Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-compliant Managers, Judging Citizens: An Experiment of Motives, Identities, and Public Reaction to Bureaucratic Rule Breaking

Abstract Despite the serious demands for public organizations to maintain political accountability and bureaucratic responsiveness, rule breaking persists among employees across all levels. Unlike our deeper understanding of corruption of elected officials, myriad questions remain regarding the nature of the public response to policy violations of government bureaucrats working in politically neutral administrative positions. This study uses a survey experiment to investigate factors influencing the intensity of citizens’ recommended punishments for rule-breaking local government managers, specifically testing the effects of managers’ demographic attributes of age, race, and gender as well as their motivations for the violations. Findings strongly suggest that motive matters to citizens in this context, with prosocial rule-breaking managers incurring significantly less harsh penalties than destructive rule-breakers for all age-race-gender profiles. However, an absence of demographic information nullifies penalty differences between prosocial and destructive rule-breaking managers. Among the demographic attributes, only the managers’ race predicted the severity of punishments favored by citizens. No interaction effects between manager attributes were present. Results suggest public communications emphasizing person and purpose are particularly important for local government managers in this context.
Urban land-use land-cover extraction for catchment modelling using deep learning techniques

Over the world, the likelihood of floods and managing the associated risk are a concern to many catchment managers and the population residing in those catchments. Catchment modelling is a popular approach to predicting the design flood quantiles of a catchment with complex spatial characteristics and limited monitoring data to obtain the necessary information for preparing the flood risk management plan. As an important indicator of urbanisation, land use land cover (LULC) plays a critical role in catchment parameterisation and modelling the rainfall–runoff process. Digitising LULC from remote sensing imagery of urban catchment is becoming increasingly difficult and time-consuming as the variability and diversity of land uses occur during urban development. In recent years, deep learning neural networks (DNNs) have achieved remarkable image classification and segmentation outcomes with the powerful capacity to process complex workflow and features, learn sophisticated relationships and produce superior results. This paper describes end-to-end data assimilation and processing path using U-net and DeepLabV3+, also proposes a novel approach integrated with the clustering algorithm MeanShift. These methods were developed to generate pixel-based LULC semantic segmentation from high-resolution satellite imagery of the Alexandria Canal catchment, Sydney, Australia, and assess the applicability of their outputs as inputs to different catchment modelling systems. A significant innovation is using the MeanShift clustering algorithm to reduce the spatial noise in the raw image and propagate it to the deep learning network to improve prediction. All three methods achieved excellent classification performance, where the MeanShift+U-net has the highest accuracy and consistency on the test imagery. The final suitability assessment illustrates that all three methods are more suitable for the parameterisation of semi-distributed modelling systems rather than the fully distributed modelling systems, where the MeanShift+U-net should be adopted for image-based impervious area extraction of urban catchment due to its superior prediction accuracy of 98.47%.
Critical success factors of cloud enterprise resource planning systems and financial performance: Evidence from emerging markets

Cloud ERP (C-ERP) systems help firms to reach greater levels of sustainable performance (Gupta, Qian, Bhushan, & Luo, 2019). Ali (2016) demonstrate that the enterprise resource planning (ERP) system implementation influences financial performance indicators. Huang, Rahim, Foster, and Anwar (2021) had investigated and identified the critical success factors (CSFs) which may affect the successful implementation of C-ERP systems. However, no empirical evidence was found on the relationship between C-ERP critical success factors and financial performance. This study examined the effect of key CSFs of the C-ERP systems on financial performance in the post-implementation stage. An online questionnaire was developed to collect data about CSFs in C-ERP firms. The financial ratios were collected from the Amman Stock Exchange (ASE) filings. OLS analysis suggests that financial performance is affected by technological competence, management support, organizational culture, and system characteristics. The study provides empirical evidence on the cause-effect relationship which emphasizes the difference made in long-term financial success by the various managerial techniques. The results provide practical implications to management and service providers that help in installing and maintaining C-ERP systems.
MEC computing resource-constrained Stackelberg game computing offloading method

Mobile Edge Computing (MEC) effectively improves user service quality by sinking the computing center to the edge of the neighboring terminal users. However, insufficient MEC cloud computing resources have created many obstacles to the promotion and application of edge cloud technology. Aiming at the problem of MEC computing offloading and resource allocation under the condition of limited computing resources, this paper builds a Stackelberg master-slave game model to conduct "cloud-side" interactive analysis on MEC revenue and user service quality, and uses differentiated pricing strategies to strengthen the constraints on offloading strategies. Obtain the largest MEC revenue unloading ratio. Finally, the optimal simulated annealing algorithm is used to iterate the optimal allocation strategy of MEC computing resources. Simulations show that the solution in this paper can effectively improve the MEC rate of return on the basis of optimizing the quality of user experience. This method has guiding significance for the study of unloading problems under resource-constrained conditions.
Spatial frequency bands used by patients with glaucoma to recognize facial expressions

ABSTRACT The authors investigated the influence of spatial frequencies in foveal vision in glaucomatous patients in a recognition task of facial expressions. Nineteen patients, 16 age-matched and 14 young controls saw centrally presented photographs of faces. Participants categorized the facial expressions as happy, angry or neutral. Two versions were tested: filtered faces of either low (LSF) or high (HSF) spatial frequency content and hybrid faces constructed from a face with LSF content superimposed on a face with HSF content with differing facial expressions. Compared to age-matched controls a significant deficit was observed both on HSF and on LSF filtered faces for patients. Controls, but not patients, were biased towards the HSF component of the hybrid faces. Different spatial frequencies are normally used to recognize different facial expressions. Impaired processing of a spatial frequency bandwidth due to an ocular pathology can therefore lead to misinterpretation of emotions, and impact on social interactions.
Maturity of Industry 4.0: A Systematic Literature Review of Assessment Campaigns

The Industry 4.0 paradigm represents the fourth industrial revolution, embodied by the marriage between information and communication technologies and manufacturing. Assessment campaigns are conducted to examine the status of deployment of that paradigm, mostly through self-assessment questionnaires. Each campaign is typically limited in scope, involving just a group of companies located in a few countries at most. Such limitation does not allow an overall view of Industry 4.0’s diffusion. In this paper, we offer that panoramic view through a systematic literature review. The number of papers devoted to Industry 4.0 assessment grows steadily. However, many papers do not provide essential information about the assessment campaigns they report, e.g., not detailing the number, type, or location of companies involved and the questionnaire employed. We observe a large diffusion in Europe and Asia but not in the U.S., with the Top 5 countries being Malaysia, Poland, Italy, Germany and Slovakia. The campaigns uniformly cover small, medium, and large companies but not all industrial sectors. The choice of questionnaires is extremely varied, with no standard emerging.
Discovery of APL-1030, a Novel, High-Affinity Nanofitin Inhibitor of C3-Mediated Complement Activation

Uncontrolled complement activation contributes to multiple immune pathologies. Although synthetic compstatin derivatives targeting C3 and C3b are robust inhibitors of complement activation, their physicochemical and molecular properties may limit access to specific organs, development of bifunctional moieties, and therapeutic applications requiring transgenic expression. Complement-targeting therapeutics containing only natural amino acids could enable multifunctional pharmacology, gene therapies, and targeted delivery for underserved diseases. A Nanofitin library of hyperthermophilic protein scaffolds was screened using ribosome display for C3/C3b-targeting clones mimicking compstatin pharmacology. APL-1030, a recombinant 64-residue Nanofitin, emerged as the lead candidate. APL-1030 is thermostable, binds C3 (KD, 1.59 nM) and C3b (KD, 1.11 nM), and inhibits complement activation via classical (IC50 = 110.8 nM) and alternative (IC50 = 291.3 nM) pathways in Wieslab assays. Pharmacologic activity (determined by alternative pathway inhibition) was limited to primate species of tested sera. C3b-binding sites of APL-1030 and compstatin were shown to overlap by X-ray crystallography of C3b-bound APL-1030. APL-1030 is a novel, high-affinity inhibitor of primate C3-mediated complement activation developed from natural amino acids on the hyperthermophilic Nanofitin platform. Its properties may support novel drug candidates, enabling bifunctional moieties, gene therapy, and tissue-targeted C3 pharmacologics for diseases with high unmet need.
The Role of 3D Printing in Planning Complex Medical Procedures and Training of Medical Professionals—Cross-Sectional Multispecialty Review

Medicine is a rapidly-evolving discipline, with progress picking up pace with each passing decade. This constant evolution results in the introduction of new tools and methods, which in turn occasionally leads to paradigm shifts across the affected medical fields. The following review attempts to showcase how 3D printing has begun to reshape and improve processes across various medical specialties and where it has the potential to make a significant impact. The current state-of-the-art, as well as real-life clinical applications of 3D printing, are reflected in the perspectives of specialists practicing in the selected disciplines, with a focus on pre-procedural planning, simulation (rehearsal) of non-routine procedures, and on medical education and training. A review of the latest multidisciplinary literature on the subject offers a general summary of the advances enabled by 3D printing. Numerous advantages and applications were found, such as gaining better insight into patient-specific anatomy, better pre-operative planning, mock simulated surgeries, simulation-based training and education, development of surgical guides and other tools, patient-specific implants, bioprinted organs or structures, and counseling of patients. It was evident that pre-procedural planning and rehearsing of unusual or difficult procedures and training of medical professionals in these procedures are extremely useful and transformative.
Mechanisms of Submarine Debris Flow Growth

Submarine debris flows are among the largest types of landslide on planet Earth. They occur under the cloak of the sea so little is known about how they reach such large volumes. Field evidence suggests that the entrainment from the sediment‐rich sea floor enables the growth of submarine debris flows. However, there is a dearth of understanding of the dynamic processes of entrainment. In this study, a new entrainment model is proposed for submarine debris flows with different clay contents. The entrainment model considers the relative contributions from basal grain friction and fluid viscous stresses that drive the entrainment process, and the effects of hydroplaning. To evaluate the new model, a new experimental setup is developed to simulate submarine debris flows, with clay contents from 4% to 12%, overriding and entraining a loose sand bed. The clay content is found to have profound effects on the entrainment dynamics. Flows with high clay contents (i.e., ≥10%) hydroplane, which enhances the mobility of the flow but reduces its entrainment potential. The predicted entrainment depths from the proposed model are consistent with the measured ones from the experiments. The proposed theoretical model and unique experimental evidence can be used as guiding tools to progress toward the inclusion of entrainment in vulnerability assessments of offshore infrastructure.
Visual Communication Design Based on 5G Technology

The progress of science and technology and the rapid development of the Internet have made the visual communication design full of unprecedented yearning and passion for the new scientific and technological civilization. This research mainly discusses the visual communication design under 5G technology. For the fifth generation mobile communication technology (5G), its brand new network architecture design can provide 10 to 20 times higher peak rate, millisecond-level network transmission delay, and 100 billion device-level network connectivity than 4G. It will open up a new era of extensive interconnection of all things and deep human-computer interaction for human society. This paper starts with the relationship between visual communication and various media, so as to prove that the development of mobile media will be inevitable, especially in environment, the visual expression and the innovation in design style. In order to reflect the inner will of the audience in the environment of rapid development of information, this article. It analyzes the changes brought by the development of mobile media to the visual communication design at this stage, predicts the development trend of visual communication, and tries to point out that the development of 5G communication technology is bringing a new round of revolution to the design industry. As a design researcher, it should pay attention to the impact of technological changes on the design field. By exploring suitable design methods, the application of visual communication in mobile media under 5G technology conditions can be better realized. Starting from the background of the evolution and development of media, this paper analyzes the reasons for the rise of 5G technology, as well as the characteristics of 5G technology and its advantages in communication. At the same time, it deeply analyzes the connotation and involved fields of visual communication design and expounds the promotion and influence of the reform of media technology. It focuses on analyzing the development level of 5G technology and the new thinking brought by visual communication design. The article also puts forward the origin of the research. 58.1% of the evaluators were satisfied with the impact of 5G technology on visual communication. Visual design, interaction design, and usability design are all indispensable factors in interface design. When designing, they are not designed in isolation from each other but interact with each other. When carrying out any one of the designs, the design influence of the other two should be combined, and the changes of each one should affect the design of the other two. For example, interaction design and usability issues must be considered when determining the visual presentation of an interface. It can be seen that the design process of the interface is a comprehensive design process. This research helps to advance the development of visual communication design in the future.
Disruption of the Ubiquitin-Proteasome System and Elevated Endoplasmic Reticulum Stress in Epilepsy

The epilepsies are a broad group of conditions characterized by repeated seizures, and together are one of the most common neurological disorders. Additionally, epilepsy is comorbid with many neurological disorders, including lysosomal storage diseases, syndromic intellectual disability, and autism spectrum disorder. Despite the prevalence, treatments are still unsatisfactory: approximately 30% of epileptic patients do not adequately respond to existing therapeutics, which primarily target ion channels. Therefore, new therapeutic approaches are needed. Disturbed proteostasis is an emerging mechanism in epilepsy, with profound effects on neuronal health and function. Proteostasis, the dynamic balance of protein synthesis and degradation, can be directly disrupted by epilepsy-associated mutations in various components of the ubiquitin-proteasome system (UPS), or impairments can be secondary to seizure activity or misfolded proteins. Endoplasmic reticulum (ER) stress can arise from failed proteostasis and result in neuronal death. In light of this, several treatment modalities that modify components of proteostasis have shown promise in the management of neurological disorders. These include chemical chaperones to assist proper folding of proteins, inhibitors of overly active protein degradation, and enhancers of endogenous proteolytic pathways, such as the UPS. This review summarizes recent work on the pathomechanisms of abnormal protein folding and degradation in epilepsy, as well as treatment developments targeting this area.
Intelligent Fault Diagnosis for Bearings of Industrial Robot Joints Under Varying Working Conditions Based on Deep Adversarial Domain Adaptation

Industrial robots are one of the most typical machines in smart manufacturing systems. Their joint bearing faults account for a significant portion of failures. Data-driven bearing fault diagnosis methods, especially deep learning methods, have become a research hotspot due to the development of the industrial Internet of Things and big data. However, the varying working conditions of industrial robots, such as the continuous changing of load and speed, challenge the existing data-driven methods. Although adversarial-based domain adaptive methods are promising for solving this problem, they still face an equilibrium issue in the model training process. Therefore, a novel deep perceptual adversarial domain adaptive (DPADA) method is proposed for fault diagnosis of industrial robot bearings under varying conditions in this article. Here, a novel perceptual loss is proposed to force the target domain and the source domain to have the same distribution, which helps to improve the stability of adversarial training. Correspondingly, a timestamp mapping-based vibration signal screening method is proposed to improve data preprocessing efficiency for fault diagnosis of industrial robots. Extensive experimental results show that the accuracy of DPADA is superior to convolutional neural network (CNN) and conditional domain-adversarial network (CDAN)-based methods. A comparison is further performed on transfer tasks in three classical transfer scenes of industrial robots.
Management Response Strategies to a Negative Online Review: Influence on Potential Guests’ Trust

Purpose – The paper aims to identify the main hotel management response strategies to a negative online review and examine their influence on the trust of potential guests reading reviews in usergenerated media. Design – Five response strategies that emerged from the literature were empirically tested: personalization, empathy, confession, denial, and excuse. A mixed-method was applied, and the research was conducted in two phases using a qualitative method with a scenario-based approach and a quantitative research using the PLS-SEM method. Methodology/Approach – A focus group was used to provide a basis for the survey. The survey included one real negative hotel review and five hypothetical responses written according to the five observed strategies. Each response was followed by a set of statements examining the level of trust. A total of 435 questionnaires completed. The influence of each strategy on trust was tested individually. Findings – The results show that personalization, empathy, and confession as response strategies positively influence the trust of potential guests, whereas denial and excuse as response strategies have a negative effect on trust. Originality of the research – The research systematizes previous literature and identifies the main response strategies to a negative online review. It empirically tests all five strategies so that they can be observed in relation to each other. Moreover, this research includes the concept of trust as a dependent variable. The results can help scholars to build further models and hotel managers to understand how they should respond to negative online reviews.
Research Methodology: For Beginners

In this paper various components of research are briefly discussed. The topics cover a part of the research methodology paper of Doctor of Philosophy (Ph.D.) course. The manuscript is intended for students and research scholars. Various stages of research are discussed in detail and restricted up to various stages of research. Special care has been taken to motivate the young researchers to take up challenging problems.
Observer-based fixed-time control for nonlinear systems with enhanced nonsingular fast terminal sliding mode

In this paper, we develop a novel observer-based fixed-time control for a class of uncertain nonlinear systems. First, a fast terminal sliding mode disturbance observer is constructed, which can guarantee accurate estimation of the lumped disturbance in fixed time. Next, using a new fixed-time stable system, a novel enhanced nonsingular fast terminal sliding mode manifold with bounded convergence time independently of the initial states is presented to enhance system convergence rate. Subsequently, by using the presented fast terminal sliding mode disturbance observer and enhanced nonsingular fast terminal sliding mode manifold , the observer-based fixed-time control scheme is developed, which can achieve system stabilization within fixed time and offer global fast convergence property. The fixed-time convergence of the system states under the proposed control approach is analyzed by utilizing the Lyapunov stability theory. Finally, corresponding simulation results are provided to confirm the feasibility and superiority of the new control strategy.
Prediction method of coal and gas outburst by analytic hierarchy process and fuzzy comprehensive evaluation

The prediction of coal and gas outburst was studied by analytic hierarchy process(AHP)and fuzzy comprehensive evaluation.In the prediction method,AHP was applied to confirm the weights of coal and gas outburst factors,the judgment matrix of each factor was constructed by membership functions,and the prediction model of coal and gas outburst was established by the fuzzy comprehensive evaluation method.The prediction method was applied in risk type areas to forecast the coal and gas outburst quantitative intensity and the risk grade was divided in Pingdingshan typical mining area.The results show that the hierarchy process and fuzzy comprehensive evaluation method was available for forecasting the coal and gas outburst intensity.