bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hybrid optimization for efficient 6G IoT traffic management and multi-routing strategy
Authors: Logeshwaran J. , Patel Shobhit K. , Kumar Om Prakash , Al-Zahrani Fahah Ahmed 
Published: December 2024

AbstractEfficient traffic management solutions in 6G communication systems face challenges as the scale of the Internet of Things (IoT) grows. This paper aims to yield an all-inclusive framework ensuring reliable air pollution monitoring throughout smart cities, capitalizing on leading-edge techniques to encourage large coverage, high-accuracy data, and scalability. Dynamic sensors deployed to mobile ad-hoc pieces of fire networking sensors adapt to ambient changes. To address this issue, we proposed the Quantum-inspired Clustering Algorithm (QCA) and Quantum Entanglement and Mobility Metric (MoM) to enhance the efficiency and stability of clustering. Improved the sustainability and durability of the network by incorporating Dynamic CH selection employing Deep Reinforcement Learning (DRL). Data was successfully routed using a hybrid Quantum Genetic Algorithm and Ant Colony Optimization (QGA-ACO) approach. Simulation results were implemented using the ns-3 simulation tool, and the proposed model outperformed the traditional methods in deployment coverage (95%), cluster stability index (0.97), and CH selection efficiency (95%). This work is expected to study the 6G communication systems as a key enabler for IoT applications and as the title legible name explains, the solutions smartly done in a practical and scalable way gives a systematic approach towards solving the IoT traffic, and multi-routing challenges that are intended to be addressed in 6G era delivering a robust IoT ecosystem in securing the process.
Extraction and chemical characterization of humic acid produced from lignite coals of arid region of Gujarat, Western India
Authors: Rani Juhi , Kumari Sushmita , Paul Biswajit 
Published: December 2024

AbstractIn the current study, extraction of humic acid (HAs) from lignite fines of kutch basin of Gujarat (western India) were reported. The extraction was done by International Humic Substances Society (IHSS) method. Several analytical and spectroscopic techniques were used to characterize of extracted HAs. The gravimetric analysis showed (28.5% and 26.4%) of humic acid extraction from panandhro mines (PM) and mata-No-Madh mines (MNMM) respectively. UV–Vis spectroscopy revealed a high degree of humification, higher stability and aromatic nature. FTIR peaks demonstrated the presence of carboxylic, alcoholic, and phenolic functional groups. SEM/EDX analysis revealed that surface were smooth, non-porous and like loose sponge that showed the presence of major elements like C, O, F, Al, Na, S, Si, Ca, Ti and Fe. The combination of results gives a better and improved understanding of the nature of lignite coals of western India. It may be helpful in choosing suitable coals for the extraction of humic acid and using it for enhancing plant growth condition, soil enrichment and creating green energy solution. This study not only helps in the research related to extraction of humic acid from lignite but also creates a new avenue for the efficient and clean use of lignite.
Performance metrics outperform physiological indicators in robotic teleoperation workload assessment
Authors: Odoh Gift , Landowska Aleksandra , Crowe Emily M. , Benali Khairidine , Cobb Sue , Wilson Max L. , Maior Horia A. , Kucukyilmaz Ayse 
Published: December 2024

AbstractRobotics holds the potential to streamline the execution of repetitive and dangerous tasks, which are difficult or impossible for a human operator. However, in complex scenarios, such as nuclear waste management or disaster response, full automation often proves unfeasible due to the diverse and intricate nature of tasks, coupled with the unpredictable hazards, and is typically prevented by stringent regulatory frameworks. Consequently, the predominant approach to managing activities in such settings remains human teleoperation. Teleoperation can be demanding, especially in high-stress situations, and involves a complex blend of both cognitive and physical workload. We present an experiment to explore a range of physiological and performance-related metrics for workload assessment during robotic teleoperation. Thirty-five participants performed a teleoperation task, during which we manipulated cognitive and physical workload conditions. We recorded multiple metrics, including brain activity using functional Near-Infrared Spectroscopy, galvanic skin responses, cardiovascular responses, subjective workload ratings, task and robot performance data. Our results suggest that robotic teleoperation performance may be the most robust metric for distinguishing between different levels of workload experienced during teleoperation, with most physiological measures becoming insignificant to distinguish high cognitive workload.
Neratinib enhances the efficacy of CDK4/6 inhibitor plus endocrine therapy in HR+/HER2-low breast cancer cell line ZR-75-1 via hsa-miR-23a-5p
Authors: Chen Liushan , Ye Lingling , Liang Yuqi , Luo Wei , Zuo Qian , Huang Ping , Hu Yuyu , Dai Yan , Wu Yingchao , Guo Qianqian , Chen Qianjun 
Published: December 2024

AbstractHR+/HER2-low breast cancer is a significant subgroup of conventional HR+/HER2-negative breast cancer, and combination of CDK4/6 inhibitor and endocrine therapy is the standard first-line and second-line treatments for advanced HR+/HER2-low breast cancer. Nevertheless, it remains uncertain whether HER2 signaling affects the effectiveness of CDK4/6 inhibitor administered in combination with endocrine therapy for HR+/HER2-low breast cancer and suitable intervention measures. This study revealed poor efficacy for CDK4/6 inhibitor combined with endocrine therapy for HR+/HER2-low breast cancer in vitro and in vivo models. Secondly, suppression of HER2 gene expression in HR+/HER2-low breast cancer cells resulted in significantly improved efficacy for CDK4/6 inhibitor combined with endocrine therapy. Furthermore, the anti-HER inhibitor neratinib was administered to enhance the effectiveness of CDK4/6 inhibitor combined with endocrine therapy in HR+/HER2-low breast cancer by inhibiting the HER2 pathway and lowering HER2 mRNA expression. Strikingly, neratinib reversed the efficacy of CDK4/6 inhibitor and endocrine therapy by reducing HER2 mRNA stability in HR+/HER2-low breast cancer through the interaction of HER2 3’-UTR region with hsa-miR-23a-5p. Even after reducing neratinib dosage to the standard 1/2 dose (20 mg/kg), it remained highly effective and well-tolerated. This study provides a viable and well-tolerated triple combination therapy for clinical HR+/HER2-low breast cancer.
Cognitive abilities predict naturalistic speech length in older adults
Authors: Neff Patrick , Demiray Burcu , Martin Mike , Röcke Christina 
Published: December 2024

AbstractPast research has demonstrated the association between social engagement and the maintenance of cognitive abilities. However, inconsistent definitions of social engagement have posed challenges to systematically investigate this association. This paper addresses the role of social relationships in cognitive functioning among older adults, focusing on the real-life communication indicator—length of own speech—as a measure of social activity. Utilizing advanced technology to unobtrusively measure older adults’ real-life speech, this study investigates its association with various cognitive abilities and sociodemographic factors. Differential cognitive measures, and sociodemographic data including factors like age, sex, education, income, persons living in the same household, loneliness, and subjective hearing status were included. Audio data of 83 participants are analyzed with a machine learning speaker identification algorithm. Using Elastic Net regularized regression, results indicate that higher levels of working memory, cognitive speed, and semantic fluency predict own speech in everyday life. While having no partner negatively predicted own speech length, we unexpectedly found that higher hearing status was related to lower speech frequency. Age was neither a relevant predictor in the regression nor correlated with any other variables. We discuss implications and future research applications based on the findings from our novel approach.
Conotoxin kM-RIIIJ reveals interplay between Kv1-channels and persistent sodium currents in proprioceptive DRG neurons
Authors: Raghuraman Shrinivasan , Carter Jackson , Walter Markel , Karthikeyan Manju , Chase Kevin , Giglio Matías L. , Giacobassi Mario , Teichert Russell W. , Terlau Heinrich , Olivera Baldomero M. 
Published: December 2024

AbstractVoltage-gated potassium channels (VGKCs) comprise the largest and most complex families of ion channels. Approximately 70 genes encode VGKC alpha subunits, which assemble into functional tetrameric channel complexes. These subunits can also combine to form heteromeric channels, significantly expanding the potential diversity of VGKCs. The functional expression and physiological role of heteromeric K-channels have remained largely unexplored due to the lack of tools to probe their functions. Conotoxins, from predatory cone snails, have high affinity and specificity for heteromeric combinations of K-channels and show great promise for defining their physiological roles. In this work, using conotoxin kM-RIIIJ as a pharmacological probe, we explore the expression and physiological functions of heteromeric Kv1.2 channels using constellation pharmacology platform. We report that heteromers of Kv1.2/1.1 are highly expressed in proprioceptive neurons found in the dorsal root ganglion (DRG). Inhibition of Kv1.2/1.1 heteromers leads to an influx of calcium ions, suggesting that these channels regulate neuronal excitability. We also present evidence that Kv1.2/1.1 heteromers counteract persistent sodium currents, and that inhibiting these channels leads to tonic firing of action potentials. Additionally, kM-RIIIJ impaired proprioception in mice, uncovering a previously unrecognized physiological function of heteromeric Kv1.2/1.1 channels in proprioceptive sensory neurons of the DRG.
Exploring the role of the MUC1 mucin in human oral lubrication by tribological in vitro studies
Authors: Ammam Ianis , Pailler-Mattéi Cyril , Ouillon Lucas , Nivet Clément , Vargiolu Roberto , Neiers Fabrice , Canon Francis , Zahouani Hassan 
Published: December 2024

AbstractIn the context of the oral cavity, an organic layer known as the mucosal pellicle (MP) adheres to the surface of the oral epithelium, playing a pivotal role in lubricating and safeguarding oral tissues. The formation of the MP is driven by interactions between a transmembrane mucin known as MUC1, located on the oral epithelium, and salivary secreted mucin, namely MUC5B and MUC7. This study aimed to investigate the function of MUC1 and the influence of its structure on MP lubrication properties. We proposed a novel methodology to study oral lubrication based on four different models of oral epithelium on which we conducted in vitro tribological studies. These models expressed varying forms of MUC1, each possessing on of the distinct domain constituting the mucin. Mechanical parameters were used as indicators of lubrication efficiency and, consequently, of the role played by MUC1 in oral lubrication. The results from the tribological tests revealed that the presence of full MUC1 resulted in enhanced lubrication. Furthermore, the structure of MUC1 protein drive the lubrication. In conclusion, the mechanical tests conducted on our epithelium models demonstrated that MUC1 actively participates in epithelium lubrication by facilitating the formation of the MP.
Mathematical analysis of fractional Chlamydia pandemic model
Authors: Alqahtani Zuhur , Almuneef Areej , DarAssi Mahmoud H. , AbuHour Yousef , Al-arydah Mo’tassem , Safi Mohammad A. , Al-Hdaibat Bashir 
Published: December 2024

AbstractIn this study, we developed a Caputo-Fractional Chlamydia pandemic model to describe the disease’s spread. We demonstrated the model’s positivity and boundedness, ensuring biological relevance. The existence and uniqueness of the model’s solution were established, and we investigated the stability of the $$\alpha$$-fractional order model. Our analysis proved that the disease-free equilibrium point is locally asymptotically stable. Additionally, we showed that the model has a single endemic equilibrium point, which is globally asymptotically stable when $${\mathscr {R}}_0$$ exceeds 1. Using Latin Hypercube sampling and partial rank correlation coefficients (PRCCs), sensitivity analysis identified key parameters influencing $${\mathscr {R}}_0$$. Numerical simulations further illustrated the impact of parameter variations on disease dynamics.
Concordance and test-retest consistency of sleep biomarker-based neurodegenerative disorder profiling
Authors: Levendowski Daniel J. , Tsuang Debby , Chahine Lana M. , Walsh Christine M. , Berka Chris , Lee-Iannotti Joyce K. , Salat David , Fischer Corrine , Mazeika Gandis , Boeve Bradley F. , Strambi Luigi Ferini , Lewis Simon J. G. , Neylan Thomas C. , Louis Erik K. St. 
Published: December 2024

AbstractBiomarkers that aid in early detection of neurodegeneration are needed to enable early symptomatic treatment and enable identification of people who may benefit from neuroprotective interventions. Increasing evidence suggests that sleep biomarkers may be useful, given the bi-directional relationship between sleep and neurodegeneration and the prominence of sleep disturbances and altered sleep architectural characteristics in several neurodegenerative disorders. This study aimed to demonstrate that sleep can accurately characterize specific neurodegenerative disorders (NDD). A four-class machine-learning algorithm was trained using age and nine sleep biomarkers from patients with clinically-diagnosed manifest and prodromal NDDs, including Alzheimer’s disease dementia (AD = 27), Lewy body dementia (LBD = 18), and isolated REM sleep behavior disorder (iRBD = 15), as well as a control group (CG = 58). The algorithm was validated in a total of 381 recordings, which included the training data set plus an additional AD = 10, iRBD = 18, Parkinson disease without dementia (PD = 29), mild cognitive impairment (MCI = 78) and CG = 128. Test–retest consistency was then assessed in LBD = 10, AD = 9, and CG = 46. The agreement between the NDD profiles and their respective clinical diagnoses exceeded 75% for the AD, LBD, and CG, and improved when NDD participants classified Likely Normal with NDD indications consistent with their clinical diagnosis were considered. Profiles for iRBD, PD and MCI participants were consistent with the heterogeneity of disease severities, with the majority of overt disagreements explained by normal sleep characterization in 27% of iRBD, 21% of PD, and 26% of MCI participants. For test–retest assignments, the same or similar NDD profiles were obtained for 88% of LBD, 86% in AD, and 98% of CG participants. The potential utility for NDD subtyping based on sleep biomarkers demonstrates promise and requires further prospective development and validation in larger NDD cohorts.
Lightweight tea bud detection method based on improved YOLOv5
Authors: Zhang Kun , Yuan Bohan , Cui Jingying , Liu Yuyang , Zhao Long , Zhao Hua , Chen Shuangchen 
Published: December 2024

AbstractTea bud detection technology is of great significance in realizing automated and intelligent plucking of tea buds. This study proposes a lightweight tea bud identification model based on modified Yolov5 to increase the picking accuracy and labor efficiency of intelligent tea bud picking while lowering the deployment pressure of mobile terminals. The following methods are used to make improvements: the backbone network CSPDarknet-53 of YOLOv5 is replaced with the EfficientNetV2 feature extraction network to reduce the number of parameters and floating-point operations of the model; the neck network of YOLOv5, the Ghost module is introduced to construct the ghost convolution and C3ghost module to further reduce the number of parameters and floating-point operations of the model; replacing the upsampling module of the neck network with the CARAFE upsampling module can aggregate the contextual tea bud feature information within a larger sensory field and improve the mean average precision of the model in detecting tea buds. The results show that the improved tea bud detection model has a mean average precision of 85.79%, only 4.14 M parameters, and only 5.02G of floating-point operations. The number of parameters and floating-point operations is reduced by 40.94% and 68.15%, respectively, when compared to the original Yolov5 model, but the mean average precision is raised by 1.67% points. The advantages of this paper’s algorithm in tea shot detection can be noticed by comparing it to other YOLO series detection algorithms. The improved YOLOv5 algorithm in this paper can effectively detect tea buds based on lightweight, and provide corresponding theoretical research for intelligent tea-picking robots.
Coupled echosounder and Doppler profiler measurements in the Strait of Gibraltar
Authors: Sammartino Simone , García-Lafuente Jesús , Nadal Irene , Sánchez-Leal Ricardo F. 
Published: December 2024

AbstractLong time series of velocity profiles collected by up-looking acoustic profilers in the westernmost sill of the Strait of Gibraltar show an unexpected pattern in the deepest ∼80 m of the water column, consisting in an appreciable diurnal weakening of the measured horizontal velocity. A harmonic analysis performed on long time series reveals a surprising magnitude of S1 constituent (exactly 1 cpd of frequency) in the horizontal velocity and echo amplitude, which prevails over the rest of diurnal constituents within this depth range, including K1, despite being around 200 times smaller than it in the tide generating potential. High resolution echograms collected by a new instrument recently installed in the mooring line, point at the diel vertical migration of living acoustic scatterers (zooplankton) as the most reasonable cause. It provokes a nightly depletion of scatterers availability near the bottom, which is registered by the instrument as a nighttime weakening of the velocity, as well as an increase of its uncertainty, at the deepest part of the profile. Newly acquired high spatial resolution measurements of the velocity near the seafloor report intense currents which are incompatible with the ones produced by the scatterers scarceness. This result indicates an overall underestimation of the Mediterranean current in previous works of approximately 17% within the depth range of 280–360 m, which in turn translates into an underestimation of previously computed outflow of ∼5%. These new findings make it necessary the re-computation of all the near-20-year long (to date) series of Mediterranean outflow based on the observations collected at this sill of the Strait of Gibraltar.
Plasma metabolomics profiles indicate sex differences of lipid metabolism in patients with Parkinson’s disease
Authors: Hu Ling , Huang Yuan-Jun , Wei You-Dong , Li Tao , Ke Wei , Chen Guang-Hui , Dong Mei-Xue 
Published: December 2024

AbstractThe effect of sexual dimorphism on the metabolism of patients with Parkinson’s disease has not been clarified. A group of patients with Parkinson’s disease and healthy controls were recruited, and their clinical characteristics and plasma were collected. Untargeted liquid chromatography-mass spectrometry-based plasma metabolomics profiling was performed. Differentially expressed metabolites between patients and healthy controls were respectively identified in the male and female participants and metabolite set enrichment analyses were further employed. A total of 75 patients with Parkinson’s disease (37 males and 38 females) and 31 healthy controls (16 males and 15 females) were enrolled while no significant differences can be discovered in clinical characteristics. The constructed male-specific metabolic model from orthogonal partial least squares-discriminant analysis can’t well recognize female patients and the female-specific model also can’t accurately identify male patients. There were 55 differentially expressed metabolites in the male participants, and fatty acids and conjugates and eicosanoids were the significantly enriched metabolite sets. Meanwhile, 86 metabolites were differentially expressed in the female participants while fatty acids and conjugates and glycerophosphocholines were enriched. Only 17 metabolites were simultaneously changed in both male and female patients. Significant sex differences of lipid metabolism were found in patients with Parkinson’s disease.
Comprehension of acoustically degraded emotional prosody in Alzheimer’s disease and primary progressive aphasia
Authors: Jiang Jessica , Johnson Jeremy C. S. , Requena-Komuro Maï-Carmen , Benhamou Elia , Sivasathiaseelan Harri , Chokesuwattanaskul Anthipa , Nelson Annabel , Nortley Ross , Weil Rimona S. , Volkmer Anna , Marshall Charles R. , Bamiou Doris-Eva , Warren Jason D. , Hardy Chris J. D. 
Published: December 2024

AbstractPrevious research suggests that emotional prosody perception is impaired in neurodegenerative diseases like Alzheimer’s disease (AD) and primary progressive aphasia (PPA). However, no previous research has investigated emotional prosody perception in these diseases under non-ideal listening conditions. We recruited 18 patients with AD, and 31 with PPA (nine logopenic (lvPPA); 11 nonfluent/agrammatic (nfvPPA) and 11 semantic (svPPA)), together with 24 healthy age-matched individuals. Participants listened to speech stimuli conveying three emotions in clear and noise-vocoded forms and had to identify the emotion being conveyed. We then conducted correlation analyses between task performance and measures of socio-emotional functioning. All patient groups showed significant impairments in identifying clear emotional prosody compared to healthy individuals. These deficits were exacerbated under noise-vocoded conditions, with all patient groups performing significantly worse than healthy individuals and patients with lvPPA performing significantly worse than those with svPPA. Significant correlations with social cognition measures were observed more consistently for noise-vocoded than clear emotional prosody comprehension. These findings open a window on a dimension of real-world emotional communication that has often been overlooked in dementia, with particular relevance to social cognition, and begin to suggest a novel candidate paradigm for investigating and quantifying this systematically.