Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the Use of Deep Learning and Implicit Feedback in K12 Educational Recommender Systems

Recommender systems are increasingly being used in university or online education. However, recommender systems still have not found major usage in K12 education. This may be because of the unique challenges that recommender systems face when used by a young and diverse population. However, recommender systems for K12 education could provide many benefits for students and teachers, such as the simplification of personalized learning. Some of the issues with K12 educational recommender systems may be solved by the use of deep learning and implicit feedback. As such, we investigated the use of deep recommendation algorithms and implicit feedback for K12 educational recommender systems. To do this, we compared metrics for highly cited traditional and deep recommendation algorithms trained on explicit and implicit data. We found that recommendation algorithms using deep learning as a group do not differ in performance compared to traditional recommendation algorithms. We also found that the use of implicit feedback led to higher performance than using explicit feedback. The best performing algorithm used both deep learning and implicit feedback. We conclude that deep learning can be a benefit for K12 recommender systems, particularly when the ordered sequence of items is carefully accounted for. We also conclude that researchers and developers must carefully consider which feedback contributes the most information for learning.
Efficient Quantization for Overcomplete

In this paper, we study construction of structured reg- ular quantizers for overcomplete expansions in . Our goal is to design structured quantizers which allow simple reconstruction al- gorithms with low complexity and which have good performance in terms of accuracy. Most related work to date in quantized redun- dant expansions has assumed that the same uniform scalar quan- tizer was used on all the expansion coefficients. Several approaches have been proposed to improve the reconstruction accuracy, with some of these methods having significant complexity. Instead, we consider the joint design of the overcomplete expansion and the scalar quantizers (allowing different step sizes) in such a way as to produce an equivalent vector quantizer (EVQ) with periodic struc- ture. The construction of a periodic quantizer is based on lattices in and the concept of geometrically scaled-similar sublattices. The periodicity makes it possible to achieve good accuracy using simple reconstruction algorithms (e.g., linear reconstruction or a small lookup table).
A Learnable Spatial Mapping for Decoding the Directional Focus of Auditory Attention Using EEG

One of the important tasks of auditory attention decoding is to identify the attended speaker’s direction from the listener’s EEG signals. Compared to rule-based methods, deep neural networks (DNNs) have recently shown significantly better identification accuracy, especially with short decision windows. However, existing DNN-based solutions rely on the direct application of the convolution neural networks and the attention mechanism, and the spatial information of the EEG electrodes is not fully exploited. In this paper, we propose a learnable spatial mapping (LSM) mechanism to transform EEG channels into a 2D form, which can be combined with the spatial attention mechanism to better extract the inherent coherence among the electrodes. Apart from validating the benefit of the proposed method in the public KUL dataset, we also test its performance in our newly collected NJU dataset, which is more challenging with more alternatives of directions of competing speakers.
The Adoption of Contact-Tracing Applications and the Integration of a Health Pass: A Prosocial Rationality in the Privacy Calculus?

Contact tracing applications (CTAs) have been presented as important tools in the fight against the Covid-19 pandemic. In France, the government developed the ‘StopCovid' CTA which later became ‘TousAntiCovid. ' This research aims at understanding the determinants of the use of this CTA and of the intention to integrate the health pass. To do that, this study focuses on the perceived value of its use based on the privacy calculus theory. A quantitative study was conducted using a sample of 779 French people. The results show that the use of the CTA and the intention to integrate the health pass are influenced, as hypothesized, by perceived value, distrust towards the government, and personal innovativeness. Perceived value is positively influenced by social and individual benefits, as well as social influence, and, to a lesser extent, negatively influenced by social risks but not by individual risks.
Clustering in globally coupled oscillators

In this paper we describe approaches to clustering in systems of globally coupled identical oscillators. The first of these approaches is based entirely on the symmetry of such systems, and gives information about the behaviour of the systems near degenerate bifurcation points. We summarize existing results from such analysis, and indicate why further techniques are required to augment the symmetry-based methods. This leads to a second approach based on constructing certain reduced models. This modelling approach relies indirectly on symmetry, using the fact that the systems in question have many invariant subspaces as a result of their symmetry. It is shown how knowledge of behaviour on certain subspaces can be used to predict behaviour on others subspaces, even when their dimensions are different. In applications, this approach can be used to predict the stable clustering behaviour that cannot be predicted by other approaches and may be hard to find numerically. All results are illustrated with examples.
LINK: Linguistic Steganalysis Framework with External Knowledge

Linguistic steganalysis is the technology to distinguish whether looking-innocent texts hide covert (possibly hazardous) messages. Traditional methods, dominantly focusing on internal linguistic difference in texts, are seriously challenged by the recent linguistic steganography technology that can reduce the difference to near zero. However, even via the most advanced linguistic steganography methods, due to the random and uncontrollable message bits, steganographic texts may express content against common sense knowledge. To fully employ this defect of linguistic steganography, we propose LINK, a novel Linguistic steganalysis framework with the help of external Knowledge. We link texts to the external knowledge database, and employ Graph Neural Networks (GNNs) to translate linked knowledge into knowledge features, while linguistic features will be captured by the same modules from existing methods. Knowledge features and linguistic features will be combined to make final decisions. Extensive experimental results show that owing to additional external knowledge, the proposed framework can effectively compensate for the shortcomings of existing methods.1
Clinicopathological Features of Invasive Breast Cancer: A Five-Year Retrospective Study in Southern and South-Western Ethiopia

Abstract Background: Breast cancer (BC) is the most common type of cancer in Ethiopia. The incidence of BC is also rising, but the exact figure is still poorly known. Therefore, this study was conducted to address the gap in epidemiological data on BC in southern and southwestern Ethiopia. Materials and Methods: This is a five-year (2015–2019) retrospective study. The demographic and clinicopathological data were collected from biopsy reports of different kinds of breast carcinomas in the pathology department of Jimma University Specialized Hospital and Hawassa University Specialized Referral Hospital. Histopathological grades and stages were conducted using Nottingham grading and TNM staging system, respectively. Collected data were entered and analyzed using SPSS Version-20 software. Results: The mean age of patients at diagnosis was 42.27 (SD = 13.57) years. The pathological stage of most BC patients was stage III, and most of them had tumor sizes greater than 5 cm. Most patients had moderately differentiated tumor grade, and mastectomy was the most common type of surgery at the time of diagnosis. Invasive ductal carcinoma was the most common histological type of BC, followed by invasive lobular carcinoma. Lymph node involvement was seen in 60.5% of cases. Lymph node involvement was associated with tumor size (χ2 = 8.55, p = 0.033) and type of surgery (χ2 = 39.69, p < 0.001). Conclusions: This study showed that BC patients in southern and southwestern Ethiopia displayed advanced pathological stages, relatively young age at diagnosis, and predominant invasive ductal carcinoma histological patterns.
High BMI and Surgical Time Are Significant Predictors of Lymphocele after Robot-Assisted Radical Prostatectomy

Simple Summary Robot-assisted prostatectomy is one of the main therapeutic options for localized prostate cancer. Lymphoceles are one of the major causes of complications after robot-assisted radical prostatectomy and pelvic lymph node dissection. Because the data on risk factors for lymphoceles remains unclear and inconclusive, they were investigated in the present study using the data set of the prospective randomized trial ProLy. In this study, high BMI was found to be an independent predictor for the occurrence of lymphoceles and symptomatic lymphoceles. In addition, a longer surgical time proved to be another risk factor for the postoperative occurrence of lymphoceles. Abstract Lymphoceles (LC) occur in up to 60% after robot-assisted radical prostatectomy (RARP) and pelvic lymphadenectomy (PLND). In 2–10%, they are symptomatic and may cause complications and require treatment. Data on risk factors for the formation of lymphoceles after RARP and PNLD remain sparse in the urologic literature and are inconclusive to date. The underlying data of this secondary analysis were obtained from the prospective multi-center RCT ProLy. We performed a multivariate analysis to focus on the potential risk factors that may influence lymphocele formation. Patients with LC had a statistically significant higher BMI (27.8 vs. 26.3 kg/m2, p < 0.001; BMI ≥ 30 kg/m2: 31 vs. 17%, p = 0.002) and their surgical time was longer (180 vs. 160 min, p = 0.001) In multivariate analysis, the study group (control vs. peritoneal flap, p = 0.003), BMI (metric, p = 0.028), and surgical time (continuous, p = 0.007) were independent predictors. Patients with symptomatic lymphocele presented with higher BMI (29 vs. 26.6 kg/m2, p = 0.007; BMI ≥ 30 kg/m2: 39 vs. 20%, p = 0.023) and experienced higher intraoperative blood loss (200 vs. 150 mL, p = 0.032). In multivariate analysis, BMI ≥ 30 kg/m2 vs. < 30 kg/m2 was an independent predictor for the formation of a symptomatic lymphocele (p = 0.02). High BMI and prolonged surgical time are general risk factors for the development of LC. Patients with a BMI ≥ 30 kg/m2 had a higher risk for symptomatic lymphoceles.
Subspace Modeling Enabled High-Sensitivity X-Ray Chemical Imaging

Resolving morphological chemical phase transformations at the nanoscale is of vital importance to many scientific and industrial applications across various disciplines. The TXM-XANES imaging technique, by combining full-field transmission X-ray microscopy (TXM) and X-ray absorption near edge structure (XANES), has been an emerging tool that operates by acquiring a series of microscopy images with multi-energy X-rays and fitting to obtain the chemical map. Its capability, however, is limited by the poor signal-to-noise ratios due to system errors and low exposure illuminations for fast acquisition. In this work, by exploiting the intrinsic properties and subspace modeling of the TXM-XANES imaging data, we introduce a simple and robust denoising approach to improve the image quality, which enables fast and high-sensitivity chemical characterization. Extensive experiments on both synthetic and real datasets demonstrate the superior performance of the proposed method.
SARS-CoV-2 Transmission Risk in the School Environment: a pilot case-ascertained prospective study to inform future school-based surveillance.

BACKGROUND There is no current active or passive disease surveillance programme focused on schools in South Africa. As such the country is missing an opportunity to rapidly and effectively flag and address pathogen outbreaks, for example SARS-CoV-2, in a key closed setting. Furthermore, the role of school transmission in the spread of the SARS-CoV-2 virus within communities is uncertain. Objective. This pilot study, conducted during March 2022 in Cape Town, aimed to indicate the feasibility of conducting intense active contact-tracing in a school environment prior to a large national study to compare school versus community SARS-CoV-2 transmission risk. Methods. We conducted a pilot school-level case-ascertained prospective study with a component of enhanced surveillance. Following study initiation, the first learner at a participating school who tested SARS-CoV-2 positive (via Polymerase Chain Reaction (PCR) or a Rapid Antigen Test (RAT)) was invited to join the study as the index case and all their school-based close contacts were followed up telephonically, monitored for symptoms for 14 days, and tested using a PCR if any symptoms were reported. Results. On 8th March 2022, a student with RAT laboratory-confirmed COVID-19 was identified and they and their guardian consented to participate as the index case. Of the 11 eligible close contacts, six provided consent/assent and completed symptom monitoring calls until the end of the 14-day study period. The Secondary Attack Rate (SAR) was 2/11 (18.18%) of all close contacts who were at risk of infection, 2/4 (50.0%) of all those close contacts who developed symptoms, and 2/4 (50.0%) of all those close contacts who developed symptoms and were tested for SARS-CoV-2. During the same period, the school reported that nine of the 926 learner body tested COVID-19 positive (0.97%). Total hours spent conducting monitoring for 6 learners was 27 hours, with each learner requiring approximately 4.5 hours of contact time during the study period. Conclusion. This is the first South African school-based COVID-19 transmission study, the results of which can inform national discussions regarding the role of schools and school-based active and passive surveillance in pathogen prevention and control.
Enological Suitability of Indigenous Yeast Strains for ‘Verdejo’ Wine Production

The use of indigenous yeasts for the production of wines is a tool to defend the typicity of a particular region. The selection of appropriate indigenous yeasts ensures the maintenance of oenological characteristics by simulating spontaneous alcoholic fermentation (AF) while avoiding the risks of stuck or sluggish fermentations. In this study, autochthonous yeasts from Verdejo grape juice (Appellation of Origin Rueda) were selected, identified, and characterized to exploit the characteristics of the ‘terroir’. The fermentation capacity of seven strains was studied individually at the laboratory scale. The most suitable strains (Saccharomyces cerevisiae: Sacch 1, Sacch 2, Sacch 4, and Sacch 6) and Sacch 6 co-inoculated with Metschnikowia pulcherrima were characterized at the pilot scale. The fermentation kinetics, bioproduct release, volatile composition, and sensory profile of the wines were evaluated. Significant differences were found, especially in the aroma profile. In particular, Sacch 6 and Sacch 6 co-inoculated with M. pulcherrima produced higher amounts of ethyl esters and acetates and lower amounts of higher alcohols than the spontaneous AF. Wines inoculated with indigenous yeasts had higher sensory scores for fruit aromas and overall rating. The selection of indigenous yeasts improved the aroma of Verdejo wines and could contribute to determining the wine typicity of the wine region.
Intergenerational Trauma in the Aftermath of Genocide

Intergenerational trauma can be understood as the transmission of historical trauma and its adverse effects and impact across generations. This has been witnessed across many nations, populations and marginalized groups, particularly in countries that have experienced long histories of war, systemic violence and/or human rights abuses. The article focuses on Cambodia in the aftermath of the Khmer Rouge and subsequent genocide as the impact of this short but profoundly devastating period in the country’s history continues to permeate many layers of life in Cambodia today. Some examples of trauma-informed research from Rwanda are also presented to highlight cross-cultural understandings of trauma and resilience. Through the research, this article explores the long-standing impacts of intergenerational trauma on the Cambodian population and discusses resilience in the aftermath of human rights violations.
COVID-19 Pandemic Responses among National Guard Service Members: Stressors, Coping Strategies, Sleep Difficultiesand Substance Use

The National Guard (NG) served as a critical component of the US COVID-19 response while concurrently managing personal COVID-19 responses. Understanding pandemic-related concerns, sleep difficulties, increased substance use, and stress management strategies can promote readiness for subsequent disasters. We surveyed 3221 NG service members (75% Army; 79% enlisted; 52% 30–49 years; 81% male) during COVID-19 (August-November 2020). Almost half were activated in response to COVID-19 (mean = 18.6 weeks) and completed the survey 2–3 months post-activation. Service members indicated great concern about family health (39%), the indefinite nature of the pandemic (35%), and their financial situation (23%). Over one-third reported changes in usual sleep amount, 33% described poor sleep quality, and 21% had trouble falling/staying asleep. Increased substance use was reported by 30%, including increased alcohol (13.5%), tobacco (9%), and caffeine/energy drinks (20.1%) consumption. Chi-square analyses and analyses of variance found those who activated reported more increased tobacco and caffeine/energy drink use versus non-activated, with no sleep difficulties nor alcohol use differences. Helpful stress management strategies included spending time outdoors (53%), exercising (48%), talking to family/friends (38%), and having a daily routine (38%). Specific health-, financial-, and job-related stressors were associated with COVID-19. Incorporating stress management in planning/preventive efforts promotes resilience during disasters.
Sound propagation through a rarefied gas in rectangular channels

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Robust H-stability of Hopfield neural networks with impulsive effects and design of impulsive controllers

This paper studies the robust H stability (e.g. in the sense of Hopfield) for Hopfield neural networks (HNN for short) with impulsive effects. By employing the method of Lyapunov functions and Riccati inequality, some sufficient conditions for robust H stability and robustly asymptotical H stability are established. On the basis of these results, the author also designs some impulsive controllers to stabilize HNN. Finally, one illustrative example is given.
Fragile Binaries: Observational Leverage on Difficult Astrophysical Problems

Abstract Loosely bound, fragile binary stars, whose separations may reach ∼ 0.1 pc, are like open clusters with two coeval components. They provide a largely overlooked avenue for the investigation of many astrophysical questions. For example, the orbital distribution of fragile binaries with two long-lived main-sequence components provides a sensitive test of the cumulative effects of the Galactic environment. In pairs where one component is evolved, the orbits have been amplified by post-main-sequence mass loss, potentially providing useful constraints on the initial-to-final mass relation for white dwarfs. The nearly featureless spectra of cool white dwarfs usually provide little information about intrinsic radial velocity, full space motion, population membership, metallicity, etc. However, distant main sequence companions provide benchmarks against which those properties can be determined. In addition, the cooling ages of white dwarf components provide useful limits on the ages of their main sequence companions, independent of other stellar age determination methods. This paper summarizes some of the ways fragile binaries provide useful leverage on these and other problems of interest.
Cảm nhận của sinh viên chính quy khi trải nghiệm học trực tuyến hoàn toàn trong thời gian phòng chống dịch Covid-19

Trong bối cảnh phòng chống đại dịch COVID-19, các cơ sở giáo dục đại học trong và ngoài nước đã triển khai đào tạo trực tuyến toàn thời gian nhằm đáp ứng nhu cầu học tập của sinh viên. Nghiên cứu này được thực hiện nhằm đánh giá cảm nhận của sinh viên hình thức đào tạo chính quy tại một cơ sở giáo dục đại học trên địa bàn Thành phố Hồ Chí Minh khi tham gia học tập trực tuyến trong thời gian ứng phó với dịch bệnh. Phiếu khảo sát được triển khai qua công cụ Google Form gửi đến sinh viên chính quy của trường và thu về 2225 phản hồi. Nghiên cứu sử dụng 04 thành phần của cấu trúc đánh giá hệ thống học trực tuyến trên nền tảng web của Shee và Wang (2008) gồm: Giao diện người dùng (Learner Interface), nội dung (Content), cá nhân hóa (Personalization), cộng đồng học tập (Learning Community). Kết quả nghiên cứu cho thấy sự khác biệt về mức độ hài lòng của sinh viên và xác định có 8 loại khó khăn sinh viên thường gặp nhất khi trải nghiệm học trực tuyến hoàn toàn.
Dynamic Capabilities, Environmental Management Capabilities, Stakeholder Pressure and Eco-Innovation of Chinese Manufacturing Firms: A Moderated Mediation Model

Growing social and academic concerns toward environmental sustainability are constantly driving attention toward eco-innovation as an effective solution to environmental problems. Extant studies on drivers of eco-innovation have not fully investigated the interaction mechanisms between different factors. Drawing upon the resource-based view, stakeholder theory, and environmental literature, this paper aims to explore the mechanisms of how firm capabilities and perceived stakeholder pressure interact to facilitate eco-innovation. Based on survey data collected from 169 Chinese manufacturing firms, the results of regression analysis based on bootstrap resampling method show that environmental management system (EMS) completely mediates the relationship between dynamic capabilities (including absorptive capability and reconfiguring capability) and eco-innovation (including eco-process and eco-product innovation). Furthermore, the relationship between absorptive/reconfiguring capabilities and EMS, as well as the direct and indirect relationship between absorptive capability and eco-process innovation, is contingent upon stakeholder pressure. The direct and indirect effects become stronger when managers perceive higher stakeholder pressure. This paper contributes to answering why firms undertake environmental activities beyond compliance through specifying the interaction between firm capabilities and stakeholder pressure.