Miracle-dz/UniFAR-FTUs huggingface dataset:
Profiles of Motor-Cognitive Interference in Parkinson’s Disease—The Trail-Walking-Test to Discriminate between Motor Phenotypes

Background and Aims. Most research on Parkinson’s disease (PD) focuses on describing symptoms and movement characteristics. Studies rarely focus on the early detection of PD and the search for suitable markers of a prodromal stage. Early detection is important, so treatments that may potentially change the course of the disease can be attempted early on. While gait disturbances are less pronounced in the early stages of the disease, the prevalence, and severity increase with disease progression. Therefore, postural instability and gait difficulties could be identified as sensitive biomarkers. The aim was to evaluate the discriminatory power of the Trail-Walking Test (TWT; Schott, 2015) as a potential diagnostic instrument to improve the predictive power of the clinical evaluation concerning the severity of the disease and record the different aspects of walking. Methods. A total of 20 older healthy (M = 72.4 years, SD = 5.53) adults and 43 older adults with PD and the motor phenotypes postural instability/gait difficulty (PIGD; M = 69.7 years, SD = 8.68) and tremor dominant (TD; M = 68.2 years, SD = 8.94) participated in the study. The participants performed a motor-cognitive dual task (DT) of increasing cognitive difficulty in which they had to walk a given path (condition 1), walk to numbers in ascending order (condition 2), and walk to numbers and letters alternately and in ascending order (condition 3). Results. With an increase in the cognitive load, the time to complete the tasks (seconds) became longer in all groups, F(1.23, 73.5) = 121, p < 0.001, ɳ2p = 0.670. PIGD showed the longest times in all conditions of the TWT, F(2, 60) = 8.15, p < 0.001, ɳ2p = 0.214. Mutual interferences in the cognitive and motor domain can be observed. However, clear group-specific patterns cannot be identified. A differentiation between the motor phenotypes of PD is especially feasible with the purely motor condition (TWT-M; AUC = 0.685, p = 0.44). Conclusions. PD patients with PIGD must be identified by valid, well-evaluated clinical tests that allow for a precise assessment of the disease’s individual fall risk, the severity of the disease, and the prognosis of progression. The TWT covers various aspects of mobility, examines the relationship between cognitive functions and walking, and enables differentiation of the motor phenotypes of PD.
Photophoresis of spherical particles in Slip-flow regime

Photophoresis is a particle-light-induced phenomenon with several applications, such as spectroscopy, 3-Dimensional displays, and nanomanufacturing, to name a few. This work synthesizes, criticizes, and compares the main hydrodynamic and gas-kinetic models developed to quantify photophoretic forces in the slip-flow regime for uniform light beams, contrasting their predictions with experimental data available in the literature. The results comparing the different models evidence the simplicity and accuracy of Loesche and Husmann's model, which is then confronted with the experimental data available in the literature. However, considering the noticeable effect of high irradiance levels on photophoretic forces, namely, when temperature variations significantly change the thermofluid properties of the gaseous layer around the particle, more experiments are recommended to validate theoretical models. Finally, considering the photophoretic models depend on two asymmetry factors, J0 and J1, a physical interpretation of their meaning is provided, especially for the oscillations in the later argued as the result of Mie resonance effects.
Real-Time Stroke Textures

Shading in line drawings is expressed by varying the stroke width or density of strokes covering an object’s surface. In their pioneering work, Winkenbach and Salesin introduced the concept of “prioritized stroke textures” to the emerging field of non-photorealistic rendering1. Despite the advances in processing power in the years since then, the sheer number of lines to draw prevents this method from running in real-time. A real-time approach for hatching was presented by Lake et al.2, which chooses from a set of textures based on the brightness at vertices, subdividing polygons if necessary. However, the method is very CPU-heavy and requires many polygons.
A High-Dimensional Approach to Predicting Audit Opinions

ABSTRACT This study develops a model for the prediction of audit reports. The research data comprises 57881 firm-year observations for public companies listed on the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), and the NASDAQ from 2000 to 2019. The dataset consists of a high dimension of predictor variables (105 variables), including accounting-based, ownership concentration, executive compensation, market price, analysts rating, macroeconomic, and audit-related variables. A commercial version of Gradient Boosting, called TreeNet®, is used to build the prediction model. The results indicate that the developed model demonstrates high performance in predicting going-concern reports with an accuracy rate of 97.5%.
Concentration‐dependent effects of proinflammatory cytokines on barrier function and tight junction protein expression in brain microvascular endothelial cells and the hypothermic and hyperthermic effects on tight junction protein expression

The mechanisms underlying therapeutic hypothermia, which protects neurons following severe brain damage, are only partially understood. We previously demonstrated that hypothermia reduced, whereas hyperthermia augmented, the release of tumor necrosis factor (TNF)‐α and interleukin (IL)‐17. Cerebral ischemia causes the loss of the blood–brain barrier (BBB) integrity, thereby increasing cerebral vascular permeability, which directly contributes to vasogenic edema, hemorrhagic transformation, and increased mortality. Brain microvascular endothelial cells (BMVECs) are a major component of BBB and tight junction proteins (TJPs) in these cells maintain the BBB integrity. In this study we determined the mechanisms underlying this treatment by measuring the effects of TNF‐α and IL‐17 on BMVEC barrier function and TJP expression in BMVECs, and by evaluating the effects of hypothermia and hyperthermia on TJP expression.
A model predictive obstacle avoidance method based on dynamic motion primitives and a Kalman filter

A dynamic motion primitive (DMP) is a robust framework that generates obstacle avoidance trajectories by introducing perturbative terms. The perturbative term is usually constructed with an artificial potential field (APF) method. Dynamic obstacle avoidance is rarely considered with this approach; furthermore, even when dynamic obstacles are considered, only the velocity and position information of the current state are incorporated into the obstacle avoidance framework. However, if the position of an obstacle changes suddenly, a robot may be placed in a dangerous position close to the obstacle, resulting in large obstacle avoidance accelerations, sharp trajectories, or even obstacle avoidance failure. Therefore, we present a model predictive obstacle avoidance method based on dynamic motion primitives and a Kalman filter. This method has three main components: Dynamic motion primitives are used to generate the desired trajectory and introduce perturbations to achieve obstacle avoidance; the Kalman filter method is adopted to estimate the future positions of the obstacles; and model predictive control is employed to optimize the repulsive force generated by the APF while minimizing the defined cost function, thus guaranteeing the safety and flexibility of the method. We validate the presented method with 2D and 3D obstacle avoidance simulations. The method is also verified with a real robot: the‐Kinova MOVO. The simulation and experimental results show that the proposed method not only avoids dynamic obstacles but also tracks the desired trajectory more smoothly and precisely.
Considering a Need for Dementia-Specific, Family-Centered Patient Navigation in Canada

Patient navigation has been proposed as a novel family-centered, integrated care model to address the care needs of persons living with dementia and their family caregivers by helping them navigate the complex range of dementia services offered in hospital and community settings. A key informant qualitative descriptive study explored the perspectives of 48 healthcare professionals to explore the need for dementia-specific patient navigation. Data were analyzed thematically. We identified one overarching theme: “Variability in the Need for Illness-Specific Patient Navigation” and five themes that highlight considerations when providing navigation to individuals with dementia: (1) Taking Part in Ongoing Training, (2) Addressing Stigma, (3) Focusing on Quality of Life, (4) Defining Home, and (5) A Continuous Process of Support. These themes provide preliminary insights into the conceptual differences about the need for illness-specific patient navigation and the areas within patient navigation where healthcare professionals are encouraged to find consensus.
Rapid Recognition of Different Sources of Heroin Drugs by Using a Hand-Held Near-Infrared Spectrometer Based on a Multi-Layer Extreme Learning Machine Algorithm

Rapid recognition of the sources of drugs can provide some valuable clues and the basis for determining the nature of the case. A novel recognition method was put forward to identify the sources of heroin drugs rapidly and non-destructively by using a hand-held near infrared (NIR) spectrometer and a multi-layer-extreme learning machine (ML-ELM) algorithm. In contrast to traditional linear discriminant analysis (LDA), support vector machine (SVM) and extreme learning machine (ELM) algorithms, the accuracy, sensitivity and specificity were the highest for the proposed ML-ELM algorithm. The prediction accuracy of the ML-ELM algorithm was 25.33, 20.00, 17.33% higher than that of LDA, SVM and ELM algorithm, respectively, for 4 cases. The ML-ELM models for recognizing the different sources of heroin drugs had the best generalization ability and prediction results. The experimental results indicated that the combination of the hand‑held NIR technology and ML-ELM algorithm can recognize the different sources of heroin drugs rapidly, accurately, and non-destructively on the spot.
Vagal milieu or electrophysiologic substrate? The link between atrial fibrillation and obstructive sleep apnea

Atrial fibrillation is the most common cardiac arrhythmia with its prevalence expected to increase to 12.1 million people in the United States by 2030. Chronic underlying conditions that affect the heart and lungs predispose patients to develop atrial fibrillation. Obstructive sleep apnea is strongly associated with atrial fibrillation. Several pathophysiological mechanisms have been proposed to elucidate this relationship which includes electrophysiological substrate modification and the contribution of the autonomic nervous system. In this comprehensive review, we highlight important relationships and plausible causality between obstructive sleep apnea and atrial fibrillation which will improve our understanding in the evaluation, management, and prevention of atrial fibrillation. This is the most updated comprehensive review of the relationship between obstructive sleep apnea and atrial fibrillation.
Simple Models Outperform More Complex Big‐Leaf Models of Daily Transpiration in Forested Biomes

Transpiration makes up the bulk of total evaporation in forested environments yet remains challenging to predict at landscape‐to‐global scales. We harnessed independent estimates of daily transpiration derived from co‐located sap flow and eddy‐covariance measurement systems and applied the triple collocation technique to evaluate predictions from big leaf models requiring no calibration. In total, four models in 608 unique configurations were evaluated at 21 forested sites spanning a wide diversity of biophysical attributes and environmental backgrounds. We found that simpler models that neither explicitly represented aerodynamic forcing nor canopy conductance achieved higher accuracy and signal‐to‐noise levels when optimally configured (rRMSE = 20%; R2 = 0.89). Irrespective of model type, optimal configurations were those making use of key plant functional type dependent parameters, daily LAI, and constraints based on atmospheric moisture demand over soil moisture supply. Our findings have implications for more informed water resource management based on hydrological modeling and remote sensing.
Complemetary Observations for the CoRoT Exoplanet Program

We review the needs of the CoRoT /exoplanet program in terms of complementary observations. Such observations are indeed an essential element of the science of the CoRoT mission at different levels: prior to the launch for a characterization and a careful selection of the target stars in the exoplanet fields and during or after the CoRoT flight phase to affirm the planetary nature of detected transit events and to obtain planet and parent star properties in more detail. To prepare the sequence of CoRoT observations and to optimize the scientific analysis of the results, we built a stellar catalog of more than 10 millions of stars, based mainly on photometric observations from a large ground-based program we conducted for 3 years, and from existing catalogs. From optical and near-IR broad-band colors, we were able to perform the spectral classification of all stars within the range of V= 11 to 16. The method we used has the big advantage of allowing the observation of very large fields in a reasonable amount of telescope time and of providing reliable results on the spectral type and the luminosity class of about 80% of the stars. The quality of these estimates has been evaluated by comparison to the first results of a spectroscopic program carried out on a limited sample of stars. Our analysis not only allows to characterize the stellar population in the exoplanet fields but also provides, as an interesting by-product, new information to models of the Galactic stellar population close to the Galactic plane. All the preliminary information we collect on the target stars will be used during the CoRoT light curves analysis to remove ambiguities about the nature of the detected transiting object. In most cases, follow-up bservations are however still necessary to further filter out non-planetary transiting objects, as the large size of the CoRoT's PSF makes confusion with background eclipsing binaries likely. They are also mandatory to get independent verifications about the true nature of detected planets, as well as to obtain a maximum of information about them. This led us to set up a complete observing strategy, involving both radial velocity measurements and high spatial resolution photometry as well as possible space-based observations. This huge observational effort will also provide a unique and detailed basis for further statistical analysis of the properties of planets and their host stars, where preparatory observations constitute an unbiased and homogeneous sample, made with stars with and without planets.
When time is short, and we are late!: A story of chronic meningitis

We often face situations when the exact etiological diagnosis of meningitis is difficult. The reason behind this is that many pathogens have similar clinical, radiological, and laboratory pictures. The low yield of the pathogen in cerebrospinal fluid (CSF), non-availability of detail tests in all corners of the world, delay in availability of reliable results (like cultures), and difficulty in performing confirmatory tests like brain biopsy (in inconclusive cases) make the job of a clinician challenging. We report here a case where a late diagnosis of a disease owing to inconclusive results leads to dissemination. The complications following the introduction of the treatment based on presumption lead to further difficulty. We remained inclined to our diagnosis based on clinical judgement, acknowledged and managed the inflammatory changes secondary to the infection, and finally won the long battle. So, sometimes we need to make decisions based on clinical grounds. We need to depend on the fact that uncommon presentations of common diseases are commoner than a common presentation of uncommon diseases.
A Comprehensive Survey on the Process, Methods, Evaluation, and Challenges of Feature Selection

Feature selection is employed to reduce the feature dimensions and computational complexity by eliminating irrelevant and redundant features. A vast amount of increasing data and its processing generates many feature sets, which are reduced by the feature selection process to improve the performance in all types of classification, regression, clustering models. This study performs a detailed analysis of motivation and concentrates on the fundamental architecture of feature selection. This study aims to establish a structured formation related to popular methods such as filters, wrappers and, embedded into search strategies, evaluation criteria, and learning methods. Different methods organize a comparison of the benefits and drawbacks followed by multiple classification algorithms and standard validation measures. The diversity of applications in multiple domains such as data retrieval, prediction analysis, and medical, intrusion, and industrial applications is efficiently highlighted. This study focuses on some additional feature selection methods for handling big data. Nonetheless, new challenges have surfaced in the analysis of such data, which were also addressed in this study. Reflecting on commonly encountered challenges and clarifying how to obtain the absolute feature selection method are the significant components of this study.
The Proportion and Type of Carbohydrates in the Diets of Children in Early Adolescence

Background: Carbohydrates are mainly substrates for energy metabolism and can affect satiety, blood glucose levels, insulin secretion, and fat metabolism. Their amount and type in the diet affect metabolic responses. High-carbohydrate diets, particularly high sugar consumption, are considered particularly harmful because of their specific characteristics related to postprandial metabolism, effects on hunger and satiety, and thus on caloric intake and energy balance. The European Food Safety Authority has suggested that the reference intake for carbohydrates should be between 45 and 60% of total energy requirements and less than 10% should be added sugars, especially for children. Objective: Investigate the proportion and type of carbohydrates in the diets of children in early adolescence in two territorially distinct areas, the continental and the Mediterranean. Methods: The study was conducted as part of a longitudinal cohort study. The survey was conducted in elementary schools in two regions: continental and Mediterranean. The School Physical Activity and Nutrition Survey was used for research purposes. Descriptive and inferential statistical tests were applied for data analysis. Results: A total of 1,411 respondents of both sexes aged 12-15 years, 729 boys and 678 girls, participated in the study. The intake of carbohydrates in the total sample is represented in the daily intake of 59%. The proportion of natural sugar in the diet of boys is statistically significantly higher in the continental compared to the Mediterranean region at the age of 12-13 years (p = 0.002), 13-14 years (p = 0.049), and 14-15 years (p = 0.002). Added sugars in total carbohydrate intake are statistically significantly higher in girls in the Mediterranean region compared to the continental region at ages 12-13 years (p = 0.048), 13-14 years (p = 0.001), and 14-15 years (p = 0.001). Conclusion: The high intake of added sugars in children in the Mediterranean region is of concern, although the intake in the continental area is well above current recommendations. Therefore, one of the public health goals is to promote proper nutrition as well as the availability of healthy foods in schools, especially during early adolescence when proper eating habits are adopted.
Modeling and Characterizing Two Dielectric Elastomer Folding Actuators for Origami-Inspired Robot

Origami-inspired robots are automated machines that achieve deformation and function through folding. This letter models and characterizes two dielectric elastomer folding actuators, and proposes a new method for driving origami-inspired robots. Multilayer bending dielectric elastomer actuators (MBDEAs) and minimum energy structural dielectric elastomer actuators (MESDEAs) are placed at the creases to drive a rigid origami-inspired robot joint. We establish an analytical model of MBDEAs based on beam bending theory. This model establishes the relationships between the deformation angle and output moment of the MBDEA and the input electric field intensity according to the design parameters. In addition, a design model of MESDEAs with the rectangular hollow area is presented for the equilibrium deformation angle and maximum output moment. The analytical model of MBDEAs for the deformation angle and the design model of MESDEAs are both preliminarily verified by experiments. Finally, we realize the drive of the joint based on MBDEAs and MESDEAs. The design and model are evaluated through experiments. This work paves the way for subsequent motion control of origami-inspired robots and further expands the application fields of dielectric elastomer actuators (DEAs).
Insulator Contamination Monitoring Based on Its Hygroscopicity Under Unsaturated Humidity

Pollution flashover of transmission line insulator seriously affects the safe operation of the power system. The insulator contamination is mostly deposited in dry weather, while the existing leakage-current-based pollution warning models could only send out a warning signal at a saturated moisture level, which seldomly happens and would be late for the pollution warning for online insulators. To monitor the change of insulation pollution degree under unsaturated humidity, a new method based on the humidity change and insulator contamination wetting characteristics is proposed in this article. It has been found that under 75%–99% relative humidity (RH), with the change of atmospheric humidity, the water content of the contamination changes from an equilibrium value to another equilibrium value exponentially, resulting in a linear relationship between the leakage current and the relative humidity with a slope proportional to the insulator pollution degree. Therefore, the site pollution degree of insulators can be obtained by the minute measured value.
Formation of planetesimals in the solar nebula

The evolution of solid particles in the solar nebula (or other circumstellar disk) is described. Motions of bodies less than about 1 km in size were dominated by gas drag rather than gravity. An original population of microscopic grains had to produce greater than km-sized planetesimals before gravitational accretion of planets could begin. Planetesimals probably formed by coagulation of grain aggregates that collided due to differential settling, turbulence, and drag-induced orbital decay. Growth of such aggregates depended on sticking mechanisms and their mechanical properties, which are poorly understood. Their growth was aided by concentration of larger bodies toward the central plane of the disk. The nebula could remain optically thick during this process. It is unlikely that a particle layer formed by settling would undergo gravitational instability, as a small amount of turbulence would keep the particle layer from reaching the critical density. This conclusion is independent of the particle size, as even large bodies do not effectively decouple from the gas. Even in a laminar disk, shear in the particle layer would generate enough turbulence to keep it stirred up.