Miracle-dz/UniFAR-FTUs huggingface dataset:
Achieving kinematic identity across shape diversity in musculoskeletal modeling

Musculoskeletal modeling is emerging as a powerful approach to investigate the locomotor biomechanics of extinct taxa. These models rely on bony morphology to define joint locations and muscle geometry. Using different motion profiles to drive models of extinct and extant taxa complicates comparisons because results reflect both morphological and kinematic differences. Here we report on an approach that permits changes in shape while maintaining model kinematics. Using a human musculoskeletal model, we carried out walking simulations of ten humans. Next, we morphed the model pelvis and proximal femur to match a reconstructed australopithecine pelvis and proximal femur. Using the kinematic results from the human walking simulations, we created new motion files based on the positions of joint centers and tracked anatomical locations. These files were used to drive simulations of the same walking trials with the australopithecine model. Joint centers and axes of the human and australopithecine models were compared for each walking trial simulation. We found that joint centers in the australopithecine simulations were typically within ~1µm of their locations in human simulations, and joint axes differed by less than 0.005 degrees. Such small differences have negligible effects on external joint moments calculated during inverse dynamics analyses. This conservative comparison will serve as a baseline for more complex simulations. Although this work focuses on one taxon, the approach outlined is applicable to a wide variety of extinct animals.
The use and beneﬁts of Craniosacral Therapy in primary health care: a prospective cohort study

Background: Patients frequently use treatments complementary to standard primary care. This prospective cohort-study examined the use, benefits, and safety of Craniosacral Therapy (CST). Methods: Consecutive out-patients utilizing CST from 2015 to 2019 were asked to provide anonymized data on symptom intensity, functional disability, and quality of life before and after treatment using an adapted 11-point numerical rating scale (NRS) version of the Measure Yourself Medical Outcome Profile
The health benefits of rooibos tea in humans (aspalathus linearis)-a scoping review

Natural remedies in the treatment of health conditions are an appealing option for many individuals. Previous studies reported that fermented and unfermented rooibos tea have considerable anti-inflammatory and antioxidative properties. Most of this knowledge, however, originates from animal and cell culture studies. The aims of this review are to evaluate the existing, but limited, body of knowledge regarding rooibos tea interventions in humans and to identify the gaps in the literature. The PRISMA extension for Scoping Reviews (PRISMA-ScR) guidelines were followed in the collation of this scoping review. Among the databases searched were Google Scholar, PubMed, Cochrane Library, Scopus, and Web of Science. This review comprised 18 publications, with half (50%) of the studies being conducted in South Africa. There were 488 participants in all, ranging in age from six to 83 years, in the investigations. Rooibos tea was either fermented, unfermented, or black in 62% of the studies. Doses ranging from 200 to 1,200 ml were employed. In both healthy and at-risk individuals, rooibos has been shown to enhance lipid profiles, boost antioxidant status, and lower blood glucose levels. The existing findings suggests that rooibos consumption demonstrated to improve lipid profiles, boost antioxidant status, and lower blood glucose levels in both apparently healthy, and individual at-risk individuals or diagnosed of chronic conditions. Thus, it can be presumed that rooibos tea provides some health benefits, yet these findings are based on a limited number of human intervention studies and a small total sample size. Additionally, a variety of rooibos dosages and types of tea in the experiments had inconsistent results that were probably impacted by the amount consumed. Future studies should include a dose-response study in humans, as well as large scaled clinical trials to evaluate the health effects of Rooibos.
The relationship between psychometrically-defined social anxiety The relationship between psychometrically-defined social anxiety and working memory performance and working memory performance

Anxiety disorders are among the most commonly diagnosed class of mental illness in the United States, and often involve abnormally high levels of stress and social fear. Despite high lifetime prevalence rates, social anxiety disorder (SAD) has remarkably low diagnosis and treatment rates. Furthermore, while individuals with other specific psychiatric disorders tend to exhibit significant neuropsychological deficits, neuropsychological functioning in individuals with SAD remains largely untested. A majority of the few existing studies concerning neuropsychological performance in SAD samples focus on specific functions, and their limited results are highly mixed. The primary objective of this investigation was to provide a more thorough, broad assessment of both auditory and visual working memory as related to psychometrically-defined social anxiety disorder. In addition, this study aimed to help clarify as to whether such deficits are related to the construct of social anxiety, or whether any potential deficits are better explained by generalized state and/or trait (in-the-moment) anxiety. The implications of a deficit in the visual and/or auditory working memory domains are multifaceted. For example, such a deficit may lead to the inability to detect visual cues in social situations. The
Global and local neuronal coding of tactile information in the barrel cortex

During tactile sensation in rodents, the whisker movements across surfaces give rise to intricate whisker motions that encompass discrete and transient stick–slip events, effectively conveying valuable information regarding surface properties. These surface characteristics are transformed into cortical neuronal responses. This study examined the coding strategies underlying these transformations in rat whiskers. We found that changes in surface coarseness modified the number and magnitude of stick–slip events, which in turn both modulated properties of neuronal responses. Global changes in the number of stick–slip events primarily affected neuronal discharge rates and the degree of neuronal synchronization. In contrast, local changes in the magnitude of stick–slip events affected the transformation of these kinematic and kinetic characteristics into neuronal discharges. Most cortical neurons exhibited surface coarseness selectivity through global and local stick–slip event properties. However, this selectivity varied across coding strategies in the same neurons, given that each coding strategy reflected different aspects of changes in whisker-surface interactions. The degree of spatial similarity in surface coarseness preference in adjacently recorded neurons differed among these coding strategies. Adjacently recorded neurons exhibited the same surface coarseness preference in their firing rates but not through other coding strategies. Through these results, we were able to show that local stick–slip event properties contribute to texture discrimination, complementing and surpassing global coding in this context. These findings suggest that the representation of surface coarseness in the cortex may rely on concurrent coding strategies that integrate tactile information across different spatiotemporal scales.
Spatial Multiplexing MIMO for Remote Areas employing MMSE Parallel Interference Cancellation for Non-Orthogonal GFDM

Remote areas are regions isolated from urban areas, mainly characterized by a low population density, such as small settlements and medium-size rural properties. Grant broadband Internet access in remote areas figures as a technical and economic challenge to any terrestrial wireless network. The high cost of spectrum license and low revenue associated with remote areas restrains this sort of investment. To keep the evolutionary trend initiated by the Remote Area Access Network for the 5th Generation (5G-RANGE), next generation of mobile communications must provide reliable long-range and cost-effective connection in these regions by exploring unused TV channels in TV White Space (TVWS) regime with high spectral efficiency. In this sense, we propose to make use of spatial multiplexing (SM)-multiple-input-multiple-output (MIMO) and a non-orthogonal (NO) waveform, compromised to meet low out-of-band (OOB) emission while harvesting multiplexing and extra diversity gain at the same time when employing a low complexity minimum mean squared error (MMSE)-parallel interference cancellation (PIC) detector. We checked out the performance of this maximum likelihood (ML) approaching method, reproducing the frame error rate (FER) from the base reference and analyze the proposed frame structure face the requirements of remote areas targeted for smart farm scenario in the agribusiness vertical.
Landscape genetics of the small-mouthed salamander (Ambystoma texanum) in a fragmented habitat: Impacts of landscape change on breeding populations in Hardin County, Ohio forests

iv DEDICATION . vi ACKNOWLEDGEMENTS . vii LIST OF TABLES . xii LIST OF FIGURES . xiii LIST OF ABBREVIATIONS . xv CHAPTERS I. Literature review Part 1: Anthropogenic Habitat Change . 1 Part 2: Review of Amphibian Landscape Genetics Studies . 11 Part 3: Forest Fragmentation in Western Ohio & Its Effect on Ambystoma texanum . 15 Part 4: Project Objectives and Hypotheses . 18 References . 21 II. A molecular screening method for unisexual Ambystoma using mitochondrial DNA Abstract . 28 Introduction . 29.28 Introduction . 29 Methods.30
Electromagnetic Performance and Application of Microwave Ferromagnetic Devices

This paper is dedicated to the consideration of modern designs and fields of application of nonreciprocal isolators and circulators based on ferromagnetic materials. We provide basic electromagnetic insight into working mechanisms of ferrite-based microwave passive devices. Structural peculiarities of the isolators applying the ferromagnetic resonance effect were revealed. Locations of dielectric and ferromagnetic plates were obtained from the analysis of theoretical fields distributions of the fundamental TE$_{\mathbf{10}}$ mode of the rectangular waveguide. The dependences of magnetic field polarization on the transversal coordinated of the waveguide are illustrated in the paper. Secondly, we have presented the structure of a ferromagnetic isolator based on the field displacement effect. Features of its structure and operation principle are considered. The circuit for possible application of the isolators in perfect excitation sources is presented. In addition, a typical designs of Y-shaped circulators based on ferromagnetic loading are considered and analyzed in the paper. Fields of application of Y- and X-shaped circulators in modern radio engineering systems are presented. Possible circuits for simultaneous multichannel transmission and isolation based on circulators are developed.
Response to “Coastal Versus Interior: Some Thoughts on the Archaeology of California's Channel Islands”

Erlandson raises two issues of concern: our definition of “interior” and our focus on sites post-dating the earliest few millennia of human occupation of the Channel Islands. The first relates to how we decided to delineate “interior,” which could be defined in a variety of ways in coastal environments based on different environmental variables. We decided on a 400-meter threshold because it effectively excludes the large, mounded habitation sites that were the focus of large-scale excavation on the Channel Islands prior to 1975, this being a principal objective in compiling our database. Erlandson proposes that 1,000 meters would be more reasonable because the effort to walk 400 meters is minimal. Although the effort is trivial, it is more than would be the case if the island inhabitants were living right at the shoreline. We argue that the various reasons we discussed for living away from the coast would have been in operation at distances as short as 400 meters. This point is not lost on the students Perry has led over the years on interpretive hikes around Scorpion Canyon on the eastern end of the island. After we disembark from the boat, hike up a road that ascends the canyon walls, andarriveat adenseshellmiddeneroding from a sheer cliff overlooking the ocean
Reaction of bean genotypes to the common bacterial blight, evaluated by two inoculation methods

The knowledge of resistance of bean genotypes to pathogens is important to genetic breeding programs. Two methods of bacterial inoculation were tested to evaluate the sensitivity of bean genotypes to common bacterial blight, caused by Xanthomonas axonopodis pv. phaseoli. Leaves of 56 bean genotypes were inoculated by the method of multiple needles and the method of incision with scissors, using the isolated XAP 15497. We classified 21 genotypes as resistant, 13 as moderately resistant, 9 as moderately susceptible, and 13 as susceptible by the method of inoculation with multiple needles. With the method of inoculation with scissors it was possible to classify 24 genotypes as resistant, 21 as moderately resistant, 7 as moderately susceptible, and 4 as susceptible. The genotypes IPR Chopim, IAPAR 81, IAPAR 16, BRS Campeiro, BRS Radiante, IAPAR 80, UTF 6, SM 9906, PI 2072620, LP 01-51, PB 4, Uirapuru, IAPAR 20, Zonin, IAPAR 31, 2 V, CNPF 7762, BRS Talisma, Perola, Lon Rosinha, and UTF 9 had similar behavior in the two methods of inoculation. Both methods of inoculation were efficient in determining the reactions of susceptibility and resistance of the genotypes but the method of inoculation with multiple needles was more precise and practical in the evaluation of the inoculated portion of the leaf.
Severity of developmental delay and parenting behavior in toddlers with neurodevelopmental disabilities

Introduction The presence of a neurodevelopmental disability (ND) represents an adverse condition for child’s development and parent–child relationship, and it is reasonable to assume that the severity of delay may influence parenting behavior. Previous research, however, did not specifically address this issue. Methods This cross-sectional study compared parental behaviors of mothers of toddlers with moderate/severe or mild/borderline developmental delay and mothers of toddlers with typical development, while considering maternal emotional states. A total of 88 dyads with children aged between 12 and 47 months participated in a 10-min video-recorded interaction then coded with the PICCOLO, a validated observation checklist that assesses four dimensions of parenting: affection, responsiveness, encouragement, and teaching. The mothers also fulfilled two standardized questionnaires assessing parental stress and presence of depressive symptoms. MANOVA and MANCOVA models were used to explore between-group differences in specific parenting dimensions, also considering parental stress. Results Mothers of toddlers with ND were less responsive than the comparison group, while the presence of a moderate/severe developmental delay specifically affected teaching behaviors. No differences emerged for affection and encouragement behaviors. Importantly, although mothers of toddlers with moderate/severe ND reported higher child-related dysfunctional interaction stress, this did not directly affect parenting behaviors. Discussion These findings highlight how the presence of a disability and the severity of developmental delay can affect specific dimensions of parenting (i.e., responsiveness, teaching) and might inform clinical practice and research on early parental interventions.
An AI-Enabled Bias-Free Respiratory Disease Diagnosis Model Using Cough Audio

Cough-based diagnosis for respiratory diseases (RDs) using artificial intelligence (AI) has attracted considerable attention, yet many existing studies overlook confounding variables in their predictive models. These variables can distort the relationship between cough recordings (input data) and RD status (output variable), leading to biased associations and unrealistic model performance. To address this gap, we propose the Bias-Free Network (RBF-Net), an end-to-end solution that effectively mitigates the impact of confounders in the training data distribution. RBF-Net ensures accurate and unbiased RD diagnosis features, emphasizing its relevance by incorporating a COVID-19 dataset in this study. This approach aims to enhance the reliability of AI-based RD diagnosis models by navigating the challenges posed by confounding variables. A hybrid of a Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks is proposed for the feature encoder module of RBF-Net. An additional bias predictor is incorporated in the classification scheme to formulate a conditional Generative Adversarial Network (c-GAN) that helps in decorrelating the impact of confounding variables from RD prediction. The merit of RBF-Net is demonstrated by comparing classification performance with a State-of-The-Art (SoTA) Deep Learning (DL) model (CNN-LSTM) after training on different unbalanced COVID-19 data sets, created by using a large-scale proprietary cough data set. RBF-Net proved its robustness against extremely biased training scenarios by achieving test set accuracies of 84.1%, 84.6%, and 80.5% for the following confounding variables—gender, age, and smoking status, respectively. RBF-Net outperforms the CNN-LSTM model test set accuracies by 5.5%, 7.7%, and 8.2%, respectively.
Optimization of Permanent Magnet Synchronous Motor for Industrial Ceiling Fans Based on Differential Evolutionary Algorithm

In this paper a 72-slot, 60-pole, high-torque, low-speed external rotor permanent magnet synchronous motor, which is aiming to fulfill the industrial large-scale ceiling fans’ demands for high torque density and minimal torque pulsation, is designed. A targeted optimization is also conducted on the motor. Given the structural properties of the permanent magnet synchronous motor, it naturally produces cogging torque. This can result in the motor’s torque ripple, vibration, and noise, particularly noticeable at low speeds. Consequently, implementing methods to reduce this cogging torque is highly significant. The paper employs a differential evolutionary algorithm to enhance a multi-objective motor design scheme and the corresponding optimization scheme is proposed. It involves tuning pole-slot coordination and adjusting motor parameters, all while reducing the cogging torque and maintaining output torque under load condition. The effectiveness of the motor design is ultimately confirmed through finite element simulation under various working conditions.
Copper Chaperone for Superoxide Dismutase Subtypes as a Prognostic Marker in Luminal B Breast Cancer

Background: Copper chaperone for superoxide dismutase (CCS) is an essential component of the oxidation-reduction system. In breast cancer cells, CCS expression is highly up-regulated, which contributes to cellular proliferation and migration. Breast cancer is a multifaceted disease with different tumor prognoses and responses to clinical treatments, which may be associated with multiple molecular subtypes of CCS. Methods: The CCS expression patterns in breast cancer were investigated by TNMplot, cBioPortal, and HPA network database. The correlation of CCS expression with clinicopathological parameters was analyzed using the UALCAN database. The Cancer Genome Atlas (TCGA) data set was used to analyze the Clinical characteristics of CCS in luminal B patients. The bc-GenExMiner database was used to analyze the effects of BReast-CAncer susceptibility gene (BRCA)1/2, TP53 mutation status, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER) expression on CCS expression. The survival curves and prognostic value of CCS in luminal B breast cancer were performed through Kaplan-Meier curves, univariate and multivariate Cox regression using the PrognoScan, bc-GenExMiner, and Clinical bioinformatics analysis platform. Results: We found that CCS expression was associated with patient age, race, ER, and PR status. We also discovered that BRCA1/2 mutations had an effect on CCS expression. The luminal B subtype had the highest CCS expression, which was linked to poor survival compared with other subtypes. In addition, Kaplan-Meier curve analysis showed that luminal B patients with high CCS mRNA expression showed a poor survival and the CCS gene is an independent predictor of outcome in patients with luminal B breast cancer by univariate and multivariate Cox regression. Conclusions: Our findings emphasize the significant expression of CCS in luminal B breast cancer and its potential as an autonomous prognostic determinant for this specific molecular subtype. These findings suggest that CCS holds promise as a prospective marker for the treatment of luminal B breast cancer.
Multirelational Fusion Graph Convolution Network With Multiscale Residual Network for Fault Diagnosis of Complex Industrial Processes

Typically, complex industrial processes possess heterogeneous spatial relationships and dynamic temporal correlations due to intervariable coupling and intravariable dynamics. Unfortunately, with the difficulty in modeling heterogeneous relationships and the high computational complexity, existing fault diagnosis methods mainly process heterogeneous relationships as homogeneous relationships, and the influence of temporal correlations is also overlooked, resulting in inappropriate representations and inaccurate fault diagnosis results. To address those issues, this article proposes a multirelational fusion graph convolution network with multiscale residual network (MR-MFGCN) for fault diagnosis of complex industrial processes. Initially, a multiscale residual network (MSRN) is designed to capture dynamic temporal correlations for multisensor data. Then, the extracted features are transformed into a heterogeneous graph, modeling the heterogeneous spatial relationships among multiple sensors. Furthermore, an adaptive multirelational fusion strategy is proposed to construct a lightweight meta-path graph, reducing the complexity of the graph structure and enhancing the overall quality of the graph. Finally, the meta-path graph is modeled by a graph convolution network (GCN), and a coarse-grained graph-level representation is obtained for fault classification. Comprehensive experiments on two industrial processes along with theoretical interpretation validate the effectiveness and reliability of our proposed MR-MFGCN for fault diagnosis of complex industrial processes.