bluuebunny/crossref_metadata_2025 huggingface dataset:
Surface Functionalization of CaCO3 Whiskers for Improved Asphalt Binder Compatibility: From Microscale Characterization to Molecular Dynamics
Authors: Xing Xiangyang , Wang Jiyang , Zhou Qingyue , Zhang Jiupeng , Sun Guoqing , Guo Shiru , Wen Yong
Published: November 2024

CaCO3 whiskers, as a micron-level inorganic fiber material, can enhance and toughen composite materials. In order to study the technical feasibility of CaCO3 whisker-modified asphalt, two types of silane coupling agent (SCA), KH-550 and KH-570, were applied to treat the surface of CaCO3 whiskers, and the treatment effects of the original and treated whiskers were characterized by scanning electron microscopy (SEM), energy-dispersive spectrometer (EDS) and contact angle test. Meanwhile, models of CaCO3 whiskers, SCA, and asphalt molecules were established by Material Studio (MS, 2020 version) software, and the adhesion mechanism between the CaCO3 whiskers-and-asphalt interface was predicted. The results of microscopic characterization experiments indicate that the surface of the whiskers treated with SCA became rougher. Compared with the original whiskers, the contact angle between the treated whisker surface and water increased from 50° to 92.2° and 103.4°, and the surface of whiskers changed from hydrophilic to hydrophobic. The results of molecular dynamics simulation analysis show that the adhesion performance between the CaCO3 whisker surface and asphalt increased from 100.1 mJ/m2 to 112.5 mJ/m2 and 126.6 mJ/m2 after modification with SCA, and the increase in adhesion energy of KH550 is greater than that of KH570. The above research results indicate that the micro-characterization results were consistent with the molecular dynamics simulation results; that is, after treatment with SCA, the adhesion energy between the whiskers and asphalt was increased to varying degrees. The research method in this article combines micro-characterization with molecular dynamics simulation, which has a certain degree of innovation.
Content-Based Image Retrieval and Image Classification System for Early Prediction of Bladder Cancer
Authors: Yildirim Muhammed
Published: November 2024

Background/Objectives: Bladder cancer is a type of cancer that begins in the cells lining the inner surface of the bladder. Although it usually begins in the bladder, it can spread to surrounding tissues, lymph nodes, and other organs in later stages. Early detection of bladder cancer is, therefore, of great importance. Methods: Therefore, this study developed two systems based on classification and Content-Based Image Retrieval (CBIR). The primary purpose of CBIR systems is to compare the visual similarities of a user-provided image with the images in the database and return the most similar ones. CBIR systems offer an effective search and retrieval mechanism by directly using the content of the image data. Results: In the proposed CBIR system, five different CNNs, two different textural-based feature extraction methods, and seven different similarity measurement metrics were tested for feature selection and similarity measurement. Successful feature extraction methods and similarity measurement metrics formed the infrastructure of the developed system. Densenet201 was preferred for feature extraction in the developed system. The cosine metric was used in the proposed CBIR system as a similarity measurement metric, the most successful among seven different metrics. Conclusions: As a result, it was seen that the proposed CBIR model showed the highest success using the Densenet201 model for feature extraction and the Cosine similarity measurement method.
Reconstructive Surgery in the Elderly: A Case Report on Maintaining the Quality of Life in a Patient with Vulvar Dermatofibrosarcoma Protuberans
Authors: Jozwik Marcin , Bednarczuk Katarzyna , Osierda Zofia , Jozwik Maciej
Published: November 2024

Background: Dermatofibrosarcoma protuberans (DFSP) is a rare proliferative condition representing skin sarcomas known to locally recur yet very rarely known to metastasize. A typical characteristic is trunk localization, making vulvar occurrences an exception. Complete resection is the primary treatment. Case Report: We present an unusual case of twice-recurrent vulvar DFSP in a 92-year-old woman. Wide local excision with tumor-negative margins (R0 resection) of a grapefruit-sized mass was followed by a rhomboid skin flap transplantation to address a substantial skin deficit at the post excision site. At 14-month follow-up, no signs of recurrence were present, all wounds were healed, and the esthetic results were assessed as highly adequate. Conclusions: This study is an argument for the role of reconstructive surgery in patients of advanced age undergoing oncological procedures; skin transplantations should be considered regardless of the patient’s age. We also provide an updated review on vulvar DFSP.
Fast Proxy Centers for the Jeffreys Centroid: The Jeffreys–Fisher–Rao Center and the Gauss–Bregman Inductive Center
Authors: Nielsen Frank
Published: November 2024

The symmetric Kullback–Leibler centroid, also called the Jeffreys centroid, of a set of mutually absolutely continuous probability distributions on a measure space provides a notion of centrality which has proven useful in many tasks, including information retrieval, information fusion, and clustering. However, the Jeffreys centroid is not available in closed form for sets of categorical or multivariate normal distributions, two widely used statistical models, and thus needs to be approximated numerically in practice. In this paper, we first propose the new Jeffreys–Fisher–Rao center defined as the Fisher–Rao midpoint of the sided Kullback–Leibler centroids as a plug-in replacement of the Jeffreys centroid. This Jeffreys–Fisher–Rao center admits a generic formula for uni-parameter exponential family distributions and a closed-form formula for categorical and multivariate normal distributions; it matches exactly the Jeffreys centroid for same-mean normal distributions and is experimentally observed in practice to be close to the Jeffreys centroid. Second, we define a new type of inductive center generalizing the principle of the Gauss arithmetic–geometric double sequence mean for pairs of densities of any given exponential family. This new Gauss–Bregman center is shown experimentally to approximate very well the Jeffreys centroid and is suggested to be used as a replacement for the Jeffreys centroid when the Jeffreys–Fisher–Rao center is not available in closed form. Furthermore, this inductive center always converges and matches the Jeffreys centroid for sets of same-mean normal distributions. We report on our experiments, which first demonstrate how well the closed-form formula of the Jeffreys–Fisher–Rao center for categorical distributions approximates the costly numerical Jeffreys centroid, which relies on the Lambert W function, and second show the fast convergence of the Gauss–Bregman double sequences, which can approximate closely the Jeffreys centroid when truncated to a first few iterations. Finally, we conclude this work by reinterpreting these fast proxy Jeffreys–Fisher–Rao and Gauss–Bregman centers of Jeffreys centroids under the lens of dually flat spaces in information geometry.
Progressive Transmission Line Image Transmission and Recovery Algorithm Based on Hybrid Attention and Feature Fusion for Signal-Free Regions of Transmission Lines
Authors: Ji Xiu , Yang Xiao , Yue Zheyu , Yang Hongliu , Guo Haiyang
Published: November 2024

In this paper, a progressive image transmission and recovery algorithm based on hybrid attention mechanism and feature fusion is proposed, aiming to solve the challenge of monitoring the signal-less region of transmission lines. The method combines wavelet transform, Swin Transformer, and hybrid attention module with the Pixel Shuffle upsampling mechanism to achieve a balance between quality and efficiency of image transmission in a low bandwidth environment. Initial preview is achieved by prioritizing the transmission of low-frequency subbands through wavelet transform, followed by dynamic optimization of the weight allocation of key features using a hybrid attention and local window multi-scale self-attention mechanism, and further enhancement of the resolution of the decoded image through Pixel Shuffle upsampling. Experimental results show that the algorithm significantly outperforms existing methods in terms of image quality (PSNR, SSIM), transmission efficiency, and bandwidth utilization, proving its superior adaptability and effectiveness in surveillance scenarios in signal-free regions.
Simple and Effective Control System for Active AC Ripple Filtering Circuits
Authors: Sharma Roshan , Karimi-Ghartemani Masoud , Iqbal Umar
Published: November 2024

In systems where dc and ac subsystems are interacting, dc capacitors are used to balance (filter or decouple) the ac power pulsations. The required capacitance often poses a limitation in terms of physical footprint, cost, and/or reliability. Active ripple filtering circuits are widely studied in the literature for reducing the size of the capacitor needed by using power electronic switches, passive circuit components, and a control system. The passive circuit components include a substantially smaller dc capacitor at a reasonably higher or lower voltage, and an inductor for filtering the switching ripples. The control systems presented in the literature for such systems are complex and need multiple sensors and are hardly plug-and-play and universal. This paper proposes a simple yet effective control system which uses only one voltage sensor. The circuit accurately emulates a large capacitor within a wide frequency bandwidth in a plug-and-play manner. The paper explains the details of the proposed control system and presents simulation and experimental results to illustrate its properties.
A Multiscale Adaptive Fusion Network for Modular Multilevel Converter Fault Diagnosis
Authors: Ke Longzhang , Hu Guozhen , Liu Zhi , Yang Yuqing , Cheng Qianju , Zhang Peng
Published: November 2024

Modular Multilevel Converters (MMCs) play a crucial role in new energy grid connection and renewable energy conversion systems due to the significant merits of good modularity, flexible scalability, and lower operating loss. However, reliability is a significant challenge for MMCs, which consist of a large number of Insulated Gate Bipolar Transistors (IGBTs). Failures of the IGBTs in submodules (SMs) are a critical issue that affect the performance and operation of MMCs. The insufficient ability of convolutional neural networks to learn key fault features affects the accuracy of MMC fault diagnosis. To resolve this issue, this paper proposes a novel deep fault diagnosis framework named the Multiscale Adaptive Fusion Network (MSAFN) for MMC fault diagnosis. In the proposed MSAFN, the fault features of the raw current in an MMC are extracted by employing multiscale convolutional neural networks (CNNs) firstly, and then a channel attention mechanism is added to adaptively select the channel containing key features, so as to improve the fault diagnosis ability of the MMC in a noisy environment. Finally, the adaptive size of a one-dimensional CNN is adopted to adjust the weight of the feature channels of different scales, which are adaptively fused for fault diagnosis. Experimental validation is performed on two different MMC datasets. Experimental results confirm that the introduction of an attention mechanism of the multiscale feature adaptive fusion channel improves the recognition accuracy of the model by an average of 15.6%. Moreover, comparative experiments under different signal-to-noise ratios (SNRs) demonstrate that the MSAFN maintains accuracy levels above 96.7%, highlighting its excellent performance, particularly under noisy conditions.
Dynamic Anomaly Detection in the Chinese Energy Market During Financial Turbulence Using Ratio Mutual Information and Crude Oil Price Movements
Authors: Xiao Lin , Sioofy Khoojine Arash
Published: November 2024

Investigating the stability of and fluctuations in the energy market has long been of interest to researchers and financial market participants. This study aimed to analyze the Chinese energy market, focusing on its volatility and response to financial tensions. For this purpose, data from eight major financial companies, which were selected based on their market share in Shanghai’s and Shenzhen’s financial markets, were collected from January 2014 to December 2023. In this study, stock prices and trading volumes were used as the key variables to build bootstrap-based minimum spanning trees (BMSTs) using ratio mutual information (RMI). Then, using the sliding window procedure, the major network characteristics were derived to create an anomaly-detection tool using the multivariate exponentially weighted moving average (MEWMA), along with the Brent crude oil price index as a benchmark and a global oil price indicator. This framework’s stability was evaluated through stress testing with five scenarios designed for this purpose. The results demonstrate that during periods of high oil price volatility, such as during the turbulence in the stock market in 2015 and the COVID-19 pandemic in 2020, the network topologies became more centralized, which shows that the market’s instability increased. This framework successfully identifies anomalies and proves to be a valuable tool for market players and policymakers in evaluating companies that are active in the energy sector and predicting possible instabilities, which could be useful in monitoring financial markets and improving decision-making processes in the energy sector. In addition, the integration of other macroeconomic factors into this field could strengthen the identification of anomalies and be considered a field for possible research.
Developing China’s Electricity Financial Market: Strategic Design of Financial Derivatives for Risk Management and Market Stability
Authors: Feng Hao , Zhang Yidi , Lan Zhou , Wang Kun , Wang Yizheng , Chen Sheng , Feng Changsen
Published: November 2024

As China progresses with its electricity market reforms in pursuit of “carbon peak and carbon neutrality” objectives, the increasing integration of renewable energy sources introduces new risks and uncertainties, necessitating the development of an efficient electricity financial market. This paper outlines the fundamental principles of electricity financial derivatives, assesses their applicability to the Chinese market through an analysis of international experiences from the United States, Nordic countries, and Australia, and highlights critical issues for the construction of a robust market framework. It offers strategic recommendations regarding the structural and developmental aspects of China’s electricity financial market and proposes derivative instruments tailored to China’s market to improve liquidity and risk management mechanisms, thereby facilitating the renewable energy transition. The study demonstrates that these derivatives are instrumental in mitigating price volatility, managing transmission congestion, and supporting the shift to renewable energy. This provides a pragmatic approach for the reform and advancement of China’s electricity financial market, aligning with global strategies and addressing the unique challenges of China’s energy transition.
Mechanical Properties and Microstructural Investigation of AA2024-T6 Reinforced with Al2O3 and SiC Metal Matrix Composites
Authors: Channar Hassan Raza , Ullah Barkat , Naseem Muhammad Shoaib , Akhter Javed , Mehmood Arshad , Aamir Muhammad
Published: November 2024

Aluminium metal matrix composites (AMMCs) using alumina (Al2O3) and silicon carbide (SiC) as reinforcement elements are gaining significant interest in various applications because of their excellent properties. In this study, Al2O3/SiC with compositions (0.5 wt.%, 1.5 wt.%, and 2.5 wt.% for each) were used as reinforcement elements in an aluminium alloy (AA2024-T6). The samples prepared were AA2024-T6 + (0.5Al2O3/0.5SiC), AA2024-T6 + (1.5Al2O3/1.5SiC), and AA2024-T6 + (2.5Al2O3/2.5SiC) using a stir-casting technique. The experimental study included density calculation mechanical properties, such as tensile strength, compressive strength and hardness. The study also included a microstructure examination of the fracture surface of the tensile specimens. The results showed that incorporating Al2O3/SiC as reinforcement materials into aluminium AA2024-T6 significantly improved its properties. Hence, increasing the reinforcement with compositions of 2.5Al2O3/2.5SiC into AA2024-T6 showed a drop in density and increased mechanical properties, such as ultimate tensile strength, compressive strength and hardness, compared to the base alloy (AA2024-T6). Furthermore, the scanning electron microscopy analysis revealed the uniform distribution of the reinforcement particles resulting in strong bonding with the matrix. The findings suggest that Al2O3/SiC reinforced with AA2024-T6 can be used in applications where a combination of lightweight and high strength is needed.
Environmental Sustainability Based on Zirconium Dioxide Utilization in Non-Conventional Energy Applications
Authors: Matei Ecaterina , Șăulean Anca-Andreea , Petriceanu Mirela , Râpă Maria , Piticescu Radu Robert , Ștefănoiu Radu , Predescu Cristian
Published: November 2024

The increasing demand for sustainable energy solutions has prompted a significant interest in non-conventional energy sources, leading to the development of innovative materials that can enhance energy conversion and storage efficiency. This review paper explores the pivotal role of zirconium dioxide (ZrO2) in industrial applications related to non-conventional energy technologies, highlighting its contributions to the circular economy. We discuss various synthesis methods for ZrO2, including top-down and bottom-up approaches, elucidating how these techniques influence the material’s properties and applicability. Furthermore, we examine the unique characteristics of nano-ZrO2 and its transformative potential in energy conversion and storage systems. By synthesizing current research findings, this review underscores the significance of ZrO2 in promoting sustainable energy practices and its role in advancing the circular economy through material reuse and recycling strategies. The insights provided herein aim to inform future research directions and industrial applications, ultimately fostering a more sustainable energy landscape.
Trends of Ocean Underwater Acoustic Levels Recorded Before, During, and After the 2020 COVID Crisis
Authors: Prieto González Rocío , Affatati Alice , van der Schaar Mike , André Michel
Published: November 2024

Since the Industrial Revolution, underwater soundscapes have become more complex and contaminated due to increased cumulative human activities. Anthropogenic underwater sources have been growing in number, and shipping noise has become the primary source of chronic acoustic exposure. However, global data on current and historic noise levels is lacking. Here, using the Listening to the Deep-Ocean Environment network, we investigated the baseline shipping noise levels in thirteen observatories (eight stations from ONC Canada, four from the JAMSTEC network, and OBSEA in the Mediterranean Sea) and, in five of them, animal presence. Our main results show yearly noise variability in the studied locations that is not dominated by marine traffic but by natural and biological patterns. The halt in transportation due to COVID was insignificant when the data were recorded far from shipping routes. In order to better design a legislative framework for mitigating noise impacts, we highlight the importance of using tools that allow for long-term acoustic monitoring, automated detection of sounds, and big data handling and management.
Multi-Criteria Filtration and Extraction Strategy for Understory Elevation Control Points Using ICESat-2 ATL08 Product
Authors: Huang Jiapeng , Wang Yunqiu , Yu Yang
Published: November 2024

Understory terrain plays a multi-faceted role in ecosystems, biodiversity, and productivity in forests by influencing different major factors, such as hydrological processes, soils, climate, and light conditions. Strong illuminants (e.g., sunlight) from ground surfaces and atmosphere can introduce additional photons into the ATLAS system. These photons can, consequently, be mistakenly identified as laser photons reflected from ground surfaces. The presence of such ambient light, particularly under low-photon-count conditions, can significantly increase elevation measurement errors. In this context, this study aims to propose a method for extracting reliable understory elevation control points under varying forest conditions, based on the parameter attributes of ICESat-2/ATLAS data. The overall filtered data resulted in a coefficient of determination (R2), root mean square error (RMSE), and standard deviation (STD) of 0.99, 2.77 m, and 2.42 m, respectively. The greatest accuracy improvement was found in the Puerto Rico study area, showing decreases in the RMSE and STD values by 2.68 and 2.67 m, respectively. On the other hand, canopy heights and slopes exhibited relatively large impacts on noise interferences. In addition, there were decreases in the RMSE and STD values by 4.57 and 4.64 m, respectively, under the very tall canopy category, whereas under steep slope conditions, the RMSE and STD values of the filtering results decreased by 4.59 and 4.34 m, respectively. The proposed method can enhance the overall accuracy of elevation data, allowing for the significant extraction of understory elevation control points, ultimately optimizing forest management practices and improving ecological assessments.
The Response of Vegetation Dynamics to Climate in Xinjiang from 1991 to 2018
Authors: Liu Yiwen , Zhao Yanni , Wu Wentong , Ao Xinmao , Chen Rensheng
Published: November 2024

Vegetation change is one of the most prominent features of terrestrial ecosystems responding to climate change. Further exploration of vegetation characteristics in this context is essential for accurately understanding and predicting ecosystem processes. Xinjiang, an arid region, is highly sensitive to slight climate changes, which can significantly affect vegetation dynamics. Therefore, determining the relationship between climate and vegetation is of paramount importance. Based on this, this study focused on Xinjiang, selecting remote sensing data (including NDVI, LAI, and GPP) as evaluating indices, and the spatiotemporal characteristics of vegetation response to climate from 1991 to 2018 were analyzed using synchronized meteorological data, examining the relationship between vegetation and climate. The results indicated that NDVI, LAI, and GPP all increased during the period, with slopes of 0.52, 0.14 m2/m2, and 1.19 g C m−2 yr−1, showing significant spatial heterogeneity in distribution. The net vegetation area increased by more than 20,000 km2, with cropland experiencing the largest increase. Vegetation in northern Xinjiang showed a more significant positive response to increased precipitation and temperature, while vegetation in southern Xinjiang responded more complexly and exhibited negative correlations with climatic factors. The results emphasized the varied responses of vegetation to climate variables, with temperature having a more complex effect on vegetation change, while precipitation showed more distinct differences between the various vegetation indices. These findings provide important insights into the ecological sustainability of Xinjiang under warming and humidification.
QRLIT: Quantum Reinforcement Learning for Database Index Tuning
Authors: Barbosa Diogo , Gruenwald Le , D’Orazio Laurent , Bernardino Jorge
Published: November 2024

Selecting indexes capable of reducing the cost of query processing in database systems is a challenging task, especially in large-scale applications. Quantum computing has been investigated with promising results in areas related to database management, such as query optimization, transaction scheduling, and index tuning. Promising results have also been seen when reinforcement learning is applied for database tuning in classical computing. However, there is no existing research with implementation details and experiment results for index tuning that takes advantage of both quantum computing and reinforcement learning. This paper proposes a new algorithm called QRLIT that uses the power of quantum computing and reinforcement learning for database index tuning. Experiments using the database TPC-H benchmark show that QRLIT exhibits superior performance and a faster convergence compared to its classical counterpart.
Impact of Virtual Reality on Decision-Making and Risk Assessment During Simulated Residential Fire Scenarios
Authors: Russell Micah D. , Bonny Justin W. , Reed Randal
Published: November 2024

Recent research has used virtual environments (VEs), as presented via virtual reality (VR) headsets, to study human behavior in hypothetical fire scenarios. One goal of using VEs in fire scenarios is to elicit patterns of behavior which more closely align to how individuals would react to real fire emergency situations. The present study investigated whether elicited behaviors and perceived risk varied during fire scenarios presented as VEs via two viewing conditions. These included a VR condition, where the VE was rendered as 360-degree videos presented in a VR headset, and a screen condition, where VEs were rendered as fixed-view videos via a computer monitor screen. We predicted that the selection of actions during the scenario would vary between conditions, that participants would rate fires as more dangerous if they developed more quickly and when smoke was rendered as thicker, and that participants would report greater levels of immersion in the VR condition. A total of 159 participants completed a decision-making task where they viewed videos of an incipient fire in a residential building and judged what action to take. Initial action responses to the fire scenarios varied between both viewing and smoke conditions, with those assigned to the thicker smoke and screen conditions being more likely to take protective action. Risk ratings also varied by smoke condition, with evidence of higher perceived risk for thicker smoke. Several factors of self-reported immersion (namely ‘interest’, ‘emotional attachment’, ‘focus of attention’, and ‘flow’) were associated with risk ratings, with perceived presence associated with initial actions. The present study provides evidence that enhancing immersion and perceived risk in a VE contributes to a different pattern of behaviors during simulated fire decision-making tasks. While our investigation only addressed the ideas of presence in an environment, future research should investigate the relative contribution of interactivity and consequences within the environment to further identify how behaviors during simulated fire scenarios are affected by each of these factors.
Effects of Drought and Fire Severity Interaction on Short-Term Post-Fire Recovery of the Mediterranean Forest of South America
Authors: Hernández-Duarte Ana , Saavedra Freddy , González Erick , Miranda Alejandro , Francois Jean-Pierre , Somos-Valenzuela Marcelo , Sibold Jason
Published: November 2024

Wildfires and drought stressors can significantly limit forest recovery in Mediterranean-type ecosystems. Since 2010, the region of central Chile has experienced a prolonged Mega Drought, which intensified into a Hyper Drought in 2019, characterized by record-low precipitation and high temperatures, further constraining forest recovery. This study evaluates short-term (5-year) post-fire vegetation recovery across drought gradients in two types of evergreen sclerophyllous forests and a thorny forest and shrubland, analyzing Landsat time series (1987–2022) from 42 wildfires. Using the LandTrendr algorithm, we assessed post-fire forest recovery based on NDVI changes between pre-fire values and subsequent years. The results reveal significant differences in recovery across drought gradients during the Hyper Drought period, among the three forest types studied. The xeric forest, dominated by Quillaja saponaria and Lithrea caustica, showed significant interaction effects between levels of drought and fire severity, while the thorny forest and shrubland displayed no significant interaction effects. The mesic forest, dominated by Cryptocarya alba and Peumus boldus, exhibited additional significant differences in recovery between the Hyper Drought and Mega Drought periods, along with significant interaction effects. These findings underscore the critical role of prolonged, severe drought in shaping forest recovery dynamics and highlight the need to understand these patterns to improve future forest resilience under increasingly arid conditions.
A Simple Mathematical Model to Predict the Pressure Drop for Transport of Deformable Particles in Homogeneous Porous Media
Authors: Matías-Pérez Víctor , López-Ramírez Simón , Franco-Urresti Elizbeth , Aguilar-Madera Carlos G.
Published: November 2024

The transport of deformable particles (TDPs) through porous media has been of considerable interest due to the multiple applications found in industrial and medical processes. The adequate design of these applications has been mainly achieved through experimental efforts, since TDPs through porous media are challenging to model because of the mechanical blockage of the pore throat due to size exclusion, deformation in order to pass through the pore throat under the driven pressure, and breakage under strong extrusion. In this work, based on the diffusivity equation and considering the TDP as a complex fluid whose viscosity and density depend on the local pressure, a simple but accurate theoretical model is proposed to describe the pressure behavior under steady- and unsteady-state flow conditions. Assuming a linear pressure dependence of the viscosity and density of the TDPs, valid for moderate pressure changes, the solution of the mathematical model yields a quantitative correlation between the pressure evolution and the parameters compressibility, viscosity coefficient, elastic modulus, particle size, and friction factor. The predictions of the model agree with experiments and allow the understanding of transport of deformable particles through a porous media.
Green Radish Polysaccharide Prevents Alcoholic Liver Injury by Interfering with Intestinal Bacteria and Short-Chain Fatty Acids in Mice
Authors: Geng Xiong , Zhuang Miaomiao , Tian Weina , Shang Huayan , Gong Ziyi , Lv Yanfang , Li Jianrong
Published: November 2024

This study aimed to ascertain the potential benefits of green radish polysaccharide (GRP) in treating alcoholic liver disease (ALD) in mice and explore its mechanism of action. Using biochemical analysis, high-throughput sequencing of gut microbiota, and gas chromatography–mass spectrometry to measure short-chain fatty acids (SCFAs) in feces, we found that GRP intervention significantly improved lipid metabolism and hepatic function in mice subjected to excessive alcohol intake. The GRP intervention reduced malondialdehyde levels by 66% and increased total superoxide dismutase levels by 22%, thereby mitigating alcohol-induced oxidative stress. Furthermore, GRP intervention in mice with alcohol consumption resulted in a reduction in tumor necrosis factor, interleukin 6, and lipopolysaccharide levels by 12%, 9%, and 25%, respectively, effectively attenuating alcoholic liver inflammation. 16S rRNA amplicon sequencing demonstrated that excessive alcohol consumption markedly altered the gut microbiota composition in mice. The GRP treatment resulted in a significant reduction in the number of beneficial bacteria (Lactobacillus and Lachnospiraceae_NK4A136_group) and an increase in the proportion of harmful bacteria (Muribaculaceae and Verrucomicrobiota). The metabolomic analyses of the SCFAs demonstrated an increase in the contents of SCFAs, acetic acid, propionic acid, and butyric acid, following GRP supplementation. Furthermore, the metabolic levels of cholinergic synapses and glycolysis/gluconeogenesis were found to be modulated. In conclusion, these findings suggest that GRP may attenuate alcohol-induced oxidative damage in the liver by modulating the gut microbiota and hepatic metabolic pathways. This may position GRP as a potential functional component for ALD prevention.
Effect of Rice Protein on the Gelatinization and Retrogradation of Rice Starch with Different Moisture Content
Authors: Zhang Yifu , Zhang Jiawang , Wang Zeyu , Fan Longxiang , Chen Ye
Published: November 2024

Rice protein and moisture content are pivotal in the gelatinization and retrogradation processes of rice starch. This study aimed to explore the influence of rice protein on these processes by preparing rice starch gels with varying moisture levels and incorporating rice protein. At a high moisture content of 1:6, rice protein exhibited a minimal effect on the gelatinization properties of rice starch but significantly retarded the retrogradation of the starch gel. At intermediate moisture levels of 1:4 and 1:2, the rice starch gels showed pronounced retrogradation. However, rice protein was effective in inhibiting this retrogradation at a 1:4 moisture content, while its inhibitory effect diminished at a 1:2 moisture content. Under low moisture conditions of 1:1, the gelatinization of rice starch was markedly constrained by the limited water availability, but rice protein mitigated this constraint. Conversely, at this moisture level, rice protein promoted the retrogradation of the rice starch gel during the retrogradation process. The findings of this study offer a theoretical foundation that could inform the production of rice-based products.
Ultrasonic Extraction of Polysaccharides from Dendrobium officinale Leaf: Kinetics, In Vitro Activities, and Characterization
Authors: Shi Xuerong , Yang Xuzhong , He Shaotong , Duan Ting , Liang Xin , Ma Shuzhen , Gong Jijun
Published: November 2024

This study explored the kinetics of ultrasonic extraction of polysaccharides (DOLP) from Dendrobium officinale leaf (DOL), evaluated the in vitro bioactivity of DOL extracts and DOLP, and characterized the DOLP. A kinetic model was developed based on Fick’s second law. A technique utilizing 400 W for 50 min was employed for the ultrasonic extraction of DOLP, with an optimal solid–liquid ratio established at 1:40 (g/mL). DOL extracts dried using different methods exhibited varying antioxidant activity and inhibitory effects against α-amylase and α-glucosidase. An in vitro study revealed that DOL extracts obtained through vacuum freeze drying demonstrated significantly stronger antioxidant activity, while those derived through microwave drying showed superior inhibitory effects against α-amylase and α-glucosidase compared to the other two drying methods. Furthermore, it was observed that the in vitro bioactivity of DOLP (purity: 74.07 ± 0.52%) was significantly lower than that of DOL extracts. Nevertheless, DOLP (5.0 mg/mL) demonstrated a scavenging ability reaching 64.86% of VC for DPPH radical and 67.14% of VC for ·OH radical, and the inhibition of DOLP (10 mg/mL) on α-amylase and α-glucosidase reached 58.40% and 38.28% of the acarbose, respectively. The findings revealed that DOLP are predominantly composed of mannose, glucose, galactose, and arabinose in a distinctive molar ratio of 89.00:16.33:4.78:1.
Decoding the Formation and Elimination Mechanism of Ethyl Carbamate in Strong-Aroma Baijiu
Authors: Zhang Liqiang , Qiu Yue , Zhang Yongqing , Jia Yintao , Sun Baoguo , Dong Wei
Published: November 2024

In the present study, changes in the physicochemical indices, ethyl carbamate (EC) precursor and EC contents, and microbial communities of fermented grains under different fermentation patterns during strong-aroma Baijiu (SAB) fermentation and changes in EC precursor and EC contents during distillation were investigated to study EC formation during these processes. In detail, the amounts of sorghum added in protocols C and D were half those added in protocols A and B (the normal SAB-producing technology). When fermented for about 30 to 35 days, the fermented grains of protocols A and C were, respectively, remixed with Daqu and second-distilled SAB (so-called “Huijiu jiaqu”, HJJQ) and fermented for about 30 to 40 days. The results showed that the acidities of the final fermented grains of protocols A (2.43 ± 0.09 mmol/10 g) and C (3.18 ± 0.08 mmol/10 g) were lower than those of protocols B (3.71 ± 0.07 mmol/10 g) and D (4.66 ± 0.10 mmol/10 g), while the alcohol contents in the final fermented grains of protocols A (18.33 ± 0.76%) and C (15.33 ± 1.08%) were higher than those of protocols B (5.10 ± 0.85%) and D (1.85 ± 0.62%). No significant differences were observed in the other physicochemical indices among the samples. The HJJQ operation significantly increases the alcohol content and reduces the acidity of the fermented grains but has little influence on the other physicochemical indices during SAB fermentation. Excluding the influence of the HJJQ operation and a half input of sorghum on the EC precursor and EC contents for the fermented grains of protocol B, the linear relationships between the EC content and alcohol (R2: 0.4465), citrulline (R2: 0.6962), urea (R2: 0.4705), and HCN (R2: 0.6324) contents were good (all the confidence levels were at 0.05), indicating that these compounds were the dominant EC precursors during SAB fermentation. HJJQ also facilitated the reaction between alcohol and other EC precursors, decreasing EC precursor content and increasing the EC content. KEGG pathway analysis demonstrated that EC precursors were mainly synthesized by alcohol and arginine metabolism. HCN (R2: 0.3875 to 0.8198) and alcohol (R2: 0.4642 to 0.8423) were the dominant EC precursors during SAB distillation. Overall, the HJJQ operation, especially in protocol C, could significantly reduce the content of EC in base SAB, and the base SAB obtained was of good quality. This, therefore, may be an alternative and effective way to reduce the EC content in base Baijiu.
Bitter Perception and Effects of Foods Rich in Bitter Compounds on Human Health: A Comprehensive Review
Authors: Qiao Kaina , Zhao Mingxia , Huang Yan , Liang Li , Zhang Yuyu
Published: November 2024

Bitter food, because of its unique taste, is not popular with the public, and is even considered to be difficult to swallow. By binding to specific sites of bitter receptors (26 hTAS2Rs), bitter compounds activate the downstream signaling pathways mediated by G protein, which convert chemical signals into electrical signals that are ultimately transmitted to the brain to produce the bitter perception. The intensity of bitterness is mainly determined by the hydrophobic recognition region of bitter receptors. The bitter compounds in foods mainly include alkaloids, polyphenols, terpenoids, amino acids, etc. Foods rich in bitter taste are mostly natural such as beans, nuts, and coffee, etc. Studies have proven that bitter foods have biological activities such as preventing hyperlipidemia, hypertension, hyperglycemia, anti-inflammatory, antitumor, antibacterial, antioxidant, and exhibit neuroprotective effects and other biological activities. The purpose of this review is to explore the bitter perception and the biological activity of bitter compounds, clarify the mechanism of their action on human health, and provide theoretical guidance for the development and application of functional foods.
Fractal Characteristics of Pore Throat and Throat of Tight Sandstone Sweet Spot: A Case Study in the East China Sea Basin
Authors: Wang Wenguang , Lin Chengyan , Zhang Xianguo
Published: November 2024

The study of the fractal characteristics of the pore throat radius (PTR) and throat radius of sweet spots is crucial for the exploration and development of tight gas sandstone. This study used conventional core analysis, X-ray diffraction analysis, scanning electron microscopy (SEM), and constant-rate mercury injection experiment (CRMI), high-pressure mercury injection experiment (HPMI), and nuclear magnetic resonance (NMR) techniques to investigate the fractal characteristics of the PTR and throat radius of the tight sandstone sweet spots of the Huagang Formation in the central uplift belt of the East China Sea Basin. Based on conventional core analysis and SEM, the main pore types of the tight sandstone samples in the Huagang Formation were determined to be intergranular dissolved pore, intragranular dissolved pore, intergranular pore, and moldic pore. HPMI and NMR techniques were used to evaluate the full-size PTR distribution of type I (TI), type II (TII), and type III (TIII) sweet spots. Based on fractal theory, CRMI was used to calculate the fractal dimension of the PTR and throat radius of three types of sweet spots, and the relationship between the fractal dimensions and pore throat structure parameters and mineral composition were investigated. The results showed that the full-size PTR distribution curve exhibited bimodal or unimodal characteristics. The peak values of the PTR distribution of the TI, TII, and TIII sweet spots were mainly concentrated at 0.002–22.5 μm, 0.001–2.5 μm, and 0.0004–0.9 μm, respectively. The fractal dimensions of the PTR and throat radius were calculated. The average throat radius fractal dimensions of the TI, TIII, and TIII sweet spots were 2.925, 2.875, and 2.786, respectively. The average PTR fractal dimensions of the TI, TII, and TIII sweet spots were 2.677, 2.684, and 2.702, respectively. The throat radius fractal dimension of the TI, TII, and TIII sweet spots was positively correlated with mercury saturation, average throat radius, feldspar content, and clay mineral content and negatively correlated with displacement pressure, quartz content, and carbonate cement content. The PTR fractal dimension of the TI, TII, and TIII sweet spots was positively correlated with displacement pressure, quartz content, and carbonate cement content and negatively correlated with feldspar content. The throat size of the TI sweet spot was large, and the heterogeneity of the throat was strong. The PTR heterogeneity of the TI sweet spot was lower than that of the TII and TIII sweet spots. The findings of this study can provide important guidance for the exploration and development of tight gas sandstone.
Phylum Firmicutes in the Faecal Microbiota Demonstrates a Direct Association with Arterial Hypertension in Individuals of the Kazakh Population Without Insulin Resistance
Authors: Abildinova Gulshara , Vochshenkova Tamara , Aitkaliyev Alisher , Abildinova Aizhan , Benberin Valeriy , Borovikova Anna , Bekenova Nazira , Kassiyeva Balzhan
Published: November 2024

The gut microbiota plays a fundamental role in the host’s energy metabolism and the development of metabolic diseases such as arterial hypertension, insulin resistance, and atherosclerosis. Our study aimed to investigate the potential role of the gut microbiota in arterial hypertension among individuals of the Kazakh population without insulin resistance. 16S rRNA gene sequencing of faecal samples from 197 Kazakh subjects was performed. Preliminary binary comparisons of the faecal microbiota composition depending on the presence of arterial hypertension and insulin resistance revealed statistically significant differences in the abundance of the phylum Firmicutes. Logistic regression analysis showed that only the phylum Firmicutes influenced hypertension risk in individuals without insulin resistance after adjusting for age, sex, BMI, fasting glucose, triglycerides, and triglyceride–glucose index. The higher the abundance of the phylum Firmicutes in faeces, the greater the risk of arterial hypertension (OR = 1.064 [95% CI 1.005–1.125]). Correlation analysis revealed a negative association between the abundance of the phylum Firmicutes and the triglyceride–glucose index, primarily driven by triglyceride levels. These findings suggest the potential role of the gut microbiota, especially the phylum Firmicutes, in the development of hypertension in individuals without insulin resistance.
Impact of the Quadriceps Angle on Health and Injury Risk in Female Athletes
Authors: Gant Hannah , Ghimire Nabin , Min Kisuk , Musa Ibrahim , Ashraf Maryam , Lawan Ahmed
Published: November 2024

The quadriceps angle, knowns as the Q-angle, is an anatomical feature of the human body that is still largely unknown and unstudied despite its initial discovery in the 1950s. The strength disparities between male and female athletes are largely determined by the Q-angle. In spite of a growing number of women participating in sports such as track, tennis, soccer, gymnastics, basketball, volleyball, swimming, and softball, studies investigating injuries in this group are scanty. Even though the Q-angle has been the subject of many studies carried out all over the world, a review of the literature regarding its effects on health and injury risk in female athletes has not yet been completed. The aim of this review is to examine the crucial role of the Q-angle in the biomechanics of the knee joint and its effect on performance and injury risk, particularly in female athletes. Furthermore, we highlight the greater likelihood of knee-related injuries seen in female athletes being caused by the Q-angle. Athletes, coaches, healthcare professionals, and athletic trainers can better comprehend and prepare for the benefits and drawbacks resulting from the Q-angle by familiarizing themselves with the research presented in this review.
Socioeconomic Disparities in the Usage of Urban Opportunities in South Korea During the COVID-19 Pandemic: Using Land Use/Land Cover and Mobile Phone Data
Authors: Lee Kangjae , Park Yoo Min , Joo Yoohyung , Joo Minsoo , Heo Joon
Published: November 2024

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 19 (COVID-19), has resulted in dramatic changes in human lifestyles and the geographic distribution of populations. However, despite the unequal impact of COVID-19 across urban spaces, research on the association between socioeconomic disparities in the usage of various types of urban amenities during the pandemic is limited. Thus, this study utilized mobile phone data and land use/land cover (LULC) data to investigate COVID-19-induced changes in the hot spots of the daytime and nighttime populations of two districts in Seoul, South Korea: Gangnam (a high-income community) and Gangbuk (a low-income community). First, the differences between Gangnam and Gangbuk in the LULC and mobile phone data, before and during the pandemic, were statistically analyzed by age. Second, the areas with significantly increased mobile phone-based populations during COVID-19 were identified using a hot spot analysis method and Welch’s t-test. This study identified that there were significant disparities in the use of green spaces during the pandemic, with a higher percentage of the mobile phone-based population in Gangnam than Gangbuk. Youths and adults in Gangnam were more likely to visit schools and enjoy physical activities in forests and open spaces during the pandemic, whereas there was no such increase in Gangbuk. The findings contribute to the understanding of the impact of COVID-19 on human behaviors and socioeconomic disparities in the quality of urban life.