Miracle-dz/UniFAR-FTUs huggingface dataset:
The Associations of Physical Activity and Screen-2 Time Behaviour with Mental Health in a Nationwide 3 Sample of Kazakhstan Adolescents 4

Mental health problems during adolescence is a serious public health issue in the Republic 17 of Kazakhstan. Early detection is necessary alongside population level monitoring. Physical 18 inactivity (PA) and increased screen-time can be a risk factor for low well-being. The aim of this 19 study was to examine the associations between PA and screen-time with well-being among young 20 adolescents in Kazakhstan. Young adolescents (n=4,731) aged 11y, 13y, and 15y from the Republic 21 of Kazakhstan took part in the World Health Organization (WHO) collaborative Health Behaviour 22 in School-aged Children (HBSC) study. Respondents completed the WHO-5 Well-being scale, PA 23 and screen-time. Internationally recommended cut-offs were used for analyses. Two adjusted 24 models of binary logistic regressions were performed; PA (Model 1) and PA with screen-time 25 (Model 2). The proportion of adolescents with good well-being reduced between 11y to 15y (boys, 26 OR=0.66 CI=0.49-0.80; girls, OR=0.55, CI=0.43-0.71). Boys with daily PA were twice more likely, and 27 girls 3.5 times more likely to report good well-being than inactive peers. More girls with low, than 28 high, screen-time had positive well-being (OR=1.28, CI=1.04-1.59). Location between rural and 29 urban was a significant factor. Daily PA can be protective of low well-being for both boys and girls. 30 However, meeting reporting screen-time recommendations was only protective for girls and not 31 boys. Designing and implementing positive well-being programmes require consideration of 32 locality and amounts of PA and screen-time. 33
1 Market discipline in Brazilian banking : an analysis for the subordinated debt holders

Market discipline is a regulatory mechanism which h as as its main task the punishment of bad risk management by financial institutions. Subordin ated debt holders are considered by the literature as the most propitious private agent to discipline the financial institutions. The key to prove the existence of market discipline is to s h w the relationship between banks’ asset prices and its respective risks. The main objective of this article is an empirical analysis of the relation between credit risk (ratings and accountin g information) and debentures return for the Brazilian case. The results denote a weak presence of market discipline in Brazil.
The Impact of Teaching Approaches and Ordering on IT Project Management: Active Learning vs. Lecturing

This study explores the difference between both active learning and lecturing to teach Scrum project management in a university setting. The goal was to understand if one approach results in higher perceived learning over the other. Additionally, lesson ordering was examined to determine student preference of lecturing prior to or after an active learning exercise. Results suggest that students perceived they learned more from the active learning exercise compared to the lecture. Students preferred the active learning exercise compared to the lecture and found the active learning to be more engaging. Recommendations based on these findings are to use active learning exercises to teach Scrum project management in conjunction with lectures on the topic and to order the lessons with the lecture first followed by the activity.
MPD-AL: An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons

One of the long-standing questions in biology and machine learning is how neural networks may learn important features from the input activities with a delayed feedback, commonly known as the temporal credit-assignment problem. The aggregate-label learning is proposed to resolve this problem by matching the spike count of a neuron with the magnitude of a feedback signal. However, the existing threshold-driven aggregate-label learning algorithms are computationally intensive, resulting in relatively low learning efficiency hence limiting their usability in practical applications. In order to address these limitations, we propose a novel membrane-potential driven aggregate-label learning algorithm, namely MPD-AL. With this algorithm, the easiest modifiable time instant is identified from membrane potential traces of the neuron, and guild the synaptic adaptation based on the presynaptic neurons’ contribution at this time instant. The experimental results demonstrate that the proposed algorithm enables the neurons to generate the desired number of spikes, and to detect useful clues embedded within unrelated spiking activities and background noise with a better learning efficiency over the state-of-the-art TDP1 and Multi-Spike Tempotron algorithms. Furthermore, we propose a data-driven dynamic decoding scheme for practical classification tasks, of which the aggregate labels are hard to define. This scheme effectively improves the classification accuracy of the aggregate-label learning algorithms as demonstrated on a speech recognition task.
econstructing the functional connectivity of multiple spike trains sing Hawkes models

Background: Statistical models that predict neuron spike occurrence from the earlier spiking activity of the whole recorded network are promising tools to reconstruct functional connectivity graphs. Some of the previously used methods are in the general statistical framework of the multivariate Hawkes processes. However, they usually require a huge amount of data, some prior knowledge about the recorded network, and/or may produce an increasing number of spikes along time during simulation. New method: Here, we present a method, based on least-square estimators and LASSO penalty criteria, for a particular class of Hawkes processes that can be used for simulation. Results: Testing our method on small networks modeled with Leaky Integrate and Fire demonstrated that it efficiently detects both excitatory and inhibitory connections. The few errors that occasionally occur with complex networks including common inputs, weak and chained connections, can be discarded based on objective criteria. Comparison with existing methods: With respect to other existing methods, the present one allows to reconstruct functional connectivity of small networks without prior knowledge of their properties or architecture, using an experimentally realistic amount of data. Conclusions: The present method is robust, stable, and can be used on a personal computer as a routine procedure to infer connectivity graphs and generate simulation models from simultaneous spike train
Contact sti ff ness e ff ects on nanoscale high-speed grinding : A molecular dynamics approach

One of the most important grinding parameters is the real depth of cut which is always lower than its programmed value. This is because in reality abrasive grains of the grinding wheel are not fixed but attached to a bonding material which is deformed during the process. In this study we investigate the effect of the contact stiffness between a single abrasive grain and the workpiece on the depth of cut and the grinding process characteristics via three-dimensional Molecular Dynamics (MD) simulations. Contact stiffness has been modelled by attaching a single trapezoid abrasive grain to a spring in the normal grinding direction. MD experiments have been repeated due to the stochastic nature of the grinding process in favour of statistical accuracy. Various grinding speeds have been considered while the case of a rough abrasive-workpiece interface has been investigated as well using fractal models. Our results indicate that the trajectory followed by the abrasive grain is not a straight line, as in the case of a rigid abrasive, but a curved one, asymptotically converging towards the equilibrium point which corresponds to the selected value of the spring stiffness. This behaviour alongside the grinding velocity and rough abrasive-workpiece interface have been found to affect the grinding forces, friction coefficient, morphology of the ground surface and subsurface temperature. The present MD model has also been proven to be capable of capturing the thermal softening phenomenon at the abrasive-workpiece interface.
Large scale video classification using both visual and audio features on YouTube-8 M dataset

Convolutional Neural Networks (CNNs) have achieved state-of-art in image classification and have been progressing rapidly in the field of video classification and audio understanding in recent years. Encouraged by these results, we propose jointly using video and audio features in order to provide a promising classifier for the Youtube-8M Kaggle challenge a video classification task for a dataset of 7 million YouTube videos belonging to 4716 classes[2]. In this paper, we explore several models of different combination of video-level visual and audio features. Our best model uses the mixture of experts (MoE) to receive three inputs. They are video level visual feature only, audio feature only and a concatenation of visual and audio feature. Then we apply a dense layer followed by a ReLu activation layer. The gating network we applied in MoE uses softmax function. We train our model with Tensorflow using 1 GPU on Google Cloud Platform. The average training time is 1 hour 15 minutes. As a result, we achieve Avg Hit@1 of 0.84, Avg PERR (average precision at equal recall rate) of 0.709, and mAP (mean average precision) of 0.415 compared to the best performing baseline proposed in [2] with Avg Hit@1 0.645, Avg PERR of 0.573, mAP of 0.266.
THE PORTRAYAL OF MASCULINITY / FEMINITY BETWEEN MALAYSIAN AND AUSTRALIAN UNIVERSITY WEBSITES

This paper analyzed web features which were applicable to a cultural dimension namely masculinity/feminity which contributed to cultural understanding and assisted web designers in customizing the websites to a specific culture. Quantitative content analysis was utilized through a t-test and discriminant analysis. 60 samples of websites were selected from Malaysian and Australian universities. Predictor variables were “Use a fluid layout”, “Pop-ups”, “Homepage length”, “Use site map”, “Use simple background image”, “Use of flash” and “Highlight critical data”. The findings yielded that there was a relationship between the masculinity/feminity cultural dimension and features of website usability of different countries. Malaysian university websites tend to have lower masculinity index. The results of Discriminant analysis also confirmed that Malaysian university websites and Australian university websites differed significantly on a linear combination of seven variables of masculinity/feminity. Hence, the masculinity/feminity dimension is a factor to consider in ensuring the usability of websites of different countries. This research also suggests that localisation is still important in terms of university web marketing. Hence, the web is not a culturally neutral medium, but they reflect the cultural environment that surrounds the developers. This study is beneficial for web policy makers and web designers of universities in providing a guide in terms of integrating cultural values for specific cultures. Future research should examine other cultural dimension in universities of other countries to gain more insights into the relationship of culture and university web usability.
Conceptual Design of Distributed Propeller Aircraft: Linear Aerodynamic Model Verification of Propeller-Wing Interaction

This paper opens an exciting new opportunity of new aircraft concepts specifically targeting to have higher aerodynamic efficiency than conventional designs through the synergistic interaction between the propeller and the wing. Previous literature on propeller and wing performance analysis methods provide a platform on theory description behind the aerodynamic modeling approach selected. The research effort began with attempts to verify previous NASA wind-tunnel tests (TN D-4448) on a medium and short wing span propeller-driven, short take off and landing (STOL) transport aircraft. One prediction is employed on isolated performance of the wing without the propellers and another is to capture one-way coupling, specifically the effect of the propeller slipstream on the wing. For the first decoupled analysis configuration , the vortex lattice model (VLM) technical tools comparison was made with the Athena Vortex Lattice (AVL) and VSPAERO. Next, the propeller and the wing interaction is predicted using three different coupling methods. The first stage of the work is based on VSPAERO solver which combined the actuator disk theory with VLM. The second approach is to compare with the in house code of blade element and lifting line theory (LLT) coupling. Thirdly, to couple the same BET model with VLM to capture the aerodynamics performance and the influence of the propeller on the wing with the aim to determine the lift and induced drag of the configuration. Perhaps the most compelling aspect offered by the technical tools selected is being economic; low computational cost and time. The numerical computation results of the model presented a good correlation with the experimental data. The aerodynamic model developed will be a strong base for more complex analysis and even greater efficiency improvements for a conceptual design studies of future distributed propeller aircraft .
SYNTHESIS , CHARACTERIZATION AND MICROBIOLOGICAL ACTIVITY EVALUATION OF TWO SILVER COMPLEXES WITH NORFLOXACIN

Silver complexes of norfloxacin (NOR) are interesting for therapeutic purposes due to possible synergistic bactericidal and antifungal potential provided by the metal and fluoroquinolones (FQ). In order to obtain new compounds with superior antibacterial and antifungal properties, we synthesized two silver complexes of NOR. A multi-analytical approach was carried out by using elemental analysis (C, H, N), conductivity measurement, differential scanning calorimetry and spectroscopic methods (FT-IR, H-NMR, UV-VIS and PL). The screening of antibacterial activity and antifungal of the complexes was performed by determination of minimal inhibitory concentration (MIC) through microtiter broth dilution method.
SourceBinder : Community-based Visual and Physical Prototyping

Physical interfaces broaden the entrance into the virtual world through sensors and actuators in our surrounding. Prototyping these interfaces demands expertise in hardware and software development – skills that are rarely found in end users, hobbyists or designers. If those users want to build a rapid prototype for a quick exploration of an idea, they are often troubled with learning the necessary programming and hardware engineering skills. The entry barriers for these target users can be lowered by providing suitable hardware and software toolkits. SourceBinder is a web-based visual programming tool that enables users to create projects and share them in a community. Users can test and adapt existing projects and even become developers by creating new nodes that can be used by the community. We want to present our extensions of SourceBinder which enables hardware to be connected to the visual programming environment, and show some example projects that can be realized in such a setting. Problem statement & motivation In biological systems, there is a tendency for specialised organisms to win out over generalised ones. My argument is that the evolution of technology will likely be no different. Rather than converging towards ever more complex multifunction tools, my claim is that going forward we must diverge towards a set of simpler more specialised tools. (Buxton, 2001) Although Buxton’s claim about the need for more specialized devices is highly controversial, actively promoted research domains like tangible or ambient interfaces and successes in industry (e.g Nintendo Wii input devices, Guitar hero 23 Bettina Conradi, Balázs Serényi, Miriam Kranz, Heinrich Hussmann (2010): SourceBinder: Community-based Visual and Physical Prototyping. In Steffen Budweg, Sebastian Draxler, Steffen Lohmann, Asarnusch Rashid, Gunnar Stevens (Eds.), International Reports on Socio-Informatics (IRSI), Proceedings of the 2nd International Workshop on Open Design Spaces (ODS 2010) (Vol. 7, Iss. 2, pp. 23-35)
A Convolutional Neural Network for Network Intrusion Detection System

System administrators can benefit from deploying Network Intrusion Detection Systems (NIDS) to find potential security breaches. However, security attacks tend to be unpredictable. There are many challenges to develop a flexible and effective NIDS in order to prevent high false alarm rates and low detection accuracy against unknown attacks. In this paper, we propose a deep learning method to implement an effective and flexible NIDS. We used a convolutional neural network (CNN), an advanced deep learning technique, on NSL-KDD, a benchmark dataset for network intrusion. Our experimental results of a 99.79% detection rate when compared against the NSL-KDD test dataset show that CNNs can be applied as a learning method for Intrusion Detection Systems (IDSs).
Canary: a Scalable Content Integrity Verifying Protocol for ICN

The per-packet signature mechanism in NDN is a basic mechanism to provide in-network security. Consumers can validate provenance and integrity with the public key-based signature attached with each Data packet. However, the creation and validation processes of signature cause significant performance bottlenecks in both of consumers and producers. The embedded manifest mechanism was proposed to ease the signing overhead for streaming data producers; a signed manifest packet being composed of digests of subsequent Data packets is inserted per bundle of Data packet while each Data packet has only its digest as SignatureInfo. For a large file, the embedded manifest mechanism still needs producers to sign multiple manifest packets. The basic idea of proposed mechanism, Canary, is to enable per-segment provenance and data integrity validation with only one signing operation of producers even for a large file by exploiting the properties of Merkle tree.
Mapping of radial velocity component in Taylor Couette flow with Ultrasound Doppler Velocimetry (UVP)

An experimental study of flow characterization in a Taylor–Couette system was made by investigating the radial velocity component by Ultrasonic Doppler Velocimetry based flow mapping (UVP-map). With the technique presented in this work, it is possible to measure the radial velocity components for variable of the axial position in a Couette cell within Taylor vortex flow (TVF), wavy vortex flow (WVF) and spiral vortex domains. The resulting r-/zmaps for the different flow states show the location of vortices in the annular gap between the inner and outer cylinder. In the present study, cylindrical and conical concentrically rotating inner bodies were applied a respective flow patterns analyzed. The method uses an additional stroboscopic triggering to synchronize flow measurements and rotational body motion. The fluctuation frequency (ƒ) of unsteady motion in WVF and spiral vortices can be obtained from the power spectrum of velocity. For this, the sampling time period of pulses Δt is calculated from the reciprocal rotational frequency (Δt=1/ƒ). The UVP transducer was preferably positioned in radial direction, normal to the surface of the inner rotating body for measuring the radial velocity component. At the same time, the transducer was moved with constant velocity vertically along the outer cylinder height. Accordingly the total measuring time corresponded to the ratio of cylinder height and velocity.
Can Industrial-Strength Static Analysis Be Used to Help Students Who Are Struggling to Complete Programming Activities?

Static analysis tools evaluate source code to identify potential problems or issues beyond typical compiler errors. Prior work has shown a statistically significant relationship between the correctness of a student’s work and statically identifiable flaws or "code smells" that are likely to indicate programming errors. This paper presents a comprehensive study of this relationship in the context of small programming exercises intended for use in student skill building. We use FindBugs, a static analysis tool that identifies program features that are likely to represent actual bugs in professional software. Our goal is to identify the extent to which FindBugs warnings might help novices struggling to solve short programming exercises. In this study, we ran FindBugs against 149,054 answers submitted by 516 students on 57 drill-and-practice coding exercises. We identify the specific FindBugs warnings that are inversely correlated with correctness. We confirm that presence of these warnings is significantly associated with struggling on an exercise, as indicated by taking more time, making more submissions, and receiving lower scores. Finally, every exercise exhibited answers that trigger these warnings, and 92.4% of students would experience these warnings over a full semester. Our results indicate that static analysis with tools designed for use in industry offers an untapped opportunity to provide hints or suggestions to students who are measurably struggling.
The development of global innovation networks

Internationalisation of R&D has been driven both by the support to global value chains (GVCs) and by the dynamics of innovation processes. Multinational have developed global innovation networks (GINs) including the set of their R&D centres and related networks of cooperation. Within GINs, foreign R&D locations have become more geographically and functionally diversified. They are located in order to take advantage of knowledge resources from different countries and operate a global division of innovation processes.
USAGE OF STATISTICAL MODELING OF LIGHTNING LEADER ADVANCEMENT PROCESS IN THE LAST STROKE PHASE FOR DETERMINATION OF LIGHTNING PROTECTION SYSTEM PARAMETERS

In the paper, the experimental data on the electrical physical characteristics of long spark gaps and lightning are used to create a lightning leader development model in the last stroke phase. The model is verified by comparison of the calculated probabilities of lightning attachments to air terminals and protected objects with normalized level. In order to determine the influence of ground system resistance on protection ability for lightning air terminals, lightning attachments with different ground system resistances have been modeled. The proposed method has been implemented for the calculation of lightning strokes probability to objects of an extended facility with oil storage tanks.