Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Computational Thinking Skills in 3D Printing: A Data Analysis of an Online Makerspace

Nowadays, the ability to code is becoming increasingly important in industry and is often mentioned as a crucial skill for future employment. In maker culture, the ability to program along with other technical skills often exceeds this limitation and also includes fun activities through personally fabricated projects. In this paper, we examine computational design projects that are intended to be 3D printed and could potentially introduce coding learning actions. To find computationally rich designs that are appealing to learners, we conducted data analysis on an online makerspace which exploits computational design tools for personal fabrication. We found the most liked designs of the online makerspace and examined which of them included programming features (iterations, conditional statements and functions/modules) and could foster computational thinking elements such as abstract and algorithmic thinking, pattern recognition, and decomposition. The most liked category of designs was Figures (of animals and popular animation characters among other things) which surprisingly often also included programming features. We discuss the implications of our research for technologists, academics and teachers who wish to include 3D modeling and printing in coding learning activities.
Resistor-Capacitor Approach for Modelling of Temperature and Humidity Response Inside Electronic Enclosures

Moisture is an important factor to reliability, functionality and durability of electronic devices. Nowadays, modelling tools have become an integral part of electronics design, because they are less expensive for searching the optimal design of moisture control. CFD and FEM are very time consuming due to their computational effort, therefore it is desirable to have a method such as well-known Resistor-Capacitor (RC) approach which is faster and has less spatial resolution. The paper concerns the development of an in-house code using the RC approach for simulating coupled heat and moisture transport inside electronic enclosure under non-isothermal conditions. Thereafter, the simulations results were compared with corresponding experiments in order to validate the developed code. Based on comparison with experiments, a new configuration RC model was developed for a more accurate humidity prediction. In general new RC model had the adsorption and desorption mechanisms included as a lumped capacitance for describing the surface of a wall on its both sides. Such modification improved the agreement with experiments.
Stable Accumulation of σ54 in Helicobacter pylori Requires the Novel Protein HP0958

ABSTRACT Several flagellar genes in Helicobacter pylori are dependent on σ54 (RpoN) for their expression. These genes encode components of the basal body, the hook protein, and a minor flagellin, FlaB. A protein-protein interaction map for H. pylori constructed from a high-throughput screen of a yeast two-hybrid assay (http://pim.hybrigenics.com/pimrider ext/common/) revealed interactions between σ54 and the conserved hypothetical protein HP0958. To see if HP0958 influences σ54 function, the corresponding gene was disrupted with a kanamycin resistance gene (aphA3) in H. pylori ATCC 43504 and the resulting mutant was analyzed. The hp0958:aphA3 mutant was nonmotile and failed to produce flagella. Introduction of a functional copy of hp0958 into the genome of the hp0958:aphA3 mutant restored flagellar biogenesis and motility. The hp0958:aphA3 mutant was deficient in expressing two σ54-dependent reporter genes, flaB′-′xylE and hp1120′-′xylE. Levels of σ54 in the hp0958 mutant were substantially lower than those in the parental strain, suggesting that the failure of the mutant to express the genes in the RpoN regulon and produce flagella was due to reduced σ54 levels. Expressing σ54 at high levels by putting rpoN under the control of the ureA promoter restored flagellar biogenesis and motility in the hp0958:aphA3 mutant. Turnover of σ54 was more rapid in the hp0958:aphA3 mutant than it was in the wild-type strain, suggesting that HP0958 supports wild-type σ54 levels in H. pylori by protecting it from proteolysis.
Prediction of Nucleosome Forming and Nucleosome Inhibiting DNA Sequences Using Convolutional Neural Networks

The nucleosome is the fundamental unit of DNA packaging in eukaryotic cells. Nucleosomes play a major role in the regulation of gene activity as they act like barriers that control the transcription by allowing or blocking DNA-binding proteins, transcription factors, and activators from accessing to DNA. In this paper, we proposed a deep learning method based on a convolutional neural network (CNN) that can accurately distinct nucleosome-forming from nucleosome-inhibiting DNA sequences. We utilize dataset of three different organisms, and for each dataset, we conduct two different experiments. We exploited $k$-mer frequency count as input as well as using the DNA sequence directly. The proposed CNN models nicely recognize the different DNA sequences by learning the key region and features that characterize each DNA sequence type. We compare our result with the previous works based on the evaluation conducted on three different datasets including Human, Fly, and Worm. The proposed CNN models achieved comparable results.
Early neonatal mortality, asphyxia related deaths, and timing of low risk births in Hesse, Germany, 1990-8: observational study

A higher neonatal mortality related to intrapartum events during the night has been reported in Great Britain.1 2 We investigated whether the time of birth affects early neonatal mortality or deaths related to asphyxia in low risk births. Data from the perinatal birth register of the federal state of Hesse, Germany, 1990-8, were used (www.med-qs-hessen.de). The register comprises detailed information about all infants born in birth clinics (more than 95% of all births in Hesse); about the mother, including the pregnancy; and about the delivery, as documented by the obstetrician in charge of the birth, using an evaluated standardised questionnaire comprising 67 items.3 Detailed information is available about the child's morbidity and reasons for death coded in 40 predefined categories adapted from ICD-9 (international classification of diseases, 9th revision). Outcome events were deaths during labour or within the …
Mining Educational Data to Analyze Students' Behavior and Performance

Predicting and supporting students' behavior turns out to be all the more difficult because of the vast volume of information in educational databases. Currently in Lebanon, the absence of existing system to dissect and screen or the student performance and progress is not used. We analyze educational data to figure out the reasons behind students' behaviors and make a decision for solutions and treatment paths. A systematical system on anticipating student performance is proposed by utilizing mining data procedures to enhance students' accomplishments. We could actually improve students' achievement, success, and bring the benefits and impacts to students, educators and academic institutions. This paper centers on how the expectation calculation can be utilized to distinguish the most imperative qualities in students' information (behavior). We could really enhance students' accomplishment, achievement, and convey the benefits and effects to students, instructors and scholarly establishments.
Designing Sets of Binary Sequences for MIMO Radar Systems

In this paper, we aim at designing sets of binary sequences with good aperiodic/periodic auto- and cross-correlation functions for multiple-input multiple-output (MIMO) radar systems. We show that such a set of sequences can be obtained by minimizing a weighted sum of peak sidelobe level (PSL) and integrated sidelobe level (ISL) with the binary element constraint at the design stage. The sets of designed sequences are neighboring the lower bound on ISL and have a better PSL than the best-known structured sets of binary sequences. To formulate the problem, we introduce a Pareto-objective of weighted auto- and cross-correlation functions by establishing a multi-objective NP-hard constrained optimization problem. Then, by using the block coordinate descent framework, we propose an efficient monotonic algorithm based on fast Fourier transform, to minimize the multi-dimensional objective function. Numerical results illustrate the superior performance of the proposed algorithm in comparison with the state-of-the-art methods.
The efficacy of psychosocial interventions for adults in contexts of ongoing man-made violence - A systematic review.

Compared to psychosocial programs implemented in post-conflict settings those executed in areas of ongoing conflicts may have different effects. Their evidence of efficacy has never been syste- matically reviewed. We searched PubMed, PsychInfo and the Dutch Tropical Institute Literature Portal from inception to31 January 2013 to identify studies on community-oriented psychosocial and psychiatric/clinical services for adults during ongoing man-made conflict or its direct after- math. Of 6358 articles screened, 16 met our inclusion criteria. The interventions varied from psy- cho-educational to psychotropic drugs. The review is presented using outcome indicators such as PTSD, anxiety, depression, physical health, functioning and well being. A substantial improvement of some outcome was found though the small number of studies and their heterogeneity did not justify strong conclusions. PTSD symptoms improved significantly by treatments that included exposure (such as narrative exposure therapy). A number of studies (eight) showed notable im- provement of the client's functioning through counseling interventions. Depression and anxiety both improved considerably using that culturally adapted interventions (two studies), whereas non-culturalized interventions did not. We found a notable lack of studies on the efficacy of medi- cation and on preferred western, evidence-based interventions for PTSD such Eye Movement De- sensitization. To measure outcomes only two studies applied locally-developed diagnostic labels and validated instruments. Future research should encourage the use of robust research methods that are culturally valid, including mixed-methods research to combine measurable outputs with qualitative research aimed at improved understanding from the client's perspective.
Ankle Flexibility and Injury Patterns in Dancers

Lower-extremity injuries are common among dancers and cause significant absences from rehearsals and performances. For this study of lower-extremity injuries in 101 ballet and 47 modern dance students, injuries requiring medical attention sustained over 1 academic year were associated with the following data obtained at the beginning of the school year: ankle flexibility, sex, dance discipline, previous injury, body mass in dex, and years of training. Eighty-three of the 148 students (age range, 12 to 28 years) reported prior lower-limb injuries, the most common being ankle sprains (28% of all dancers). Previous leg injuries cor related significantly with lower dorsiflexion meas urements and with more new injuries. Female students had greater ankle and first metatarsophalangeal flexi bility. Modern dancers had greater ankle inversion. Ninety-four students sustained 177 injuries during the study, including 75 sprains or strains and 71 cases of tendinitis. Thirty-nine percent (N = 69) were ankle injuries; 18% (N = 33) were knee injuries; 23% (N = 40) were foot injuries; and 20% (N = 35) were either hip or thigh injuries. Sixty-seven percent (N = 78) of the injured students were ballet dancers. Age, years of training, body mass index, sex, and ankle range of motion measurement had no predictive value for injury; previous injury and dance discipline both correlated with increased risk of injury.
Efficient Scale-Adaptive License Plate Detection System

License plate detection is a common problem in traffic surveillance applications. Although some solutions have been proposed in the literature, their success is usually restricted to very specific scenarios, with their performance dropping in more demanding conditions. One of the main challenges to be addressed for this kind of systems is the varying scale of the license plates, which depends on the distance between the vehicles and the camera. Traditionally, systems have handled this issue by sequentially running single-scale detectors over a pyramid of images. This approach, although simplifies the training process, requires as many evaluations as considered scales, which leads to running times that grow linearly with the number of scales considered. In this paper, we propose a scale-adaptive deformable part-based model which, based on a well-known boosting algorithm, automatically models scale during the training phase by selecting the most prominent features at each scale and notably reduces the test detection time by avoiding the evaluation at different scales. In addition, our method incorporates an empirically constrained-deformation model that adapts to different levels of deformation shown by distinct local features within license plates. As shown in the experimental section, the proposed detector is robust and scale and perspective independent and can work in quite diverse scenarios. Experiments on two datasets show that the proposed method achieves a significantly better performance in comparison with other methods of the state of the art.
Polyethylene blends with/without graphene for potential recyclable HVDC cable insulation

This paper presents investigations on a usage of graphene as a voltage stabilizer for polyethylene blends in the potential recyclable high voltage direct current (HVDC) cable insulation. Thermal and electrical properties of the blends with/without graphene were evaluated by thermo-gravimetric analysis (TGA), differential scanning calorimetry (DSC), electrical treeing tests, DC conductivity and space charge measurements. Trap energy distributions in the blends were estimated using the measured space charge decay data. The obtained results show that additive-like amounts of graphene can improve the thermal stability of the polyethylene blends. The influence of the graphene on the tree inception voltage (TIV) of the polyethylene blends is not significant, whereas the low density polyethylene/high density polyethylene (LDPE/HDPE) with/without graphene demonstrates the highest TIV comparing to the LDPE, LDPE/polypropylene, and their corresponding graphene added materials. It is found that the DC conductivity of the polyethylene blends with/without graphene increases consistently with the increase of the temperature. The conductivity of the LDPE/HDPE decreases apparently with the inclusion of graphene. It has been shown that space charge accumulations can be suppressed by the addition of graphene in the polyethylene blends. It is postulated that the high trap level and trap energy density of the polyethylene blends with graphene are closely connected to the suppression of the space charge accumulation in the blends.
Assessment of Oral Communication in Senior Engineering Students

Senior engineering students are required to practice oral communication skills during their studies in preparation for their professional practice. However, most technical courses dedicate their time to engineering knowledge rather than oral (or other) communication skills. The paper presents a method with specific materials and rubrics to help students improve their oral communication skills in a technical course. The method prepares students for the final presentation in the Capstone Design course, evaluated by faculty and practicing engineers. Results show that most students attain good and excellent performance in their final oral presentation, demonstrating student’s ability to communicate effectively with practitioner engineers.
Contribution of photoreceptor subtypes to spectral wavelength preference in Drosophila

The visual systems of most species contain photoreceptors with distinct spectral sensitivities that allow animals to distinguish lights by their spectral composition. In Drosophila, photoreceptors R1–R6 have the same spectral sensitivity throughout the eye and are responsible for motion detection. In contrast, photoreceptors R7 and R8 exhibit heterogeneity and are important for color vision. We investigated how photoreceptor types contribute to the attractiveness of light by blocking the function of certain subsets and by measuring differential phototaxis between spectrally different lights. In a “UV vs. blue” choice, flies with only R1–R6, as well as flies with only R7/R8 photoreceptors, preferred blue, suggesting a nonadditive interaction between the two major subsystems. Flies defective for UV-sensitive R7 function preferred blue, whereas flies defective for either type of R8 (blue- or green-sensitive) preferred UV. In a “blue vs. green” choice, flies defective for R8 (blue) preferred green, whereas those defective for R8 (green) preferred blue. Involvement of all photoreceptors [R1–R6, R7, R8 (blue), R8 (green)] distinguishes phototaxis from motion detection that is mediated exclusively by R1–R6.
Modeling Decisions in Collective Risk Social Dilemma Games for Climate Change Using Reinforcement Learning

Prior research has used reinforcement-learning (RL) models like Expectancy-Valence-Learning (EVL) and Prospect-Valence-Learning (PVL) to investigate human decisions in choice games. However, currently little is known on how RL models would account for human decisions in games where people face a collective risk social dilemma (CRSD) against societal problems like climate change. In CRSD game, a group of players invested some part of their private incomes to a public fund over several rounds with the goal of collectively reaching a climate target, failing which climate change would occur with a certain probability and players would lose their remaining incomes. Next EVL and PVL models were calibrated to human decisions across two between-subject conditions in CRSD (Info-all: N=120; No-Info: N=120), where half of the players in each condition possessed lesser wealth (poor) compared to the other half (rich). A symmetric Nash model was also run in both conditions as a benchmark. In Info-all condition, players possessed complete information on investments of other players after every round; whereas, in the No-info condition, players did not possess this information. Our results showed that for both rich and poor players, the EVL model performed better than the PVL model in No-info condition; however, the PVL model performed better than the EVL model in the Info condition. Both the EVL and PVL models outperformed the symmetric Nash model. Model parameters showed reliance on recency, reward-seeking, and exploitative behaviours. We highlight the implications of our model results for situations involving a collective risk social dilemma.
Gender differences in gambling progression.

The authors compared 39 women and 38 men entering an outpatient treatment program for pathological gambling. They were diagnosed according to DSM-IV and selected by SOGS, followed by a semi-structured interview for demography and progression of the gambling behavior prior to treatment. Women were more often single (59% vs. 26%; p = .005) and started gambling significantly later than men (34.2 vs. 20.4 years; p < .001). The progression of the disorder was more than 2 times faster in women than in men. There was no difference in the age of seeking treatment (44.7 vs. 42.3 years). Findings from this study resemble gender differences in other addictions--in particular the faster progression among women--challenge pharmacodynamic hypotheses for this phenomenon, and suggest gender into account when devising treatment strategies for pathological gambling.
Link adaptation strategies for IEEE 802.15.4 WPANs: Protocol design and performance evaluation

This paper proposes two link adaptation strategies for IEEE 802.15. 4 wireless personal area networks (WPANs), using a multi-rate signaling set. In the proposed link adaptation strategies, the most adequate modulation and coding scheme (MCS) satisfying the target bit error rate (BER) of the end device is selected based on the signal-to-interference-plus-noise ratio (SINR) of either a beacon or an acknowledgement (ACK) frame. The beacon-based link adaptation scheme has low complexity and overhead, given that it performs link adaptation only once per superframe. In contrast, the ACK-based strategy performs link adaptation at every ACK frame, and therefore provides a faster and more effective link adaptation, but at the expense of a larger overhead. The specific protocol design for the proposed link adaptation strategies is developed by constructing the signal flow based on the service primitives between the protocol stack layers. The network simulator OPNET is used to implement an accurate IEEE 802.15. 4 WPAN protocol stack and the simulation environment required for performance evaluation. The simulation results show that the received throughput of IEEE 802.15. 4 WPANs can be improved by exploiting the proposed link adaptation strategies instead of auto-rate fallback, the conventional WPAN strategy.
DeepPCA Based Objective Function for Melanoma Detection

In this paper, we propose an objective function for the convolutional neural network to acquire the variation separability as opposed to the categorical cross entropy which maximizes according to the target labels. This approach is an unsupervised learning method which tends to separate the classes according to their variation in the subspace. Finally, the features extracted are classified using support vector machines (SVM). The deep representative features from the CNN are directly from the data, and thus additionally increase the variance between the images making it more discriminative. The idea is to build a CNN (Convolutional Neural Network) and perform the principal component analysis on top of this while training it in an end-to-end fashion. The backpropagation is done to update the parameters according to the eigen representation of the training data. Experimental results on the widely used MEDNODE database which consists of clinical (non-dermoscopic) images shows that our approach is efficient for the classification of melanoma skin cancer detection task.