Miracle-dz/UniFAR-FTUs huggingface dataset:
Nature of blackbody stars

A selection of 17 stars in the Sloan Digital Sky Survey, previously identified as DC-class white dwarfs (WDs), has been reported to show spectra very close to blackbody radiation in the wavelength range from ultraviolet to infrared. Because of the absence of lines and other details in their spectra, the surface gravity of these objects has previously been poorly constrained, and their effective temperatures have been determined by fits to the continuum spectrum using pure helium atmosphere models. We computed model atmospheres with pure helium and H/He mixtures and used Gaia DR2 parallaxes that are available for 16 of the 17 selected stars to analyze their physical properties. We find that the atmospheres of the selected stars are very probably contaminated with a trace amount of hydrogen of −6 ≤ log(NH/NHe) ≤ −5.4. For the 16 stars with Gaia parallaxes, we calculate a mean stellar mass 0.606 ± 0.076 M⊙, which represents typical mass values and surface gravities (7.8 < logg < 8.3) for WDs.
A Low loss Power Combining Module for UTC-PD in the W Band

This paper proposes a power combining module for uni-travelling-carrier (UTC-PD) in the W-band, which is designed to be low loss. By using two paths for power combining and a single DC input port, the module is able to increase the overall output power. And this module can achieve low insertion loss, ranging from 0.24dB to 0.35dB in W band.
Understanding the Paradoxical Effects of (Environmental) Activists and Their Discourses: When and How are They Penalized for Seeking Change?

ABSTRACT Activists are often negatively stereotyped and appraised, yet they can also influence the change they seek. This suggests that the dimensions and processes involved in their stereotyping and their influence are still unclear, as are the impacts of their argumentative style and the level of social consensus about the cause they defend. We focus on clarifying through an experimental study (n = 226): (1) how the argumentative style – radical or moderate – environmental activists employ and the level of societal consensus about their cause affect how they are viewed in three stereotypical dimensions (warmth, competence, and trustworthiness); (2) how these dimensions are associated with a general appraisal of the activist and with (3) respondents’ pro-environmental behavioral intentions. Results both corroborate and challenge previous findings, suggesting that activists are penalized on warmth, but not competence, that trustworthiness elicited by (radical) activists, and societal consensus play relevant roles. Suggestions for more nuanced communication strategies informed by these findings are discussed.
The effect on cardiovascular risk factors of migration from rural to urban areas in Peru

During the 20 years of political violence in Peru starting in the late 1970’s, Ayacucho, an Andean department, was one of the most severely affected areas. Mass-migration to Lima increased largely driven by escaping from violence rather than by economic reasons. This provides a unique opportunity to study the effects of migration on health since selection biases are likely to be reduced. This study investigates differences in cardiovascular risk factors comparing three groups: i) always lived in Ayacucho (n=289); ii) migrated from Ayacucho to Lima (n=589); and, iii) always lived in Lima (n=199). A cross sectional design was used. A clear gradient of risk was seen for the majority of factors studied: body mass index (BMI), total and LDL-cholesterol, fasting blood glucose and insulin, CRP and fibrinogen, the rural group having the lowest risk, the urban group the highest. The migrant group had intermediate risk, although generally more similar to the urban than the rural group. Blood pressure did not show a clear gradient of difference between groups. The migrant group had similar systolic blood pressure (SBP) but lower diastolic blood pressure (DBP) than the rural group. The urban group had higher SBP but similar DBP than rural group. In the case of lipid profile, no difference was observed between groups for HDL and triglycerides. Obesity, diabetes, metabolic syndrome and estimated absolute cardiovascular risk were all higher in migrant and urban groups than in the rural sample. Within the migrant group, when classified by time since migration or age at migration, differences were observed in total cholesterol, LDL, fasting glucose and insulin resistance. The findings of this study suggest the impact of migration on cardiovascular risk is not uniform across risk factors. The study provides new insights into the increased disease risk associated with migration and urbanisation.
Which hydrological activity in weathered bedrock during flash floods? The case of Mediterranean catchments

"Flash flood" term refers to flood with a high specific discharge resulting from storm events of strong intensity. The steepness of numerous small catchments (of a few km2) contributes to a short response time, and the generation of runoff can suddenly turn into devastating floods. In these cases, the discharge seems to be controlled by fast flow transfers. Overland flows explain most of the peak discharge, but subsurface flows can also represent a significant contribution, particularly during the recession limb. Owing to the short time scales, subsurface flows seem to occur into shallow soil horizons. Therefore, hydrological models often use soil characteristics of the upper horizons from BD-sols databases. Unfortunately, experimental data on subsurface flow are not available at the studied space scale (about 100km2). However, many studies (Garambois, 2012; Vannier et al, 2013; Sayama et al, 2011) show that the storage capacities of upper horizons cannot explain alone the water balance during flash floods. As a matter of fact, effective soil storage capacities on Mediterranean catchments often largely exceed the storage capacities of the upper soil layers described in the BD-sols (Vannier et al., 2013). This study implements two methods to assess the actuality of a hydrological dynamic into weathered rock layers during flash floods. These are applied on two past decades observations of flash flood over Mediterranean catchments with different geological characteristics. The first one consists in assessing water storage capacities on weathered rock from observed events data. The second one consists in using a distributed hydrological model dedicated to flash flood events (Roux et al., 2011) to estimate the flow and storage in the deeper soil horizons. Results show that flows through weathered bedrock layers contribute significantly to the flood hydrograph and more particularly on catchments with granitic bedrock. As an example, on the Ardeche catchment, the observed water storage of some events is up to twice the storage capacity of the upper soil layers. Hydrological simulations also estimate an average contribution of 30 % of the deeper layers to the total flood water volume. As a conclusion, the study emphasizes the impact of the weathered bedrock on the hydrological dynamic and shifts future researches toward a more realistic representation of the subsurface flows.
Frequency Selective Hybrid Beamforming and Optimal Power Loading for Multiuser Millimeter Wave Cognitive Radio Networks

In this work, frequency selective hybrid precoders and combiners are designed for a millimeter wave (mmWave) multiuser (MU) multiple-input-multiple-output (MIMO) downlink underlay cognitive radio network (CRN) utilizing multiple radio frequency (RF) chains and uniform rectangular planar arrays (URPAs) both at the CR base station (CBS) and the secondary users (SUs). The proposed designs maximize the downlink spectral efficiency (SE) of the secondary users, while keeping the interference introduced to the primary user within a prescribed threshold. In the first phase, considering only the channel knowledge at each subcarrier, a novel blind hybrid MMSE-RC (minimum mean squared error-receiver combiner) design is determined using the modified simultaneous orthogonal matching pursuit (MSOMP). Further, employing feedback for each SU’s effective channel, a two-stage decoupled strategy is developed for hybrid transmit precoder (TPC) design, wherein the RF and stage-1 BB-TPC are designed in the first step relying on a capacity-optimal fully digital (FD)-TPC approximation problem followed by the stage-2 BB-TPC design using a low-complexity ZF approach with the goal of mitigating the MUI. Towards this, a novel Modified Alternating Minimization-Zeroforcing (MAM-ZF) algorithm is proposed to compute the hybrid-TPC weights. Furthermore, a low complexity alternating minimization-zeroforcing (LAM-ZF)-based precoding algorithm is also proposed towards the same. Finally, a per-subcarrier optimal power loading solution is derived in closed-form with the objective of maximizing the sum SE while satisfying the interference and transmit power budget limitations. Our simulation findings show that the proposed schemes outperform other state-of-the-art techniques and achieve a spectral efficiency comparable to that achieved by fully-digital beamforming, while requiring a significantly fewer number of RF chains.
Customer Personality Segmentation Using K-Means Clustering

Enhancing sales strategies and developing targeted marketing approaches that effectively resonate with customers are crucial for achieving success in today's highly competitive marketplace. To accomplish this, sales organizations can invest in their teams and equip them with analytical tools to examine customer personality and behavior. By employing unsupervised learning algorithms such as K-Means clustering, customer data can be efficiently analyzed, facilitating the grouping of customers into clusters based on shared characteristics. This enables the identification of patterns in customer behavior, allowing companies to create tailored marketing strategies. This study provides practical recommendations for companies to enhance their sales and marketing strategies based on the analysis of a benchmark dataset from Kaggle, revealing three primary customer clusters: new customers with lower income and spending, old customers with average income and behavior, and old customers with higher income and spending. These insights empower companies to align their efforts with customer preferences and improve.
Impact of Pharmacist-Led PDCA Cycle in Reducing Prescription Abandonment: An Action Research from China

Purpose Taking medicine as prescribed in time plays an important role in the treatment of diseases. However, some prescriptions have not picked up in time for various reasons. To analyze the influencing factors in patients with prescription abandonment and the role of pharmacists in Plan–Do–-Check–Act (PDCA) cycle, we conducted a study in our hospital of Hangzhou, China. Methods Based on the prescription abandonment from October 1, 2021 to March 31 2022, we collected and analyzed the possible causes. According to the PDCA management method, we conducted improvement measures and supervised the implementation of measures from April 1, 2022 to September 30, 2022. The number, the proportion and the amount of prescription abandonment before and after establishment of the PDCA cycle were analyzed. Results Three measures were proposed and applied to improve the prescription abandonment:(I) Enhancing the education and training to the staff. (II) Improving the medical environment for patients, especially the environment for taking medicine. (III) Updating the computer information software. After the implementation of PDCA, the number of prescription abandonment decreased from 2030 to 775, there was significant reduction in the proportion of prescription abandonment (4.75‰ vs 1.77‰, P<0.05), and the amount of prescription abandonment decreased from $36,161.11 to $17,041.59. The target compliance rate was 108.36%. Conclusion The implementation of pharmacist-led PDCA can effectively reduce the number, the proportion and the amount of prescription abandonment, Moreover, Pharmacists play an important role in improving the management quality of outpatient pharmacy, and PDCA is a feasible and effective management tool for reducing prescription abandonment.
Breaking the Throughput Limit of LED-Camera Communication via Superposed Polarization

With the popularity of LED infrastructure and the camera on smartphone, LED-Camera visible light communication (VLC) has become a realistic and promising technology. However, the existing LED-Camera VLC has limited throughput due to the sampling manner of camera. In this paper, by introducing a polarization dimension, we propose a hybrid modulation scheme with LED and polarization signals to boost throughput. Nevertheless, directly mixing LED and polarized signals may suffer from channel conflict. We exploit well-designed packet structure and Symmetric Return-to-Zero Inverted (SRZI) coding to overcome the conflict. In addition, in the demodulation of hybrid signal, we alleviate the noise caused by polarization on the LED signals by polarization background subtraction. We further propose a pixel-free approach to correct the perspective distortion caused by the shift of view angle by adding polarizers around the liquid crystal array. We build a prototype of this hybrid modulation scheme using off-the-shelf optical components. Extensive experimental results demonstrate that the hybrid modulation scheme can achieve reliable communication, achieving 13.4 kbps throughput, which is 400 % of the existing state-of-the-art LED-Camera VLC.
NeoStarling: An Efficient and Scalable Collaborative Blockchain-Enabled Obstacle Mapping Solution for Vehicular Environments

The Vehicular Self-Organizing Network (VANET) is a burgeoning research topic within Intelligent Transportation Systems, holding promise in enhancing safety and convenience for drivers. In general, VANETs require large amounts of data to be shared among vehicles within the network. But then two challenges arise. First, data security, privacy, and reliability need to be ensured. Second, data management and security solutions must be very scalable, because current and future transportation systems are very dense. However, existing Vehicle-to-Vehicle solutions fall short of guaranteeing the veracity of crucial traffic and vehicle safety data and identifying and excluding malicious vehicles. The introduction of blockchain technology in VANETs seeks to address these issues. But blockchain-enabled solutions, such as the Starling system, are too computationally heavy to be scalable enough. Our proposed NeoStarling system focuses on proving a scalable and efficient secure and reliable obstacle mapping using blockchain. An opportunistic mutual authentication protocol, based on hash functions, is only triggered when vehicles travel a certain distance. Lightweight cryptography and an optimized message exchange enable an improved scalability. The evaluation results show that our collaborative approach reduces the frequency of authentications and increases system efficiency by 35%. In addition, scalability is improved by 50% compared to previous mechanisms.
A 1.2V Low-Power Multi-Band Mixing Frequency Synthesizer for FDD System

This article presents a novel low-power multi-band mixing frequency synthesizer for FDD System. The synthesizer can provide local oscillation signals for both TX and RX simultaneously with only one phase-locked loop (PLL). By selecting the spacing frequency between the uplink and downlink as its reference, plus a notch filter removing strong spur component, this PLL achieves lower power consumption and smaller die area. The mixing frequency synthesizer is fabricated in 65 nm CMOS process with an area of 0.571 mm2, The test results show that the proposed synthesizer achieves a 3.3-3.66 GHz frequency tuning range with the out-of-band PN of -114.9 dBc/Hz at 1 MHz offset from a 3.42 GHz carrier. And the reference spur is measured to be -50.16 dBc at 180 MHz offset. The entire mixing frequency synthesizer consumes 7.2 mW at the 1.2 V supply voltage with 4.15 mW associated with VCO.
A Proposed Quality Model For Social Media Websites

This research paper proposes a new quality model for social media websites based on an extensive literature review and analysis of previous studies. The study identifies seven key quality factors that are essential for evaluating social networking websites: user friendliness, community-drivenness, website appearance, entertainment, security and privacy, efficiency, and navigability. These factors were selected based on their prominence in previous research and their relevance to user satisfaction in the context of social media platforms. The paper explores each quality factor, providing definitions and highlighting their significance in shaping users' perceptions of website quality and satisfaction. The research aims to contribute to a deeper understanding of the factors that influence user experiences and satisfaction with social media websites, providing valuable insight to website designers and developers to enhance user engagement and overall website quality.
CLP: A Community based Label Propagation Framework for Multiple Source Detection

Given an aftermath of an information spreading, i.e., an infected network GN after the propagation of malicious rumors, malware or viruses, how can we identify the sources of the cascade? Answering this problem, which is known as the multiple source detection (MSD) problem, is critical whether for forensic use or insights to prevent future epidemics.Despite the recent considerable effort, most of them are built on a preset propagation model, which limits their application range. Some attempts aim to break this limitation via a label propagation scheme where the nodes surrounded by a large proportion of infected nodes are highlighted. Nonetheless, the detection accuracy may suffer since the node labels are simply integers with all infected or uninfected nodes sharing the same initialization setting respectively, which fall short of sufficiently distinguishing their structural properties. To this end, we propose a community based label propagation (CLP) framework that locates multiple sources through exploiting the community structures formed by infected subgraphs of different sources. Besides, CLP tries to enhance the detection accuracy by incorporating node prominence and exoneration effects, namely the nodes surrounded by larger proportions of infected nodes are more likely to be sources, and the uninfected nodes or infected ones in neighboring community hold the key in exonerating an infected node from being the source. As such, CLP is applicable in more propagation models, and is provably convergent. Experiments on both synthetic and real-world networks further validate the superiority of CLP to the state-of-the-art, boosting the F-score from few percents to approximately 68× in large-scale networks.
Computed tomography angiography-based radiomics model to identify high-risk carotid plaques

Background Extracranial atherosclerosis is one of the major causes of stroke. Carotid computed tomography angiography (CTA) is a widely used imaging modality that allows detailed assessments of plaque characteristics. This study aimed to develop and test radiomics models of carotid plaques and perivascular adipose tissue (PVAT) to distinguish symptomatic from asymptomatic plaques and compare the diagnostic value between radiomics models and traditional CTA model. Methods A total of 144 patients with carotid plaques were divided into symptomatic and asymptomatic groups. The traditional CTA model was built by the traditional radiological features of carotid plaques measured on CTA images which were screened by univariate analysis and multivariable logistic regression. We extracted and screened radiomics features from carotid plaques and PVAT. Then, a support vector machine was used for building plaque and PVAT radiomics models, as well as a combined model using traditional CTA features and radiomics features. The diagnostic value between radiomics models and traditional CTA model was compared in identifying symptomatic carotid plaques by Delong method. Results The area under curve (AUC) values of traditional CTA model were 0.624 and 0.624 for the training and validation groups, respectively. The plaque radiomics model and PVAT radiomics model achieved AUC values of 0.766, 0.740 and 0.759, 0.618 in the two groups, respectively. Meanwhile, the combined model of plaque and PVAT radiomics features and traditional CTA features had AUC values of 0.883 and 0.840 for the training and validation groups, respectively, and the receiver operating characteristic curves of combined model were significantly better than those of traditional CTA model in the training group (P<0.001) and validation group (P=0.029). Conclusions The combined model of the radiomics features of carotid plaques and PVAT and the traditional CTA features significantly contributes to identifying high-risk carotid plaques compared with traditional CTA model.
Ethics of Using Technology in Strengthening Students Religious Character

In the current era of globalization, technology is increasing and offers many unstoppable conveniences. This is the biggest challenge for humans, so all parties must be jointly responsible for controlling the use of technology to be in harmony with human values. This study examines the ethics of using technology to strengthen students' religious character. This study uses a qualitative research design with a phenomenological approach, namely research that focuses on individual experiences of a phenomenon by collecting data through interviews, observation, and documentation. Ten people became research subjects, including five lecturers and five students. The resulting data were analyzed through data reduction, presentation, verification, and conclusion. The use of technology brings positive impacts and ethical challenges. Studies show that religious beliefs influence students' religious character, and character strengthening can be done through religious education and the wise use of technology. Integrating ethics and strengthening religious character will create a society that is responsible, cultured and has a solid ethical awareness in the digital era. The findings from this study can provide students with an in-depth understanding of the importance of the ethical use of technology.
Political Institutions, ICT Infrastructure, and Social Networks Impact on Citizens’ Policy Formulation E-participation Engagement Behaviour in Uganda

This paper assessed the impact of political institutions, ICT infrastructure, and social networks on citizens’ self-motivation and engagement in policy formulation. The study was motivated by limited citizen engagement in policy formulation in Uganda which has made Uganda as a country to score poorly both in the e-government and e-participation index and contradict Article 38 of the Constitution of Uganda which advocates for citizen engagement in policy formulation. Thus, this study aimed to increase citizen engagement through the adaption of the Motivation, Opportunity, and Ability (MOA) model. A survey collected Primary data from 361 village health teams and local council Chairpersons. The collected data was analysed using SPSS and SEM. Results found that; political institutions, ICT infrastructure, and social networks influence self-motivation, political institutions, and self-motivation influence engagement while self-motivation fully mediates the relationship between ICT infrastructure, social networks, and citizen engagement, it partially mediates the relationship between political institutions and engagement. The practical implication is that political institutions are essential in stimulating citizens’ self-motivation and engagement.