Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy transference in time‐dependent Cattaneo–Christov double diffusion of second‐grade fluid with variable thermal conductivity

The current investigation communicates the characteristics of upper‐convected second grade nanofluid thin film flow over a time‐dependent stretching sheet with variable thermal conductivity and Cattaneo–Christov double diffusion theory. The mathematical model generates a system of nonlinear partial differential equations (PDEs) for heat, momentum, and mass transfer phenomena. Similarity variables converted the PDEs into nonlinear ordinary differential equations (ODEs). Furthermore, received ODEs are numerically rescued with the built‐in program Bvp4c in MATLAB. The impact of physical parameters like second‐grade fluid λ , unsteadiness parameter S , Prandtl number Pr , Schmidt number Sc , variable thermal conductivity ε , variable diffusivity ε 1 , the square of dimensionless film thickness γ , relaxation time δ e , and retardation time δ c are scrutinized. Tables revealed numerical exposure and graphs depict the geometrical aspect of the current study. The velocity field is improved by heightening the λ, magnification in temperature is found for greater conductivity parameter ε . Greater δ e in the temperature profile goes smaller. The rate of mass transfer diminishes by uplifting the estimations in relaxation time parameter δ c .
The Temperature of Morality: A Behavioral Study Concerning the Effect of Moral Decisions on Facial Thermal Variations in Video Games

In this paper, we report on an experiment with The Walking Dead (TWD), which is a narrative-driven adventure game with morally charged decisions set in a post-apocalyptic world filled with zombies. This study aimed to identify physiological markers of moral decisions and non-moral decisions using infrared thermal imaging (ITI). ITI is a non-invasive tool used to capture thermal variations due to blood flow in specific body regions that might be caused by sympathetic activity. Results show that moral decisions seem to elicit a significant decrease in temperature in the chin region 20 seconds after participants are presented with a moral decision. However, given the small sample involved, and the lack of significance in other regions, future studies might be needed to confirm the results obtained in this work.
A Newly Developed Dispersive Interaction Approach, DFT-D3, to the Three-Dimensional Topological Host Material Sb2Te3

Antimony Telluride (Sb2Te3), a topological insulator is a layered semiconductor material with hexagonal unit cell similar to graphene. The characteristic presence of their conducting edges or surfaces with self-induced protection, promise for remarkable future applications. In this exertion based on the first principle approach, the structural and electronic properties of Sb2Te3 compound have been investigated for both without and with spin orbit coupling (SOC). Lattice structure, band structure, total density of states (TDOS), partial density of states (PDOS), energy bands of surface states are determined within Quantum Espresso simulation package. Furthermore, dispersive interactions, induced due to the presence of van-der-Waals forces have also been taken care of. The newly developed method of DFT-D3 has been incorporated for accurate predictions of band gap and lattice parameters. A proficient model, TheSlabModel, has been used to observe the presence of single Dirac cone on the surface. To our knowledge, our theoretical investigations are valid and are found to be congruous with the observed data.
Altered effective connectivity of the extended face processing system in depression and its association with treatment response: findings from the YoDA-C randomized controlled trial

Abstract Background Depression is commonly associated with fronto-amygdala dysfunction during the processing of emotional face expressions. Interactions between these regions are hypothesized to contribute to negative emotional processing biases and as such have been highlighted as potential biomarkers of treatment response. This study aimed to investigate depression associated alterations to directional connectivity and assess the utility of these parameters as predictors of treatment response. Methods Ninety-two unmedicated adolescents and young adults (mean age 20.1; 56.5% female) with moderate-to-severe major depressive disorder and 88 healthy controls (mean age 19.8; 61.4% female) completed an implicit emotional face processing fMRI task. Patients were randomized to receive cognitive behavioral therapy for 12 weeks, plus either fluoxetine or placebo. Using dynamic causal modelling, we examined functional relationships between six brain regions implicated in emotional face processing, comparing both patients and controls and treatment responders and non-responders. Results Depressed patients demonstrated reduced inhibition from the dlPFC to vmPFC and reduced excitation from the dlPFC to amygdala during sad expression processing. During fearful expression processing patients showed reduced inhibition from the vmPFC to amygdala and reduced excitation from the amygdala to dlPFC. Response was associated with connectivity from the amygdala to dlPFC during sad expression processing and amygdala to vmPFC connectivity during fearful expression processing. Conclusions Our study clarifies the nature of face processing network alterations in adolescents and young adults with depression, highlighting key interactions between the amygdala and prefrontal cortex. Moreover, these findings highlight the potential utility of these interactions in predicting treatment response.
SBL Kalman Filter Based Hybrid Precoder/ Combiner for mmWave MIMO Systems: A Frequency Domain Approach

The optimal design of hybrid precoder/ combiner for Millimetre Wave (mmWave) Multiple Input and Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM ) system is developed presented. In the frequency domain approach, Sparse Bayesian Learning - Kalman Filter (SBL-KF) algorithm is used to design the optimal hybrid precoder/ combiner in mmWave MIMO OFDM systems. Sparse signal recovery problem for Single Measurement Vector (SMV) is discussed, that is close to the design of ideal digital baseband precoder by maximizing the mutual information from the hybrid precoder. SBL-KF scheme select the minimum number of active Radio Frequency (RF) chains based on the hyper parameter estimator. The minimum number of RF chain is approximate the ideal digital precoder / combiner design. Proposed SBL-KF scheme achieve low power consumption and enhanced spectral efficiency, when compared to the SBL, Orthogonal Matching Pursuit (OMP), Simultaneous OMP (SOMP) and Least Square schemes, which activate a fixed data streams and fixed number of RF chains.
Research on the Integration of New Media Technology and Ideological and Political Education Teaching

The concept and characteristics of new media are summarized and summarized, and the influence of Ideological and political education in Colleges and universities is briefly analyzed, and the connotation and development process of Ideological and political education in Colleges and universities are briefly written. From two angles of the subject and object of Ideological and political education in Colleges and universities, the application of new media in the ideological and political education of colleges and universities is combined with the data from the questionnaire survey, and the quantitative and qualitative two analytical methods are used to analyze the application of the new media in the ideological and political education of colleges and universities. The existing problems are studied from four aspects: the application degree of the new media, the authority of the main body of education, the increase of education difficulty and the existing problems of the object of education. Through the in-depth study of the causes of the problem, the solution of the theoretical knowledge of other disciplines is put forward by the combination of theory and practice as a principle. Countermeasures and creatively explore new ways of combining new media with ideological and political education.
Analysis of customer satisfaction using Total Quality Management (TQM) junior high school

To develop the potential of students must be supported by quality education. Total Quality Management becomes a management approach centered on quality for long-term success through customer satisfaction. The purpose of this study is to find out how customer satisfaction is assessed from aspects of tangibles (direct evidence), reliability, responsiveness, assurance, and empathy. This research uses mixed methods with the Embedded Concurrent model (unbalanced mixture), applied to students with a sample of 90 students as respondents chosen randomly with 25 items of questions, observations, interviews, documentation. The findings of these study address customers getting satisfaction with the services provided by schools. With responsiveness aspects that are more prominent than other elements.
System Identification of Coupled Electric Drive Using Machine Learning Algorithms

: System identification is behaviour of the system and hence nonlinear system identification is important. Machine learning which the application of artificial intelligence technique are programs that can learn and adapt to the changes without human interference. These are implemented in such a way that they try to find the relationship between the inputs and the target. Hence machine learning algorithms such as gradient descent based linear regression and neural networks are implemented for a coupled electric drive system. The simulation results are then analysed for their performance indices. the method of developing mathematical relationship between the input and output variables. Linear models cannot capture the non-linear
Thriving or surviving at work: how workplace learning opportunities and subjective career success are connected with job satisfaction and turnover intention?

Purpose The purpose of this study is to better understand factors related to turnover intention (TI) and job satisfaction (JS) in the information technology and engineering sectors. Specifically, this study investigates the role of workplace learning opportunities (WLO) afforded by the environment and individual’s subjective career success (SCS). The connections between learning opportunities and career success are examined, as well as their connections to JS and TI. Design/methodology/approach The current research was based on self-report questionnaire data (N = 153). The questionnaire included existing instruments measuring WLO, SCS, JS and TI. The analyses of the data included Pearson product-moment correlations, path analysis (based on multiple regression) and analysis of relative importance (dominance analysis). Findings Results indicated that higher access to resources that support learning, more opportunities for professional growth and satisfactory career decisions made by employees were connected to lower TI. The processes of well-being and learning are strongly intertwined and mutually reinforce each other, reducing the willingness to change a job in the near future. Originality/value This study adds to the previous research by providing more detailed knowledge on the connections between the various dimensions of WLO and SCS. The findings of the present study can offer insights for developing work environments where employees wish to remain, learn and are satisfied with their job and careers, thus ultimately supporting their well-being.
Measurement results for compensation of impairments of LTE stimulated direct‐conversion transmitter through augmented MoE

This work presents a neural network‐based one‐step solution for modeling predistorter and mitigating the nonlinear distortion of PA along with impairments, I/Q imbalance, and DC offset of the direct conversion transmitter for wide‐band signals. In this work, a modified form of Mixture of experts (MoE), augmented MoE is used as a predistorter to linearize direct conversion transmitter. MoE model encompasses a family of modular neural network architectures having several expert networks connected to a single gating network, and it follows the Divide‐and‐Conquer principle. The direct‐conversion transmitter with class AB‐PA was stimulated with a wide‐band three carriers Long‐Term Evolution (LTE) with different bandwidth signals. The presented method's measurement results show that the proposed model has good linearization performance in the presence of transmitter impairments.
Self-Reliant Learning Strategy in Vocational and Technical Education: Insights from Group Collaboration

In this study, a self-reliant learning strategy was used in the teaching and learning of a Mathematics module at a local technical institution to investigate its effectiveness in improving the students' performance in descriptive statistics. This study also examined how group work activity, when integrated with the self-reliant strategy, can contribute to students' development in directing their learning. Forty-two students were observed on how a self-reliant learning strategy affects their performance. It is found that the self-reliant learning strategy had a positive impact on the students' performance in their learning of descriptive statistics and that group work activity improved students' learning skills, especially on planning, monitoring, and evaluating their course of learning on their own. The findings of this study hoped to provide pedagogical alternatives and persuade teachers to consider the self-reliant learning strategy that promotes flexibility in the course of the students' learning.
Is Attentional Bias To Idiosyncratic Stimuli Related To Borderline Symptomatology?

Background: In borderline personality disorder, attentional bias to emotional stimuli may be a fundamental component in their origin and maintenance. However, the authors seem divided between the hypothesis of hypervigilance for negative stimuli and the hypothesis of over-reactivity against any type of stimuli. Aims: We aimed to observe the association between borderline symptoms and the allocation of attention to neutral, idiosyncratic negative and general negative emotional words. Method: We tested thirty-five portuguese university students, aged between 18 and 40 years old with an Emotional Stroop paradigm. Results: Our results suggest that a higher score of borderline symptoms are associated with a greater interference of idiosyncratic negative words in the colour identification task. Conclusions: These results support the hypervigilance hypotheses for idiosyncratic borderline stimuli. In other words, this study suggested that borderline sympotms is linked to an inability to disengage attention from negative words typically of borderline disorder. Based on these findings, mood-dependent therapeutic interventions focusing on attentional processes may represent a useful contribute to established therapies in patients with BPD.
A Codesigned Integrated Photonic Electronic Neuron

In the modern era of artificial intelligence, increasingly sophisticated artificial neural networks (ANNs) are implemented, which pose challenges in terms of execution speed and power consumption. To tackle this problem, recent research on reduced-precision ANNs opened the possibility to exploit analog hardware for neuromorphic acceleration. In this scenario, photonic-electronic engines are emerging as a short-medium term solution to exploit the high speed and inherent parallelism of optics for linear computations needed in ANN, while resorting to electronic circuitry for signal conditioning and memory storage. In this paper we introduce a precision-scalable integrated Photonic-Electronic Multiply-Accumulate Neuron (PEMAN). The proposed device relies on (i) an analog photonic engine to perform reduced-precision multiplications at high speed and low power, and (ii) an electronic front-end for accumulation and application of the nonlinear activation function by means of a nonlinear encoding in the analog-to-digital converter (ADC). The device has been numerically validated through cosimulations to perform multiply-accumulate operations (MAC). Simulations are based on the iSiPP50G SOI process for the photonic engine and a commercial 28 nm CMOS process for the electronic front-end. The PEMAN exhibits a multiplication accuracy of 6.1 ENOB up to 10 GMAC/s, while it can perform computations up to 56 GMAC/s with a reduced accuracy down to 2.1 ENOB. The device can trade off speed and power consumption with resolution, significantly outperforming its analog electronics counterparts both in terms of speed and energy consumption. With respect to other photonic ANNs, the PEMAN has comparable speed and energy consumption with a higher resolution, while outperforming them by a hundredfold in the fan-in, which opens the possibility to accelerate more complex networks.
Climate-Induced Relocation and Social Change in Keta, Ghana

In this article, I analyze the resettlement of three communities in the Keta municipality of Ghana as a result of rising sea levels that threatened life and property. Although a few studies have documented the effects of relocation because of slow-onset climate-induced environmental change, little is known about how such resettlements have contributed to positive social change in the affected communities. I used critical theory to determine whether Keta’s relocation process contributed to positive social change. Transcriptions of interviews with a purposeful sample of 35 household members were coded and categorized into themes for essence description. Improved educational infrastructure for personal development, improved housing facilities, saved lives and protected culture, and improved healthcare facilities and general well-being were among the positive outcomes. Hence, through this study, I provide evidence to consider the need to prioritize the positive social change such resettlements will make in the lives of the affected populations in climate-induced resettlement and adaptation in Ghana and other parts of the world. Keywords: Climate change, relocation, resettlement, social change, sea level rise, improved livelihoods
Couples’ perceptions of each other’s depressive symptoms: Empathic accuracy and assumed similarity bias

The link between depressive symptoms and relationship functioning has been well-documented. Evidence for affective concordance in depressive symptoms between partners suggests that couples are aware of each other’s mood and symptoms; however, there have been no direct tests of the extent to which couples accurately perceive their partner’s mental health. The present study assessed spouses’ empathic accuracy and assumed similarity bias in rating each other’s depressive symptoms using the truth and bias actor-partner interdependence model for indistinguishable dyads. We hypothesized that husbands and wives would show significant assumed similarity but not significant empathic accuracy when rating their partner’s depressive symptoms. Participants were 55 racially and ethnically diverse heterosexual couples (N = 110 individuals) with a child between the ages of 10–16 recruited from the community. Results did not provide evidence for empathic accuracy in rating a spouse’s depressive symptoms. Instead, we found significant assumed similarity, such that ratings of a spouse’s depressive symptoms were associated with one’s own level of depressive symptoms. We also found evidence of directional bias, such that, on average, spouses overestimated each other’s level of depressive symptoms. These preliminary findings suggest that couples may not be particularly attuned to their partner’s subjective ratings of depression-related thoughts, feelings, and behaviors. Future research should explore the processes accounting for partners’ perceptions of each other’s mental health, and the impact of these perceptions on relationship functioning.
Biogas Reforming as a Precursor for Integrated Algae Biorefineries: Simulation and Techno-Economic Analysis

Biogas is a significant by-product produced in algae processing and may be used for many different applications, not only as a renewable energy carrier but also as a chemical intermediate in integrated algae-based biorefineries. In this work, the reforming of biogas to H2/CO2 mixtures (referred to as SynFeed) as feed for the direct hydrogenation of CO2 to methanol is investigated. Two conventional processes, namely steam methane and autothermal reforming, with upstream CO2 separation from raw biogas are compared to novel concepts of direct biogas bi- and tri-reforming. In addition, downstream CO2 separation from SynFeed using the commercial Selexol process to produce pure H2 and CO2 is considered. The results show that upstream CO2 separation with subsequent steam methane reforming is the most economic process, costing 142.48 €/tSynFeed, and taking into consideration the revenue from excess hydrogen. Bi-reforming is the most expensive process, with a cost of 413.44 €/tSynFeed, due to the high demand of raw biogas input. Overall, SynFeed from biogas is more economical than SynFeed from CO2 capture and water electrolysis (464 €/tSynFeed), but is slightly more expensive than using natural gas as an input (107 €/SynFeed). Carbon capture using Selexol comes with costs of 22.58–27.19 €/tCO2, where approximately 50% of the costs are derived from the final CO2 compression.
vlda: An R package for statistical visualization of multidimensional longitudinal data

The vlda is an R (R Development Core team et al. , 2011) package which provides functions for visualization of multidimensional longitudinal data. In particular, the R package vlda was developed to assist in producing a plot that more e ﬀ ectively expresses changes over time for two di ﬀ erent types (long format and wide format) and uses a consistent calling scheme for longitudinal data. The main features of this package allow us to identify the relationship between categories and objects using an indicator matrix with object information, as well as to cluster objects. The R package vlda can be used to understand trends in observations over time in addition to identifying relative relationships at a simple visualization level. It also o ﬀ ers a new interactive implementation to perform additional interpretation, therefore it is useful for longitudinal data visual analysis. Due to the synergistic relationship between the existing VLDA plot and interactive features, the user is empowered by a reﬁned observe the visual aspects of the VLDA plot layout. Furthermore, it allows the projection of supplementary information (supplementary objects and variables) that often occurs in longitudinal data of graphs. In this study, practical examples are provided to highlight the implemented methods of real applications.
Diagnosis of Broken Bars in Wind Turbine Squirrel Cage Induction Generator: Approach Based on Current Signal and Generative Adversarial Networks

To ensure the profitability of the wind industry, one of the most important objectives is to minimize maintenance costs. For this reason, the components of wind turbines are continuously monitored to detect any type of failure by analyzing the signals measured by the sensors included in the condition monitoring system. Most of the proposals for the detection and diagnosis of faults based on signal processing and artificial intelligence models use a fault-free signal and a signal acquired on a system in which a fault has been provoked; however, when the failures are incipient, the frequency components associated with the failures are very close to the fundamental component and there are incomplete data, the detection and diagnosis of failures is difficult. Therefore, the purpose of this research is to detect and diagnose failures of the electric generator of wind turbines in operation, using the current signal and applying generative adversarial networks to obtain synthetic data that allow for counteracting the problem of an unbalanced dataset. The proposal is useful for the detection of broken bars in squirrel cage induction generators, which, according to the control system, were in a healthy state.