Miracle-dz/UniFAR-FTUs huggingface dataset:
Screening of TRPC Channel Activators Identifies Novel Neurotrophic Piperazine Compounds

Department of Synthetic Chemistry and Biological Chemistry, Graduate School of Engineering, Kyoto University, Kyoto, Japan (S.S., M.H., Y.T., H.H., M.H., R.R., S.K., M.M., Y.M.); Department of Technology and Ecology, Hall of Global Environmental Studies, Kyoto University, Kyoto, Japan (S.K., Y.M.); Sumitomo Dainippon Pharma Co., Ltd. (Y.T., K.H., T.K., J.T., H.N., R.N.); Division of Systems Medical Science, Institute for Comprehensive Medical Science, Fujita Health University, Toyoake, Japan (A.N.); Division of Cardiocirculatory Signaling, Okazaki Institute for Integrative Bioscience (National Institute for Physiological Sciences), National Institutes of Natural Sciences, Japan (M.N.); Department of Physiology, School of Medicine, Fukuoka University Fukuoka, Japan (Y.H., R.I.) MOL #102863 This article has not been copyedited and formatted. The final version may differ from this version. Molecular Pharmacology Fast Forward. Published on January 5, 2016 as DOI: 10.1124/mol.115. 102863
Alignment and bonding of silicon mirrors for high-resolution astronomical x-ray optics

Recent advances in the fabrication of silicon mirrors and their alignment and integration methods make it possible to build large-area, lightweight, high-resolution x-ray telescopes with arc-second angular resolution. Such a telescope, having simultaneously arc-second resolution and large (> 1 m2 ) collecting area, has never been built before and it will revolutionize high energy astronomy. For such optics, the challenges are twofold: fabrication of high quality mirror segments and precise integration of thousands of these mirrors to a common sharp focus. In this paper, we address the technology for the mirror integration carried out at Goddard Space Flight Center and report the recent result of making such high-resolution optics. We address the crucial technology components: positioning a mirror, measuring its focus, adjusting its mount pointsto optimize the focus, bonding the mirror, and co-alignment of mirrors. We also present the latest x-ray test results that demonstrate the efficacy of such methods and address areas for further improvement. Presently, mirrors built this way have a resolution of 2²-3² HPD (half-ower diameter).
Eigenvalue, eigenvector, eigenmode of reducible matrix and its application

There are three essential components of matrix that must be understood in the process of completing the scheduling problems using max-plus algebra. They are eigenvalue, eigenvector, and eigenmode. The result showed that the reducible matrix does not necessarily have eigenvalue. If it has eigenvalue, the eigenvalue is not necessarily unique with finite value. The eigenvector corresponding to the eigenvalue of reducible matrix is not unique that contains at least a finite element. Furthermore, the eigenmode of a regular reducible matrix is not unique with all finite elements for each component.There are three essential components of matrix that must be understood in the process of completing the scheduling problems using max-plus algebra. They are eigenvalue, eigenvector, and eigenmode. The result showed that the reducible matrix does not necessarily have eigenvalue. If it has eigenvalue, the eigenvalue is not necessarily unique with finite value. The eigenvector corresponding to the eigenvalue of reducible matrix is not unique that contains at least a finite element. Furthermore, the eigenmode of a regular reducible matrix is not unique with all finite elements for each component.
Adaptive safe control for tethered aircrafts with input and output constraints

In this article, an adaptive safe control scheme is presented for tethered aircrafts subject to unknown disturbances, input saturations, and deferred asymmetric time‐varying output constraints. By integrating a shifting function into an asymmetric barrier Lyapunov function, the deferred asymmetric time‐varying output constraints are first solved. Then, to eliminate the conflict between input saturations and output constraints, an auxiliary system is designed to enlarge output constraint boundaries when input saturation occurs and the system has no tolerance for output constraints, which ensures system safety. Furthermore, disturbance observers are employed to estimate unknown disturbances. Finally, both theoretical proof and simulation results demonstrate the validity of the proposed control scheme.
Estimation of proton-boron reaction cross-sections by neural networks

The proton-boron fusion reaction is one of the interesting reactions in nuclear energy production. The fact that neutrons and radioactive products do not come out as a result of the reaction makes these reactions special. However, the realization of this reaction is very difficult due to the low reactivity of the plasma and high radiation losses at temperatures achievable in today's fusion devices. Therefore, it is important to determine the cross-sections of these reactions. In our study, we obtained the cross-sections of proton-boron fusion reactions using the machine learning methods after performing machine learning with the limited data available in the literature.
Are Effects of Small Classes Cumulative? Evidence From a Tennessee Experiment

Abstract Some scholars argue that the effects of small classes in the early grades are not cumulative—that the benefits of small classes accrue in the 1st year of small classes. That argument suggests both policy implications and scientific questions of why additional benefits should not accrue from additional exposure to small classes. In this article, the cumulative effects of small classes on achievement were investigated with data from Project STAR, a 4-year, large-scale randomized experiment on the effects of class size. Controlling for achievement in the previous-year small classes in Grades 1, 2, and 3 yielded additional positive effects on reading and mathematics achievement. Thus, there are additional (cumulative) effects of small classes after the 1st year that may be large enough to be important for education policy.
Application of the ensemble Kalman filter FEM for estimation of flow field in shallow water regions

We present here an estimation of a shallow water flow field based on ensemble Kalman filter FEM. With this technique, the stochastic distribution of the state variables is represented by the ensemble approximation, and the special distribution of the state variables is obtained using the FEM. The shallow water equation is employed as the governing equation, and the SUPG method, a discretization method within the FEM, is applied to discretize the governing equation. The influence of sample number on estimation accuracy and the effect of the advection term in the shallow water equation are investigated in an open-channel model.
Minimum-dissipation scalar transport model for large-eddy simulation of turbulent flows

The anisotropic minimum dissipation (AMD) subfilter eddy-viscosity model for large-eddy simulations is tested, and results show good agreement with well-established empirical correlations and theoretical predictions of the resolved flow statistics. In particular, the AMD model can accurately predict the expected surface-layer similarity profiles and power spectra for both velocity and scalar concentration.
The Father’s Part: Influences of Paternal Psychopathology and Parenting Behavior on Child and Adolescent Well-Being

Family influences on child quality of life (QoL) are increasingly understood. Parenting behavior and parent individual psychopathology are among the established predictors of offspring mental health. However, literature often addresses these factors as ‘parental’, lacking further gender-specific differentiation while predominantly studying maternal aspects. Social and biological fathers are still underrepresented in family research. The aim of this study was to analyze paternal contributions to child well-being. A total of 197 father/mother-dyads gave a standardized self-report on parenting behavior and their own psychopathology at child primary school age (t1; 6–10 y). Ratings were compared mutually and associated with child self-rated QoL at t1 and adolescence (t2; 12–14 y). Fathers and mothers differed in psychopathology and most parenting behavior dimensions (positive parenting, involvement, responsible parenting, poor monitoring, and corporal punishment). Father psychopathology made a relevant predictive contribution to girls’ QoL at t2. Boys’ t1 QoL was significantly influenced by maternal parenting factors (positivity and corporal punishment). Compared to mothers, fathers are faced with different individual stressors; paternal parenting behavior is different, while fathers’ influences are significant, particularly for daughters. Father-addressed pre- and intervention programs in child psychotherapeutic treatment are of high relevance.
Goji-Berry-Mediated Green Synthesis of Gold Nanoparticles and Their Promising Effect on Reducing Oxidative Stress and Inflammation in Experimental Hyperglycemia

The present report focuses on a rapid and convenient method applicable in the green synthesis of gold nanoparticles (AuNPs) using goji berry (Lycium barbarum—LB) extracts rich in antioxidant compounds, as well as on the structural analysis and evaluation of the induced antioxidant protection and anti-inflammatory effects of the synthesized gold nanoparticles upon endothelial cells (HUVECs) exposed to hyperglycemia. The synthesized AuNPs were characterized using ultraviolet–visible (UV-Vis) spectroscopy and transmission electron microscopy (TEM), whereas the presence of bioactive compounds from the L. barbarum fruit extract on the surface of the nanoparticles was confirmed using Fourier transform infrared spectroscopy (FTIR). The antioxidant activity of the biosynthesized gold nanoparticles was evaluated on the HUVEC cell line. The results reveal that AuNPs with a predominantly spherical shape and an average size of 30 nm were obtained. The UV-Vis spectrum showed a characteristic absorption band at λmax = 536 nm of AuNPs. FTIR analysis revealed the presence of phenolic acids, flavonoids and carotenoids acting as capping and stabilizing agents of AuNPs. Both the L. barbarum extract and AuNPs were well tolerated by HUVECs, increased the antioxidant defense and decreased the production of inflammatory cytokines induced via hyperglycemia-mediated oxidative damage.
Editorial: Images from red cells, Volume II

Department of Biology and Biotechnology “L. Spallanzani”, Laboratories of Biochemistry, University of Pavia, Pavia, Italy, Hematology Unit, Physiopathology of Anemias Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore PoliclinicoMilano, Milan, Italy, Red Blood Cell Research Group, Institute of Veterinary Physiology, and Center for Clinical Studies (ZKS), Vetsuisse Faculty, University of Zurich, Zurich, Switzerland, Zurich Center for Integrative Human Physiology (ZIHP), Zurich, Switzerland, Theoretical Medicine and Biosciences, Medical Faculty, Saarland University, Homburg, Germany, Dynamics of Fluids, Experimental Physics, Saarland University, Saarbrücken, Germany
Nuclear Norms for Tensors and Their Use for Convex Multilinear Estimation

A promising convex relaxation for rank-constrained matrix problems relies on the use of the nuclear norm, namely the sum of the singular values of the optimization matrix. In this paper we introduce a proper extension of the concept of Shatten-q norms for matrices — including the nuclear norm — to higher order tensors. Successively we study a general class of nonsmooth convex optimization problems where the tensorial nuclear norm is employed as a penalty function. We further explore the consequence for the optimization of the link between multilinear ranks and the new norm. From a methodological perspective, the considered general formulation can be specialized to accomplish different (and possibly supervised) data-driven modeling tasks. Existing preliminary works on the tensor completion problem can be regarded as a specific instance of the more general class of problems considered here. From an algorithmical perspective the main algorithm that we develop, termed Convex MultiLinear Estimation (CMLE), leads to exploiting results from distributed convex optimization. Variants of this computational scheme are additionally proposed to ensure fast convergence and to deal with certain equality constrained problems.
Heuristics for the robust coloring problem

Let $G$ and $\bar{G}$ be complementary graphs. Given a penalty function defined on the edges of $G$, we will say that the rigidity of a $k$-coloring of $G$ is the sum of the penalties of the edges of G joining vertices of the same color. Based on the previous definition, the Robust Coloring Problem (RCP) is stated as the search of the minimum rigidity $k$-coloring. In this work a comparison of heuristics based on simulated annealing, GRASP and scatter search is presented. These are the best results for the RCP that have been obtained.
What did CRISPR-Cas9 accomplish in its first 10 years?

It’s been 10 years now from the debut of clustered regularly interspaced short palindromic repeats-associated protein 9 (CRISPR/Cas9) era in which gene engineering has never been so accessible, precise and efficient. This technology, like a refined surgical procedure, has offered the ability of removing different types of disease causing mutations and restoring key proteins activity with ease of outperforming the previous resembling methods: zinc finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs). Additionally, CRISPR-Cas9 systems can systematically introduce genetic sequences to the specific sites in the human genome allowing to stimulate desired functions such as anti-tumoral and anti-infectious faculties. The present brief review provides an updated resume of CRISPR-Cas9’s top achievements from its first appearance to the current date focusing on the breakthrough research including in vitro, in vivo and human studies. This enables the evaluation of the previous phase ‘the proof-of-concept phase’ and marks the beginning of the next phase which will probably bring a spate of clinical trials.
Effect of Eucalyptus globulus wood density on papermaking potential

It is well documented that the characteristics of raw materials determine the papermaking potential of the pulp. The variability of the wood used by the pulp mills is extremely wide. We report on the behavior of three Eucalyptus globulus wood chip samples with basic densities of 0.467, 0.537, and 0.600 g/cm3, in kraft cooking and papermaking. The pulp yield range of 49%–58.7% was attributed to the different wood chemical composition, in particular to the lignin content and relative proportion of cellulose and hemicelluloses. The morphological characteristics of the pulp fibers were also markedly different. The average fiber length is 0.71, 0.80, and 0.85 mm, respectively for the E. globulus of low, intermediate, and high wood basic density. The pulp fibers from the lowest density wood exhibit very high wet fiber flexibility, while those from the highest density wood exhibit rigid behavior. Using this structural property as reference, the corresponding papers are stronger, but exhibit lower light scattering coefficients than those from the lowest density wood
Application of Double/Debiased Machine Learning

Available data grows fast, for example characteristics of individuals. When estimating the average treatment effect by controlling for characteristics using Ordinary Least Squares, this method will become inconsistent. The new method Double/Debiased Machine Learning delivers unbiased estimators and is able to construct confidence intervals that is root-N consistent, the sample size is N, and approximately normally distributed. This method is applied to the data sets of the two papers “The Long-Term Effects of Africa’s Slave Trades” and “The Slave Trade and the Origins of Mistrust in Africa”. These papers have drawn conclusions about the effect of Africa’s Slave Trade using OLS and Instrumental Variables, based on a large data set. The first paper uses a specific measure for the slave trade in every table. This thesis shows that it is better to use another more important measure. Moreover, this thesis shows more reliable estimations and confidence intervals for the treatment variable. Besides applying DML, the most important results of these two papers are replicate using OLS. For almost every result the estimations are the same, however, when estimating for channels of causality, the estimations differ.
Quality of Life after Brain Injury in Children and Adolescents (QOLIBRI-KID/ADO)—The First Disease-Specific Self-Report Questionnaire after Traumatic Brain Injury

The subjective impact of the consequences of pediatric traumatic brain injury (pTBI) on different life dimensions should be assessed multidimensionally and as sensitively as possible using a disease-specific health-related quality of life (HRQoL) instrument. The development and psychometrics of the first such self-report questionnaire for children and adolescents after TBI are reported here. Focus group interviews with children, adolescents, and their parents, cognitive debriefing, item pool generation and reduction using Delphi expert panels were performed. The resulting version was psychometrically tested on 300 individuals aged 8–17 years. After item reduction based on factor analyses, differential item functioning, reliability, and validity were investigated. The final 35 items were associated with six scales (Cognition, Self, Daily Life and Autonomy, Social Relationships, Emotions, Physical Problems). Internal consistency and construct validity were satisfactory. Health-related Quality of life (HRQoL) was significantly lower in older and in female participants, as well as those with cognitive disabilities, anxiety, depression and post-concussion symptoms, than in comparative groups. The new QOLIBRI-KID/ADO is a comprehensive, multidimensional, reliable, and valid instrument, comparable in content and items to the QOLIBRI adult version. Therefore, disease-specific HRQoL can now be measured across the lifespan and may support the amelioration of treatment, care, rehabilitation, and daily life of children and adolescents after TBI.
Iodine Biofortification of Dandelion Plants (Taraxacum officinale F.H. Wiggers Coll.) with the Use of Inorganic and Organic Iodine Compounds

Iodine is a crucial microelement necessary for the proper functioning of human and animal organisms. Plant biofortification has been proposed as a method of improving the iodine status of the population. Recent studies in that field have revealed that iodine may also act as a beneficial element for higher plants. The aim of the work was to evaluate the efficiency of the uptake and accumulation of iodine in the plants of dandelion grown in a pot experiment. During cultivation, iodine was applied through fertigation in inorganic (KI, KIO3) and organic forms (5-iodosalicylic acid, 5-ISA; 3,5-diiodosalicylic acid, 3,5-diISA) at two concentrations (10 and 50 µM). The contents of total iodine and iodosalicylic acids, as well the plant biomass and antioxidant capacity of dandelion leaves and roots, were analyzed. The uptake of inorganic and organic forms by dandelion plants was confirmed with no negative effect on plant growth. The highest efficiency of improving iodine content in dandelion leaves and roots was noted for 50 µM KI. The applicability of iodosalicylates, especially 5-ISA, for plant biofortification purposes was confirmed, particularly as the increase in the iodine content after the application of 5-ISA was higher as compared to that with commonly used KIO3. The chemical analyses have revealed that iodosalicylates are endogenous compounds of dandelion plants.
Predicting vacancy-mediated diffusion of interstitial solutes in α -Fe

Based on a systematic first-principles study, the lowest-energy migration mechanisms and barriers for small vacancy-solute clusters (VnXm) are determined in α-Fe for carbon, nitrogen, and oxygen, which are the most frequent interstitial solutes in several transition metals. We show that the dominant clusters present at thermal equilibrium (VX and VX2) have very reduced mobility compared to isolated solutes, while clusters composed of a solute bound to a small vacancy cluster may be significantly more mobile. In particular, V3X is found to be the fastest cluster for all three solutes. This result relies on the large diffusivity of the most compact trivacancy in a bcc lattice. Therefore, it may also be expected for interstitial solutes in other bcc metals. In the case of iron, we find that V3X may be as fast as or even more mobile than an interstitial solute. At variance with common assumptions, the trapping of interstitial solutes by vacancies does not necessarily decrease the mobility of the solute. Additionally, cluster dynamics simulations are performed considering a simple iron system with supersaturation of vacancies, in order to investigate the impacts of small mobile vacancy-solute clusters on properties such as the transport of solute and the cluster size distributions.
Experimental Characterization and Electro-Thermal Modeling of Double Side Cooled SiC MOSFETs for Accurate and Rapid Power Converter Simulations

The paper presents a precise and efficient model of Double-Side Cooled (DSC) SiC MOSFET, which incorporates the dynamics of both electrical and thermal variables. It offers a suitable computational complexity for simulating transients in complex power converters. The objective is to define a model that enables multi-scale time simulations and facilitates rapid power converter design in system-level tools such as Simulink. Additionally, the model aims to achieve simulation accuracy comparable to device-level models for the next generation of SiC MOSFETs. The paper demonstrates the complete test bench measurement procedure for the device. This procedure is essential for experimentally extrapolating the intrinsic characteristics and developing a model-reduction approach based on electro-thermal modeling. The approach strikes a balance between computational complexity and level of detail. The proposed model has been seamlessly integrated into Simulink to simulate a 3-phase inverter for several grid cycles at the grid frequency. To evaluate the model’s validity, the predicted inverter performance is compared with experimental measurements. These simulations require significantly less time compared to those based on LTspice models.
YOLOv7‐EAS: A Small Target Detection of Camera Module Surface Based on Improved YOLOv7

The camera module surface may introduce defects in the focusing process, and manual detection of these defects is inefficient and costly. To address this problem, a method to automatically expand the dataset for deep learning models with fewer original images is developed. A defect detection method is also presented, YOLOv7‐EAS, that enhances YOLOv7 for camera module images with complex backgrounds and small target defects. This method introduces NewEIOU Loss, a bounding box regression loss function that extends EIOU Loss with a nonlinear compensation term. This function improves the model's convergence rate to quadratic order. Moreover, the detection head based on ASFF is redesigned to adapt the layer features and spatially filter out irrelevant information to improve the detection rate of small targets. Finally, a 3D attention mechanism is applied to increase the model's ability to extract fine‐grained features without increasing the network parameters. Experimental results show that the improved YOLOv7 algorithm achieves 90.5% mAP for the camera module image dataset, which is 10.7% higher than the original algorithm, at 136 FPS. This method can perform the camera module surface defect detection task more accurately and meet the real‐time requirements of the production line.