bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics of Fermentation Parameters and Bacterial Community in Rumen of Calves During Dietary Protein Oscillation
Authors: Zhang Kun , Teng Zhanwei , Meng Qing , Liu Shuai , Yuan Liping , Fu Tong , Zhang Ningning , Gao Tengyun
Published: October 2024

Dietary crude protein concentration oscillation can improve the nitrogen utilization efficiency of ruminants. However, little is known about the dynamic changes in microbiota and fermentation in the rumen of calves during the oscillation period. In this study, six calves were fed an oscillating diet at 2-day intervals, including a high-protein diet (HP) and a low-protein diet (LP). The rumen fermentation parameters, plasma urea-N concentration, and rumen bacterial diversity were characterized throughout the oscillation period. The concentrations of volatile fatty acids, NH3-N, and plasma urea-N in rumen changed significantly with an oscillating diet. The abundance of Prevotella_1, Selenomonadales, Succiniclasticum, Clostridiales, Ruminococcaceae, Lachnospiraceae, and Rikenellaceae_RC9_gut_group showed significant changes with diet. Prevotella_1 was positively correlated, and Lachnospiraceae_AC2044_group and Saccharofermentans were negatively correlated with NH3-N. The abundance of Amino Acid Metabolism, Metabolism of Other Amino Acids, and Glycan Biosynthesis and Metabolism pathways, annotated by bacterial functional genes, decreased when the diet changed from HP to LP. The abundance of the Carbohydrate Metabolism pathway increased after the two dietary changes. In conclusion, the plasma urea-N concentration was not as sensitive and quick to adapt to diet changes as the rumen fermentation parameters. Rumen bacteria were responsible for increasing the nitrogen utilization efficiency of calves fed an oscillating diet.
Preliminary Assessment of the Protective and Antitumor Effects of Several Phytoene-Containing Bacterial and Microalgal Extracts in Colorectal Cancer
Authors: Perazzoli Gloria , Luque Cristina , León-Vaz Antonio , Gómez-Villegas Patricia , Rengel Rocío , Molina-Márquez Ana , Morón-Ortiz Ángeles , Mapelli-Brahm Paula , Prados José , Melguizo Consolación , Meléndez-Martínez Antonio , León Rosa
Published: October 2024

The identification of new functional food constituents is a priority to improve the prognosis and prevention of colorectal cancer (CRC). In this study, several bacterial and algal phytoene-enriched extracts were obtained, and their potential activity against oxidative damage and their ability to inhibit proliferation and cell migration in several human colon-adenocarcinoma-derived cell lines were assessed. The main conclusions indicate that total extracts of Sphingomonas echinoides and Chlorella sorokiniana exhibited the highest protective effect against oxidative damage. All extracts enhanced the activity of detoxifying enzymes, particularly importantly the increase of NAD(P)H:quinone oxidoreductase activity, which reached a value 40% higher than that of untreated control cells upon exposure to Escherichia coli extracts. Staphylococcus haemolyticus and transgenic E. coli extracts significantly arrested the migration capacity of both cell lines, while S. haemolyticus and C. sorokiniana extracts inhibited cell proliferation by 15 to 20% compared to untreated cells. These results point to these extracts as potential antioxidant complements able to protect cells against oxidative damage and with a moderate ability to inhibit the proliferation and migration of CRC tumor cells, paving the way to design functional foods or probiotic formulations with preventive properties against oxidative stress-related diseases, such as cancer, or as starting point for purifying anticancer compounds.
Ideal Photothermal Materials Based on Ge Subwavelength Structure
Authors: Wu Jingjun , Wang Kaixuan , Wei Cong , Ma Jun , Xu Hongbo , Zheng Wanguo , Zhu Rihong
Published: October 2024

Photothermal materials often prioritize solar absorption while neglecting thermal radiation losses, which diminishes thermal radiation conversion efficiency. This study addresses this gap by introducing a germanium (Ge) subwavelength structure (SWS) designed to optimize both solar absorption and infrared emissivity. Using a self-masked reactive ion etching (RIE) technique, we achieved a peak absorption of 98.8% within the 300 nm to 1800 nm range, with an infrared emissivity as low as 0.32. Under solar illumination of 1000 W/m2, the structure’s temperature increased by 50 °C, generating a heating power of 800 W/m2. Additionally, it demonstrated good mechanical and thermal stability at high temperatures and possessed a hydrophobic angle of 132°, ensuring effective self-cleaning. These characteristics make the Ge SWS suitable for application in solar panels, displays, sensors, and other optoelectronic devices.
DNA Catalysis: Design, Function, and Optimization
Authors: Stratton Rebecca L. , Pokhrel Bishal , Smith Bryce , Adeyemi Adeola , Dhakal Ananta , Shen Hao
Published: October 2024

Catalytic DNA has gained significant attention in recent decades as a highly efficient and tunable catalyst, thanks to its flexible structures, exceptional specificity, and ease of optimization. Despite being composed of just four monomers, DNA’s complex conformational intricacies enable a wide range of nuanced functions, including scaffolding, electrocatalysis, enantioselectivity, and mechano-electro spin coupling. DNA catalysts, ranging from traditional DNAzymes to innovative DNAzyme hybrids, highlight the remarkable potential of DNA in catalysis. Recent advancements in spectroscopic techniques have deepened our mechanistic understanding of catalytic DNA, paving the way for rational structural optimization. This review will summarize the latest studies on the performance and optimization of traditional DNAzymes and provide an in-depth analysis of DNAzyme hybrid catalysts and their unique and promising properties.
Adsorption and Permeation Events in Molecular Diffusion
Authors: Grebenkov Denis S.
Published: October 2024

How many times can a diffusing molecule permeate across a membrane or be adsorbed on a substrate? We employ an encounter-based approach to find the statistics of adsorption or permeation events for molecular diffusion in a general confining medium. Various features of these statistics are illustrated for two practically relevant cases: a flat boundary and a spherical confinement. Some applications of these fundamental results are discussed.
Polyphenolic Compounds in the Stems of Raspberry (Rubus idaeus) Growing Wild and Cultivated
Authors: Raal Ain , Vahtra Anni , Koshovyi Oleh , Ilina Tetiana , Kovalyova Alla , Püssa Tõnu
Published: October 2024

The stems of Rubus idaeus L., a byproduct of the fruit–food industry, are known sources of bioactive compounds. The main objective of this study was to investigate the composition of polyphenolic compounds in R. idaeus stems. Seven cultivated raspberry varieties, thirteen garden samples, including five well-known raspberry varieties, and thirteen wild raspberry samples from different locations in Estonia were analyzed. The HPLC-MS method detected 62 substances, of which 42 were identified, 12 were tentatively identified, and 8 compounds remained unknown. Protocatechuic acid pentoside was dominant in most varieties and in all garden and wild raspberry samples. Dihydroxybenzoic acid hexoside 1, p-coumaroyl quinic acid 1, quercetin 4’-glucuronide, and p-coumaric acid glycoside were found in significant quantities. Correlations among the contents of individual compounds were established. When studying the dynamics of polyphenolic compound accumulation in, for example, the GR1 sample over a year, it was found that, in raspberry stems, the largest amount of them accumulated in April and slightly less in January and October. Investigating the dependence of the accumulation of polyphenols on the parts of the stem, it was found that the upper parts have the highest phenolic contents. Therefore, it is recommended to harvest approximately the upper third of the stem.
Sodium Alginate/MXene-Based Flexible Humidity Sensors with High-Humidity Durability and Application Potentials in Breath Monitoring and Non-Contact Human–Machine Interfaces
Authors: Chen Huizhen , Huang Xiaodong , Yang Yikai , Li Yang
Published: October 2024

Flexible humidity sensors (FHSs) with fast response times and durability to high-humidity environments are highly desirable for practical applications. Herein, an FHS based on crosslinked sodium alginate (SA) and MXene was fabricated, which exhibited high sensitivity (impedance varied from 107 to 105 Ω between 10% and 90% RH), good selectivity, prompt response times (response/recover time of 4 s/11 s), high sensing linearity (R2 = 0.992) on a semi-logarithmic scale, relatively small hysteresis (~5% RH), good repeatability, and good resistance to highly humid environments (negligible changes in sensing properties after being placed in 98% RH over 24 h). It is proposed that the formation of the crosslinking structure of SA and the introduction of MXene with good conductivity and a high specific surface area contributed to the high performance of the composite FHS. Moreover, the FHS could promptly differentiate the respiration status, recognize speech, and measure fingertip movement, indicating potential in breath monitoring and non-contact human–machine interactions. This work provides guidance for developing advanced flexible sensors with a wide application scope in wearable electronics.
Rice Under Dry Cultivation–Maize Intercropping Improves Soil Environment and Increases Total Yield by Regulating Belowground Root Growth
Authors: Wu Zhihai , Xue Bei , Wang Shiwen , Xing Xu , Nuo Min , Meng Xin , Wu Meikang , Jiang Hao , Ma Huimin , Yang Meiying , Wei Xiaoshuang , Zhao Guangxin , Tian Ping
Published: October 2024

Under the one-season-a-year cropping pattern in Northeast China, continuous cropping is one of the main factors contributing to the degradation of black soil. Previous studies (on maize–soybean, maize–peanut, and maize–wheat intercropping) have shown that intercropping can alleviate this problem. However, it is not known whether intercropping is feasible for maize and rice under dry cultivation, and its effects on yield and soil fertility are unknown. A three-year field-orientation experiment was conducted at Jilin Agricultural University in Changchun city, Jilin Province, China, consisting of three cropping regimes, namely rice under dry cultivation–maize intercropping (IRM), sole rice under dry cultivation (SR), and sole maize (SM). All straw was fully returned to the field after mechanical harvesting. Rice under dry cultivation–maize intercropping with a land-equivalent ratio of 1.05 (the average of three years values) increased the total yield by 8.63% compared to the monoculture system. The aggressivity (A), relative crowding coefficient (K), time–area-equivalent ratio (ATER), and competition ratio (CR) value were positive or ≥1, also indicating that the rice under dry cultivation–maize intercropping had a yield advantage of the overall intercropping system. This is because the intercropped maize root length density (RLD) increased by 33.94–102.84% in the 0–40 cm soil layer, which contributed to an increase in the soil porosity (SP) of 5.58–10.10% in the 0–30 cm soil layer, an increase in the mean weight diameter of soil aggregates (MWD) of 3.00–15.69%, an increase in the geometric mean diameter of soil aggregates (GMD) of 8.16–26.42%, a decrease in the soil bulk density (SBD) of 4.02–7.35%, and an increase in the soil organic matter content (SOM) of 0.60–4.35%. This increased the water permeability and aeration of the soil and facilitated the absorption of nutrients and water by the root system and their transportation above ground, and the plant nitrogen, phosphorus, and potassium accumulation in the intercropping system were significantly higher than that in monoculture treatment, further promoting the total yield of intercropping. This suggests that rice under a dry cultivation–maize intercropping system is feasible in Northeast China, mainly because it promotes belowground root growth, improves the soil environment, and increases the total yield of intercropping.
CVW-Etr: A High-Precision Method for Estimating the Severity Level of Cotton Verticillium Wilt Disease
Authors: Pan Pan , Yao Qiong , Shen Jiawei , Hu Lin , Zhao Sijian , Huang Longyu , Yu Guoping , Zhou Guomin , Zhang Jianhua
Published: October 2024

Cotton verticillium wilt significantly impacts both cotton quality and yield. Selecting disease-resistant varieties and using their resistance genes in breeding is an effective and economical control measure. Accurate severity estimation of this disease is crucial for breeding resistant cotton varieties. However, current methods fall short, slowing the breeding process. To address these challenges, this paper introduces CVW-Etr, a high-precision method for estimating the severity of cotton verticillium wilt. CVW-Etr classifies severity into six levels (L0 to L5) based on the proportion of segmented diseased leaves to lesions. Upon integrating YOLOv8-Seg with MobileSAM, CVW-Etr demonstrates excellent performance and efficiency with limited samples in complex field conditions. It incorporates the RFCBAMConv, C2f-RFCBAMConv, AWDownSample-Lite, and GSegment modules to handle blurry transitions between healthy and diseased regions and variations in angle and distance during image collection, and to optimize the model’s parameter size and computational complexity. Our experimental results show that CVW-Etr effectively segments diseased leaves and lesions, achieving a mean average precision (mAP) of 92.90% and an average severity estimation accuracy of 92.92% with only 2.6M parameters and 10.1G FLOPS. Through experiments, CVW-Etr proves robust in estimating cotton verticillium wilt severity, offering valuable insights for disease-resistant cotton breeding applications.
Challenges and Strategies in the Industrial Application of Dendrobium officinale
Authors: Bao Hexigeduleng , Bao Hainan , Wang Yu , Wang Feijuan , Jiang Qiong , He Xiaoqi , Li Hua , Ding Yanfei , Zhu Cheng
Published: October 2024

Dendrobium officinale Kimura & Migo (D. officinale) is a well-recognized traditional Chinese medicinal herb that is both medicinal and edible. Contemporary pharmacological studies have revealed that D. officinale contains abundant bioactive compounds, including polysaccharides, flavonoids, alkaloids, and dendrobine, exhibiting diverse pharmacological properties such as antioxidant, anti-inflammatory, and immunomodulatory effects. However, the industrial application of D. officinale faces many problems, such as the scarcity of wild resources, low natural reproduction rate, and slow growth rate as well as the lack of relevant industrial standards. Nevertheless, substantial advancements, including the exploitation of artificial propagation techniques and breeding of new varieties, have been achieved in recent years. These developments have effectively addressed the challenges associated with its low natural reproduction rate and the scarcity of wild resources. This review summarizes the progress in the industrial development, seedling cultivation, and pharmacological exploration of D. officinale in recent years. Furthermore, it analyzes current research inadequacies and offers strategic solutions to enhance its application in healthcare and medicine.
The Impact of Adsorption Property Modification by Crosslinkers on Graphene Oxide Membrane Separation Performance
Authors: Ayala-Claveria Martin , Carlesi Carlos , Puig Julieta , Olguin Gianni
Published: October 2024

The health risks associated with the presence of heavy metals in drinking water can be severe. To address this issue, membrane separation technology is one of the consolidated alternatives. Inorganic, porous membranes were found in applications where low energy consumption is highly desirable. The selectivity of these membranes is attained by functionalisation. Graphene oxide functionalised membrane technology is promising for removing heavy metal ions. This work summarises, discusses and presents the relationship between adsorption and overall membrane separation process performance for heavy metal ions removal from wastewater when a graphene oxide-functionalised membrane is used. The separation performance depends on the hydrophobic interactions of the membrane and the solute. The electrostatic interaction between the negatively charged membrane surface and positively charged metal ions facilitates the adsorption, leading to the rejection of these metal ions. The influences of the chemical nature of the modifiers of graphene oxide layers are highlighted.
Selective Processing of the Kaolinite Fraction of High-Silicon Bauxite
Authors: Gladyshev Sergey , Dyussenova Symbat , Abikak Yerkezhan , Akhmadiyeva Nazym , Imangaliyeva Leila , Bakhshyan Arina
Published: October 2024

When processing low-quality gibbsite–kaolinite bauxites, technologies that involve different methods of mechanical and chemical enrichment with the separation of a difficult-to-utilize fine kaolinite fraction for disposal are used. Before production, problems related to waste storage and disposal arise. To solve the problem of utilization, it is necessary to develop an effective technology for the selective processing of the kaolinite fraction. The efficiency of the technology will depend on the quality of pretreatment of raw materials prior to processing for Al2O3 extraction. Preliminary preparation of kaolinite fraction is associated with the maximum removal of excess silica during chemical enrichment by treatment with an alkaline solution. The presence of silica reduces the quality of final alumina products and requires a large consumption of reagents during the desiliconization of aluminate solutions. During the chemical enrichment of kaolinite fraction in alkaline solution, a serious problem of the co-dissolution of Al2O3 with silica arises. The solution to this problem can be the transformation of phase composition with the transformation of kaolin into a chemically resistant compound corundum, which will create conditions for the selective removal of silica. Kazakhstan’s alumina refinery, Pavlodar Aluminum Smelter, processes low-quality gibbsite–kaolinite bauxite from the Krasnogorsk deposit. To improve the quality of bauxite, preliminary gravity enrichment is carried out to separate the kaolinite fraction to a quantity greater than 50%. The purpose of this work was to study the possibility of the selective processing of the kaolinite fraction via various techniques, including preliminary thermal transformation, through sintering, chemical enrichment, autoclave leaching in a circulating aluminate solution, and low-temperature desiliconization, to obtain a solution for decomposition. As a result of this study, the possibility of obtaining a corundum phase after sintering at a temperature of 900–1000 °C was established, which made it possible to obtain 58.8% chemical enrichment through the extraction of SiO2 into solution. Further use of the enriched kaolinite fraction in autoclave leaching in a circulating aluminate solution with low-temperature desiliconization made it possible to obtain an aluminate solution with a caustic modulus of 1.65–1.7, which is suitable for decomposition.
Cross-Border Electricity Cooperation in Southern Asia: Consequences and Benefits
Authors: Borge-Diez David , Rosales-Asensio Enrique , Cabrera Pedro , Sarmento Paula , Carta José Antonio
Published: October 2024

This study analyzes the potential of cross-border electricity cooperation as an effective way to reduce the costs of renewable energy deployment in the South Asian region using a novel cooperation mechanism among countries. This paper studies the case of India, Bhutan, and Nepal. From the analysis, Bhutan and Nepal have a large under-exploited hydropower potential that presents a great opportunity for India’s energy supply by developing cross-border electricity trading infrastructure and associated markets. For this, developing the infrastructure for power transmission and hydropower plants in each country is necessary to reduce investment in flexibility solutions, power system costs, and CO2 emissions. According to a previous analysis, in Nepal’s case, the Cross-Border Electricity Market (CBEM) development would increase Nepal’s Gross Domestic Product (GDP) by up to 39%. India would also benefit from this mechanism. Using this energy trade mechanism, India’s power generation needs would be reduced by 2% and CO2 emissions would be reduced by 5.60% by 2045. The most important conclusions to highlight are that (i) there is an important opportunity to simultaneously enhance the economy sector in some undeveloped countries in the region when, at the same time, reducing carbon intensity in India; (ii) at the same time, there is a large barrier, as the analysis shows that despite these associated benefits there is a major risk in the lack of policy harmonization among all countries involved; and (iii) that one of the most important key aspects for success is the development of a coordinated regulation strategy. These results show the potential of CBEM systems in the region but also encourage researchers and policymakers worldwide to explore this mechanism as an effective way to enhance the decarbonization of power systems.
Study on the Stress Distribution Characteristics of Rock in the Bottomhole and the Influence Laws of Various Parameters Under the Impact of a Liquid Nitrogen Jet
Authors: Xiao Bo , Cai Chengzheng , Gao Yanan , Wang Bo , Feng Yinrong , Li Jiacheng , Zou Zengxin
Published: October 2024

This study presents research on the stress distribution characteristics of rock in the bottomhole and the influence laws of various parameters under the impact of liquid nitrogen jet. A multi-field coupled numerical model considering transient flow field, conjugate heat transfer, and nonlinear solid deformation was established to investigate the damage-induced fracturing mechanism of rock under liquid nitrogen jet. The study compares the impact effects of liquid nitrogen jet and water jet on rock and analyzes the variations in the stress field under different parameters. Due to its extremely low temperature, the liquid nitrogen jet creates a strong thermal stress gradient in a short time, significantly increasing the maximum principal stress and Mises stress in the rock compared to a water jet. Solid parameters, particularly the confining pressure and elastic modulus of the rock, have a more significant impact on stress distribution, while fluid parameters such as outlet pressure and fluid temperature have a smaller and more volatile effect. An increase in confining pressure inhibits tensile failure in the rock, while a higher elastic modulus enhances both tensile and shear failure. The initial rock temperature significantly affects the stress distribution, with optimal tensile failure observed at intermediate temperatures. The liquid nitrogen jet achieves a higher maximum velocity and overflow velocity than the water jet, contributing to more effective rock fracturing. The results provide a theoretical basis for the optimization of liquid nitrogen jet drilling parameters, which can help improve drilling efficiency.
A Systematic Literature Review of Insurance Claims Risk Measurement Using the Hidden Markov Model
Authors: Surya Hilda Azkiyah , Sukono  , Napitupulu Herlina , Ismail Noriszura
Published: October 2024

In the rapidly evolving field of insurance, accurate risk measurement is crucial for effective claims management and financial stability. Therefore, this research presented a systematic literature review (SLR) on insurance claims risk measurement using the Hidden Markov Model (HMM). Bibliometric analysis was conducted using VOSviewer 1.6.20 and ResearchRabbit software to map research trends and collaboration networks in this topic. This review explored the implementation of the HMM in predicting the frequency and severity of insurance claims, with a focus on the statistical distribution methods used. In addition, the research emphasized the influence of the number of hidden states in the HMM on claims behavior, both in terms of frequency and magnitude, and provided interpretations of these hidden dynamics. Data sources for this review comprised three databases, namely, Scopus, ScienceDirect, and Dimensions, and additional papers from a website. The article selection process followed updated PRISMA 2020 guidelines, resulting in twelve key papers relevant to the topic. The results offered insights into the application of the HMM for forecasting the frequency and severity of insurance claims and opened avenues for further investigation on distribution models and hidden state modeling.
Multi-Strategy Bald Eagle Search Algorithm Embedded Orthogonal Learning for Wireless Sensor Network (WSN) Coverage Optimization
Authors: Niu Haixu , Li Yonghai , Zhang Chunyu , Chen Tianfei , Sun Lijun , Abdullah Muhammad Irsyad
Published: October 2024

Coverage control is a fundamental and critical issue in plentiful wireless sensor network (WSN) applications. Aiming at the high-dimensional optimization problem of sensor node deployment and the complexity of the monitoring area, an orthogonal learning multi-strategy bald eagle search (OLMBES) algorithm is proposed to optimize the location deployment of sensor nodes. This paper incorporates three kinds of strategies into the bald eagle search (BES) algorithm, including Lévy flight, quasi-reflection-based learning, and quadratic interpolation, which enhances the global exploration ability of the algorithm and accelerates the convergence speed. Furthermore, orthogonal learning is integrated into BES to improve the algorithm’s robustness and premature convergence problem. By this way, population search information is fully utilized to generate a more superior position guidance vector, which helps the algorithm jump out of the local optimal solution. Simulation results on CEC2014 benchmark functions reveal that the optimization performance of the proposed approach is better than that of the existing method. On the WSN coverage optimization problem, the proposed method has greater network coverage ratio, node uniformity, and stronger optimization stability when compared to other state-of-the-art algorithms.
Changes in Motor Strategy and Neuromuscular Control During Balance Tasks in People with a Bimalleolar Ankle Fracture: A Preliminary and Exploratory Study
Authors: Salas-Gómez Diana , Barbado David , Sánchez-Juan Pascual , Pérez-Núñez María Isabel , Laguna-Bercero Esther , Lantarón-Juarez Saray , Fernandez-Gorgojo Mario
Published: October 2024

Ankle fractures can lead to issues such as limited dorsiflexion, strength deficits, swelling, stiffness, balance disorders, and functional limitations, which complicate daily activities. This study aimed to describe neuromuscular adaptations at 6 and 12 months post-surgery during static and dynamic balance tasks, specifically using the Y-Balance Test (YBT). Additionally, the relationship between neuromuscular patterns, balance, and musculoskeletal deficits was evaluated. In 21 participants (14 at 6 months and 21 at 12 months) with bimalleolar fractures, hip strength, ankle dorsiflexion, ankle functionality, and static and dynamic balance were assessed using electromyography of five lower limb muscles (tibialis anterior, peroneus longus, lateral gastrocnemius, biceps femoris, and gluteus medius). A significant interaction effect (limb × proximal [hip]—distal [ankle] muscle) (F = 30.806, p < 0.001) was observed in the anterior direction of the Y-Balance Test (YBTA) at 6 months post-surgery. During the YBTA and YBT posteromedial (YBTPM), it was found that a lower dorsiflexion range of movement was associated specifically at 6 months with greater activation of the lateral gastrocnemius. However, these differences tended to diminish by 12 months. These findings suggest that neuromuscular patterns differ between operated and non-operated limbs during the YBTA at 6 months post-surgery. The Y-Balance Test, particularly its anterior direction, effectively highlighted these neuromuscular changes. This is a preliminary study; further research is needed to explore these findings in depth.
Implementing AI-Driven Bed Sensors: Perspectives from Interdisciplinary Teams in Geriatric Care
Authors: Acosta Cromwell G. , Ye Yayan , Wong Karen Lok Yi , Zhao Yong , Lawrence Joanna , Towell Michelle , D’Oyley Heather , Mackay-Dunn Marion , Chow Bryan , Hung Lillian
Published: October 2024

Sleep is a crucial aspect of geriatric assessment for hospitalized older adults, and implementing AI-driven technology for sleep monitoring can significantly enhance the rehabilitation process. Sleepsense, an AI-driven sleep-tracking device, provides real-time data and insights, enabling healthcare professionals to tailor interventions and improve sleep quality. This study explores the perspectives of an interdisciplinary hospital team on implementing Sleepsense in geriatric hospital care. Using the interpretive description approach, we conducted focus groups with physicians, nurses, care aides, and an activity worker. The Consolidated Framework for Implementation Research (CFIR) informed our thematic analysis to identify barriers and facilitators to implementation. Among 27 healthcare staff, predominantly female (88.89%) and Asian (74.1%) and mostly aged 30–50 years, themes emerged that Sleepsense is perceived as a timesaving and data-driven tool that enhances patient monitoring and assessment. However, barriers such as resistance to change and concerns about trusting the device for patient comfort and safety were noted, while facilitators included training and staff engagement. The CFIR framework proved useful for analyzing implementation barriers and facilitators, suggesting future research should prioritize effective strategies for interdisciplinary team support to enhance innovation adoption and patient outcomes in rehabilitation settings.
Heart Rate Estimation Considering Reconstructed Signal Features Based on Variational Mode Decomposition via Multiple-Input Multiple-Output Frequency Modulated Continuous Wave Radar
Authors: Nakatani Sara , Bouazizi Mondher , Ohtsuki Tomoaki
Published: October 2024

Accurate heart rate estimation using Doppler radar and Frequency Modulated Continuous Wave (FMCW) radar is highly valued for privacy protection and the ability to measure through clothing. Conventional methods struggle to isolate the heartbeat from respiration and body motion. This paper introduces a novel heart rate estimation method using Variational Mode Decomposition (VMD) via Multiple-Input Multiple-Output (MIMO) FMCW radar. The proposed method first estimates human positions within the radar’s coverage, reducing noise by focusing on signals from these positions. The signal is then decomposed into multiple Intrinsic Mode Function (IMF) signals using VMD, and the heartbeat-specific IMF is extracted based on its center frequency. The heart rate signal is reconstructed using weighted addition of IMF signals for each radar cell, with cells defined by specific angles and distances within the coverage area. Peak detection is used to estimate heart rate from these reconstructed signals. To ensure accuracy, the method selects the heart rate estimate with the highest energy and periodicity for the first four time windows. From the fifth time window onward, it selects the estimate closest to the average of the previous four, minimizing extraneous variations. Experiments conducted with one and two subjects showed promising results. In case 1, with one subject, the method achieved a Mean Absolute Error (MAE) of 2.54 BPM and an exclusion rate of 0.94% using MIMO FMCW radar, compared to 4.72% with Doppler radar. In case 2, with two subjects, the method achieved an MAE of 2.28 BPM, confirming accurate simultaneous heart rate estimation.
Dynamic Temporal Denoise Neural Network with Multi-Head Attention for Fault Diagnosis Under Noise Background
Authors: Li Zhongzhi , Fan Rong , Ma Jinyi , Ai Jianliang , Dong Yiqun
Published: October 2024

Fault diagnosis plays a crucial role in maintaining the operational safety of mechanical systems. As intelligent data-driven approaches evolve, deep learning (DL) has emerged as a pivotal technique in fault diagnosis research. However, the collected vibrational signals from mechanical systems are usually corrupted by unrelated noises due to complicated transfer path modulations and component coupling. To solve the above problems, this paper proposed the dynamic temporal denoise neural network with multi-head attention (DTDNet). Firstly, this model transforms one-dimensional signals into two-dimensional tensors based on the periodic self-similarity of signals, employing multi-scale two-dimensional convolution kernels to extract signal features both within and across periods. Secondly, for the problem of lacking denoising structure in traditional convolutional neural networks, a temporal variable denoise (TVD) module with dynamic nonlinear processing is proposed to filter the noises. Lastly, a multi-head attention fusion (MAF) module is used to weight the denoted features of signals with different periods. Evaluation on two datasets, Case Western Reserve University bearing dataset (single sensor) and Real aircraft sensor dataset (multiple sensors), demonstrates that the DTDNet can reduce the useless noises in signals and achieve a remarkable improvement in classification performance compared with the state-of-the-art method. DTDNet provides a high-performance solution for potential noise that may occur in actual fault diagnosis tasks, which has important application value.
The Use of Laser Sensing for Solving Meteorological Problems Related to Researching and Ensuring the Safety of Space Flights
Authors: Boreysho Anatoly S. , Konyaev Maxim A. , Strakhov Sergey Y. , Trilis Andrey V. , Sotnikova Natalia V.
Published: October 2024

This paper is devoted to the issue of using laser (lidar) sensing to determine wind speed and direction when solving practical problems during the analysis of meteorological conditions in the area around spaceports. This issue is relevant both for making decisions on the possibility of a safe launch of a launch vehicle and for conducting search and rescue operations using groups of manned and unmanned aerial vehicles. Based on numerical and experimental modeling, it is shown that lidars provide highly accurate measurements of wind speed profiles and allow for the determination of weak wind shear in vertical and horizontal directions. This paper proposes a method for determining the main parameters of lidar sensing (range, resolution, detectability, etc.), which allows for the capabilities of this technology in solving the practical problems of meteorological monitoring to be predicted. Of particular interest in this article are experimental modeling data verifying the proposed calculation methods and the experimental determination of the capabilities of lidar diagnostics. This paper summarizes the data from multi-month experiments measuring wind speed in clear weather conditions when other means of remote diagnostics are ineffective. As a result of the experiments, a statistical distribution of the maximum range of wind speed measurement in normal weather conditions with natural variation in the concentration of scattering particles in the atmosphere was obtained. This article also discusses the possibility of combining lidars and meteorological radars for the meteorological support of flights.
Research on Abnormal State Detection of CZ Silicon Single Crystal Based on Multimodal Fusion
Authors: Jiang Lei , Wei Haotan , Liu Ding
Published: October 2024

The Czochralski method is the primary technique for single-crystal silicon production. However, anomalous states such as crystal loss, twisting, swinging, and squareness frequently occur during crystal growth, adversely affecting product quality and production efficiency. To address this challenge, we propose an enhanced multimodal fusion classification model for detecting and categorizing these four anomalous states. Our model initially transforms one-dimensional signals (diameter, temperature, and pulling speed) into time–frequency domain images via continuous wavelet transform. These images are then processed using a Dense-ECA-SwinTransformer network for feature extraction. Concurrently, meniscus images and inter-frame difference images are obtained from the growth system’s meniscus video feed. These visual inputs are fused at the channel level and subsequently processed through a ConvNeXt network for feature extraction. Finally, the time–frequency domain features are combined with the meniscus image features and fed into fully connected layers for multi-class classification. The experimental results show that the method can effectively detect various abnormal states, help the staff to make a more accurate judgment, and formulate a personalized treatment plan for the abnormal state, which can improve the production efficiency, save production resources, and protect the extraction equipment.
Magnetic Garments Promote Parasympathetic Dominance and Improve Sleep Quality in Male Long-Distance Runners Following a 30 km Run
Authors: Nobue Ayaka , Sano Kanae , Ishikawa Masaki
Published: October 2024

This study aimed to investigate the effects of high-intensity running on the autonomic nervous system and sleep quality of male long-distance runners and to examine the impact of wearing magnetic garments on these parameters. Fifteen highly trained male collegiate long-distance runners participated in a randomized, double-blind crossover study. Participants completed two 30 km runs (30k-RUN) during a 10-day training camp. After each run, they wore either magnetic (MAG) or non-magnetic control (CTRL) garments. Sleep quality and heart rate variability (HRV) were assessed using a wrist-worn device before and after each 30k-RUN. Wearing MAG garments post-30k-RUN resulted in significantly longer deep sleep duration compared to CTRL. HRV analysis revealed that the MAG condition led to a significantly higher root mean square of successive RR interval differences and high-frequency power, indicating enhanced parasympathetic activity. The low-frequency to high-frequency ratio was significantly lower in MAG than in CTRL. Perceived recovery scores were significantly higher in MAG than in CTRL. The findings of this study suggest that wearing magnetic garments following high-intensity endurance running may promote parasympathetic dominance and improve sleep quality in male long-distance runners. These findings indicate that magnetic garments may be a practical method for enhancing recovery in athletes following intense training.
Identification of Ginseng Radix et Rhizoma, Panacis Quinquefolii Radix, Notoginseng Radix et Rhizoma, and Platycodonis Radix Based on UHPLC-QTOF-MS and “Matrix Characteristics”
Authors: Zhang Jiating , He Fangliang , Wang Xianrui , Jing Wenguang , Li Minghua , Guo Xiaohan , Cheng Xianlong , An Fudong , Wei Feng
Published: October 2024

Ginseng Radix et Rhizoma (GRR), Panacis Quinquefolii Radix (PQR), Notoginseng radix et rhizoma (NRR) and Platycodonis Radix (PR) are often confused in the material market because of similar appearances and characteristics. Moreover, chemical identification methods tend to characterize the whole herb with regard to a single or a few components, which is an inaccurate representation and does not demonstrate the effective utilization of unknown components, and the result is unconvincing. In order to strengthen quality control, improve identification efficiency, and realize digital identification at the individual level of traditional Chinese medicine (TCM), we have put forward the “matrix characteristics” of TCM, combined with a UHPLC-QTOF-MS analysis to explore and realize the digital identification of GRR, PQR, NRR, and PR. The mass spectrometry was quantized to extract common data from different batches of the same TCMs as their matrix characteristics, and the matching credibility (M) was given by matching the “matrix characteristics” with unknown Chinese medicines. The results show that within a reasonable parameter threshold range, the M of four TCMs was higher than 92.00% compared with their own “matrix characteristics”, which was significantly higher than the M ranked second. Furthermore, the digital identification of four TCMs can be successfully realized based on the UHPLC-QTOF-MS analysis and “matrix characteristics”. This has important reference significance for developing the digital identification of GRR at an individual level based on UPLC-QTOF-MS and “matrix characteristics”.
The Influence of the Convergence of Digital and Green Technologies on Regional Total Factor Productivity: Evidence from 30 Provinces in China
Authors: Wang Yachu , Hou Renyong
Published: October 2024

This paper explores the development of digital and green collaboration, empirically examining both the linear and nonlinear impacts of the convergence of digital and green technologies on regional total factor productivity (TFP). Using data from 30 provinces and cities in China from 2010 to 2022, the study constructs a panel threshold model with business environment and intellectual property protection as threshold variables to investigate their roles in mediating the effects of digital–green technology convergence on regional TFP. The key findings are as follows: (1) The linear analysis reveals that the convergence of digital and green technologies significantly enhances regional TFP. (2) The nonlinear analysis demonstrates a nonlinear relationship between the convergence of these technologies and regional TFP. (3) The threshold effect test identifies a single-threshold effect for the business environment, showing that once the threshold is surpassed, the positive influence of the convergence of digital and green technologies on TFP increases. Additionally, a double-threshold effect is found with intellectual property protection; as intellectual property protection surpasses the first and second thresholds, the positive impact initially strengthens but then weakens. (4) A heterogeneity analysis shows that the convergence of digital and green technologies significantly contributes to TFP in the eastern regions, while the effects in central and western regions are not significant.
Bearing Characteristics of Deep Cement Mixing Integrated Drilling, Mixing and Jetting Piles Based on Numerical Simulation
Authors: Wang Yang , Zhang Yuhe , Zhang Kaixing , Rong Yu , Xu Runze , Li Jie , Feng Weizhe , Sang Zihan , Yao Zhanyong , Yao Kai
Published: October 2024

The Deep Cement Mixing Integrated Drilling, Mixing and Jetting (DMJ) technique has been developed through the installation of high-pressure spray holes at the mixing blades, with the objective of enhancing the bearing capacity of deep-mixed piles in the Yellow River floodplain. In order to enhance the bearing capacity of the foundation, variable-modulus piles and capped piles were incorporated within the DMJ piles. Engineering applications have demonstrated that DMJ piles can effectively address the issue of foundation reinforcement in the Yellow River floodplain region, minimize the wastage of cement, and reduce the environmental pollution associated with waste slurry. Nevertheless, a comprehensive study of the relevant factors is still lacking in the available literature. This study addresses this gap by conducting a numerical simulation of these two types of DMJ piles based on the preliminary field test data, with the objective of analyzing both the single-pile-bearing characteristics and the composite foundation-bearing characteristics. Furthermore, the study seeks to optimize the DMJ pile’s structure based on the simulation results. The findings demonstrate that the premature failure of a single pile during the bearing process can be averted if the modulus of the pile core reaches a minimum of 0.3 GPa or if the pile cap thickness exceeds 1 m. The utilization of large-diameter drilling, stirring and spraying piles can markedly enhance the bearing capacity of the composite foundation and mitigate the differential settlement of pile and soil. The spacing of the pile has been identified as a significant factor influencing the differential settlement of pile and soil. Consequently, this study also examines the impact of pile spacing on the differential settlement of piles and soil.
The Prevalence of Polycystic Ovary Syndrome and Fibromyalgia in Women with Borderline Personality Disorder and Their Association with Childhood Abuse
Authors: Mu Eveline , Tsinanis Tia , de Boer Kathleen , Thomas Elizabeth H. X. , Kulkarni Jayashri
Published: October 2024

Childhood abuse is a significant factor in the development of borderline personality disorder (BPD) and many physical health disorders, including polycystic ovary syndrome (PCOS) and fibromyalgia. This study aimed to examine the prevalence of PCOS and fibromyalgia in women with BPD compared to the general population. Additionally, it compared the prevalence of these conditions in women who experienced different types of childhood abuse (emotional, physical, or sexual). Participants were identified from the Multidisciplinary Alfred Psychiatry research centre’s Women’s Mental Health Clinic database, including 150 women diagnosed with BPD. Clinicians collected information on PCOS, fibromyalgia, and trauma history. Results showed higher rates of PCOS (17.3%) and fibromyalgia (8.7%) in women with BPD compared to general population samples. Emotional abuse was associated with the highest PCOS prevalence (22.8%), while co-occurring physical, sexual, and emotional abuse was linked to the highest fibromyalgia prevalence. These findings highlight the significant prevalence of PCOS and fibromyalgia in women with BPD and their association with childhood abuse.
Analysis of natural health resources for the development of health tourism in Bulgaria
Authors:   Patrice Lumumba Russian People’s Friendship University, Moscow, Balev N. N. , Zeveke O. Yu. ,   Patrice Lumumba Russian People’s Friendship University, Moscow
Published: October 2024

The article examines the potential of natural healing resources for the development of health tourism in Bulgaria.
Foreign Economic Activities of The Russian Federation: Contemporary Problems and Prospects
Authors:   Vladimir State University named after Alexander Grigorievich and Nikolai Grigorievich Stoletovs, Vladimir, Aksenov I. A.
Published: October 2024

Modern conditions for the development of foreign economic activity of the Russian Federation are formed under the influence of many factors, including international sanctions, economic diversification, development of transport and digital infrastructure, as well as active international cooperation. In the context of global economic and political changes, the Russian Federation seeks to adapt and look for new opportunities to strengthen its position in the world market. The article identifies the features of the organization of foreign economic activity in the Russian Federation taking into account the sanctions pressure, in particular, reflects the features of the decline in foreign trade, limited access to international fi nance, difficulties in international settlements, change of trading partners, problems with technology imports, problems with logistics. The article analyzes the main problems faced by the Russian Federation in its foreign economic strategy. In the article, the author examines in detail the main problems faced by the Russian Federation in the formation of its foreign economic strategy, and within the framework of each problem, considers the prospects for its solution, taking into account the established development trends, such as: strengthening economic cooperation with Asian countries, in particular with China and India, as a strategic priority; the use of new technologies and innovations to increase the competitiveness of Russian goods in world markets; development of transport and logistics infrastructure to improve export opportunities. The article reflects the aspect of a comprehensive approach to solving current problems and implementing strategic tasks aimed at sustainable development of foreign economic activity of the Russian Federation in the long term.