bluuebunny/crossref_metadata_2025 huggingface dataset:
Inflammatory Biomarkers to Predict Major Adverse Cardiovascular Events in Patients with Carotid Artery Stenosis
Authors: Li Ben , Shaikh Farah , Zamzam Abdelrahman , Abdin Rawand , Qadura Mohammad
Published: June 2024

Background and Objectives: Inflammatory proteins and their prognostic value in patients with carotid artery stenosis (CAS) have not been adequately studied. Herein, we identified CAS-specific biomarkers from a large pool of inflammatory proteins and assessed the ability of these biomarkers to predict adverse events in individuals with CAS. Materials and Methods: Samples of blood were prospectively obtained from 336 individuals (290 with CAS and 46 without CAS). Plasma concentrations of 29 inflammatory proteins were determined at recruitment, and the patients were followed for 24 months. The outcome of interest was a major adverse cardiovascular event (MACE; composite of stroke, myocardial infarction, or death). The differences in plasma protein concentrations between patients with vs. without a 2-year MACE were determined using the independent t-test or Mann–Whitney U test to identify CAS-specific prognostic biomarkers. Kaplan–Meier and Cox proportional hazards analyses with adjustment for baseline demographic and clinical characteristics were performed to assess the prognostic value of differentially expressed inflammatory proteins in predicting a 2-year MACE in patients with CAS. Results: The mean age of the cohort was 68.8 (SD 10.2) years and 39% were female. The plasma concentrations of two inflammatory proteins were significantly higher in individuals with a 2-year MACE relative to those without a 2-year MACE: IL-6 (5.07 (SD 4.66) vs. 3.36 (SD 4.04) pg/mL, p = 0.03) and CD163 (233.825 (SD 230.306) vs. 159.673 (SD 175.669) pg/mL, p = 0.033). Over a follow-up period of 2 years, individuals with elevated levels of IL-6 were more likely to develop MACE (HR 1.269 (95% CI 1.122–1.639), p = 0.042). Similarly, over a 2-year period, patients with high levels of CD163 were more likely to develop MACE (HR 1.413 (95% CI 1.022–1.954), p = 0.036). Conclusions: The plasma levels of inflammatory proteins IL-6 and CD163 are independently associated with adverse outcomes in individuals with CAS. These CAS-specific prognostic biomarkers may assist in the risk stratification of patients at an elevated risk of a MACE and subsequently guide further vascular evaluation, specialist referrals, and aggressive medical/surgical management, thereby improving outcomes for patients with CAS.
Silymarin Supplementation in Active Rheumatoid Arthritis: Outcomes of a Pilot Randomized Controlled Clinical Study
Authors: Zugravu Georgeta Stefanovici , Pintilescu Carmen , Cumpat Carmen-Marinela , Miron Sorin Dan , Miron Anca
Published: June 2024

Background and Objectives: Coadministration of natural products to enhance the potency of conventional antirheumatic treatment is of high interest. This study aimed to assess the impact of administration of silymarin (a nutritional supplement) in patients with active rheumatoid arthritis under treatment with conventional disease-modifying antirheumatic drugs. Materials and Methods: One-hundred and twenty-two patients diagnosed with active rheumatoid arthritis and treated with conventional disease-modifying antirheumatic drugs were randomly assigned to either control or intervention groups; the latter was supplemented with silymarin (300 mg/day) for 8 weeks. Indicators of disease activity, inflammatory markers, disease activity and disability indices, European League Against Rheumatism responses, fatigue, depression, and anxiety scores were determined at baseline and week 8. Results: Silymarin supplementation significantly reduced the number of tender and swollen joints, duration of morning stiffness, severity of pain, disease activity and disability indices, European League Against Rheumatism responses, levels of fatigue, depression, and anxiety. According to our results, silymarin substantially improved patients’ general condition. Conclusions: Our study provides evidence for the benefits of silymarin supplementation to disease-modifying antirheumatic drugs in patients with active rheumatoid arthritis.
Comparative Study of the Mechanical Properties and Fracture Mechanism of Ti-5111 Alloys with Three Typical Microstructures
Authors: Liu Haitao , Lu Longlong , Zhang Yanmin , Zhou Fei , Song Kexing
Published: June 2024

In this work, Ti-5111 alloys with equiaxed, bimodal and lamellar microstructures were prepared by various heat treatment processes. The room-temperature tensile properties, deformation microstructure and fracture mechanism of the alloys with different microstructures were investigated. Furthermore, the mechanism by which the microstructure affects the mechanical properties of Ti-5111 alloys with three typical microstructures was confirmed. The Ti-5111 alloy with a bimodal microstructure has minimum grain size and a large number of αs/β phase boundaries, which are the primary reasons for its higher strength. Simultaneously, the excellent coordination in the deformation ability between the lamellar αs and β phases is what enables the alloy with a bimodal microstructure to have the most outstanding mechanical properties. Additionally, the presence of a grain boundary α phase and the parallel arrangement of a coarse αs phase are the main reasons for the inferior mechanical properties of the Ti-5111 alloy with a lamellar microstructure. The fracture mechanism of the alloy with an equiaxed microstructure is a mixed fracture mechanism including ductile fracture and destructive fracture. The fracture mechanisms of the Ti-5111 alloy with bimodal and lamellar microstructures are typical ductile fracture and cleavage fracture, respectively. These findings serve as a guide for the performance improvement and application of the Ti-5111 alloy.
Impact of COVID-19 Restrictions on Incidence of Enteropathogenic Bacteria, Virus, and Parasites in Denmark: A National, Register-Based Study
Authors: Nanthan Kumanan Rune , Plantener Eva , Coia John , Engberg Jørgen , Andersen Leif Percival , Marmolin Ea , Hartmeyer Gitte Nyvang , Nielsen Hans Linde , Stensvold Christen Rune , Engsbro Anne Line , Olesen Bente , Lemming Lars , Chen Ming
Published: June 2024

Diarrheal diseases caused by enteric pathogens are a significant public health concern. It is widely considered that close contact between persons, poor hygiene, and consumption of contaminated food are the primary causes of gastroenteritis. Clinical microbiology laboratory observations indicate that the incidence of enteropathogenic microorganisms may have been reduced in Denmark during the COVID-19 pandemic. All Departments of Clinical Microbiology in Denmark provided data on the monthly incidence of Salmonella spp., Escherichia coli, Campylobacter spp., Clostridioides difficile, Norovirus GI+GII, Giardia duodenalis, and Cryptosporidium from March 2018 to February 2021. The data were divided into three periods as follows: Control Period 1 (March 2018 to February 2019); Control Period 2 (March 2019 to February 2020); and the Restriction (pandemic) Period (March 2020 to February 2021). The incidences of pathogenic Salmonella spp.-, Escherichia coli-, and Campylobacter spp.-positive samples decreased by 57.3%, 48.1%, and 32.9%, respectively, during the restriction period. No decrease in C. difficile was observed. Norovirus GI+GII-positive samples decreased by 85.6%. Giardia duodenalis-positive samples decreased by 66.2%. Cryptosporidium species decreased by 59.6%. This study demonstrates a clear decrease in the incidence of enteropathogenic bacteria (except for C. difficile), viruses, and parasites during the SARS-CoV-2 restriction period in Denmark.
Periodontal Inflammation and Dysbiosis Relate to Microbial Changes in the Gut
Authors: Kamer Angela R. , Pushalkar Smruti , Hamidi Babak , Janal Malvin N. , Tang Vera , Annam Kumar Raghava Chowdary , Palomo Leena , Gulivindala Deepthi , Glodzik Lidia , Saxena Deepak
Published: June 2024

Periodontal disease (PerioD) is a chronic inflammatory disease of dysbiotic etiology. Animal models and few human data showed a relationship between oral bacteria and gut dysbiosis. However, the effect of periodontal inflammation and subgingival dysbiosis on the gut is unknown. We hypothesized that periodontal inflammation and its associated subgingival dysbiosis contribute to gut dysbiosis even in subjects free of known gut disorders. We evaluated and compared elderly subjects with Low and High periodontal inflammation (assessed by Periodontal Inflamed Surface Area (PISA)) for stool and subgingival derived bacteria (assayed by 16S rRNA sequencing). The associations between PISA/subgingival dysbiosis and gut dysbiosis and bacteria known to produce short-chain fatty acid (SCFA) were assessed. LEfSe analysis showed that, in Low PISA, species belonging to Lactobacillus, Roseburia, and Ruminococcus taxa and Lactobacillus zeae were enriched, while species belonging to Coprococcus, Clostridiales, and Atopobium were enriched in High PISA. Regression analyses showed that PISA associated with indicators of dysbiosis in the gut mainly reduced abundance of SCFA producing bacteria (Radj = −0.38, p = 0.03). Subgingival bacterial dysbiosis also associated with reduced levels of gut SCFA producing bacteria (Radj = −0.58, p = 0.002). These results suggest that periodontal inflammation and subgingival microbiota contribute to gut bacterial changes.
The Utilization of Bacillus subtilis to Design Environmentally Friendly Living Paints with Anti-Mold Properties
Authors: Dorfan Yuval , Nahami Avichay , Morris Yael , Shohat Benny , Kolodkin-Gal Ilana
Published: June 2024

The anti-fungal properties of the probiotic bacterium Bacillus subtilis have been studied extensively in agriculture and ecology, but their applications in the built environment remain to be determined. Our work aims to utilize this biological component to introduce new diverse anti-mold properties into paint. “Mold” refers to the ubiquitous fungal species that generate visible multicellular filaments commonly found in household dust. The development of mold leads to severe health problems for occupants, including allergic response, hypersensitivity pneumonitis, and asthma, which have significant economic and clinical outcomes. We here demonstrate the robust effect of a commercial paint enhanced with Bacillus subtilis cells against the common mold agent, Aspergillus niger, and identify three biosynthetic clusters essential for this effect. Our results lay the foundation for bio-convergence and synthetic biology approaches to introduce renewable and environmentally friendly bio-anti-fungal agents into the built environment.
Synthetic Modifications of Andrographolide Targeting New Potential Anticancer Drug Candidates: A Comprehensive Overview
Authors: Messire Gatien , Rollin Patrick , Gillaizeau Isabelle , Berteina-Raboin Sabine
Published: June 2024

This review collects the synthetic modifications performed on andrographolide, a natural molecule derived from Andrographis paniculata, for oncology applications. Various pharmacomodulations were carried out, and the products were tested on different cancer cell lines. The impact of these modifications was analyzed with the aim of mapping the positions essential for activity to facilitate future research in this field. However, this study makes it clear that, in addition to structural modifications of the molecule, which can result in varying degrees of effectiveness in targeting interactions, the lipophilic capacity of the structures obtained through hemisynthesis is of significant importance.
Asymmetrically Wettable, PET/PA6, Hollow, Segmented-Pie, Microfiber Nonwovens for a Synthetic Leather Base
Authors: Zhao Baobao , Liu Chunbiao , Wang Zhen , Feng Quan , Han Xu , Zhang Jin , Hu Chenggong , Han Dongxu
Published: June 2024

PET/PA6, hollow, segmented-pie, microfiber nonwovens (PET/PA6 HSMNs) play an important role in a microfiber, synthetic leather base. Most of the current PET/PA6 HSMNs generally lack in hygiene performance. Moreover, there is an urgent need for the asymmetric wettability of PET/PA6 HSMNs to ensure the comfort of clothing. In this work, a novel, asymmetrically wettable, PET/PA6 HSMN with a gradient structure is proposed, which can regulate liquid adsorption and directional transport. An MOF-303 was successfully synthesized and loaded onto the PET/PA6 HSMN, which had been pre-treated with gradient hydrolysis under sulfuric acid. The droplet quickly permeated the modified PET/PA6 HSMN, and the droplet disappearance time decreased to 62.40 ms. The liquid strikethrough time of the modified PET/PA6 HSMN reached 5.16 s. The maximum adsorption capacity of the modified PET/PA6 HSMN was 68.161 mg/g, which was improved by 122.83%. In addition, the air permeability of the pre-treated PET/PA6 HSMN increased from 308.70 mm/s to 469.97 mm/s, with the sulfuric acid concentrations increasing from 0% to 20%, and the air permeability of the modified PET/PA6 HSMN decreased gradually from 247.37 mm/s to 161.50 mm/s. Furthermore, the tensile strength of the modified PET/PA6 HSMN treated with sulfuric acid and MOF-303 was also obviously enhanced compared with the PET/PA6 HSMN treated with pure sulfuric acid. This PET/PA6 HSMN, with asymmetric wettability, owing to its high hygiene performance and water transport capabilities, is promising and able to extend the application of a microfiber synthetic leather base for clothing.
Candle Soot as a Novel Support for Nickel Nanoparticles in the Electrocatalytic Ethanol Oxidation
Authors: Mansor Muliani , Budiman Siti Noorleila , Zainoodin Azran Mohd , Khairunnisa Mohd Paad , Yamanaka Shinya , Jusoh Nurfatehah Wahyuny Che , Liza Shahira
Published: June 2024

The enhancement of carbon-supported components is a crucial factor in augmenting the interplay between carbon-supported and metal-active components in the utilization of catalysts for direct ethanol fuel cells (DEFCs). Here, we propose a strategy for designing a catalyst by modifying candle soot (CS) and loading nickel onto ordered carbon soot. The present study aimed to investigate the effect of the Ni nanoparticles content on the electrocatalytic performance of Ni–CS, ultimately leading to the identification of a maximum composition. The presence of an excessive quantity of nickel particles leads to a decrease in the number of active sites within the material, resulting in sluggishness of the electron transfer pathway. The electrocatalyst composed of nickel and carbon support, with a nickel content of 20 wt%, has demonstrated a noteworthy current activity of 18.43 mA/cm2, which is three times that of the electrocatalyst with a higher nickel content of 25 wt%. For example, the 20 wt% Ni–CS electrocatalytic activity was found to be good, and it was approximately four times higher than that of 20 wt% Ni–CB (nickel–carbon black). Moreover, the chronoamperometry (CA) test demonstrated a reduction in current activity of merely 65.80% for a 20 wt% Ni–CS electrocatalyst, indicating electrochemical stability. In addition, this demonstrates the great potential of candle soot with Ni nanoparticles to be used as a catalyst in practical applications.
Short-Term Forecasting of Photovoltaic Power Using Multilayer Perceptron Neural Network, Convolutional Neural Network, and k-Nearest Neighbors’ Algorithms
Authors: Iheanetu Kelachukwu , Obileke KeChrist
Published: June 2024

Governments and energy providers all over the world are moving towards the use of renewable energy sources. Solar photovoltaic (PV) energy is one of the providers’ favourite options because it is comparatively cheaper, clean, available, abundant, and comparatively maintenance-free. Although the PV energy source has many benefits, its output power is dependent on continuously changing weather and environmental factors, so there is a need to forecast the PV output power. Many techniques have been employed to predict the PV output power. This work focuses on the short-term forecast horizon of PV output power. Multilayer perception (MLP), convolutional neural networks (CNN), and k-nearest neighbour (kNN) neural networks have been used singly or in a hybrid (with other algorithms) to forecast solar PV power or global solar irradiance with success. The performances of these three algorithms have been compared with other algorithms singly or in a hybrid (with other methods) but not with themselves. This study aims to compare the predictive performance of a number of neural network algorithms in solar PV energy yield forecasting under different weather conditions and showcase their robustness in making predictions in this regard. The performance of MLPNN, CNN, and kNN are compared using solar PV (hourly) data for Grahamstown, Eastern Cape, South Africa. The choice of location is part of the study parameters to provide insight into renewable energy power integration in specific areas in South Africa that may be prone to extreme weather conditions. Our data does not have lots of missing data and many data spikes. The kNN algorithm was found to have an RMSE value of 4.95%, an MAE value of 2.74% at its worst performance, an RMSE value of 1.49%, and an MAE value of 0.85% at its best performance. It outperformed the others by a good margin, and kNN could serve as a fast, easy, and accurate tool for forecasting solar PV output power. Considering the performance of the kNN algorithm across the different seasons, this study shows that kNN is a reliable and robust algorithm for forecasting solar PV output power.
Self-Assembled Nanocomposite DOX/TPOR4@CB[7]4 for Enhanced Synergistic Photodynamic Therapy and Chemotherapy in Neuroblastoma
Authors: Lu Zhouxia , Chen Xu , Wang Conghui , Luo Xuelian , Wu Xiaohan , Zhao Xing , Xiao Song
Published: June 2024

DOX/TPOR4@CB[7]4 was synthesized via self-assembly, and its physicochemical properties and ability to generate reactive oxygen species (ROS) were evaluated. The impact of photodynamic therapy on SH-SY5Y cells was assessed using the MTT assay, while flow cytometry analysis was employed to detect cell apoptosis. Confocal laser scanning microscopy was utilized to observe the intracellular distribution of DOX/TPOR4@CB[7]4 in SH-SY5Y cells. Additionally, fluorescence imaging of DOX/TPOR4@CB[7]4 in nude mice bearing SH-SY5Y tumors and examination of the combined effects of photodynamic and chemical therapies were conducted. The incorporation of CB[7] significantly enhanced the optical properties of DOX/TPOR4@CB[7]4, resulting in increased ROS production and pronounced toxicity towards SH-SY5Y cells. Moreover, both the apoptotic and mortality rates exhibited significant elevation. In vivo experiments demonstrated that tumor growth inhibition was most prominent in the DOX/TPOR4@CB[7]4 group. π–π interactions facilitated the binding between DOX and photosensitizer TPOR, with TPOR’s naphthalene hydrophilic groups encapsulated within CB[7]’s cavity through host–guest interactions with CB[7]. Therefore, CB[7] can serve as a nanocarrier to enhance the combined application of chemical therapy and photodynamic therapy, thereby significantly improving treatment efficacy against neuroblastoma tumors.
Long-Term Conservation for the Safeguard of Abies nebrodensis: An Endemic and Endangered Species of Sicily
Authors: Benelli Carla , Tarraf Waed , İzgü Tolga , Anichini Monica , Faraloni Cecilia , Salvatici Maria Cristina , Jouini Nourhene , Germanà Maria Antonietta , Danti Roberto , Lambardi Maurizio
Published: June 2024

The combined approaches between ex situ and in situ conservation are of great importance for threatened species in urgent need of protection. This study aims to develop concrete actions to preserve the relic of 30 adult trees of the Sicilian fir (Abies nebrodensis) from extinction using long-term germplasm conservation in liquid nitrogen (LN, −196 °C). Pollen grains were collected, and their moisture content (MC) was measured. Then, viability (2,3,5-tryphenyl tetrazolium chloride, TTC), in vitro germinability, and enzymatic antioxidant activity (ascorbate peroxidase, APX; catalase, CAT) were evaluated before and after cryopreservation. Seeds collected from mature cones underwent X-ray analysis, and only full seeds were used to excise the zygotic embryos (ZEs) for cryopreservation. The MC percentage of ZEs was determined, and then they were plunged in LN with (+PVS2) or without (−PVS2) Plant Vitrification Solution 2; untreated ZEs were used as a control. Viability (TTC test) and in vitro germination were assessed for all ZEs (+PVS2, −PVS2, and control). Embryogenic callus (EC) lines obtained from mature ZEs were cryopreserved applying the ‘encapsulation-dehydration’ technique. This study has allowed, after optimizing cryopreservation protocols for pollen, ZEs, and EC of A. nebrodensis, to establish the first cryobank of this endangered species in Polizzi Generosa (Palermo, Italy), inside the ‘Madonie Regional Park’. The strategy developed for Sicilian fir conservation will pave the way for similar initiatives for other critically endangered conifer species.
Study on the Inner Mechanisms of Gas Transport in Matrix for Shale Gas Recovery with In Situ Heating Technology
Authors: Li Zhongkang , Hu Zantong , Li Ying , Wu Xiaojun , Tian Junqiang , Zhou Wenjing
Published: June 2024

In order to improve the productivity of shale gas, in situ heating technology has been applied generally. However, this technology is limited by unknown properties in heated matrix, e.g., permeability. Therefore, a method for measuring the permeability of heated shale matrix particles was designed, and transport tests were conducted on the shale matrix at heating temperatures of 100~600 degrees centigrade. Through fitting the experimental data with numerical simulation results, pore structures and permeabilities at different heating temperature conditions were obtained and the corresponding transport properties were determined. The porosity and pore radius were positively correlated with the heating temperature, while the tortuosity was negatively correlated with the temperature of the heat treatment. Despite the weakening effect of Knudsen diffusion transport, slippage transport played a critical role in the transport function of the heated shale matrix, and the domination became stronger at higher heating temperatures. The study of gas transport in heated shale matrix provides a guarantee for the effective combination of in situ heating technology.
An Efficient Real-Time Vehicle Classification from a Complex Image Dataset Using eXtreme Gradient Boosting and the Multi-Objective Genetic Algorithm
Authors: Mani Pemila , Rakkiya Goundar Komarasamy Pongiannan , Rajamanickam Narayanamoorthi , Alroobaea Roobaea , Alsafyani Majed , Afandi Abdulkareem
Published: June 2024

Recent advancements in image processing and machine-learning technologies have significantly improved vehicle monitoring and identification in road transportation systems. Vehicle classification (VC) is essential for effective monitoring and identification within large datasets. Detecting and classifying vehicles from surveillance videos into various categories is a complex challenge in current information acquisition and self-processing technology. In this paper, we implement a dual-phase procedure for vehicle selection by merging eXtreme Gradient Boosting (XGBoost) and the Multi-Objective Optimization Genetic Algorithm (Mob-GA) for VC in vehicle image datasets. In the initial phase, vehicle images are aligned using XGBoost to effectively eliminate insignificant images. In the final phase, the hybrid form of XGBoost and Mob-GA provides optimal vehicle classification with a pioneering attribute-selection technique applied by a prominent classifier on 10 publicly accessible vehicle datasets. Extensive experiments on publicly available large vehicle datasets have been conducted to demonstrate and compare the proposed approach. The experimental analysis was carried out using a myRIO FPGA board and HUSKY Lens for real-time measurements, achieving a faster execution time of 0.16 ns. The investigation results show that this hybrid algorithm offers improved evaluation measures compared to using XGBoost and Mob-GA individually for vehicle classification.
Demand Management for Manufacturing Loads Considering Temperature Control under Dynamic Electricity Prices
Authors: Yang Yan , Yu Junhui , Ma Hengrui
Published: June 2024

Demand response (DR) can provide extra scheduling flexibility for power systems. Different from industrial and residential loads, the production process of manufacturing loads includes multiple production links, and complex material flow and energy flow are closely coupled, which can be seen as a typical nondeterministic polynomial-time (NP) hard problem. In addition, there is a coupling effect between the temperature-controlled loads (TCLs) and the manufacturing loads, which has often been ignored in previous research, resulting in conservative electricity consumption planning. This paper proposes an optimal demand management for the manufacturing industry. Firstly, the power consumption characteristics of manufacturing loads are analyzed in detail. A state task network (STN) is introduced to decouple the relationship between energy and material flow in each production link. Combining STN and production equipment parameters, a general MILP model is constructed to describe the whole production process of the manufacturing industry. Then, a mathematical model of the TCLs considering a comfortable human degree is established. Fully considering the electricity consumption behavior of equipment and TCLs, the model predictive control (MPC) method is adopted to generate the optimal scheduling plan. Finally, an actual seat production enterprise is used to verify the feasibility and effectiveness of the proposed demand management strategy.
Cross-Sectional Determinants of Analyst Coverage for R&D Firms
Authors: Khallaf Ashraf , Salama Feras M. , Darayseh Musa , Alotaibi Eid
Published: June 2024

Prior research document a positive association between analyst coverage and R&D. However, they do not investigate what particular attribute of R&D leads to this positive association. In this study we aim to fill the gap in the extant literature and explore the cross-sectional determinants of the association between R&D and analyst coverage. We investigate four cross-sectional determinants: reporting biases arising from expensing of R&D compared to capitalization of R&D, uncertainty associated with R&D, investors’ attention, and scale effects of R&D. We find that while reporting biases and uncertainty decrease analyst coverage for R&D firms, investors’ attention and scale effects of R&D increase analyst coverage. Furthermore, we find that the positive association between R&D and analyst coverage documented by Barth et al. is fully explained by scale effects of R&D.
A Strategy for Neighboring Pixel Collaboration in Landslide Susceptibility Prediction
Authors: Wang Xiao , Wang Di , Zhang Mengmeng , Song Xiaochuan , Xu Luting , Sun Tiegang , Li Weile , Cheng Sizhi , Dong Jianhui
Published: June 2024

Landslide susceptibility prediction usually involves the comprehensive analysis of terrain and other factors that may be distributed with spatial patterns. Without considering the spatial correlation and mutual influence between pixels, conventional prediction methods often focus only on information from individual pixels. To address this issue, the present study proposes a new strategy for neighboring pixel collaboration based on the Unified Perceptual Parsing Network (UPerNet), the Vision Transformer (ViT), and Vision Graph Neural Networks (ViG). This strategy efficiently utilizes the strengths of deep learning in feature extraction, sequence modeling, and graph data processing. By considering the information from neighboring pixels, this strategy can more accurately identify susceptible areas and reduce misidentification and omissions. The experimental results suggest that the proposed strategy can predict landslide susceptibility zoning more accurately. These predictions can identify flat areas such as rivers and distinguish between areas with high and very high landslide susceptibility. Such refined zoning outcomes are significant for landslide prevention and mitigation and can help decision-makers formulate targeted response measures.
Methodology for Identifying Optimal Pedestrian Paths in an Urban Environment: A Case Study of a School Environment in A Coruña, Spain
Authors: Fernández-Arango David , Varela-García Francisco-Alberto , Esmorís Alberto M.
Published: June 2024

Improving urban mobility, especially pedestrian mobility, is a current challenge in virtually every city worldwide. To calculate the least-cost paths and safer, more efficient routes, it is necessary to understand the geometry of streets and their various elements accurately. In this study, we propose a semi-automatic methodology to assess the capacity of urban spaces to enable adequate pedestrian mobility. We employ various data sources, but primarily point clouds obtained through a mobile laser scanner (MLS), which provide a wealth of highly detailed information about the geometry of street elements. Our method allows us to characterize preferred pedestrian-traffic zones by segmenting crosswalks, delineating sidewalks, and identifying obstacles and impediments to walking in urban routes. Subsequently, we generate different displacement cost surfaces and identify the least-cost origin–destination paths. All these factors enable a detailed pedestrian mobility analysis, yielding results on a raster with a ground sampling distance (GSD) of 10 cm/pix. The method is validated through its application in a case study analyzing pedestrian mobility around an educational center in a purely urban area of A Coruña (Galicia, Spain). The segmentation model successfully identified all pedestrian crossings in the study area without false positives. Additionally, obstacle segmentation effectively identified urban elements and parked vehicles, providing crucial information to generate precise friction surfaces reflecting real environmental conditions. Furthermore, the generation of cumulative displacement cost surfaces allowed for identifying optimal routes for pedestrian movement, considering the presence of obstacles and the availability of traversable spaces. These surfaces provided a detailed representation of pedestrian mobility, highlighting significant variations in travel times, especially in areas with high obstacle density, where differences of up to 15% were observed. These results underscore the importance of considering obstacles’ existence and location when planning pedestrian routes, which can significantly influence travel times and route selection. We consider the capability to generate accurate cumulative cost surfaces to be a significant advantage, as it enables urban planners and local authorities to make informed decisions regarding the improvement of pedestrian infrastructure.
Exploring the Dual Potential of Artificial Intelligence-Generated Content in the Esthetic Reproduction and Sustainable Innovative Design of Ming-Style Furniture
Authors: Wang Yali , Xi Yuchen , Liu Xinxiong , Gan Yan
Published: June 2024

The present research aims to explore the dual potential of artificial intelligence-generated content (AIGC) technology in the esthetic reproduction of Ming-style furniture and its innovative design while promoting sustainable practices and cultural heritage preservation. For this purpose, a combination of methodologies integrating the principles of grounded theory, empirical research, sustainable design, and design practice and evaluation techniques is employed. The results are as follows: First, the three-level coding method in grounded theory is used to construct a multi-dimensional esthetic feature library of Ming-style furniture, including 6 esthetic feature dimensions and 102 groups of esthetic elements. Second, a set of databases specifically for Ming-style furniture is developed based on the Midjourney platform. The AIGC exclusive toolkit for furniture (MFMP) contains a language package of 61 keywords and a basic formula for Ming-style furniture design. The MFMP toolkit accurately reproduces Ming-style furniture esthetics through empirical validation. Finally, combined with sustainable design principles, a new path is explored in order to utilize the MFMP toolkit for the sustainable and innovative design of new Chinese-style furniture. The research results demonstrate that AIGC enhances traditional and modern furniture design, offering tools for industry growth in a sustainable way and preserving cultural heritage.
A Critical Literature Review on Blockchain Technology Adoption in Supply Chains
Authors: Wong Simon , Yeung John Kun Woon , Lau Yui-Yip , Kawasaki Tomoya , Kwong Raymond
Published: June 2024

Inspired by the discontinuation of the blockchain platform TradeLens, co-developed by IBM and Maersk, due to the lack of the involved supply chain stakeholders’ adoption, a critical literature review on the models of supply chain stakeholders’ adoption of blockchain applications was conducted. This review is significant as it provides insights into the exploration of a more universal approach to investigate which factors really influence blockchain adoption, which is a pre-requisite for the technical sustainability of blockchain technology in supply chains. As observed in the review, the technology acceptance model (TAM), the technology–organization–environment (TOE) framework, and the unified theory of acceptance and use of technology (UTAUT) are frequently used in the literature, but little attention has been paid to whether blockchain technology fits the users’ tasks in understanding blockchain adoption in the supply chain. Among the technology adoption theories, task–technology fit (TTF) considers whether a technology fits the tasks, but only two previous studies involved the use of TTF. This study discusses the suitability of these existing models of technology adoption for blockchain applications in supply chains and comes up with a new unified model, namely TOE-TTF-UTAUT. This review also has implications for a more appropriate conceptual research design using mixed methods.
Update of the Interpretive Conceptual Model of Ladeira de Envendos Hyposaline Hydromineral System (Central Portugal): A Contribution to Its Sustainable Use
Authors: Marques José M. , Carreira Paula M. , Caçador Pedro , Antunes da Silva Manuel
Published: June 2024

The aim of this paper is to describe the surveys performed in order to update the interpretive conceptual circulation model of the Ladeira de Envendos hyposaline hydromineral system (Central Portugal). The geology of the Ladeira de Envendos region is strongly controlled by the Amêndoa-Carvoeiro synform, of Ordovician-Silurian age, presenting continuous and aligned quartzite ridges on the NE flank, that form the basic structure of a set of inselbergs. The physico-chemical analysis of the Ladeira de Envendos natural mineral spring and borehole waters was provided by the Super Bock Group Enterprise (Concessionaire of the Ladeira de Envendos). Furthermore, two sampling campaigns took place to increase knowledge on the isotopic composition of the studied natural mineral waters. The stable (δ2H, δ18O) isotopic data indicate that local meteoric waters infiltrate around 400 m altitude and evolve to the natural mineral waters (of Cl-Na facies) through a NW–SE underground flow path ascribed to the highly fractured and permeable quartzite rocks. From recharge to discharge, the infiltrated meteoric waters acquire silica (±9 mg/L) due to water–quartzite rock interaction. These natural mineral waters emerge at temperatures around 21 °C, being the up flow of these waters controlled by the rock fractures and local faults. The natural mineral waters mean residence time range between 25 and 40 years, as indicated by the 3H content of these waters, enhancing an active recharge of this hydromineral system. The results obtained indicate existence of three hydrogeological subsystems, ascribed to three inselbergs, with similar groundwater circulation paths. These multi and interdisciplinary studies should be seen as an important contribution to the sustainable management of this type of natural mineral water resources.
Thermodynamics and Decay of de Sitter Vacuum
Authors: Volovik Grigory E.
Published: June 2024

We discuss the consequences of the unique symmetry of de Sitter spacetime. This symmetry leads to the specific thermodynamic properties of the de Sitter vacuum, which produces a thermal bath for matter. de Sitter spacetime is invariant under the modified translations, r→r−eHta, where H is the Hubble parameter. For H→0, this symmetry corresponds to the conventional invariance of Minkowski spacetime under translations r→r−a. Due to this symmetry, all the comoving observers at any point of the de Sitter space perceive the de Sitter environment as the thermal bath with temperature T=H/π, which is twice as large as the Gibbons–Hawking temperature of the cosmological horizon. This temperature does not violate de Sitter symmetry and, thus, does not require the preferred reference frame, as distinct from the thermal state of matter, which violates de Sitter symmetry. This leads to the heat exchange between gravity and matter and to the instability of the de Sitter state towards the creation of matter, its further heating, and finally the decay of the de Sitter state. The temperature T=H/π determines different processes in the de Sitter environment that are not possible in the Minkowski vacuum, such as the process of ionization of an atom in the de Sitter environment. This temperature also determines the local entropy of the de Sitter vacuum state, and this allows us to calculate the total entropy of the volume inside the cosmological horizon. The result reproduces the Gibbons–Hawking area law, which is attributed to the cosmological horizon, Shor=4πKA, where K=1/(16πG). This supports the holographic properties of the cosmological event horizon. We extend the consideration of the local thermodynamics of the de Sitter state using the f(R) gravity. In this thermodynamics, the Ricci scalar curvature R and the effective gravitational coupling K are thermodynamically conjugate variables. The holographic connection between the bulk entropy of the Hubble volume and the surface entropy of the cosmological horizon remains the same but with the gravitational coupling K=df/dR. Such a connection takes place only in the 3+1 spacetime, where there is a special symmetry due to which the variables K and R have the same dimensionality. We also consider the lessons from de Sitter symmetry for the thermodynamics of black and white holes.
Strategies for Humanitarian Logistics and Supply Chain in Organizational Contexts: Pre- and Post-Disaster Management Perspectives
Authors: Aghsami Amir , Sharififar Simintaj , Markazi Moghaddam Nader , Hazrati Ebrahim , Jolai Fariborz , Yazdani Reza
Published: June 2024

Every organization typically comprises various internal components, including regional branches, operations centers/field offices, major transportation hubs, and operational units, among others, housing a population susceptible to disaster impacts. Moreover, organizations often possess resources such as staff, various vehicles, and medical facilities, which can mitigate human casualties and address needs across affected areas. However, despite the importance of managing disasters within organizational networks, there remains a research gap in the development of mathematical models for such scenarios, specifically incorporating operations centers/field offices and external stakeholders as relief centers. Addressing this gap, this study examines an optimization model for both before and after disaster planning in a humanitarian supply chain and logistical framework within an organization. The affected areas are defined as regional branches, operational units, major transportation hubs, operations centers/field offices, external stakeholders, and medical facilities. A mixed-integer nonlinear model is formulated to minimize overall costs, considering factors such as penalty costs for untreated injuries and demand, delays in rescue and relief item distribution operations, and waiting costs for the injured in emergency medical vehicles and air ambulances. The model is implemented using GAMS software 47.1.0 for various test problems across different scales, with the Grasshopper Optimization Algorithm proposed for larger-scale scenarios. Numerical examples are provided to show the effectiveness and feasibility of the proposed model and to validate the metaheuristic approach. Sensitivity analysis is conducted to assess the model’s performance under different conditions, and key managerial insights and implications are discussed.
Association between Volatile Organic Compound Exposure and Sex Hormones in Adolescents: The Mediating Role of Serum Albumin
Authors: Lian Xinyao , Guo Jianhui , Wang Yaqi , Wang Shaoguan , Li Jing
Published: June 2024

The associations between VOCs and sex hormones in adolescents remain unclear, and the role of serum albumin in these associations deserves to be explored. We conducted cross-sectional analyses using generalized linear models (GLMs), weighted quantile sum (WQS) regression, and mediation analysis, based on data from 584 adolescents from the National Health and Nutrition Examination Survey (NHANES). The GLM analyses revealed that seven kinds of mVOCs potentially affected sex hormone levels. According to the WQS regression results, 2-aminothiazoline-4-carboxylic acid (ATCA) was the major contributor to the significant associations of mixed mVOC exposure with testosterone, estradiol, and free androgen index in males; N-acetyl-S-(N-methylcarbamoyl)-L-cysteine (AMCC) was the major contributor to the significant associations of mixed mVOC exposure with sex hormone-binding globulin in males; and N-acetyl-S-(benzyl)-L-cysteine (BMA) was the major contributor to the significant associations of mixed mVOC exposure with the ratio of testosterone to estradiol in females. Moreover, serum albumin could mediate up to 9.2% of the associations between mixed exposure to mVOCs and sex hormones. Our findings could provide a reference for studies on the mechanisms underlying the effects of VOCs on sex hormones in adolescents and emphasize the necessity of reducing exposure to ATCA, AMCC, BMA, and their parent compounds.
Association between KSHV-Specific Humoral and T Cell Responses with Recurrence of HIV-Associated Kaposi Sarcoma
Authors: Mukasine Marie-Claire , Mulundu Gina , Kawimbe Musonda , Mutale Keagan , Mumba Chibamba , Lidenge Salum J. , Ngalamika Owen
Published: June 2024

Kaposi sarcoma (KS) is an AIDS-defining angio-proliferative malignancy, with the Kaposi sarcoma-associated herpes virus (KSHV) as its etiologic agent. Upon treatment with chemotherapy, a proportion of HIV-associated KS patients experience disease recurrence within a few months of completing treatment. We aimed at determining whether KSHV-specific adaptive immune responses were associated with KS recurrence upon complete remission. We conducted a prospective cohort study. The primary outcome was the recurrence of HIV-associated KS. An immunofluorescence assay was used to determine anti-KSHV antibodies, an enzyme-linked immunospot was conducted for T cell responses, PCR was carried out to determine KSHV status, and flow cytometry was used for CD4 counting and immunophenotyping. KSHV detection in PBMCs was high and not associated with KS recurrence-free survival (p = 0.29). Anti-KSHV antibody titers were high and not associated with recurrence-free survival (p = 0.63). KSHV-specific T cell responses dropped from baseline levels among individuals with recurrence, but the drop was not statistically significant. Individuals experiencing KS recurrence had a significantly higher proportion of T cell subsets expressing PD1, while those with sustained remission had a significant increase in CD4 T cell counts from baseline levels during the follow-up period (p = 0.02). Anti-KSHV antibodies are not a good correlate of protection from KS recurrence. T cells in individuals experiencing KS recurrence hadhigh PD1 expression, while an increase in CD4 counts was associated with sustained KS remission.
On Dark Matter and Dark Energy in CCC+TL Cosmology
Authors: Gupta Rajendra P.
Published: June 2024

Relaxing the temporal constancy constraint on coupling constants in an expanding universe results in Friedmann equations containing terms that may be interpreted as dark energy and dark matter. When tired light (TL) was considered to complement the redshift due to the expanding universe, the resulting covarying coupling constants (CCC+TL) model not only fit the Type Ia supernovae data as precisely as the ΛCDM model, but also resolved concerns about the angular size of cosmic dawn galaxies observed by the James Webb Space Telescope. The model was recently shown to be compliant with the baryon acoustic oscillation features in the galaxy distribution and the cosmic microwave background (CMB). This paper demonstrates that dark energy and dark matter of the standard ΛCDM model are not arbitrary but can be derived from the CCC approach based on Dirac’s 1937 hypothesis. The energy densities associated with dark matter and dark energy turn out to be about the same in the ΛCDM and the CCC+TL models. However, the critical density in the new model can only account for the baryonic matter in the universe, raising concerns about how to account for observations requiring dark matter. We therefore analyze some key parameters of structure formation and show how they are affected in the absence of dark matter in the CCC+TL scenario. It requires reconsidering alternatives to dark matter to explain observations on gravitationally bound structures. Incidentally, since the CCC models inherently have no dark energy, it has no coincidence problem. The model’s consistency with the CMB power spectrum, BBN element abundances, and other critical observations is yet to be established.
Embracing Urban Micromobility: A Comparative Study of E-Scooter Adoption in Washington, D.C., Miami, and Los Angeles
Authors: Jafarzadehfadaki Mostafa , Sisiopiku Virginia P.
Published: June 2024

E-scooters have emerged as a popular micromobility option for short trips, with many cities embracing shared e-scooters to enhance convenience for travelers and reduce reliance on automobiles. Despite their rising popularity, there is a lack of clear understanding of how user preferences and adoption practices vary by location. This study aims to explore user and non-user attitudes towards e-scooter use in diverse urban settings. A meta-analysis of data from three surveys (N = 1197) conducted in Washington, D.C., Miami, FL, and Los Angeles, CA, was performed to compare e-scooter users and non-user profiles, mode choice factors, and attitudes and preferences towards e-scooter use. Additionally, machine learning (ML) and SHAP (SHapley Additive exPlanations) analysis were utilized to identify influential factors in predicting e-scooter use in each city. The results reveal that the majority of e-scooter users are 25 to 39 of age, male, with higher income and a bachelor’s degree, and 92% possess a driver’s license. Significant differences in attitudes between e-scooter users and non-users highlight the complexity of perceptions towards e-scooter usage. The ML model indicates that employment status negatively impacts the prediction of e-scooter users, while factors such as living without a car and using non-motorized modes positively influence e-scooter use. Educational background is a significant e-scooter mode choice factor in Washington, D.C. and Miami, whereas attitudinal questions on car and technology usage are influential in Los Angeles. These findings provide valuable insights into the factors shaping e-scooter adoption, informing urban transportation planning and policymaking and enhancing understanding of shared micromobility and its impact on urban mobility.
Correction: Liu et al. Cholesterol 25-Hydroxylase Suppresses Swine Acute Diarrhea Syndrome Coronavirus Infection by Blocking Spike Protein-Mediated Membrane Fusion. Viruses 2023, 15, 2406
Authors: Liu Dakai , Shi Da , Shi Hongyan , Zhang Liaoyuan , Zhang Jiyu , Zeng Miaomiao , Feng Tingshuai , Yang Xiaoman , Zhang Xin , Chen Jianfei , Jing Zhaoyang , Ji Zhaoyang , Zhang Jialin , Feng Li
Published: June 2024

In the original publication [...]