Miracle-dz/UniFAR-FTUs huggingface dataset:
Temperature and Rainfall Are Separate Agents of Selection Shaping Population Differentiation in a Forest Tree

Research highlights: We present evidence indicating that covariation of functional traits among populations of a forest tree is not due to genetic constraints, but rather selective covariance arising from local adaptation to different facets of the climate, namely rainfall and temperature. Background and Aims: Traits frequently covary among natural populations. Such covariation can be caused by pleiotropy and/or linkage disequilibrium, but also may arise when the traits are genetically independent as a direct consequence of natural selection, drift, mutation and/or gene flow. Of particular interest are cases of selective covariance, where natural selection directly generates among-population covariance in a set of genetically independent traits. We here studied the causes of population-level covariation in two key traits in the Australian tree Eucalyptus pauciflora. Materials and Methods: We studied covariation in seedling lignotuber size and vegetative juvenility using 37 populations sampled from throughout the geographic and ecological ranges of E. pauciflora on the island of Tasmania. We integrated evidence from multiple sources: (i) comparison of patterns of trait covariation within and among populations; (ii) climate-trait modelling using machine-learning algorithms; and (iii) selection analysis linking trait variation to field growth in an arid environment. Results: We showed strong covariation among populations compared with the weak genetic correlation within populations for the focal traits. Population differentiation in these genetically independent traits was correlated with different home-site climate variables (lignotuber size with temperature; vegetative juvenility with rainfall), which spatially covaried. The role of selection in shaping the population differentiation in lignotuber size was supported by its relationship with fitness measured in the field. Conclusions: Our study highlights the multi-trait nature of adaptation likely to occur as tree species respond to spatial and temporal changes in climate.
The Factors Affecting to Job Satisfaction on Non-Technical Employees Working at Power and Energy Sector in Sri Lanka

Employees are the backbone of any organization. They are the most precious and important asset among all the assets of any organization. The power and energy sector plays a vital role in sustaining the economic development of a country, so the employee job satisfaction becomes one of the priority in the power and energy sector. Therefore, the study aims to identify what are the major factors affecting to job satisfaction of non-technical employees in power and energy sector in Central Province in Sri Lanka with reference to Ceylon Electricity Board. All employees who are working in Ceylon Electricity board in Central Province where the population of the study and out of them 150 employees were selected as sample of the study based on stratified sampling technique. Further study result highlighted statistically significant impacts of pay and rewards, job security, working condition and recognition on employee job satisfaction in power and energy sector, however possibility of growth no longer make significant impacts on employee job satisfaction. Finally, study identified pay and rewards as a greatest explanatory variable of employee job satisfaction in Power and energy sector, in Sri Lanka
A POWER CONSERVATIVE UNDERWATER LOCALIZATION PROTOCOL

This paper introduces an algorithm to determine the position of wireless sensors operating in the underwater environment. It has been designed to improve the existing ones by limiting the use of power which is the most critical resource that shortens the active life of acoustic underwater sensor networks. The presented algorithm is analyzed by showing that its limit case is the well-known localization algorithm described in [1]. Index Terms — localization algorithms, underwater localization, power preservation, sensor networks
Efficient Management of Road Intersections for Automated Vehicles—The FRFP System Applied to the Various Types of Intersections and Roundabouts

In the last decade, automatic driving systems for vehicles circulating on public roads have become increasingly closer to reality. There is always a strong interest in this topic among research centers and car manufacturers. One of the most critical aspects is the management of intersections, i.e., who will have to go first and in what ways? This is the question we want to answer through this research. Clearly, the goal is to manage the intersection safely, making it possible to reduce road congestion, travel time, emissions, and fuel consumption as much as possible. The research is conducted by comparing a new management system with the systems already known in the state of the art for different types of intersections. The new system proposed by us is called FRFP (first to reach the end of the intersection first to pass). In particular, vehicles will increase or decrease their speed in collaboration with each other by making the right decision. The vehicle that can potentially reach the intersection exit first.
An Improved Method for Packed Malware Detection using PE Header and Section Table Information

Malware poses one of the most serious threats to computer information systems. The current detection technology of malware has several inherent constraints. Because signature-based traditional techniques embedded in commercial antiviruses are not capable of detecting new and obfuscated malware, machine learning algorithms are applied in identifing patterns of malware behavior through features extracted from programs. There, a method is presented for detecting malware based on the features extracted from the PE header and section table PE files. The packed files are detected and then unpacke them. The PE file features are extracted and their static features are selected from PE header and section tables through forward selection method. The files are classified into malware files and clean files throughs different classification methods. The best results are obtained through DT classifier with an accuracy of 98.26%. The results of the experiments consist of 971 executable files containing 761 malware and 210 clean files with an accuracy of 98.26%.
Contracting for Innovation: Defining and Exchange that Fosters Creativity While Mitigating Opportunism

We explore how firms govern exchanges that require innovation. Transaction cost economics focuses on the role of overcoming bounded rationality and mitigating opportunism when designing governance mechanisms such as contracts. While TCE is very powerful in illustrating how to prevent negative events during transactions, it is less able to explain how to design contracts that can help foster a strong positive environment that facilitates innovation. By incorporating insights from social psychology to complement TCE, we argue that firms can improve their chances to generate innovative outcomes in inter-firm transactions. Contracts can do more than simply eliminate negative outcomes and can help set a frame that can encourage a positive outcome. A major challenge occurs when a transaction involves a need for innovation and a significant exchange hazard. While innovation often leads firms to use more detailed task descriptions, because these can be framed in ways that don’t necessarily imply distrust or negative expectations, the presence of exchange hazards makes this framing challenge more difficult and leads firms to rely less on detailed task descriptions. We also explore how firms structure the payment mechanism in the contract to help foster the flexible, creative environment that is most suitable for innovation. We examine and find support for these effects in a sample of contracts from the information technology services industry.
ix-minute walk distance as parameter of functional utcome after pulmonary endarterectomy for chronic hromboembolic pulmonary hypertension

esults: The mean standard error of the mean 6-minute walk distance was 391 9 m. The 6-minute walk distance decreased in proportion to New York Heart ssociation functional class and correlated (all P .0001) with mean pulmonary rtery pressure (r 0.62), cardiac output (r 0.76), total pulmonary resistance r 0.75), mixed venous oxygen saturation (r 0.77), and brain natriuretic eptide (r 0.65). One year after pulmonary endarterectomy, the 6-minute walk istance increased from 417 19 m to 517 16 m (P .0001). The change from aseline in 6-minute walk distance correlated with the changes after 1 year in New ork Heart Association functional class (P .01) and brain natriuretic peptide (r .57, P .002), and with the observed hemodynamic changes directly after ulmonary endarterectomy (change in mean pulmonary artery pressure: r 0.52; hange in cardiac output: r 0.70; change in total pulmonary resistance r 0.70; ll P .001). In patients with residual pulmonary hypertension after pulmonary ndarterectomy, the 6-minute walk distance was significantly lower than in hemoynamically normalized patients. However, the absolute increase in the 6-minute alk distance was higher in patients with residual pulmonary hypertension (137 6 m and 82 20 m, respectively; P .03).
Resonance Damping and Parameter Design Method for LCL-LC Filter Interfaced Grid-Connected Photovoltaic Inverters

In order to attenuate PWM harmonics effectively and reduce filter cost and volume, LCL-LC filter is proposed using a combination of LCL filter and an LC series resonant part. Compared with LCL filter, LCL-LC filter is characterized with decreased total inductance and better switch-frequency harmonics attenuation ability, but the resonant problem affects the system stability remarkably. In this paper, active damping based on the capacitor voltage feedback is proposed using the concept of the equivalent virtual impedance in parallel with the capacitor. With the consideration of system delay, this paper presents a systematic design method for the LCL-LC filtered grid-connected photovoltaic (PV) system. With this method, controller parameters and the active damping feedback coefficient are easily obtained by specifying the system stability and dynamic performance indices, and it is more convenient to optimize the system performance according to the predefined satisfactory region. Finally, the simulation results are presented to validate the proposed design method and control scheme. Keywords—active damping; grid-connected photovoltaic (PV) converter; LCL-LC filter; proportional resonant (PR) controller;
A Configurable Software Aging Detection and Rejuvenation Agent for Android

This paper presents the design of ADaRTA, an aging detection and rejuvenation tool for Android. The tool is a software agent which i) performs selective monitoring of system processes and of trends in system performance indicators; ii) detects the aging state and estimates the time-to-aging-failure, through heuristic rules; iii) schedules and applies rejuvenation, based on the estimated time-to-aging-failure. The agent rules and parameters have been defined for ease of configuration and tuning by device designers. A stress testing experiment is discussed, showing ADaRTA's configurability for the device under test, and the ability of detecting the aging state to prevent device enter a failure state.
Modelling HSV-2 transmission dynamics with risk factor∗

The prevalence of herpes simplex virus type 2 (HSV-2) is on the rise within the general population and no perfect vaccine has been found yet. In this paper, a mathematical model for the spread of HSV-2 is developed and analysed. The impact of counselling/educational campaigns, vaccination and treatment are examined. The disease free equilibrium has been shown to be globally asymptotically stable when the reproduction number is less than unity. Furthermore, by the Krasnoselskii sub-linearity trick and the Lyapunovs functional approach we managed to show the local and global stability of the endemic equilibrium respectively. Results from the study suggest that vaccination of more high risk susceptible individuals with a vaccine of high efficacy would be crucial in combating HSV-2 epidemic. Further, we applied optimal control theory to the proposed model. The optimal control is characterised and numerically solved. Overall, the application of optimal control theory in the study suggests that, more effort should be devoted to vaccination and treatment.
Frontiers in Dentistry

Article type: Original Article Objectives: Myofascial pain dysfunction syndrome (MPDS) is the most common form of temporomandibular disorders. Because of the multifactorial nature of the problem, its management usually involves several treatment modalities to maximize their synergistic effects. This randomized clinical trial aimed to assess the efficacy of low-level laser therapy (LLLT) and transcutaneous electrical nerve stimulation (TENS) as an adjunct to pharmaceutical therapy for treatment of MPDS. Materials and Methods: This clinical trial evaluated 108 MPDS patients. First, the initial pain intensity of patients was determined using a visual analogue scale (VAS). The first phase of the study included education, awareness, self-care, behavior and relaxation therapy. After 1 month, the pain score was measured again using VAS. Patients who acquired a pain score >1 were divided into three groups of LLLT with diode (GAAlAr) laser with 0.2 W power, TENS, and control, using block randomization. All groups received 10 mg fluoxetine once daily, 0.25 mg clonazepam once daily and 10 mg baclofen three times a day. ANOVA was used to compare the recovery rate of the three groups. Results: Pain in the trapezius muscle and pain on mouth opening resolved faster in the laser + medication group. The recovery rate was faster in the mean muscle pain, general pain reported by patients, pain in the masseter and pterygoid muscles and pain and limitation in lateral movements in both laser + medication and TENS groups. Conclusion: Combination of LLLT and TENS with medication accelerated pain relief and resolved movement restrictions in MPDS patients. (IRCT registration number: IRCT201411113144N4)
E-learning readiness among faculty members of medical sciences universities and provide strategies to improve it

Background: The competence of faculty in conducting e-learning is one of the preconditions for e-learning implementation in a university. This study aimed at investigating the readiness of the faculty members of Ardabil University of Medical Sciences (ARUMS) to have e-learning. Methods: To fulfil this purpose, a triangulation method has been used. In the quantitative section, based on the Technological Pedagogical Content Knowledge (TPACK) model, the faculty competence in conducting e-learning has been measured in four areas: pedagogical knowledge, technological knowledge, content knowledge, and finally the skill of combiningpedagogical knowledge, technological knowledge, and content knowledge. Subsequently,with the qualitative data of the semi-structured interview, the findings of the research have been explained. Finally, the strategies for improving the readiness of ARUMS faculty have been identified in e-learning. Results: One-sample t test with a significant level (P ≤ 0.5) showed that the faculty e-learning of ARUMS had the highest mean of pedagogical knowledge, content knowledge and content pedagogical knowledge respectively. In other words, the faculty had a high level of pedagogical,content and content-pedagogical knowledge, but they need to improve their technological,technological-content, technological-pedagogical and ultimately, technological-pedagogical content knowledge. Conclusion: That is why, in order to have effective e-learning at ARUMS, the faculty has to improve their technological, technological-content, technological-pedagogical and technological-pedagogical-content knowledge. In this regard, several solutions have been proposed in this paper.
An Air Traffic Control Model Based Local Optimization over the Airways Network

The introduction of a new SESAR scenario in the European Airspace will impact the functioning and the performances of the current Air Traffic Management (ATM) System. The understanding of the features and the limits of the current system could be crucial in order to improve and design the structure of the future ATM. In this paper we present some results of the “Assessment of Critical Delay Patterns and Avalanche Dynamics” PhD project from the ComplexWorld Network. During this project we developed a model of Air Traffic Control (ATC) based on Complex Network theory capable of reproducing the features of the real ATC in three European National Airspaces. We then developed an optimization algorithm based on “Extremal Optimization” in order to build efficient and globally optimized planned trajectories. The ATC model is applied in order to study the efficiency of this new planned trajectories when subject to external perturbations and to compare them to the current situation.
Universal Trajectory Synchronization for Highly Predictable Arrivals Enabled by Full Automation

One of the greatest challenges that the future ATM system will need to face in the next decades is the integration of new airspace users and the continuous increase in delegating capacity and safety critical traffic management functions to automated systems. The accommodation of these new airspace users, which will have to coexist with conventional users, a widely reorganized airspace and the increased level of automation will necessarily need a paradigm shift with regard to the trajectory management functions already foreseen in the SESAR master plan for 2020. The objective of the UTOPIA project is to provide a better understanding of which trajectory management functions will be needed to deal with heterogeneous traffic when those functions are executed by autonomous ATM systems (and humans involved in the decision and execution of the air traffic management actions). In particular, the study executed in this project will focus on the data models, synchronization requirements and algorithms needed to ensure the safe management of merging traffic in an extended TMA, executed by an autonomous arrival management function acting as separator. The converging flows of traffic that will be studied comprise heterogeneous airborne systems, in particular, unmanned airvehicles and advanced and legacy flight management systems, representing airspace users with different synchronization capabilities. Keywords-heterogenous traffic, arrival management, formal languages, disruption, uncertainty, synchronization, multidimensional trajectory,
Markerless landmark localization on body shape scans by non-rigid model fitting

We present a method of localizing anatomical landmarks on the human body by fitting a template mesh model to individual scans. The template is created from a corpus of body scans, and then registered onto individual scans using a non-rigid variant of iterative closest point (ICP) techniques. The proposed algorithm is robust against such defects as incomplete body parts and presence of background objects, and capable of generating a high-resolution mesh model without large geometric distortion. To evaluate the performance of the proposed system, 1) the template models of Japanese female and male were created from the AIST/HQL Anthropometric Database 2003, 2) the average error in the estimated landmark positions were examined using a different dataset, and 3) the accuracy and reliability of the landmark positions were evaluated according to the criteria specified in ISO 20685. The experiments confirm that the accuracy depends on landmarks, and fifty-six landmarks out of sixty-four can be localized within allowable error variations.
Thermal Analysis and Operational Characteristics of an AlGaN/GaN High Electron Mobility Transistor with Copper-Filled Structures: A Simulation Study

In this study, we investigated the operational characteristics of AlGaN/GaN high electron mobility transistors (HEMTs) by applying the copper-filled trench and via structures for improved heat dissipation. Therefore, we used a basic T-gate HEMT device to construct the thermal structures. To identify the heat flow across the device structure, a thermal conductivity model and the heat transfer properties corresponding to the GaN, SiC, and Cu materials were applied. Initially, we simulated the direct current (DC) characteristics of a basic GaN on SiC HEMT to confirm the self-heating effect on AlGaN/GaN HEMT. Then, to verify the heat sink effect of the copper-filled thermal structures, we compared the DC characteristics such as the threshold voltage, transconductance, saturation current, and breakdown voltage. Finally, we estimated and compared the lattice temperature of a two-dimensional electron gas channel, the vertical lattice temperature near the drain-side gate head edge, and the transient thermal analysis for the copper-filled thermal trench and via structures. Through this study, we could optimize the operational characteristics of the device by applying an effective heat dissipation structure to the AlGaN/GaN HEMT.
EV Charging Behavior Analysis Using Hybrid Intelligence for 5G Smart Grid

With the development of the Internet of Things (IoT) and the widespread use of electric vehicles (EV), vehicle-to-grid (V2G) has sparked considerable discussion as an energy-management technology. Due to the inherently high maneuverability of EVs, V2G systems must provide on-demand service for EVs. Therefore, in this work, we propose a hybrid computing architecture based on fog and cloud with applications in 5G-based V2G networks. This architecture allows the bi-directional flow of power and information between schedulable EVs and smart grids (SGs) to improve the quality of service and cost-effectiveness of energy service providers. However, it is very important to select an EV suitable for scheduling. In order to improve the efficiency of scheduling, we first need to determine define categories of target EV users. We found that grouping on the basis of EV charging behavior is one effective method to identify target EVs. Therefore, we propose a hybrid artificial intelligence classification method based on the charging behavior profile of EVs. Through this classification method, target EVs can be accurately identified. The results of cross-validation experiments and performance evaluations suggest that this method is effective.
Perpetual Voting: Fairness in Long-Term Decision Making

In this paper we introduce a new voting formalism to support long-term collective decision making: perpetual voting rules. These are voting rules that take the history of previous decisions into account. Due to this additional information, perpetual voting rules may offer temporal fairness guarantees that cannot be achieved in singular decisions. In particular, such rules may enable minorities to have a fair (proportional) influence on the decision process and thus foster long-term participation of minorities. This paper explores the proposed voting rules via an axiomatic analysis as well as a quantitative evaluation by computer simulations. We identify two perpetual voting rules as particularly recommendable in long-term collective decision making.