Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of e-governance in Ukraine based on the concept of m-governance

: Technological solutions within the concept of m-governance accelerate the provision of public services to citizens under certain conditions. The main prerequisites for efficiency are the expected perception of technology, trust in the government’s actions, the expected efficiency and quality of electronic communications. The purpose of the research is to study the trends and problems of e-governance development in Ukraine on the basis of the concept of m-governance through the assessment of the usability of the mobile application of the government “Diia” (“Action”). This study is based on the concept of m-governance, a technocentric approach to quantifying the usability of mobile applications within the digital concept of Ukraine “Country in your smartphone”. Based on a survey of 800 users, the usability of the mobile application “Diia” was assessed. The article is based on a comparison of the practice of developed and developing countries. It has been revealed no differences in the effectiveness of the integration of the concept of m-governance. The results prove the importance of usability criteria in the use of mobile applications, but there is no connection between the socio-economic characteristics of users and usability. The study proves the importance of emotional components in the integration of the concept of m-governance: trust, perception, expectations of citizens. Integration strategy and tactics are important, as digital user skills and application specifications (visibility, user control and freedom, consistency and standards, error prevention, recognition, flexibility and efficiency of use, aesthetic and minimalist design, help users recognize, diagnose, and recover from errors, help and documentation). Both the government and citizens are responsible for the effectiveness of technological interaction solutions. The study proves that the government should ensure the formation of confidence in the effectiveness of technology, develop a strategy, tactics of integration based on best practices. On the other hand, citizens are responsible for their own technological readiness through an objective assessment of digital skills.
Comparison Analysis of Online Shop between Lazada and Shopee on Students of The Faculty of Economics and Business (FEB) Narotama University Surabaya, Indonesia

This study aims to analyze differences in consumer satisfaction in buying products through the Online Shop between SHOPEE and LAZADA among FEB students of Narotama University Surabaya seen from the perception of how to use applications, promotions, prices, and satisfaction. This type of research is comparative research with a quantitative approach. The population in this study were students of the Faculty of Economics and Business at Narotama University who had used both Lazada and Shoppe online shop applications using purposive sampling in the research sample. The research data was obtained by distributing research questionnaires on How to Use, Promotion, Price, and Customer Satisfaction, to 85 respondents. The results showed that: (1) There are differences in the variable of how to use the application between the Lazada online shop and Shopee, (2) There is no difference in the variable promotional activities carried out between the Lazada online shop and Shopee, (3) There are differences in the product price variables offered between the Lazada online shop and Shopee, (4 There is no difference in the consumer satisfaction variable in shopping through the Lazada online shop with Shopee.
Study of Work-Function Variation on Performance of Dual-Metal Gate Fin Field-Effect Transistor

The impact of work-function variation (WFV) on performance of an inversion-mode (IM) dual-metal gate (DMG) fin field-effect transistor (FinFET) was investigated for the first time. The statistical fluctuations induced by WFV on the threshold-voltage (VTH), transconductance (gm), and subthreshold slope (SS) were demonstrated and estimated utilizing a 3D technology computer-aided design (TCAD) simulator. We found that the performance variations of the DMG FinFET were affected by two different metals near the drain and near the source, respectively. Additionally, this effect of the two metals on the channel was not monotonic with the length of the channel of their own control. Our work fills a gap in the study of WFV for a DMG IM FinFET and provides a reference for optimizing the distribution of the two metals.
Micromorphology and anatomy of the flowers of Galanthus nivalis and Leucojum vernum (Amaryllidaceae)

We studied the structure of flowers of Galanthus nivalis and Leucojum vernum using cross-sections and longitudal sections of permanent preparations using a light microscope. Genera Galanthus and Leucojum belong to the Galantheae tribe characterized by a unique combination of features of the family Amaryllidaceae, i.e. absence of septal nectaries, poricidal anthers and fruit – fleshy capsule. Both species are represented in the flora of Ukraine and have the life form of bulb ephemeroid of decidous forests. Microscopic surveys of flowers are considered as an instrument for determining yet unknown structural adaptations of plants to specialized ways of pollination and determining the first stages of morphogenesis of fruit, because many features of the fruit appear already at the stage of flower. We determined that the tepals of both studied species have multi-bundle traces of 8–9 vascular bundles. Apical dehiscence of the anthers occurs due to short longitudinal sutures in the upper part of the anthers. The nectar disk on the roof of the inferior ovary is poorly differentiated, and has no vascular bundles. We associate the indicated peculiarities of the flower structure with the offer of pollen as the main reward of the pollinator during buzz-polination, which has not reported for the studied species. Placentation is axile in the lower part of the ovary and parietal in the upper one. We consider that the gynoecium of the studied species is eusyncarpous. The vascular system of the inferior ovary is composed of three dorsal and three septal veins, paired ventral bundles of carpels, which form the traces of ovules, and also small additional bundles in the wall of the ovary. For the first time, we have determined the presence of airy parenchyma in the ovules, ovary roof, the style and anthers’ connectives and have confirmed their presence in the tepals and the wall of the ovary at the stage of flowering. We found differentiation of the mesocarp into photosynthesizing and airy parenchyma, small sizes of cells of the endocardium in the area of the dorsal vein, bifurcate dorsal bundles of the carpels, which could be considered as adaptation of different stages of morphogenesis of fruit to dehiscence. Anatomical peculiarities of the ovaries of G. nivalis and L. vernum: numerous vascular bundles in the pericarp, thick parenchyma mesocarp with air-filled cavities, non-lignified endocarp at the stage of the flower we consider adaptations to the formation of fleshy fruit. The new data we obtained on the anatomical structure of the flowers is a significant addition of information about anthecological and carpological (post-anthetic) peculiarities of the surveyed species.
Diagnosis and Treatment of Infertility in Men: AUA/ ASRM Guideline

Failure to conceive within 12 months of attempted conception is due in whole or in part to the male in approximately one-half of all infertile couples. Although many couples can achieve a pregnancy with assisted reproductive technologies (ART), evaluation of the male is important to most appropriately direct therapy. Some male factor conditions are treatable with medical or surgical therapy, and others may only be managed with donor sperm or adoption. Some conditions are life threatening, while others have health and genetic implications for the patient and potential offspring. Without a male evaluation it is not possible to adequately design management of the patient and the couple.
Risk in Contemporary Economy The Equestrian Tourism Valorisation in Romania

Our argument for this achievement took into account medical recommendations for this tourism product, giving tourists the possibility of treating major medical conditions (e.g. autism, depression, poliomyelitis squeals, encephalitis, neurological disorders, behavioral disorders, stress, etc.) and the fact that the first herds of horses in Romania are attested in documents since 1870. Romania holds a recognized potential to develop this tourism product, due to its natural setting that offers multiple equestrian tourism practice opportunities for Romanian and foreign tourists with multiple benefits for them. Admitting the fact that “the touristic space managing cannot be exclusively determined by its natural properties”, our paper aims a tourism marketing strategy portfolio within positive results for the Romanian equestrian tourism promotion and also may increase the local attractiveness of the regions/areas/localities of our country within potential to equestrian tourism
Middle School Teachers Making Sense of Education During the COVID-19 Pandemic

Middle school teachers are working to create an environment suitable for distance learning by promoting consistency of instruction for middle-level students during the coronavirus disease (COVID-19). This qualitative research inquiry used a phenomenological approach to study how nine middle school teachers made sense of education, amid an interruption of normal instruction during the pandemic. The theory of transformative learning supported this research inquiry from which four themes emerged: (1) forced readjustment with teacher-student interaction and quality education, (2) consistency using a virtual platform, (3) middle school teachers’ methods, and (4) middle school teachers’ instructional practices. The researcher recommends the following COVID-19-related topics for further inquiry: (1) understanding the challenges that impacted middle school teachers, (2) exploring disparities impacting the community in the area of technology readiness and other resources, (3) examining student accountability, and (4) discovering student achievement amid the pandemic.
Effect of Artemisia annua on performance , carcass characteristics and oxidative stability of Japanese quail meat

هدیکچ :یتاعلاطم هنیمز دم رویط شرورپ تعنص رد هک تسا یفادها نیرتمهم زا تشوگ تیفیک یرادیاپ شیازفا و درکلمع دوبهب یم رارق رظن . دریگ :فده هیذغت ریثات ینونک هعلاطم فده هریج ی هنمرد فلتخم حوطس یواح یاه بیکرت ،درکلمع رب یرزخ . دوب ینپاژ نیچردلب تشوگ ویتادیسکا یرادیاپ و هشلا شور :راک دادعت 375 حرط بلاق رد هزور کی ینپاژ نیچردلب هعطق اب یفداصت ًلاماک 5 و رامیت 5 و رارکت 15 ،رفص حوطس یواح هیاپ هریج اب رارکت ره رد نیچردلب هعطق 5 / 0 ، 1 ، 5 / 1 و 2 هنمرد دصرد یط یرزخ تدم 42 نس رد . دندش هیذغت زور 42 تهج و باختنا هدنرپ هعطق ود شیامزآ دحاو ره زا ،یگزور هزادنا و هشلا تایصوصخ نییعت نولام یریگ ید هچیهام دیئدلآ . دندش راتشک نار و هنیس ی :جیاتن ریثات تحت نزو شیازفا نیچردلب کاروخ فرصم اما ،تفرگن رارق یشیامزآ یاهرامیت هیذغت یاه اب هدش 2 هنمرد دصرد نییاپ کاروخ فرصم زا رت ( دوب دهاش هورگ 05 / 0 > P ینعم فلاتخا ،نینچمه .) دصرد ،خبط لباق هشلا نزو دصردرظن زا یشیامزآ یاهرامیت نیب یراد نییاپ و نیرتلااب . دشن هدهاشم بلق و دبک ،هنیس و نار نولام رادقم نیرت ید گ رد بیترت هب ،نار هچیهام رد ،دیئدلآ دهاش هور اب هدش هیذغت ناگدنرپ و 5 / 1 ( دش هدهاشم هنمرد دصرد 05 / 0 > P نییاپ ،هنیس هچیهام رد هکیلاحرد .) نولام رادقم نیرت ید -
Electronic Insurance and its application in e-commerce

Situations and procedures of business continuously are changing and every day, more options are delivering to businesses. In recent years, due to rapid growth of information and communications technology, and most importantly, the expansion and development of internet, the trend of these variations has been accelerated. Electronic is one of these options that many debates are performed concerning the implementation and in particular, its impact on business. The financial services sectors and especially the insurance industry were not excluded from this issue and in this regard, there are considerable studies that most of them have been carried out in developed and industrialized countries; moreover, some studies have been performed in undeveloped or developing countries. In present paper, in addition to defining the electronic insurance, the impact of e-commerce on insurance industry has been discussed. This paper has been organized through the category in which, in the next part insurance industry and the challenges about it and a review on Iranian insurance industry are presented. Fourth part has discussed the electronic insurance and role that it plays in e-commerce. Fifth section has focused on the impact of e-commerce on the insurance. And next section has investigated the advantages and disadvantages of e-commerce in the insurance industry, and finally, in the last part, the conclusions of this paper are presented.
Secant acceleration of sequential residual methods for solving large-scale nonlinear systems of equations

Sequential Residual Methods try to solve nonlinear systems of equations $F(x)=0$ by iteratively updating the current approximate solution along a residual-related direction. Therefore, memory requirements are minimal and, consequently, these methods are attractive for solving large-scale nonlinear systems. However, the convergence of these algorithms may be slow in critical cases; therefore, acceleration procedures are welcome. In this paper, we suggest to employ a variation of the Sequential Secant Method in order to accelerate Sequential Residual Methods. The performance of the resulting algorithm is illustrated by applying it to the solution of very large problems coming from the discretization of partial differential equations.
Control of computer pointer using hand gesture recognition in motion pictures

This paper presents a user interface designed to enable computer cursor control through hand detection and gesture classification. A comprehensive hand dataset comprising 6720 image samples was collected, encompassing four distinct classes: fist, palm, pointing to the left, and pointing to the right. The images were captured from 15 individuals in various settings, including simple backgrounds with different perspectives and lighting conditions. A convolutional neural network (CNN) was trained on this dataset to accurately predict labels for each captured image and measure their similarity. The system incorporates defined commands for cursor movement, left-click, and right-click actions. Experimental results indicate that the proposed algorithm achieves a remarkable accuracy of 91.88% and demonstrates its potential applicability across diverse backgrounds.
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations

Multi-agent reinforcement learning (MARL) has been increasingly explored to learn the cooperative policy towards maximizing a certain global reward. Many existing studies take advantage of graph neural networks (GNN) in MARL to propagate critical collaborative information over the interaction graph, built upon inter-connected agents. Nevertheless, the vanilla GNN approach yields substantial defects in dealing with complex real-world scenarios since the generic message passing mechanism is ineffective between heterogeneous vertices and, moreover, simple message aggregation functions are incapable of accurately modeling the combinational interactions from multiple neighbors. While adopting complex GNN models with more informative message passing and aggregation mechanisms can obviously benefit heterogeneous vertex representations and cooperative policy learning, it could, on the other hand, increase the training difficulty of MARL and demand more intense and direct reward signals compared to the original global reward. To address these challenges, we propose a new cooperative learning framework with pre-trained heterogeneous observation representations. Particularly, we employ an encoder-decoder based graph attention to learn the intricate interactions and heterogeneous representations that can be more easily leveraged by MARL. Moreover, we design a pre-training with local actor-critic algorithm to ease the difficulty in cooperative policy learning. Extensive experiments over real-world scenarios demonstrate that our new approach can significantly outperform existing MARL baselines as well as operational research solutions that are widely-used in industry.
In Vitro Electron Density Refinement from Solution X-ray Scattering in the Wide-Angle Regime

We present Frequency Marching, FM, an algorithm that refines three-dimensional electron density distributions from solution X-ray scattering data in both the smalland wide-angle regimes. This algorithm is based on a series of optimization steps, marching along the frequency (reciprocal) space and refining detailed periodic structures with the corresponding real-space resolution. Buffer subtraction and excluded volumes, key factors in extracting the signatures of the biomolecule of interest from the sample, are accounted for using implicit density models. We provide the numerical and analytical basis of the FM algorithm. We demonstrate this technique by application to structured and unstructured nucleic acid systems, where higher resolution features are carved out of low resolution reconstructions as the algorithm marches into wider angles.
Transverse Coupled Cavity VCSEL: Making 100 GHz Bandwidth Achievable

Enhancing the modulation bandwidth (MBW) of semiconductor lasers has been the challenge of research and technology to meet the need of high-speed photonic applications. In this paper, we propose the design of vertical-cavity surface-emitting laser integrated with multiple transverse coupled cavities (MTCCs) as a promising device with ultra-high 3-dB bandwidth. The laser features high modulation performance because of the accumulated strong coupling of the slowlight feedback from the surrounding lateral TCCs into the VCSEL cavity. Photon-photon resonance (PPR) is predicted to occur at ultra-high frequencies exceeding 145 GHz due to the optical feedback from short TCCs, which achieves 3-dB MBW reaching 170 GHz. The study is based on the modeling of the VCSEL dynamics under multiple transverse slow-light feedback from the surrounding TCCs. We show that the integration of the VCSEL with four or six feedback cavities is advantageous over the TCC-VCSEL in achieving much higher MBW enhancement under weaker coupling of slow-light into the VCSEL cavity. We also characterize the noise properties of the promising MTCC-VCSEL in the regime of ultra-high bandwidth in terms of the Fourier spectrum of the relative intensity noise (RIN).
Distortion-Aware Linear Precoding for Massive MIMO Downlink Systems with Nonlinear Power Amplifiers

We introduce a framework for linear precoder design over a massive multiple-input multiple-output downlink system in the presence of nonlinear power amplifiers (PAs). By studying the spatial characteristics of the distortion, we demonstrate that conventional linear precoding techniques steer nonlinear distortions towards the users. We show that, by taking into account PA nonlinearity, one can design linear precoders that reduce, and in single-user scenarios, even completely remove the distortion transmitted in the direction of the users. This, however, is achieved at the price of a reduced array gain. To address this issue, we present precoder optimization algorithms that simultaneously take into account the effects of array gain, distortion, multiuser interference, and receiver noise. Specifically, we derive an expression for the achievable sum rate and propose an iterative algorithm that attempts to find the precoding matrix which maximizes this expression. Moreover, using a model for PA power consumption, we propose an algorithm that attempts to find the precoding matrix that minimizes the consumed power for a given minimum achievable sum rate. Our numerical results demonstrate that the proposed distortion-aware precoding techniques provide significant improvements in spectral and energy efficiency compared to conventional linear precoders.
Effective Deployment of CNNs for 3DoF Pose Estimation and Grasping in Industrial Settings

In this paper we investigate how to effectively deploy deep learning in practical industrial settings, such as robotic grasping applications. When a deep-learning based solution is proposed, usually lacks of any simple method to generate the training data. In the industrial field, where automation is the main goal, not bridging this gap is one of the main reasons why deep learning is not as widespread as it is in the academic world. For this reason, in this work we developed a system composed by a 3-DoF Pose Estimator based on Convolutional Neural Networks (CNNs) and an effective procedure to gather massive amounts of training images in the field with minimal human intervention. By automating the labeling stage, we also obtain very robust systems suitable for production-level usage. An open source implementation of our solution is provided, alongside with the dataset used for the experimental evaluation.
Handling SQL Nulls with Two-Valued Logic

The design of SQL is based on a three-valued logic (3VL), rather than the familiar Boolean logic. 3VL adds a truth value unknown to true and false to handle nulls. Viewed as indispensable for SQL expressiveness, it is at the same time much criticized for unintuitive behavior of queries and being a source of programmer mistakes. We show that, contrary to the widely held view, SQL could have been designed based on the standard Boolean logic, without any loss of expressiveness and without giving up nulls. The approach itself follows SQL's evaluation, which only retains tuples for which conditions in WHERE evaluate to true. We show that conflating unknown with false leads to an equally expressive version of SQL that does not use the third truth value. Queries written under the two-valued semantics can be efficiently translated into the standard SQL and thus executed on any existing RDBMS. These results cover the core of the SQL 1999 Standard: SELECT-FROM-WHERE-GROUP BY-HAVING queries extended with subqueries and IN/EXISTS/ANY/ALL conditions, and recursive queries. We also investigate new optimization rules enabled by the two-valued SQL, and show that for many queries, including most of those found in benchmarks such as TPC-H and TPC-DS, there is no difference between three- and two-valued versions.
A Survey on Spatial and Spatiotemporal Prediction Methods

With the advancement of GPS and remote sensing technologies, large amounts of geospatial and spatiotemporal data are being collected from various domains, driving the need for effective and efficient prediction methods. Given spatial data samples with explanatory features and targeted responses (categorical or continuous) at a set of locations, the problem aims to learn a model that can predict the response variable based on explanatory features. The problem is important with broad applications in earth science, urban informatics, geosocial media analytics and public health, but is challenging due to the unique characteristics of spatiotemporal data, including spatial and temporal autocorrelation, spatial heterogeneity, temporal non-stationarity, limited ground truth, and multiple scales and resolutions. This paper provides a systematic review on principles and methods in spatial and spatiotemporal prediction. We provide a taxonomy of methods categorized by the key challenge they address. For each method, we introduce its underlying assumption, theoretical foundation, and discuss its advantages and disadvantages. Our goal is to help interdisciplinary domain scientists choose techniques to solve their problems, and more importantly, to help data mining researchers to understand the main principles and methods in spatial and spatiotemporal prediction and identify future research opportunities.