Miracle-dz/UniFAR-FTUs huggingface dataset:
Co-development of internalizing symptoms and regulatory emotional self-efficacy in adolescence: Time-varying effects of COVID-19-related stress and social support

The COVID-19 pandemic disrupted opportunities for adolescents to progress through a typical developmental trajectory of adjustment and self-regulation. Adolescents across many contexts have shown an increase in adjustment difficulties during the pandemic compared to pre-pandemic levels. Utilizing data collected from 830 Italian adolescents from one time-point just prior to when pandemic restrictions were enacted, and then at two additional time-points 12 and 24 months later, we examined trajectories of internalizing symptoms, regulatory self-efficacy for managing negative emotions, and the time-varying impact of COVID-related stress and social support. Latent Growth Curve Analyses (LGCAs) revealed that COVID stress predicted increased internalizing symptoms and decreased regulatory self-efficacy beyond what was estimated by the developmental trajectory. Further, at Time 3, the impact of perceived COVID stress on internalizing symptoms and regulatory self-efficacy was stronger than at Time 2. Co-development results were similar for males and females. There was no time-varying impact of social support on the co-development of internalizing symptoms and regulatory self-efficacy. The findings are important for informing interventions to strengthen coping strategies for adolescents during stressful community-wide events.
La persistencia del “edadismo” en el trato hacia las personas mayores. Un análisis de los medios digitales en Chile (2014-2022)

El presente trabajo corresponde a un análisis sobre el uso de los encuadres del edadismo y el envejecimiento positivo utilizado por parte de los medios digitales en Chile. El periodo temporal asignado corresponde al gobierno de Michelle Bachelet Jeria en su segundo periodo (2014-2018) y Sebastián Piñera Echeñique también en su segundo periodo presidencial (2018-2022), estableciendo las posibilidades del cambio de la estigmatización hacia este importante grupo etario de la población nacional. Para ello se trabaja con el software de minería de datos Orange Data Mining considerando la base de datos de prensa MyNews, y en el cual se entrena la búsqueda por códigos boleanos y se realiza un posterior entrenamiento para trabajar de manera automatizada por medio del algoritmo SVM o Máquina de Soporte Vectorial. Como principales resultados del presente trabajo, se puede exponer que la temática ligada a las personas mayores es bastante alta en los medios digitales del país, principalmente para el periodo de la pandemia del Sars-Cov-2, estableciendo en tanto una estigmatización del grupo etario con vocablos ligados al edadismo por sobre la lógica del envejecimiento positivo.
Performance and characteristics of the BILBY time-of-flight small-angle neutron scattering instrument

BILBY is a recently constructed and commissioned time-of-flight small-angle neutron scattering instrument, operated by the Australian Centre for Neutron Scattering at the Australian Nuclear Science and Technology Organisation (ANSTO). BILBY provides a wide accessible q range (q ≃ 1.0 × 10−3 Å−1 to ∼1.8 Å−1) and variable wavelength resolution (Δλ/λ ≃ 3–30%) to complement the other small-angle and ultra-small-angle neutron scattering capabilities available at ANSTO. Since its construction, BILBY has been used to study samples from a wide range of scientific disciplines, including biology, chemistry, physics and materials science. This article describes the BILBY design and components, and shows data collected from a number of reference samples.
Beamforming for Reduced-Rank MIMO Interference Channels in Dynamic TDD Systems

Dynamic Time Division Duplexing (DynTDD) enables flexible time slot allocation based on changing communication needs, which distinguishes it from traditional Time Division Duplexing (TDD) systems that rely on fixed time slot allocation. However, despite the benefits offered by DynTDD, cross-link interference (CLI) can still occur when neighboring cells use different transmission directions on the same or partially-overlapping time-frequency resources. Two types of cross-link interference exist: Base Station (BS) to BS or Downlink (DL) to Uplink (UL) interference, and User Equipment (UE) to UE or UL to DL interference. To address this interference, coordinated beamforming is a crucial signal-processing technique. This study focuses on designing zero-forcing (ZF) transmit beamforming at initialization, and the iterative weighted minimum mean-square error (WMMSE) algorithm to maximize the sum rate in a Multiple Input Multiple Output (MIMO) User Equipment to User Equipment (UE-to-UE) Interference Channel (IC). The study also examines the potential advantages of non-uniform Degrees-of-Freedom (DoF) at Uplink (UL) and/or Downlink (DL) User Equipment (UEs), which can enhance the sum DoF, leading to higher sum rates at high Signal-to-Noise Ratio (SNR).
Performance Evaluation of Square Emboss Absorber Solar Water Heaters

An effective solution for increasing global demand for energy is the utilization of renewable energy sources. Solar energy is taken as an alternative source of energy for numerous domestic and industrial applications. Solar energy is considered as one of the best alternative sources of energy since it is clean and sustainable for the environment. Extensive research on various aspects of solar water heating systems has been done in order to increase the overall efficiency of the system and optimize the design. The aim of present work is to analyze thermal performance of serpentine tube solar water heater with square embossed on the absorber plater using K type thermocouples.
Studies on Genetic Variability and Character Association for Quantitative Traits of Garden Pea (Pisum sativum L.)

The field experiment was carried out in randomized block design repeating each genotype into 3 blocks at Agriculture Farm of Lovely Professional University, Jalandhar, Punjab, India during rabi season (November–March) of 2015–16. Variability in the breeding population is essential pre-requisite to improve yield, earliness, disease resistance, lodging resistance etc. and the study of correlation and path analysis help in formulating selection indices for yield improvement. Therefore, a study was carried out undertaken to assess the magnitude of genetic variability and character association in twenty four diverse genotypes of garden pea (Pisum sativum L.) based on eleven quantitative characters. Analysis Of Variance (ANOVA) showed the existence of wide variability among the genotypes for all the characters studied. Closer magnitude of genotypic and phenotypic variation also indicated the presence of considerable genetic variability for all characters. High proportion of GCV accompanied with high heritability (in broad sense) and high genetic gain/genetic advance as percentage of mean were recorded for the characters like days to 50% flowering, plant height, harvesting span, dry matter and pod yield. Significant positive genotypic and phenotypic correlations were observed among pod yield and days to 50% flowering, number of pods plant-1 and number of seeds pod-1. These characters also had positive direct effect on pod yield. Hence, it can be concluded that selection is feasible for improvement of the characters studied under investigation.
Orbital Transfer Performance Analysis for the First Turkish Lunar Mission

The First Turkish Lunar Mission is an ongoing space research mission of the Space Technologies Research Institute of the Scientific and Technological Research Council of Türkiye (TUBITAK VZAY) under the National Space Program coordinated by Turkish Space Agency (TUA). The mission will be the first of a two phase program which will perform a Lunar orbit acquisition, carry out scientific observations and attain hard landing on the lunar surface as part of its main objectives. In this paper, performance analyses for the most critical parts of the orbital transfer, namely Earth escape maneuver, trajectory correction maneuver and Lunar orbit insertion maneuver are presented. First, a brief summary of the mission profile is provided with system definition, transfer design strategy and transfer orbits. Then, the results of dispersion analysis investigating the effects of errors for the three critical maneuvers are summarized. Finally, the orbit determination strategy is discussed and preliminary results are given.
Advances in the treatment of pancreatic cancer with traditional Chinese medicine

Pancreatic cancer is a common malignancy of the digestive system. With a high degree of malignancy and poor prognosis, it is called the “king of cancers. ” Currently, Western medicine treats pancreatic cancer mainly by surgical resection, radiotherapy, and chemotherapy. However, the curative effect is not satisfactory. The application of Traditional Chinese Medicine (TCM) in the treatment of pancreatic cancer has many advantages and is becoming an important facet of comprehensive clinical treatment. In this paper, we review current therapeutic approaches for pancreatic cancer. We also review the protective effects shown by TCM in different models and discuss the potential molecular mechanisms of these.
The burden of acute eye conditions on different healthcare providers: a retrospective population-based study

Background The demand for acute eyecare exponentially outstrips capacity. The public lacks awareness of community eyecare services. Aim To quantify the burden of acute eyecare on different healthcare service providers in a national population through prescribing and medicines provision by GPs, optometrists, and pharmacists, and provision of care by accident and emergency (A&E) services. A secondary aim was to characterise some of the drivers of this burden. Design and setting A retrospective data-linkage study set in Wales, UK. Method Analysis of datasets was undertaken from the Secure Anonymised Information Linkage Databank (GP and A&E), the Eye Health Examination Wales service (optometry), and the Common Ailments Scheme (pharmacy) during 2017–2018. Results A total of 173 999 acute eyecare episodes delivered by GPs (168 877 episodes) and A&E services (5122) were identified during the study. This resulted in 65.4 episodes of care per 1000 people per year. GPs prescribed a total of 87 973 653 prescriptions within the general population. Of these, 820 693 were related to acute eyecare, resulting in a prescribing rate of 0.9%. A total of 5122 eye-related and 905 224 general A&E attendances were identified, respectively, resulting in an A&E attendance rate of 0.6%. Optometrists and pharmacists managed 51.8% (116 868) and 0.6% (2635) of all episodes, respectively. Older females and infants of both sexes were more likely to use GP prescribing services, while adolescent and middle-aged males were more likely to visit A&E. GP prescribing burden was driven partially by economic deprivation, access to services, and health score. Season, day of the week, and time of day were predictors of burden in GP and A&E. Conclusion Acute eyecare continues to place considerable burden on GP and A&E services in Wales, particularly in urban areas with greater economic deprivation and lower overall health. This is likely to increase with a rapidly ageing population. With ongoing pathway development to better utilise optometry and pharmacy, and improved public awareness, there may be scope to change this trajectory.
Design and Implementation of an FFT-Based Neural Network Accelerator Using Rapid Single-Flux-Quantum Technology

Deep neural networks (DNNs) are continually expanding in size and complexity, making it essential to enhance their energy efficiency and performance without sacrificing accuracy. The model size significantly influences the performance, scalability, and energy efficiency of DNNs, which has led to increased interest in model compression and hardware acceleration research. This paper presents a novel convolution processor architecture specifically designed for a block-circulant matrices-based neural network processing approach. The proposed design employs ultra-fast (tens of gigahertz) superconductor-based devices and leverages fast Fourier transform (FFT)-based rapid multiplication, achieving a simultaneous reduction in both computational complexity and storage complexity from $\mathrm{O}(\mathrm{n}^{2})$ to O(n log n). To validate the concept, we implement a 7-bit, 8-point convolution processing element (CPE) based on the proposed architecture, demonstrating high-speed operation up to 43.1 GHz. The implemented circuit consists of 21,575 Josephson junctions and is fabricated using a 10kA/cm$^{2}\,9 -$layer niobium superconductor process
A survey of Stomoxys Geoffroy, 1762 (Diptera: Muscidae) in eight administrative regions of Cameroon

Stomoxys Geoffroy, 1762 are major livestock pests in the tropics and are common in diverse habitats. This study aims to conduct a survey on the Stomoxys fauna of Cameroon. From 2015 to 2017, entomological studies using standard traps (n=204) were conducted in eight administrative regions found in five agro-ecological zones (AEZs) of Cameroon with 606 trap-points over 22,032 traps days. A total of 77,804 Stomoxys specimens were collected, with eight taxa consisting of six species (S. calcitrans (Linnaeus, 1758), S. omega Newstead, Dutton & Todd, 1907, S. xanthomelas Roubaud, 1937, S. inornatus Grunberg, 1906, S. transvittatus Villeneuve, 1916
DECISION TREE SIMPLIFICATION THROUGH FEATURE SELECTION APPROACH IN SELECTING FISH FEED SELLERS

Feed is a crucial variable because it can determine the success of fish farming. Breeders can use two types of artificial feed, namely alternative feed and pellets. Many cultivators need pellets as the main consumption for the fish they are cultivating because the pellets contain a composition that has been adjusted to their needs based on the type and age of the fish. However, currently, cultivators are facing a problem, namely the high price of fish pellets on the market. Therefore, an analysis of the classification of the selection of fish feed sellers is needed that is adjusted to several criteria like the number of types of feed, price, order, delivery, and availability of discounts. This study conducted a classification analysis of simplification of characteristics in selecting fish feed sellers in Kendal Regency that would then be compared with a model without feature selection by utilizing the Decision Tree C4.5 method. The results of this study are the decision tree with the best performance where C4.5 with the application of the selected feature has an accuracy value of 92%, while C4.5 without the selection feature has an accuracy of 86.8%. The results of this study indicate that the C4.5 method with the application of selection features is better than C4.5 without selection features so that it can be applied to the selection of freshwater fish feed sellers in Kendal Regency.
Backstepping Sliding Mode Control for Quadrotor UAV Based on Adaptive Observer

This paper considers the accurate trajectory control of quadrotor unmanned aerial vehicles (UAVs) under the presence of both actuator faults and uncertain disturbances. A new approach that combines an adaptive observer with a backstepping sliding mode control method is proposed. The proposed adaptive observer is designed to accurately observe and compensate for the uncertain faults and external disturbances in a quadrotor system. Stability analysis shows that the error of trajectory control by the proposed controller is guaranteed to converge to zero when both actuator faults and uncertain disturbances are present in a quadrotor system. Simulation results show that the proposed controller can achieve performance better than that of a few other control methods for the trajectory control of quadrotor UAVs under the presence of both actuator faults and uncertain disturbances.
Proposal for the High Energy Neutrino Telescope

The Large High Altitude Air Shower Observatory (LHAASO) has observed tens of gamma-ray sources with significant emission above 100 TeV. These gamma-ray sources are probably the Galactic accelerators of PeV cosmic-rays. Thus, high energy neutrinos above 100 TeV are expected to be observed from these PeVatron candidates. We propose the Huge Underwater high-energy Neutrino Telescope (HUNT) with instrumented volume up to 30 km 3 to search for neutrino sources above 100 TeV, which will help us to identify the PeVatrons in our Galaxy and understand the acceleration of PeV cosmic-rays in the deep universe. Here, we present some preliminary results of the telescope simulation, the performance evaluation and the pathfinder experiment
Flexible Analog-to-Feature Converter for Wireless Smart Healthcare Sensors

Analog-to-Feature (A2F) conversion based on Non-Uniform Wavelet Sampling (NUWS) has demonstrated the ability to drastically reduce the energy consumption in wireless sensors while employed for electrocardiogram (ECG) anomaly detection. The underlying idea is to extract relevant features from the analog signal and perform the classification in the digital domain. We adopt the same approach for a human activity recognition (HAR) task, considered as a second application for a proposed generic A2F converter. By extracting only 16 features from the inertial signals of the UCI-HAR data set and using these features as inputs for a simple Neural Network, we achieved an 87.7% accuracy in multiclass classification. From the simulation results, we defined the relevant features and the hardware specifications required for a complete circuit design and chip fabrication.
Multiple Camera based Lightweight Localization Technology for Indoor Parking lot

Recently, there has been an active development in AVP (Auto Valet Parking) solutions for various last mile services. Despite the efforts, there is a limitation in reaching complete automation by only relying on autonomous vehicle sensors in complex and diverse parking environments. Especially in an indoor parking environment where GPS sensors are not supported, the autonomous vehicles have difficulties in locating themselves. In a such environment, the localization problem can be effectively coped by using smart infrastructure installed in the parking lot to analyze parking environment information. In this paper, we propose a method for mapping multiple camera images into a single grid map, and lightweight localization algorithm by tracking vehicles in parking lots, including environment where perceptive fields of surveillance cameras are not overlapping. By providing localization information of autonomous vehicles, the safety in AVP solution can be improved.
Changes in Diet Quality over 10 Years and Subsequent Mortality from Cardiovascular Disease in the Multiethnic Cohort Study

This study investigated how diet quality changes over a ten-year period, assessed using the following four diet quality indexes, the Healthy Eating Index-2015 (HEI-2015), Alternative Healthy Eating Index-2010 (AHEI-2010), alternate Mediterranean Diet (aMED), and Dietary Approaches to Stop Hypertension (DASH), were related to mortality from cardiovascular disease (CVD) in the Multiethnic Cohort Study. The analysis included 61,361 participants who completed both the 1993–1996 baseline survey and the 2003–2008 10-year follow-up surveys. Over the mean follow-up period of 13 years after the 10-year survey, 4174 deaths from CVD were identified. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using multivariable Cox models. Increases in diet quality scores were associated with a reduced risk of CVD mortality for all indexes: HRs per one SD increment of 0.94 to 0.99 (HR (95% CI), 0.96 (0.92–1.01) for HEI-2015, 0.96 (0.91–1.01) for AHEI-2010, 0.99 (0.94–1.04) for aMED, and 0.94 (0.89–0.99) for DASH) in men and 0.88 to 0.92 (0.88 (0.84–0.92) for HEI-2015, 0.90 (0.85–0.95) for AHEI-2010, 0.89 (0.84–0.95) for aMED, and 0.92 (0.87–0.96) for DASH) in women. The inverse association generally did not vary by race and ethnicity, age, body mass index, smoking, and hypertension in each sex. Our findings suggest that improving diet quality and maintaining a high-quality diet over time may help reduce the risk of CVD mortality and could also be beneficial for those at higher risk of CVD.
Numerical simulation of the North Atlantic Ocean at 1/10 degrees

Abstract In this paper an initial analysis of an 0.1° simulation of the North Atlantic Ocean using a level-coordinate ocean general circulation model forced with realistic winds covering the period 1985–96 is presented. Results are compared to the North Atlantic sector of a global 0.28° simulation with similar surface forcing and to a variety of satellite and in situ observations. The simulation shows substantial improvements in both the eddy variability and the time-mean circulation compared to previous eddy-permitting simulations with resolutions in the range of 1/2°–1/6°. The resolution is finer than the zonal-mean first baroclinic mode Rossby radius at all latitudes, and the model appears to be capturing the bulk of the spectrum of mesoscale energy. The eddy kinetic energy constitutes 70% of the total basin-averaged kinetic energy. Model results agree well with observations of the magnitude and geographical distribution of eddy kinetic energy and sea-surface height variability, with the wavenumber–fre.
Machine Learning Regression to Predict Soil Moisture in Domestic Garden Environments

Due to the rapid growth of the global population and limited water resources, water shortages have become an urgent problem for our society. Over 71% of freshwater withdrawals in the world are for irrigation purposes. Thus, more accurate and robust soil moisture modeling is needed to create more efficient irrigation systems, which, in turn, may lead to substantial water savings. However, existing soil moisture modeling methodologies have limited accuracy and low temporal resolution. In this study, the accuracy of using a machine learning model for high temporal resolution soil moisture modeling is demonstrated. A multimodal sensing system is designed and implemented to create a high temporal resolution dataset in the water-scarce region of South Africa. This data is then used to evaluate the accuracy of different algorithms for soil moisture modeling, where the Random Forest regressor shows promising results.