Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiagent-Based Consensus Optimal Control for Microgrid With External Disturbances via Zero-Sum Game Strategy

Due to the fact that the external disturbances are unavoidable in nonlinear microgrids (MGs) systems, which could induce the oscillation of the controller, leading to excessive line loss, and the nonlinearity of system could also result in controller design difficulty in MGs. Therefore, based on the distributed consensus algorithm of multiagent systems, this article studies the distributed voltage recovery consensus optimal control problem for the MGs with a nonlinear item and external disturbances. First, the distributed secondary voltage restoration consensus control problem can be transformed into a distributed zero-sum (ZS) differential game problem of the voltage restoration consensus tracking error dynamics via applying the adaptive command-filtered backstepping technique, in which the auxiliary system and neural networks are introduced to solve the unknown nonlinearities and external disturbances. Subsequently, the distributed voltage restoration consensus optimal control protocol is constructed via the ZS differential game algorithm to achieve the voltage recovery of island MGs, in which a critic network is proposed to estimate the associated cooperative cost function online with a designed weight update law. Further, the consensus optimal control protocol proposed not only ensures the cooperative cost function to be minimized, but also ensures in the closed-loop systems all signals to be cooperatively uniformly ultimately bounded. In addition, based on the Lyapunov stability theory, it is proved that the voltage recovery synchronization error can converge to an arbitrarily small range near the origin. Finally, simulation results verify the effectiveness of the proposed controller in island MG.
Socioeconomic and Behavioral Disparities Among Diabetics in Saudi Arabia: A Nation-Wide Descriptive Study

Purpose This study aims to explore sociodemographic, behavioral and clinical factors in adult participants with Diabetes in Saudi Arabia. Methods A population-based cross-sectional study of 20492 potential participants conducted in quarters 1 and 2 in 2021 from all 13 administrative regions of Saudi Arabia. A backward maximum likelihood logistic regression model, including all variables, was used to identify variables associated with participants living with Diabetes. Results A total of 14007 participants, aged ≥18 years, completed the interview, with a response rate of 68.3% and successful quota sampling. Fifty percent were male, the mean age was 36.7 (SD 13.7; range: 18–90). Of the total sample, 1633, 11.7% had Diabetes. Seven percent only of diabetic patients (124 participants) had an acceptable level of fruit and vegetable intake. In addition, only (274, 16.8%) had an acceptable level of physical activity, compared to (2389, 19.3%) in the non-diabetic group. Daily smokers were slightly higher in the diabetic group compared to the non-diabetic group (13.2% vs 11.7%). Hypertension was reported mostly by the diabetic group (45.1% vs 8%). Overweight and Obesity were more prevalent in patients with Diabetes (72.50% vs 51.62%). The results of the logistic regression have shown that several sociodemographic, behavioral and intermediate risk factors were significantly associated with Diabetes. Conclusion The study found that the prevalence of Diabetes in Saudi Arabia is around 12%, which is lower than the previously reported prevalence of Diabetes in Saudi Arabia. Moreover, Diabetes was found to be associated with lower educational level, smoking, obesity and overweight, hypercholesterolemia and hypertension. These factors are essential to be identified and screened in the community at regular interval; furthermore, controlling these factors may improve their disease management and quality of life. Additionally, knowing these factors will assist policymakers to shape an effective practical approach to combat diabetes widespread.
The Usefulness of Type Ia Supernovae for Cosmology - a Personal Review

We review some results of the past 12 years derived from optical and infrared photometry of Type Ia supernovae. A combination of optical and infrared photometry allows us to determine accurately the extinction along the line of sight. The resulting distance measurements are much more accurate than can be obtained from optical data alone. Type Ia supernovae are very nearly standard candles in the near-infrared. Accurate supernova distances, coupled with other observational data available at present, allow us to determine the matter density in the universe and lead to evidence for the existence of Dark Energy. We can now address some questions on the grandest scale such as, "What is the ultimate Fate of the universe? "
Enhanced Optimality Conditions and New Constraint Qualifications for Nonsmooth Optimization Problems

The main purpose of this dissertation is to investigate necessary optimality conditions for a class of very general nonsmooth optimization problems called the mathematical program with geometric constraints (MPGC). The geometric constraint means that the image of certain mapping is included in a nonempty and closed set. We first study the conventional nonlinear program with equality, inequality and abstract set constraints as a special case of MPGC. We derive the enhanced Fritz John condition and from which, we obtain the enhanced Karush-Kuhn-Tucker (KKT) condition and introduce the associated pseudonormality and quasinormality condition. We prove that either pseudonormality or quasinormality with regularity implies the existence of a local error bound. We also give a tighter upper estimate for the Frechet subdifferential and the limiting subdifferential of the value function in terms of quasinormal multipliers which is usually a smaller set than the set of classical normal multipliers. We then consider a more general MPGC where the image of the mapping from a Banach space is included in a nonempty and closed subset of a finite dimensional space. We obtain the enhanced Fritz John necessary optimality conditions in terms of the approximate subdifferential. One of the technical difficulties in obtaining such a result in an infinite dimensional space is that no compactness result can be used to show the existence of local minimizers of a perturbed problem. We employ the celebrated Ekeland’s variational principle to obtain the results instead. We then apply our results to the study of exact penalty and sensitivity analysis.
Theory of functions, zeros, polynomials, determinants, number theory, geometry

Four. Functions of One Complex Variable. Special Part. - Five. The Location of Zeros. - Six. Polynomials and Trigonometric Polynomials. - Seven. Determinants and Quadratic Forms. - Eight. Number Theory. - Nine. Geometric Problems. - x 1 Additional Problems to Part One. - New Problems in English Edition. - Author Index. - Topics.
DEATH AS PORTRAYED RESPECTIVELY BY ABDUL GHANI KHAN AND EMILY DICKINSON: A COMPARATIVE THEMATIC ANALYSIS

This article studies the theme of death in the works of the two poets Ghani khan and Emily Dickinson for whom death is the most resonant, mysterious, moving, and fascinating experience in human finitude. A comparative analysis of a selection of their works, carried out within a qualitative mode of inquiry that deploys the thematic analysis model of Braun and Clarke (2006), asserting that their poems endow the idea of death with a range of symbolic implications. They either personalize it, symbolize it, or directly elaborate on death in an optimistic way without forgetting about the sheer truth about its exterminatory impact on all living entities. Despite the fact that the American poet Emily Dickinson and the Pashto poet Abdul Ghani Khan belong to two different backgrounds, cultures, and eras their poetry has many points of similarity that curtail the distance of time and space between them
‘Me’ versus ‘We’: exploring the personal and professional identity-threatening experiences of police officers and the factors that contribute to them

ABSTRACT From semi-structured interviews with 42 Canadian police officers, the study suggests that the occupational context created both personal and professional identity threats are largely based on the degree to which officers aligned with the image of the ideal worker as physically strong, aggressive and committed to the job. Because perceived nonconforming members also violated gendered expectations for behavior, they not only experienced threats to their personal identities, but also were potentially subjected to bullying, harassment, and isolation. Socialization processes and occupational stigma were identified as two key factors that intensified the occupational identity and the ‘us’ and ‘them’ divide leading to more vigorous defenses against group identity threats. Despite the salience of these contextual factors, not all officers experienced the identity threats in the same way, highlighting changing views on what it means to be an ‘ideal’ police officer as well as opportunities for reform.
Review of studies on FDI: The case of Baltic States

The authors reviewed the foreign direct investment in Baltic countries. The theoretical part of the paper systemizes essential driving forces (elements) of FDI studies and the methods most common in FDI studies; the hierarchy of qualitative methods and models is presented. Three-tier methodology is suggested. The first tier (or level) represents a mathematical approach towards interconnections between FDI variables. The second tier of methodology is dedicated to sector analysis and benchmarking. The third tier targets revising economic variables and their links with variables representing FDI. The suggested approach could be applied for similar analysis. The authors have constructed a correlation matrix. The results of the analyzed variables via the dynamic regression approach show that the strongest links among variables appeared in several-year periods. The obtained results may have significant policy implication.
Effectiveness and Safety of Immunosuppressants and Biological Therapy for Chronic Spontaneous Urticaria: A Network Meta-Analysis

Chronic spontaneous urticaria (CSU) is the most common phenotype of chronic urticaria. We compared treatment effects and safety profiles of the medications in patients with CSU. We searched PubMed, MEDLINE, and Web of Science for randomized control trials (RCTs), from 1 January 2000 to 31 July 2021, which evaluated omalizumab and immunosuppressants. Network meta-analyses (NMAs) were performed with a frequentist approach. Outcome assessments considered the efficacy (Dermatology Life Quality Index (DLQI) and weekly urticaria activity score (UAS7)) and tolerability profiles with evaluations of study quality, inconsistencies, and heterogeneity. We identified 14 studies which we included in our direct and indirect quantitative analyses. Omalizumab demonstrated better efficacy in DLQI and UAS7 outcomes compared to a placebo, and UAS7 assessments also demonstrated better outcomes compared to cyclosporine. Alongside this, omalizumab demonstrated relatively lower incidences of safety concerns compared to the other immunosuppressants. Cyclosporin was also associated with higher odds of adverse events than other treatment options. Our findings indicate that omalizumab resulted in greater improvements in terms of the DLQI and UAS7 with good tolerability in CSU patients compared to the other immunosuppressants.
The immunity priming effect of the Arabidopsis phyllosphere resident yeast Protomyces arabidopsidicola strain C29

The phyllosphere is a complex habitat for diverse microbial communities. Under natural conditions, multiple interactions occur between host plants and phyllosphere resident microbes, such as bacteria, oomycetes, and fungi. Our understanding of plant associated yeasts and yeast-like fungi lags behind other classes of plant-associated microbes, largely due to a lack of yeasts associated with the model plant Arabidopsis, which could be used in experimental model systems. The yeast-like fungal species Protomyces arabidopsidicola was previously isolated from the phyllosphere of healthy wild-growing Arabidopsis, identified, and characterized. Here we explore the interaction of P. arabidopsidicola with Arabidopsis and found P. arabidopsidicola strain C29 was not pathogenic on Arabidopsis, but was able to survive in its phyllosphere environment both in controlled environment chambers in the lab and under natural field conditions. Most importantly, P. arabidopsidicola exhibited an immune priming effect on Arabidopsis, which showed enhanced disease resistance when subsequently infected with the fungal pathogen Botrytis cinerea. Activation of the mitogen-activated protein kinases (MAPK), camalexin, salicylic acid, and jasmonic acid signaling pathways, but not the auxin-signaling pathway, was associated with this priming effect, as evidenced by MAPK3/MAPK6 activation and defense marker expression. These findings demonstrate Arabidopsis immune defense priming by the naturally occurring phyllosphere resident yeast species, P. arabidopsidicola, and contribute to establishing a new interaction system for probing the genetics of Arabidopsis immunity induced by resident yeast-like fungi.
Radar-Based Multisensor Fusion for Uninterrupted Reliable Positioning in GNSS-Denied Environments

Multi-sensor integration is necessary to provide high-precision navigation solutions for autonomous vehicles. Land-vehicles often rely on global navigation satellite systems (GNSS) to acquire its position. However, there are some environments where GNSS signals are unavailable, such as indoor-parking garages, tunnels, and under bridges. Additional sensors are required to allow reliable positioning regardless of location. The vehicle’s on-board low cost inertial sensors (accelerometers and gyroscopes) are used for positioning in GNSS-denied environments. Despite their fidelity in short-term usage, inertial navigation systems (INS) are susceptible to drifts in their positioning solution due to the inherent inertial sensor errors, causing positioning errors over time in prolonged scenarios, such as indoor-parking garages. Modern land-vehicles can be equipped with a diversified set of perception systems (e.g. LiDAR, cameras) to provide information about the surrounding environment. These systems are well-studied in literature to provide accurate positioning. Yet, the performance of these systems may degrade in weather conditions such as heavy snow or rain, and may fail in degraded vision environments. The proposed research addresses some of the limitations of current positioning technologies for land vehicles by integrating low-cost on-board motion sensors with the all-weather electronic scanning radar (ESR) systems presently used in adaptive cruise control. This research employs a method of estimating the vehicle position based on multiple ESR systems. Integration with the on-board motion sensors guarantees continuous positioning estimation for uninterrupted navigation. The multi-sensor system integration utilizes extended Kalman filter (EKF) with a unique dynamic tuning approach for reliable and uninterrupted positioning. The proposed solution was examined in real GNSS-denied scenario of an indoor parking. This research has reached an uninterrupted self-contained EKF-based multi-sensor positioning system providing less than 2m error 90% of the time in a GNSS-denied environment for up to four minutes.
Complete mitochondrial genome of the top hat blenny, Omobranchus fasciolatoceps Richardson (Blenniiformes: Blenniinae) in Southern China Coast

Abstract The complete mitochondrial genome sequence of Omobranchus fasciolatoceps was firstly described in this article. The total length of mitogenome was 16,569 bp. It contains 13 protein-coding genes, 22 tRNA genes, and two ribosomal RNA genes. The overall base composition of H-strand was 29.04% A, 27.14% C, 27.89% T, and 15.93% G, with an A＋T bias of 56.93%. The phylogenetic analysis results showed that the O. fasciolatoceps was most closely related to O. elegans.
Corn Disease Detection Based on an Improved YOLOX-Tiny Network Model

In order to detect corn diseases accurately and quickly and reduce the impact of corn diseases on yield and quality, this paper proposes an improved object detection network named YOLOX-Tiny, which fuses convolutional attention module (CBAM), mixup data enhancement strategy, and center IOU loss function. The detection network uses the CSPNet network model as the backbone network and adds the CBAM to the feature pyramid network (FPN) of the structure, which re-assigns the feature maps' weight of different channels to enhance the extraction of deep information from the structure. The performance evaluation and comparison results of the methods show that the improved YOLOX-Tiny object detection network can effectively detect three common corn diseases, such as cercospora grayspot, northern blight, and commonrust. Compared with the traditional neural network models (90.89% of VGG-16, 97.32% of YOLOv4-tiny, 97.85% of YOLOX-Tiny, 97.91% of ResNet-50, and 97.31% of Faster RCNN), the presented improved YOLOX-Tiny network has higher accuracy.
Identity-Based Broadcast Signcryption Scheme for Vehicular Platoon Communication

Vehicular platooning is emerging as a promising method that can enhance road utilization, alleviate traffic congestion, and even decrease energy expenditure by shortening the distance between vehicles in the platoon. In platooning, a platoon leader (PL) is required to communicate with platoon members (PMs) to issue instructions. In this way, the PMs are simply expected to follow the command and enjoy their free time. However, when the same instruction is sent to different PMs in the form of single-hop unicast, the ciphertext will go up as the quantity of PMs in the platoon resulting in a dramatic increase in transmission time. Moreover, transmission instructions without security and authentication guarantees are easily intercepted, forged, or deleted. Therefore, in this article, we propose broadcast signcryption scheme for platoon communication (BSPC), a broadcast signcryption scheme for platoon communication based on identity. In our BSPC, with only one signcryption, the PL can generate a public verifiable ciphertext with fixed-length for PMs, while employing broadcast functionality to deliver the ciphertext to multiple PMs at once. In such a manner, the confidentiality, integrity, and authentication of transmitted commands are ensured, such that malicious vehicles cannot manipulate data and unauthorized vehicles have no way to access it. Besides, the instructions' transmit time is greatly reduced. Our BSPC proposal is proved to be secure and unforgeable through rigorous analysis. Furthermore, simulation results demonstrate our BSPC is practical and efficient for platoon communication.
Local techniques in quadratic optimization and Satisfiability, and their applications

Optimization problems are important from both theoretical and practical points of view. For decades, they have been in the focus of a wide and very active research area. There are studies on designing efficient heuristics and exact algorithms for solving optimization problems, as well as, using them to build practical applications. In many cases that are important for applications finding exact or even approximate solutions is NP-hard. In this thesis, we attempt to design heuristics and algorithms for certain NP-hard optimization problems, analyze those algorithms, evaluate their performance empirically, and look for possible applications. In particular, we focus on incorporating quantum annealing devices into our heuristic methods and applications. We conduct an experimental evaluation on the quantum annealing device built by DWave Systems Inc, a Vancouver based startup company. As a new piece of technology which is still under development, there are many open questions related to the current device. The aim of the evaluation is to understand the behaviour and performance of the device on NP-hard optimization problems. The results of our study show that the device performs well on several classes of benchmark problems. Moreover, the evaluation also reveals two pressing issues that limit the practical use of the device. To tackle these issues, we consider the random Max2SAT problem, in which instances are 2CNFs with a fixed clause-to-variables ratio, drawn at random according to some distribution. More precisely, we introduce two distributions of 2CNFs, in both of which instances are drawn from the set of formulas with more than average number of satisfiable clauses. We establish a connection between these two distributions, identify the likely level of satisfiability of a random 2CNF, and evaluate the performance of very basic local heuristics on these distributions.
Control and motivation in task performance of public servants at home office in the face of the COVID-19 pandemic

PurposeThe purpose of the article is to analyze the influence of output control, autonomous motivation and controlled motivation on task performance of public servants at home office owing to the COVID-19 pandemic.Design/methodology/approachA survey was conducted based on the perception of 236 public servants, and structural equation modeling (SEM) technique was used for data analysis.FindingsBoth autonomous motivation and output control are positively and significantly related to task performance.Research limitations/implicationsThe present study expands the literature with information about individual performance and management control, which can be related to the control, motivation and task performance of public servants at home office in a pandemic context.Practical implicationsThe results could offer a basis for understanding how managers can deal with the challenges while at home office. They can also provide managers with information that they can use to build management strategies to foster the performance of public servants at home office.Social implicationsHome office can decrease commuting to a central workplace, alleviate traffic problems and reduce car pollution. It also allows for business continuity in the face of storms and pandemics.Originality/valueMost studies about home office, COVID-19 and task performance have addressed personal, professional and organizational characteristics. However, little is known about the analysis of combinations of the following constructs: output control, autonomous and controlled motivations, and how both affect task performance of public servants.