Miracle-dz/UniFAR-FTUs huggingface dataset:
Economic gender gap in the Global South: how institutional quality matters

One of the most challenging gender gaps in the Global South remains in the economic sphere. This paper examines how public institutional quality affects the gender gap in economic participation and opportunities in 74 developing and emerging countries during the period 2006-2016. We find that the quality of public institutions is closely associated with the economic gender gap. Specifically, the protection of property rights, security guarantees and government efficiency seem to be the main factors associated to lower values of the economic gender gap. Nevertheless, public institutions do not matter equally throughout economically backward countries. Whereas in emerging countries, particularly in Latin America and the Caribbean, a broad variety of institutional aspects, including undue influence on judicial and government decisions, are closely related to the economic gender gap, in low-income developing countries, such as Sub-Saharan countries, the problems of ethics and corruption stand out as a key element against economic gender equality. Some significant policy implications are derived from our findings on the potential of public institutions reforms to reduce economic gender gap.
The Periodic Leaky-Wave Antenna With Different Unit Cells Based on Consistent Fundamental Mode

In this article, we present a novel periodic microstrip leaky-wave antenna (MLWA) design based on different unit cells. The proposed antenna consists of three different kinds of unit cells developed in our previous works, in which the wavenumber of fundamental mode is basically consistent. Big period cascaded by the three different unit cells is introduced for producing a relatively narrow radiation beam. Almost same radiation angle of the antenna is obtained regardless of the permutation of unit cells, which provides more design freedom on antenna structure. Slotting and pins loading technique are applied in unit cells for canceling the reactance of the big period, thus a continuous beam scanning with small gain fluctuation around broadside direction could be achieved. The prototype is fabricated and measured, demonstrating the feasibility of this novel periodic antenna design and well agreement between simulated and measured results. Measurement results show the main beam steers continuously from −46° to 31° with the operating frequency changes from 6 to 9 GHz. The peak gain reaches up to 12.8 dBi at the frequency of 7 GHz.
Area-optimized design of SOT-MRAM

In this letter, we present a new structure of spin-orbit torque magnetic random access memory (SOT-MRAM) for area optimization. Based on the observation of SOT-MRAM layout that the metal line can be added in the horizontal direction without increasing the cell area, the proposed design optimizes the metal line routing direction as well as biasing conditions for read and write operations. Implemented with a 45-nm CMOStechnology, theproposeddesignachievescellareareductionof42% (23%) compared with the conventional SOT-MRAM (STT-MRAM). The proposed design achieves 6.26x lower write power than STT-MRAM by taking advantage of high spin current injection eﬃciency. Also, owing to separatereadandwritecurrentpaths,theproposeddesigncanoptimizeeachpathindependently,resultingin7.69xlowerreadpowerand1. 88xhigher read-disturbmarginincomparisontoSTT-MRAMthathasacommonpathforreadandwriteoperations.
Microbial contamination of cow’s milk and operator hygiene

А. P. Palii, A.P. Paliy, K.O. Rodionova, S.A. Zolotaryova, L.L. Kushch, V.M. Borovkova, M.V. Kazakov, I.S. Pavlenko, Y.O. Kovalchuk, V.S. Kalabska, O.V. Kovalenko, O.M. Pobirchenko, O.S. Umrihina Kharkiv Petro Vasylenko National Technical University of Agriculture, 44 Alchevskih St., Kharkiv, 61002, Ukraine. National Scientific Center «Institute of Experimental and Clinical Veterinary Medicine, 83 Pushkinska St., Kharkiv, 61023, Ukraine. Luhansk National Agrarian University, 23 Svobody St., Sloviansk, Donetsk region, 84122, Ukraine. Kharkiv National Agrarian University named after V.V. Dokuchaeva, p/o "Dokuchaev-2", training camp of KNAU, Kharkiv region, Kharkiv, 62483, Ukraine. Kharkiv State Veterinary Academy, 1 Academic St., Village Malaya Danilivka, Dergachi District, Kharkiv Region, 62341, Ukraine. Uman National University of Horticulture, 1 Instytutska St., Uman, Cherkasy region, 20305, Ukraine. Pavlo Tychyna Uman State Pedagogical University, 2 Sadova St., Uman, Cherkassy region, 20300, Ukraine.
A Recommendation Method for Highly Sparse Dataset Based on Teaching Recommendation Factorization Machines

: There is no reasonable scientific basis for selecting the excellent teachers of the school’s courses. To solve the practical problem, we firstly give a series of normalization models for defining the key attributes of teachers’ professional foundation, course difficulty coefficient, and comprehensive evaluation of teaching. Then, we define a partial weight function to calculate the key attributes, and obtain the partial recommendation values. Next, we construct a highly sparse Teaching Recommendation Factorization Machines (TRFMs) model, which takes the 5-tuples relation including teacher, course, teachers’ professional foundation, course difficulty, teaching evaluation as the feature vector, and take partial recommendation value as the recommendation label. Finally, we design a novel Top-N excellent teacher recommendation algorithm based on TRFMs by course classification on the highly sparse dataset. Experimental results show that the proposed TRFMs and recommendation algorithm can accurately realize the recommendation of excellent teachers on a highly sparse historical teaching dataset. The recommendation accuracy is superior to that of the three-dimensional tensor decomposition model algorithm which also solves sparse datasets. The proposed method can be used as a new recommendation method applied to the teaching arrangements in all kinds of schools, which can effectively improve the teaching quality.
Performance of a Cooperative Communication Network With Green Self-Sustaining Nodes

The desire to reduce carbon foot-print and avoid frequent battery replacement has increased interest in green self-sustaining wireless nodes based on energy harvesting. In this article, we analyze the performance of a two-hop cooperative network with green self-sustaining nodes. The source and relay nodes are equipped with energy buffers, and store the energy harvested from the ambience. Signal transmission is powered at both source and relay solely by the stored energy. Both fixed and adaptive-rate transmission schemes are considered, and analytical expressions are presented for throughput and ergodic rate. Unlike all previous works that use discrete-state Markov chains to model the buffer dynamics, we use the more appropriate discrete-time continuous-state space Markov chain. We consider two different energy management policies at the source and relay: best-effort policy (BEP) and on-off policy (OOP). It is observed that for fixed-rate transmission, the better choice of buffer management policy (throughput-wise) at the source and the relay buffers depends on the relay location and target rate. On the other hand, for adaptive rate transmission, using BEP policy at both the energy buffers ensures best performance. The derived analytical expressions are validated by Monte Carlo simulations.
Cost-Effective App User Allocation in an Edge Computing Environment

Edge computing is a new distributed computing paradigm extending the cloud computing paradigm, offering much lower end-to-end latency, as real-time, latency-sensitive applications can now be deployed on edge servers that are much closer to end-users than distant cloud servers. In edge computing, edge user allocation (EUA) is a critical problem for any app vendors, who need to determine which edge servers will serve which users. This is to satisfy application-specific optimization objectives, e.g., maximizing users’ overall quality of experience, minimizing system costs, and so on. In this article, we focus on the cost-effectiveness of user allocation solutions with two optimization objectives. The primary one is to maximize the number of users allocated to edge servers. The secondary one is to minimize the number of required edge servers, which subsequently reduces the operating costs for app vendors. We first model this problem as a bin packing problem and introduce an approach for finding optimal solutions. However, finding optimal solutions to the <inline-formula><tex-math notation="LaTeX">$\mathcal {NP}$</tex-math><alternatives><mml:math><mml:mi mathvariant="script">NP</mml:mi></mml:math><inline-graphic xlink:href="lai-ieq1-3001570.gif"/></alternatives></inline-formula>-hard EUA problem in large-scale scenarios is intractable. Thus, we propose a heuristic to efficiently find sub-optimal solutions to large-scale EUA problems. Extensive experiments conducted on real-world data demonstrate that our heuristic can solve the EUA problem effectively and efficiently, outperforming the state-of-the-art and baseline approaches.
Does Capture in Aerogel Change Carbonaceous Raman D and G Bands

Introduction: Since the first demonstration of capture of hypervelocity particles [1] the use of aerogel to capture cosmic dust in space has become well established (see [2] for a recent review). The recent success of the NASA Stardust mission which returned cometary samples to Earth shows how fruitful this can be [3]. The particular advantage that capture and return of dust from space offers researchers lies in our ability to apply a full range of analytic tools in the laboratory to samples of known provenance. However, to obtain the full benefit from such analyses, any potential biases due to the capture method need to be understood and, if possible, corrected. Raman and Organics: Raman spectroscopy has long been used to study the carbon content of samples, and this has been applied to dust from space since at least the early 1980s. The technique mostly relies on study of first order carbon D and G peaks, their peak position and width (and ratios thereof) to identify the presence of carbonaceous materials and to infer the history of the materials (i.e. how processed/dis-ordered is the carbon and what does that imply about the thermal history of the sample, etc.). Examples of analyses on interplanetary dust particles (IDPs) can be found in [4], meteorites in [5] and terrestrial samples in [6]. In parallel, laboratory tests have shown that Raman techniques can be used to identify the mineral [7] and organic [8, 9] content of small particles after their high speed capture in aerogel. The Stardust mission has recently reported on studies of the organic content of dust particles captured from comet 81P/Wild 2 [10]. Raman analysis of the D and G bands for particles captured in 3 aerogel tracks was conducted, and it was found that the grains gave signals similar to the full range found with IDPs and meteorites. However, in [10] it was noted that this wide range of results could be attributable to either a large degree of heterogeneity amongst the samples or processing during capture in the aerogel. To clarify this issue, we have carried out a range of laboratory studies looking at processing of organics in dust particles during capture in aerogel. Method: Three meteorite samples were used in this study (Orgueil, Murchison and Allende). These were from samples provided from the collection of the Natural History Museum (London). Powdered samples of each meteorite (grain size 39 53 microns) were separately fired in a two stage light gas gun at the University of Kent [11] at speeds of typically 6.1 km s -1 (the Stardust cometary encounter speed). The targets were blocks of aerogel of density 28 – 29 kg m -3 . These blocks were not Stardust grade aerogels which had a density gradient from the front face of 5 kg m -3 , rising to 50 kg m -3 at the rear face. The density used here is thus intermediate between these two extremes. Several grains were captured in each shot.
A Hybrid Path Planning Method Based on Articulated Vehicle Model

: Due to the unique steering mechanism and driving characteristics of the articulated vehicle, a hybrid path planning method based on the articulated vehicle model is proposed to meet the demand of obstacle avoidance and searching the path back and forth of the articulated vehicle. First, Support Vector Machine (SVM) theory is used to obtain the two-dimensional optimal zero potential curve and the maximum margin, and then, several key points are selected from the optimal zero potential curves by using Longest Accessible Path (LAP) method. Next, the Cubic Bezier (CB) curve is adopted to connect the curve that satisfies the curvature constraint of the articulated vehicle between every two key points. Finally, Back and Forth Rapidly-exploring Random Tree with Course Correction (BFRRT-CC) is designed to connect paths that do not meet articulated vehicle curvature requirements. Simulation results show that the proposed hybrid path planning method can search a feasible path with a 90-degree turn, which meets the demand for obstacle avoidance and articulated vehicle back-and-forth movement.
Single-Filter Finite Fault Detection and Exclusion Methodology for Real-Time Validation of Plug-and-Play Sensors

All-source navigation has become increasingly relevant over the past decade with the development of viable alternative sensor technologies. However, as the number and type of sensors informing a system increases, so does the probability of corrupting the system with sensor modeling errors, signal interference, and undetected faults. Though the latter of these has been extensively researched, the majority of existing approaches have designed algorithms centered around the assumption of simultaneously redundant, synchronous sensors with well-understood measurement models, none of which are guaranteed for all-source systems. As part of an overall all-source assured or resilient navigation objective, this research contributes a key component—validation of sensors which have questionable sensor models, in a fault-agnostic and sensor-agnostic manner, and without compromising the ongoing navigation solution in the process. The proposed algorithm combines a residual-based test statistic with the partial update formulation of the Kalman–Schmidt filter to provide a reliable method for sensor model validation that protects the integrity of the navigation solution during the validation process, all using only a single existing filter. The performance of the proposed method is validated against traditional fault detection and exclusion methods (such as normalized solution separation and conventional residual sequence monitoring) using Monte–Carlo simulations in a 2D non-Global Positioning System navigation problem with a plug-and-play position sensor.
Structural improvement of a kinematic wave-based distributed hydrologic model to estimate long-term river discharge in a tropical climate basin

: A distributed hydrologic model based on a kinematic wave approximation with surface and subsurface flow com‐ ponents is applicable to basins that have temperate climatic conditions similar to those in Japan. However, it is difficult to present long-term river discharge using the existing model structure in basins with different climatic conditions. This study aims to improve the model structure for better estimates of long-term discharge in the Nam Ngum River, the main tributary of the Mekong River, by incorporating bedrock aquifers as part of the slope flow component of the original model structure. Three bedrock groundwater struc‐ tures are configured to incorporate the original model structure. The results show that a combination of the origi‐ nal model component and one unconfined aquifer structure are the best representations of the river flow regime from the original model structure, in which the rate of infiltration from the layer into the bedrock aquifer was calculated using vertical hydraulic conductivity. The Nash–Sutcliffe efficiency coefficient of the original and improved models increased from 0.80 to 0.86 during the calibration period and from 0.56 to 0.62 during the validation period. The results of this study show that the improved model structure is applicable for long-term hydrologic predictions in South‐ east Asian catchments with distinct dry and rainy seasons.
The Perceptions and Preferences of 8th Grade Students in Digital Storytelling in English.

Digital storytelling is the focus of the present study due to scarcity of studies in Turkey. This study investigates the perceptions of 8 th grade students on the integration of technology via Digital Storytelling to English courses. Another aim is to find out students’ preferences for topic and characters in their digital stories. The study was conducted with 15 students in a public school. The data were collected through pre-survey, digital stories, and post-survey. The study was carried out in a month period in which 5 different digital stories were created. The findings based on qualitative and quantitative analysis indicated that the perceptions of the participants toward the use of digital storytelling in English lessons were positive before and after the implementation process with no significant difference between them pre and post-tests. In general, the participants wanted to keep using digital storytelling because they believed digital storytelling is motivating, contributes to language learning, and enables collaboration. The topics preferred were adrenalin, love, sadness, friendship, and fear. The characters were generally female heroines. The implications are that digital storytelling can be integrated into speaking, listening, grammar, vocabulary and writing activities since it is an engaging way of practising language skills.
Disturbance Compensating Adaptive Regulator for MIMO Time-Delayed Discrete-Time Systems

A discrete-time adaptive regulator for uncertain MIMO LTI systems with input delays is proposed. The input delays are assumed to be constant and unknown except for a known upper bound, and it is possible for delays to be different across input channels. An adaptive estimator is used for online parameter estimation, and the control law is obtained by applying Artstein’s model reduction to the adaptive model after it has been rewritten using a second order difference. The resulting controller is, then, able to stabilize the system while mitigating the effects of the unmeasurable exogeneous disturbances.
Nepali Handwriting Recognition using Convolution Neural Network

- The recognition of texts from the scanned image can have various applications, which are based on optical character recognition. This paper was proposed and carefully experimented to analysis and recognize handwritten Nepali character using Convolution Neural Network. The preliminary experiment has been done with 92 thousand images of 46 different classes of 32 * 32 characters of Nepali Handwriting which went through different preprocessing stages like clipping and cropping, grayscale conversion and through different processes like feature extraction etc. The recognition has been experimented with the help of template matching technique. This proposal will employ Back Propagation algorithm along with Gradient descent algorithm will be used to update the weights, an artificial neural network training and testing. Thus, this experiment concluded that the convolution neural network model has more accuracy than the Feed Forward neural network in character recognition.
Clinical features of non-classical celiac disease in children and adolescents

1 Academy of Medical Sciences of the Serbian Medical Society, Belgrade, Serbia; 2 University Children’s Hospital, Belgrade, Serbia; 3 University of Belgrade, Faculty of Medicine, Belgrade, Serbia; 4 University of Belgrade, School of Dental Medicine, Clinic for Pediatric and Preventive Dentistry, Belgrade, Serbia; 5 Singidunum University, Faculty of Health, Legal and Business Studies, Valjevo, Serbia; 6 Railways of Serbia Institute for Health Care of Workers, Belgrade, Serbia; 7 Pediatric Clinic of the Clinical Center Kragujevac, Kragujevac, Serbia; 8 University of Kragujevac, Faculty of Medical Sciences, Kragujevac, Serbia
Simulating the kinematics, shocks and cooling of gas-rich direct disk-disk galaxy collisions to study the evolution and morphology of the multi-phase ISM

xiii CHAPTER 1. GENERAL INTRODUCTION . 1 1.1 Outline . 1 1.2 Galaxy Interactions . 1 1.3 Previous Models . 3 1.4 Some Systems of Note . 6 1.5 References . 8 CHAPTER 2. MODELS OF MULTI-COMPONENT SPLASH BRIDGES IN FACE-ON GALAXY DISC COLLISIONS . 12 2.1 Abstract . 12 2.2 Introduction: Swing and Splash Bridges . 13 2.3 The Model . 17 2.3. 1 Numerical Methods . 17 2.3. 2 Initial Conditions . 18 2.3. 3 Cloud Collisions . 19 2.3. 4 Shocks and Heating . 21 2.3. 5 Gas Cooling . 23 2.4 Results . 25 2.4. 1 Single Component ISM Models of HI discs with 500 pc offset . 28 2.4. 2 HI Bridges with Various Offsets . 29 2.4. 3 Five component ISM models with 500 pc offset . 33 2.4. 4 Five component ISM models with 21 kpc offset . 42 2.4. 5 Taffy-Like Run . 43 2.4. 6 Cloud Populations . 49 2.4. 7 Paths of H2 Formation . 49 2.5 Discussion Some Systems of Interest . 50 2.6 Conclusions . 51 2.7 Code Tests . 53 2.8 References . 56
Analyzing the Factors Which Influence the Development of Mangrove Forest in Kulon Progo Using Binary Logistic Regression and Remote Sensing Method

The Province of Yogyakarta is one of the tourism destinations in Indonesia. In recent years, there are new many tourism sites in Yogyakarta. One of them is the Mangrove forest in Kulon Progo. The Mangrove forest is a popular tourist site among the locals in there but many outsiders of Yogyakarta that do not know about this site yet. That is because the access to that site is quite difficult. Also, we believe that there are many factors which delay the development that Mangrove site. In order to help the development of that area, we would like to know the real factor which impacts the development of the Mangrove site, especially from the tourism perspective. Therefore we analyze the factors which influence the happiness of the tourist using the binary logistic regression, because the happier the tourist, the site will be more popular and hopefully develop from the tourism perspective. The binary logistic regression’s result shows that the happiness of the tourist influenced by mangrove location, age, and gender. The mangrove location factor that influences tourist happiness is about the difficultness of access. As for that factor, we will use the remote sensing method to identify what really happened in the locations and give solutions to that problem.
Differential tractography as a track-based biomarker for neuronal injury

Diffusion MRI tractography has been used to map the axonal structure of human brain, but its ability to detect neuronal injury is yet to be explored. Here we report differential tractography, a new type of tractography that utilizes repeat MRI scans and a novel tracking strategy to map the exact segment of fiber pathways with a neuronal injury. We examined differential tractography on multiple sclerosis, Huntington disease, amyotrophic lateral sclerosis, and epileptic patients. The results showed that the affected pathways shown by differential tractography matched well with the unique clinical symptoms of the patients, and the false discovery rate of the findings could be estimated using a sham setting to provide a reliability measurement. This novel approach enables a quantitative and objective method to monitor neuronal injury in individuals, allowing for diagnostic and prognostic evaluation of brain diseases.