Miracle-dz/UniFAR-FTUs huggingface dataset:
Household Willingness to Pay for Forest Ecological Restoration in Giant Panda Habitats: A Discrete Choice Experiment

Rural households have played an increasingly significant role in the conservation and restoration process of natural habitats. This paper explores rural households’ preference and willingness to pay for ecological restoration attributes in giant panda habitats using the discrete choice experiment (DCE). The DCE survey was conducted in and around giant panda habitats in Sichuan province with a sample size of 474. Using the mixed logit model, the results indicate that rural households have positive attitudes towards the improvement of ecological restoration functions, including forest vegetation restoration, biodiversity conservation, and giant panda corridor construction, but have a negative attitude towards payment, showing that rural households are inclined to pay less to gain better restoration outcomes. Among the ecological restoration attributes, forest vegetation restoration (4.44 RMB) wins the highest payment value, indicating households’ preferences and priorities of ecological restoration. In general, rural households’ willingness to pay could reach 34.28 RMB for the best choice option designed in DCE. This study emphasizes the awareness of payment among rural households to improve ecological restoration functions in giant panda habitats and indicates the importance of household participation in long-term adaptation and implementation of ecological conservation plans.
Road safety and accident prevention in India: a review

Road accidents are a human tragedy. They involve high human suffering and monetary costs in terms of untimely deaths, injuries and loss of potential income. Although we have undertaken many initiatives and are implementing various road safety improvement program the overall situation as revealed by data is far from satisfactory. During the calendar year 2010, there were close to 5 lakh road accidents in India, which resulted in more than 1.3 lakh persons. These numbers translate intone road accident every minute, and one road accident death every 4 minutes. Unfortunately, more than half the victims are in the economically active age group of 25-65 years. The loss of the main bread winner can be catastrophic. Road traffic accidents are amenable to remedial action. Many a countries have curbed the menace of road accidents by adopting a multipronged approach to road safety that encompasses broad range of measures, such as, traffic management, design and quality of road infrastructure, application of intelligent transport system, safer vehicles, law enforcement, effective and quick accident response and care etc. The Government alone cannot tackle road safety problems. There is a need for active involvement of all stake- holders to promote policy reform and implementation of road safety measures. Addressing road safety is comprehensive manner underscores the need to involve multiple agencies and sectors like health, transport and police. The present study provides the magnitude and various dimensions of road accident in India. The analysis on road accidents in this study will help to create awareness, guidelines and assist in informed decision making on road safety. Language: en
Regeneración in vitro de brotes de Polianthes tuberosa L. a partir de yemas vegetativas de la inflorescencia y de tejido de cormo

Tuberose ( Polianthes tuberosa L. ) is a plant endemic to Mexico, commercially grown for cut flower, and is also used in pharmaceutical and perfume industries. Traditionally, producers propagate this plant using corms, being this cause of the present little genetic variability in the crop and possibly for this reason only cultivars white flowers are known. The objective of this research was to develop a practical and economical method for the regeneration of plantlets from vegetative of the inflorescence and corm. Small buds and corm tissue segments were placed on the surface of the culture medium base GC (personal comunication Guillermo Carrillo), containing inorganic salts of Murashige and Skoog (1962) and also having per liter 50 mL of coconut water, 20 g of sucrose, 6.4 g of agar, being the pH adjusted to 5.7. With this basic medium were prepared a series of culture media containing benzylaminopurine (BAP), naphthaleneacetic acid (NAA), 2,4-dichlorophenoxyacetic acid (2,4-D), indole acetic acid (IAA), and kinetin. The shoot formation that gave rise to small plantlets occurred through the direct regeneration of the flower bud which to grow a plantlets arising only from base of the bud From this region were obtained up to six buds in medium containing BAP, 4.5 mg and NAA, 0.1 mg, being the regeneration of buds higher (56.1%). Corm if the contamination problem was in some cases up to 100% of the cultures. It is important to highlight the importance of achieving massive regeneration in vitro tuberose plant from flower bud
The complete chloroplast genome of Sedum tricarpum Makino. (Crassulaceae)

Abstract Sedum tricarpum Makino. , is a perennial succulent herb, which was first discovered and established as a new species ten years ago. Here, we report the complete chloroplast genome of S. tricarpum. It shows a typical quadripartite structure with a total length of 149,349 bp, including the large single-copy region (LSC) of 81,644 bp, the small single-copy region (SSC) of 16,643 bp, and two separated inverted regions (IRs) of 25,531 bp, respectively. For the whole genome, there are a total of 131 genes, including 85 protein-coding genes (PCGs), 8 rRNA genes, and 37 tRNA genes. The overall GC content of the cp genome is 37.8%. A well-supported phylogenetic tree revealed monophyly formed by S. tricarpum and S. sarmentosum, suggesting a relatively closer phylogenetic relationship with the clade consisting of S. lineare and Graptopetalum amethystinum. The complete chloroplast genome of S. tricarpum provides valuable information for further phylogenetic reconstruction of the Crassulaceae family.
Personalized and Explainable Employee Training Course Recommendations: A Bayesian Variational Approach

As a major component of strategic talent management, learning and development (L&D) aims at improving the individual and organization performances through planning tailored training for employees to increase and improve their skills and knowledge. While many companies have developed the learning management systems (LMSs) for facilitating the online training of employees, a long-standing important issue is how to achieve personalized training recommendations with the consideration of their needs for future career development. To this end, in this article, we present a focused study on the explainable personalized online course recommender system for enhancing employee training and development. Specifically, we first propose a novel end-to-end hierarchical framework, namely Demand-aware Collaborative Bayesian Variational Network (DCBVN), to jointly model both the employees’ current competencies and their career development preferences in an explainable way. In DCBVN, we first extract the latent interpretable representations of the employees’ competencies from their skill profiles with autoencoding variational inference based topic modeling. Then, we develop an effective demand recognition mechanism for learning the personal demands of career development for employees. In particular, all the above processes are integrated into a unified Bayesian inference view for obtaining both accurate and explainable recommendations. Furthermore, for handling the employees with sparse or missing skill profiles, we develop an improved version of DCBVN, called the Demand-aware Collaborative Competency Attentive Network (DCCAN) framework, by considering the connectivity among employees. In DCCAN, we first build two employee competency graphs from learning and working aspects. Then, we design a graph-attentive network and a multi-head integration mechanism to infer one’s competency information from her neighborhood employees. Finally, we can generate explainable recommendation results based on the competency representations. Extensive experimental results on real-world data clearly demonstrate the effectiveness and the interpretability of both of our frameworks, as well as their robustness on sparse and cold-start scenarios.
Soultz-sous-Forêts Geothermal Reservoir: Structural Model Update and Thermo-Hydraulic Numerical Simulations Based on Three Years of Operation Data

The geothermal powerplant of Soultz-sous-Forêts (France) is investigating the possibility of producing more energy with the same infrastructure by reinjecting the geothermal fluid at lower temperatures. Indeed, during the operation of the powerplant, the geothermal fluid is currently reinjected at 60–70 °C in a deep fractured granite reservoir, and the MEET project aims to test its reinjection at 40 °C. A 3D hydrothermal study was performed in order to evaluate the spreading of the thermal front during colder reinjection and its impact on the production temperature. In the first step, a 3D structural model at fault scale was created, integrating pre-existing models from 2D vintage seismic profiles, vertical seismic profiles, seismic cloud structure and borehole image logs calibrated with well data. This geometrical model was then adapted to be able to run hydrothermal simulation. In the third step, a 3D hydrothermal model was built based on the structural model. After calibration, the effect of colder reinjection on the production temperature was calculated. The results show that a decrease of 10 °C in the injection temperature leads to a drop in the production temperature of 2 °C after 2 years, reaching 3 °C after 25 years of operation. Lastly, the accuracy of the structural model on which the simulations are based is discussed and an update of the structural model is proposed in order to better reproduce the observations.
Solar cell array design handbook, volume 1

Twelve chapters discuss the following: historical developments, the environment and its effects, solar cells, solar cell filters and covers, solar cell and other electrical interconnections, blocking and shunt diodes, substrates and deployment mechanisms, material properties, design synthesis and optimization, design analysis, procurement, production and cost aspects, evaluation and test, orbital performance, and illustrative design examples. A comprehensive index permits rapid locating of desired topics. The handbook consists of two volumes: Volume 1 is of an expository nature while Volume 2 contains detailed design data in an appendix-like fashion. Volume 2 includes solar cell performance data, applicable unit conversion factors and physical constants, and mechanical, electrical, thermal optical, magnetic, and outgassing material properties. Extensive references are provided.
Improvement of satellite conflict prediction reliability through use of the adaptive splitting technique

Collision between satellites and debris is a rare event but with high financial consequences. This risk therefore has to be addressed carefully. To support the decision to start a collision avoidance maneuver, a dedicated tool to characterize the risk uncertainty is the probability of collision between the debris and the satellite. 1 Crude Monte Carlo could be a way if it could cope with very small probabilities, say 10−6, within the available simulation budget and time. The methodology nowadays in use is a numerical integration made tractable by physical hypothesis and numerical approximation. 2 We advocate the adaptive splitting technique, presented in Cérou et al., 3 as it avoids all the hypothesis needed for the numerical integration and clearly outperforms Crude Monte Carlo with respect to rare events. A direct comparison between Crude Monte Carlo and adaptive splitting technique approach is also given on real-life examples.
SMART GRID: POWER GRID OF FUTURE

The power sector across the world is facing numerous challenges including generation diversification, demand for reliable and sustainable power supply, energy conservation and reduction in carbon emission. It is evident that such critical issues cannot be addressed within the confines of the existing electricity grid. Smart Grid is next generation digitally enhanced power system assimilating concepts of modern communications and control technologies which allows much greater robustness, efficiency and flexibility than today’s power systems. As smart grid is identified as solution to various challenging problems of power system, so aspects regarding its implementation are important. A smart grid impacts all the components of a power system especially the distribution level.
A System Transferability Questionnaire (STQ)

The usability of a multiple device system largely depends on the ease of which users can transfer between using different devices. This paper is aimed at constructing a System Transferability Questionnaire (STQ) to effectively measure the subjective transferability of a multiple device system. Theoretical rationale and approach to develop the questionnaire were presented. A software usability study was conducted to test the STQ. Results showed that STQ helps to capture four factors regarding transferability, which are transfer experience (TE), overall experience (OE), consistency perception (CP) and functionality perception (FP). Users were more satisfied with OE (M=5.11 out of 7) and FP (M=5.20), as compared to TE (M=4.28) and CP (M=3.54), indicating redesign is necessary to improve the transferability of the two-software system.
Stabilization of a Cart-Inverted Pendulum with Interconnection and Damping Assignment Passivity-Based Control Focusing on the Kinetic Energy Shaping

Interconnection and damping assignment passivity-based control (IDA-PBC) is a nonlinear control method which stabilize a system shaping its total energy and utilizing passivity. In previous studies, IDA-PBC is shown to be a powerful method to stabilize underactuated mechanical systems. However, the transient performances tend to be slow. In this study, to improve the slow responses and realize fast transient ones, the IDA-PBC is applied for a cart-inverted pendulum and free parameters in a closed-loop inertia matrix which have not been used in the previous studies are utilized. This means modifying the kinetic energy more actively. On the other hand, the additional use of the free parameters makes the selection of them more complicated because several assumptions must be satisfied to derive an IDA-PBC controller. To deal with this problem, we also propose a systematic method to select them graphically from a simple two dimensional region. Finally, we show that the transient performances of the IDA-PBC can be as fast as the LQR with the active modification of the kinetic energy. The IDA-PBC with suitable parameters also theoretically estimates as large domain of attraction as the upper half plane preserving the fast transient performances.
An explainable Artificial Intelligence approach to study MCI to AD conversion via HD-EEG processing

An explainable Artificial Intelligence (xAI) approach is proposed to longitudinally monitor subjects affected by Mild Cognitive Impairment (MCI) by using high-density electroencephalography (HD-EEG). To this end, a group of MCI patients was enrolled at IRCCS Centro Neurolesi Bonino Pulejo of Messina (Italy) within a follow-up protocol that included two evaluations steps: T0 (first evaluation) and T1 (three months later). At T1, four MCI patients converted to Alzheimer’s Disease (AD) and were included in the analysis as the goal of this work was to use xAI to detect individual changes in EEGs possibly related to the degeneration from MCI to AD. The proposed methodology consists in mapping segments of HD-EEG into channel-frequency maps by means of the power spectral density. Such maps are used as input to a Convolutional Neural Network (CNN), trained to label the maps as “T0” (MCI state) or “T1” (AD state). Experimental results reported high intra-subject classification performance (accuracy rate up to 98.97% (95% confidence interval: 98.68–99.26)). Subsequently, the explainability of the proposed CNN is explored via a Grad-CAM approach. The procedure detected which EEG-channels (i.e., head region) and range of frequencies (i.e., sub-bands) were more active in the progression to AD. The xAI analysis showed that the main information is included in the delta sub-band and that, limited to the analyzed dataset, the highest relevant areas are: the left-temporal and central-frontal lobe for Sb01, the parietal lobe for Sb02, the left-frontal lobe for Sb03 and the left-frontotemporal region for Sb04.
Time-domain measurements of the electromagnetic backscatter of pyramidal absorbers and metallic plates

A wideband time-domain measurement system has been developed for the evaluation of the backscatter performance of dissipative macrostructures. Backscatter measurements have been performed in an ordinary room environment on metal plates as well as samples of pyramidal absorbing material. The backscattering performance of pyramidal absorbers is evaluated in the 50- to 1000-MHz frequency range with a varying incident field angle of incidence. In the case of rectangular metal plates, numerically generated results are compared with measured data in order to gauge the accuracy of the system. >
Modeling and Concept Evaluation of a Hybrid Drivetrain System

Energy efficiency and performance optimization are two important aspects in any construction and agricultural machine development. Most construction machines are designed for specific tasks and have repetitive work cycles. Analyzing these work cycles from a component level, it is possible to identify various opportunities in a cycle to capture energy that would otherwise have been wasted. This research focuses on strategies to develop a regenerative energy capture system to harness this otherwise wasted energy
Dead-time effect and compensations of three-level neutral point clamp inverters for high-performance drive applications

Due to the use of high-power devices and slow-switching frequency in a three-level neutral point clamp inverter, the dead-time effect may not be compensated sufficiently fast by using methods developed for the two-level inverter. In this paper, the dead-time effect in a three-level inverter with snubber circuits is analyzed to reveal that it does not only depend on load current direction, but also on magnitude. The snubber network also plays an important role in determining the output phase voltage during the dead-time period. Software techniques are proposed to compensate the dead-time effect as soon as it occurs as demanded by the slow-switching frequency. Experimental results show their effectiveness.
The potential counter effect of COVID-19 outbreak on an antimicrobial agents prescribing educational intervention.

INTRODUCTION Educational interventions targeting health care professionals can contribute to improving knowledge and behaviors of antimicrobial agents prescribing. However, the unprecedented COVID-19 outbreak caused a disruption of the current practices and treatment guidelines. Therefore, it is highly likely that the pandemic had its disruptive effect on any educational interventions that were going on during the outbreak. This study aims to evaluate the effectiveness of an educational intervention in improving antimicrobial agents prescribing. METHODOLOGY This was a randomized controlled study that included 69 resident physicians in a teaching hospital. The intervention group received an educational intervention focusing on antimicrobial agents prescribing and resistance. Before and after the intervention, outpatient antimicrobial agents prescribing rates for the two study arms were compared for the pre- and post-intervention periods. Additionally, all participants were asked to complete an online questionnaire that measured their knowledge, attitudes and behavioral intention towards antimicrobial agents resistance and prescription. The post-intervention period included the months of February, March, and June 2020. April and May were excluded from the study period since clinics were closed due to the COVID -19 pandemic. RESULTS Post-intervention, the rate of antimicrobial agents prescribing by the intervention group was significantly higher than that of the control group (p < 0.001). Mean fear score for the intervention group was significantly lower than that for the control group after the intervention. CONCLUSIONS Findings indicate failure of the educational intervention in improving antimicrobial agents prescribing. However, an unexpected counter effect of the COVID-19 outbreak is highly likely.
Effect of Project-Based, Demonstration and Lectur e Teaching Strategies on Senior Secondary Students' Achievement in an Aspect of Agricultural Science

This study investigated the effect of three teaching strategies; project-based, demonstration and lecture strategies of teaching on students' achievement in pasture and forage crops which is an aspect of agricultural science. Lecture strategy served both as a teaching strategy as well as control since it is assumed to be a conventional strategy of teaching. A 3X2X2 pre-test, posttest experimental design with a control group was used in which a hundred and fifty randomly selected Senior Secondary School II (SSS II) Agricultural science students were drawn from three schools. The data was analyzed using ANCOV A and Scheffe posthoc test analysis. There is significant main effect of treatment on students' achievement in an aspect of agricultural science that is, pasture and forage crops (F = 20.860; p 0.05). Project-based and demonstration strategies of teaching are 2, 137
Object Recognition Based on Wave Atom Transform

This study presents an efficient method for recognizing object in an image based on Wave Atom Trans- form (WAT). Object recognition is achieved by extracting the energies from all coefficients of WAT. The original image is decomposed by using the WAT. All coefficients are considered as features for the classification process. The extracted features are given as an input to the K-Nearest Neighbor (K-NN) classifier to recognize the object. The evaluation of the system is carried on using Columbia Object Image Library Dataset (COIL-100) database. The classification performance of the proposed system is evaluated by using classification rate in percentage, which is achieved by varying the angle between the views.