Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive neural optimal control via command filter for nonlinear multi‐agent systems including time‐varying output constraints

In this article, an optimal command‐filtered backstepping control approach is proposed for uncertain strict‐feedback nonlinear multi‐agent systems (MASs) including output constraints and unmodeled dynamics. One‐to‐one nonlinear mapping (NM) is utilized to recast constrained systems as corresponding unrestricted systems. A dynamical signal is applied to cope with unmodeled dynamics. Based on dynamic surface control (DSC), the feedforward controller is designed by introducing error compensating signals. The optimal feedback controller is produced applying adaptive dynamic programming (ADP) and integral reinforcement learning (IRL) techniques in which neural networks are utilized to approximate the relevant cost functions online with established weight updating laws. Therefore, the entire controller, including feedforward and feedback controllers, not only ensures that all signals in the closed‐loop systems are cooperative semi‐globally uniformly ultimately bounded (SGUUB) and the outputs maintain in the provided time‐varying constraints, but also makes sure that the cost functions achieve minimization. A simulation example is presented to illustrate the feasibility of the proposed control algorithm.
MoS2/TiO2 van der Waals heterostructures for promising photocatalytic performance: a first-principles study

Heterostructures have attracted extensive attention due to their van der Waals interactions between layers. The photocatalysts of Two-dimensional (2D) heterostructure based on MoS2 have tempted more and more attention because of their eminent photocatalytic performance, but they are still limited by the weak absorption of visible light and lesser conversion efficiency of solar-to-hydrogen. In this work, we exhaustively investigate the electronic, optical and the structural properties of 2D MoS2/TiO2 heterostructures by using first-principles calculations. The result shows that both MoS2/TiO2(100) and MoS2/TiO2(001) heterostructures are stable interfaces and direct Z-scheme photocatalysts, which is favourable for the separation and migration of electron and hole pairs under the excitation of light. And what’s more, both the MoS2/TiO2(100) and MoS2/TiO2(001) heterostructures exhibit direct band gap at the Γ point, this is conductive to better electronic transition and absorption of light because of lower energy depletion than indirect band gap semiconductors. The relatively small band gap (1.08 eV of MoS2/TiO2(001) and 0.52 eV of MoS2/TiO2(100)) cause the entire visible light region can be covered by the light absorption spectrum. The result is that building heterostructures of TiO2 with MoS2 advances the absorption of light and hastens the separation and migration of electron and hole pairs, the activity of photocatalysis could be advanced by all of these. The results provide a basis of heterostructure photocatalysts based on monolayer MoS2 and deep comprehension of their physical mechanism.
Recent development and challenges in fuel cells and water electrolyzer reactions: an overview

Water electrolysis is the most promising method for the production of large scalable hydrogen (H2), which can fulfill the global energy demand of modern society. H2-based fuel cell transportation has been operating with zero greenhouse emission to improve both indoor and outdoor air quality, in addition to the development of economically viable sustainable green energy for widespread electrochemical applications. Many countries have been eagerly focusing on the development of renewable as well as H2-based energy storage infrastructure to fulfill their growing energy demands and sustainable goals. This review article mainly discusses the development of different kinds of fuel cell electrocatalysts, and their application in H2 production through various processes (chemical, refining, and electrochemical). The fuel cell parameters such as redox properties, cost-effectiveness, ecofriendlyness, conductivity, and better electrode stability have also been highlighted. In particular, a detailed discussion has been carried out with sufficient insights into the sustainable development of future green energy economy.
Spin Susceptibility, Phase Diagram, and Quantum Criticality in the Eelctron-Doped High Tc Superconductor Ba(Fe1-xCox)2As2

We report a systematic investigation of Ba(Fe 1- x Co x ) 2 As 2 based on transport and 75 As NMR measurements, and establish the electronic phase diagram. We demonstrate that doping progressively suppresses the uniform spin susceptibility and low frequency spin fluctuations. The optimum superconducting phase emerges at x c ≃0.08 when the tendency toward spin ordering completely diminishes. Our findings point toward the presence of a quantum critical point near x c between the SDW (spin density wave) and superconducting phases.
Theory of optical spin orientation in silicon

We theoretically investigate the indirect optical injection of carriers and spins in bulk silicon, using an empirical pseudopotential description of electron states and an adiabatic bond charge model for phonon states. We identify the selection rules, the contribution to the carrier and spin injection in each conduction band valley from each phonon branch and each valence band, and the temperature dependence of these processes. The transition from the heavy hole band to the lowest conduction band dominates the injection due to the large joint density of states. For incident light propagating along the $[00\bar{1}]$ direction, the injection rates and the degree of spin polarization of injected electrons show strong valley anisotropy. The maximum degree of spin polarization is at the injection edge with values 25% at low temperature and 15% at high temperature.
Interatomic potentials for the vibrational properties of III-V semiconductor nanostructures

We derive interatomic potentials for zinc blende InAs, InP, GaAs and GaP semiconductors with possible applications in the realm of nanostructures. The potentials include bond stretching interaction between the nearest and next-nearest neighbors, a three body term and a long-range Coulomb interaction. The optimized potential parameters are obtained by (i) fitting to bulk phonon dispersions and elastic properties and (ii) constraining the parameter space to deliver well behaved potentials for the structural relaxation and vibrational properties of nanostructure clusters. The targets are thereby calculated by density functional theory for clusters of up to 633 atoms. We illustrate the new capability by the calculation Kleinman and Gr\"uneisen parameters and of the vibrational properties of nanostructures with 3 to 5.5 nm diameter.
Student Concerns and Perceived Challenges in Introductory Statistics, How the Frequency Shifted during COVID-19, and How They Differ by Subgroups of Students

ABSTRACT The COVID-19 pandemic and shift to remote instruction disrupted students’ learning and well-being. This study explored undergraduates’ incoming course concerns and later perceived challenges in an introductory statistics course. We explored how the frequency of concerns changed with the onset of COVID-19 ( 1417) and, during COVID-19, how incoming concerns compared to later perceived challenges ( 524). Students were most concerned about R coding, understanding concepts, workload, prior knowledge, time management, and performance, with each of these concerns mentioned less frequently during than before COVID-19. Concerns most directly related to the pandemic—virtual learning and inaccessibility of resources—showed an increase in frequency. The frequency of concerns differed by gender and URM status. The most frequently mentioned challenges were course workload, virtual learning, R coding, and understanding concepts, with significant differences by URM status. Concerns about understanding concepts, lack of prior knowledge, performance, and time management declined from the beginning to the end of the term. Workload had the highest rate of both consistency and emergence across the term. Because students’ perceptions have an impact on their experiences and expectations, understanding and addressing concerns and challenges could help guide instructional designers and policymakers as they develop interventions.
Factors Influencing Purchase Decision of Agriculture Products: A Case Study in Selangor

This research was conducted to understand the factors that influence the purchase decision of fruits and vegetables among consumers in Selangor. Understanding consumer behavior is key in increasing the consumption of agricultural produces. Consumer knowledge, satisfaction, and experience are studied to understand the effects of these variables on attitude. Attitude is known as one of the predictors in influencing the purchase decision, thus the relationship between these variables was also studied in this research. The study was conducted in Teluk Panglima Garang with 203 respondents who took part in the survey. Descriptive analysis was performed to understand the demographic background of the respondents and their consumption patterns. Correlation analysis was conducted to identify the relationship between consumer knowledge, consumer satisfaction, and consumer experience with attitude. The result shows that all independent variables are found to be significant with consumer experience being the most influential factor among the three. The relationship between attitude and purchase decision was analyzed using multiple regression analysis. Attitude shows a significant relationship with the purchase decision. The results found in this study can be used by farmers and marketers to increase the purchase pattern of agricultural products among consumers. new
Extended dynamic Mott transition in the two-band Hubbard model out of equilibrium

We reformulate the time-dependent Gutzwiller approximation by M. Schir\'o and M. Fabrizio, [Phys. Rev. Lett. 105, 076401 (2010)] in the framework of slave-boson mean-field theory, which is used to investigate the dynamical Mott transition of the generic two-band Hubbard model at half filling upon an interaction quench. Interorbital fluctuations lead to notable changes with respect to the single-band case. The singular dynamical transition is replaced by a broad regime of long-lived fluctuations between metallic and insulating states, accompanied by intriguing precursor behavior. A mapping to a spin model proves helpful to analyze the different regions in terms of the evolution of an Ising-like order parameter. Contrary to the static case, singlet occupations remain vital in the Mott-insulating regime with finite Hund's exchange.
LHC signatures of vector-like quarks

This work provides an overview on the current status of phenomenology and searches for heavy vector-like quarks, which are predicted in many models of new physics beyond the Standard Model. Searches at Tevatron and at the LHC, here listed and shortly described, have not found any evidence for new heavy fermionic states (either chiral or vector-like) and have therefore posed strong bounds on their masses: depending on specific assumptions on the interactions and on the observed final state, vector-like quarks with masses up to roughly 400–600 GeV have been excluded by all experiments. In order to be as simple and model independent as possible, the chosen framework for the phenomenological analysis is an effective model with the addition of a vector-like quark representation (singlet, doublet, or triplet under ) which couples through Yukawa interactions with all SM families. The relevance of different observables for the determination of bounds on mixing parameters is then discussed and a complete overview of possible two body final states for every vector-like quark is provided, including their subsequent decay into SM particles. A list and short description of phenomenological analyses present in the literature are also provided for reference purposes.
Can We Understand an Auxetic Pion-Photon Transition Form Factor within QCD?

A. V. P. is thankful to Professor Vicente Vento and Professor Pedro Gonzalez for the warm hospitality at the University of Valencia, where part of this investigation was carried out. The work of A. V. P. was supported in part by the Ministry of Education and Science of the Russian Federation, project 14.B37. 21.0910, and by HadronPhysics2, Spanish Ministerio de Economia y Competitividad and EU FEDER under Contracts No. FPA2010-21750-C02-01, No. AIC10-D-000598, and No. GVPrometeo2009/129. We acknowledge support from the Heisenberg-Landau Program under Grants 2012 and 2013, and the Russian Foundation for Fundamental Research (Grants No. 12-02-00613a, No. 11-01-00182a).
Violation of detailed balance for charge‐transfer statistics in Coulomb‐blockade systems

We discuss the possibility to generate in Coulomb‐blockade systems steady states that violate detailed balance. This includes both voltage biased and non‐biased scenarios. The violation of detailed balance yields that the charge‐transfer statistics for electrons tunneling into an island experiencing strong Coulomb interaction is different from the statistics for tunneling out. This can be experimentally tested by time‐resolved measurement of the island's charge state. We demonstrate this claim for two model systems.
EUI Working Papers

Econometric modeling based on the Student's t distribution introduces an additional parameter -the degree of freedom. In this paper we use a simulation study to investigate the ability of (i) the GARCH-t model (Bollerslev, 1987) to estimate the true degree of freedom parameter and (ii) the sample kurtosis coefficient to accurately determine the implied degrees of freedom. Simulation results reveal that the GARCH-t model and the sample kurtosis coefficient provide biased and inconsistent estimates of the degree of freedom parameter. Moreover, by varying σ2, we find that only the constant term in the conditional variance equation is affected, while the other parameters remain unaffected.
Regulatory mechanisms of fatty acids biosynthesis in Armeniaca sibirica seed kernel oil at different developmental stages

Background Armeniaca sibirica seed kernel oil is rich in oleic acid and linoleic acid, thus holding potential value as a source of high-quality edible oils. However, some regulatory factors involved in fatty acids accumulation in A. sibirica seed kernels remain largely elusive. Thus, the aim of this study was to elucidate the regulatory mechanisms underlying fatty acids biosynthesis in A. sibirica developing seed kernels. Methods Seed kernels from six plants from a single A. sibirica clone were taken at five different developmental stages (days 30, 41, 52, 63, and 73 after anthesis). Fatty acid composition in seed kernel oil was determined by gas chromatography-mass spectrometry (GC-MS). In addition, transcriptome analysis was conducted using second-generation sequencing (SGS) and single-molecule real-time sequencing (SMRT). Results Rapid accumulation of fatty acids occurred throughout the different stages of seed kernels development, with oleic acid and linoleic acid as the main fatty acids. A total of 10,024, 9,803, 6,004, 6,719 and 9,688 unigenes were matched in the Nt, Nr, KOG, GO and KEGG databases, respectively. In the category lipid metabolism, 228 differentially expressed genes (DEGs) were annotated into 13 KEGG pathways. Specific unigenes encoding 12 key enzymes related to fatty acids biosynthesis were determined. Co-expression network analysis identified 11 transcription factors (TFs) and 13 long non-coding RNAs (lncRNAs) which putatively participate in the regulation of fatty acid biosynthesis. This study provides insights into the molecular regulatory mechanisms of fatty acids biosynthesis in A. sibirica developing seed kernels, and enabled the identification of novel candidate factors for future improvement of the production and quality of seed kernel oil by breeding.
Deep convolutional neural network for single remote sensing image super resolution

Abstract. The existing deep learning-based remote sensing image super-resolution (SR) reconstruction methods have some problems, such as insufficient feature extraction and detail loss. We propose an efficient and fast deep convolutional neural network (CNN) single-image SR model, which achieves relatively advanced reconstruction performance. The number of layers and filter layers of CNNs are completely optimized, and the computing cost is significantly reduced. The global and local features of the original image are extracted by multiscale features; then, contextual information is enhanced in the inference network, and the reconstruction is done in advance of the dimensionality reduction operation to reduce the computational effort. The reconstruction performance is further improved using skip connection network in the whole network to solve the inefficiency of information in the transmission process. The experimental results show that the algorithm is 0.32 to 4.38 dB higher than other algorithms in peak signal-to-noise ratio value, the structure similarity index measure value reaches 0.9618, and the reconstructed image extracts more features and is richer in details.
Environmental Quality and Economic Growth: An empirical analysis in Asian countries

This study investigates the relationship between environmental quality and economic growth in Asian countries. The findings from Pooled Mean Group (PMG) estimator affirmed the existence of a long-run relationship between environmental quality and economic development. The higher the economic growth, the higher the CO2 consumption. In the short run, economic growth exacts no harmful impact. Researchers and policymakers should be careful about the effect of economic growth and rising incomes on environmental pollution with the prioritisationation of sustainable usage of environmental policy. Investment and consumption of renewable energy that is less harmful to the environment should be focused on minimisingizing environmental pollution. Keywords: environmental quality; economic growth; Asian countries; PMG eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7i21. 3676
Influence of “Hospital-Community-Family” Integrated Management on Blood Pressure, Quality of Life, Anxiety and Depression in Hypertensive Patients

Objective To explore the Influence of “hospital-community-family” integrated management on blood pressure, quality of life, anxiety and depression in hypertensive patients. Methods A total of 60 patients with hypertension were treated in our hospital from July 2019 to July 2021. The patients were randomly divided into control group (n =30) and study group (n =30). The former accepts routine management, while the latter accepts “hospital-community-family” integrated management. Nursing satisfaction, blood pressure, disease awareness rate, anxiety and depression scores, disease control ability and quality of life scores were compared. Results First of all, we compared the nursing satisfaction: the study group was very satisfied in 25 cases, satisfactory in 4 cases, general in 1 case, the satisfaction rate was 100.00%, while in the control group, 10 cases were very satisfied, 8 cases were satisfied, 7 cases were general, and 5 cases were dissatisfied, the satisfaction rate was 83.33%; The nursing satisfaction of the study group was higher than that of the control group (P <0.05). Secondly, we compared the level of blood pressure. There was no significant difference before management (P >0.05) but the blood pressure decreased after treatment. In the control group, the level of blood pressure in the study group was lower than that in the control group (P <0.05). In terms of disease awareness rate the scores of hypertension related knowledge hypertension harmfulness community management methods regular reexamination and blood pressure monitoring in the study group were significantly higher than those in the control group (P <0.05). There was no significant difference in anxiety and depression scores before treatment (P >0.05), but decreased after treatment. Compared with the control group, the anxiety and depression scores of the study group were lower (P <0.05). In terms of disease control ability, the total scores of diet management, medication management, behavior management and information management in the study group were higher compared to the control group (P <0.05). Finally, we compared the scores of qualities of life. Before management, there exhibited no significant difference (P >0.05). After management, the scores of quality of life decreased. Compared to the control group, the scores of physiological function, psychological function, social function and health self-cognition in the study group were lower than those in control group (P <0.05). Conclusion The application of integrated “hospital, community and family” management can vertically integrate medical resources and establish a truly effective hierarchical treatment model. Integrated “hospital-community-family” management can improve patient compliance with treatment, enhance patients' self-management ability and confidence, and improve the management efficiency of medical staff.
Triple-Mode Average Current Control with Valley Current Shaping for DCM/CRM/CCM Boost PFC Converter

This paper presents a triple-mode average current control (TACC) strategy to achieve unity power factor and reduce the current stress for a boost PFC converter. The controller switches among different modes in each half-line cycle, and smooth transition is ensured by mapping of the operation region. By adaptive mode shifting, it reduces the current stress and current distortion caused by non-linear effects. With valley current shaping and comparisons, the TACC controller accordingly incorporates three control laws to adapt different modes. In discontinuous conduction mode (DCM), a variable on-time is calculated while the modulation is equivalent to PWM. In critical conduction mode (CRM), a constant on-time is derived, while the switching cycle is modified to regulate the current average value. For both DCM and CRM, the switching cycle is slightly extended to realize valley switching. Furthermore, with valley current shaping, the proposed controller reuses the CRM calculation to form continuous conduction mode (CCM) control law. To make the control laws compatible, normalized mapping and design rules are provided with respect to mode boundaries. This allows the TACC controller to automatically switch among different modes. Finally, experimental results prove the effectiveness of the controller in reducing the current stress and enlarging the preferable power range.