Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating barrier island characteristics and piping plover (Charadrius melodus) habitat availability along the U.S. Atlantic Coast—Geospatial approaches and methodology

Policy makers, individuals from government agencies, and natural resource managers face increasing demands to manage coastal areas in a way that meets economic, social, and ecological needs as sea levels rise. Scientific knowledge of how coastal processes drive beach and barrier island changes and how those changes affect habitat use can support decision makers as they balance sometimes conflicting human and ecological needs. However, uncertainties in the knowledge of the cumulative results of coastal processes make it challenging to forecast specific changes for a particular location and time. The U.S. Geological Survey is developing tools for identifying and forecasting barrier island characteristics as well as suitable coastal habitats for species of concern (such as piping plovers, Charadrius melodus) given ongoing sea-level rise. As part of this effort, we use three Bayesian networks to calculate probabilities of shoreline change rates, changes in barrier island biogeomorphic characteristics, and piping plover habitat availability, which together forecast the effects of different sea-level-rise rates and storm regimes. This report details the methodology used to derive geospatial biogeomorphic datasets that are used as inputs for two of these Bayesian networks, which forecast barrier island geomorphology and piping plover habitat availability at sites along the U.S. Atlantic coast (Maine to North Carolina). Further information about the project, including specific study sites, can be found at https://woodshole.er. usgs.gov/project-pages/ beach-dependent-shorebirds/.
Creation and development of an AI teaching assistant

During this project, an end-to-end solution has been provided, creating and developing a Chatbot that, using Artificial Intelligence, is able to solve doubts that students may have within the domain of a university subject. To do so, Advanced Statistics Techniques such as Machine Learning Classification Methods or Text Mining have been used in order to make a Natural Language Processing system that understands a question and provides either a pre-built or a generative answer, based on the documentation of the subject. This system has then been integrated into Telegram, which serves as a front-end application. Several functionalities have been incorporated, such as interactive answers, user registration, administrator rights, multiple language selection or database connec- tions handling, among others.
Asymmetric Relationship Between Government Revenues and Expenditures in a Developing Economy: Evidence from a Non-linear Model

Abstract Understanding the revenue–expenditure nexus is the core essence of this research in the Pakistani context. This research examines the non-linear relationship between government revenues and government expenditures during 1972–2014. The recently developed non-linear co-integration technique has been used along with the symmetry test. The result shows that the revenues and expenditures have co-integration and provide the evidence in favour of fiscal synchronization hypothesis in the budgetary process. Moreover, the finding also reveals that the relationship between these two fiscal elements is asymmetric and negative changes in revenues and expenditures have a greater impact than the positive ones. Furthermore, another important aspect that was revealed during the study was that the negative shocks in the revenues will lead towards the drastically large increase in the expenditure.
Technological Innovation and Its Impact on Public Sector Efficiency and Performance: Aerial Imagery in Property Tax Assessment Administration

ABSTRACT Technological innovations can help public organizations deliver higher quality public goods and services at lower average costs. While a considerable literature exploring the determinants of technology adoption and diffusion exists, much less is known on whether technology innovations improve public sector outputs. This study investigates the impact of high-resolution, oblique aerial imagery, an increasingly common technology used by local governments in the US, on the inspection efficiency and quality of property assessment administration. Aerial imagery is often argued to be a low-cost substitute to in-person inspections of property. Drawing on data from 2013 through 2017 for property assessing districts in Texas, aerial imagery use is found to improve the rate at which properties are inspected as well as improve the quality of assessments. The results further provide evidence that investments in aerial imagery are best justified on budgetary grounds rather than as a means to improve organizational performance.
An urban big data-based air quality index prediction: A case study of routes planning for outdoor activities in Beijing

Urban big data include various types of datasets, such as air quality data, meteorological data, and weather forecast data. Air quality index is broadly used in many countries as an indicator to measure the air pollution status. This indicator has a great impact on outdoor activities of urban residents, such as long-distance cycling, running, jogging, and walking. However, for routes planning for outdoor activities, there is still a lack of comprehensive consideration of air quality. In this paper, an air quality index prediction model (namely airQP-DNN) and its application are proposed to address the issue. This paper primarily consists of two components. The first component is to predict the future air quality index based on a deep neural network, using historical air quality datasets, current meteorological datasets, and weather forecasting datasets. The second component refers to a case study of outdoor activities routes planning in Beijing, which can help plan the routes for outdoor activities based on the airQP-DNN model, and allow users to enter the origin and destination of the route for the optimized path with the minimum accumulated air quality index. The air quality monitoring datasets of Beijing and surrounding cities from April 2014 to April 2015 (over 758,000 records) are used to verify the proposed airQP-DNN model. The experimental results explicitly demonstrate that our proposed model outperforms other commonly used methods in terms of prediction accuracy, including autoregressive integrated moving average model, gradient boosted decision tree, and long short-term memory. Based on the airQP-DNN model, the case study of outdoor activities routes planning is implemented. When the origin and destination are specified, the optimized paths with the minimum accumulated air quality index would be provided, instead of the standard static Dijkstra shortest path. In addition, a Web-GIS-based prototype has also been successfully developed to support the implementation of our proposed model in this research. The success of our study not only demonstrates the value of the proposed airQP-DNN model, but also shows the potential of our model in other possible extended applications.
A Method for Reducing Cogging Torque of Integrated Propulsion Motor

How to reduce the cogging torque of the integrated propeller motor is an important means to improve its noise performance because cogging torque is one of the key factors causing torque ripple. We proposed a method to reduce the cogging torque by optimizing the size of the Halbach array’s auxiliary pole. First, an analytical model for the airgap magnetic field of Halbach array based on different dimensions (including the circumference ratio and the radial thickness) of the auxiliary pole is given. Then the finite element method is used to verify the analytical model. On the basis, we calculated the cogging torque of different size of auxiliary poles as sample data by combining different circumference ratio and radial thickness. Furthermore, using the two-variable single-objective neural network genetic optimization algorithm based on Backpropagation (BP), we obtain the optimal size of the auxiliary pole. Finally, comparing the motor cogging torque and torque ripple before and after optimization indicated that the cogging torque and torque ripple are effectively reduced after optimizing the size of the auxiliary pole.
A Randomized Controlled Trial of Metacognitive Therapy for Depression: Analysis of 1-Year Follow-Up

This paper reports the 1-year follow-up results from a randomized controlled trial (RCT), which examined the efficacy of metacognitive therapy (MCT) for unipolar depression compared to a waiting condition. Thirty-nine patients with major depression were offered MCT and were divided into two conditions; immediate MCT with 10 weekly sessions or a waiting period that had a 10-week delayed MCT start. Two participants dropped out during the waiting condition. Thirty-four patients participated in the follow-up assessment. Based on the intent-to-treat sample and all patients, 67% were classified as recovered, 13% improved, and 20% were unchanged at 1-year follow-up. For the completers sample 73% recovered, 12% improved, and 15% were unchanged. Five of the 31 patients (13%) that were in remission at post-treatment experienced relapse at 1-year follow-up. Within-group effect sizes were large for reductions in symptoms of depression (d = 2.09) and anxiety (d = 1.16) at 1-year. Treatment response was associated with reductions in rumination, worry, and metacognitive beliefs as predicted by the metacognitive model, but reductions in metacognitions independently predicted reductions in depression scores from pre-treatment to 1-year follow-up. The results suggest that treatment gains are stable at 1-year follow-up. The study sets the stage for future research, which should evaluate MCT over a longer term and compare it with active treatments using suitably powered RCTs.
KOLABORASI ANTARA KEPALA SEKOLAH, GURU, DAN SISWA DALAM MENCIPTAKAN SISTEM PENDIDIKAN YANG BERKUALITAS

The creation of education in accordance with the mandate of the law is a matter that must be built with the hard work and cooperation of all the important elements in Indonesia's national education system today. A good education system is created when the school is led by a competent and creative principal, as well as those who are able to foster good relationships with teachers at the school. In addition, teachers with appropriate personalities and competencies will support the creation of a good learning environment and encourage their students to actively perform and make them personal. This study aims to provide clear information about the importance of collaboration among elements of educational support. The study used a mixed case study methodology, an open questionnaire, and a descriptive statistical analysis of 173 subjects consisting of two principals, 43 teachers, and 130 students. The results of case studies explain how the role of principals is crucial in shaping the character and performance of schools, especially with regard to their leadership style and creativity. While the analysis of open questionnaires categorizes that students expect to become dream teachers are those who are able to become partners, those who have the competence, and those who are experienced. The role of the principal, the presence of a qualified teacher, and the similarity of students' perceptions to their school will result in a collaboration that is mutually supportive of one another.
Don’t hurt my outgroup friend: A multifaceted form of imagined contact promotes intentions to counteract bullying

A growing body of research has shown that imagined intergroup contact can improve outgroup attitudes. The aim of the present study was to examine the effectiveness of a multifaceted form of imagined contact in counteracting bullying in school children, and additionally to test the underlying processes of this effect. Two hundred and fifteen Italian elementary school children took part in a 3-week intervention, where they were asked to imagine a scenario in which they become friends with an unknown disabled child, interact in various social settings, and react to forms of discrimination toward the newly acquired friend. After each session, they discussed collectively what they had imagined. The dependent measures were administered 1 week after the last session. Results revealed that inclusion of an outgroup member in the self mediated the effect of imagined contact on intentions to counteract social exclusion and bullying of disabled children, as well as helping intentions. Imagined contact also promoted greater willingness for outgroup contact via more positive outgroup attitudes and empathy. Our findings are important in delineating new forms of imagined contact, and understanding ways to promote behaviors that defend victims of social exclusion and bullying in school environments.
Non-Intrusive Computing

Pervasive computing is an important trend today. It concerns devices and services in a smart space that interact with users in a simple, natural, and harmonious way. Many problems in this domain have been studied from different perspectives in various projects. However, one important characteristic of pervasive computing, which is how to make it non-intrusive so that users can focus on their tasks, has received little formal attention. Nowadays, many computing entities including smart devices, and software components, are involved in our daily lives, and users need to deal with them as well as with other people. Besides, people are easy to reach with multiple devices. We believe there should be a systematic way to help users avoid intrusive ones. We propose a model for posing and answering two questions: will an interaction intrude on its receiver if delivered, and given that the interaction is deliverable, how can it be delivered effectively and not too overtly? With this model, the intrusion problem is analyzed and the essential factors are identified. A quantitative approach is used, so that factors have quantitative values for comparison and computation. We also apply context to refine them in order to achieve better results. We then illustrate how to materialize the model and build a system whose design is inspired by the Jabber framework that includes a collection of standards, technologies, and projects for instant messaging. The discussion is at a general level that does not depend on Jabber. However, by choosing Jabber in implementation, we reuse existing software and technologies, and benefit from Jabber/XMPP standardization, its low entry barrier for application developers, and its rich community support. The main contributions of our work are two-fold. First, we propose a model for intrusiveness in pervasive computing. Second, we address the problem at the system level by designing and realizing it. We also make use of standardized instant-messaging technologies, more precisely Jabber, in the system instantiation to reuse existing software, making the system more flexible and extensible.
MODERN SKILLS AND CONVERGENT ENVIRONMENT – SWOT ANALYSIS, TRENDS AND CHALLENGES IN VOCATIONAL EDUCATION AND TRAINING. A BULGARIAN EXPERIENCE

The paper considers the alternative to the modern vocational education and training, continuing throughout life. The aim of the study is to use SWOT analysis as one of the most effective tools for the modern management of organizations and processes. It is effective for systematically analyzing environmental management; for strategic results-oriented planning; for organizational balance and value added; to identify external and internal factors, trends, threats and opportunities for full development of the system of vocational continuing education in Bulgaria, especially in the field of cultural and creative industries. The main research tasks include terminological analysis and literature review on topical issues; to study the situation with the SWOT analysis tools; issuing recommendations for future development. In this regard, the research hypothesis argues that the SWOT analysis can make a qualitative assessment and achieve better planning and market efficiency of the system of continuing vocational education and training, as well as effective communication with all actors in this fast-moving, modern educational service for the benefit of the business and the public sector. A methodology related to the SWOT analysis tools is applied; content analysis of concepts and official documents on thematic issues; analytical bibliographic study; methods of analysis and synthesis; monitoring methods. As a result of our research, the barriers and opportunities for developing a sustainable system of continuing vocational education and training in the country are established. Summarized recommendations and conclusions are provided.
Relationships Among Helicopter Parenting, Self-Efficacy, and Academic Outcome in American and South Korean College Students

Although numerous studies have examined the role of helicopter parenting in child outcomes, there is little empirical cross-cultural research on the academic outcomes of helicopter parenting for late adolescents. This study investigated the differences in the association between mothers’ and fathers’ helicopter parenting and college students’ (N = 343) academic outcomes across American and South Korean contexts, examining the role of self-efficacy as a mediator. Multigroup structural equation modeling analyses showed that South Korean fathers’ helicoptering has a negative relation with students’ academic outcomes. Higher levels of fathers’ parenting were directly related to students’ lower academic outcomes in the Korean context. However, comparable results were not observed with South Korean mothers or American parents. In addition, mothers’ helicopter parenting was not related to either self-efficacy or academic outcomes across the two countries. Although there are cultural differences in helicopter parenting practices, there appear to be potentially more cultural similarities across the two cultures than was conjectured.
Energy Efficient Computing on Multi-core Processors: Vectorization and Compression Techniques

Over the past few years, energy consumption has become the main limiting factor for computing in general. This has led CPU vendors to aggressively promote parallel computing using multiple cores without significantly increasing the thermal design power of the processor. However, achieving maximum performance and energy efficiency from the available resources on the multi-core and many-core platforms mandates efficient exploitation of the existing and emerging architectural features at the application level. This thesis presents the study of some of the existing and emerging technologies in order to identify the potential of exploiting these technologies in achieving high performance and energy efficiency for a set of Smart Grid applications on Intel multi-core and many-core platforms. The first part of this thesis explores the energy efficiency impact of different multi-core programming techniques for a selected set of benchmarks and smart grid applications on Intel SandyBridge and Haswell multi-core processors. These techniques include different parallelism techniques such as thread-level parallelism using OpenMP, task-based parallelism using OmpSs, data parallelism using SIMD (Single Instruction Multiple Data) instruction sets, code optimizations and use of different existing optimized math libraries. In our initial case studies, SIMD vectorization is proven very effective in providing both high performance and energy efficiency. Though the SIMD vectorization is proven very effective, it can also exert pressure on the available memory bandwidth for some applications like Powel Time-Series Kernel, causing under-utilization of the computing resources and thus energy inefficient executions. In the second part of this research, we investigate the opportunities of improving the performance of SIMD vectorization for memory-bound applications using SIMD data compression, SIMD software prefetching, SIMD shuffling, code-blocking and other code transformation techniques. The key idea is to reduce the
Factors that Sustain Health and Safety Management Practices in the Food Industry

Due to the significant change in business organizations, scholarly interest has diverted from studying the determinants of financial performance to understanding the environmental activities, sustainability practices, and health and safety management practices. Despite the extensive literature, it is yet to understand either internal or external factors that improve health and safety management practices in SMEs. This research examines the influence of the internal factors—intellectual capital, information technology capabilities (ITC), and entrepreneurial orientation, and the external capabilities—government financial support, institutional pressure, and managerial networking on six health and safety management practices: management commitment, staff training, worker involvement, safety communication and feedback, safety rules and procedures, and safety promotion policies. We researched 410 Pakistani SMEs from the food business industry. The results indicate that intellectual capital significantly improves management commitment, safety communication and feedback, and safety rules and produces; ITC significantly improves management commitment and safety communication and feedback; and entrepreneurial orientation significantly facilitates safety training and worker involvement only. In the external capabilities, government financial support has a significant influence on management commitment, worker involvement, safety rules and policies, and safety promotion policies. Institutional pressure has a significant influence on management commitment, safety training, safety communication, and feedback and safety promotion policies. Managerial networking significantly influences safety training, worker involvement, safety rules and procedures, and safety promotion policies of SMEs. Focusing only on the food industry is the major limitation of this research, this study recommends SMEs to give sufficient attention to their internal and external factors to enhance health and safety management practices. Further implications are discussed.
Development of the Parentified Child Scale- Adult Version: A Reliability and Validity Study

Bu calismanin amaci yetiskin bireyler icin ebeveynlestirilme duzeylerini gecerli ve guvenilir bir sekilde olcebilecek bir olcme araci gelistirmektir. Arastirmaya iki farkli calisma grubu olarak toplam 705 kisi (510 kadin, 195 erkek) katilmistir. Benzer olcek gecerliligi icin Jurkovic, Thirkield ve Morel (2001) tarafindan gelistirilen, Karagobek (2014) tarafindan Turkce uyarlamasi yapilan Filial Sorumluluk Olcegi – Yetiskin Versiyonu kullanilmistir. ECO-Y’nin faktor yapisini belirlemek amaciyla acimlayici ve dogrulayici faktor analizleri yapilmis ve bulgular isiginda olcegin iki alt olcekten olustugu, ilk alt olcegin dort faktorlu, ikinci alt olcegin tek faktorlu bir yapi oldugu bulunmustur. ECO-Y’nin Cronbach alpha ic tutarlik katsayisi . 88 olarak hesaplanmistir. Madde toplam korelasyon katsayilari ise . 37 ile . 71 arasinda bulunmustur. Olcegin ilk alt olceginin dogrulayici faktor analizi sonucunda 22 maddenin dort faktorlu oldugu sonucu elde edilmistir ve ki-kare uyum degerinin ( c 2=506.42, sd=203, p=.00) anlamli oldugu gorulmustur. Modelin uyumuna iliskin c 2 /sd sonucu 2.49 olarak tespit edilmistir. Ayrica RMSEA= . 073, CFI=. 95, NFI=. 92, NNFI=. 94, IFI=. 95, RFI=. 91 ve GFI=. 86 olarak hesaplanmistir. Test tekrar test guvenirlik katsayi . 91 bulunmustur. ECO-Y’nin, FSO ile arasindaki iliskideki korelasyon katsayisi . 81 olarak analiz edilmistir. Yapilan gecerlik ve guvenirlik calismalari sonucunda, ECO-Y yeterli degerlere sahip gecerli ve guvenilir bir olcme araci oldugu gorulmustur.