Miracle-dz/UniFAR-FTUs huggingface dataset:
A Bayesian Methodology for Estimation for Sparse Canonical Correlation

It can be challenging to perform an integrative statistical analysis of multi-view high-dimensional data acquired from different experiments on each subject who participated in a joint study. Canonical Correlation Analysis (CCA) is a statistical procedure for identifying relationships between such data sets. In that context, Structured Sparse CCA (ScSCCA) is a rapidly emerging methodological area that aims for robust modeling of the interrelations between the different data modalities by assuming the corresponding CCA directional vectors to be sparse. Although it is a rapidly growing area of statistical methodology development, there is a need for developing related methodologies in the Bayesian paradigm. In this manuscript, we propose a novel ScSCCA approach where we employ a Bayesian infinite factor model and aim to achieve robust estimation by encouraging sparsity in two different levels of the modeling framework. Firstly, we utilize a multiplicative Half-Cauchy process prior to encourage sparsity at the level of the latent variable loading matrices. Additionally, we promote further sparsity in the covariance matrix by using graphical horseshoe prior or diagonal structure. We conduct multiple simulations to compare the performance of the proposed method with that of other frequently used CCA procedures, and we apply the developed procedures to analyze multi-omics data arising from a breast cancer study.
Teaching strategies for cultivating preschoolers’ sharing behavior based on gender roles in Chinese culture

Chinese boys and girls manifest distinct sharing behavior compared with children of other nationalities following different cross-national pathways. Undoubtedly, the Chinese traditional culture projects distinct expectations of female and male roles. Kindergarten teachers are responsible for delivering cultural norm knowledge to children and shaping their behaviors and beliefs. This study aims to provide an insight into how kindergarten teachers cultivate preschoolers’ sharing behavior considering the traditional gender-role culture in China. This study adopted the multiple case study approach and involved six participants working in a Chinese public provincial kindergarten in Hebei Province. The data collection techniques used comprise semi-structured interviews and document analysis. This study’s findings showed teachers develop both boys’ and girls’ sharing awareness through an other-oriented strategy. They also elicit sharing practices through benefits-oriented and habits-forming strategies. However, different treatments of boys and girls could be observed in some respects. These findings demonstrate that children’s sharing behaviors are shaped through the same strategy with a subtle gender bias. They further imply that the gender-role knowledge of Chinese kindergarten teachers impacts how they cultivate preschoolers’ sharing behavior.
Detecting Community Evolution by Utilizing Individual Temporal Semantics in Social Networks

Social networks are becoming increasingly popular and significant. One of the most distinctive features of these networks is their dynamic nature, which means that they change over time. Consequently, the community structure on these platforms also changes with time, making the detection of community structure a crucial area of research. Specifically, there is still a lack of understanding of how social networks and communities evolve over time. In this paper, we reveal that individual changing topics (i.e., individual temporal semantics) are a vital factor that drives community evolution. A novel dynamic community detection model is proposed, which takes into account natural evolutionary features. The model first partitions social networks into snapshots. It then detects the community structure at each snapshot by utilizing individual changing topics and information from the previous snapshot. Finally, the evolution of users’ interested topic distributions and topic distributions of communities are identified. The model is compared with five state-of-the-art baselines on two real datasets, and the experimental results demonstrate that our model outperforms all baselines.
Regional Tourism Development in Pringsewu Regency: Perspective on Community-Based Tourism and Sustainable Livelihood

Institutionally, the Tourism Awareness Group (Pokdarwis) has encouraged community participation in each village (pekon) to optimize the potential of natural, cultural, and human resources as tourist attractions. This study aims to describe in-depth the dynamics of the collaboration of the Tourism Awareness Group in Pringsewu Regency to increase public awareness in each village about the benefits of the tourism sector for the sustainability of household livelihoods, preservation of social-cultural values, and environmental sustainability. This study uses a community-based tourism perspective. Meanwhile, the qualitative research method with a case study approach is used for three tourist objects developed by Pokdarwis, namely Akasia valley, Talang Indah, and Teluk Kenyo. Retrieval of research data is conducted using in-depth interviews, observation, and document study while, data processing uses triangulation techniques to obtain valid and credible information. This study indicates that Pokdarwis in each village (pekon) are organized because the Pokdarwis Communication Forum is the central organization that connects 37 Tourism Awareness Groups throughout the Pringsewu Regency, Lampung Province. Proactively, Forkom Pokdarwis establishes communication with the government, local entrepreneurs, academics, and rural communities to optimize natural, cultural, and human resources by pioneering tourist destinations. Several tourist destinations have successfully pioneered and developed through reasonable assistance and coordination, opening up local communities' job opportunities.
A Chip-Integrated 240-GHz-Reflectarray with Antennas on Glass Superstrate

In this article, a chip-based reflectarray for operation at 240 GHz is presented, where the unit cell is designed in compatibility with standard chip technology to allow integration of a switchable element in a subsequent design iteration. Different reflection phase states are obtained by connecting a transmission line of variable length to an on-chip patch, which in turn is coupled to a radiating patch antenna on a glass superstrate. To verify the design, a large array synthesized from three discrete phase states is investigated in full-wave simulations for different beam steering scenarios. As a proof-of-concept, a back-end-of-line chip with a fixed phase progression is fabricated and assembled. Experimental characterization of its far-field radiation pattern successfully demonstrates beam steering by 41°.
Mass-extinction: Evolution and the effects of external influences on unfit species

We present a new model for extinction in which species evolve in bursts or `avalanches', during which they become on average more susceptible to environmental stresses such as harsh climates and so are more easily rendered extinct. Results of simulations and analytic calculations using our model show a power-law distribution of extinction sizes which is in reasonable agreement with fossil data. e also see a number of features qualitatively similar to those seen in the fossil record. For example, we see frequent smaller extinctions in the wake of a large mass extinction, which arise because there is reduced competition for resources in the aftermath of a large extinction event, so that species which would not normally be able to compete can get a foothold, but only until the next cold winter or bad attack of the flu comes along to wipe them out.
A Review of Blockchain Approaches for KYC

The traditional Know Your Customer (KYC) procedure used by banks is deemed unreliable and costly. Therefore, the adoption of emerging technologies is essential for banking firms’ future prospects. One such technology that has gained widespread acceptance is Blockchain, which is known for its reliability and security across various fields. This study aims to investigate how the implementation of Blockchain technology can modify the existing banking business, particularly the KYC document verification process, by storing and monitoring of information. The current need for an optimized KYC system is paramount; one that is coupled with a secure and trustworthy technology like Blockchain that can withstand fraudulent activities while also overcoming scalability and privacy challenges. The article analyzes previous relevant works, which highlight how the implementation of Blockchain technology eliminates the need for intermediaries, thereby reducing the possibility of malicious activities and errors that may occur when there are multiple manual tasks involved.
Factores de riesgo de violencia escolar (bullying) severa en colegios privados de tres zonas de la sierra del Perú Severe bullying risk factors in three Peruvian highland private schools

Objective: To identify severe bullying risk factors in three highland Peruvian zones private school students. Design: Survey type study. Setting: Faculty of Medicine, Universidad Nacional Mayor de San Marcos, Lima, Peru. Participants: Fifth elementary school to fifth high school private school students. Interventions: A survey validated in previous studies to identify school violence (bullying) was applied to 736 students from Ayacucho, Huancavelica and Cusco (Sicuani) private schools between fifth year of elementary school and fifth year of high school. We considered severe bullying when they answered positively five or more of the nine questions referring to types of bullying. We compared 37 students with severe bullying and 74 students randomly selected from the group not having bullying. With bivariate analyses and multivariate logistic regression analysis we identified factors significantly associated to severe bullying. Main outcome measures: Risk factors for severe bullying. Results: Severe bullying was significantly associated to parents’ reaction when knowing the fact, repeated threatening in spite of bullying communication, presence of school gangs, having gang friends, and possessing a physical defect. Logistic regression found significant association with parents’ reaction, gang presence, and possessing a physical defect. Conclusions: Severe bullying is associated to multiple risk factors that can and must be detected early because of the psychological damage generating in the students.
On definable $f$-generic groups and minimal flows in $p$-adically closed fields

Let $X$ be a definable group definable over a small model $M_0$. Recall that a global type $p$ on $X$ is definable $f$-generic over $M_0$ if every left translate of $p$ is definable over $M_0$. We call $p$ strongly $f$-generic over $M_0$ if every left translate of $p$ does not fork over $M_0$. Let $H$ be a group definable over the field ${\mathbb Q}_p$ of $p$-adic numbers admitting global definable $f$-generic types over ${\mathbb Q}_p$. We show that $H$ has unboundedly many global weakly generic types iff there is a global type $r$ on $H$ which is strongly $f$-generic over ${\mathbb Q}_p$ and a ${\mathbb Q}_p$-definable function $\theta$ such that $\theta(r)$ is finitely satisfiable in ${\mathbb Q}_p$. Recall that the $\mu$-type $\mu(x)$ on $H$ is the partial type consisting of the formulas over ${\mathbb Q}_p$ which define open neighborhoods of the identity of $H$. We show that every global weakly generic type $r$ on $H$ is $\mu$-invariant: For any $\epsilon\models \mu$ and $a\models r$, we have $\epsilon\cdot a\models r$. Let $G$ be groups definable over ${\mathbb Q}_p$ such that $H$ is a normal subgroup of $G$ and $G/H$ is a definably compact group. Then we show that the weakly generic types on $G$ coincide with almost periodic types $G$ iff $G$ has boundedly many global weakly generic types.
Production and circulation of thin walled pottery from the Roman port of Neapolis, Campania (Italy)

Seventeen samples of thin walled pottery from the Roman port of Neapolis (late II century B.C. - early III century A.D.) were studied in order to ascertain the type of clay and temper utilised, and their provenance. Seven samples of thin walled pottery from a homogeneous group (based on mineralogical and chemical characteristics) represent a local production of this ceramic class within the Neapolis area. This group was manufactured with a low-CaO clay, that probably derived from a weathered or alluvial deposit, together with reworked pyroclastic material (e.g., Sorrento area or Sebeto River plain) and volcanic sand from the Neapolitan area, containing both Somma-Vesuvius and Phlegraean Fields products. Two other fragments could be attributed to different Campanian production areas, such as the Pozzuoli area. Eight outlier fragments found in the port of Neapolis probably originate from extra regional production sites (e.g. southern Tuscany or the Arno valley).
Automatic Reading Method for Pointer Meters Based on Improved Deeplabv3+

In response to the problems of imprecise and poor segmentation of pointer meters by the original Deeplabv3+ algorithm in complex environments, this paper proposes an automatic meters reading method based on the improved Deeplabv3+. Firstly, the semantic segmentation algorithm Deeplabv3+ is structurally improved, including replacing the backbone network with Res-Net50, using DenseASPP instead of ASPP and adding a new coordinate feature refinement module to improve the feature extraction and the perception of edge information, so as to extract the dials and pointers of meters more accurately. The experimental results show that the improved Deeplabv3+ prompts MPA by 2.46% and MIOU by 3.59% compared with the original model. These results are better than other segmentation algorithms. Subsequently, the post-segmented image is expanded into a rectangular map by polar coordinate transformation, and the readings are completed using the distance method. It is verified that the average relative error between the adopted automatic reading algorithm and manual reading is 0.25%, meeting the accuracy requirement. The proposed automatic reading method proves its strongly potential in intelligent meter identification.
Proposed Electrical Stimulation Device for Wound Healing Therapy

The management of chronic wounds has emerged as a crucial and significant concern for patients afflicted with chronic diseases like diabetic foot disease. This condition has escalated into a life-threatening issue for numerous individuals worldwide. Electrical stimulation devices have played a pivotal role in addressing various cases and have had a direct impact on the advancement of therapeutic techniques and healthcare in the domain of wound treatment and healing. Design an Electrical Stimulation ES device facing many challenges suck as the compellability of the device, how to design ES device able to provide many therapeutic techniques with high efficiency and low cost. This paper presents a proposed electrical stimulation device, which has been designed utilizing the Arduino platform's Integrated Development Environment IDE and fritzing. The proposed model in this research paper offers characteristics such as current, voltage, and variable frequencies. It applies to numerous medical conditions and diverse types of wounds, be they acute or chronic. The Electrical Stimulation ES device in this study delivers a direct or monophasic current signal with varying strengths and adjustable periods, which contribute to the healing process. To assess the efficacy of the electrical stimulation device, both the Direct Current Mode DCM and the Monophasic Current Mode MPCM were tested on whole blood WB samples using an in vitro method. The vitro results show that the Direct current mode provide the best effect on the blood sample during the testing of the proposed Electrical stimulation device on patients that suffer or not suffer from diabetic foot disease.
Exploring the Impact of the COVID-19 Pandemic on Academic Burnout Among Nursing College Students in China: A Web-Based Survey

Background The COVID-19 pandemic has brought changes and challenges to nursing students. However, little is known about the prevalence of academic burnout among nursing students in this challenging circumstance. This study aimed to assess nursing student academic burnout and its influencing factors. Material/Methods We conducted a sample survey of a 4-year undergraduate nursing university in Wuhu, Anhui Province, China. The social-demographic information questionnaire, Academic Burnout Scale, Connor-Davidson Resilience Scale, Impact of Event Scale-6, Patient Health Questionnaire-2, and Professional Identity Scale were used. Stepwise multiple linear regression was used to clarify the relationship among sociodemographic characteristics, resilience, and academic burnout. Results Of all the study participants, 51.30% had a certain degree of academic burnout. Academic year, satisfaction with specialty, satisfaction with online learning, professional identity, and psychological resilience were negatively correlated with academic burnout among nursing students. Depression was positively correlated with academic burnout. Conclusions Nursing students had a high degree of academic burnout. Academic year, satisfaction with specialty, satisfaction with online learning, professional identity, and psychological resilience were protective factors that reduced nursing students’ academic burnout.
Students’ Housing and Academic Performance in University of Ibadan, Nigeria

Constrained by inadequate bed ~paces for her teeming students population, the management of the University of Ibadan evolved a policy ensuring that, on the average, each undergraduate student is accommodated on-campus yin the first and final veal’s while intervening years are spent off-campus. The study investigated the effects of this students’ housing programme 011 academic performance. Faculty of the Social Sciences was randomly selected, front where all final year undergraduate students were purposively sampled for the study; using a set of pre-tested questionnaires and in-depth interviews. Only 195 of the 230 copies of the questionnaire administered were returned and analyzed for the study. Secondary data were also obtained front both published and unpublished sources. Both descriptive and inferential statistics were used to analyze the data collected Significant differences were not found in academic performances of on-campus and Off-campus students. While analysis of quantitative data revealed no significant relationships between indicators of students’ housing quality and academic performance, qualitative data from in-depth interviews identified diverse challenges posed by these indicators to students’ academic performance in the university. Strategies were proposed to address the identified
Current Regulation in Case of Open Circuit Fault for Six-phase Traction Open-end Winding Machine

The electric aircraft propulsion system should comply high safety standards and implement fault tolerant operation in case of partial failures. The fault tolerant operation is enabled due to both hardware and control. The paper considers the six-phase permanent magnet propulsion motor with open-end winding configuration. The open circuit fault in a single phase is the most common fault when it is possible to continue producing the same torque by changing the current references in other phases. The paper proposes the method of forming the referenced current vector with the help of the phases left in operation. It is shown that the increase in the current magnitude by 23.6% is required, whereas the simple increase of the currents by 20% produces the same average torque over the revolution with 20% torque pulsation. As the torque pulsations may cause the mechanical resonance and failure of the propeller, the proposed method is advisable even having a little bit higher ohmic losses.
Journal self-citation on the h5-index of Ibero-American journals

Abstract: It aims to analyze journal self-citation in Ibero-American journals from the h5-index of the Google Scholar Metrics. The bibliometric tool Gsm_hdata was used to identify 4049 Ibero-American journals indexed simultaneously in Latindex and Google Scholar Metrics. Self-citations were identified, self-citation rates by country and research area were calculated, and the h5-index was recalculated without self-citations (hs5-index). No self-citations were identified in almost 40% of the journals, especially those with an h5-index lower than 5. The overall average self-citation rate was 3.6%. Among the 1859 most cited journals with at least one self-citation, the rate was 4.8%, lower than that of research based on the Impact Factor. Journals of Engineering, Exact and Natural Sciences, and Agricultural Sciences had the highest self-citation rates, while Social Sciences and Humanities journals presented the lowest. Journals with excessive rates (outliers) were identified in all areas. These results suggest that the prior exclusion of journal self-citations in the calculation of the h5-index is not necessary. However, monitoring journals with excessive self-citation rates is recommended to avoid distortions in impact assessment procedures based on h5-index of Google Scholar Metrics.
Deep State Space Visual Prediction for Robotic Manipulation

We propose a deep state space visual prediction framework for robotic manipulation. A circumstance is concerned when part of the robotic arm is clipped out of the image captured by the camera hung above. A two-stage Deep Neural Networks (DNNs) architecture is suggested to perform state extracting and image restoring, and a Sparse Bayesian Learning (SBL) approach is applied to identify the State Space equation representing the dynamics between the state generated by the former Networks and the position of the robotic arm’s end-effector. The proposed framework is able to predict the future robotic arm’s location in a image-based fashion by incorporating the current robotics image and future trajectory of the end-effector’s position in a large prediction time period when most part of the robotic arm is unseen by the camera. The experiments operated on UR5 (6-DOF robotic arm) show a satisfying prediction results measured by IoU (Intersection over Union) of 0.947 in a robotic arm manipulation which predicts from the start position to the end position.
Complex Permittivity Extraction of IC-Package Materials beyond 110 GHz by Band-Limited Waveguide-Cavity Measurements

In this work, an accurate method for extracting the frequency-dependent complex permittivity in frequency bands above 110 GHz using a resonant waveguide (WG) cavity is presented. Although the measurement information is band-limited and the first TE-mode cannot be measured, the method can dispense with this information in a two-stage measurement procedure. The information from a prior non-resonant, but still band-limited, measurement is used to assign resonance peaks occurring in the resonant measurement to the corresponding resonance modes. This enables the correct mapping of the respective TE-modes from the air-filled to MUT-filled WG cavity across different frequency bands, and subsequently extracting the complex permittivity from their comparison. To ensure distortion-free determination of the complex permittivity at multiple frequency points throughout the frequency band, the influence of WG cavity coupling on the determination of the resonant frequency and quality factor (Q) is compensated.