Miracle-dz/UniFAR-FTUs huggingface dataset:
A small electrostatic retarding field energy analyzer with compensating differentiation circuit

A small electrostatic retarding field energy analyzer is constructed in order to measure locally the ion energy distribution functions parallel and perpendicular to a magnetic field. A compensating differentiation circuit enables it to yield the energy distributions clearly in spite of the smallness of the signal available in a low‐density plasma. An application is performed to reveal local anisotropic heating due to a plasma instability.
Structural Basis of Botulinum Toxin Type F Binding to Glycosylated Human SV2A: In Silico Studies at the Periphery of a Lipid Raft

Botulinum neurotoxins are the deadliest microbial neurotoxins in humans, with a lethal dose of 1 ng/kg. Incidentally, these neurotoxins are also widely used for medical and cosmetic purposes. However, little is known about the molecular mechanisms that control binding of botulinum neurotoxin type F1 (BoNT/F1) to its membrane receptor, glycosylated human synaptic vesicle glycoprotein A (hSV2Ag). To elucidate these mechanisms, we performed a molecular dynamics simulation (MDS) study of initial binding kinetics of BoNT/F1 to SV2A. Since this toxin also interacts with gangliosides, the simulations were performed at the periphery of a lipid raft in the presence of both SV2A and gangliosides. Our study suggested that interaction of BoNT/F1 with SV2A is exclusively mediated by N-glycan moiety of SV2A, which interacts with aromatic residues Y898, Y910, F946, Y1059 and H1273 of this toxin. Thus, in contrast with botulinum neurotoxin A1 (BoNT/A1), BoNT/F1 does not interact with protein content of SV2A. We attributed this incapability to a barrage effect exerted by neurotoxin residues Y1132, Q1133 and K1134, which prevent formation of long-lasting intermolecular hydrogen bonds. We also provided structural elements that suggest that BoNT/F1 uses the strategy of BoNT/A1 combined with the strategy of botulinum neurotoxin type E to bind N-glycan of its glycoprotein receptor. Overall, our study opened a gate for design of a universal inhibitor aimed at disrupting N-glycan–toxin interactions and for bioengineering of a BoNT/F1 protein that may be able to bind protein content of synaptic vesicle glycoprotein for therapeutic purposes.
The Determination of Deposition Parameters for Carbon-Based Materials in an Inductively Coupled Plasma System Using COMSOL

A 2-D axisymmetric fluid model simulation of inductively coupled discharges of a methane plasma is presented. The continuity equations for charged species and electron energy are solved with COMSOL Multiphysics. A constant frequency and gas pressure, 13.56 MHz and 0.02 Torr, respectively, are used. Initially, a coil power of 100 W is used, but this is later adjusted to include various coil powers up to 600 W. A Boltzmann equation solver is used to calculate the electron energy distribution function (EEDF) and reduced electron mobility. The effects of increased coil power are investigated, and the results indicate that increases in power increases moderately the electron temperature and charge densities. The growth rate of carbon across the substrate holder is mapped to determine a growth profile for the system.
Linear multi‐scale modeling of diffusion MRI data: A framework for characterization of oriented structures across length scales

Diffusion‐weighted magnetic resonance imaging (DW‐MRI) has evolved to provide increasingly sophisticated investigations of the human brain's structural connectome in vivo. Restriction spectrum imaging (RSI) is a method that reconstructs the orientation distribution of diffusion within tissues over a range of length scales. In its original formulation, RSI represented the signal as consisting of a spectrum of Gaussian diffusion response functions. Recent technological advances have enabled the use of ultra‐high b‐values on human MRI scanners, providing higher sensitivity to intracellular water diffusion in the living human brain. To capture the complex diffusion time dependence of the signal within restricted water compartments, we expand upon the RSI approach to represent restricted water compartments with non‐Gaussian response functions, in an extended analysis framework called linear multi‐scale modeling (LMM). The LMM approach is designed to resolve length scale and orientation‐specific information with greater specificity to tissue microstructure in the restricted and hindered compartments, while retaining the advantages of the RSI approach in its implementation as a linear inverse problem. Using multi‐shell, multi‐diffusion time DW‐MRI data acquired with a state‐of‐the‐art 3 T MRI scanner equipped with 300 mT/m gradients, we demonstrate the ability of the LMM approach to distinguish different anatomical structures in the human brain and the potential to advance mapping of the human connectome through joint estimation of the fiber orientation distributions and compartment size characteristics.
From dark to darkness, negative phototropism influences the support-tree location of the massive woody climber Hydrangea serratifolia (Hydrangeaceae) in a Chilean temperate rainforest

ABSTRACT Climbing plants rely on suitable support to provide the light conditions they require in the canopy. Negative phototropism is a directional search behavior proposed to detect a support-tree, which indicates growth or movement away from light, based on light attenuation. In a Chilean temperate rainforest, we addressed whether the massive woody climber Hydrangea serratifolia (H. et A.) F. Phil (Hydrangeaceae) presents a support-tree location pattern influenced by light availability. We analyzed direction and light received in two groups of juvenile shoots: searching shoots (SS), with plagiotropic (creeping) growth vs. ascending shoots (AS), with orthotropic growth. We found that, in accordance with light attenuation, SS and AS used directional orientation to search and then ascend host trees. The light available to H. serratifolia searching shoots was less than that of the general forest understory; the directional orientation in both groups showed a significant deviation from a random distribution, with no circular statistical difference between them. Circular-linear regression indicated a relationship between directional orientations and light availability. Negative phototropism encodes the light environment’s heterogeneous spatial and temporal information, guiding the shoot apex to the most shaded part of the support-tree base, the climbing start point.
Challenges Facing Single Mothers in Supporting their Adolescent Children: A Case of Dodoma, Tanzania

This study investigated on challenges facing single mothers in supporting their adolescent children in Dodoma, Tanzania. The study employed the qualitative approach with the phenomenological research design. The population of the study comprised of all single mothers of three wards in Dodoma City Council and eight Social Welfare Officers from the studied wards and city council. A sample of 30 single mothers was drawn through a purposive sampling technique, and five Social Welfare Officers were selected as key informants. Semi-structured interview guides were used to gather data from respondents and key informants and the responses were tape-recorded. Data was transcribed and analysed using the thematic analysis method. The study established that single mothers experienced manifold challenges in supporting their adolescent children. The challenges ranged from economic, social, cultural, to psychological. The study recommended that support mechanisms from government and non-governmental organisations be in place to empower single mothers with prerequisite tools that will help them become economically stable. Social cultural practices that stigmatize and deprive single women’s property and consequently hinder single mothers from supporting their children adolescents should be stopped. Social welfare officers should provide training to the community on the rights of single mothers to live, to be respected, to own land and other property and to be supported.
Racial Differences in 25-Hydroxy Vitamin D and Self-Reported Pain Severity in a Sample of Individuals Living with Non-Specific Chronic Low Back Pain

Introduction Considerable evidence suggests that there are significant ethnic/racial differences in the experience of pain among individuals suffering from chronic musculoskeletal conditions. Additionally, low levels of vitamin D have been associated with pain severity. Further, vitamin D deficiency is more prevalent in Non-Hispanic Black (NHB) individuals compared to Non-Hispanic Whites (NHW). Objective The aim of this study was to investigate the associations among race, pain severity, and serum levels of vitamin D in a sample of patients with chronic low back pain (cLBP). Methods All study participants (n = 155) self-identified their race/ethnicity as either NHB or NHW. Blood samples were collected to assess circulating levels of serum 25- hydroxy vitamin D. Vitamin D levels were categorized as optimal (≥20 ng/mL), insufficient (12–19 ng/mL) or deficient (<12 ng/mL). Participants then self-reported their pain severity using the Brief Pain Inventory – Short Form. Results Results showed that a greater proportion of NHB versus NHW participants were categorized as Vitamin D deficient (χ2 (2, N = 155) = 16.79, p < 0.001). An analysis of covariance (ANCOVA) revealed that NHBs reported significantly greater pain severity relative to NHWs (F(1150) = 6.45) p = 0.012. Further, self-reported pain severity significantly differed according to Vitamin D clinical categories (F(2150) = 4.19, p = 0.013). Participants with deficient vitamin D reported significantly greater pain severity in comparison to participants with optimal vitamin D (F(1101) = 7.28, p = 0.008). Conclusion The findings suggest that Vitamin D deficiency may be linked to greater pain severity in a sample of individuals with cLBP, especially for those who identify as NHB.
Cholestasis associated to inborn errors in bile acid synthesis

Several metabolic pathways are involved in the biotransformation of C27 neutral cholesterol to C24 primary bile acids (BAs), mainly cholic acid (CA) and chenodeoxycholic acid (CDCA), which are then conjugated with glycine or taurine. This process can start with the modification of the steroid ring or the shortening of the side chain and involves enzymes present in different subcellular compartments. Inborn errors affecting the biogenesis of organelles, such as peroxisomes, or the expression or function of specific enzymes of these convergent routes result in: i) the lack of mature C24-BAs, with the subsequent impairment in digestion and absorption of dietary fat and liposoluble vitamins, such as vitamin K, which may account for a deficient hepatic synthesis of several coagulation factors; ii) the accumulation of intermediate metabolites, which may affect hepatocyte physiology, causing cholestasis as a commonly shared alteration besides other deleterious hepatic events; and iii) extrahepatic clinical manifestations due to accumulation of toxic metabolites in other territories, such as the nervous system, causing neurological disorders. In general, diseases whose primary alteration is a genetic defect in BA synthesis are diagnosed in children or young individuals with a very low incidence. The symptomatology can markedly vary among individuals, ranging from mild to severe conditions. Oral therapy, based on the enrichment of the BA pool with natural C24-BAs, such as CA, CDCA, glyco-CA, or ursodeoxycholic acid (UDCA), depending on the exact deficiency causing the disease, may be beneficial in preventing life-threatening situations. In contrast, in other cases, a liver transplant is the only option for these patients. This review describes the updated information on the genetic and molecular bases of these diseases and the current approaches to achieve a selective diagnosis and specific treatment.
Secondary neutron-production cross sections from heavy-ion interactions in composite targets

Secondary neutron-production cross-sections have beenmeasured from interactions of 230 MeV/nucleon He, 400 MeV/nucleon N, 400MeV/nucleon Kr, 400 MeV/nucleon Xe, 500 MeV/nucleon Fe, and 600MeV/nucleon Ne interacting in a variety of elemental and compositetargets. We report the double-differential production cross sections,angular distributions, energy spectra, and total cross sections from allsystems. Neutron energies were measured using the time-of-flighttechnique, and were measured at laboratory angles between 5 deg and 80deg. The spectra exhibit behavior previously reported in otherheavy-ion-induced neutron production experiments; namely, a peak atforward angles near the energy corresponding to the beam velocity, withthe remaining spectra generated by preequilibrium and equilibriumprocesses. The double-differential spectra are fitted with amoving-source parameterization. Observations on the dependence of thetotal cross sections on target and projectile mass arediscussed.
Deep Generative Modelling of Aircraft Trajectories in Terminal Maneuvering Areas

Airspace design is subject to a multitude of constraints, which are mainly driven by the concern to keep the risk of mid-air collision below a target level of safety. For that purpose, Monte Carlo simulation methods can be applied to estimate aircraft conflict probability but require the accurate generation of artificial trajectories. Generative models allow to generate an infinite number of trajectories for air traffic procedures where only few observations are available. The generated trajectories must not only resemble observed trajectories in terms of statistical distributions but they should stay flyable and consider uncertainty due to weather, air traffic control, aircraft performances, or human factors. This paper focuses on the generation problem, and its main contribution lies in the adaptation of the Variational Autoencoder structure to the problem of 4-dimensional aircraft trajectories modelling using Temporal Convolutional Networks and a prior distribution composed of a Variational Mixture of Posteriors (VampPrior). The proposed model has been trained on trajectories in the Terminal Manoeuvre Area of Zurich airport, which have a particularly high degree of variability as air traffic controllers often take actions that deviate aircraft from the nominal approach procedure. The model has demonstrated great abilities to take into account such amount of uncertainty. Regarding metrics that evaluate the estimation of the statistical distribution of the observed trajectories, and the flyability of the generated ones, the proposed method outperforms traditional statistical methods by being able to generate more complex and realistic trajectories.
Path Planning and Obstacle Avoidance Control for Autonomous Multi-Axis Distributed Vehicle Based on Dynamic Constraints

Obstacle avoidance problem for the autonomous vehicle has received more and more attention these years, especially for the autonomous heavy vehicle, which has the high gravity center, large carrying capacity and promising commercial prospect. However, the vehicle dynamic properties have been rarely considered for path planning, which is a crucial factor for driving safety. An integrated collision avoidance framework that consists of a new path planner and a tracking controller considering multiple dynamic constraints is proposed for an autonomous multi-axis distributed vehicle. In the upper level, a new optimal path generator based on the B-splines is designed for safety and stability purposes, and the collision avoidance path is optimized considering multiple dynamic constraints, including the tire nonlinear dynamic, lateral stability limits and the anti-slip constraints. Meanwhile, a safety assessment evaluator according to the time to collision calculation is designed for risk level recognition and path planning weight determination. In the lower level, a path tracking controller based on the nonlinear model predictive control (NMPC) is designed to improve the control accuracy, and a high-fidelity nonlinear dynamic predictive vehicle model with 16 degrees of freedom is established to depict the vehicle dynamic properties comprehensively. To solve the nonlinear optimization problem and get the optimal control steering angle output, an adaptive weight adjustment strategy and a varying predictive duration method are formulated. The optimization constraints related to steering actuator ability, plane stability limits, rollover prevention thresholds and tire adhesion requirements are constructed and converted as the bounds of the vehicle dynamic states. To verify the proposed framework, the simulation and HIL test platform are built and different driving scenarios are validated. The test results show the satisfactory performance of path planning and path tracking considering the dynamic constraints for safety and stability.
Comparison of Two Dental Age Estimation Methods: The London Atlas and the Schour & Massler Atlas in 3-23 Years Old Indonesian

: Age estimation is an important process in forensic identification, especially when there is insufficient antemortem information. Tooth is one of the strong variables which could be used in estimating the age of living or deceases. Non-invasive age estimation methods, including dental radiographs, have the advantage of uncomplicated application without damaging the oral and surrounding tissues. The aim of this research was to compare two radiographic dental age estimation methods, the London Atlas by Al Qahtani and the Schour & Massler Atlas in 3-23 years old Indonesian population. Two hundred and fifty-three panoramic radiographs from 156 females and 97 males with age ranged between 3-23 years old were retrospectively collected from a Dental Hospital. Age estimation was performed on the radiographs using the London Atlas and the Schour & Massler Atlas. Mann-Whitney U test was used to compare the chronological age and estimated age from two methods. There was an insignificant difference between estimated age by both Atlases (p> 0.05). Furthermore, there was also insignificant differences between estimated age of both Atlases and the chronological age (p> 0.05). The performance of London Atlas and Schour & Massler Atlas were equivalent in estimating 3-23 years old Indonesian in present study population.
Robust Estimation for Discrete Time-Varying Uncertain Systems with Observation Losses in Networked Control System

In this paper, we deal with the robust minimum variance filtering problem for discrete time-varying systems with observation losses. The system under consideration is subjected to time-varying norm-bounded parameter uncertainties in both the state and output matrices, and the observation losses are described by a Bernoulli process with a known probability. An upper bound on the variance of the state estimation error is first found under certain probability of missing observations and admissible parameter uncertainties. Then, a robust filter is derived by minimizing the prescribed upper bound in the sense of the matrix norm. It is shown that the desired filter can be obtained in terms of the solutions to two discrete Riccati difference equations.
Family Resilience: Traits, Positivity, and Close Relationship in Adolescents

: High stress can be experienced by all family members, including adolescents. This can cause the family to function less optimally and interfere with the adaptation of each family member. A family that has resilience is one solution for the family to be able to still adapt well when experiencing strong pressure. The purpose of this study is to determine the role of traits in family resilience with the mediators of close relationship and positivity. Data were collected using reliable instruments. The research participants consisted of 312 adolescents aged 15-18 years old. The data were processed by using the mediation analysis technique using Model 4 from Hayes PROCESS. The results showed that there was a significant relationship between traits and family resilience through close relationship and positivity. The role of the five traits in family resilience can occur if they are mediated by the mediator variables. From the three mediators, namely close relationship, positive emotions, and negative emotions, it was found that positive emotions had the strongest role as a mediator of the five traits in family resilience. Implications for theory and practice are discussed.
Direct-motion stereo

In this paper, we show how the translational motion of a stereo vision system relative to, and its distance from, the scene can be recovered in closed form directly from the measurements of image gradients and time derivatives. There is no need to estimate image motion or establish correspondences between features across images. The direction of translational motion is recovered using a procedure which involves minimizing the sum squared error of a linear constraint equation over the image. The solution is given in terms of the eigenvector corresponding to the smallest eigenvalue of a 3 x 3 positive semi-definite matrix. Using the average disparity, which maximizes the crosscorrelation between the left and right images, we estimate the scale-factor necessary to compute the magnitude of the translational motion, and consequently the distance to the scene.
CMOS-GAN: Semi-Supervised Generative Adversarial Model for Cross-Modality Face Image Synthesis

Cross-modality face image synthesis such as sketch-to-photo, NIR-to-RGB, and RGB-to-depth has wide applications in face recognition, face animation, and digital entertainment. Conventional cross-modality synthesis methods usually require paired training data, i.e., each subject has images of both modalities. However, paired data can be difficult to acquire, while unpaired data commonly exist. In this paper, we propose a novel semi-supervised cross-modality synthesis method (namely CMOS-GAN), which can leverage both paired and unpaired face images to learn a robust cross-modality synthesis model. Specifically, CMOS-GAN uses a generator of encoder-decoder architecture for new modality synthesis. We leverage pixel-wise loss, adversarial loss, classification loss, and face feature loss to exploit the information from both paired multi-modality face images and unpaired face images for model learning. In addition, since we expect the synthetic new modality can also be helpful for improving face recognition accuracy, we further use a modified triplet loss to retain the discriminative features of the subject in the synthetic modality. Experiments on three cross-modality face synthesis tasks (NIR-to-VIS, RGB-to-depth, and sketch-to-photo) show the effectiveness of the proposed approach compared with the state-of-the-art. In addition, we also collect a large-scale RGB-D dataset (VIPL-MumoFace-3K) for the RGB-to-depth synthesis task. We plan to open-source our code and VIPL-MumoFace-3K dataset to the community (https://github.com/skgyu/CMOS-GAN).