Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding Motion Capture for Computer Animation, Second Edition

The power of today? s motion capture technology has taken animated characters and special effects to amazing new levels of reality. And with the release of blockbusters like Avatar and Tin-Tin, audiences continually expect more from each new release. To live up to these expectations, film and game makers, particularly technical animators and directors, need to be at the forefront of motion capture technology. In this extensively updated edition of Understanding Motion Capture for Computer Animation and Video Games, an industry insider explains the latest research developments in digital design and film, games, medicine, sports, and security engineering. This completely updated new edition tells the complete story of motion capture, including the current state-of-the-art technology, methodology, and the explosive growth of the motion capture industry. In-depth technical explanations pair text and code, to help you understand not only the fundamental tenets of motion capture, but also the reasons behind its successes and failures. This timely new edition is an essential resource for anyone producing realistic motion graphics. Completely revised to include almost 40% new content with emphasis on RF and Facial Motion Capture Systems Companion site with source code, motion capture data translator, and example files help you write conversion and motion data manipulation programs Describes all the mathematical principles associated with motion capture and 3D character mechanics Helps you budget by explaining the costs associated with individualized motion capture projects Table of Contents 1: Motion Capture Primer 1.1 Motion Capture and Performance Animation 1.2 History of Performance Animation in the Entertainment Field 1.3 Types of Motion Capture 1.4 Applications of Motion Capture 2: Motion Capture Case Studies and Controversy 2.1 Digital Humans and the Uncanny Valley 2.2 Relevant Motion Capture Accounts 3: The Motion Capture Session 3.1 Deciding to Use Motion Capture 3.2 Preparing for the Session 3.3 During the Session 3.4 Summary 4: The Motion Data 4.1 Motion Data Types and Formats 4.2 Writing a Motion Capture Translator 5: Setting Up Your Character 5.1 Setting Up a Character with Rotational Data 5.2 Setting Up a Character with Translational Data 5.3 Facial Motion Capture 5.4 Tips and Tricks Conclusion Appendix A: Motion Capture Equipment and Software Manufacturers Appendix B: Motion Capture Service Providers Appendix C: Web Resources
Human arm redundancy: a new approach for the inverse kinematics problem

The inverse kinematics (IK) problem addresses how both humans and robotic systems coordinate movement to resolve redundancy, as in the case of arm reaching where more degrees of freedom are available at the joint versus hand level. This work focuses on which coordinate frames best represent human movements, enabling the motor system to solve the IK problem in the presence of kinematic redundancies. We used a multi-dimensional sparse source separation method to derive sets of basis (or source) functions for both the task and joint spaces, with joint space represented by either absolute or anatomical joint angles. We assessed the similarities between joint and task sources in each of these joint representations, finding that the time-dependent profiles of the absolute reference frame’s sources show greater similarity to corresponding sources in the task space. This result was found to be statistically significant. Our analysis suggests that the nervous system represents multi-joint arm movements using a limited number of basis functions, allowing for simple transformations between task and joint spaces. Additionally, joint space seems to be represented in an absolute reference frame to simplify the IK transformations, given redundancies. Further studies will assess this finding’s generalizability and implications for neural control of movement.
Zingerone attenuates sciatic nerve damage caused by sodium arsenite by inhibiting NF-κB, caspase-3, and ATF-6/CHOP pathways and activating the Akt2/FOXO1 pathway

Objective(s): In the present study, the potential protective effects of zingerone (ZNG) against sciatic nerve damage caused by sodium arsenite (SA), a common environmental pollutant, were evaluated by various biochemical, molecular, and histological methods. Materials and Methods: In the study, SA and ZNG were given to 35 male Sprague Dawley rats for 14 days. At the end of the period, the sciatic nerve tissues were taken and the markers involved in oxidative stress, endoplasmic reticulum stress, inflammation, and apoptosis were analyzed. Results: The data obtained showed that SA decreased glutathione (GSH) levels and increased malondialdehyde (MDA) levels in the sciatic nerve tissue. However, it was determined that these markers approached the control group levels due to the anti-oxidant properties of ZNG. While SA triggered endoplasmic reticulum stress and apoptosis pathways, ZNG suppressed them. Moreover, SA up-regulated inflammatory markers such as nuclear factor kappa-B (NF-κB), tumor necrosis factor-alpha (TNF-α), interleukin-1-beta (IL-1β), and neuronal nitric oxide synthases (nNOS) in the sciatic nerves and caused neuro-inflammation and inhibited cell survival by suppressing serine/threonine-protein kinase 2 (Akt2) and forkhead box protein O1 (FOXO1) genes. It has also been shown histopathologically that SA causes degeneration in the sciatic nerves. In contrast, ZNG suppressed neuro-inflammation, activated Akt2/FOXO1 signaling, and repaired histological irregularities. Conclusion: In general, SA caused oxidative stress, inflammation, ER stress, and apoptosis in the sciatic nerves of rats, causing damage to the tissues, however, ZNG suppressed these pathways and protected the sciatic nerves from the destructive effect of SA.
An eight-season analysis of the teams’ performance in the Spanish LaLiga according to the final league ranking

This study aimed to analyse the performance of 5,518 collective observations of the Spanish LaLiga teams for eight consecutive seasons (from 2011–12 to 2018–19), considering the final league ranking. The teams were divided into four groups: Europe (from 1st to 6th), Upper-Middle (from 7th to 11th), Lower-Middle (from 12th to 17th) and Relegation (from 18th to 20th). The variables recorded were: Passes, Successful Passes, Crosses, Shots, Goals, Corners, Fouls, Width, Length, Height, distance from the goalkeeper to the nearest defender (GkDef), total distance covered (TD) and number of points accumulated. The main results were that: 1) Europe, being superior to the rest of the groups, showed lower values of Length from 2015–16, and lower values of GkDef from 2014–15; 2) Upper-Middle showed lower values of Length from 2015–16; 3) Lower-Middle showed fewer Shots from 2013–14, and lower values of Length, GkDef and TD from 2014–15; and, 4) Relegation barely showed significant differences between seasons in any variable. The study concludes that the teams of the Europe, Upper-Middle and Relegation groups showed quite stable performance, while the teams of the Lower-Middle group presented a worsening in different dimensions as the seasons progressed. The information provided in this study makes it possible to have reference values that have characterized the performance of the teams for each group.
Social domains of poor mental health: A qualitative pilot study of community stakeholders’ understanding and demarcation of mental illness and its interpretations in rural Nigeria

Abstract Background and Aims Although previous studies on mental health/illness in Nigeria have explored knowledge and attitude of community members using quantitative approaches, few studies have engaged stakeholders within rural communities on the issue of mental illness using qualitative approaches. Community stakeholders play a critical role in influencing health behaviors. The objective of this pilot study was to explore community stakeholders’ understanding and demarcation of mental illness, and its interpretations in a rural Nigerian town. This is with the aim of shaping stakeholders understanding of people when they experience mental distress within the community. Methods The study was conducted in Ijebu‐Igbo town of Ogun State in south‐west Nigeria. In‐depth interviews were conducted among two religious’ leaders: a Pastor and an Imam, a traditional healer, a medical doctor, and a registered nurse, and a focus group discussion was held in a church with members of its advisory committee. Results The findings showed that community stakeholders gave multiple interpretations of mental illness and many attribute mental illness to spiritual attack, ancestral curse, anger of the gods, and personal affliction (Ogun‐Afowofa). This has been categorized as familial and individual attributes in this study which is part of the main themes derived. The study findings also show that the understanding of community members regarding the root causes of mental illness is somewhat vague based on their poor knowledge of mental illness. This is because of the various interpretations they gave to explain mental health is based on their cultural orientation, socialization, and belief system, and not based on any medical knowledge. Conclusion This pilot study was conducted to justify the main study. There is therefore a need for health education interventions to enlighten and educate community stakeholders with requisite knowledge for better understanding and interpretation of mental illness. Also, through mental health education interventions, community members will gain clarity on what mental health is and what it is not.
An overview of pharmacological effects of Crocus sativous and its constituents

Crocus sativus L. was used for the treatment of a wide range of disorders in traditional medicine. Due to the extensive protective and treatment properties of C. sativus and its constituents in various diseases, the purpose of this review is to collect a summary of its effects, on experimental studies, both in vitro and in vivo. Databases such as PubMed, Science Direct, and Scopus were explored until January 2023 by employing suitable keywords. Several investigations have indicated that the therapeutic properties of C. sativus may be due to its anti-oxidant and anti-inflammatory effects on the nervous, cardiovascular, immune, and respiratory systems. Further research has shown that its petals also have anticonvulsant properties. Pharmacological studies have shown that crocetin and safranal have anti-oxidant properties and through inhibiting the release of free radicals lead to the prevention of disorders such as tumor cell proliferation, atherosclerosis, hepatotoxicity, bladder toxicity, and ethanol induced hippocampal disorders. Numerous studies have been performed on the effect of C. sativus and its constituents in laboratory animal models under in vitro and in vivo conditions on various disorders. This is necessary but not enough and more clinical trials are needed to investigate unknown aspects of the therapeutic properties of C. sativus and its main constituents in different disorders.
Significant duration prediction of seismic ground motions using machine learning algorithms

This study aims to predict the significant duration (D5-75, D5-95) of seismic motion by employing machine learning algorithms. Based on three parameters (moment magnitude, fault distance, and average shear wave velocity), two additional parameters(fault top depth and epicenter mechanism parameters) were introduced in this study. The XGBoost algorithm is utilized for characteristic parameter optimization analysis to obtain the optimal combination of four parameters. We compare the prediction results of four machine learning algorithms (random forest, XGBoost, BP neural network, and SVM) and develop a new method of significant duration prediction by constructing two fusion models (stacking and weighted averaging). The fusion model demonstrates an improvement in prediction accuracy and generalization ability of the significant duration when compared to single algorithm models based on evaluation indicators and residual values. The accuracy and rationality of the fusion model are validated through comparison with existing research.
Protective effects of naringin against oxaliplatin-induced testicular damage in rats: Involvement of oxidative stress, inflammation, endoplasmic reticulum stress, apoptosis, and histopathology

Objective(s): Oxaliplatin (OXL) is a platinum-based chemotherapeutic agent widely used in the treatment of colorectal cancer. Unfortunately, this important drug also causes unwanted side effects such as neuropathy, ototoxicity, and testicular toxicity. This study aimed to investigate the possible protective effects of naringin (NRG) against OXL-induced testicular toxicity in rats. Materials and Methods: In the present study, rats were injected with OXL (4 mg/kg, b.w./day, IP) in 5% dextrose solution 30 min after oral administration of NRG (50 and 100 mg/kg, b.w./day) on the 1st, 2nd, 5th, and 6th days. Then, the rats were sacrificed on the 7th day and the testicular tissues were removed. Results: The results showed that NRG decreased (P<0.001) lipid peroxidation, increased (P<0.001) the activities of superoxide dismutase (SOD), glutathione peroxidase (GPx), catalase (CAT), and the levels of glutathione (GSH), and also maintained the testis histological architecture and integrity. NRG decreased the levels of apoptosis-related markers such as caspase-3, Bax, and Apaf-1 and increased Bcl2 in the OXL-induced testicular toxicity (P<0.001). In addition, NRG reversed the changes in mRNA transcript levels of oxidative stress, inflammation, and endoplasmic reticulum stress parameters such as Nrf2, HO-1, NQO1, RAGE, NLRP3, MAPK-14, STAT3, NF-κB, IL-1β, TNF-α, PERK, IRE1, ATF6, and GRP78 in OXL-induced testicular toxicity (P<0.001). Conclusion: Our results demonstrated that NRG can protect against OXL-induced testicular toxicity by enhancing the anti-oxidant defense system and suppressing apoptosis, inflammation, and endoplasmic reticulum stress.
Exploring men’s health in medium and high complexity care in Brazil: A deductive thematic analysis of social determinants

Background Men’s health is influenced by a complex interplay of social, economic, and cultural determinants. Understanding how these aspects affect the health of adult cisgender men in medium and high-complexity healthcare settings is essential for improving healthcare services and promoting better health outcomes. Objective This study aimed to analyze the health status of adult cisgender men in medium and high-complexity healthcare settings based on social determinants and conditioners. Methods This study employed a qualitative design involving 45 adult cisgender men receiving care in medium/high complexity services in Bahia, Brazil. Semi-structured interviews were conducted from July 2019 to February 2020, and data were interpreted based on Dahlgren and Whitehead’s Model of Social Determinants of Health using deductive thematic analysis. Results Proximal determinants included biological aspects, preventive behaviors, lifestyle/social life, and aging processes. Intermediate factors included work conditions, access/utilization of healthcare services/medications, and psychosocial factors. Macro determinants involved income distribution, power dynamics, resource allocation, health inequalities/iniquities, morbidity, culture, political decisions, environmental factors, and structural elements. Conclusion The health status of men in medium/high complexity care was profoundly influenced by structural social determinants. These determinants impacted healthcare attention, service organization, cultural influences, the reproduction of hegemonic masculinity patterns, lifestyle, social support, and socioeconomic conditions necessary to realize the right to health. Nursing practices should conduct comprehensive assessments that extend beyond physical health indicators.
and Its Association with Craving and Dependence in

Increased salience of drug-related cues over non-drug reinforcers can drive drug use behaviors and contribute to tobacco use disorder (TUD). An important scientific and clinical goal is to effectively measure this elevated drug-seeking behavior in TUD. However, most TUD assessments rely on self-reported cravings and cigarette consumption, not providing an objective measure of cue-induced drug seeking. The probabilistic image choice (PIC) task, initially developed and validated for cocaine use disorder (and since validated in users of methamphetamine and opioids), investigates the choice of viewing drug-related pictures as compared to other salient pictures (e.g., pleasant and unpleasant cues). This study aimed to develop and validate the PIC task for TUD and evaluate the associations between behavioral choice and tobacco craving, daily cigarette consumption, and nicotine dependence (the Fagerström score). We recruited 468 smokers and 121 nonsmokers using the Prolific online platform. Participants performed the PIC task twice (at a one-month interval) and completed other measures relevant to TUD. As expected, compared to nonsmokers, tobacco smokers selected to view significantly more tobacco images and less pleasant (non-drug reinforcer) images, a profile that remained stable at retest. Drug seeking on the PIC task was associated with craving but not with the other tobacco dependence measures, suggesting that the task is better at modeling current drug “wanting” rather than cumulative nicotine exposure or physical dependence. In conclusion, these results suggest that the PIC task can be a valuable tool for objectively assessing craving-associated tobacco seeking in TUD.
Psychometric properties of a Saudi Arabian version of the Birth Satisfaction Scale-Revised (BSS-R)

Background Maternal outcomes are closely associated with birth satisfaction, and the Birth Satisfaction Scale-Revised (BSS-R), a concise, multidimensional self-report measure, has undergone translation and validation internationally. However, research on birth satisfaction in Saudi Arabia is scarce. The absence of valid Arabic-language tools for the Saudi population may impede critical research on this topic, necessitating the translation and use of psychometrically sound instruments for measuring birth satisfaction in Saudi women. Objective This study aimed to translate and evaluate the psychometric properties of the Saudi Arabian version of the BSS-R (SA-BSS-R). Methods A total of 218 Saudi women participated in the study, and psychometric analysis of the translated SA-BSS-R involved confirmatory factor analysis, divergent validity analysis, and known-group discriminant validity assessment within a cross-sectional study design. Results The three-factor BSS-R measurement model displayed poor fit, and internal consistency fell below the threshold value. Additionally, it was observed that women undergoing an episiotomy had significantly lower overall SA-BSS-R scores. Conclusion The SA-BSS-R manifested atypical measurement properties in this population. Despite insightful observations related to episiotomy, the identified measurement shortcomings highlight the need for a more robust and culturally sensitive translation to enhance measurement characteristics.
On-the-Fly Pipeline Parallelism

Pipeline parallelism organizes a parallel program as a linear sequence of stages. Each stage processes elements of a data stream, passing each processed data element to the next stage, and then taking on a new element before the subsequent stages have necessarily completed their processing. Pipeline parallelism is used especially in streaming applications that perform video, audio, and digital signal processing. Three out of 13 benchmarks in PARSEC, a popular software benchmark suite designed for shared-memory multiprocessors, can be expressed as pipeline parallelism. Whereas most concurrency platforms that support pipeline parallelism use a “construct-and-run” approach, this article investigates “on-the-fly” pipeline parallelism, where the structure of the pipeline emerges as the program executes rather than being specified a priori. On-the-fly pipeline parallelism allows the number of stages to vary from iteration to iteration and dependencies to be data dependent. We propose simple linguistics for specifying on-the-fly pipeline parallelism and describe a provably efficient scheduling algorithm, the Piper algorithm, which integrates pipeline parallelism into a work-stealing scheduler, allowing pipeline and fork-join parallelism to be arbitrarily nested. The Piper algorithm automatically throttles the parallelism, precluding “runaway” pipelines. Given a pipeline computation with T1 work and T∞ span (critical-path length), Piper executes the computation on P processors in TP ≤ T1/P+O(T∞+lg P) expected time. Piper also limits stack space, ensuring that it does not grow unboundedly with running time. We have incorporated on-the-fly pipeline parallelism into a Cilk-based work-stealing runtime system. Our prototype Cilk-P implementation exploits optimizations such as “lazy enabling” and “dependency folding. ” We have ported the three PARSEC benchmarks that exhibit pipeline parallelism to run on Cilk-P. One of these, x264, cannot readily be executed by systems that support only construct-and-run pipeline parallelism. Benchmark results indicate that Cilk-P has low serial overhead and good scalability. On x264, for example, Cilk-P exhibits a speedup of 13.87 over its respective serial counterpart when running on 16 processors.
Classification of chronic ankle instability using machine learning technique based on ankle kinematics during heel rise in delivery workers

Objective Ankle injuries in delivery workers (DWs) are often caused by trips, and high recurrence rates of ankle sprains are related to chronic ankle instability (CAI). Heel rise requires joint angles and moments similar to those of the terminal stance phase of walking that the foot supinates. Thus, our study aimed to develop, determine, and compare the predictive performance of statistical machine learning models to classify DWs with and without CAI using ankle kinematics during heel rise. Methods In total, 203 DWs were screened for eligibility. Seven predictors were included in our study (age, work duration, body mass index, calcaneal stance position angle [CSPA] in the initial and terminal positions during heel rise, calcaneal movement during heel rise [CMHR], and plantar flexion angle during heel rise). Six machine learning algorithms, including logistic regression, decision tree, AdaBoost, Extreme Gradient boosting machines, random forest, and support vector machine, were trained. Results The random forest model (area under the curve [AUC], 0.967 [excellent]; F1, 0.889; accuracy, 0.925) confirmed the best predictive performance in the test datasets among the six machine learning models. For Shapley Additive Explanations, old age, low CMHR, high CSPA in the initial position, high PFA, long work duration, low CSPA in the terminal position, and high body mass index were the most important predictors of CAI in the random forest model. Conclusion Ankle kinematics during heel rise can be considered in the classification of DWs with and without CAI.