Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation and characterization of acid‐treated multiwalled carbon nanotubes interlinked nickel vanadate microcomposites for lithium‐ion batteries

Vanadium‐based hybrid metal oxides have a crystalline layer structure and excellent kinetics for high‐power‐density lithium (Li)‐ion batteries. Different oxidation levels and harmonizing chemistry of vanadium need a cost‐effective and robust integration approach for the proportion of their form and surface benefits. One of the most attractive methodologies for obtaining pure phase and unique development over varying temperature and pressure conditions is to use hydrothermal technique. Herein, a simple one‐pot hydrothermal procedure is used to make the acid‐treated multiwalled carbon nanotubes (AMWCNTs) decorated on Ni3V2O8 (NVO) microspheres (MSs). The synthesized AMWCNTs interlinked NVO (NVO@AMWCNTs) MS composite electrode delievers significantly improved Li‐ion storage capacities when employed as a negative electrode. At 100 mA g−1, the NVO@AMWCNTs MS composite electrode exhibits a specific capacity of 609.6 mA h g−1 as well as excellent cycling stability of 306.6 mA h g−1 at 1000 mA g−1. The improved electrochemical properties are mainly owing to the large surface area (78.72 m2 g−1), high porosity of connected MSs, and outstanding cooperative chemistry between the NVO and AMWCNTs. The porous structure and high surface area of NVO@AMWCNTs MS composite material allow more voids to adjust the massive amount of Li+ ions in the charge‐discharge process. This beneficial composition enhances Li+ ion diffusivity and electrical conductivity by increasing the interface area between the electrolyte and electrode, the specific surface area of the electrodes, and the electrolyte absorption.
Three-Dimensional Modeling and Kinematic Analysis of Human Elbow Joint Axis Based on Anatomy and Screw Theory

Ensuring the motion consistency of human and exoskeletons is the key to the research of wearable exoskeleton robots. However, as the complexity of the coupling of sliding and rolling motion in human joint tissue, it is hard to depict the dynamic states of the joint axis. Exploring the changed human joint axis can be significant in the process of studying the bionic joint of the exoskeleton robots. We proposed a method to build the biological joint model based on anatomy and used screw theory to explore the human biological joint axis on it. The humerus and ulna models were only reconstructed by scanning CT images of the elbow joint in any single position. According to anatomy, humerus trochlear and trochlear notch of models were tangent to build a movable elbow joint model. The screw theory was used to study the elbow joint axis based on the kinematic data of samples in the motion simulation of joint model. Comparing the motion between model and human experiment, the ${\boldsymbol{R}^{\boldsymbol{2}}}$ of the Euler angles were above 0.97, and $\boldsymbol{RMSE}$ were below 2.85, which showed the model following anatomical principles can reflect the human joints well. And the pattern that depicted joint axis travelled is similar to the shape of the Mobius Strip. This work provides a new method to study human joint axis, and the axis results provide references to the design of exoskeleton joints and bionic robots.
Drug Discovery Strategies for Inherited Retinal Degenerations

Simple Summary Inherited retinal degeneration is a group of heterogeneous genetic disorders impairing vision. In these diseases, photoreceptor or retinal ganglion cells become dysfunctional and degenerate. Currently, no cures exist for these devastating blinding conditions. In this review, we will discuss targets and drug discovery strategies for inherited retinal degeneration using animal models, stem cells, and small molecule screening with updates on preclinical developments. Abstract Inherited retinal degeneration is a group of blinding disorders afflicting more than 1 in 4000 worldwide. These disorders frequently cause the death of photoreceptor cells or retinal ganglion cells. In a subset of these disorders, photoreceptor cell death is a secondary consequence of retinal pigment epithelial cell dysfunction or degeneration. This manuscript reviews current efforts in identifying targets and developing small molecule-based therapies for these devastating neuronal degenerations, for which no cures exist. Photoreceptors and retinal ganglion cells are metabolically demanding owing to their unique structures and functional properties. Modulations of metabolic pathways, which are disrupted in most inherited retinal degenerations, serve as promising therapeutic strategies. In monogenic disorders, great insights were previously obtained regarding targets associated with the defective pathways, including phototransduction, visual cycle, and mitophagy. In addition to these target-based drug discoveries, we will discuss how phenotypic screening can be harnessed to discover beneficial molecules without prior knowledge of their mechanisms of action. Because of major anatomical and biological differences, it has frequently been challenging to model human inherited retinal degeneration conditions using small animals such as rodents. Recent advances in stem cell-based techniques are opening new avenues to obtain pure populations of human retinal ganglion cells and retinal organoids with photoreceptor cells. We will discuss concurrent ideas of utilizing stem-cell-based disease models for drug discovery and preclinical development.
A Refined Supervision Model of Rice Supply Chain Based on Multi-Blockchain

With the development of Agriculture 4.0, the requirements for sustainable agriculture and precision agriculture continue to grow. As one of the three major staple foods globally, the quality and safety of rice affect human health as well as social development. To ensure the quality and safety of rice and reduce the flow of problematic rice, a multi-layer blockchain-based rice supply chain refinement supervision model MBRRSM (Multi-blockchain Rice Refined Supervision Model) is proposed from the information level. First, the characteristics of information flow in the rice supply chain are analyzed, and a classification table of key information is constructed. Second, the MBRRSM framework is designed. Based on a multi-party hybrid encryption algorithm, secure multi-party computing algorithm, multi-mode storage mechanism, and SPOP (Supervision Proof of Peers) consensus algorithm, a set of mechanisms is designed for the transmission, use, storage, and consensus of rice data in MBRRSM. Subsequently, the security and performance capabilities of MBRRSM are analyzed. Meanwhile, the SPOP consensus algorithm is analyzed. Finally, a prototype system is built based on MBRRSM and verified through exemplary scenarios in different usage situations. The results show that research on the refined supervision of the rice supply chain based on multi-blockchain can finely supervise all types of data in the rice supply chain, and provide a guarantee for enterprise users to safely transmit and use data with different privacy levels. This study presents a unique research paradigm that introduces the theories and methods of the new information field generation into the field of agricultural research, and thus assists in the strategy implementation of “holding grain in the land and storing grain in technology”.
Variable selection when confronted with missing data

Variable selection is a common problem in linear regression. Stepwise methods, such as forward selection, are popular and are easily available in most statistical packages. The models selected by these methods have a number of drawbacks: they are often unstable, with changes in the set of variable selected due to small changes in the data, and they provide upwardly biased regression coefficient estimates. Recently proposed methods, such as the lasso, provide accurate predictions via a parsimonious, interpretable model. Missing data values are also a common problem, especially in longitudinal studies. One approach to account for missing data is multiple imputation. The simulation studies were conducted comparing the lasso to standard variable selection methods under different missing data conditions, including the percentage of missing values and the missing data mechanism. Under missing at random mechanisms, missing data were created at the 25 and 50 percent levels with two types of regression parameters, one containing large effects and one containing several small, but nonzero, effects. Five correlation structures were used in generating the data: independent, autoregressive with correlation 0.25 and 0.50, and equicorrelated again with correlation 0.25 and 0.50. Three different missing data mechanisms were used to create the missing data: linear, convex and sinister. Least angle regression performed well under all conditions when the true regression parameter vector contained large effects, with its dominance increasing as the correlation between the predictor variables increased. This is consistent with complete data simulations studies suggesting the lasso performed poorly in situations where the true beta vector contained small, nonzero effects. When the true beta vector contained small, nonzero effects, the performance of the variable selection methods considered was situation dependent. Ordinary least squares had superior performance in terms confidence interval coverage under the independent correlation structure and with correlated data when the true regression parameter vector consists of small, nonzero effects. A variety of methods performed well when the regression parameter vector consisted of large effects and the predictor variables were correlated depending on the missing data situation.
Quantum State Reconstruction From Incomplete Data

Knowing and guessing, these are two essential epistemological pillars in the theory of quantum-mechanical measurement. As formulated quantum mechanics is a statistical theory. In general, a priori unknown states can be completely determined only when measurements on infinite ensembles of identically prepared quantum systems are performed. But how one can estimate (guess) quantum state when just incomplete data are available (known)? What is the most reliable estimation based on a given measured data? What is the optimal measurement providing only a finite number of identically prepared quantum objects are available? These are some of the questions we address. We present several schemes for a reconstruction of states of quantum systems from measured data: (1) We show how the maximum entropy (MaxEnt) principle can be efficiently used for an estimation of quantum states on incomplete observation levels. (2) We show how Bayesian inference can be used for reconstruction of quantum states when only a finite number of identically prepared systems are measured. (3) We describe the optimal generalized measurement of a finite number of identically prepared quantum systems which results in the estimation of a quantum state with the highest fidelity.
A Novel Damping Control of Grid-Connected Converter Based on Optimal Split-Inductor Concept

In this paper, a grid-connected converter is investigated. Since the AC side of the grid-connected converter is the LC filter, there is a second-order system resonance problem, and the conventional passive damping control has an inherent limitation of excessive power loss. Based on the mathematical model, a new damping control method is proposed in this paper. It is compared with the traditional solution in terms of damping effect, power loss and system stability. The optimal inductor split ratio is also discussed. The theoretical analysis demonstrates that the proposed method can not only achieve almost the same damping effect as the conventional solution, but also reduce the power loss of the damping resistor. The experimental tests are carried out and the experimental results verify the effectiveness of the proposed method.
The largest X-ray-selected sample of $\boldsymbol {z>3}$ AGNs: C-COSMOS and ChaMP

We present results from an analysis of the largest high-redshift (z > 3) X-ray-selected active galactic nucleus (AGN) sample to date, combining the Chandra C-COSMOS and ChaMP surveys and doubling the previous samples. The sample comprises 209 X-ray-detected AGN, over a wide range of rest frame 2-10 keV luminosities logL_{X}=43.3 - 46.0 erg s^{-1}. X-ray hardness rates show that ~39% of the sources are highly obscured, N_{H}>10^{22} cm^{-2}, in agreement with the ~37% of type-2 AGN found in our sample based on their optical classification. For ~26% of objects have mismatched optical and X-ray classifications. Using the 1/V_{max} method, we confirm that the comoving space density of all luminosity ranges of AGNs decreases with redshift above z > 3 and up to z ~ 7. With a significant sample of AGN (N=27) at z > 4, it is found that both source number counts in the 0.5 -2 keV band and comoving space density are consistent with the expectation of a luminosity dependent density evolution (LDDE) model at all redshifts, while they exclude the luminosity and density evolution (LADE) model. The measured comoving space density of type-1 and type-2 AGN shows a constant ratio between the two types at z > 3. Our results for both AGN types at these redshifts are consistent with the expectations of LDDE model.
Dielectric and magnetic enhancements in BiFeO3–PbTiO3 solid solutions with La doping

Solid solutions of 0.45(Bi1−xLax)FeO3–0.55PbTiO3 (BLFPTx) for x=0.1, 0.2, and 0.3 were prepared by the mixed oxide method. BLFPTx showed the tetragonal perovskite structure of which the c∕a ratio and Curie temperature decreased with the increase of La content. Significant dielectric and magnetic enhancements were observed for BLFPTx with La doping. The ferroelectric and ferromagnetic hysteresis loops revealed the maximum remanent polarization and magnetization of 28μC∕cm2 and 0.14emu∕g, respectively, for BLFPTx of x=0.3. Results indicated that BLFPTx was of the insulating and switchable multiferroics with both ferroelectric and ferromagnetic properties.Solid solutions of 0.45(Bi1−xLax)FeO3–0.55PbTiO3 (BLFPTx) for x=0.1, 0.2, and 0.3 were prepared by the mixed oxide method. BLFPTx showed the tetragonal perovskite structure of which the c∕a ratio and Curie temperature decreased with the increase of La content. Significant dielectric and magnetic enhancements were observed for BLFPTx with La doping. The ferroelectric and ferromagnetic hysteresis loops revealed the maximum remanent polarization and magnetization of 28μC∕cm2 and 0.14emu∕g, respectively, for BLFPTx of x=0.3. Results indicated that BLFPTx was of the insulating and switchable multiferroics with both ferroelectric and ferromagnetic properties.
Assessment of high‐pressure hydrogen storage performance of Basolite metal‐organic frameworks

The hydrogen storage performance of a series of Basolite metal‐organic frameworks (MOFs) has been estimated within a pressure range up to 700 bar at temperatures from 77 to 293 K. Crystal structure and texture properties of the MOFs were determined using X‐ray diffraction and nitrogen cryoadsorption, respectively. Hydrogen excess adsorption isotherms were measured and then converted to gravimetric and volumetric total adsorption. To calculate the total volumetric capacity, the crystallographic density of materials for the theoretically maximum capacity was used. At 700 bar, the highest volumetric total adsorption was about 65 mg/cm3 shown by Z1200 and Z377. The heat of adsorption at 298 K vs pressure was evaluated by the Clausius‐Clapeyron equation. Peculiar adsorption behavior of C300 in the high‐pressure region manifested in specific forms of isotherms and baric dependence of the heat of adsorption has been revealed. The relation of this phenomenon with a possible transition from Cu2+ to Cu+ in the C300 framework under the reducing effect of hydrogen has been discussed. The upper‐pressure limit of the MOFs' effectiveness in hydrogen storage systems compared to adsorbent‐free compressed gas has been estimated and did not exceed 127 bar at 298 K and 82 bar at 77 K due to the large amount of hydrogen that remains adsorbed at release pressure 5 bar. It has been concluded that conventional testing methods based only on excess adsorption isotherm measurements give initial data on the surface interaction and do not reflect the actual amount of stored and deliverable hydrogen. Besides the excess adsorption, the density of the adsorbent and the low‐pressure capacity are the key factors defining the applicability of materials in high‐pressure storage systems.
Secure software development: industrial practice - a review

The current state of application assets with respect to their development, functionality, scalability, user friendliness, and compatibility with legacy systems has witnessed an unprecedented degree of positive improvements. This induced increase in productivity and value has been a product of the technological innovations within and around the software development landscape. Owing to specific software development practices including software reusability, Object Oriented Programming (OOP), encapsulation, and portability, all sectors of the economy have come to embrace software products that have helped to drive business transactions. Nonetheless, the proliferation of software which has driven up the velocity, veracity and volume of data associated with transactions has become a goldmine for grabs. Hackers and adversaries alike have thus capitalized on this development to exploit the potential threats and vulnerabilities associated with software products. Insecure software is global issue, and one that impacts individuals, organizations and governments. Data loss is both a security and privacy issue, with compliance, regulatory and legal concerns, and bad actors are relentless in their efforts to steal, deface, alter/manipulate, destroy, and compromise software systems. Organizations should therefore embrace secure code principles, threat modeling, and institute a Secure Software Development Lifecycle (SSDLC) practice that will aid the embedment of security into the development phase, to contain the risks, threats, and vulnerabilities that are inherent in software development. This paper demonstrates an effort to provide and arm organizations with the necessary tools, processes, and mechanisms that can be leveraged to combat cyber-threats and enforce Information Assurance (IA) within and around enterprise application assets. Beginning with an overview of the contemporary software development practices witnessed in diverse organizations, including financial, energy, aviation, commerce, nuclear, defense, and several other Critical Infrastructure (CI) organizations, the tenets of a composite, structured and robust. SSDLC has been presented to promote a defense-in-depth security for enterprise organizations.
Híbrido 180º de banda ancha en tecnología Microstrip a 41 GHz

A broadband modified rat-race hybrid with around 30% bandwidth is presented in this paper. The hybrid was developed from 35 to 47 GHz bandwidth (centre frequency 41 GHz) using microstrip technology on Alumina substrate. The design uses CPWG-Microstrip transitions to measure the response of the circuit in a coplanar probes station. The measurements over the frequency bandwidth show a maximum amplitude imbalance of 0.5 dB, the phase variation is ± 5o, the isolation is better than 20 dB and the return loss is greater than 10 dB. Moreover, the circuit is planar and consists of a single layer, without requirements of metallic holes and bonding wires, so it is also a low-cost circuit. I. INTRODUCCION Los hibridos 180o se emplean en diversas aplicaciones en circuitos integrados de microondas, por ejemplo en circuitos donde resulta imprescindible dividir la potencia de entrada entre varias ramas, o bien combinar potencias procedentes de distintos origenes, ya sea en fase o contra fase de forma equilibrada entre sus ramas, es decir para sumar y restar senales. El acoplador hibrido 3 dB 180o en su configuracion mas tipica se muestra en la Fig. 1, la cual consiste en una red de cuatro accesos compuesta por tres lineas de longitud λ/4, y una de longitud 3λ/4, todas ellas de impedancia Z0·√2. Este hibrido es muy conocido y su estudio teorico puede encontrarse en [1]. A modo de resumen, en la ecuacion (1) se muestra la matriz de parametros S de dicho hibrido.
Relationship between Moderate-to-Vigorous Physical Activity with Health-Related Physical Fitness Indicators among Pakistani School Adolescents: Yaali-Pak Study

Background The current study is the foremost study exploring the relationships between moderate-to-vigorous physical activity and health-related physical fitness indicators among 12–16-year-old adolescents of the South Punjab region of Pakistan. Methods The researcher adopted the cross-sectional research design for the study. A total of 2970 participants (1477 boys and 1493 girls) aged adolescents from South Punjab, Pakistan, completed health-related physical fitness indicators measuring strength, endurance, and aerobic capacity through a hand-grip strength test, modified pull-up test, plank test, and 20-m shuttle run test, and physical activity were subjectively assessed by International Physical Activity Questionnaire Short Form (IPAQ-SF). Linear regression models were used to explore the between moderate-to-vigorous physical activity (MVPA) with health-related physical fitness indicators. Results Positive associations were observed between hand-grip strength (p < 0.001), modified pull-up (p < 0.001), plank exercise (p < 0.001), and 20-m shuttle run test (p < 0.001), with MVPA. The gender-specific comparison also indicated a significant (p < 0.001) and positive relationship. The results revealed that as MVPA increases, body composition, muscular strength, core muscular endurance, and aerobic capacity could improve in both genders. Conclusions MVPA appears to be an effective and reliable predictor of health-related physical fitness among school adolescents.
The number statistics and optimal history of non-equilibrium steady states of mortal diffusing particles

Suppose that a point-like steady source at x = 0 injects particles into a half-infinite line. The particles diffuse and die. At long times a non-equilibrium steady state sets in, and we assume that it involves many particles. If the particles are non-interacting, their total number N in the steady state is Poisson-distributed with mean predicted from a deterministic reaction-diffusion equation. Here we determine the most likely density history of this driven system conditional on observing a given N. We also consider two prototypical examples of interacting diffusing particles: (i) a family of mortal diffusive lattice gases with constant diffusivity (as illustrated by the simple symmetric exclusion process with mortal particles), and (ii) random walkers that can annihilate in pairs. In both examples we calculate the variances of the (non-Poissonian) stationary distributions of N.