Miracle-dz/UniFAR-FTUs huggingface dataset:
MILLENNIAL INVESTOR DECISION ANALYSIS AND ITS DETERMINANTS (AN ENDOGENEITY PERSPECTIVE)

This study aims to see 1) The effect of Financial Literacy on the investment decisions of the millennial generation in Padang City 2) The effect of Risk Perception on the investment decisions of the millennial generation in Padang City 3) This type of research is a comparative causal research (Causative). The sample in this study was 96 respondents who are the Millennial generation of Padang City with a purposive sampling method. The types of data in this study are primary data and secondary data. This study uses panel data regression analysis. The data collection technique used is a questionnaire. Instrument trials use validity and reliability tests. Prerequisite analysis tests carried out included normality tests, heteroscedasticity tests, and multicollinearity tests. The collected data was analyzed using SPSS version 20.0. This study also examines endogeneity by using financial literacy as an endogenous variable and risk perception as an instrument variable. The results of this study indicate 1) Financial Literacy has a significant positive effect on the investment decisions of the millennial generation in Padang City 2) Risk Perception has a positive but not significant effect on the investment decisions of the millennial generation in Padang City due to endogeneity
Temperature Variation of Radiant Heater Modules Used for Re-Entry Heating Simulations

Launch Vehicles/Spacecrafts are thermally protected from ascent/reentry flight aero heating using different types of thermal protection systems (TPS) that are selected based on the maximum heat flux and total heat load. The TPS is designed/qualified by simulating the actual heat flux history on test samples. The heat flux history can be simulated on the test panels using radiant heater modules which are dynamic, fast response and actively controllable. During heat flux simulation, the actual heat absorbed by the material depends on the surface absorptivity of the exposed surface to the heating. The effective surface absorptivity is derived from the absorptivity spectrum using the emission spectrum of the heating filament at its source temperature. Hence it is important to estimate the filament temperature for a given heat flux simulation in order to determine the effective surface absorptivity. This is essential for accurately determining the actual heat flux absorbed by the material and thereby attaining the correct material thermal response. The radiant heater module used in this study consists of tungsten filaments enclosed in argon filled quartz bulbs. Calculation of the filament temperature and quartz tube temperature is done by solving the energy balance equation of both filament and quartz tube. For the filament, power input is the product of voltage and current, which can be experimentally measured. Properties like emissivity of filament, conductivity of argon as a function of temperature is incorporated in the model, theoretical modelling of heat transfer and filament temperatures have been undertaken elsewhere, but details of estimation of filament temperature with respect to the simulated heat flux and distance from lamp module for high power rated 8kW filaments used in re-entry aero thermal simulations are not available. This work describes the estimation of the filament temperature variation as a function of heat flux and distance from the heater module utilizing actual measurement of current and voltage through each filament.
Sum Capacity-Based Modeling and Secrecy Analysis of MISO-NOMA Cooperative IoT Framework

Non-orthogonal multiple access (NOMA) has emerged as an effective technology, aiding in latency reduction, improving security and reliability, and enhancing the spectral efficiency and capacity in Internet of Things (IoT)-enabled communication systems. In this work, an implementation of co-operative secure multiple-input single-output NOMA IoT framework is proposed and examined in a two-fold manner. First, under the consideration of standalone links, a user selection criteria which relies on the characterization of sum ergodic capacity (SEC) is investigated in the presence of an eavesdropper (ED) and beamforming constraints. Next, using the optimized beamformers, a user selection criteria which relies on the outage probability analysis is performed under cooperative relaying considerations. We demonstrate that our optimization approach achieves reduced capacity and coverage for the ED while maximizing the overall SEC and coverage of the network under multiple network configurations. The proposed optimization solution demonstrates superior performance compared to the benchmarked schemes. Derived closed-form analytical expressions are validated through simulation means.
State of Art Enhanced Fatigue Meter Adaptable across Aircrafts

This paper discusses the novel design and development of the state of art fatigue meter for the fighter aircrafts. The unique features of the enhanced fatigue meter (eFM) are its capability to be configured for critical parameters, adaptable across different aircrafts and flexible for using internal or external accelerometer. The combat aircrafts carry out a lot of maneuvers while flying. While doing so, these aircrafts experience large range of variations in the accelerations due to gravity i.e. G-variations. This sudden and large change in acceleration due to gravity, as a function of time forms the fatigue loading on the airframe. This fluctuating loading causes fatigue damage to be accumulated in the aircraft structure. Over a period of time, the accumulated fatigue damage leads to development of crack and breakdown of the structure. In order to monitor and keep track of the g-loads experienced by the aircraft and to predict the remaining service life of the aircraft, a system that measures the g-loads encountered by the aircraft every time it flies is essential. The relevant g-load spectrum of the aircraft can be derived from these recorded data.
Integrative approach for sustainable viticulture in Portugalˈs Douro Valley: The NOVATERRA approach in mountain viticulture

United Nations' Sustainable Development Goal number 12 pledges to ensure the sustainability of production and consumption of the food system. Towards more sustainable agriculture, a reduction of contentious pesticides, increasing spray application efficiency, and supporting strategies for integrated control is required. This can be obtained by developing innovative eco-friendly strategies that protect both the environment and human health. In this sense, SOGRAPE, a family-owned wine company, is a partner of project NOVATERRA (funded by EU’s Horizon 2020), aiming at improving the sustainability of viticulture by integrating new plant protection products (PPPs) of natural origin, biodiversity conservation, precision agriculture, robotics, and integrated soil and crop management strategies. NOVATERRA project trials have been made at SOGRAPE’s Quinta do Seixo, located in Cima Corgo, central sub-region of the Douro valley. This project is based in a practical and integrative approach, promoting multivariate case studies, in real scale trials executed by SOGRAPE to maximize adoption of successful solutions obtained from case studies. In this way, SOGRAPE engages in promoting the sustainability of the viticulture sector, working on several assignments of the project. The novel approaches assessed in NOVATERRA project work for the same goal of paving the way towards increasingly sustainable agriculture, combined into an integrated vine protection strategy.
Habitat of Yilgarn gold - from fault and worm analysis

The A1 project seeks to characterise and discriminate between penetrative faults that are permissive to mineralisation from those that appear not so prospective. Such faults populate the Tectonic Targets database, where a lower limit of 100km strike length is imposed on the input data. Although restrictive, this makes for easier management of a global database. However, in nature, populations of faults occur over a range of scales and, in this regard, the Yilgarn fault population is being assessed.
ANALYSIS OF SERVICE QUALITY LIVESTOCK MARKET ON TRADERS SATISFACTION USING THE IMPORTAND PERFORMANCE ANALYSIS METHOD

The study was conducted to determine the level of interest of traders in the quality of service provided by the Palangki Livestock Market Service, Sijunjung Regency, with the performance level of service quality provided by the Palangki Livestock Market Service, Sijunjung Regency to traders in the Palangki Sijunjung Regional Livestock Market. This type of research is a quantitative descriptive research. The sample used was 72 respondents. Sampling using non-probability with incidental sampling technique. The analytical methods used include Importance and Performance Analysis, Customer Satisfaction Index. The results of the calculation of the overall Customer Satisfaction Index on the quality of service provided by the Palangki Livestock Market Service are 55 percent, indicating that the traders of the Palangki Livestock Market are "Quite Satisfied" with the quality of service provided by the Palangki Livestock Market Service, Sijunjung Regency. Keywords: Livestock Market, IPA, Customer Satisfaction Index.
SMART TEA: Churn, Trend, Inventory and Sales Prediction System Using Machine Learning

Managing operations at a tea factory requires consistency and planning. This paper presents a complete platform that uses advanced machine learning methods specifically designed for the tea sector. Sales prediction, churn prediction, trend prediction, and smart inventory management are the four essential features of our solution. While using Neural Networks for Churn Prediction offers exact insights into customer churn, utilizing Gradient Boosting for Sales Prediction guarantees accurate revenue estimates. Linear regression models were used for trend prediction and smart inventory management to enable efficient utilization of resources and trend identification. With the help of this integrated system, tea companies can now operate more profitably and sustainably in a market that is always changing. This research acts as a beacon, demonstrating the revolutionary potential of data-driven management as operations in the tea industry evolve.
RAPID AND AUTOMATED BODY MEASUREMENT OF CATTLE BASED ON STATISTICAL SHAPE MODEL

Abstract. The current methods of non-contact livestock body measurement directly deal with the low-quality point cloud data of livestock, which have low robustness and lack practicality. On the one hand, the success rate of keypoint detection for livestock body measurement is low. Due to the severe occlusion and noise in the point cloud data, body measurements of some data cannot be performed. On the other hand, the key frames need to be manually selected from the point cloud sequence during processing. Inspired by the work of 3D reconstruction based on animal statistical shape models, we implement the construction and learning of the statistical shape model of real cattle. Given the establishment of the statistical shape model of cattle, a 3D reconstruction and body measurement approach of real cattle based on low-quality point cloud data is proposed. Nine indicators are calculated and the overall estimation MAPE (Mean Absolute Percentage Error) is 10.27%. The whole process of the body measurement algorithm proposed in our paper can be extended to other quadrupeds.
Investigation of the stability of nanofluids based on water and carbon nanoparticles synthesized by the electric arc method

In this work, arc discharge synthesis was carried out by sputtering electrodes of various compositions in a helium medium, as a result of which two types of materials containing carbon globules and graphene flakes were obtained. The synthesized materials were characterized with transmission electron microscopy, scanning electron microscopy, and Raman spectroscopy. The effect of the type and concentration of carbon nanoparticles and the type of surfactants on the stability of water-based nanofluids was studied with optical spectroscopy. For carbon globules and water, the mass concentrations of nanoparticles and sodium dodecyl sulfate were determined to obtain a nanofluid based on them stable for 1 month, which are 0.02% and 1%, respectively. It was shown that the use of neonol AF 9-12 at a concentration of 2% didn’t lead to the stabilization of carbon globules with a mass concentration of 0.02% in water. For graphene flakes, the mass concentrations of nanoparticles and stabilizers to obtain a water-based nanofluid stable for 1 month were: 0.02% graphene flakes and 1% SDS, as well as 0.02% graphene flakes and 2% neonol AF 9-12, respectively.
Surveillance and Outcomes of Pediatric Hematopoietic Stem Cell Transplantation Recipients During the Recent COVID-19 Outbreak in China

Background The COVID-19 pandemic presents challenges for healthcare systems globally, especially in vulnerable populations such as pediatric hematopoietic stem cell transplant (HSCT) recipients. This study examines the clinical characteristics and outcomes of COVID-19 infection in pediatric HSCT recipients within one year post-HSCT. Methods Retrospective analysis was conducted on data from 247 pediatric patients. None of them had received SARS-CoV-2 vaccination or had prior infection. SARS-CoV-2 infection was confirmed using RT-PCR testing. COVID-19 disease severity was categorized according to established guidelines. Demographic, clinical, laboratory, imaging and treatment data were collected. Results The median age of the cohort was 7±3.7 years, with thalassemia major as the predominant underlying disease. Allogeneic HSCT was performed in the majority of cases, with haploidentical donors being the most common source of grafts. Nearly half of the patients developed COVID-19, with significantly higher infection rates observed in recipients over 100 days compared to recipients within 100 days post-HSCT (40.1% vs 21.7%, p<0.05, Fisher’s Exact test). Fever (n=107, 43.2%) and cough (n=88, 35.6%) were the most common symptoms. While most patients had mild disease and did not require specific anti-viral treatment, a significant proportion required hospitalization (n=34, 13.8%). Various treatments were employed hospitalized patients, including Paxlovid (n=19, 55.9%), methylprednisolone (n=7, 20.6%), IL-6 antibody (n=2, 5.9%), mesenchymal stem cells (n=3, 8.8%), and exosomes nebulization therapy (n=2, 5.9%). Despite multidisciplinary approaches, one patient died from severe respiratory failure. However, overall survival of all patients remained high (99.53%; CI 96.72–99.93%), indicating favorable outcomes in pediatric HSCT recipients with COVID-19. Conclusion This study provides insights into clinical features, therapeutic measures, and outcomes of pediatric HSCT recipients following COVID-19 infection in a large HSCT center in China. These findings contribute to our understanding of COVID-19 in this population and inform strategies to mitigate the impact the pandemic’s impact on their care.
Factors Affecting the Achievement of Students in Mathematics

The program offered at the secondary level (specially in class 9 and 10) of Nepal requires the completion of mathematics courses. To go to science and technology subjects in class 11 and 12 as well as in university level, the students should succeed in the class 10 examination (SEE) in mathematics so that this will provide the pathway for them to be succeed in the study of university level. This research aims to investigate the factors affecting the achievement of students in mathematics at secondary level. For acquiring this aim, this study has used qualitative research method for completing the entire work. The primary data for this study was collected through focus group discussion with mathematics teachers and head teachers. All secondary schools in Nepal were considered as the population of the study and selected four districts viz Chitwan, Gorkha, Makawanpur and Parsa as the first stage of sampling. In the second stage, secondary level mathematics teachers of Chitwan, Gorkha, Makawanpur and Parsa districts were taken as sampling population. Eight groups of mathematics teachers consisting of two groups from each district and two group of head teachers from Chitwan district chosen using purposive sampling method were sample for this study. The collected information was analyzed using constant comparison method of data analysis. The results of the study showed that teachers beliefs solely not responsible for the students’ achievement in mathematics, but integrated effects of variables such as students’ factors, teachers’ factors, system factors, environmental and societal factors were the causes for the low achievements of students in SLC/SEE.
Snow data assimilation‐constrained land initialization improves seasonal temperature prediction

We present the first systematic study to quantify the impact of land initialization on seasonal temperature prediction in the Northern Hemisphere, emphasizing the role of land snow data assimilation (DA). Three suites of ensemble seasonal integrations are conducted for coupled land‐atmosphere runs. The land component is initialized using datasets from (1) no DA, (2) assimilating Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF), and (3) assimilating both MODIS SCF and Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage. Results show that snow DA improves temperature predictions especially in the Tibetan Plateau (by 5–20%) and high latitudes. Improvements at low latitudes are seen immediately and last up to 60 days, whereas improvements at high latitudes only appear later in transitional seasons. At high latitudes, assimilating GRACE data results in marked and prolonged improvements (by ~25%) due to large initial snow mass changes. This study has great implications for future land DA and seasonal climate prediction studies.
Learning Anatomy with Augmented Reality

An Augmented Reality (AR) application was developed to help students at SDU to learn the anatomy of the human body (mediastinum). This research project intended to evaluate whether AR strengthened the students’ self-efficacy and motivation, improved learning, and provided a good learning experience. This study focusses on how AR can help students to translate two-dimensional into three-dimensional understanding and evaluates formats of the app (the use of quizzes) together with the didactic design of the teaching sessions with AR. The objectives were to examine A. the effectiveness of using AR on student’s short, long term, and transfer learning outcome compared with traditional teaching, B. the effect of quizzes, and C. app design in relation to didactic design. In the AR world students saw a standardized hologram body combined with selected images from a computed tomography (CT) scan. The CT images were presented at the proper spatial positions in a hologram body. The user could select which structures to be shown at the body (e.g. skin, the vascular system, etc.). They could approach the body, circumvent it, study structures in details and compare the concurrent presentation with the different CT images. During class one group received traditional teaching and two groups studied CT scans in Augmented Reality. One AR-group complemented the AR app with quiz questions and received corrective feedback. The other AR group did not use quiz questions but studied content on their own hand. A teacher was present and ready to help students in all groups. The aim of this paper is to share lessons learned from this intervention and suggest solutions for app design and learning design to facilitate deeper learning processes and scaffold learners’ needs with AR as a learning resource.
Datastore Distillation for Nearest Neighbor Machine Translation

Nearest neighbor machine translation (i.e., <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>NN-MT) is a promising approach to enhance translation quality by equipping pre-trained neural machine translation (NMT) models with the nearest neighbor retrieval. Despite its great success, <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>NN-MT typically requires ample space to store its token-level datastore, causing <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>NN-MT to be less practical in edge devices or online scenarios. In this paper, inspired by the concept of knowledge distillation, we provide a new perspective to ease the storage overhead by datastore distillation, which is formalized as a constrained optimization problem. We further design a novel model-agnostic iterative nearest neighbor merging method for the datastore distillation problem to obtain an effective and efficient solution. Experiments on three benchmark datasets indicate that our approach not only reduces the volume of the datastore by up to 50% without significant performance degradation, but also outperforms other baselines by a large margin at the same compression rate. Another experiment conducted on WikiText-103 further demonstrates the effectiveness of our method in the language model task.
Vegetation of the Warra silvicultural systems trial

Vegetation types were classified within a trial testing alternative silvicultural systems to clearfell, burn and sow at the Warra Long-Term Ecological Research Site. Three vegetation types were recognised within the silvicultural systems trial: Eucalyptus obliqua wet forest with a wet sclerophyll understorey dominated by tea-tree, cutting grass and bauera (G-type), E. obliqua mixed forest with an understorey of rainforest species typical of thamnic rainforest, particularly horizontal scrub (T-type) and E. obliqua mixed forest with an understorey of rainforest species typical of callidendrous rainforest (C-type). The three types were floristically distinct and were readily recognisable in the field. The ordination of internal and remote (external) control plots established recently agrees with the ordination of the vegetation prior to the establishment of the silvicultural systems trial. Therefore, these plots will be useful for future monitoring. Fire history was shown to have a major influence on the vegetation.