Miracle-dz/UniFAR-FTUs huggingface dataset:
Revisited Molecular Phylogeny of the Genus Sphaerotheca (Anura: Dicroglossidae): The Biogeographic Status of Northernmost Populations and Further Taxonomic Changes

Heretofore, the populations of the genus Sphaerotheca Günther, 1859 (Dicroglossidae) in their northern and western borders laying in Pakistan have been assigned to two species, S. breviceps (Schneider, 1799) and S. strachani (Murray, 1884). The genus originated in the Oriental zoogeographic region and comes to close geographic proximity with the Palearctic region in Pakistan. The recent molecular studies have on one hand restricted the distribution range of S. breviceps to the eastern coastal plains of India and, on the other hand, revealed the northern- and westernmost population in India as a separate species, S. pashchima Padhye et al., 2017. This species has recently been synonymized with S. maskeyi (Schleich and Anders, 1998). These taxonomic changes, however, warranted the need for validation of Pakistani Sphaerotheca based on genetic data. We sequenced and analyzed 16S rRNA mitochondrial gene from specimens originating from the Himalayan foothills of Pakistan and compared these with all available GenBank sequences of the genus. Based on this data, we conclude that the Himalayan foothills of Pakistan are occupied by S. maskeyi. Simultaneously, we bring the first record of this species for the Palearctic region. We further suggest that more genetic material from across Pakistan is required to ascertain the validity of S. strachani and for the phylogeographic evaluation of western and northern border populations of the genus. Our geographically wide and revisited molecular phylogeny shows that the genus exhibits genetic diversity suggesting further taxonomic changes. The low level of genetic divergences between S. breviceps and S. magadha Prasad et al., 2019 compared to other species of the genus, indicates that the taxonomic status of S. magadha is questionable. Moreover, we found that S. magadha and S. swani (Mayers and Leviton, 1956) are genetically conspecific with S. breviceps and both should be thus considered its junior synonyms. On the other hand, S. dobsonii and populations from Myanmar need further detailed investigations.
End-to-End Deep Neural Network Architectures for Speed and Steering Wheel Angle Prediction in Autonomous Driving

The complex decision-making systems used for autonomous vehicles or advanced driver-assistance systems (ADAS) are being replaced by end-to-end (e2e) architectures based on deep-neural-networks (DNN). DNNs can learn complex driving actions from datasets containing thousands of images and data obtained from the vehicle perception system. This work presents the classification, design and implementation of six e2e architectures capable of generating the driving actions of speed and steering wheel angle directly on the vehicle control elements. The work details the design stages and optimization process of the convolutional networks to develop six e2e architectures. In the metric analysis the architectures have been tested with different data sources from the vehicle, such as images, XYZ accelerations and XYZ angular speeds. The best results were obtained with a mixed data e2e architecture that used front images from the vehicle and angular speeds to predict the speed and steering wheel angle with a mean error of 1.06%. An exhaustive optimization process of the convolutional blocks has demonstrated that it is possible to design lightweight e2e architectures with high performance more suitable for the final implementation in autonomous driving.
Using a Hybrid Recommending System for Learning Videos in Flipped Classrooms and MOOCs

New challenges in education require new ways of education. Higher education has adapted to these new challenges by means of offering new types of training like massive online open courses and by updating their teaching methodology using novel approaches as flipped classrooms. These types of training have enabled universities to better adapt to the challenges posed by the pandemic. In addition, high quality learning objects are necessary for these new forms of education to be successful, with learning videos being the most common learning objects to provide theoretical concepts. This paper describes a new approach of a previously presented hybrid learning recommender system based on content-based techniques, which was capable of recommend useful videos to learners and lecturers from a learning video repository. In this new approach, the content-based techniques are also combined with a collaborative filtering module, which increases the probability of recommending relevant videos. This hybrid technique has been successfully applied to a real scenario in the central video repository of the Universitat Politècnica de València.
Corrosion Resistance of Open Die Forged Austenitic Stainless Steel Samples Prepared with Different Surfaces

The use of corrosion-resistant metal materials in highly aggressive environments contributes to the preservation of the environment because it reduces the use of protective agents and coatings. Most metal objects are produced by some metal-forming process. It is well-known that plastic deformation affects the corrosion resistance of different metal materials in different ways. As a rule, austenitic stainless steels show a positive impact of plastic deformation on corrosion resistance, especially when hot deformed with protective surface oxide layers. However, most research carried out on these metals involves a carefully prepared surface which is either finely ground or polished. This paper investigates the corrosion resistance of cold-formed (open die forged) austenitic stainless steel in three different surface states for three different degrees of deformation. In doing so, we simulate possible damage to the treated surface and evaluate the stability of the material with respect to corrosion. Good corrosion resistance is shown for all three stages of deformation and for all three surface states, with some differences in the obtained results. Although the polished surface shows the highest corrosion resistance, as expected, the other two surfaces also demonstrate good results when exposed to aggressive environments. All of the results were statistically processed and presented. The results demonstrate the high usability of such materials in corrosion-aggressive environments with minimal danger of corrosion and minimal need to include additional surface protection agents, even against possible surface damage.
Tuning the Mesopore Size of Titania Thin Films Using a Polymeric Swelling Agent

A method is reported to generate mesoporous titania thin films with large pores and large surface areas by adding poly(propylene glycol), PPG, to the coating sol of films prepared by templating with Pluronic surfactant P123. Because P123 has an average structure (PEO)20(PPO)70(PEO)20 where PEO is a poly(ethylene oxide) unit and PPO is a poly(propylene oxide) unit, the hypothesis underlying this work is that PPG segregates to the PPO domains to induce swelling of the template micelles. With the introduction of PPG, the final calcined films are observed to have well-defined mesoporous structures, although the degree of long-range order diminishes with added PPG. The mesopore size of the films increases with increasing amounts of PPG, but PPG also introduces smaller mesopores into the films under our synthesis conditions to generate a bimodal pore size distribution. The size of these smaller pores remains nearly constant at ∼2.4 nm over a large range of PPG:P123 mass ratios, even as the larger mesopore size .
Putting knowledge to work: the combined role of marketing and sales employees' knowledge and motivation to produce superior customer experiences

Purpose This paper aims to adopt a contextual approach to the knowledge-performance linkage by deepening into the role of marketing and sales employees’ knowledge resources in the generation and delivery of superior customer experiences (CEs) and into the motivational antecedents of knowledge acquisition and development. Design/methodology/approach To gather information about the variables studied in this research, a survey was conducted among Spanish firms with at least 100 employees, resulting in a representative sample of 346 companies. Structural equation modeling based on partial least squares was then applied to test the hypothesized relationships. Findings The results show that employees’ motivation (and especially intrinsic motivation) affects CE both directly and indirectly through its influence on marketing-specific human capital. More precisely, customer knowledge and different types of marketing-related skills (creativity, targeting, problem-solving, social media management and communication skills) are the only constituents of marketing-specific human capital that significantly affect relative CE performance (i.e. performance vis-à-vis competitors), while product/service and market knowledge do not play a relevant role. Originality/value The results contribute both to the knowledge management and intellectual capital literatures by highlighting the motivational levers of human capital in the context of the marketing and sales function and the specific types of employee knowledge resources that induce superior CEs. Consequently, marketing and sales managers are provided with useful guidance to shape their human resource management policies and to establish their knowledge priorities.
Electro-structural analysis and optimization studies of laminated composite beam energy harvester

Abstract Modern ambient energy harvesters meet the micropower demands of the industrial sensors and communication hardware. Optimum design of such systems to maximize the power output is, therefore, of vital importance. This paper presents a multi-objective optimization methodology of smart laminated composite beam energy harvester by considering different geometric parameters. A typical multilayer carbon-epoxy composite beam with unimorph piezoelectric configuration is analyzed with finite element model. The coupled electro-mechanical effects are considered and the resultant free vibration solution is validated with that of a three-dimensional model. The structural response and power density of the base excited beam are obtained by varying thickness ratio of piezo layer, composite lamination sequence, number of layers, circuit resistance, piezoelectric materials, and so on. The most influencing design variables are identified using analysis of variance (ANOVA). By minimization of the frequency band gap between first two modes and maximization of output power density simultaneously, optimum solution is obtained from grey relation analysis technique. The results are validated with a surrogate model employing multilayer perceptron (MLP) neural network in conjunction with multi-objective genetic algorithms. The structural dynamic response and electrical power output characteristics of optimized configuration are found to be improved.
Individual or collaborative projects? Considerations influencing the preferences of students with high reasoning ability and others their age

ABSTRACT Conditions influencing 328 students’ (Grades 6-8) preferences for collaborating or working alone on challenging projects were investigated, as well as their potential interactions with ability, grade and sex. Each student completed the Cognitive Abilities Test (Form 7) and Project Context Survey. No overall preference for individual or collaborative projects was found. Students’ preferences were sensitive to features of the context (subject, nature of the task and social dynamics). Individual projects were preferred in art and shared projects in science and social studies. Students with high ability and boys preferred individual projects in Math. Principal components analyses revealed three contextual considerations influenced students’ desire to work on projects alone (enjoyment, optimizing the outcome, and risk management) and five influenced the appeal of collaborating (inclusiveness and trust, access to the strengths of others, their perceived need for support, familiarity, and fair assessment). High ability students were more concerned with the efficiency and quality of their work, and their grades while others their age were more influenced by the potential for fun. Grade 8 students were more concerned with risk management and the assessment process than younger students. If the safe, supportive, fair conditions they sought for collaborating were not available, students’ default preference was to work alone on a challenging project.
Mechanical Design and Analysis of the End-Effector Finger Rehabilitation Robot (EFRR) for Stroke Patients

Most existing finger rehabilitation robots are structurally complex and cannot be adapted to multiple work conditions, such as clinical and home. In addition, there is a lack of attention to active adduction/abduction (A/A) movement, which prevents stroke patients from opening the joint in time and affects the rehabilitation process. In this paper, an end-effector finger rehabilitation robot (EFRR) with active A/A motion that can be applied to a variety of applications is proposed. First, the natural movement curve of the finger is analyzed, which is the basis of the mechanism design. Based on the working principle of the cam mechanism, the flexion/extension (F/E) movement module is designed and the details used to ensure the safety and reliability of the device are introduced. Then, a novel A/A movement module is proposed, using the components that can easily individualized design to achieve active A/A motion only by one single motor, which makes up for the shortcomings of the existing devices. As for the control system, a fuzzy proportional-derivative (PD) adaptive impedance control strategy based on the position information is proposed, which can make the device more compliant, avoid secondary injuries caused by excessive muscle tension, and protect the fingers effectively. Finally, some preliminary experiments of the prototype are reported, and the results shows that the EFRR has good performance, which lays the foundation for future work.
Characterization of radiolytically generated degradation products in the strip section of a TRUEX flowsheet

This report presents a summary of the work performed to meet the FCRD level 2 milestone M3FT-13IN0302053, “Identification of TRUEX Strip Degradation. ” The INL radiolysis test loop has been used to identify radiolytically generated degradation products in the strip section of the TRUEX flowsheet. These data were used to evaluate impact of the formation of radiolytic degradation products in the strip section upon the efficacy of the TRUEX flowsheet for the recovery of trivalent actinides and lanthanides from acidic solution. The nominal composition of the TRUEX solvent used in this study is 0.2 M CMPO and 1.4 M TBP dissolved in n-dodecane and the nominal composition of the TRUEX strip solution is 1.5 M lactic acid and 0.050 M diethylenetriaminepentaacetic acid. Gamma irradiation of a mixture of TRUEX process solvent and stripping solution in the test loop does not adversely impact flowsheet performance as measured by stripping americium ratios. The observed increase in americium stripping distribution ratios with increasing absorbed dose indicates the radiolytic production of organic soluble degradation compounds.
Design of a Novel Current Mode Charge Pump for Very-Low-Voltage Applications in 130 nm
SOI-BCD Technology

A novel charge pump with current mode control suitable to work under a very-low-voltage supply is proposed in this paper. The proposed charge pump consists of two sections. The first section is a power switches stage which consists of seven cascaded DEPMOS power switches. The second section is a low voltage stage which consists of a Low Voltage Level Shifter, Current Mode control, Follower Amplifier, Error Amplifier, Soft Start Comparator, and Skip mode & Over Voltage Comparator. The charge pump has been designed, simulated, and layout in Cadence using TSMC 130 nm SOI technology with LDMOS transistors, which have very low on-resistance. The input range of the charge pump is 2.7– 4.4 V, and it can supply up to 100 mA load current. The maximum efficiency is 90%, and the chip area is only 0.597 mm².
Understanding destination brand love using machine learning and content analysis method

ABSTRACT This study aims to apply the concept of brand love in tourist destinations in order to identify the core-elements that could have influential impacts on generating destination brand love. This study has been carried out using a mixed-method of machine learning and content analysis. We have discovered that the topics have been generated for historical landmarks and destinations by analysing the visitors’ online reviews are architecture, historical sites, tradition and shrine places, which could be similar to other tourist historical destinations in a different part of the world. However, this study has the potential to be a model for other researches related to different destinations with possible different topics that emerged. Our study contributes by providing both researchers and managers a novel method to understand what attributes of destination brand love they need to posit more emphasize to attract more visitors based on the destination type.
Propuestas para unas estrategias de marketing en redes sociales, más eficientes. El análisis de las cuentas corporativas universitarias

The present work examines the aspects to take into consideration for more efficient marketing strategies in social network services. The authors address the variables that lead users to acknowledge, through retweets and favorites, the content published on the corporative accounts of university institutions. This research analyses 18.092 posts in a sample of ten Spanish universities, in Twitter. The study uses a quantitative methodology considering thirty variables. The researchers carry out a descriptive analysis and two linear regressions; revealing: (a) the usual trends of use, and (b) the variables that improve the acknowledgment of the content published through retweets, on the one hand, and favorites, on the other. The results corroborate the existence of two robust regression models. The first one (p-value < ,0001 and R2= ,792) shows how the acknowledgment through retweets is determined by the use of links and hashtags. Similarly, the second (p-value < ,0001 and R2= ,886) reveals that the acknowledgment of content in the form of favorites is conditioned by the daily volume of posts and the messages published from 8:00 to 10:00 am. The findings of this research provide, both academics and professionals, with an up-to-date view of the variables that affect this acknowledgment indicators and that, consequently, lead to more efficient marketing strategies in social network services.
Demographic and health characteristics of 3,4-methylenedioxymethamphetamine users (MDMA, ecstasy).

OBJECTIVES MDMA is one of the most commonly used drugs in the world. Clinical studies are currently being conducted around the world on the use of this substance in the treatment of PTSD and alcoholism. However, little demographic information is available on users who use the substance for recreational purposes. The aim was to determine basic demographic and helath characteristics with validated tools. METHODS The authors prepared an original questionnaire on the demography of MDMA users and combined it with the General Health Questionnaire-28 (GHQ-28) and the Hospital Anxiety and Depression Scale (HADS). The survey was sent to Polish MDMA users via the Internet. RESULTS 304 responses were received from people over 18 years of age. MDMA is widespread among young adults, in many different places of residence and regardless of gender. The users take MDMA in both pill and crystal form and very rarely test drugs bought from a dealer. Most users feel that MDMA has had a good impact on their lives. CONCLUSIONS MDMA is rarely used as the only psychoactive substance. MDMA users rate their health higher than people using other psychoactive substances.
Landslide Inventory Mapping Method Based on Adaptive Histogram-Mean Distance With Bitemporal VHR Aerial Images

Landslide inventory mapping (LIM) on the basis of change detection techniques has potential significance for landslide disaster analysis. In this letter, a novel LIM approach based on the adaptive histogram-mean distance (AHMD) is proposed, which adaptively considers spatial contextual information of different landslide regions to improve the detection performance. First, to adapt the shape, size, and distribution of various landslides, an adaptive region around a pixel is extracted by a novel adaptive region extension algorithm without parameter setting. Second, the pixels within the adaptive region are taken to construct the spectral frequency histograms, and then, the adaptive histogram mean (AHM) is developed as the feature of a histogram. Third, the AHMD is defined based on the bin-to-bin (B2B) distance to measure change magnitude between the pairwise AHMs. Finally, LIM can be obtained by a supervised threshold method called double-window flexible pace search (DFPS). Experimental results tested on two real datasets with a very high spatial resolution (VHR) demonstrate the outperformance of the proposed AHMD approach with seven comparative methods.
Multisensor and Multimodel Monitoring and Investigation of a Wintertime Air Pollution Event Ahead of a Cold Front Over Eastern China

Given the limitations in pollutant measurements (e.g., coverage, observation errors) and air quality model uncertainties (e.g., with parameterizations and emissions), a multisensor and multimodel approach offers additional benefits compared to a single‐instrument and deterministic approach for monitoring, investigating, and predicting air pollution events. In this study, we use multisensors (including the spaceborne MODIS, OCO‐2, AIRS, and OMPS instruments as well as surface instruments) and multimodels (including WRF‐Chem and WRF‐CO2) to investigate a severe air pollution event on December 9, 2016 over eastern China. During this episode, a strong cold front moved southward. At the leading edge of the front, WRF‐CO2 simulates an enhanced XCO2 belt while WRF‐Chem simulates a belt of high PM2.5 concentration. The XCO2 and PM2.5 belts are generally colocated, due to coemission of CO2 and pollutants (or their precursors). Satellite observations including MODIS AOD, OCO‐2 XCO2, OMPS NO2, AIRS CO, and surface data confirm the simulated pollution and XCO2 belts. Later on, the front became distorted due to terrain blocking and mountain channel flows. Both observations and simulations show that the channel winds between Mountains Dabie and Huang transport the haze plume into Jiangxi province, enhancing pollution in the region. It is concluded that the multisensor (including space‐based and ground‐based instruments) and multimodel (e.g., WRF‐CO2, WRF‐Chem) approach can be used to collectively monitor and investigate air pollution events, given that emissions of the involved species have generally similar spatial distributions.