby minimizing additional memory and computational resource requirements. Experimental findings underscore the method’s remarkable precision of 95.4% and efficiency in monitoring jet trajectory, thereby laying a solid foundation for advancements in trajectory detection and tracking. This methodology holds significant potential for application in firefighting systems and industrial processes, offering a robust framework to address dynamic trajectory monitoring challenges and augment computer vision capabilities in practical scenarios.
Predicting the Potential Risk Area of the Invasive Plant Galinsoga parviflora in Tibet Using the MaxEnt Model
Authors: Wang Junwei , Zeng Zhefei , Chen Yonghao , La Qiong
Published: May 2024

The Tibetan plateau, with complex and diverse ecosystems, is an important ecological security barrier to China. However, climate change and the spread of invasive plant species have imperiled the once pristine and diverse ecosystem of the region. To prevent the further spread and control of invasive plants, it is important to delineate the potential distribution patterns of alien invasive plants at the regional scale across Tibet and understand their responses to climate change. Galinsoga parviflora Cav., a member of the family Asteraceae, is an annual herbaceous plant distributed globally as an invasive weed and possesses characteristics that make it highly invasive, such as a strong ability to proliferate and disperse. The species is also known to have an allelopathic effect. There has been no report on the spatial distribution of G. parviflora in Tibet. Using field survey data, we investigated the risk of G. parviflora invasion and its impacts on the ecological safety of Tibet. We employed the MaxEnt model using the R language and SPSS software to optimize and select model parameters and data. We acquired various environmental variables along with current and future climate change scenarios (two carbon emission scenarios, SSP126 and SSP585, for the years 2050 and 2090) to predict the geographic distribution and potential risk areas in Tibet that G. parviflora can invade. The MaxEnt model accurately predicted the distribution of G. parviflora in Tibet with an average AUC of 0.985. The most suitable environmental conditions in which G. parviflora performed the best in Tibet included a mean annual temperature of 6.2–10.0 °C and an elevation range of 2672–3744 m above sea level. Our results indicate that low precipitation during the coldest quarter of the year (mean temperature −2–3 °C) was the most important variable predicting G. parviflora distribution. The results also showed that the species was hardly found when precipitation in the coldest quarter exceeded 155 mm. The current potential invasion risk areas for G. parviflora included the river valleys of central, southeastern, and eastern Tibet. With future climate change scenarios (i.e., SSP126, SSP585), the suitable habitats for G. parviflora distribution will likely shift to northwest regions from the southeast. Particularly under the highest carbon emission scenario (i.e., SSP585), the potential risk area expands more rapidly, and the center of distribution shifts to northwest regions. These findings provide useful information about the current and future changes in G. parviflora distribution in Tibet, which is crucial for the comprehensive and proactive management and control of G. parviflora under future climate change.
Expressway Vehicle Trajectory Prediction Considering Historical Path Dependencies
Authors: Lai Shukun , Xu Hongke , Zou Fumin , Luo Yongyu , Hu Zerong , Zhong Huan
Published: May 2024

The prediction of expressway vehicle trajectories is a crucial aspect in the development of intelligent expressways. This paper proposes a novel approach, namely the W-GRU-Attention (WGA) model, which utilizes ETC transaction data to predict trajectory selection based on historical traffic paths and previous passed gantry information. In this study, we apply the concept of word embedding models to extract contextual semantics from the historical trajectories on expressways. Additionally, we introduce an average pooling technique for converting the historical vehicle trajectory into a fixed-length Historical Trajectory Vector (HTV), enabling us to capture dependency relationships within experience paths. By combining proximity gantry vectors during transit, we accurately predict the next gantry location. Finally, our proposed method is evaluated using a real-world expressway ETC dataset. It achieves an impressive accuracy rate of 96.14% in capturing the relationship between historical trajectories and adjacent gantries, surpassing other models in path prediction.
Analysis of Spatial Distribution and Spillover Effects of Fertilizer Application Intensity in Inner Mongolia, China
Authors: Da Benna , Wu Yunhua , Bao Wuyuntana
Published: May 2024

The overuse of fertilizers has caused significant environmental pollution. In this paper, we aim to improve fertilizer utilization and promote sustainable agricultural development. Based on panel data at the flag (county) level in Inner Mongolia from 2001 to 2020, we analyzed the spatial heterogeneity and correlation of fertilizer application intensity using a two-stage nested Theil index and Moran’s I, and employed a Durbin model to elucidate its spatial spillover effects. The results show that overall disparities in fertilizer application intensity showed a decreasing trend, with league (city) disparities being the main reason for the overall disparities. In terms of spatial patterns, there is a positive spatial correlation between flags (counties), with the western region exhibiting a “high-high” type that gradually shifts towards the eastern region, particularly the cities of Tongliao and Chifeng. The central and eastern regions exhibit a “low-low” type. Future endeavors to decrease fertilizer application intensity are mainly focused on establishing “high-high” clusters. Policymakers should leverage these spatial interactions to diminish fertilizer usage and mitigate environmental pollution. Farmers, affluence, agricultural economic development, and grain yield positively influence fertilizer application intensity while agricultural modernization and land size have negative effects. All these factors demonstrate significant spatial spillover effects.
Circular Economy Approach: Recycling Toner Waste in Cement-Based Construction Materials
Authors: Peralta Ring Rocio , Cordoba Gisela , Delbianco Natalia , Priano Carla , Rahhal Viviana
Published: May 2024

Based on a waste generated survey by companies in the area of the city of Bahia Blanca (Argentina), the possibility of incorporating part of them in a Portland cement matrix was examined. Among the waste is toner (TW), which is obtained from cartridges used in photocopiers, laser printers, and faxes. This paper aims to analyze the physical and mechanical properties of cement pastes and mortars using toner as a Portland cement replacement compared to a reference sample without toner. The mixes were made with 2.5, 5, 10, and 15 wt.% replacement of cement by toner, and it was measured the flow, normal consistency, setting time, calorimetry, and Frattini test in pastes and mechanical strengths in mortars employing standardized tests. Also, an analysis of the leachate in the curing water was carried out after 56 days to look for contaminating materials. The replacement of up to 5% cement with toner did not produce substantial alterations in the final setting time or mechanical properties. No heavy metals were found in the leachate, so TW can be immobilized in a cementitious matrix as it does not cause leaching above the established limits. Therefore, TW from a local industry can be used in construction materials and could contribute to a reduction of up to 14% of CO2 emissions with a cement replacement of 15% in cement-based materials.
Identification and Distribution of Antibiotic Resistance Genes and Antibiotic Resistance Bacteria in the Feces Treatment Process: A Case Study in a Dairy Farm, China
Authors: Wang Hailun , Gao Yongchao , Zheng Liwen , Ji Lei , Kong Xue , Du Jianhua , Wang Hui , Duan Luchun , Niu Tian , Liu Jianhui , Shang Ming
Published: May 2024

The overuse of antibiotics has resulted in the prevalence of antibiotic resistance genes (ARGs) and antibiotic resistance bacteria (ARB) in the environment. High-density livestock farming is one of the major industries for antibiotic overuse. In this study, we sampled wastewater and manure at different stages of the feces treatment process from a dairy farm, as well as the soil in the farmland where the treated wastewater was being used for irrigation purpose. High-throughput Illumina sequencing was used to analyze the profiles of bacteria communities and ARGs. The results showed that the main ARG types were multidrug, aminoglycoside, glycopeptide, and tetracycline resistance genes, and Actinobacteria, Proteobacteria and Firmicutes were the main host bacteria phyla of these ARGs. The genus Nocardioides sp. and Ornithinimicrobium sp. were closely associated with the ARGs in the investigated samples. The relative abundances of ARGs in wastewater and manure were reduced by 68.5% and 62.1%, respectively, by the existing feces treatment process. Anaerobic fermentation and high-temperature fermentation were the most efficient treatment steps; the relative abundances of ARGs were reduced by 29.3% and 33.6% in the treated wastewater and manure, respectively. Irrigation with the treated wastewater significantly increased the abundance and diversity of ARGs and ARB in the surface soil of the farmland. The residual ARGs were found to transit through vertical gene transfer (VGT) and horizontal gene transfer (HGT) in soil. Therefore, the direct application of this inadequately treated wastewater and/or manure could risk spreading ARGs into the environment, and potentially impact human health. In order to effectively restrain the spread of ARGs, it is necessary to modify the wastewater and manure treatment processes and improve the regulations and guidelines of applying treated wastewater for irrigation.
Electromagnetic Water Treatment and Soil Compost Incorporation to Alleviate the Impact of Soil Salinization
Authors: Suvendran Subanky , Johnson David , Acevedo Miguel , Smithers Breana , Xu Pei
Published: May 2024

This study explores the effects of alternating current-induced electromagnetic field (EMF) on mitigating brackish water irrigation and soil salinization impacts. Greenhouse experiments were conducted to evaluate the effect of EMF on plant growth, soil properties, and leaching of ions under different conditions, including using brackish water and desalinated water for irrigation and soil compost incorporation. The experiment was performed with four types of irrigation water using soil columns representing field soil layers. EMF-treated brackish water maintained a sodium adsorption ratio of 2.7 by leaching Na+ from the soil. EMF-treated irrigation columns showed an increase in soil organic carbon by 7% over no EMF-treated columns. Compost treatment reduced the leaching of NO3− from the soil by more than 15% using EMF-treated irrigation water. EMF-treated brackish water and compost treatment enhanced plant growth by increasing wet weight by 63.6%, dry weight by 71.4%, plant height by 22.8%, and root length by 115.8% over no EMF and compost columns. EMF-treated agricultural water without compost also showed growth improvements. The findings suggest that EMF treatment, especially combined with compost, offers an effective, low-cost, and eco-friendly solution to mitigate soil salinization, promoting plant growth by improving nutrient availability and soil organic carbon.
Comprehensive Review of Global Perspectives on Per- and Polyfluoroalkyl Compounds: Occurrence, Fate, and Remediation in Groundwater Systems
Authors: Benaafi Mohammed , Bafaqeer Abdullah
Published: May 2024

Groundwater contamination with per- and polyfluoroalkyl compounds (PFASs) has become a growing worldwide environmental issue. The current review comprehensively evaluates the global perspective of PFAS pollution in groundwater. Data from 224 recent research articles covering various land use and source types were reviewed, including industrial facilities, landfills, biosolids applications, and firefighting training sites. The bibliographic analysis shows an exponential increase in publications on PFAS pollution in groundwater in the last five years, with more than 50% coming from the USA, followed by Australia, Canada, China, and Sweden. The recent groundwater PFAS pollution research provides insight into the analytical techniques, absorbing materials, treatment strategies, field tests, and enhanced natural attenuation. Nevertheless, the current review identified significant research gaps in the areas of precursor characterization, subsurface behavior, model validation with field data, and long-term and sustainable solutions. Moreover, a global cross-disciplinary approach is required to reduce and regulate PFASs’ risks to humans and the ecological system. This review presents a case study of PFASs in Saudi Arabian groundwater, revealing elevated levels of PFOA and PFOS and highlighting the need for region-specific studies and remediation strategies. The review results will guide global efforts to protect drinking water supplies from life-threatening contaminants.
Saint Jérôme, la Vulgate et la hebraica veritas : du mythe aux textes
Authors: Balliu Christian
Published: May 2024

Many historians of translation have looked into the works of Saint Jerome, and more particularly into the Vulgate. They have often confined themselves to secondhand sources without studying the original texts. Countless mistakes have thus been repeated with time. The present study will analyse the myths that have been created around Saint Jerome and will dissect the faulty statements by comparing them to Latin sources.
Energy and Exergy Analysis of Heat Recovery from the Accumulating Tanks of a Central Heating System by Employing a Sample of Thermoelectric Generators
Authors: Şahmerdan Orhan , Tıkız İsmet
Published: May 2024

Heat recovery using a series of thermoelectric generator (TEG) samples improved and studied previously is investigated in this paper. For this, such TEGs are connected to the accumulating tanks (ATs) of a geothermal central heating system assisted by natural gas to recover all waste heat from those devices. The study was carried out based on energy and exergy analysis. In the energy analysis part of the study, the proposed energy conversion efficiency of the TEG sample for the temperature difference in an AT-TEG system in this current study, which is 2%, was applied to find power output and energetic efficiency. As a result, total net power production was 9.888 kW, while overall energy efficiency was 7.717%. It can be observed that this amount of net power generation is sufficient to supply 61.262% of the electrical power needed for the circulating pumps in the remaining parts of the central heating system. This research reveals that TEG application in heat recovery is a promising way forward, but there is still a need to enhance the conversion efficiency of such devices.