Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Workload Caused by the Pandemic on Depression, Anxiety and Stress Levels in Surgical and Operating Room Nurses

INTRODUCTION The new type of coronavirus that emerged in WuhanChina in December 2019 was named Covid-19 by the World Health Organization (WHO). It has spread to many countries and has been identified as a pandemic (1). Various social restriction precautions have been taken by central authorities and health units around the world. However, it has spread rapidly and caused more than 75 million diagnoses and 1.6 million deaths globally (2). It is known that healthcare professionals are at serious risk and are infected with Covid-19 14 times more than other segments of the ABSTRACT
Influencing Factors of Online Health Information Seeking in Selected European Countries

Patients’ participation in healthcare requires comprehensive health knowledge and can benefit from online health information seeking behaviours (O-HISB). The internet is a particularly vital source for seeking health-related information in many regions of the world. Therefore, we take a European cross-country comparative perspective on O-HISB. We aim to compare the importance of personal, health(care)-related, and cognitive determinants of using the internet for health-related purposes in four European countries. We conducted online surveys among the German, Swiss, Dutch, and Austrian public and described patterns of health information seeking online. The internet seemed to be a widely used source of health information in the four selected European countries. The explanation patterns of personal, health(care)-related, and cognitive factors differ by country and between selecting the internet as a source of health information and the frequency of online use. Using online media appeared to be more common for women and for current health problems. Respondents’ willingness and competencies are essential for online health information seeking. To prevent the increase of social and health-related disparities, there is an urgent need to support underprivileged population groups and increase motivations and eHealth literacy to use the internet for health-related purposes.
Driving and tilt‐hovering – An agile and manoeuvrable aerial vehicle with tiltable rotors

Driving and tilt ‐ hovering help unmanned aerial vehicles extend their time of operation and the visible range of the equipped sensors. Standard quadrotors are underactuated, whose translational and rotational motions are strongly coupled. As a result, it is impossible to maintain the attitude invariably while changing position. Meanwhile, larger flying speed results in greater air resistance, which is also not desirable. A novel aerial platform with tiltable rotors is proposed. Compared with standard quadrotors, the aerial vehicle has three special capabilities: vector ‐ flying, tilt ‐ hovering, and driving. The platform consists of two tilting ‐ axes to change the direction of thrusts with respect to the aircraft body. To guarantee flexible manoeuvres, a geometric tracking control scheme that adapts on the fly to the thrust vectoring is exploited. Manoeuvrability of the proposed vehicle in different manoeuvres is demonstrated, such as flight with vectoring thrust that can reduce the flight resistance, tilt ‐ hovering expanding the reachable set of the equipped sensors. The prototype equipped with an electromechanical controller is constructed, and several associated preliminary experiments are performed. The feasibility of the mechanical design and the geometric control strategy are demonstrated.
Consecutive Extratropical Cyclones Daniel, Elsa and Fabien, and Their Impact on the Hydrological Cycle of Mainland Portugal

The extratropical cyclones that originate in the North Atlantic and propagate towards Europe are one of the major natural hazards in mid-latitudes. In December 2019, three consecutive extratropical cyclones named Daniel, Elsa, and Fabien affected Portugal. In this study, the synoptic and upper-level dynamic conditions associated with these systems during their impact in mainland Portugal are evaluated. The persistent intense zonal flow that crossed the entire Atlantic revealed by the integrated vapor transport and the vertically integrated moisture flux favored these hydro-meteorological systems. The patterns of mean sea level pressure, geopotential, potential vorticity, total column water, and convective available potential energy were used to characterize the influence of every system over mainland Portugal. A cluster analysis of monthly precipitation permitted the classification of the country into four main regions named the Northwest, Centre West, Northeast and Centre East, and South region on which the analysis was focused. The three storms affected every region on consecutive days by the middle of December, producing extreme precipitation events and significant effects on the accumulated rainfall and runoff, particularly in the Northwest, Centre West, Northeast and Centre East regions. As consequence, multiple incidences of damage were reported along mainland Portugal. However, an assessment of the Standardized Precipitation Index (SPI) and the Standardized Precipitation–Evapotranspiration Index (SPEI) on time scales of 1, 3, 6, and 12 months revealed a positive impact of rainfall increase on the attenuation of short and long term accumulated drought conditions, particularly in the center and north regions.
Optimizing Deep Neural Network for Automatic Number Plate Recognition in Challenging Environment

The study of automatic number plate recognition, a subfield of computer vision and machine learning, has grown in importance. Parking management, toll collection, and traffic monitoring are just a few of the many uses for automatic number plate recognition devices. However, automatic number plate recognition in difficult situations like dim lighting, bad image quality, and occlusions is still a difficult task. In this study, using the TensorFlow and EasyOCR libraries, a novel deep neural network architecture is suggested for automatic number plate recognition in difficult environments. First, examination of the different automatic number plate recognition challenges and how they affect the effectiveness of the current automatic number plate recognition systems. It is then suggested that a deep neural network design should be used to boost the automatic number plate recognition systems’ recognition accuracy in difficult environments by combining convolutional and recurrent layers. Overall, this study suggests new deep neural network architecture for Automatic Number Plate Recognition (automatic number plate recognition) in difficult environments. To increase recognition accuracy, the proposed architecture combines convolutional and recurrent layers, including a kind of recurrent neural network (RNN) dubbed long short-term memory (LSTM). On an openly accessible dataset, the system’s accuracy was 91% and it was developed using the libraries TensorFlow and EasyOCR. The results of this study could be used in a number of industries, including law enforcement, transportation, and parking administration.
Penaeid Shrimp in Chesapeake Bay: Population Growth and Black Gill Disease Syndrome

Since 1991, the number of penaeid shrimp occurring in Virginia waters of Chesapeake Bay has steadily increased, prompting an interest in developing a fishery. Although development of a shrimp fishery in the Chesapeake Bay region could bring economic benefits, the fishery may be hampered by the presence of a disease syndrome known as shrimp black gill (sBG). The objectives of our study were to (1) describe the spatial distribution and abundance patterns of shrimp in Chesapeake Bay, (2) relate relative abundance of shrimp to habitat characteristics, and (3) determine the presence and seasonality of sBG to better understand disease dynamics in the region. Subadult penaeid shrimp were collected monthly from Virginia waters by trawl from 1991 to 2017, and individuals were identified to species and counted. White shrimp Litopenaeus setiferus were the most numerous species captured, followed by brown shrimp Farfantepenaeus aztecus and pink shrimp F. duorarum. Shrimp were captured primarily from July to December. White shrimp were the only species that exhibited visible signs of sBG, which was first observed in October 2016 (13.4% prevalence); the condition continued into November and recurred the following year. Shrimp with visible signs of gill disease were examined by microscopy, histology, and PCR assay and were diagnosed with infections of a histophagous apostome ciliate, presumably Hyalophysa lynni. Any impacts of sBG on shrimp survival or marketability should be considered in fishery management plans to ensure sustainability of the resource. Penaeid shrimp have been observed in Chesapeake Bay waters as far back as 1880, occurring in some of the earliest fisheries surveys undertaken by the U.S. Fish Commission (Baird 1882). However, the relative abundance of penaeid shrimp was very low, and catches in fishery-independent surveys were not recorded until a notable increase in catch was observed in 1991 (Geer et al. 1993). In the southeastern USA, penaeid shrimp support a valuable commercial fishery, with a dockside value of more than US$436 million in 2016 (NMFS 2018). Three species of penaeid shrimp support the commercial fishery, including white shrimp Litopenaeus setiferus, brown shrimp *Corresponding author: tuckey@vims.edu Received February 18, 2020; accepted September 10, 2020 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Marine and Coastal Fisheries 13:159–173, 2021 © 2021 The Authors. Marine and Coastal Fisheries published by Wiley Periodicals LLC on behalf of American Fisheries Society ISSN: 1942-5120 online DOI: 10.1002/mcf2.10143
Experimental investigations of manifold structure on cooling performance in embedded microfluidic cooling

For embedded microfluidics cooling, the morphology of the microfluidics structure and the liquid injection mode have a great impact on the cooling performance. Manifold structure can adjust the flow direction of the coolant before heat convection, reducing pumping power and improving cooling efficiency of embedded cooling. In this work, four manifold structures for embedded cooling are designed and fabricated, the cooling performance and hydraulic performance of different structures is compared through experimental investigations. The results show that compared with the horizontal cooling, the manifold structure based on vertical cooling not only reduces the temperature by 20.8%, but also reduces the pressure loss by 43.5%.
Using User-Item Sub-Block to Improve Recommendation Systems

As an indispensable technique in the field of information filtering, recommendation systems (RSs) have been well studied and developed both in academia and in industry recently. In this paper, we propose the intimacy among users to obtain a user-item objective rating matrix, which can reflect user’s real interest. For the sake of better predicting ratings, a user-item sub-block is presented to cluster a group of intimate users and a subset of items. Then, the sub-block can be detected through intimacy among users and similarity between items. In order to improve recommendation accuracy, we propose a social contribution degree and social similarity based matrix factorization method to predict scores in sub-block. The final predicted ratings are obtained by combining all sub-blocks. Top- N items with highest predicted scores are recommended to each user. Systematic simulations on real world data set have demonstrated the effectiveness of our proposed approach.
Graph Convolutional Networks Based Standard Essential Patents Identification

The standard essential patents are some patents for which the patent technology solutions are adopted by the technological standard. The identification of standard essential patents is an important task in the standardization. With the sharply increasing number of patents and much more diversity of standard domains, the manual standard essential patents identification methods to check the patent by word for word, are not applicable for the big patent data processing. The automatic standard essential patents identification methods face some challenges from the extraction and representation of features to the construction and learning of models. To solve the above issues, we develop a graph convolutional network based standard essential patents identification. We propose a hypothesis that the standard essential patents under the same standard are structure-association and the associated relations can be used in standard essential patents identification. Herein, we extract the co-occurrence relations including keyword-keyword relation, document-keyword relation. We construct a heterogeneous graph consisting of patent nodes, keyword nodes and their co-occurrence relations, which include rich structural information for the identification of standard essential patents. Thereafter, a graph convolutional network is developed to identify the potential standard essential patents. Since the number of standard essential patents and nonstandard essential patents is imbalance in practice, we utilize the sampling method to alleviate the imbalanced issue on the graph. To validate the effectiveness of the proposed model, we conduct experiments on five datasets of patent in the real world and the experimental results show that the proposed model outperforms existing research in the identification of standard essential patents.
Cooperative Dual Leo Satellite Transmission in Multi-User OTFS Systems

This paper explores multi-satellite transmission schemes. The focus is on the multi-user downlink scenario, where two low Earth orbit satellites transmit data cooperatively, which are then combined at each of the ground user terminals. A single synchronization circuit is employed at the receiver to reduce the terminal burden. The orthogonal time and frequency space (OTFS) waveform is utilized to handle the residual offsets and schedule users on non-overlapping delay-Doppler resources. The paper leverages on OTFS, beam-centric compensation and the characteristics of the satellite channel to eliminate inter-user interference. Numerical results assess the effectiveness of the proposed scheme and highlight the improvement in performance achieved through satellite cooperation as compared to single satellite transmission.
WebEnclave: Protect Web Secrets From Browser Extensions With Software Enclave

Browser extensions are widely used nowadays to customize users’ browsers with more functionalities, meanwhile introduce potential risks due to escalated privileges. Existing security mechanisms, such as Same Origin Policy and Content Security Policy, do not apply to browser extensions that can read and write on web applications at any time. In spite of the state-of-the-art industrial efforts that rely on centralized management to inspect and detect malicious behaviors massively, the detection-based method cannot analyze fast-evolving behaviors of malicious browser extensions. To this end, we adopt a novel approach to protect users from malicious browser extensions, where we consider the problem of malicious extensions on the side of web applications. From a high level point of view, web developers are allowed to specify sensitive parts in a web application by using our provided software enclave. With our proposed WebEnclave extension installed, when users visit a web application, sensitive information required for the web application to work normally is sealed into an isolated world locally that malicious extensions cannot access. Extensive evaluation of our built prototype shows it can effectively protect user secrets from malicious extensions with negligible performance overhead and usability inconvenience. We also publish source codes for public use.
Characteristics of herbaceous vegetation on abandoned fallow fields in south central Zimbabwe

Fields abandoned to fallow, due to biophysical and socio-economic factors in communal areas of Zimbabwe, are used for livestock grazing. A study was conducted to characterise vegetation from such fields, and assess its grazing suitability across four agroecological regions (AER II – AER V) characterised by annual rainfall ranging from 750 mm to 400 mm, and five categories of fallow age groups (0-5; 6-10; 11-20, > 20 years and normal rangeland). Most fallow fields did not mature into woodlands but remained grasslands with or without sparse shrubs regardless of the period of fallowing and AER because of high stocking rates. There were no variations in palatability, ecological value, diversity, biomass and grazing capacity across fallow age groups. However, significant differences were observed across AERs. The quality of vegetation from fallows in AER II and III was poor but good in AER IV and V. The quantity of vegetation from fallows in AER II was higher than from other AERs. However, all fallow fields from the four AERs had low grazing capacity than expected from literature. We conclude that using fallow fields for uncontrolled grazing is unsustainable. There is need to investigate better management strategies for livestock production in fallow fields.
The influence of a standardized experimental environment on early diagenetic changes to animal bone

We evaluated the dynamics of the diagenetic changes to pig bones incubated for 4, 10, and 31 months in a controlled environment (soil type, moisture and pH, air humidity, and temperature). The criteria for the assessment were as follows: physical parameters (bone weight), biomechanical parameters (compressive strength), bone microstructure (using micro‐computed tomography), and phosphorus and calcium content in the surrounding soil. It was shown that the bone weight decreased the most after 4 months of incubation, whereas the biggest change in the compressive strength was not observed until after 31 months of incubation. Also, the main changes to the bone microstructure were observed in the initial period of degeneration. After 4 months of the experiment, a major drop in the percentage of the thinnest bone trabeculae was noted, whereas a reverse trend was observed for the thickest trabeculae. Moreover, the most significant decrease in the Ca/P ratio in the surrounding soil was observed after the experiment's first 4 months. We conclude that the bioerosion of collagen observed after the initial experimental period was followed by hydroxyapatite chemical decomposition. These results indicate the usefulness of the applied analyses and the feasibility of ensuring a standardized environment for diagenetic research.
Music learning, engagement, and personal growth: child perspectives on a music workshop developed in a Portuguese state school

ABSTRACT This article examines the perspectives and feelings of children in the first two years of a music workshop developed with pupils from a state school in northern Portugal. The study followed a participatory action research design, with data including field notes, two group interviews with the children, children’s artefacts, such as texts or paintings, and their musical compositions. The results detail how an informal, collaborative and creative approach to music learning seems to open the space for a ‘pedagogy of interruption’ (Biesta 2010), which, in turn, suggests the development of what O’Neill (2012a) terms ‘transformative music engagement’. This article identifies this transformation process through the three major themes that emerge from data analysis: (a) the shifts the children report as occurring in their modes of connecting and relating with music and music education, (b) the deep engagement they began displaying towards collaborative music-making activities, and (c) their personal and social development.
A novel method based on probabilistic linguistic term sets and its application in ranking products through online ratings

In practical decision‐making problems, the coexistence of several complex situations increases the difficulty for decision makers to make reasonable decision, such as attributes outnumber alternatives, heterogeneous relationships among multiple attributes, and individual risk tendency of decision maker. In view of the advantage of probabilistic linguistic term sets (PLTSs) in presenting qualitative information, a novel decision‐making approach with PLTSs is constructed to deal with the above special situations simultaneously. To realize this goal, some basic models have been proposed. First of all, to truly reflect the importance of attributes from the heterogeneous relationships, a weight determination model with generalized Banzhaf values is developed to analyze the interaction between combinations of attributes. Then, for analyzing the individual risk tendency of decision maker, the generalized Banzhaf TODIM method with PLTSs is constructed. Moreover, based on the above research results, the generalized Banzhaf TODIM‐QUALIFLEX method with PLTSs is developed to solve decision‐making problems where the number of attributes exceeds the number of alternatives, the combinations of attributes are interacted with each other, and decision maker is affected by individual risk propensity. Lastly, smartphones selection through online ratings is a typical case of decision‐making problems with the above situations, which is designed to illustrate the performance of the proposed method. And its rationality and advantages are further demonstrated through some comparative analyses with other methods.
Comparative Analysis of Runoff and Evaporation Assessment Methods to Evaluate Wetland–Groundwater Interaction in Mediterranean Evaporitic-Karst Aquatic Ecosystem

This work compares the applicability of several free-surface evaporation and runoff equations in simulating water level variations of small Mediterranean wetlands. The Amarga and Jarales wetland are two pilot sites with an evaporite-karst genesis located in southern Spain. The water level was continuously recorded in both wetlands, and exhaustive weather monitoring was performed. The combined datasets have permitted quantification of the surficial elements of their water budget (precipitation, runoff, and evaporation). Several campaigns of groundwater level measurements were also done to characterize the direction of groundwater flows. The morphometrical analysis of the Jarales wetland was accurately performed based on a LiDAR dataset. A total of 225 limnimetric simulations of the Jarales (90) and Amarga (135) wetlands were performed, combining different evaporation and runoff equations. During the study period, the curve number method, coupled with the Penman equation, reached the Jarales wetland’s best calibrations. The Vardavas–Fountoulakis modification of the Penman model fit better with the Amarga wetland record. The obtained results permit specification of the water budget of both wetlands during several years and confirm that the groundwater–surface water relationship affects the wetland hydric dynamic to different degrees. Nonetheless, the limnimetric models were calibrated for a short period, including dry years, making it necessary to extend the control period longer and validate the models under different hydroclimatic conditions. Finally, the differences between wetland functioning are explained in a conceptual hydrological model that can be useful for wetland conservation and management of related aquatic ecosystems. The understanding of the origin and fate of water in wetlands permits assessment of how future scenarios would affect hydric functioning and suggests adequate conservation measurements.