bluuebunny/crossref_metadata_2025 huggingface dataset:
Unsupervised Image Segmentation on 2D Echocardiogram
Authors: Cacao Gabriel Farias , Du Dongping , Nair Nandini
Published: November 2024

Echocardiography is a widely used, non-invasive imaging technique for diagnosing and monitoring heart conditions. However, accurate segmentation of cardiac structures, particularly the left ventricle, remains a complex task due to the inherent variability and noise in echocardiographic images. Current supervised models have achieved state-of-the-art results but are highly dependent on large, annotated datasets, which are costly and time-consuming to obtain and depend on the quality of the annotated data. These limitations motivate the need for unsupervised methods that can generalize across different image conditions without relying on annotated data. In this study, we propose an unsupervised approach for segmenting 2D echocardiographic images. By combining customized objective functions with convolutional neural networks (CNNs), our method effectively segments cardiac structures, addressing the challenges posed by low-resolution and gray-scale images. Our approach leverages techniques traditionally used outside of medical imaging, optimizing feature extraction through CNNs in a data-driven manner and with a new and smaller network design. Another key contribution of this work is the introduction of a post-processing algorithm that refines the segmentation to isolate the left ventricle in both diastolic and systolic positions, enabling the calculation of the ejection fraction (EF). This calculation serves as a benchmark for evaluating the performance of our unsupervised method. Our results demonstrate the potential of unsupervised learning to improve echocardiogram analysis by overcoming the limitations of supervised approaches, particularly in settings where labeled data are scarce or unavailable.
A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling
Authors: Han Pujie , Hu Wentao , Zhai Zhengjun , Huang Min
Published: November 2024

ARINC 653 Part 1 Supplement 5 (ARINC 653P1-5) provides temporal partitioning capabilities for real-time applications running on the multicore processors in Integrated Modular Avionics (IMAs) systems. However, it is difficult to schedule a set of ARINC 653 multicore partitions to achieve a minimum processor occupancy. This paper proposes a model-based optimization method for ARINC 653 multicore partition scheduling. The IMA multicore processing system is modeled as a network of timed automata in UPPAAL. A parallel genetic algorithm is employed to explore the solution space of the IMA system. Owing to a lack of priori information for the system model, the configuration of genetic operators is self-adaptively controlled by a Q-learning algorithm. During the evolution, each individual in a population is evaluated independently by compositional model checking, which verifies each partition in the IMA system and combines all the schedulability results to form a global fitness evaluation. The experiments show that our model-based method outperforms the traditional analytical methods when handling the same task loads in the ARINC 653 multicore partitions, while alleviating the state space explosion of model checking via parallelization acceleration.
Combining UAV Multispectral and Thermal Infrared Data for Maize Growth Parameter Estimation
Authors: Yu Xingjiao , Huo Xuefei , Qian Long , Du Yiying , Liu Dukun , Cao Qi , Wang Wen’e , Hu Xiaotao , Yang Xiaofei , Fan Shaoshuai
Published: November 2024

The leaf area index (LAI) and leaf chlorophyll content (LCC) are key indicators of crop photosynthetic efficiency and nitrogen status. This study explores the integration of UAV-based multispectral (MS) and thermal infrared (TIR) data to improve the estimation of maize LAI and LCC across different growth stages, aiming to enhance nitrogen (N) management. In field trials from 2022 to 2023, UAVs captured canopy images of maize under varied water and nitrogen treatments, while the LAI and LCC were measured. Estimation models, including partial least squares regression (PLS), convolutional neural networks (CNNs), and random forest (RF), were developed using spectral, thermal, and textural data. The results showed that MS data (spectral and textural features) had strong correlations with the LAI and LCC, and CNN models yielded accurate estimates (LAI: R2 = 0.61–0.79, RMSE = 0.02–0.38; LCC: R2 = 0.63–0.78, RMSE = 2.24–0.39 μg/cm2). Thermal data reflected maize growth but had limitations in estimating the LAI and LCC. Combining MS and TIR data significantly improved the estimation accuracy, increasing R2 values for the LAI and LCC by up to 23.06% and 19.01%, respectively. Nitrogen dilution curves using estimated LAIs effectively diagnosed crop N status. Deficit irrigation reduced the N uptake, intensifying the N deficiency, while proper water and N management enhanced the LAI and LCC.
An Integrated Profiling of Liver Metabolome and Transcriptome of Pigs Fed Diets with Different Starch Sources
Authors: Yu Miao , Li Zhenming , Cui Yiyan , Rong Ting , Tian Zhimei , Deng Dun , Liu Zhichang , Zhang Ruiyang , Ma Xianyong
Published: November 2024

Diets containing higher-amylose-content starches were proved to have some beneficial effects on monogastric animals, such as promoting the proliferation of intestinal probiotics. However, current research on the effects of diets with different starch sources on animals at the extraintestinal level is still very limited. We hypothesized that diets with different starch sources may affect lipid-related gene expression and metabolism in the liver of pigs. This study aimed to use adult pig models to evaluate the effects of diets with different starch sources (tapioca starch, TS; pea starch, PS) on the liver gene expressions and metabolism. In total, 48 growing pigs were randomly assigned to the TS and PS diets with 8 replicate pens/group and 3 pigs per pen. On day 44 of the experiment, liver samples were collected for metabolome and transcriptome analysis. Metabolome data suggested that different starch sources affected (p < 0.05) the metabolic patterns of liver. Compared with the TS diet, the PS diet increased (p < 0.05) some unsaturated fatty acids and several amino acids or peptide levels in the liver of pigs. Moreover, transcriptome data indicated the PS diets elevated (p < 0.05) fatty acid β-oxidation-related gene expression in the liver of pigs, and reduced (p < 0.05) unsaturated fatty acid metabolism-related gene expression. The results of quantitative real-time PCR confirmed that the PS diet upregulated (p < 0.05) the expression of acyl-CoA dehydrogenase very long chain (ACADVL), carnitine palmitoyl transferase (CPT) 1A, and malonyl-CoA decarboxylase (MLYCD), and downregulated (p < 0.05) the expression level of cytochrome P450 2U1 (CYP2U1) and aldehyde dehydrogenase 1B1 (ALDH1B1) in the liver. In addition, the results of a Mantel test indicated the muscle fatty acids were significantly closely correlated (p < 0.05) with liver gene expressions and metabolites. In summary, these findings suggest that diets containing higher amylose starches improved the lipid degradation and the unsaturated fatty acid levels in pig livers, and thus can generate some potential beneficial effects (such as anti-inflammatory and antioxidant) on pig health.
Caspase-8-and Gasdermin D (GSDMD)-Dependent PANoptosis Participate in the Seasonal Atrophy of Scented Glands in Male Muskrats
Authors: Tong Xiaofeng , Zhao Xuefei , Ma Yue , Li Haimeng , Zhang Jinpeng , Zhang Zuoyang , Hua Sirui , Li Bo , Zhang Wei , Zhang Yu , Bai Suying
Published: November 2024

The muskrat (Ondatra zibethicus) is an animal with special economic significance whose scented glands rapidly atrophy during the non-breeding season, but the mechanism of atrophy is not clear, with significant differences in apoptotic and pyroptotic signaling pathway expression according to transcriptome sequencing. During the non-breeding season, key apoptosis-related genes such as Tnfr1 (TNF Receptor Superfamily Member 1A), TRADD (TNFRSF1A Associated via Death Domain), FADD (Fas Associated via Death Domain), Casp-8 (Cysteine-aspartic proteases-8), and Bax (Bcl-associated X protein) were upregulated in the scented glands, while Bcl2 (B-cell lymphoma-2) expression was downregulated. In the classical pyroptosis pathway, the mRNA expression levels of key genes including Nlrp3 (the Nod-like receptor family pyrin domain-containing 3), ASC (the apoptosis-associated speck-like protein), Casp-1 (Cysteine-aspartic proteases-1), Gsdmd (Gasdermin D), and IL-1β (Interleukin 1 Beta) were higher during the non-breeding season, similar to the transcription level of Ripk1 (Receptor Interacting Serine/Threonine Kinase 1) in the non-canonical pyroptosis pathway, while TAK1 (transforming growth factor kinase) expression was downregulated in this latter pathway. TUNEL assays and immunofluorescence analysis indicated increased apoptosis and GSDMD and Caspase-8 protein levels during the non-breeding season. Indeed, the protein levels of GSDMD-N, Caspase-8 p43, and Caspase-8 p18 were significantly higher during the non-breeding season, while the GSDMD levels were significantly lower compared to the secretion season. These results suggest that apoptosis and pyroptosis play regulatory roles in scented gland atrophy and that there is an interplay between them during this process.
Screening and Functional Prediction of Rumen Microbiota Associated with Methane Emissions in Dairy Cows
Authors: Bao Jiatai , Wang Lei , Li Shanshan , Guo Jiahe , Ma Pan , Huang Xixia , Guo Gang , Zhang Hailiang , Wang Yachun
Published: November 2024

Agricultural activities are a significant contributor to global greenhouse gas emissions, accounting for 14.5% of total anthropogenic emissions. Specifically, greenhouse gas emissions from beef cattle and dairy cattle constitute 35% and 30% of total global livestock emissions, respectively. This study focuses on dairy cattle, exploring the complex relationships between rumen microbiota and methane emission. The methane emissions of 968 lactating Holstein cows were measured using a laser methane detector (LMD, Shanghai Hesai Technology Co., Ltd., Shanghai, China). Among the measured cows, 107 individuals were further selected into high (HME) and low methane-emitting (LME) groups, including 50 cows in the HME group and 57 in the LME group. This study analyzed differences in rumen microbiota and microbial functions between cows with varying levels of methane emissions. The results showed significant differences in the Simpson and Pielou indices of rumen bacterial communities between the HME and LME groups. Beta diversity analysis revealed significant differences in microbial community structure between the two groups. It was found that the abundance of Bacteroidales and Prevotellaceae in the rumen of cows in the HME group cows was significantly higher than that of cows in the LME group (LDA > 3, p < 0.05). Additionally, bacterial functions related to biosynthesis and carbohydrate metabolism were more active in the HME group. This study revealed distinct differences in the rumen bacterial communities between HME and LME cow in Chinese Holstein cattle, and identified specific bacteria and their functional differences in the HME group. The microbial characteristics and metabolic pathways provide new insights for developing strategies to reduce methane emissions, supporting the sustainable development of the dairy industry.
Research on Behavior Recognition and Online Monitoring System for Liaoning Cashmere Goats Based on Deep Learning
Authors: Chen Geng , Yuan Zhiyu , Luo Xinhui , Liang Jinxin , Wang Chunxin
Published: November 2024

Liaoning Cashmere Goats are a high-quality dual-purpose breed valued for both their cashmere and meat. They are also a key national genetic resource for the protection of livestock and poultry in China, with their intensive farming model currently taking shape. Leveraging new productivity advantages and reducing labor costs are urgent issues for intensive breeding. Recognizing goatbehavior in large-scale intelligent breeding not only improves health monitoring and saves labor, but also improves welfare standards by providing management insights. Traditional methods of goat behavior detection are inefficient and prone to cause stress in goats. Therefore, the development of a convenient and rapid detection method is crucial for the efficiency and quality improvement of the industry. This study introduces a deep learning-based behavior recognition and online detection system for Liaoning Cashmere Goats. We compared the convergence speed and detection accuracy of the two-stage algorithm Faster R-CNN and the one-stage algorithm YOLO in behavior recognition tasks. YOLOv8n demonstrated superior performance, converging within 50 epochs with an average accuracy of 95.31%, making it a baseline for further improvements. We improved YOLOv8n through dataset expansion, algorithm lightweighting, attention mechanism integration, and loss function optimization. Our improved model achieved the highest detection accuracy of 98.11% compared to other state-of-the-art (SOTA) target detection algorithms. The Liaoning Cashmere Goat Online Behavior Detection System demonstrated real-time detection capabilities, with a relatively low error rate compared to manual video review, and can effectively replace manual labor for online behavior detection. This study introduces detection algorithms and develops the Liaoning Cashmere Goat Online Behavior Detection System, offering an effective solution for intelligent goat management.
SOD1 Is an Integral Yet Insufficient Oxidizer of Hydrogen Sulfide in Trisomy 21 B Lymphocytes and Can Be Augmented by a Pleiotropic Carbon Nanozyme
Authors: Mouli Karthik , Liopo Anton V. , Suva Larry J. , Olson Kenneth R. , McHugh Emily A. , Tour James M. , Derry Paul J. , Kent Thomas A.
Published: November 2024

Down syndrome (DS) is a multisystemic disorder that includes accelerated aging caused by trisomy 21. In particular, overexpression of cystathionine-β-synthase (CBS) is linked to excess intracellular hydrogen sulfide (H2S), a mitochondrial toxin at higher concentrations, which impairs cellular viability. Concurrent overexpression of superoxide dismutase 1 (SOD1) may increase oxidative stress by generating excess hydrogen peroxide (H2O2) while also mitigating the toxic H2S burden via a non-canonical sulfide-oxidizing mechanism. We investigated the phenotypic variability in basal H2S levels in relation to DS B lymphocyte cell health and SOD1 in H2S detoxification. The H2S levels were negatively correlated with the DS B lymphocyte growth rates but not with CBS protein. Pharmacological inhibition of SOD1 using LCS-1 significantly increased the H2S levels to a greater extent in DS cells while also decreasing the polysulfide products of H2S oxidation. However, DS cells exhibited elevated H2O2 and lipid peroxidation, representing potential toxic consequences of SOD1 overexpression. Treatment of DS cells with a pleiotropic carbon nanozyme (pleozymes) decreased the total oxidative stress and reduced the levels of the H2S-generating enzymes CBS and 3-mercaptopyruvate sulfurtransferase (MPST). Our results indicate that pleozymes may bridge the protective and deleterious effects of DS SOD1 overexpression on H2S metabolism and oxidative stress, respectively, with cytoprotective benefits.
Myokines and Their Potential Protective Role Against Oxidative Stress in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)
Authors: Bucarey José Luis , Trujillo-González Isis , Paules Evan M. , Espinosa Alejandra
Published: November 2024

Myokines, bioactive peptides released by skeletal muscle, have emerged as crucial regulators of metabolic and protective pathways in peripheral tissues, particularly in combating oxidative stress and inflammation. Their plasma concentration significantly increases following exercise, offering valuable insights into the role of physical activity in preventing sarcopenia and mitigating metabolic diseases, including obesity, diabetes, and metabolic dysfunction-associated steatotic liver disease (MASLD). This review focuses on discussing the roles of specific myokines in activating intracellular signaling pathways within the liver, which confer protection against steatosis and lipid peroxidation. We detail the mechanism underlying lipid peroxidation and highlight the liver’s antioxidant defenses, such as glutathione (GSH) and glutathione peroxidase 4 (GPX4), which are pivotal in reducing ferroptosis. Furthermore, we provide an in-depth analysis of key myokines, including myostatin, brain-derived neurotrophic factor (BDNF), and irisin, among others, and their potential impact on liver function. Finally, we discuss the molecular mechanisms through which these myokines influence oxidate stress and lipid metabolism, emphasizing their capacity to modulate antioxidant responses in the liver. Finally, we underscore the therapeutic potential of exercise as a non-pharmacological intervention to enhance myokine release, thereby preventing the progression of MASD through improved hepatic antioxidant defenses. This review represents a comprehensive perspective on the intersection of exercise, myokine biology, and liver health.
A Tuning Method for Speed Tracking Controller Parameters of Autonomous Vehicles
Authors: Chen Jianqiao , Tian Guofu
Published: November 2024

Autonomous driving technology, as a key component of intelligent transportation systems, has gained considerable attention in recent years. While significant progress has been made in areas such as path planning, obstacle detection, and navigation, relatively less focus has been placed on vehicle speed control, which plays a critical role in ensuring safe and efficient operation, especially in complex and dynamic road environments. This paper addresses the challenge of speed tracking by proposing a genetic algorithm-based optimization method for PID controller parameters. Traditional PID controllers often struggle with maintaining accuracy and response time in highly variable conditions, but by optimizing these parameters through the genetic algorithm, substantial improvements in speed control precision and adaptability can be achieved, enhancing the vehicle’s ability to navigate real-world driving scenarios with greater stability. The experimental results clearly indicate that the autonomous vehicle, after PID parameter optimization using a genetic algorithm, demonstrated the following speed tracking errors: when the road surface adhesion coefficient was 0.5, the maximum speed tracking error was 0.22, the average value was 0.063, and the standard deviation was 0.124; when the adhesion coefficient was 0.6, the maximum speed tracking error was 0.180, the average value was 0.056, and the standard deviation was 0.099; when the adhesion coefficient was 0.8, the maximum speed tracking error was 0.179, the average value was 0.056, and the standard deviation was 0.098. This method significantly improved the controller’s performance in maintaining the desired speed, even under challenging conditions. These findings highlight the potential of genetic algorithms in supporting the future development of autonomous driving technology, ensuring its successful integration into intelligent transportation systems.
Research on the Designing and Experimental Performance Evaluation of a New Sand Control Screen for Argillaceous Fine Silt Gas Hydrate Reservoirs
Authors: Wang Echuan , Liao Hualin , Zhang Heen
Published: November 2024

Argillaceous fine silt hydrate reservoirs have a clay content of 20–25% and a median sand particle size of 10–15 um. Sand control is extremely difficult, restricting the continuous and stable testing of gas hydrate. This paper focuses on the sand production mechanisms, plugging characteristics, and clogging mechanisms of these hydrate reservoirs. Based on the actual characteristics of hydrate reservoirs, it presents an understanding of the sand production mechanism of argillaceous fine silt. The characteristics and properties of three different sand control methods and six kinds of sand control screens are analyzed. Clear design concepts for sand control screens in argillaceous fine silt hydrate reservoirs are proposed. Two types of new sand control screen with metal filter screens and pre-filled screens have been innovatively designed, and the sand control ability and overflow performance of the screens are evaluated using the meter production index conversion method. Sand production simulation and comprehensive experimental evaluation and analysis of the flow performance of seven kinds of screens (themselves from two categories of screens) were carried out using a self-made special experimental testing device. The experimental results show that the newly designed screens have good flow performance and can meet the requirements of a certain gas production rate. Specifically, Class A metal screens (60/70 mesh) and Class B pre-filled screens (40/70 mesh) have excellent sand control capacity and flow performance, with 10 g sand output and 300 L total water output, thus fulfilling the sand control requirements and achieving the purpose of “effective sand control, prevention without plugging, and continuous stable production” of argillaceous fine silt gas hydrate reservoirs. They therefore provide a reference for future research on sand control and new screen designs for argillaceous fine silt hydrate reservoirs.
Enhancing Pose Estimation Using Multiple Graphical Markers with Spatial and Temporal Outlier Detection
Authors: Kim Doyoung , Bong Jae Hwan , Jeong Seongkyun
Published: November 2024

This paper presents a novel approach to enhance pose estimation accuracy and precision in mobile robotics using multiple graphical markers. While traditional single-marker methods using graphical markers such as ArUco offer simple implementation, their performance is susceptible to environmental variations and measurement errors. To address these limitations, we propose a robust pose estimation algorithm that leverages multiple markers simultaneously. Our approach incorporates two key mechanisms: spatial consistency verification to detect invalid markers within the marker array, and temporal stability analysis to identify and exclude outlier measurements. The algorithm enhances pose estimation accuracy by averaging measurements from valid markers while preventing any single marker from dominating the estimation process. The effectiveness of our approach was validated through experiments using both fixed and drone-mounted camera configurations. The results demonstrated that the pose estimation using multiple markers significantly improved both accuracy and precision compared with single-marker approaches. In fixed-camera experiments, the proposed method showed reduced mean errors and standard deviations in both position and orientation measurements across various camera poses. Similarly, in drone-mounted camera experiments, our approach exhibited superior stability with significantly lower measurement variations during hovering maneuvers. These improvements were particularly pronounced in challenging scenarios, such as when the camera was tilted at large angles relative to the marker plane. This research contributes to the advancement of reliable pose estimation methodologies in mobile robotics and autonomous systems, with potential applications across diverse environments where precise position and orientation measurements are crucial.
Single-Handed Gesture Recognition with RGB Camera for Drone Motion Control
Authors: Yun Guhnoo , Kwak Hwykuen , Kim Dong Hwan
Published: November 2024

Recent progress in hand gesture recognition has introduced several natural and intuitive approaches to drone control. However, effectively maneuvering drones in complex environments remains challenging. Drone movements are governed by four independent factors: roll, yaw, pitch, and throttle. Each factor includes three distinct behaviors—increase, decrease, and neutral—necessitating hand gesture vocabularies capable of expressing at least 81 combinations for comprehensive drone control in diverse scenarios. In this paper, we introduce a new set of hand gestures for precise drone control, leveraging an RGB camera sensor. These gestures are categorized into motion-based and posture-based types for efficient management. Then, we develop a lightweight hand gesture recognition algorithm capable of real-time operation on even edge devices, ensuring accurate and timely recognition. Subsequently, we integrate hand gesture recognition into a drone simulator to execute 81 commands for drone flight. Overall, the proposed hand gestures and recognition system offer natural control for complex drone maneuvers.
Compression Law and Settlement Calculation Method of Over-Wet Soil Based on Large Samples
Authors: Peng Bo , Wu Lijian , Feng Ruiling , Song Changjun , Liu Jiangxin , Bian Xiaolin
Published: November 2024

Previous studies have shown that over-wet soil is challenging to compact and exhibits large creep deformation. The consolidation test of small specimens cannot accurately reflect the compression law, and creep is underestimated owing to size effects, which affects the engineering quality. In order to accurately analyze the compression process of over-wet soil and establish its settlement calculation method, this study focuses on over-wet soil in Anhui Province, China, and uses a large-sized tester to load and analyze its compression law. The thermogravimetric analysis method was employed to investigate the changes in water with different binding forces during the compression process, and the settlement calculation method for over-wet soil was explored. The results show that the creep of over-wet soil is large and long-lasting, and the three-stage consolidation division method based on the d−t curve is more effective in analyzing its regularity. The creep of over-wet soil is directly proportional to its water content. When the load exceeds the pre-consolidation pressure, the creep deformation becomes more significant, accounting for about 60% of the deformation under a single level load. It is recommended to use the creep coefficient (λ) for calculation. The results of the thermogravimetric analysis indicate that during the primary consolidation stage, free water is discharged, and weakly bound water is mainly discharged during the third consolidation stage, which is the main cause of creep. Finally, based on the relationship between the creep strain and water content of large samples, a calculation method for the settlement of over-wet soil foundations based on the layered summation method was established, which had a higher prediction accuracy than the conventional layered summation method. The results of this study will help clarify the deformation process and principle of over-wet soil and improve the quality of engineering.
Evaluation of the Nutritional Value of Insect-Based Complete Pet Foods
Authors: Jacuńska Weronika , Biel Wioletta , Zych Krzysztof
Published: November 2024

Since the legalization of insect protein in pet food, a variety of products incorporating this ingredient have emerged on the market. Although edible insects are acknowledged for high protein content, chitin can also elevate the quantity of indigestible carbohydrates. The objective of this study was to evaluate the nutritional adequacy of fourteen complete dog foods containing edible insects in accordance with the FEDIAF nutritional guidelines. Due to the use of insects as the predominant animal component in all diets, analyses of dietary fiber fractions were carried out to estimate the content of indigestible carbohydrates. The analyses included the assessment of chemical composition, calcium, and phosphorus levels and metabolizable energy. The findings were then compared with the data provided by the manufacturers. All diets were found to meet the minimum recommended levels from the FEDIAF nutritional guidelines for protein (18.0 g/100 g DM) and fat (5.5 g/100 g DM). However, discrepancies were noted between the label data and analysis results. The results for the dietary fiber fraction differed from the crude fiber content, which is consistent with the imprecision inherent to the crude fiber determination method. In one food, there was a discrepancy of up to 19.21 g between the NDF fraction and the crude fiber content. Calcium levels were inadequate in two foods, and furthermore, twelve foods exhibited an abnormal calcium/phosphorus ratio. These findings indicate that while edible insects can be a valuable protein source, their inclusion may lead to increased indigestible carbohydrates, potentially causing digestive issues and gastric discomfort in dogs.
Tracking Control and Backlash Compensation in an Inverted Pendulum with Switched-Mode PID Controllers
Authors: Awan Aisha Akbar , Khan Umar S. , Awan Asad Ullah , Hamza Amir
Published: November 2024

In electromechanical systems, backlash in gear trains can lead to a degradation in control performance. We propose a drive–anti-drive mechanism to address this issue. It consists of two DC motors that operate in opposite directions. One motor acts as the drive, while the other serves as the anti-drive to compensate for the backlash. This work focuses on switching between the drive and anti-drive motors, controlled by a switched-mode PID controller. Simulation results on an inverted pendulum demonstrate that the proposed scheme effectively compensates for backlash, improving position accuracy and control. This switched controller approach enhances the performance of electromechanical systems, particularly where gear backlash poses challenges to closed-loop performance.
Storied Rocks: Portals to Other Dimensions
Authors: Stoffle Richard , Van Vlack Kathleen , Bell Alannah , Eguino Uribe Bianca
Published: November 2024

Storied Rocks (Tumpituxwinap) is a term of reference used by the Numic speaking tribal elders whom we have worked with for over 60 years on an estimated 200 ethnographic studies. Key to this analysis are the protocols for approaching, interacting, and using the places where Storied Rocks have been located. Concomitant with these traditional protocols are ones established to resolve the curiosity of non-Natives about why they are in a particular place and what they mean. This analysis shares the cultural understandings of tribal representatives who participate in these ethnographic studies. Studies used in the analysis were funded by U.S. federal agencies, supported by federally recognized Native American tribal governments, and composed with the cultural understandings shared and made public by tribally appointed elders to clarify the conundrums that are Storied Rocks.
On Resonance Enhancement of E1-E2 Nondipole Photoelectron Asymmetries in Low-Energy Ne 2p Photoionization
Authors: Dolmatov Valeriy K. , Manson Steven T.
Published: November 2024

Earlier, a significant enhancement of the nondipole parameters γ2p, δ2p, and ζ2p=γ2p+3δ2p in the photoelectron angular distribution for Ne 2p photoionization was predicted, owing to resonance interference between dipole (E1) and quadrupole (E2) transitions. This enhancement manifests as narrow resonance spikes in the parameters due to the low-energy 2s→3p and 2s→4p dipole, as well as the 2s→3d quadrupole autoionizing resonances. Given the unique nature of this predicted enhancement, it requires further validation, specifically regarding whether these narrow spikes in γ2p, δ2p and ζ2p will or will not retain their values for experimental observation if one accounts for a typical finite frequency spread in the ionizing radiation. To address this, we revisit the previous study, now incorporating the effect of frequency spread in the ionizing radiation, assuming a spread as large as 5 meV at the half-maximum of the radiation’s intensity. In the present paper we demonstrate that while the frequency spread does affect the resonance enhancement of γ2p, δ2p and ζ2p, these parameters still retain quantitatively significant values to be observed experimentally. The corresponding calculations were performed using the random phase approximation with exchange, which accounts for interchannel coupling in both dipole and quadrupole photoionization amplitudes.
Research Progress and Challenges of Carbon/MXene Composites for Supercapacitors
Authors: Sun Li , Dong Yu , Li Hangyu , Meng Hanqi , Liu Jianfei , Cao Qigao , Pan Chunxu
Published: November 2024

Carbon materials/MXenes composite materials have gained widespread attention in the field of supercapacitors due to their excellent electrochemical performance. Carbon materials are considered ideal electrode materials for supercapacitors due to their high specific surface area, good conductivity, and outstanding electrochemical stability. MXenes, as a novel two-dimensional material, exhibit prominent conductivity, mechanical properties, and ionic conductivity, thereby showing great potential for applications in energy storage devices. The combination of carbon materials and MXenes is expected to fully leverage the advantages of both, optimizing electrode conductivity, enhancing the energy density and power density, and improving the charge–discharge performance. This article reviews the key research progress of carbon/MXenes composite materials in supercapacitors in recent years, including their synthesis methods, structural tuning, and improvements in their electrochemical performance. Finally, the article looks forward to future research directions and proposes potential strategies to enhance the overall performance of the composite materials and achieve large-scale applications. By addressing the existing challenges, carbon/MXenes composite materials are anticipated to achieve higher energy and power outputs for the supercapacitor field in the future, providing strong support for the development of new energy storage technologies such as electric vehicles and wearable devices.
Recent Advances in High-Performance Carbon-Based Electrodes for Zinc-Ion Hybrid Capacitors
Authors: Liu Ying , Song Lechun , Li Chenze , Song Caicheng , Wu Xiang
Published: November 2024

Aqueous zinc-ion hybrid capacitors (ZIHCs) have emerged as a promising technology, showing superior energy and power densities, as well as enhanced safety, inexpensive and eco-friendly features. Although ZIHCs possess the advantages of both batteries and supercapacitors, their energy density is still unsatisfactory. Therefore, it is extremely crucial to develop reasonably matched electrode materials. Based on this challenge, a surge of studies has been conducted on the modification of carbon-based electrode materials. Herein, we first summarize the progress of the related research and elucidate the energy storage mechanism associated with carbon-based electrodes for ZIHCs. Then, we investigate the influence of the synthesis routes and modification strategies of the electrode materials on electrochemical stability. Finally, we summarize the current research challenges facing ZIHCs and predict potential future research pathways. In addition, we suggest key scientific questions to focus on and potential directions for further exploration.
Non-Contact Cross-Person Activity Recognition by Deep Metric Ensemble Learning
Authors: Ye Chen , Xu Siyuan , He Zhengran , Yin Yue , Ohtsuki Tomoaki , Gui Guan
Published: November 2024

In elderly monitoring or indoor intrusion detection, the recognition of human activity is a key task. Owing to several strengths of Wi-Fi-based devices, including their non-contact and privacy protection, these devices have been widely applied in the area of smart homes. By the deep learning technique, numerous Wi-Fi-based activity recognition methods can realize satisfied recognitions, however, these methods may fail to recognize the activities of an unknown person without the learning process. In this study, using channel state information (CSI) data, a novel cross-person activity recognition (CPAR) method is proposed by a deep learning approach with generalization capability. Combining one of the state-of-the-art deep neural networks (DNNs) used in activity recognition, i.e., attention-based bi-directional long short-term memory (ABLSTM), the snapshot ensemble is the first to be adopted to train several base-classifiers for enhancing the generalization and practicability of recognition. Second, to discriminate the extracted features, metric learning is further introduced by using the center loss, obtaining snapshot ensemble-used ABLSTM with center loss (SE-ABLSTM-C). In the experiments of CPAR, the proposed SE-ABLSTM-C method markedly improved the recognition accuracies to an application level, for seven categories of activities.
The Role of Insulin Within the Socio-Psycho-Biological Framework in Type 2 Diabetes—A Perspective from Psychoneuroimmunology
Authors: Wevers Anne , San Roman-Mata Silvia , Navarro-Ledesma Santiago , Pruimboom Leo
Published: November 2024

The interplay between socio-psychological factors and biological systems is pivotal in defining human health and disease, particularly in chronic non-communicable diseases. Recent advancements in psychoneuroimmunology and mitochondrial psychobiology have emphasized the significance of psychological factors as critical determinants of disease onset, progression, recurrence, and severity. These insights align with evolutionary biology, psychology, and psychiatry, highlighting the inherent social nature of humans. This study proposes a theory that expands insulin’s role beyond traditional metabolic functions, incorporating it into the Mitochondrial Information Processing System (MIPS) and exploring it from an evolutionary medicine perspective to explore its function in processing psychological and social factors into biological responses. This narrative review comprises data from preclinical animal studies, longitudinal cohort studies, cross-sectional studies, machine learning analyses, and randomized controlled trials, and investigates the role of insulin in health and disease. The result is a proposal for a theoretical framework of insulin as a social substance within the socio-psycho-biological framework, emphasizing its extensive roles in health and disease. Type 2 Diabetes Mellitus (T2DM) with musculoskeletal disorders and neurodegeneration exemplifies this narrative. We suggest further research towards a comprehensive treatment protocol meeting evolutionary expectations, where incorporating psychosocial interventions plays an essential role. By supporting the concept of ‘insulin resilience’ and suggesting the use of heart rate variability to assess insulin resilience, we aim to provide an integrative approach to managing insulin levels and monitoring the effectiveness of interventions. This integrative strategy addresses broader socio-psychological factors, ultimately improving health outcomes for individuals with T2DM and musculoskeletal complications and neurodegeneration while providing new insights into the interplay between socio-psychological factors and biological systems in chronic diseases.
Editorial for the Special Issue “Angiogenic Growth Factors in Tumor Development: Beyond New Blood Vessels Formation”
Authors: Palumbo Camilla , Albonici Loredana
Published: November 2024

A myriad of growth factors and receptors, whose effects are intertwined in complex interactions, do not only orchestrate tumor angiogenesis [...]
A Spectrophotometric Method to Determine Minimal Erythema Dose for Ultraviolet Radiation in Human Skin
Authors: Lee Eun Ju , Lee Chung Han , Baek Ji Hwoon , Koh Jae Sook , Boo Yong Chool
Published: November 2024

Background/Objectives: Ultraviolet radiation (UVR) induces oxidative stress in the skin by generating reactive oxygen species (ROS), which can lead to inflammatory conditions including erythema (a sign of sunburn). This clinical study aims to develop an instrumental evaluation method to determine the minimal erythema dose (MED) for UVR. Methods: Fourteen human subjects aged 27 to 57 years (48.93 ± 8.54) participated in this study. Six subsites were designated on the test skin site of each subject and irradiated with UVR at different doses. The examiner visually assessed erythema, determining the ‘visual MED’. Additionally, the a* value (a chrominance parameter presenting greenness to redness) was measured using a spectrophotometer as an indicator of erythema. The a* values of the UVR-irradiated subsites were compared to the non-irradiated control value, and the differences were referred to as Δa*. The Δa* value of the subsites irradiated with UVR at the ‘visual MED’ was referred to as the Δa*VMED for each subject. The mean of the Δa*VMED values of all subjects was chosen as a criterion value for the ‘instrumental MED’. The ‘instrumental MED’ was defined as the lowest dose of UVR that causes an Δa* value equivalent to the criterion value. The ‘visual MED’ and ‘instrumental MED’ values of all subjects were subjected to correlation analysis. Results: The mean of the Δa*VMED values of all subjects was 1.88 ± 0.8. The means of the ‘visual MED’ and ‘instrumental MED’ values (in J m−2 unit) of all subjects were 300.14 ± 84.16 and 303.29 ± 77.99, respectively. In Pearson correlation analysis, the ‘instrumental MED’ and ‘visual MED’ values had a very strong positive correlation with each other (r = 0.864, p = 0.000). Conclusions: This study suggests that the instrumental evaluation method of MED based on the spectrophotometric measurement of the a* values can complement or replace the visual evaluation method and that this method will be useful in monitoring skin tolerance to oxidative stress affected by prooxidant factors and defensive factors.
Emerging Ocular Side Effects of Immune Checkpoint Inhibitors: A Comprehensive Review
Authors: Wu Kevin Y. , Yakobi Yoel , Gueorguieva Diana D. , Mazerolle Éric
Published: November 2024

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, offering significant improvements in patient survival across various malignancies. However, their use is associated with a broad spectrum of immune-related adverse events (irAEs), including those affecting the eye and its surrounding structures, collectively termed ocular irAEs (OirAEs). Although rare, OirAEs (e.g., keratitis, uveitis, retinal vasculitis, etc.) can significantly impact a patient’s quality of life, leading to ocular complications if left untreated. This review provides a comprehensive overview of OirAEs associated with ICIs, including their clinical manifestations, underlying mechanisms, and current management strategies. We delve into the anterior and posterior segment adverse events, highlighting conditions such as dry eye, uveitis, and retinal disorders, as well as neuro-ophthalmic and orbital complications. Furthermore, we discuss the challenges in diagnosing and treating these conditions, particularly given the overlap with other autoimmune and paraneoplastic syndromes. Finally, we identify key knowledge gaps and suggest future research directions aimed at optimizing the management of OirAEs while maintaining the efficacy of cancer therapy. This review underscores the need for increased awareness among clinicians to prevent irreversible ocular damage and enhance patient outcomes.
A Numerical Study of Flow Past a Wall-Mounted Dolphin Dorsal Fin at Low Reynolds Numbers
Authors: Lin Zhonglu , Gao Ankang , Zhang Yu
Published: November 2024

Dolphin swimming has been a captivating subject, yet the dorsal fin’s hydrodynamics remain underexplored. In this study, we conducted three-dimensional simulations of flow around a wall-mounted dolphin dorsal fin derived from a real dolphin scan. The NEK5000 (spectral element method) was employed with a second-order hex20 mesh to ensure high simulation accuracy and efficiency. A total of 13 cases were simulated, covering angles of attack (AoAs) ranging from 0° to 60° and Reynolds numbers (Re) between 691 and 2000. Our results show that both drag and lift increase significantly with the AoA. Almost no vortex was observed at AoA=0°, whereas complex vortex structures emerged for AoA≥30°, including half-horseshoe, hairpin, arch, and wake vortices. This study offers insights that can inform the design of next-generation underwater robots, heat exchangers, and submarine sails.
Neuroplastic Responses to Chiropractic Care: Broad Impacts on Pain, Mood, Sleep, and Quality of Life
Authors: Haavik Heidi , Niazi Imran Khan , Amjad Imran , Kumari Nitika , Ghani Usman , Ashfaque Moeez , Rashid Usman , Navid Muhammad Samran , Kamavuako Ernest Nlandu , Pujari Amit N. , Holt Kelly
Published: November 2024

Objectives: This study aimed to elucidate the mechanisms of chiropractic care using resting electroencephalography (EEG), somatosensory evoked potentials (SEPs), clinical health assessments (Fitbit), and Patient-reported Outcomes Measurement Information System (PROMIS-29). Methods: Seventy-six people with chronic low back pain (mean age ± SD: 45 ± 11 years, 33 female) were randomised into control (n = 38) and chiropractic (n = 38) groups. EEG and SEPs were collected pre and post the first intervention and post 4 weeks of intervention. PROMIS-29 was measured pre and post 4 weeks. Fitbit data were recorded continuously. Results: Spectral analysis of resting EEG showed a significant increase in Theta, Alpha and Beta, and a significant decrease in Delta power in the chiropractic group post intervention. Source localisation revealed a significant increase in Alpha activity within the Default Mode Network (DMN) post intervention and post 4 weeks. A significant decrease in N30 SEP peak amplitude post intervention and post 4 weeks was found in the chiropractic group. Source localisation demonstrated significant changes in Alpha and Beta power within the DMN post-intervention and post 4 weeks. Significant improvements in light sleep stage were observed in the chiropractic group along with enhanced overall quality of life post 4 weeks, including significant reductions in anxiety, depression, fatigue, and pain. Conclusions: These findings indicate that many health benefits of chiropractic care are due to altered brain activity.
Learning Family: Concept, Measurement and the Effect on Individuals’ Behaviors
Authors: Kong Ming , Lu Yahua
Published: November 2024

A learning society cannot be built without each family playing its role. The learning family integrates the modern education concept and the actual needs of family education. However, scholars are still exploring the concept, structure, and measuring tools of the learning family. Based on the bioecological system theory, this study explored the concept and characteristic dimension of the learning family and verified the effect of the learning family through cross-population samples. The results of this study showed that, first, the learning family involves a process of mutual influence on the part of family members, who view the enhancement of comprehensive literacy as their core goal and can continuously accumulate knowledge and improve skills from the internal and external environments of the family through learning support and learning involvement, thereby achieving common growth, the main structure of which includes four characterizing dimensions of learning involvement, learning effectiveness, learning support and continuous learning. Second, the developed learning family scale has good reliability and validity. Third, learning families have significant positive effects on individual creativity, innovative behavior, prosocial behavior, proactive behavior, work performance, academic achievement, and science literacy. This study not only deepens our understanding of the importance of family learning and family education but also contributes to exploring the influence mechanisms underlying learning families on individual psychology and behavior in the future.