Miracle-dz/UniFAR-FTUs huggingface dataset:
Examination of military personnel’s changed psychological states during long-term deployment in a war zone

Título: Examen de los cambios en el estado psicológico de los militares durante el despliegue de larga duración en una zona militar. Resumen: Una de las formas más eficaces para prevenir las consecuencias negativas del despliegue en la zona militar para la salud mental de los militares es diagnosticar su estado psicológico. En el presente estudio se determinan las particularidades de los cambios en el estado psicológico de los militares (n = 192) durante el despliegue de seis meses en la zona militar en el este de Ucrania. Los resultados obtenidos confirmaron ambas hipótesis formuladas: en cuanto a la posibilidad de determinar, sobre la base del diagnóstico del estado psicológico, el plazo recomendado para el despliegue de los militares en la línea de demarcación en el este de Ucrania, que es de tres meses. Así como también sobre las posibles diferencias significativas en la dinámica del estado psicológico de los militares que tienen y no tienen experiencia en el despliegue. Asimismo, se argumenta la necesidad de monitorear el estado psicológico de los militares durante el despliegue con el propósito de prevenir oportunamente las consecuencias negativas para su salud mental y para la ejecución exitosa de las tareas de la subunidad militar. Palabras clave: Militares. Factores estresantes de combate. Despliegue. Estado psicológico. Salud psíquica. Abstract: Examining military personnel’s psychological states is an effective way to prevent negative mental health consequences during their deployment in a war zone. The present study identifies changes in the psychological states of military personnel (n = 192) during a 6-month deployment in a war zone in eastern Ukraine. The results confirmed both of our proposed hypotheses. First, with regard to time limits on military personnel’s deployment on the front lines in eastern Ukraine on the basis of examined psychological states, the estimated recommended deployment duration was three months. Second, we found significant differences in the dynamics of the psychological states of service members with versus without previous deployment experience. The results also substantiate that military personnel’s psychological states should be monitored during deployment in order to prevent negative mental health consequences and to ensure that military units successfully accomplish their tasks.
DB101434 2457..2464

RESEARCH DESIGN AND METHODS—EL expression in placental tissues from pregnancies complicated by obesity, GDM, or obesity combined with GDM (obese-GDM) was analyzed by quantitative RT-PCR. Moreover, primary placental cells were isolated and treated with insulin, glucose, leptin, or tumor necrosis factor (TNF)-a, and EL expression was measured. Inhibitors of nuclear factor (NF)-kB or mitogen-activated protein kinase (MAPK) signaling were used to detect potential pathways of EL regulation in primary placental endothelial cells (ECs).
TRACKING OF OBJECTS IN MOTION

: Object tracking manage non-stationary objects that change after some time. Object tracking in computer vision identified with the undertaking of tracking singular mobile objects precisely starting with one edge then onto the next in a picture grouping or in video. This paper gives a relative audit of late tracking techniques, specifically as for their capacity of tracking objects under different issues. In this papers scientists displayed diverse technique for object tracking, for example, Parameter in object tracking, Particle-Filter Based Multi-Object Tracker, Multi-Track Linking and Long-Term Online Multiface Tracking Using Particle Filter and Hidden Markov Model (
Heuristic solutions for interval-valued games

When we design the payoff matrix of a game on the basis of the available information, then rarely the information is free from impreciseness, and as a result, the payoffs of the payoff matrix have a certain amount of ambiguity associated with them. In this work, we have developed a heuristic technique to solve two persons m × n zero-sum games ( m > 2 ,n > 2) , with interval-valued payoffs and interval-valued objectives. Thus the game has been formulated by representing the impreciseness of the payoffs with interval numbers. To solve the game, a real coded genetic algorithm with interval fitness function, tournament selection, uniform crossover, and uniform mutation has been developed. Finally, our proposed technique has been demonstrated with a few examples and sensitivity analyses with respect to the genetic algorithm parameters have been done graphically to study the stability of our algorithm.
SURVEY ON SECURE DATA ACCESS CONTROL SCHEMES IN CLOUD COMPUTING

: Today the presence of cloud computing technology has become essential for many organizations, businesses enterprises and personal usage for sharing resources, flexible data storage, reduced maintenance cost, anytime anywhere access and availability of applications and many more. Managing and maintaining data has become a tedious operation for the data owners. Hence data owners prefer to outsource their data to cloud. Despite of having many benefits, issues related to data security, data privacy and data control are haunting the data owners. Access control mechanism provides the data owner to control and regulate access of data users which achieves the goal of safeguarding data or sensitive information. Access control method is the ultimate way to ensure access to authorized data users only and have complete control over the data. This paper reviews different secure data access control methodologies and study the functionality of the schemes that helps to build a secure, scalable, flexible, efficient and dynamic data access control standard in cloud computing.
A model of consensus reaching process for Group Decision Problems with multi-granular linguistic information

In the literature, group decision making problems have been solved by carrying out two processes: a consensus process and a selection process. In the consensus one, decision makers or experts try to achieve an agreement among their opinions in order to solve the problem. In the selection process, the experts choose the solution set with the best alternative/s to solve the problem. The consensus is a process composed of several discussion rounds where the experts provide and change their opinions. This process is guided by the ﬁgure of a human moderator that helps to the experts to make their opinion closer. In this paper we propose a model for the consensus reaching process in group decision making problems deﬁned in a multi-granular linguistic context. The proposed model measures the agreement and deﬁnes a set of rules which will be used by the moderator to suggest changes to the experts in order to improve the agreement in the next consensus round.
Endogenous growth with environmental pollution and depreciation of public : a theoretical

In this note, we develop a model of endogenous growth in which public infrastructure maintenance expenditure and abatement expenditure play special role to explain economic growth. We consider industrial production as the source of environmental pollution; and treat public capital depreciation as endogenous, being dependent upon environmental quality and maintenance expenditure. We find out the properties of the steady-state equilibrium growth path; and then analyze the properties of growth rate maximizing fiscal policy along this path. Abstract: In this note, we develop a model of endogenous growth in which public infrastructure maintenance expenditure and abatement expenditure play special role to explain economic growth. We consider industrial production as the source of environmental pollution; and treat public capital depreciation as endogenous, being dependent upon environmental quality and maintenance expenditure. We find out the properties of the steady-state equilibrium growth path; and then analyze the properties of growth rate maximizing fiscal policy along this path.
Validation of the Spanish version of the Childhood Executive Functioning Inventory (CHEXI) in 4-5 year-old children

Background: The Childhood Executive Functioning Inventory (CHEXI) was designed to identify EF deficits in daily life contexts. The aim of the present study was to validate the Spanish version of the CHEXI in 4-5-year-old children. Method: Parents’ ratings of the CHEXI and laboratory tests of EF were investigated in two large samples of 445 children aged 4 years (196 girls, 249 boys) and 459 children aged 5 years (208 girls, 251 boys). CHEXI ratings were collected again after one-year. Results: The two-factor structure of the CHEXI (i.e., Working Memory and Inhibition) was replicated, showing high internal consistency and temporal stability. The 4-year-olds were reported to have higher EF deficits than 5-year-olds have. Boys were rated as having higher EF deficits than girls were. However, gender differences were not significant contrasting performance on EF tasks. Finally, associations between CHEXI ratings and EF tests were weak, suggesting that EF tests and EF ratings capture different aspects of EF. Conclusions: The Spanish CHEXI provides a suitable instrument to assess EF in 4-5-year-old children. Contexto: El Childhood Executive Functioning Inventory (CHEXI) se diseñó para detectar déficit de Funciones Ejecutivas (FE) en contextos de la vida diaria. El propósito del presente estudio era validar la versión española del CHEXI para niños de 4 y 5 años. Método: Se obtuvieron las valoraciones de los padres y las puntuaciones en test de laboratorio en una muestra de 445 niños de 4 años (196 niñas, 249niños) y otra de 459 niños de 5 años (208 niñas, 251 niños). Un año más tarde se volvieron a recoger las valoraciones de los padres en CHEXI. Resultados: Se replicó la estructura de dos factores de CHEXI (Memoria de Trabajo e Inhibición), obteniendo una alta consistencia interna y estabilidad temporal. Los niños de 4 años eran valorados con mayor déficit en FE que los niños de 5 años. Los niños alcanzaban puntuaciones más elevadas de déficit de FE. Sin embargo, no aparecieron diferencias significativas de género en las pruebas conductuales. Finalmente, se encontró una baja asociación entre las valoraciones de CHEXI y las puntuaciones de las pruebas conductuales. Este resultado sugiere que los inventarios y las medidas conductuales evalúan diferentes aspectos de las FE. Conclusiones: La versión española de CHEXI ofrece un instrumento válido para evaluar las FE en niños de 4 y 5 años.
A Study on the Privatization of School Facilities Maintenance

School facilities maintenance is concerned about providing clean and safe environments for children. It is also about creating a physical setting that is appropriate and adequate for learning. But many of the school buildings in Korea have been maintained and operated by each school manger or pubic officers in the Educational Department. This system could not extend the life of building components, keep equipment functioning as designed or sustain a sage and healthful environment because of its non-professionality and the dual fiscal system. In order to improve such problems, it is proposed to privatize the maintenance of school building. It is sure that the new way to outsource services reduce costs and provide high quality services. Competitive contracting with the private sector can provide schools with expertise, flexibility and cost efficiencies as well as help school administrators focusing on educating the children. This study explores the maintaining status of existing schools, analyses the cases about BTL schools and the foreign country's policies and surveys the outsourcing cases of Kyungki-do schools. Finally it proposes more appropriate plans for privatizing the maintenance way of school building in Korea.
Comparative Efficiency of Solar Panel by Utilize DC Water Pump and DC Hybrid Cooling System

The purpose of this paper is discussed about comparative efficiency of solar panel by utilize DC water pump and DC hybrid cooling system. Ambient temperature and solar irradiance are played main role of the efficiency of PV module. When temperature of PV module increase, the efficiency of PV module will decreased and vice versa. When solar irradiance increase, output current and output power will increase with linear and output voltage will increase with marginal and vice versa. A solution is provided to solve problem of low efficiency of PV module which is DC cooling system. DC brushless fan and water pump with inlet/outlet manifold were designed for actively cool the PV module to improve efficiency of PV cells. The PV module with DC water pump cooling system increase 3.52 %, 36.27 %, 38.98 % in term of output voltage, output current, and output power respectively. It decrease 6.36 °C compare than to PV module without DC water pump cooling system. While PV module with DC hybrid cooling system increase 4.99 %, 39.90 %, 42.65 % in term of output voltage, output current, and output power respectively. It decrease 6.79 °C compare to PV module without DC water pump cooling system. The higher efficiency of PV module, the payback period of the system can be shorted and the lifespan of PV module can be longer.
AN APPROACH FOR SENTIMENT ANALYSIS AND OPINION MINING USING SUPERVISED CLASSIFICATION ALGORITHM

: An important part of our information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges arise as people now can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden eruption of activity in the area of opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object. This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. Our focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. We include material on summarization of evaluative text and on broader issues regarding privacy, manipulation, and economic impact that the development of opinion-oriented information-access services gives rise to. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided.
AN EFFICIENT APPROACH FOR SENTIMENT ANALYSIS OF HEALTH POSTS

: The Social Networks/Media and various Internet-based Communities/Forums are emerged as the platform for people to share information, regarding their daily lives and their experiences, in this era of knowledge and technology. Such user generated information may contain useful/valuable information as well as misinformation. In this paper, we are proposing a scheme to collect the real time health posts posted by the patients, physicians which includes their views and experiences on the medicines and diseases, on various forums or websites. We then come out with some conclusions, by summarizing the collected information, that will be helpful for the patient community and the medical community. We further classify the patients into different classes based on their posts. We also perform knowledge discovery to discover useful patterns to make our work more accurate using Association rule mining. We also shall propose a scheme to correct the errors and spelling mistakes in the user posts.
TunePad Playbooks: Designing Computational Notebooks for Creative Music Coding

This paper describes the design of an online learning platform that empowers musical creation and performance with Python code. For this platform we have developed an innovative computational notebook paradigm that we call TunePad playbooks. While playbooks borrow ideas from popular computational notebooks like Jupyter, we have designed them from the ground up to support creative musical expression including live performances. After discussing our design principles and features, we share findings from a series of artifact-centered interviews conducted with experienced TunePad users. Our results show how systems like ours might flexibly support a variety of creative workflows, while suggesting opportunities for future work in this area.
BCI (BRAIN COMPUTER INTERFACE) TO PLAY VIDEO GAME USING EEG (ELECTROENCEPHALOGRAPHY) SIGNAL

-BCI (Brain computer interface) using to Brain EEG (electroencephalography) video game we can use maximum 80% human ability to play video game. [4] The obtained using a specially designed electrode cap and equipment, and sent to a PC that processes it in real time. [2] The signal was then mapped onto two control signals and sent through gaming device. Brain signals taken from brain using EEG cap made of silver plated electrodes. [3] After it, Amplifier (where common-mode noise is measured using a right-leg driver attached to the patient's mastoid or ear lobe), along with an operational amplifier and some filters (to The overall structure of the project consists of an amplifier pipeline consisting of a differential instrumentation remove DC offsets, 60 Hz power-line noise, and other artifacts). From there, the signal passes to the microcontroller, where it is digitized via an ADC. Next, it is send over an isolated US B UART connection to a PC via an FTDI chip. [4] The PC then performs signal processing and is able to output the results to the user, creating a neuron feedback loop which allows the user to control the PC using their brain waves.
A REVIEW ON COVID-19 RELATED RESEARCH IN LEADING INFORMATION SYSTEMS JOURNALS

To identify the key challenges, issues and opportunities affecting individuals, organizations, and society on coping with COVID-19, we reviewed extant research related to the COVID-19 pandemic in the leading information systems journals. Six major research themes and representative literature for each theme are identified by content analysis. The six major research themes include digital transformation, data visualization and artificial intelligence, infodemic and cybersecurity, IT governance, digital divide, and IS research direction in the post-pandemic period. Moreover, we discussed the challenges, current research, and opportunities related to each of the themes. The review provides a snapshot of IS literature on the COVID-19 pandemic and can enable scholars to evaluate possible opportunities for conducting research and development activities related to the pandemic.
VOLTAGE STABILITY ANALYSIS OF POWER SYSTEM USING CONTINUATION POWER FLOW METHOD

Growing rate of consumption of power in power systems, power plants and transmission lines usually works on the edge of stability, and it is possible that with a little increase in load or occurrence of a contingency, the system goes out of control. In such systems, maximum loading condition is almost determined in such a way that static stability of the system will be maintained not only in normal operation of the system but also in emergency conditions and in case of the occurrence of a contingency for at least one of the components of the system. In this paper, using a continuation power flow method and using change in load parameter, we analyze maximum loading of the system. We performed simulations on IEEE 14-bus test systems. Power system analysis toolbox (PSAT) is used as simulation environment for analyzing voltage stability performance of sample 14 bus system. Continuation power flow method is used as theoretical base for carrying out voltage stability performance analysis of the 14 bus system. It is used to obtain P-V curve of power system. In P-V curve Continuation power flow starting with initial operating point and increasing load to the maximum loading point.
A Multi-granular Linguistic Based-Content Recommender System Model

Recommender systems have recently emerged in the area of e-commerce to assist consumers in their search processes by means of recommendations that arise from the information provided by different sources, due to the fact, they must deal with a vast quantity of information that is stored in huge data bases of different e-shops. We focus in based-content recommender systems that deal with information provided by customers regarding the features they wish, in order to reach the most suitable item according to their preferences. Most of the current recommender systems force their customers to provide the information in a numerical scale in spite of it is usually incomplete, vague and imprecise. We propose a multi-granular linguistic based-content recommender system model that manage the uncertainty of the information using linguistic terms and allow each source to use their own linguistic term set to express their preferences according to their knowledge.
INFORMATION RETRIEVAL FROM UNSTRUCTURED DATA

: the Internet has an enormous amount of data in the unstructured form, unstructured data most often is written in natural languages like English or Hindi and does not have a predefined data model, and it can’t be mapped directly to relational databases. This data exists in form of emails, Google searches, eBooks, social media content, blogs etc., in short, it’s the written word and is everywhere in our lives. Unstructured data also exists in form of audio, images, and video in addition to the text format, the current best approach to make all this non text-data searchable is to add appropriate keywords, labels, and text descriptions or convert audio to text using speech recognition so that it could be used as text, so it does not matter how much structure is added to this unstructured data, it all comes back to text for us to understand our content. Once we have unstructured data in text form, the next challenge is to extract high-quality (relevant, novel, and interesting) and useful information from it. One of the foremost challenges in retrieving information from the unstructured text written in natural languages is to transform it into structured attribute-based instances, for this purpose various natural language processing techniques such as encoding/normalization, tokenization, removing whitespaces/stop-words, parts of speech tagging, lemmatization or stemming, named entity recognition and sentence detection are applied. After text processing, various different algorithms may be applied for finding different types of information as per information need.
SPAN DETECTION AND TECHNIQUES OF SPAM DETECTION : AN OVERVIEW

: In the todays world , number of social sites is growing day by days on which reviews and information is being given by number of people. Together with the informative reviews , the number of spam revies are also growing. So in our paper we have studied about the concept of spam detection , classification of spam detection and the overall structure of spam detection framework.
Notes sur CTL et les automates d’arbres

We use tree-automata techniques to develop model-checking algorithms. We recall the definitions and main results of this classical setting, and refer to [MS87, MS95, Tho97, KVW00] for a more detailed presentation. We begin with defining alternating tree automata, which we will use in the proof. This requires the following definition : the set of positive boolean formulas over a finite set P of propositional variables, denoted with PBF(P ), is the set of formulas defined as