Miracle-dz/UniFAR-FTUs huggingface dataset:
Bellman's principle of optimality and deep reinforcement learning for time-varying tasks

ABSTRACT This paper presents the first framework (up to the authors' knowledge) to address time-varying objectives in finite-horizon Deep Reinforcement Learning (DeepRL), based on a switching control solution developed on the ground of Bellman's principle of optimality. By augmenting the state space of the system with information on its visit time, the DeepRL agent is able to solve problems in which its task dynamically changes within the same episode. To address the scalability problems caused by the state space augmentation, we propose a procedure to partition the episode length to define separate sub-problems that are then solved by specialised DeepRL agents. Contrary to standard solutions, with the proposed approach the DeepRL agents correctly estimate the value function at each time-step and are hence able to solve time-varying tasks. Numerical simulations validate the approach in a classic RL environment.
Application of a Controlled Aquarium Experiment to Assess the Effect of Mesh Sizes and Mesh Opening Angles on the Netting Selectivity of Antarctic Krill (Euphausia superba)

Understanding the interactions between target species and netting is paramount for increasing the sustainability of trawling activities. The selectivity of the utilized netting depends on the sizes and opening angles of the mesh. The effects of the mesh size and mesh opening angle on the fishing selectivity of Antarctic krill (Euphausia superba) were assessed via micro-cosmos experiments. The results show that both the absolute abundance and the incidence of larger krill individuals passing through experimental panels are proportional to the utilized mesh size. Krill individuals larger than 35 mm passed through experimental panels at mesh opening angles larger than 50° for a 15 mm mesh size, 35° for a 20 mm mesh size and 20° for a 30 mm mesh size. Additionally, all L50 values increased with an increasing mesh size and an increasing mesh opening angle at the same mesh size. Furthermore, the selection range increased with an increasing mesh size and with an increasing mesh opening angle at the same mesh size. This paper provides scientific guidance for the choice of liner mesh sizes of krill trawl with the aim to improve fishing efficiency while minimizing fishing losses and potential negative ecosystem impacts from fisheries.
Influence of qualifications in initial training on the professional development and motivation of primary teachers in the Balearic Islands

ABSTRACT This paper analyses, using a cross-sectional design, the relationship between academic qualifications during the initial training of primary school teachers and their professional development. Among all graduates of 13 promotions, from year 2004 to 2016, we selected the 15% of those students with the best qualifications and the 15% with the worst ones from each promotion. All participants answered the same questionnaire on employability, participation in induction programmes, participation in continuing education programmes, and professional motivation. Analyses performed included distribution analyses using chi-square and independent group comparisons with Student’s t-test. Participants with better grades showed higher employability rates, increased participation in initial education programmes, and more motivation towards their profession. Continuing education programmes were only slightly affected by initial grades. These results support academic positions in Spain that defend the need to apply measures to select those candidates with the best grades to become teachers.
Validation of the Copenhagen Burnout Inventory in Pharmacists

Abstract Objectives: This study aimed to 1) determine the validity of the Copenhagen Burnout Inventory (CBI) for use in the assessment of burnout in a sample of pharmacists using confirmatory factor analysis (CFA), and 2) use the CBI items and other measures of work-life to assess burnout in pharmacists employed in various types of practice. Methods: A cross-sectional survey was administered to a sample of 2,582 pharmacists in a single Midwestern US state. The survey included the three subscales of the CBI, each of which measures personal, work-related, and patient-related dimensions of burnout. Other items included demographics, practice type, workload, and work-life balance. CFA was used to measure fit, and Cronbach’s alpha was used to assess reliability. Correlation was used to assess criterion validity of the CBI. Logistic regression and bivariate analyses were used to assess pharmacist burnout based on demographics. Results: Following the removal of 2 items from the measurement model, a 17-item 3-factor CBI was found to possess satisfactory psychometric properties for use in pharmacists. The CBI correlated with measures of work-life demonstrating criterion validity. A logistic regression showed that younger pharmacists and community pharmacists experience higher burnout than older pharmacists and clinical pharmacists. Community pharmacists also more often reported high workloads and poorer work-life integration. Both community and clinic pharmacists desired more time providing patient care services and less time dispensing. Conclusion: The CBI is a psychometrically reliable and valid instrument for assessing burnout in pharmacists. Younger pharmacists and community pharmacists warrant attention due to their higher degree of burnout.
What You Sense is Not Where You are: on the Relationships Between Fingerprints and Spatial Knowledge in Indoor Positioning

Positioning is a task of increasing importance in today’s life, with applications in many different contexts. The fact that people spend most of their time inside buildings makes indoor positioning a fundamental research topic. A variety of approaches to indoor positioning have been proposed over the years; however, most often it is carried out through WiFi fingerprinting, by reason of its ease of deployment. WiFi fingerprints are (arrays of) signal strengths of access points observed at given locations. A fingerprint can thus be viewed both as a point in the real-world 2D/3D (geometrical) space and as a point in the high dimensional (fingerprint) space determined by access points. In this paper, we explore the relationships between these two spaces. To the best of our knowledge, such an investigation has never been systematically carried out in the literature, that mainly focuses on position estimation. We first highlight some connections between the geometrical and the fingerprint space. Then, we show that, by making use of conventional approaches, it is unfeasible to reconstruct real-world spatial knowledge on the basis of fingerprint data only. All findings are supported by a thorough analysis that takes into consideration various metrics, fingerprint representations (i.e., normalization functions), and granularity levels (e.g., a single building rather than a single floor), and makes use of 15 public well-recognized indoor datasets. Some general considerations on the outcomes of the analysis conclude the paper.
A hydrogen‐storing quinaldine polymer: nickel‐electrodeposition‐assisted hydrogenation and subsequent hydrogen evolution

Quinaldine-substituted poly(acrylic acid) (PQD) and its hydrogenated 1,2,3,4-tetrahydroquinaldine derivative (PHQD) were prepared, and a cycle of hydrogen fixing and hydrogen evolution in and from the polymer, respectively, is described. A PQD layer coated on a carbon substrate was electrochemically reduced or hydrogenated using water as a hydrogen source, accompanied by the electrodeposition of nickel microparticles in the polymer layer, to convert PQD to PHQD. The conversion efficiency was enhanced by coating PQD on the substrate as a scaffold of nickel electrodeposition, in comparison with that of quinaldine and PQD dissolved in the electrolyte. The formed PHQD evolved hydrogen by simply warming it in water containing an iridium complex catalyst. Hydrogen fixing and evolution under mild conditions could suggest a new system of hydrogen carriers. © 2017 Society of Chemical Industry
Defective Product Classification System for Smart Factory Based on Deep Learning

Smart factories merge various technologies in a manufacturing environment in order to improve factory performance and product quality. In recent years, these smart factories have received a lot of attention from researchers. In this paper, we introduce a defective product classification system based on deep learning for application in smart factories. The key component of the proposed system is a programmable logic controller (PLC) artificial intelligence (AI) embedded board; we call this an AI Edge-PLC module. A pre-trained defective product classification model is uploaded to a cloud service from where the AI Edge-PLC can access and download it for use on a certain product, in this case, electrical wiring. Next, we setup the system to collect electrical wiring data in a real-world factory environment. Then, we applied preprocessing to the collected data in order to extract a region of interest (ROI) from the images. Due to limitations on the availability of appropriate labeled data, we used the transfer learning method to re-train a classification model for our purposes. The pre-trained models were then optimized for applications on AI Edge-PLC boards. After carrying out classification tasks, on our electrical wire dataset and on a previously published casting dataset, using various deep neural networks including VGGNet, ResNet, DenseNet, and GoogLeNet, we analyzed the results achieved by our system. The experimental results show that our system is able to classify defective products quickly with high accuracy in a real-world manufacturing environment.
The insular herpetofauna of Mexico: Composition, conservation, and biogeographic patterns

Abstract We compile a Mexican insular herpetofaunal checklist to estimate endemism, conservation status, island threats, net taxonomic turnover among six biogeographic provinces belonging to the Nearctic and Neotropical regions, and the relationships between island area and mainland distance versus species richness. We compile a checklist of insular herpetofaunal through performing a literature and collection review. We define the conservation status according to conservation Mexican law, the Red List of International Union for Conservation of Nature, and Environmental Vulnerability Scores. We determine threat percentages on islands according to the 11 major classes of threats to biodiversity. We estimate the net taxonomic turnover with beta diversity analysis between the Nearctic and Neotropical provinces. The Mexican insular herpetofauna is composed of 18 amphibian species, 204 species with 101 subspecies of reptiles, and 263 taxa in total. Endemism levels are 11.76% in amphibians, 53.57% in reptiles, and 27.91% being insular endemic taxa. Two conservation status systems classify the species at high extinction risk, while the remaining system suggests less concern. However, all systems indicate species lacking assessment. Human activities and exotic alien species are present on 60% of 131 islands. The taxonomic turnover value is high (0.89), with a clear herpetofaunal differentiation between the two biogeographic regions. The species–area and species–mainland distance relationships are positive. Insular herpetofauna faces a high percentage of threats, with the Neotropical provinces more heavily impacted. It is urgent to explore the remaining islands (3,079 islands) and better incorporate insular populations and species in ecological, evolutionary, and systematic studies. In the face of the biodiversity crisis, islands will play a leading role as a model to apply restoration and conservation strategies.
GraphMS: Drug Target Prediction Using Graph Representation Learning with Substructures

The prediction of drug–target interactions is always a key task in the field of drug redirection. However, traditional methods of predicting drug–target interactions are either mediocre or rely heavily on data stacking. In this work, we proposed our model named GraphMS. We merged heterogeneous graph information and obtained effective node information and substructure information based on mutual information in graph embeddings. We then learned high quality representations for downstream tasks, and proposed an end–to–end auto–encoder model to complete the task of link prediction. Experimental results show that our method outperforms several state–of–the–art models. The model can achieve the area under the receiver operating characteristics (AUROC) curve of 0.959 and area under the precise recall curve (AUPR) of 0.847. We found that the mutual information between the substructure and graph–level representations contributes most to the mutual information index in a relatively sparse network. And the mutual information between the node–level and graph–level representations contributes most in a relatively dense network.
The moderating effect of the perception of cyber violence on the influence of exposure to violent online media on cyber offending in Korean adolescents

The aim of this study was to verify the moderating effect of the relationship between exposure to violent online media and cyber offending in adolescents. The study utilized information from the 2019 cyber violence survey; data from 3,202 adolescents (mean age = 16.56, SD = 1.71; boys = 1,800, girls = 1,402) were used for the final analysis. The moderating effect was analyzed using PROCESS Macro 3.4 (model 1), and the main results revealed that exposure to violent online media had a positive effect on cyber offending, while the perception of cyber violence had a negative influence on cyber offending. Specifically, the effect of exposure to violent online media on cyber offending was moderated by the perception of cyber violence. As a result of simple regression to verify the conditional effect according to the level of perception of cyber violence, cyber violence increased as exposure to violent online media increased in all level perceptions of violence (−1SD, M, +1SD). This study implies the need for education to raise awareness that cyber violence is dangerous and illegal along with supervision from parents and schools to reduce exposure to risky online media in order to prevent adolescents’ cyber violence.
Mixed-method Research: A Basic Understanding

Aim and objective: Describe the basics of the mixed-method type of research. Background: Traditionally, the research has been quantitative in nature which provided measures for the parameter of interest. This was followed by the era of qualitative research which helped in a detailed understanding of a phenomenon. This is especially important in healthcare research as it also gives an account of the individual interaction with their environment which is a significant contributor to health. Around the 1970s, the concept of combining both these approaches was used in social sciences. Recently, this mixed-method approach was integrated into health research and educators. However, there has been a continuing debate on the basic nature of this research design. Thus, a complete understanding of this type of research is important. Review results: Various authors described various purposes of the mixed-method approach. The main ones being triangulation, complementarity, development, initiation, and expansion. Theoretical drives, timings, and point of integration are the three factors that need to be considered for the development of studies using this design. Throughout times, different classifications for mixed-method studies have evolved, however, the most accepted one, based on the utility and internal consistency is the classification by Creswell and Clarke. They describe four major designs for mixed-method research as triangulation design, embedded design, explanatory design, and exploratory design. The application, principle, variants, strengths, challenges, and examples of each have been described extensively in this article. Conclusion and clinical significance: Mixed-method approach is a valuable research type as it capitalizes on the strength of both qualitative and quantitative research. It is of significance in health research as it gives a broader range of perspectives to the complex phenomena studied. Thus, proper knowledge of the basics is required to accurately combine and interpret findings of the qualitative and quantitative aspects. This article is a contribution to this basic understanding of mixed-method research.
A paper fortune teller-inspired reconfigurable soft pneumatic gripper

Soft pneumatic grippers (SPGs) have shown great grasping performances for various objects due to their simplicity, adaptability and rapid response. However, there are few SPGs that can grasp both flat and non-planar targets robustly. A reconfigurable mechanism that can transform the gripper into different states for grasping varied objects is desired by such versatile SPGs. Paper fortune teller (PFT) is a distinctive origami with 2D/3D shape switchability and 3D shape reconfigurability. In this paper, we propose a novel reconfigurable SPG which is inspired from PFT and augmented with an indirect vacuum adhesion (IVA) mechanism. The resultant gripper can not only lift flat-surface objects such as a piece of square glass (278 g) with the IVA force in its pad shape, but also pick up non-planar objects such as an orange (151 g) in a traditional grasping way in its four-converging-fingered shape. The experimental results reveal that our gripper can produce a maximum IVA force of about 4.24 N on acrylic plates and a maximum pulling force of about 2.10 N on 3D-printed non-planar objects respectively. The gripper’s traditional grasping robustness is also demonstrated when non-planar objects are placed irregularly (allowing up to 55 mm multi-orientation offsets or 20° multi-orientation drift angles). This new SPG design realizes the multi-function nature of origami transformation and is expected to promote the application of origami and soft gripper technologies.
Adaptive backstepping control of induction motor powered by photovoltaic generator

This paper is aimed at addressing the design of an effective adaptive nonlinear control of a photovoltaic (PV) water pumping system powering a submersible induction motor and a centrifugal water pump. Four objectives are achieved using an adaptive Backstepping controller. First, it is applied to ensure maximum power point tracking, and uses the latter as a reference in regulation of the rotor speed to convert the maximum electrical power into maximum mechanical power. Second, the adaptive controller is synthesized to control motor rotor flux and restrict the magnetic circuit to its linear interval. Third, it is used to online estimate the rotor time-constant and the load torque disturbance estimation. Finally, this controller is employed to limit the stator currents to protect induction motor windings. Mathematical modelling of the main elements of the system is presented. A sliding mode rotor flux estimator is employed in the output feedback control of the whole system. DC-AC converter is controlled by pulse width modulation. The feasibility, the robustness and the effectiveness of the proposed adaptive nonlinear controller are evaluated through simulations in MATLAB/Simulink environment.
Properties and Applications of 2-Dimensional Layered Materials

This focus issue provides a forum for the latest research on material properties, device physics, fabrications and applications of twodimensional (2D) based materials including boron nitrides, black phosphorous and transition metal dichalcogenides/oxides beyond graphene. It features a balance between original theoretical and experimental research in basic physics, device physics, novel materials and device structures, processes and systems. Recent developments in the isolation and growth of atomically thin layered materials has provided new possibilities for studying the surfaces, chemistry and physics of a true 2D platform. In addition to the known graphene layers, other 2D materials such as transition metal dichalcogenides/oxides, boron nitride and black phosphorous have shown great potential in various applications. The 2D nature of these materials makes their electronic structure easily tunable by an external field. Thus, applications in electronic, optoelectronic, sensor and other devices are anticipated. The large surface areas and layered structures land to high-efficiency energy storage and conversion. The following sub-fields, as well as others at the cutting edge of research in this field are addressed:
Reporting Conflict from Afar: Journalists, Social Media, Communication Technologies, and War

ABSTRACT We conducted interviews with conflict journalists who covered the conflicts in Syria, Yemen, Libya, and Iraq and who work for the major international news agencies and media companies. These journalists did most of their reporting from remote locations as the conflict zones were too dangerous to be physically present. We investigated how the journalist did their jobs with the communicative affordances of digital tools and how digital trust-building occurred. The trust-building process between journalists and sources shifted across platforms and according to the technologies’ communicative affordances. We established that reporters had embraced the flow of news material on social media platforms as a valuable source of information, but after exercising extreme caution. Journalists upheld the boundaries that separated them from amateurs by emphasizing their role in making sense of events. They also fortified their gatekeeping role through verifying and vetting information – a task needed to maintain credibility and protect readers and viewers from misinformation and propaganda. Encrypted messaging applications such as WhatsApp played a major role in speeding up communication with and protecting potential sources and verification.
First Observation of the Oxygen 630 nm Emission in the Martian Dayglow

Following the recent detection of the oxygen green line airglow on Mars, we have improved the statistical analysis of the data recorded by the NOMAD/UVIS instrument on board the ExoMars Trace Gas Orbiter mission by summing up hundreds of spectra to increase the signal‐to‐noise ratio. This led to the observation of the OI 630 nm emission, the first detection in a planetary atmosphere outside the Earth. The average limb profile shows a broad peak intensity of 4.8 kR near 150 km. Comparison with a photochemical model indicates that it is well predicted by current photochemistry, considering the sources of uncertainty. The red/green line intensity ratio decreases dramatically with altitude as a consequence of the efficient quenching of O(1D) by CO2. Simultaneous observations of the green and red dayglow will provide information on variations in the thermosphere in response to seasonal changes and the effects of solar events.
ZnAl2O4 Nanoparticles as Efficient and Reusable Heterogeneous Catalyst for the Synthesis of 12-phenyl-8,12-dihydro-8,10-dimethyl-9H-naphtho[1′,2′:5,6] pyrano[2,3-d] pyrimidine-9,11-(10H)-diones Under Microwave Irradiation

ABSTRACT A simple and one-pot synthesis of naphthopyranopyrimidines is reported by the three-component condensation reaction of aldehydes, β-naphthol, and 1,3-dimethylbarbituric acid using ZnAl2O4 nanoparticles under microwave irradiation. This flexible and nano-catalytic procedure showed good recyclability and provides a clean condensation reaction in a short reaction time.