bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Isometric Squat Strength to Predict Concentric and Eccentric Squat Strength in Young and Older Adults
Authors: Dunn Michael T. , Quach Phuong T. M. , McGraw Monica , Preus Richard I. , Barefoot Robert C. , Lancaster Winston C. , Ponder Jennifer , Singh Harshvardhan 
Published: February 2025

ABSTRACTBackgroundResistive squat exercise is a well‐established technique to enhance the strength of muscles and bones of the back extensors in humans. Rehabilitation programs aimed at strengthening the muscles and bone of the back require the knowledge of the patient's 1 repetition maximum (RM) of squat exercise. Finding the 1RM value of squat exercise could lead to injury or seem nonfeasible because of the higher weights involved, especially in older adults.PurposeTo investigate the predictive relationship between the maximum voluntary isometric squat strength and the 1RM concentric and eccentric squat strength in young and older individuals.MethodsIn our cross‐sectional study, individuals from two age populations, 21–35 years (young) and 55–75 years (older) were recruited and participated in two visits within a two‐week period. Our main outcome measures were: Maximum voluntary isometric squat strength (IsoMax) and 1RM of concentric (ConMax) and eccentric (EccMax) back squat strength were calculated for young and older adults. All the strength measures were normalized for body weight.ResultsIsoMax was a significant predictor of the ConMax (p = 0.003; Normalized ConMax = 0.708 + 1.376(Normalized IsoMax); 95%CI: 0.583–2.169) and EccMax (p = 0.003, Normalized EccMax = 0.844 + 1.433(Normalized IsoMax); 95%CI = 0.582–2.284) in older adults only. There was a trend toward significance for the relationship between IsoMax and ConMax (p = 0.058) in young adults.DiscussionOur novel findings show that safe techniques for muscle strength assessment, such as maximum voluntary isometric squat strength, can be utilized in older populations to predict their 1RM of concentric and eccentric squat strength. Our novel equations provide the information necessary for designing effective rehabilitation regimes for strengthening the muscles and bone of the back in older adults.
Geometric Adaptive Neural Controller and Optical Flow‐Based Invariant Extended Kalman Filter for Mars Quadrotor Under Disturbance
Authors: Li Yiqun , Qiao Siyuan , Shao Haoluo , Yin Zhouping 
Published: February 2025

ABSTRACTWith the continuous progress of deep space robotics technology and the deepening of human understanding of the Martian surface environment, the rotorcraft is expected to overcome the limitations of Mars orbiters and rovers in terms of exploration accuracy, range, and flexibility. Rotorcraft are poised to become essential vehicles for future deep space exploration missions. In this paper, an invariant extended Kalman filter (IEKF) and geometric adaptive neural controllers (GANC) are introduced for the state estimation and trajectory tracking of the Mars quadrotor. The IEKF fuses the IMU and depth camera information to estimate the optimal states of the quadrotor, which are used as the inputs of the trajectory tracking controller. Multilayer perceptron networks (MLP) and temporal convolutional networks (TCN) are designed and trained to predict the force and torque disturbances to improve the tracking accuracy and robustness of the proposed geometric adaptive neural controllers, including the feedforward (FF) proportional‐differential (PD) neural controller on SE(3) for large‐angle maneuver and the differential‐flatness based neural controller (DFBC) for flight in strong winds. Especially, for underpowered situations, an event‐trigger neural model predictive contouring controller (ET‐NMPCC) is designed to optimize the control inputs, foresee and adapt to potential future external forces, and ultimately achieve higher trajectory tracking accuracy. Physical simulation systems are established to mimic the terrain and atmosphere of the Martian surface in Webots and Airsim simulator. The simulation and real‐world experimental results show the effectiveness and superiority of these methods in flight navigation and control performances of the quadrotor on the Martian surface.
LCRBot: Load‐Carrying Rolling Robot Based on Truncated Hexahedral Tensegrity
Authors: Liu Jilei , Xu Zhiyin , Lu Jinyu , Gu Xun , Wu Jiarong 
Published: February 2025

ABSTRACTThe tensegrity robot consists of rigid compression bars and elastic tension cables, offering several advantages over traditional load‐carrying robots, including impact resistance, lightweight design, unique movement patterns, and modularity. However, research on tensegrity robots capable of carrying loads and rolling is very limited. This paper proposes a load‐carrying and rolling tensegrity robot (LCRBot) based on truncated hexahedral tensegrity structure, which offers ample load‐carrying space and the ability to perform rolling. LCRBot can achieve active deformation by elongating and shortening its internal bars. The gait control strategies of LCRBot under different numbers of actuators and rolling directions, as well as variations in different environments are investigated. The MATLAB‐based dynamic model of LCRBot is proposed and its simulation results of basic gait are consistent with the experiment. The proposed LCRBot showcases its potential for carrying sensors, power sources, and other equipment during rolling motions, making it highly valuable for research.
Shifts in phytoplankton communities in inland waterways: Insights from the Beijing–Hangzhou Grand Canal, China
Authors: Mao Xueru , Zhu Lin , Liu Boyi , Zeng Chenjun , Yang Huijian , Shi Wenqing 
Published: February 2025

AbstractPhytoplankton play a crucial role in maintaining the health of river ecosystems, and their communities are closely linked to river hydrodynamics. In inland waterways, disturbances generated by ship propellers alter flow dynamics and may affect phytoplankton communities. To clarify it, phytoplankton communities in the Zhenjiang section of the Beijing–Hangzhou Grand Canal (BHGC) in China, the world's longest canal, were studied and compared them with its undisturbed tributaries. The results revealed major alternations in seasonal patterns of phytoplankton communities in the BHGC, shifting the peak of phytoplankton density from spring to autumn and the lowest diversity from summer to autumn. Ship disturbances increased water turbidity and created optimal N/P ratios, which provided Cyanobacteria with a competitive advantage in autumn. The proliferation of Cyanobacteria resulted in a phytoplankton density in the BHGC, exceeding that in the tributaries by more than tenfold, accompanied by a decrease in diversity to its lowest level. Due to habitat alterations, functional groups emerged that are resilient to strong disturbances and high turbidity. The findings add to the understanding of the impact of ship traffic on river ecosystems.
Putting the Pieces Back Together: Challenges Recomposing Elementary Science Teaching
Authors: Canipe Martha M. 
Published: February 2025

ABSTRACTElementary teacher educators endeavor to prepare prospective elementary teachers to teach science in ways which best support student learning. A well‐documented challenge in teacher education is the disconnect between theory and practice which many programs have worked to overcome. One framework which has been used in many teacher preparation programs is practice‐based teacher education which consists of three‐parts: representation, decomposition, and approximations of practice. This framework has been studied in a number of contexts, but the ways in which prospective teachers recompose practice have not been fully explored. In this study, I examined the science teaching of three student teachers enrolled in the same teacher education program to understand how they enacted teaching practices from their teacher education coursework. Findings showed that each student teacher adopted a different, singular practice as their primary guide for teaching science rather than a more integrated and recomposed approach. This suggests that a more explicit focus on recomposition of practice is a necessary part of teacher education.
Random Survival Forest for Censored Functional Data
Authors: Loffredo Giuseppe , Romano Elvira , Maturo Fabrizio 
Published: February 2025

ABSTRACTThis article introduces a Random Survival Forest (RSF) method for functional data. The focus is specifically on defining a new functional data structure, the Censored Functional Data (CFD), for addressing the challenge of accurately modelling time‐to‐event data in the presence of censoring and irregular temporal structures. Traditional survival models struggle to incorporate complex functional patterns, making the proposed approach particularly valuable for improving prediction and interpretation. This approach allows for precise modelling of functional survival trajectories, leading to improved interpretation and prediction of survival dynamics across different groups. A medical survival study on the benchmark Sequential Organ Failure Assessment (SOFA) dataset and an extensive simulation study are presented. Results show good performance of the proposed approach, particularly in ranking the importance of predicting variables.
Tunable Bi‐directional Broadband Self‐Powered Photoresponse in a 0D C60/2‐D SnS2 Nanoflower Heterostructure
Authors: Kumar Mahesh , Chen Sheng‐Chi , Saravanan Adhimoorthy , Huang Bohr‐Ran , Sun Hui 
Published: February 2025

AbstractRealizing bidirectional photodetection is essential for developing next‐generation artificial neuromorphic systems, visual information processing, and future optoelectronic logic gates. Photodetectors are promising visible light communication systems due to their energy efficiency and cost‐effectiveness. Color shift keying is frequently used in visible light communication to meet non‐negative light intensity modulation demands. However, requiring a minimum of two photodetectors with filters to decode optical signals raises the device cost and complicates the communication system. Here, novel bidirectional photo response of 0‐D C60/2‐D SnS2 nanoflower heterostructure for self‐powered broadband photodetector synthesis using sol–gel methods is presented. The photodetector exhibits significantly enhanced currents, with increases of ≈17000% (365 nm), 8750% (456 nm), 3333% (532 nm), 17647% (632 nm), and 124500% (850 nm) under zero bias, compared to C60. Furthermore, by adjusting the wavelength of the incident light, controllable bidirectional photoresponse (negative for wavelength = 365 nm and positive for 456–850 nm wavelengths) is achieved through the C60/SnS2, owing to the synergistic interplay between the photothermoelectric effect of C60 and the photovoltaic effect of SnS2. Polarity switching bestows multifunctional attributes upon photoelectric devices, potentially providing innovative approaches to overcome conventional challenges and fulfill the demands of emergent technological paradigms.
CDK16+ Luminal Progenitor Cell‐Like Tumor Cells Interacted with POSTN+ Cancer‐Associated Fibroblasts Associate with Chemo‐Resistance In Breast Cancer
Authors: Ding Xinyu , Wu Qi , Du Yanhua , Ji Meng‐meng , Yang Hua , Hu Qingsong , Ye Youqiong 
Published: February 2025

AbstractTumor heterogeneity and interaction with tumor microenvironment play a crucial role in neoadjuvant chemotherapy (NAC) resistance in breast cancer (BRCA). Unraveling this dynamic interaction may help uncover novel therapeutic targets. Here, dynamic changes in tumor states and cellular composition are systemically characterized using 175,825 single‐cell transcriptomics from naïve and post‐treatment biopsies of BRCA patients receiving NAC. CDK16+ tumors are identified featured with luminal progenitor cell (LPC)‐like tumor cells enriched in the triple‐negative subtype of BRCA, associated with chemo‐resistance. Integrating single‐cell RNA sequencing (scRNA‐seq), spatial transcriptomics, and six independent public gene expression profiles that underwent chemotherapy revealed that POSTN+ cancer‐associated fibroblasts (CAFs) are closely localized and interacted with CDK16+ LPC‐like tumor cells to promote chemo‐resistance. In vivo, CDK16 knockdown in tumor cells combined with chemotherapy significantly enhanced therapeutic efficacy. This in‐house scRNA‐seq from a mouse model validated that CDK16 knockdown reduced the LPC‐like tumor cell signature, and the interaction of tumor featured with LPC‐like tumor cells and POSTN+ CAFs. Together, the systematically integrated analyses uncovered an interaction network of CDK16+ tumor and POSTN+ CAFs that contributed to NAC‐ resistance, providing a new strategy for targeting CDK16 to enhance chemotherapy efficacy.
Enhancing Malware Detection With Deep Learning Convolutional Neural Networks: Investigating the Impact of Image Size Variations
Authors: Hawana Ahmed , Hassan Emad S. , El‐Shafai Walid , El‐Dolil Sami A. 
Published: February 2025

ABSTRACTTo address the growing challenges posed by cyber threats, anti‐malware organizations have increasingly turned to machine learning (ML), a well‐established field in computer science known for its proficiency in tasks like image recognition and decision‐making. Leveraging ML enables these organizations to enhance their ability to detect and classify malware. However, identifying an optimal method for malware detection remains a critical challenge in cybersecurity. This paper proposes a simplified detection model using deep learning (DL)‐based convolutional neural networks (CNNs) to achieve effective malware classification while maintaining simplicity. The proposed model focuses on employing a minimalistic architecture without compromising detection accuracy, even when working with an imbalanced dataset. The primary objective is to evaluate the impact of varying malware image sizes (32 × 32, 64 × 64, 128 × 128, and 256 × 256) on detection performance. The malware images dataset was divided into 80% for training and 20% for testing. The data were preprocessed to generate image datasets of the specified sizes, which were then fed into a two‐layer CNN model. The model's performance was assessed using key metrics such as accuracy, precision, recall, and F1‐score. Experimental results demonstrate that the size of malware images inversely affects detection performance, with smaller images yielding better results. Specifically, the 32 × 32‐pixel size emerged as the most efficient for malware detection using the proposed model, achieving 99.601% accuracy, 98.942% precision, 98.910% recall, and 98.915% F1‐score. Additionally, the 32 × 32 images required the least training time, highlighting the model's computational efficiency.
Sustainable concrete solutions: Evaluating the structural performance of coconut shells as coarse aggregate substitute
Authors: Boakye Kingsley Asare , Tarantsev Dmitrii , Ahmed Mohammed , Bainge Gilbert 
Published: February 2025

AbstractThe increasing demand for concrete in urban development raises significant environmental concerns associated with the extraction of natural aggregates. This study addresses the need for sustainable alternatives by evaluating coconut shells as a substitute for coarse aggregates in concrete. The primary objectives were to assess the impact of varying percentages of coconut shells (5%, 10%, and 15%) on the workability and strength of concrete, as well as to investigate the effects of superplasticizers on these properties. A systematic approach was employed to prepare concrete mix proportions, incorporating coconut shells and superplasticizers. Concrete specimens were cast and subjected to strength tests after curing periods of 7, 14, and 28 days, in accordance with BS EN 12390‐3 standards. The principal results indicated that while the inclusion of coconut shells improved the sustainability of the concrete, it also led to a decrease in workability, particularly as the percentage of coconut shells increased. Additionally, the use of superplasticizers, although intended to enhance flow properties, resulted in diminished workability at higher coconut shell content. Compressive strength tests showed that up to 15% replacement of coarse aggregates with coconut shells did not significantly compromise strength. In conclusion, coconut shells can serve as a viable alternative to traditional aggregates, promoting sustainability in construction. However, careful consideration of superplasticizer use is essential to maintain optimal workability and strength in concrete mixes.
The Common Alzheimer's Disease Research Ontology (CADRO) for biomarker categorization
Authors: Leisgang Osse Amanda M. , Kinney Jefferson W. , Cummings Jeffrey L. 
Published: February 2025

AbstractBiomarkers are vital to Alzheimer's disease (AD) drug development and clinical trials, and will have an increasing role in clinical care. In this narrative review, we demonstrate the use of the National Institutes on Aging/Alzheimer's Association (NIA/AA) Common Alzheimer's Disease Research Ontology (CADRO) system for the categorization of biomarkers based on the primary mechanism on which they report. We show that biomarkers are available (in various levels of validation) for all CADRO processes. Application of the CADRO system demonstrates gaps in the field where novel biomarkers are needed for specific aspects of the disease, and assays to detect and measure biological changes, in individuals with symptomatic or preclinical AD. We demonstrate the CADRO system as a means of categorizing established and candidate AD biomarkers, showing the feasibility and practicality of the system. CADRO can assist with biomarker selection for AD clinical trials and drug development, and may eventually be applied to implementing biomarkers in patient care.Highlights
The Common Alzheimer's Disease Research Ontology (CADRO) system can be used to categorize biomarkers for drug development.
We demonstrate the use of CADRO with Alzheimer's disease (AD) biomarkers.
We identified AD biomarkers in each of the CADRO categories.
CADRO can be incorporated into current AD drug development and clinical trial systems.
Innate Immunity Toll‐Like Triad TLR6‐1‐10 and Its Diversity in Distinct Horse Breeds
Authors: Stejskalova Karla , Vychodilova Leona , Janova Eva , Oppelt Jan , Horin Petr 
Published: February 2025

ABSTRACTToll‐like receptors (TLRs) play important roles in innate immunity and developmental processes. Due to their nature as molecular pattern recognition receptors, their genetic diversity may reflect the effects of various pathogen pressures. Here, the extent of variability in the TLR1‐6‐10 gene cluster in three geographically and historically distinct breeds of horses was analysed. A genetically diverse group of representatives of 14 other horse breeds provided additional information on the variability of this gene cluster in the domestic horse. Altogether, 25 SNPs were identified in the TLR6‐1‐10 gene cluster across the 4 equine breed groups studied, of which 7 were synonymous and 18 non‐synonymous. Twenty‐eight inferred SNPs and 22 in silico translated amino acid haplotypes were identified. A predominant major haplotype present in all breed groups along with several group‐specific haplotypes were identified. Strong linkage disequilibrium was detected for several SNPs, as well as effects of pervasive, site‐specific selection. The existence of a major haplotype suggests it may confer a selective advantage across breeds. Less frequent breed‐specific haplotypes may represent variability required or beneficial for responses to local pathogen pressures. Purifying site‐specific selection was detected in the TIR domain and its vicinity in TLR6, whereas AA sites under diversifying selection were located in LRR domains and/or their surroundings in TLR1. Population structure models based on immune‐related TLR6‐1‐10 markers did not distinguish between breed groups, whereas in models based on neutral microsatellite markers, breed groups clustered separately. This supports the assumption that the diversity of the TLR6‐1‐10 cluster is of adaptive value. The TLR6‐1‐10 alleles and haplotypes identified represent potential candidate markers for disease association studies.
Seasonal variations and correlation analysis of water quality parameters in the Chambal River, Rajasthan, India
Authors: Singh Krishna Pal , Saxena Abhishek 
Published: February 2025

AbstractThe study investigated the water quality of the Chambal River from 2010 to 2022 throughout the year. The measured parameters like pH, EC (Electrical Conductivity), TDS (Total Dissolved Solids), and Total Hardness (TH) fluctuate between 7.70 and 8.35 (with an average of 8), 289 and 484 μS/cm (with an average of 347 μS/cm), 185 and 315 mg/l (with an average of 224 mg/l), and 68 and 120 mg/l (with an average of 93 mg/l), respectively, on the yearly basis. While the turbidity, nitrate levels, ammonia nitrogen, fluoride, and boron dissolved) fluctuate between 0.79 and 8 NTU (with an average of 2 NTU), 0.38 and 2 mg/l (with an average of 0.92 mg/l), 0.06 and 0.61 mg/l (with an average of 0.22 mg/l), 0.24 and 0.94 mg/l (with an average of 0.67 mg/l), and 0.04 and 0.33 mg/l (with an average of 0.16 mg/l), respectively, on the yearly basis. The water Quality Index (WQI) ranges between 10 to 149 with an average of 73 on a yearly basis. However, WQI ranges between 27 to 95 (with an average of 56) in summer, 6 to 294 (with an average of 116) in rainy, 4 to 123 (with an average of 156) in autumn, and 1 to 82 (with an average of 52) in winter. These results indicate a poor overall Water Quality Index (WQI), rendering the Chambal River's water unsuitable for drinking purposes. Furthermore, the principal component analysis and dendrogram analysis were used in this study. The findings highlight the urgent need for stricter pollution control measures to safeguard the river's health.Practitioner Points
The present study is based on Seasonal Variations and Correlation Analysis of Water Quality Parameters via multiparametric approaches from 2010 to 2022 throughout the year in the Chambal River, Rajasthan, India.
Two types of statistics (Principal Component Analysis and Dendrogram analysis) have been applied here to know the variation and distribution of WQI.
pH fluctuated within the IS standard, with a slight summer alkalinity increase. EC remained stable, higher in summer due to evaporation. Turbidity peaked in the monsoon and reduced in dry periods.
Poor overall Water Quality Index (WQI) was found in the sampling site hence the reader of the discussed journal may take an interest in it. Urgent need to control the river's health from the different pollutants.
Pearson correlation analysis reveals strong positive correlations between WQI, turbidity, pH, TDS, TH, and EC while negative correlations are observed between these clusters and boron concentration.
Wege für bessere Impfraten
Authors: Floege Jürgen , Schwarz Toralf , Wanner Christoph , Heemann Uwe , Gallwitz Baptist , Witzke Oliver 
Published: February 2025

Zusammenfassung
Impfungen stellen eine wichtige Präventionsmaßnahme gegen Viruserkrankungen dar und haben seit ihrer Einführung schon viele Menschenleben gerettet. Heutzutage kann jeder Arzt bzw. jede Ärztin eine Impfung verabreichen. Bei Patienten mit chronischen Erkrankungen sollte eine Indikationsimpfung erfolgen. Generell bietet es sich an, wenn möglich, eine Koadministration vorzunehmen, die in der Regel bei vielen Impfstoffen, insbesondere Totimpfstoffen, problemlos möglich ist. Ein entsprechendes Qualitätsmanagement vermag Komplikationen zu vermeiden. Wichtig ist es auch, die Patienten über Impfungen zu informieren und sie ggf. nach der ersten Impfung an ihren Zweittermin zu erinnern, um die maximale Wirksamkeit zu gewährleisten.