Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultraviolet reflectance and cryptic sexual dichromatism in the ocellated lizard, Lacerta (Timon) lepida (Squamata: Lacertidae)

Ultraviolet (UV) colorations have garnered extensive theoretical and empirical treatment in recent years, although the majority of studies have concerned themselves with avian taxa. However, many lizards have acute visual systems with retinal photoreceptors that are sensitive to UV wavelengths, and also display UV-reflecting colour patches. In the present study, we used UV photography and full-spectrum reflectance spectrophotometry to describe intra- and intersexual colour variation in adult ocellated lizards Lacerta (Timon) lepida and to obtain evidence of UV-based ornamentation. We also investigated whether any colour traits correlate with morphological traits potentially related to individual quality. The results obtained show that the prominent eyespots and blue outer ventral scales (OVS) that ocellated lizards have on their flanks reflect strongly in the UV range and are best described as UV/blue in coloration. The eyespots of males are larger and cover a larger surface area than those of females. However, these differences can be entirely accounted for by sex differences in body size, with males being generally larger than females. We also found differences in the shape of reflectance curves from males and females, with the eyespots and blue OVS of males being more UV-shifted than those of females. Other body regions have extremely low UV reflectance and are not sexually dichromatic. Eyespot size and the total surface area covered by eyespots increases with body size in males but not in females, suggesting that they may be signalling an intrinsic individual characteristic such as body size or male fighting ability. We also discuss the alternative and non-exclusive hypothesis that eyespots may function in lizards of both sexes as protective markings against predators. © 2009 The Linnean Society of London, Biological Journal of the Linnean Society, 2009, 97, 766–780.
Adjustments to amputation and artificial limb, and quality of life in lower limb amputees

Amputatie van ledematen heeft een grote impact op het individu, niet alleen bij de vervalsing van het lichaamsbeeld, maar ook van invloed op hun sociale en psychologische functioneren. Prothese is de enige manier waarop deze mensen kunnen onafhankelijk zijn, deel te nemen aan de samenleving, en hervatten hun werk. Er zijn verschillende factoren, die het gebruik van prothese door geamputeerden kan ook van invloed zijn en op hun beurt van invloed op hun kwaliteit van leven (QoL). De onderzoeksvragen die zullen worden bestudeerd zijn: I. Wat is er bekend in de wetenschappelijke literatuur over de kwaliteit van leven van mensen met een beenamputatie? 2. Is de vertaald en aangepast gezondheidsgerelateerde QoL instrument in het Hindi taal betrouwbare en valide om te worden gebruikt in India? 3. Welke sociaal-demografische, medische en amputatie-gerelateerde factoren zijn gerelateerd aan de aanpassing van amputatie en prothese? 4. Wat zijn de rollen van de aanpassing aan amputatie en prothese bij het bepalen van de kwaliteit van leven in de onderste ledematen amputatie?
Floating photovoltaic plants on artificial accumulations — Example of Jablanica Lake

The paper analyzes the problem of the construction of utility-scale solar photovoltaic power plants (US-PV). Two main problems of this construction are: occupying usable areas and the connection and integration of the power plant into the electricity system. The construction of US-PV power plants on water accumulations of existing hydro power plants was analyzed, as one of the solutions to these problems. The Jablanica Lake was taken as an example. Jablanica Lake is an artificial accumulation lake on the river Neretva with an area of 13 km2 within the hydroelectric power plant (HPP) Jablanica with 180 MW of installed power. It was shown that on a surface of less than 3% of the total area of the accumulation of HPP Jablanica, there could be built a floating photovoltaic (PV) plant with a power of 30 MW. This power would add another generator of 30 MW to HPP Jablanica, which would increase the current number of the 6 generators to 7. This would enable significantly better exploitation of the Neretva and Rama river basins, and increase production in the summer period with a decrease in lake level oscillations. Suitable locations for the installation of floating solar power plant were analyzed. Locations are selected on the basis of requirements for the preservation of existing lake functions, and provide the possibility of installing a 3 MW power plant. 10 of these plants, connected by a 20 kV power grid, represent one US-PV 30 MW plant, which at one point connects to the transmission network of 220 kV. The specifications of one 3 MW power plant are given in terms of the required area, number of modules and number of inverters. A preliminary techno-economic analysis of the total plant was carried out. In this analysis, the possible production, the indicative price of the plant, and the price of the produced kWh of electricity are calculated.
Optimal operation of storage systems in distribution networks considering battery degradation

Energy storage systems are lauded solutions for integrating the ever-increasing amounts of renewable energy sources in distribution networks. Electrochemical batteries, principally lithium-ion based, are among the most promising storage technologies for these applications due their high energy densities, capacities, and efficiencies. The operation of these energy storage resources must be optimized since every charge/discharge cycle wears the battery and reduces its lifespan. This paper presents a stochastic second-order cone programming model, that considers the AC power flow equations, for optimizing the operation of battery storage systems in distribution networks, taking into account their degradation characteristics explicitly. A 33-node distribution network is used to demonstrate the effectiveness of the proposed method. Results also demonstrate the importance of including the degradation characteristics in the model, in order to attain solutions that strike a balance between operating costs and the benefits of prolonging the lifespan of the batteries.
Scrutinizing action performed by user on mobile app through network using machine learning techniques: A survey

Smartphones are used in a large scale for different activities like bank transaction, shopping, surfing knowledge etc. Everyone is carrying mobile in their pocket where sensitive or private information is stored about individual user. As user interacted with mobile apps lot of network traffic is generated by sending or receiving request. Generated network traffic analyzed by attacker and there is a possibility that private information can be viewed by attacker. That means user data is not secured so how attacker track user is explained in the paper. The organization of this paper is as follows. First section describes introduction in brief, section II provides related work done on analyzing network traffic, section III describes machine learning background with example, and section IV includes conclusion which help to extend current work.
A platform for the authoring of educational games

An Educational Game Authoring (EGA) tool is a software to assist teachers in the authoring of games. Game authoring can be approached from two different perspectives. The first, where the educator creates a game from scratch, and a second one, where specific game components of an existing game can be configured (edited) by the teacher, abstracting the technical aspects of game development for non-programmer users. Nevertheless, whatever the perspective, the authoring games in an easy way is still a challenge, and even more, there is a lack of works considering educational aspects like Intended Learning Outcomes (ILOs), students' learning and playing styles, and learning mechanics. This work takes the second perspective and proposes an EGA platform that although embraces both the game and educational domains, puts the emphasis on the educational one. The platform provides educators with a mean for configuring educational games, and so adapt game's educational content to lessons pacing and students' learning needs. This platform is conceived generic enough to serve those educational games that are adapted to interact with it using a given protocol and communication language. In this paper, we present the architecture of the EGA platform, the communication protocol and the Authoring Description Language (ADL). We show the approach with an example of a maths game.
Detection the mid-sagittal plane in brain slice MR images by using local ternary pattern

The detection and localization of the mid-sagittal plane (MSP) in brain MR images is an important step in the diagnosis of brain pathologies and calculation of the symmetry between the two sides of a MSP. In this paper, a new method is proposed to locate MSP in T1-weighted MRI images, based on the computation of the different local texture between inter-hemispheric fissure (IF) region and the surrounding tissue. This method is based on local binary pattern technique. It is high-performance texture features to describe local structures. However, the LBP method is sensitive to noise. To overcome this disadvantage, we proposed a new method by using Block Local Ternary Patterns for achieving high classification accuracy thus improving the encoding of the texture feature. The proposed method is based on the second-moments method to solve the tilted brain problem; the rotation angle resulted is used to determine the initial line of the MSP. The performances of the proposed method are compared with the two extensions of LBP features, average LBP and block-based LBP. As it can be seen from the experimental data, the efficiency of the proposed method is better in comparison to the traditional LBP techniques in terms of classification accuracy.
Advanced superconducting tapes for high voltage fault current limiters

Superconducting fault current limiters based on high temperature superconducting coated conductors are novel devices which enables further development of the electricity network. In this contribution analyse properties of advanced superconducting tapes with modified architecture to withstand higher electric fields and thus higher heat generation during limiting period. We have shown that additional heat capacity layer, made of hasteloy, reduces maximum temperature of superconductor despite of enhanced heat generation resulting from lower resistance of the modified tape.
High voltage current analyzer with galvanic separation

Possible solutions of the current measurement at any node or branch of the high voltage circuit are described in this paper. By default, the current in the high voltage circuits is measured at or in the vicinity of ground potential, where they are not too large differential voltage potentials or intense electric field. The current is measured using a shunt resistor, Rogowski coils or by using Hall effect probes. However, sometimes it is necessary to measure the current directly at the high voltage potential, for example, at the output of the high voltage source, during the measurement of partial discharges, measurement on an electronic bridge, etc. Therefore, it is necessary to look for alternatives, as this current measurement to ensure. The biggest problem is the galvanic isolation, because it is not possible to work directly on high voltage potential. And also it is not possible to provide a powering of measuring device. Especially for online measurements on high voltage potential, it is necessary to ensure power supply and signal transmission with a measured value of the current.
Classifying for a mixture of object images and character patterns by using CNN pre-trained for large-scale object image dataset

Neural networks are a powerful means of classifying object images and character patterns. The proposed common classification method for object images and handwritten digits combines convolutional neural networks (CNNs) and support vector machines (SVMs). A pre-trained CNN, called Alex-Net, is used as a pattern-feature extractor. Alex-Net is pre-trained for the large-scale object-image dataset ImageNet. An SVM is used as trainable classifier. The feature vectors are passed to the SVM from Alex-Net. A mixture of STL-10 object images and MNIST handwritten digit patterns is trained by the SVM. Experimental test error rate for the mixture of test 8k STL-10 object images and 10k MNIST digit patterns was 7.734%, which shows that the proposed method is effective for common-category classification.
The Impact of Family Structure and Family Change on Child Outcomes: A Personal Reading of the Research Literature

The paper provides a brief overview of the research literature on the impacts of family structure and family change on child outcomes, with a particular focus on parental separation. It takes as a starting point the existence of pervasive associations between family change and child outcomes and addresses a range of issues that are examined in the research literature. Do family changes primarily have short-term impacts on children, or do they also have more enduring impacts? How does remarriage affect child outcomes? What impact do frequent changes of family structure have on child outcomes? What are the mechanisms that link family structure and family change to child outcomes? How much of the impact is attributable to income changes consequent on parental separation? How much is attributable to the absence of a parent figure? How much is attributable to poorer mental health of lone parents following a parental separation? How much is attributable to the conflict between parents which often accompanies a parental separation? And how much of the association between family change and child outcomes is due to non-causal mechanisms, such as selection effects? The paper will sketch out answers to these questions, as far as these can be determined from the published results of research.
Training with enlightening model for games with difficult-starting problem

Self-play process is known to work in training an AI Go player. But in some other games, such as Competition Mahjong, we find that only with this method it's hard to reach a usable final state for an agent of primary level, which makes training difficult in the early stages. This work presents a new learning framework, Training with Enlightening Model (TEM), that aims to solve the difficult-starting problem in games. We evaluate our framework with comparison to self-play model and show that it outperforms this baseline.
Modeling and digital simulation of a back-to-back converter to integrate a variable speed generator using the openmodelica platform

This work presents the modeling steps of a back-to-back converter using the OpenModelica plata-form. OpenModelica is a free and open source environment based on the Modelica language for modeling, simulating, optimising and analysing complex dynamic systems. The main goal is the application of the developed converter model to integrate a variable speed generator into the main grid. The back-to-back converters and their controllers are modeled using the components and language available on the OpenModelica platform. Furthermore, all results were obtained with the OpenModelica simulation platform.
Meter-Scale Morphology and Stratigraphy of Phyllosilicate-rich Outcrops in Mawrth Vallis

Introduction: Phyllosilicates on Mars were first detected definitively by the OMEGA spectrometer [1]. OMEGA-based studies have identified phyllosilicate spectral signatures scattered across the lower martian latitudes, usually in Noachian outcrops of light-toned, layered materials [2,3]. The phyllosilicates detected by OMEGA have spectra consistent with those of aluminum, iron, and magnesium smectite clays. On Earth, clay minerals form most commonly at the planet’s surface, through interactions with liquid water in an alkaline-to-neutral environment sustained over a geologically significant period of time [4]. Martian phyllosilicates may have formed in a similar environment, which may have been more Earth-like than either the present, late Amazonian arid climate or the acidic environment likely present when sulfate minerals formed in the late Noachian or Hesperian [3,5,6]. Alternatively, the phyllosilicates could have formed through subsurface aqueous alteration of initially anhydrous Noachian layered deposits, which would permit a range of possible surface conditions. Determining which mechanism(s) formed the martian phyllosilicates could have significant implications for our understanding of the planet’s early climate. OMEGA spectra have been used to identify—and CRISM spectra have confirmed—two distinct phyllosilicate mineralogies in light-toned layered outcrops in and around Mawrth Vallis: Fe/Mg-rich smectite consistent with the spectrum of nontronite, and Al-rich smectite consistent with montmorillonite [2,7]. Mawrth Vallis is an outflow channel that cuts through Noachian cratered terrain in Western Arabia [8] before debouching into the Chryse basin at 26° N, 340° E (Figure 1). Several studies have interpreted the phyllosilicate outcrops there as part of an ancient sedimentary deposit predating the formation of Mawrth Vallis [7,9]; alternatively, it has been suggested that this deposit may post-date Mawrth Vallis [10].
Fabrication technology of PDMS based cylindrical and structured microchannels for LOC

Cylindrically shaped microchannels are still challenging in lab-on-a-chip applications because of more laminar flow of biological samples and reagents inside. A simple, cheap and flexible technology to fabricate cylindrical and structured microchannels in polydimethylsiloxane (PDMS) is presented here. We proposed an unconventional method, where photoresist of appropriate viscosity can be drawn into thin fibers of cylindrical shape at room temperature and formatted into various microfluidic channel templates. Also we present unique technology of patterning the prepared photoresist fiber by optical interference lithography. By embedding process of patterned photoresist fiber in liquid PDMS we obtained very interesting structured microchannels. The photoresist fibers and embossed PDMS microchannels exhibit excellent mechanical and surface characteristics suitable for microchannel structures and passive micromixers. Prepared microchannel structures are good candidates for using in different microfluidic and biomedical systems for simple integration on the PDMS based chips.
Optimization of vehicular node clustering process using evolutionary algorithms

Numerous methods are available for vehicular node clustering. These vehicular nodes in vehicular ad hoc Network (VANETs) move very fast. These nodes, on the basis of different parameters, are grouped together in same group called cluster. Elementary reason for creating vehicular cluster is to enable vehicles to communicate with each other. Cluster Heads (CHs) are selected in each cluster for managing the whole cluster. CH is liable for inter and intra cluster communication. Life time of each cluster is directly linked with the performance of network, moreover, the less number of clusters tend to more efficient network due the reduced communication overhead. Gray Wolf Optimization (GWO) is a technique based on the social behavior of gray wolves, a novel algorithm, for clustering in VANET, based on this technique is proposed in this paper. This algorithm delivers optimized solution for smooth and robust communication in the VANETs. The vital parameters which are kept under consideration in the proposed algorithm are grid size, load balance factor (LBF), the speed of the nodes, directions and transmission range. The ICGWO is compared by the tested method with the well-known meta-heuristics, Comprehensive Learning Particle Swarm Optimization (CLPSO) and Multi-Objective Particle Swarm Optimization (MOPSO) for VANETs. Experiments are performed by the varying the key parameters of the ICGWO. This is done for measuring the effectiveness of the proposed algorithm. The graphical results show that the proposed methodology is providing the optimized results as compare to competitors.
Stochastic tarot® model: Stocastic economic market model for risk evaluation of a regulated electricity distribution company

This document proposes the improvement of an economic model to evaluate the performance of electricity distribution companies considering the inherent risks of the sector. Through scenarios, the model proposes a stochastic evaluation of the variations in the expenditures made by the electric companies, such as operational costs of management, operation and maintenance, as well as the uncertainties associated to the consumer market model. Such variations can be, for example, consequences imposed by economic issues in the national scenario or due to environmental changes. As a result, the model enables the analysis of the economic risk of the company and the socioeconomic well-being produced by the energy distribution activity.
A modified incremental conductance algorithm for partially shaded PV array

For a partially shaded PV array there will be several peaks in the Maximum Power Point (MPP) characteristics. The conventional Incremental Conductance (INC) algorithm cannot extract global maximum power point during shading. Therefore the INC algorithm is slightly modified to extract global maximum point during worst atmospheric conditions. Hybrid Cuk converter performance is better compared to Cuk and boost converters. The algorithm is experiment on Hybrid Cuk converter. This paper presents the performance of Cuk converter by applying modified INC algorithm to generate the switching pulses to extract maximum power when the panel is partially shaded. The results of the modified algorithm are compared with basic incremental conductance algorithm.
Detection of fake followers using feature ratio in self-organizing maps

Detection of Fake followers has been a challenging task for the social media research community. Fake followers adopt varied methods to accomplish the goal. Identifying and modeling the behavior of fake followers is an interesting ongoing active research field. In this paper we propose a measure based on a computed feature ratio value to effectively isolate fake follower accounts from genuine users. A twitter dataset comprising of fake follower information has been used for the analytics presented in this paper. The artificial neural network referred to as Self-Organizing Map has been used for training and analysis of the Twitter fake follower dataset. The analysis presented demonstrates that the proposed metric is an efficient measure to cluster fake followers.
DFSA: A classification capability quantification method for human action recognition

Motion related human action recognition using wearable sensors can potentially enable various useful daily applications. So far, most studies view it as a stand-alone mathematical classification problem without considering the physical nature of human motions. Consequently, they suffer from data dependencies and encounter the disaster of dimension problem and the o1ver-fitting issue, and their models are never human-readable. In this study, we start from a deep analysis on natural physical properties of human motions, and then propose a useful feature selection method to quantify each feature's classification contribution capability. On one hand, the “disaster of dimension” problem can be avoid to some extent, due to the constrained dimension of key features; On the other hand, over-fitting issue can be eased since the knowledge implied in human motions are nearly invariant, which compensates the possible data inadequacy. The experiment results indicate that the proposed method performs superior to those adopted in related works, such as decision tree, k-NN, SVM, neural networks.