Miracle-dz/UniFAR-FTUs huggingface dataset:
Interest-Based Content Clustering for Enhancing Searching and Recommendations on Smart TV

Smart TV has become a pervasive device due to its support for numerous entertainment options. These capabilities of smart TV make it attractive for viewers and researcher. Besides, a plethora of multimedia content continues to grow, which makes searching and browsing the desired content a difficult, time-consuming, and contributes to cognitive overload problem. In the case of smart TV, making clusters of the related content based on user’s interest is among the best solutions. In this connection, this study proposed a dynamic approach for clustering the TV-related online multimedia content and presenting them in a manageable format on smart TV to mitigate the issue of searching and relevant recommendations. We collected and clustered the content from diverse data sources based on the viewer’s interest. This further recommends novel content to the viewers without social metadata, such as rates, tags, which is normally insignificant in for smart TV viewership due to its shared nature. We used bisecting K -means, Lingo, and Suffix Tree Clustering (STC) algorithms. A comparative analysis of these algorithms and suitability in the context of smart TV is also presented. Results show that the proposed approach enhances search results and recommends relevant content based on user’s interests.
From Hydrogen Manifesto, through Green Deal and Just Transition, to Clean Energy Act

The Year 2020 charted a seminal change in the way we see hydrogen technology as the backbone of decarbonization of the economy. And this charter was taken by far most ambitiously by the countries of the European Union. Streaming from their Hydrogen Manifesto, the governments and businesses, political parties and NGOs all stood on the path that leads to the European Green Deal, which starts with the Recovery and Resilience Facility and continues through the Just Transition Platform. The European Commission was the first to declare the official “taxonomy” for hydrogen as “green”, “blue” and “gray” hydrogen. This article will introduce the vision: Fit for 55 as a goal of cutting CO2 emissions by 55% in less than a decade and will touch on some of the regulatory and financial instruments to reach it. What year 2021 will bring is germinated in close to 300 running projects with the contributions from every corner of the European Union.
DESIGN, SIMULATION AND ANALYSIS OF THE SWITCHING AND RF PERFORMANCE OF MULTI-GATE SILICON-ON-INSULATOR MOSFET DEVICE STRUCTURES

Silicon-only MOSFETs have fast approached their scaling limitations and new technologies are constantly being investigated with an intention to replace the planar MOSFET. The Silicon-on-Insulator (SOI) technology is the forerunner in many such ongoing investigations. Devices fabricated using this technology exhibit reduced capacitances, lower leakage currents and higher ease of integration when scaled into the sub-nanometer regime. With the advent of novel and reliable fabrication techniques, multi-gate SOI devices viz. the FinFET, TriGate, Omega-gate and Quadruple gate devices are expected to make inroads into integrated circuit applications previously dominated exclusively by planar MOSFETs. This study examines the switching and RF performance of these multi-gate devices under aggressive scaling conditions. A three dimensional numerical simulator ATLAS, from SILVACO International has been employed for the purpose of device simulations. The primary focus of attention is a variation in the subthreshold device performance when subjected to a change in dimensions. This study also examines the microwave performance of the devices by virtue of a simulation analysis of their small-signal behavior. In conjunction with N-channel devices, the study also focuses on P-channel devices and compares the performances of the two types of devices. The study also includes an analysis of device behavior under high temperature conditions. Also included is an investigation into device performance that accounts for the presence of the extension and LDD regions that are very much common to decananometer gatelength MOSFETs. Out of the four possible multi-gate SOI device structures, the FinFET and the TriGate devices appear to be the most promising alternatives to replace the conventional MOSFET in future applications.
Cuvier’s beaked whale foraging dives identified via machine learning using depth and triaxial acceleration

: Knowledge of Cuvier’s beaked whale Ziphius cavirostris behavior has expanded through the utilization of animal-borne tags. However, many tag types do not record sound — thus preventing echolocation click detections to identify foraging — or have short deployments that sample a limited range of behaviors. As the quantity of such non-acoustic tag data grows, so too does the need for robust methods of detecting foraging from non-acoustic data. We used 692 dives from 5 sound-recording tags on Cuvier’s beaked whales in southern California, USA, to develop extreme gradient boosting tree models to detect foraging based on 1 Hz depth and 16 Hz triaxial acceleration data. We performed repeated 10-fold cross validation using classification accuracy to tune 500 models with randomly partitioned training and testing datasets. An average of 99.9 and 99.2% of training and testing dataset dives, respectively, were correctly classified across the 500 models. Dives without associated sound recordings (n = 2069 from 7 whales including 4 non-acoustic tags) were classiﬁed via a model that maximized training information using dive depth and duration, ascent and descent rates, bottom-phase average vertical speed, and roll circular variance during dive descents and bottom phases. Of all long, deep dives (conventionally assumed to include foraging), 2.4% were classified as non-foraging dives, while 0.3% of short, shallow dives were classified as foraging dives. Results confirm that conventional depth and/or duration classifiers provide reasonable estimates of longer-term foraging patterns. However, additional variables previously listed enhance foraging detections for unusual dives (notably non-foraging deep dives) for southern California Cuvier’s beaked whales.
Design of Leg Wheel Hybrid Hexapod with C-Leg Analysis

The conventional mobile robotic platforms which either uses wheels or legs are quite familiar and each one of them has its own advantages and disadvantages. The wheeled robot is suitable for only plain and smooth terrain, whereas the legged robot can travel in any kind of terrain but is comparatively slower than the wheeled robot. So, a hybrid of both wheeled and legged platform would be quite suitable for any kind of terrain. The primary focus of this paper is to design and develop a leg-wheel hybrid robotic platform with a concurrent engineering and mechatronics approach to produce results with optimised design metrics at each and every stage of its development. An overall view of the entire mechatronics system is considered for design and development of the robot at each and every stage rather than a sequential engineering approach. This paper details the Finite Element Analysis (FEA) of the C – Legs which are used in the robot.
Utilizing a storyline approach to facilitating pupils’ agency in primary school sustainability education context

Abstract This article presents a six-week long action research study in two primary school classes, with the aim of exploring how a Storyline approach can facilitate learning and acting on sustainability issues, and how this approach might enhance pupils’ agency. This study is underpinned by and analyzed through theories of relational pedagogy, in which communication processes and interaction are central aspects of the learning process. The empirical material consists of video observations from classroom situations. The results show relational aspects of the teacher’s work in a Storyline and highlight the importance of the teacher’s caring role Storyline instruction. Further, results suggest that the reflective process entails critical thinking and has potential to support development of pupils’ democratic capabilities, including a civic dimension. This action research study adds to evidence concerning how relational agency has been exercised and performed through features of a Storyline.
Accessing Supermarket Shelves: Retail Category Managers Advice to Upcycled Food Manufacturers

ABSTRACT Upcycled food is a new way of communicating to consumers the age-old process of creating new foods from by-products or unmarketable produce. Consumers are open to the idea of purchasing upcycled foods yet the availability of these products in supermarkets is limited. Securing shelf space will help to ensure the growth of this trend. Therefore, this research identified the enabling attributes of upcycled products that category managers approve for retail. Seven semi-structured, qualitative interviews were conducted with retail category managers using the Delphi technique. Category managers assess new products through two lenses, a customer-focused lens where they seek evidence that a new product can meet an identified customer demand, and a vendor-focused lens through which they seek confidence in the manufacturer’s marketing plan, pricing structure, and product placement within the relevant category architecture. This research delivers guidance for food industry stakeholders and serves as a call to action for upcycled food manufacturers.
CLIMATE CHANGE IMPACTS ON HYDROPOWER GENERATION AT KENYIR LAKE

Climate change is triggered by human activities that produce greenhouse gas emissions and affect people in various ways. It is crucial to study the severity of rainfall in the certain potential areas that exposed to hydro-meteorological disasters in climatic trends transition. The objectives of the study are to evaluate the severity of rainfall trends and also to predict the fluctuations of hydropower generation in Kenyir Lake triggered by the variations of climatic factors under selected Representative Concentration Pathways, RCPs (RCP2.6, RCP4.5 and RCP8.5) suggested in the Intergovernmental Panel on Climate Change’s (IPCC) fifth assessment report. The historical daily data of seven rainfall stations for 30 years’ period (1988 - 2017) and global climate model data for RCP2.6, RCP4.5 and RCP8.5 also for 30 years’ period (2041-2070) were used. The statistical downscaling model (SDSM) was used to analyse the data. The predicted rainfall data from 2041 to 2070 then compared with the base period rainfall (1988-2017). Kenyir Lake received highest amount of rainfall in November to January during north-east monsoon. The significance differences were recorded in November and December where abrupt fall of rainfall distribution predicted to happen for all RCPs. The results proved that the higher emissions level will give the more effect to the climate trend as previous researcher found that warming will remain beyond 2100 for all RCP scenarios except RCP2.6. The lowest generated value at Kenyir is in 1997 and the highest value is in 2017. The increment of NUG clearly happens in 10 years’ interval where there was 78.67% of increment in 2007 compared to 1997. There is an increase that occurs although there are fluctuations every year. Increases in temperature because of climate change effects will increase the energy demand. Rising temperatures gives the varies patterns of demand because higher temperature will create higher cooling demand. Besides that, power generation can change accordingly by the decreasing stream flow and increasing water temperature. It shows that climate change tremendously affects the energy demand patterns and supply systems.
Programming Languages for Data-Intensive HPC Applications: a Systematic Literature Review

We present the results of a systematic literature review that examines the main paradigms and properties of programming languages developed for and used in High Performance Computing for Big Data processing. The systematic literature review is based on a combination of automated keyword-based search in the Elsevier Science Direct database and further digital databases for articles published in international peer-reviewed journals and conferences, leading to an initial sample of 420 articles, which was then narrowed down in a second phase to 152 articles found relevant and published 2006-2018. The manual analysis of these articles allowed us to identify 26 languages used in 33 of these articles for HPC for Big Data processing. We analyzed the languages and their usage in these articles by 22 criteria and summarize the results in this article. We evaluate the outcomes of the literature review by comparing them with opinions of domain experts. Our results indicate that, for instance, the majority of the used HPC languages in the context of Big Data are text-based general-purpose programming languages and target the end-user community.
Effect of micro graphite particles on the microstructure and mechanical behavior of aluminium 6061 (Al-Mg-Si) alloy composites developed by novel two step casting technique

In the present research, the effect of micron sized graphite addition on the microstructure and tensile failure of Al6061 alloy has been studied. The Al6061 alloy metal matrix composites reinforced with 6, 9 and 12 varying weight percentages of graphite particles were fabricated by novel two step stir cast route which helps in improving the wettability of Al6061 alloy matrix with graphite particles. The synthesized composites were subjected to microstructural studies, density, hardness and tensile properties testing. Microstructural characterizations of obtained samples were carried out by SEM microscopy, EDS and XRD patterns. The occurrence of graphite particles were confirmed by the XRD patterns. The density and hardness of metal composites have been decreased with adding of graphite reinforcement, while the ultimate tensile strength and yield strengths were improved with the addition of graphite particles. There was increase in the elongation of the Al6061 alloy composite after the incorporation of the reinforcement. Various fracture mechanisms were observed in the Al6061-graphite composites using SEM.
The Effectiveness of a Positive Youth Development Education Program with an Islamic Approach on Social Health and Rumination of Male Adolescents at Risk of Methadone Addiction

: The aim of this study was to evaluate the effectiveness of the positive youth development education program with an Islamic approach on social health and rumination of male adolescents at risk of methadone addiction in Bushehr city, Iran in 2022. This quasi-experimental study was conducted with a pretest-posttest control group design. The statistical population of the study was male adolescents at risk of methadone addiction in Bushehr. Thirty male adolescents at risk of methadone addiction who had the highest scores in problems of social health and rumination were purposefully selected and randomly assigned into experimental and control groups. After performing the pre-test, the experimental group was exposed to the positive youth development education program with an Islamic approach based on Kiani study, for 9 sessions of 60 minutes (one session per week). The Keyes Social Health Questionnaire and the Hoeksema and Morrow Ruminative Response Scale were used to collect data. The results indicated that the positive youth development education program with an Islamic approach improved social health and its components including social cohesion, social adaptation, social participation, social prosperity and social acceptance in the experimental group compared to the control group. The intervention also reduced rumination in the experimental group compared to the control group. of positive youth development education program on life satisfaction and self-efficacy in adolescents. The results showed that in the short and long term, the positive youth development education program is effective on adolescent life satisfaction and self-efficacy. Babaee et al. (2018) in a study on the psychometric properties of the Adolescent Positive Development Scale in students showed that positive adolescent development has a positive relationship with discipline and academic achievement and a negative and significant relationship with bullying. Jiang et al. (2021) in a study examined the effect of the positive youth development education program on psychological wellbeing and mental health among Chinese adolescents. The results showed that the characteristics of positive change affect the psychological well-being of homeless youth. Wong (2012) in a study examined the effect of the negative versus positive thinking development program on the psychological well-being and intellectual maladaptation of Singaporean students. The results showed that the evolution of negative thinking leads to a decrease in psychological well-being and an increase in psychological maladaptation in Singaporean students. Rew et al. (2019) in a study examined the effect of positive youth development education program on the mental health and psychological well-being of homeless youth. The results showed that the characteristics of positive change affect the mental health of homeless
Burst Spinal Cord Stimulation in the Management of Chronic Pain: Current Perspectives

Over the last several decades, opioid diversion, misuse, and over-prescription have run rampant in the United States. Spinal cord stimulation (SCS) has been FDA approved for treatment for a primary indication of neuropathic limb pain that is resistant to more conservative medical therapy. The disorders qualified for treatment include neuropathic, post-surgical, post-amputation, osteodegenerative, and pain related to vascular disease. Some of the most frequently cited conditions for treatment of SCS include failed back surgery syndrome, complex regional pain syndrome (CRPS) Type I and Type II, and post-herpetic neuralgias. Developments in SCS systems have led to the differentiation between the delivered electromechanical waveform patterns, including tonic, burst, and high-frequency. Burst SCS mitigates traditional paresthesia due to expedited action potential and offers improved pain relief. Burst SCS has been shown in available studies to be non-inferior to the traditional SCS, which can cause pain paresthesia in patients who already have chronic pain. Burst SCS does not seem to cause or need the paresthesia seen in traditional SCS, making SCS not tolerable to patients. Moreover, some studies suggest that burst SCS may decrease opioid consumption in patients with chronic pain. This can make burst SCS an extremely useful tool in the battle against chronic pain and the raging opioid epidemic. As of now, more research needs to be performed to further delineate the effectiveness and long-term safety of this device.
Haptic texture rendering and perception using coil array magnetic levitation haptic interface: Effects of torque feedback and probe type on roughness perception

A Novel maglev-based haptic platform was deployed to investigate the effects of torque feedback and stylus type on human roughness perception. For this purpose, two haptic probes, fingertip and penhandle, were 3D printed each with one and four embedded magnets respectively. Three different torque renderings namely No Torque, Slope Torque, and Stiff Torque were developed, in tendem with penetration-based force feedback to render simulated surfaces. The main difference between these conditions was the amount and type of active torque that was generated. Conventional magnitude estimation experiment for data gathering and analysis was performed. The results of the experiment showed strong effects of wavelength within all torques and probes. Participants rated surfaces rougher in the Slope Torque and with the fingertip compared to penhandle. These results revealed new means of torque-based surface generation that lead to higher roughness perception. The outcomes also highlight the importance of probe type on human roughness perception.
DESIGN OF 1KB SRAM ARRAY USING ENHANCED STABILITY 10T SRAM CELL FOR FPGA BASED APPLICATIONS

SRAM used for the FPGA, requires higher stability and low power consumption. 8T SRAM cell has degraded write stability with the decreasing supply voltages. 10T SRAM cell has higher write stability because of the cut-off switch employed in the pull-up path in one of the inverters. The design of SRAM array with low power consumption and higher stability is of major importance. So, 1Kb SRAM array using 8T and 10T SRAM cells has been designed and compared for different design metrics. Write 0 and Write 1 power is lower by 1.98×, 3.52× in 10T SRAM Array than 8T SRAM Array at 0.9V DD , SS corner. Due to the usage of High-V th transistors in 10T SRAM cell, the Read power is lower by 1.6× than 8T SRAM Array for 0.9V V DD at SS Corner. The leakage power while holding 0 is lower by 1.13× in 10T SRAM array than 8T SRAM array at FF corner at 0.9V V DD. The design metrics are evaluated for a wide range of supply voltage. The designs are implemented in Cadence Virtuoso in 45nm Technology node.
Psychedelics use predicts more positive emotional reactivity and diminished outward-focused self-consciousness: the mediating role of ego dissolution and mystical experiences

Background: Psychedelics are able to acutely alter emotional reactivity and self-consciousness. However, whether regular, naturalistic use of psychedelics can be linked to more persistent, trait-level changes in these domains remains an open question.Aim: To test three hypotheses: i) psychedelics use is related to higher positive and lower negative emotional reactivity; ii) psychedelics use is related to enhanced inward-focused self-consciousness and diminished outward-focused self-consciousness; iii) these relations are mediated by the intensity of past ego-dissolution and mystical experiences.Methods: Data from 2,516 participants (1,661 psychedelics users) were collected via an online survey. The survey included questions about the history of psychoactive substance use, questionnaires measuring trait-levels of emotional reactivity and self-consciousness, and questionnaires for retrospective assessment of ego-dissolution and mystical experiences. Data were analyzed using robust linear regression and mediation analysis.Results: First, a higher number of lifetime psychedelic experiences predicted greater positive and lower negative emotional reactivity. Second, in the domain of self, it predicted greater reflection and internal self-awareness, and reduced rumination tendency and public self-consciousness. Finally, intensity of past mystical and ego-dissolution experiences mediated almost all observed relationships between the lifetime psychedelics use and psychological variables. Conclusions: Lifetime psychedelics use predicts an adaptive pattern of trait-level emotional reactivity and self-consciousness. The past ego-dissolution and mystical experiences are essential in understanding the long-lasting psychological effects of psychedelics use. Our findings might potentially explain previous observations of increased well-being in psychedelics users.
A Novel Credit Risk Assessment Model Based on LightGBM

: Credit risk assessment is a critical process in the bank’s approval of loans and is of great significance in the bank’s risk management. With the development of big data and artificial intelligence technology, it is an important research direction to comprehensively evaluate enterprise or individual credit based on multidimensional data. In this paper, we apply a new LightGBM model based on the decision tree algorithm promotion framework to implement credit risk assessment, which is a typical binary classification problem. The results show that compared with the classical SVM model, LightGBM could achieve higher prediction accuracy, so it is an accurate and effective credit risk assessment method.