Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Unfolding Network for Spatiospectral Image Super-Resolution

In this paper, we explore the spatiospectral image super-resolution (SSSR) task, i.e., joint spatial and spectral super-resolution, which aims to generate a high spatial resolution hyperspectral image (HR-HSI) from a low spatial resolution multispectral image (LR-MSI). To tackle such a severely ill-posed problem, one straightforward but inefficient way is to sequentially perform a single image super-resolution (SISR) network followed by a spectral super-resolution (SSR) network in a two-stage manner or reverse order. In this paper, we propose a model-based deep learning network for SSSR task, named unfolding spatiospectral super-resolution network (US3RN), which not only uses closed-form solutions to solve SISR subproblem and SSR subproblem, but also has extremely small parameters (only 295 K). In specific, we reformulate the image degradation and incorporate the spatiospectral super-resolution (SSSR) model, which takes the observation models of SISR and SSR into consideration. Then we solve the model-based energy function via the alternative direction multiplier method (ADMM) technique. Finally, we unfold the iterative process of the ADMM algorithm into a multistage network. Therefore, US3RN combines the merits of interpretability and generality of model-based methods with the advantages of learning-based methods. The experimental results show that, compared with the two-step method, US3RN achieves better results both quantitatively and qualitatively, while sharply reducing the number of parameters and FLOPs. Source code will be available at https://github.com/junjun-jiang/US3RN.
Fuzzing Methods Recommendation Based on Feature Vectors

Fuzzing is a technique that aims to detect vulnerabilities or exceptions through unexpected input and has found tremendous recent interest in both academia and industry. Although these fuzzing methods have great advantages in the field of vulnerability detection, they also have their own disadvantages in the face of different target programs. It is obviously impractical for a fuzzing test method to adapt to all the target programs. Therefore, we study how to select the appropriate fuzzing methods for different target programs. Specifically, we first analyze the program, and then extract the feature vectors of the target program to get the information of the program, such as syntax, context and so on. Next, we build a matching model to match the similarity of target program and the fuzzing algorithm to select the fuzzing algorithm with higher matching degree. Through our matching model, we get a more suitable fuzzing algorithm to improve the detection efficiency, precision, recall, F-measure, and other statistical measures.
Muskit: A Mutation Analysis Tool for Quantum Software Testing

Given that quantum software testing is a new area of research, there is a lack of benchmark programs and bugs repositories to assess the effectiveness of testing techniques. To this end, quantum mutation analysis focuses on systematically generating faulty versions of Quantum Programs (QPs), called mutants, using mutation operators. Such mutants can be used as benchmarks to assess the quality of test cases in a test suite. Thus, we present Muskit - a quantum mutation analysis tool for QPs coded in IBM's Qiskit language. Muskit defines mutation operators on gates of QPs and selection criteria to reduce the number of mutants to generate. Moreover, it allows for the execution of test cases on mutants and generation of results for test analyses. Muskit is provided as command line interface, GUI, and web application. We validated Muskit by using it to generate and execute mutants for four QPs. Muskit code: https://github.com/Simula-COMPLEX/muskitWeb app: https://qiskitmutantcreatorsrl.pythonanywhere. com/YouTube Video: EbPHJOK_AEA Artifact Available: https://doi.org/10.5281/zenodo.5288917
Factors Affecting Adoption of Heytea Based on SICAS Model

Heytea pioneered the digitization of Chinese beverage chains by leveraging social apps like WeChat, Weibo, etc. Due to the trend of consumption upgrades, it is observed that consumers are having more demand for the bubble tea chain industry. Based on SICAS and TAM, the research constructs a theoretical model of consumers' consumption factors, summarizes the existing problems, and suggests the corresponding solutions. This study provides a new perspective on bubble tea chains.
Effects of Voltage Harmonics on the No-load losses of a Three-phase Distribution Transformer

The increased use of the direct current components and power electronic equipment's increase the significance of harmonics in the power system. In the power system, the transformer is one of the important equipment. Non-sinusoidal voltage source leads to higher losses and decreases the life of the transformer. In this study, the three-dimensional finite element method was used to examine four different conditions for the evolution of the no-load losses of the transformer. During the first condition, no-load losses were examined for the normal conditions i.e. without any harmonics. The finite element analysis result of the normal condition is also compared with the experimental and analytical results. For condition II, III and IV, harmonic voltages were added to the primary voltage. The main aim of this study is to analyze the effect of the different harmonic orders and magnitudes on the no-load losses. This study will help the transformer designers, to evaluate the effect of the different harmonics on the no-load losses.
Application of Social Networks Data Mining in Strengthening College Ideological Environment

Application of social networks data mining in strengthening college ideological environment is studied in this manuscript. In the actual application of machine learning, the number of features is often large, and there may be irrelevant features, and there may also be interdependence between the features. However, a large amount of the above classification work is based on a single-dimensional complex network, with this basis, this paper defines the novel mining algorithm. The model is applied into the scenarios and the experimental results are also tested.
Study and Application of the Measurement Method of Phase Difference in the Single Component Dye Solution Concentration

Spectrophotometer can accurately detect the medium-light color dye concentration but will produce a large error for the dark or very light color dye solution. In this paper, the laser is used as the test signal and expressed in the form of optical quantum wave function, the dye solution is regarded as a one-dimensional square potential barrier, a model is established between the single component dye concentration and the phase difference of transmitted light that tunneled the barrier. The experimental device for the relationship between the dye concentration and the phase difference of transmitted light is designed. The model coefficients were obtained by the experimental data and the least square method, and finally, the model of laser measurement the dye concentration online was obtained. The dye concentration in the model is proportional to the phase difference of transmitted light, which is easy to calculate and measure. The accuracy of the model was verified by experiments.
Transcriptome Analysis Reveals Key Pathways and Candidate Genes Controlling Seed Development and Size in Ricebean (Vigna umbellata)

Ricebean (Vigna umbellata) is a lesser known pulse with well-recognized potential. Recently, it has emerged as a legume with endowed nutritional potential because of high concentration of quality protein and other vital nutrients in its seeds. However, the genes and pathways involved in regulating seed development and size are not understood in this crop. In our study, we analyzed the transcriptome of two genotypes with contrasting grain size (IC426787: large seeded and IC552985: small seeded) at two different time points, namely, 5 and 10 days post-anthesis (DPA). The bold seeded genotype across the time points (B5_B10) revealed 6,928 differentially expressed genes (DEGs), whereas the small seeded genotype across the time point (S5_S10) contributed to 14,544 DEGs. We have also identified several candidate genes for seed development–related traits like seed size and 100-seed weight. On the basis of similarity search and domain analysis, some candidate genes (PHO1, cytokinin dehydrogenase, A-type cytokinin, and ARR response negative regulator) related to 100-seed weight and seed size showed downregulation in the small seeded genotype. The MapMan and KEGG analysis confirmed that auxin and cytokinin pathways varied in both the contrasting genotypes and can therefore be the regulators of the seed size and other seed development–related traits in ricebeans. A total of 51 genes encoding SCF TIR1/AFB , Aux/IAA, ARFs, E3 ubiquitin transferase enzyme, and 26S proteasome showing distinct expression dynamics in bold and small genotypes were also identified. We have also validated randomly selected SSR markers in eight accessions of the Vigna species (V. umbellata: 6; Vigna radiata: 1; and Vigna mungo: 1). Cross-species transferability pattern of ricebean–derived SSR markers was higher in V. radiata (73.08%) than V. mungo (50%). To the best of our knowledge, this is the first transcriptomic study conducted in this crop to understand the molecular basis of any trait. It would provide us a comprehensive understanding of the complex transcriptome dynamics during the seed development and gene regulatory mechanism of the seed size determination in ricebeans.
Performance Assessment of Two Stage Operational Transconductance Amplifier in 180nm with Optimised Compensation Capacitance and Nulling Resistor

This paper illustrates the performance assessment and design of CMOS Two Stage OTA under 180nm technology node focusing on optimization in compensation capacitance, reduction in power dissipation. The designed circuit operates at supply voltage of 1.8V and varying supply up to 1.2V. The input relay is dependent on bias current. In this paper, the device parameters such as AC-Gain, Phase margin, CMRR, Noise and Power dissipation are theoretically calculated and analyzed using LT spice software 180nm technology for given specifications. As the power is a major design parameter, the bias current and supply voltage is varied within the range of respective technology nodes to achieve a minimum power dissipation design. For minimum power design, reduction in bandwidth and stability of the system are major trade-offs. The designed circuit uses a specific compensation methodology for implementing the compensation called Miller compensation. It is used for improving the bandwidth and phase of the system for various capacitive driven loads.
Exploring the Impact of Digital Global Governance through Affordance Theory: the Case of Climate Reporting

The world is facing global challenges, which has led to international policy development such as the Paris Agreement (the United Nations climate agreement). An important element of the Paris Agreement is reporting. As digital technologies are used in reporting, this can be considered a case of digital global governance. Surprisingly, the global dimension of digital governance has received little attention from the academic community. Thus, theoretical and empirical understanding of digital global governance and how it responds to global challenges is needed. To address this, climate reporting to the United Nations, with Sweden as a case, has been studied. Reporting was chosen because of the significant role of embedded IT artefacts. Empirical data was analyzed with the lens of affordance theory. Findings suggest that IT artefacts and information in the reporting have affordances that enables monitoring, transparency, implementation of agreement, coordination & collaboration, analysis & visualization, and re-use of information.
Adoption of Automation Technologies in Public Organizations: The Perception of Healthcare Professionals in Greece

The purpose of this study was to investigate the beliefs and perceptions of Greek healthcare professionals working in public hospitals about the new automation technologies in health services. Focus was placed on two representative examples, namely, the Automated Decision-Making and the Robotic Process Automation systems. Towards this goal, and in order to acquire a holistic viewpoint, we interviewed personnel from different positions, with different hierarchical duties and with variable working experience. Most of the participants were not aware of the two aforementioned technologies and, as a result, did not use any related tool in everyday practice. However, they were positive to be educated and trained in programs that specifically relate to their duties. The central criteria for adopting the new technology were the reduction in effort and time for accomplishing a work, the increase in reliability and efficiency as well as the lower levels of anxiety when a program could serve as a “checklist” add-on. Key issues, such as the improvement of the already available software to follow the modern systems and the initiation of educational programs to address the “electronic illiteracy” of the staff were emphasized. Finally, concerns about the implementation of these technologies were expressed, such as the potential lack of trust from patients to healthcare professionals, the complacency of younger colleagues and the low applicability of these tools in cases of manual work or dynamic conditions.
A Snapshot of AI Solutions in the Public Sector

: The implementation of Artificial Intelligence (AI) in public settings is not a new topic. However, only recently it gained momentum, and practitioners started investigating the potentialities of this technology also within the public boundaries. On the opposite scholars rarely focus on AI, leaving an urgent gap to fill. Moreover the current body of literature is muddleheaded and scholars fatigue in disentangling and clarifying the various domains and fields of analysis. This paper aims at providing an overview of the state-of-the-art of AI applications, in order to explore the trends and identify promising paths for future research. For doing that it relies on an original and up-to-date study of existing AI projects worldwide.
Lessons from Psychological First Aid: Supporting Healing of Healthcare Workers Affected by COVID-19

A few months ago, I (SM) was invited to do a presentation to a group of frontline healthcare providers who were attending a professional retreat as respite from the intensity of the pandemic. All of the healthcare workers were vaccinated, and while the room was filled with a sense of hope due to the vaccine, the heaviness of patients, colleagues, and loved ones lost was intensely present, as was the knowledge that many more would be lost over
Anger - the Missing Piece in the 5 Essential Elements Approach

Since its publication, the “Essential Elements of Mass Trauma Intervention” by Hobfoll et al. (2007) has been a seminal paper in guiding disaster response interventions for governments, health, welfare and emergency services, and practitioners internationally. In the absence of an extant evidence base for post-disaster interventions – an arena where conducting controlled intervention trials is extremely difficult – it gathers expert opinion to inform core guiding principles of intervention. To date, the five response elements it promotes, namely, 1) a sense of safety; 2) calming; 3) a sense of self and community efficacy; 4) connectedness; and 5) hope, have proven resilient and exist as the cornerstone for psychological care and support in the acute and mediumterm aftermath of disaster. The Hobfoll paper also elaborates on various interventions for operationalizing these principles and how to best apply them to address postdisaster psychological distress. The field continues to seek opportunities to build the evidence base around post-disaster interventions, and other papers in this series will comment on further developments in this area. The focus of this commentary, however, is to highlight a critically important phenomenon within the human post-disaster response that appears to have been overlooked by Hobfoll and colleagues, that of extreme or “dysfunctional” anger and is hence not represented in the application of the principles or elements for intervention. This commentary seeks to highlight anger’s prominence in the post-disaster environment and posit strategies for intervention consistent with the Hobfoll paper elements so dysfunctional anger may be more efficaciously addressed in postdisaster response. The Hobfoll paper identifies the range of cognitive, emotional, behavioral, and physical responses to the experience of disaster-related trauma as pertaining to internalized dysphoric states. The paper cites uncertainty, fear, sadness, depression and grief, numbing, panic, dissociation, loneliness, futility, helplessness and hopelessness and arousal and distress. In thus describing the psychological response to disasters, the paper reflects the then practical and theoretical psychological zeitgeist and the lineage of psychotraumatology preceding it. In this context, however, this commentary emphasizes the importance of updating the recovery model articulated in the Hobfoll paper, by accommodating angry affect, and particularly dysfunctional anger, and its behavioral correlates, within the array of psychological, emotional, and
Timing Optimization for Two-phase Intersections Considering Pedestrian Crossing

Considering the relevant moving characteristics of vehicle and pedestrian crossing,their interactions at intersections,and the safety of pedestrian,this study adds the leading and lagging green time in signal timing of the two-phase control.In view of the needs of pedestrian crossing,the maximum delay and the total pedestrian delay are introduced into the timing optimization model.The model takes the cycle,stopping rate,saturation,queue length,and maximum accepting delay of both pedestrian and vehicle as the constraint conditions.Minimum total delay of pedestrian and vehicle is the optimization object of the model.The solving methods are also provided in following part.The concept and proposed method of this study offer new ideas for the timing optimization of the signalized intersections.
User experiences using e-Hailing food delivery service in Klang Valley

The service quality is always of the utmost significance for generating the experiences in using e-Hailing food delivery service because the quality of goods and services are highly dependent on the e-Hailing food delivery service apps' users. Thus, this paper examines the relationships between the e-Hailing food delivery service quality dimensions (i.e., App Responsiveness, App Reliability, Product Expectation, Rider Professionalism
THE RELATHIONSIP BETWEEN PEER ATTACHMENT AND SELF- REGULATED LEARNING

This researching is motivated by the emergence of the phenomenon of students who experience low self-regulated learning (SRL), this can have an impact on the mastery of tasks to gain understanding of learning topics optimally so that they have difficulty in facing academic tasks that are their responsibility as students. Some of the factors that affect SRL are personal, behavioral and environmental. Environmental factor for example is a relationship with peers (Peer Attachment), Knowing the relationship between peer attachment and self-regulated learning and how much relationship between peer attachment and self-regulated learning. The method used by researchers is a quantitative method with a population of 63 students. The Non-Probability sampling technique used in this study was Incidental Sampling and obtained the number of respondents as many as 41 students. The data collection in this study uses scale (questionnaire) through Google Form uses the likert scale. Testing the research hypothesis uses spearman rho correlation analysis technique with the help of SPSS 25.0 software. Statistical analysis is not have relationship between peer attachment variables and Selfregulated learning. This researching is expected to add knowledge, insight and can be an information material for students about the relationship between peer attachment variables and self-regulated learnig. The limited number of samples willing to be respondents in the researching process there are obstacles in extracting information or encountering subjects caused by pandemic factors. Further research is expected to add to the variables studied regarding Self-Regulated learning.
OP-NARE120455 1..14

A major fraction of the transcriptome of higher organisms comprised an extensive repertoire of long non-coding RNA (lncRNA) which express in a cell type and development stage-specific manner. While lncRNAs are a proven component of epigenetic gene expression modulation, epigenetic regulation of lncRNA itself remains poorly understood. Here we have analysed pan-genomic DNA methylation and histone modification marks (H3K4me3, H3K9me3, H3K27me3 and H3K36me3) associated with transcription start site (TSS) of lncRNA in four different cell types and three different tissue types representing various cellular stages. We observe that histone marks associated with active transcription H3K4me3 and H3K36me3 along with the repressive histone mark H3K27me3 have similar distribution pattern around TSS irrespective of cell types. Also, the density of these marks correlates well with expression of protein-coding and lncRNA genes. In contrast, the lncRNA genes harbour higher methylation density around TSS than protein-coding genes regardless of their expression status. Furthermore, we found that DNA methylation along with the other repressive histone mark H3K9me3 does not seem to play a role in lncRNA expression. Thus, our observation suggests that epigenetic regulation of lncRNA shares common features with mRNA except the role of DNA methylation which is markedly dissimilar.
Multidisciplinary Optimal Design of an Active Control System and State Estimator for an Aircraft Wing

A multidisciplinary and multi-objective optimization approach that integrates the design of the control surfaces’ sizes, active control system, and estimator for an aircraft’s wing with three control surfaces is developed in this paper. Four objectives are considered: minimizing impacts of external gust loads, maximizing stability robustness, reducing control energy consumption, and minimizing the Frobenius norm of the estimator gains. For simulation purposes, a mathematical model of a flexible wing having three ailerons is used. The control system and observer are designed simultaneously. The optimization problem is formulated and solved by NSGA-II (non-dominated sorting genetic algorithm II). The solution of the optimization problem is called the Pareto set and the corresponding set of function evaluations is called Pareto front. The properties of the Pareto set and Pareto front; sensitives of the dominant poles of the open-loop system, closed-loop system, and estimator to the airspeed; and responses of the controlled, uncontrolled, and observer models at selected objective values are obtained. The results shows that the simultaneous design of the control and estimator algorithms, and the geometry of the ailerons in the multi-objective settings is very effective, the closed-loop control system can suppress the flutter and stabilize the system, and the estimator converges very quickly and always stable regardless of the air stream velocity.