Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectroscopic studies of OB stars in the Magellanic Clouds with VLT-UVES

We present results from optical and ultraviolet analysis of nine LMC/SMC supergiants. Temperatures, mass-loss rates and CNO abundances are obtained using the non-LTE, line-blanketed model atmosphere code of Hillier & Miller (1998). In general, the derived temperatures are significantly lower than those determined from unblanketed, plane-parallel models.
Mathematical Models for Analysis the Impact of Institutional Quality and Multilateral Financial Institutions on the Success of Green PPP Projects

Green PPP projects are of great significance to green infrastructure construction and green economic development. This study analyzes 552 Green PPP projects related to sewage treatment and clean energy in African countries during 2005-2019 to determine how institution quality and multilateral financial institutions influence Green PPP projects’ success. We find that (1) successful (failed) Green PPP projects experience increase (decrease) new Green PPP projects’ success rate. (2) Higher private capital risk-taking degree increases the likelihood of failure. (3) Institution quality affects project success through a mixed effect on private capital’s risk-taking degree: rule of law, government effectiveness, control of corruption, and regulatory quality positively promote private capital’s risk taking; voice has an opposite effect. (4) Multilateral financial institutions’ participation in Green PPP projects promotes higher private capital risk taking.
Particles Detection System with CR-39 Based on Deep Learning

We present a novel method that we call FAINE, fast artificial intelligence neutron detection system. FAINE automatically classifies tracks of fast neutrons on CR-39 detectors using a deep learning model. This method was demonstrated using a LANDAUER Neutrak® fast neutron dosimetry system, which is installed in the External Dosimetry Laboratory (EDL) at Soreq Nuclear Research Center (SNRC). In modern fast neutron dosimetry systems, after the preliminary stages of etching and imaging of the CR-39 detectors, the third stage uses various types of computer vision systems combined with a manual revision to count the CR-39 tracks and then convert them to a dose in mSv units. Our method enhances these modern systems by introducing an innovative algorithm, which uses deep learning to classify all CR-39 tracks as either real neutron tracks or any other sign such as dirt, scratches, or even cleaning remainders. This new algorithm makes the third stage of manual CR-39 tracks revision superfluous and provides a completely repeatable and accurate way of measuring either neutrons flux or dose. The experimental results show a total accuracy rate of 96.7% for the true positive tracks and true negative tracks detected by our new algorithm against the current method, which uses computer vision followed by manual revision. This algorithm is now in the process of calibration for both alpha-particles detection and fast neutron spectrometry classification and is expected to be very useful in analyzing results of proton-boron11 fusion experiments. Being fully automatic, the new algorithm will enhance the quality assurance and effectiveness of external dosimetry, will lower the uncertainty for the reported dose measurements, and might also enable lowering the system’s detection threshold.
Prediction of potential credit card users of bank based on deep learning

In the post epidemic era and the rapid development of science and technology finance, bank credit card marketing has been greatly impacted. This paper proposes a new deep learning model DeepAFM (Deep Attentional Factorization Machine), which is used to predict potential credit card users of bank, so as to provide an effective basis for bank precision marketing. The model uses factorization machine and embedding layer to decompose the parameter matrix into low dimensional parameter matrix; The Attentional Mechanism is introduced to learn the weight of cross features and extract important features; A fully connected depth network is introduced to realize the mining of higher-order cross features. Finally, through the comparison with other algorithms, the results show that the expression ability of DeepAFM model is better and the automatic mining of important data is more accurate.
Some tropical geometry of algebraic groups, minimal orbits, and secant varieties

Given a variety X embedded in a projective space PV , the (k - 1)-st secant variety of X, denoted kX, is the closure of the union of all (k -1)-spaces spanned by k points on X. We usually require that X spans PV , so that kX = PV for k sufficiently large. We often work with the cone C in V over X rather than with X, and write kC for the cone over kX. Secant varieties appear in applications as diverse as phylogenetics [2, 5, 12], complexity theory [10, 11], and polynomial interpolation [1]. The references in this note are by no means complete, but they themselves contain many further relevant references.
TAXONOMIC ASSESSMENT OF CURCULIGO ORCHIOIDES USING matK AND rbcL DNA BARCODES

Curculigo orchioides is most commonly used as an imperative medicinal plant in Vietnam. The plant roots are mainly used to treat sexual dysfunction, back pain, arthritis, nephritis, jaundice, and infertility. Given the high market demand in the herbal market, C. orchioides traders commonly adulterate with other similar plants for illegitimate benefits. Maturase K (matK) and ribulose 1,5-biphosphate carboxylase (rbcL) DNA barcode loci are presently used to identify the blends and counterfeit the medicinal herbs, as well as, identify the propagating conservation material. Nevertheless, the identification accuracy is highly dependent on NCBI Genbank or Barcode of Life Database (BOLD). In the recent study, the efficiency of DNA barcode loci, matK and rbcL for the classification of C. orchioides populations, was investigated during 2020–2021. After examining 11 accessions of C. orchioides collected from different locations in Vietnam, the obtained results revealed that using NCBI database is more effective for classifying C. orchioides. In addition, the matK locus also showed higher identification power than rbcL. The obtained findings could be helpful in the trading management, conservation, and development of C. orchioides in Vietnam.
Energy Use Greenization, Carbon Dioxide Emissions, and Economic Growth: An Empirical Analysis Based in China

Developing countries are constantly facing the problem of environmental degradation. Environmental degradation is caused by the consumption of non-renewable energy for economic growth, but the consequences of environmental degradation cannot be ignored. The main purpose of this study is to investigate the relationship between three variables (i.e., energy use greenization, CO2 emission, and economic growth) in the case of China using simultaneous equation modeling techniques and data for the period 2000–2018. The results indicate that (1) there is a long-term equilibrium relationship between energy use greenization, carbon emissions, and economic growth in China. Energy use greenization not only reduces carbon dioxide emissions but also promotes sustainable economic growth in China. (2) Carbon emissions and economic growth have promoted energy use greenization, indicating that the pressures of environmental climate and economic transformation in China have forced energy use greenization to a certain extent. (3) The contribution rate of energy use greenization to economic growth shows an inverted U-shaped trend that rises first and then decreases subsequently, while carbon emissions have a relatively large contribution rate to green energy use and economic growth. These results have far-reaching policy directions for the environmental sustainability goals of the Chinese economy.
Improving the Power Efficiency of a PV Power Generation System Using a Proposed Electrochemical Heat Engine Embedded in the System

An important issue in the photovoltaic (PV) power generation systems is the massive amount of heat wasted by PV modules/panels. For the first time, this paper provides a new solution to recover a portion of the mentioned waste heat by utilizing a proposed electrochemical heat engine. A thermally regenerative electrochemical cycle (TREC) system has been designed, constructed, and embedded in a PV power generation system including a 200-W PV module to harvest the waste heat of its PV module, so a PV-TREC hybrid system has been organized and built. The hot cell of the TREC system has been positioned in direct contact with the backside of the PV module, and the cold cell is in direct contact with a heat sink located in the shade of the PV module. Experimental verifications demonstrate that the proposed TREC system efficiently converts the waste heat into electric power ranging from 0.1 to 54.5 W. In this manner, up to 6% of the waste heat of the PV module is recovered. It also substantiated that the daily energy efficiency of the PV-TREC hybrid system is improved by 27.5% compared to a usual PV system, and this is the main contribution and novelty of this paper.
The Effects of Temperature and Impact Velocity on the Shock Wave Response of Pore-Embedded Metallic Glasses

In this work, the shock wave response of a pore-embedded CuZr metallic glass (PEMG) under different impact velocities (0.5–1.5 km/s) and initial temperatures (300–600 K) was evaluated through the molecular dynamics (MD) simulation. The results indicated that the nucleation and growth of nanoscale shear events around the pore were the dominant mechanisms for plastic deformation under the shock wave. It was also found that the increase in the impact velocity led to the filling of pore, which was due to the structural softening and the local temperature increment in the vicinity of pore. Moreover, the spall event originated from the formation and coalescence of tension transformation zones, leading to the formation of nanovoids in the system. At higher velocities, the spallation was accompanied with the formation of more nanovoids with smaller sizes, inducing the brittle failure in the system. The MD outcomes also showed that the increase in initial temperature decreased the shock pressure and flow shear stress and led to the smoother spallation in the PEMG.
Stem Cell Growth and Differentiation in Organ Culture: New Insights for Uterine Fibroid Treatment

Organ culture allows for the understanding of normal and tumor cell biology, and tissues generally remain viable for 5–7 days. Strikingly, we determined that myometrial and MED12 mutant leiomyoma cells repopulated cell-depleted tissue slices after 20 days of culture. Using immunofluorescence and quantitative PCR of stem cell and undifferentiated cell markers, we observed clusters of CD49b+ cells in tumor slices. CD49b+ cells, however, were sparsely detected in the myometrial slices. Almost all LM cells strongly expressed Ki67, while only a few myometrial cells were stained for this proliferation marker. The CD73 marker was expressed only in tumor cells, whereas the mesenchymal stem cell receptor KIT was detected only in normal cells. HMGA2 and CD24 showed broader expression patterns and higher signal intensity in leiomyoma than in myometrial cells. In this study, we propose that activating CD49b+ stem cells in myometrium leads to asymmetrical division, giving rise to transit-amplifying KIT+ cells that differentiate to smooth muscle cells. On the contrary, activated leiomyoma CD49b+ cells symmetrically divide to form clusters of stem cells that divide and differentiate to smooth muscle cells without losing proliferation ability. In conclusion, normal and mutant stem cells can proliferate and differentiate in long-term organ culture, constituting a helpful platform for novel therapeutic discovery.
A Deep Neural Network-Based Approach for Sentiment Analysis of Movie Reviews

The number of comments/reviews for movies is enormous and cannot be processed manually. Therefore, machine learning techniques are used to efficiently process the user’s opinion. This research work proposes a deep neural network with seven layers for movie reviews’ sentiment analysis. The model consists of an input layer called the embedding layer, which represents the dataset as a sequence of numbers called vectors, and two consecutive layers of 1D-CNN (one-dimensional convolutional neural network) for extracting features. A global max-pooling layer is used to reduce dimensions. A dense layer for classification and a dropout layer are also used to reduce overfitting and improve generalization error in the neural network. A fully connected layer is the last layer to predict between two classes. Two movie review datasets are used and widely accepted by the research community. The first dataset contains 25,000 samples, half positive and half negative, whereas the second dataset contains 50,000 specimens of movie reviews. Our neural network model performs sentiment classification among positive and negative movie reviews called binary classification. The model achieves 92% accuracy on both datasets, which is more efficient than traditional machine learning models.
Understanding the links between glycemic control, management adherence and hemoglobin level among type 2 diabetes mellitus

Patients with diabetes must be monitored for hyperglycemia due to the risk of macrocellular and microcellular complications. High blood sugar levels force the kidneys to work harder to filter blood, which results in renal leakage. The objective of this study was to establish a relationship between glycemic control, management adherence, and hemoglobin level in patients with type 2 diabetes. This study employed a correlational design with a cross-sectional approach and a sample size of 72 respondents selected using purposive technique. Compliance with diabetes mellitus, which includes diet compliance, exercise compliance, medication compliance, and blood sugar monitoring compliance, is strongly correlated with glycemic control levels. Completely contrary, there was no link between hemoglobin levels and adherence to treatment. Microcellular processes of renal function are linked to the interaction between glycemic control and hemoglobin levels.
Planned oocyte cryopreservation for fertility preservation

Background: Oocyte cryopreservation opens up opportunities for women to preserve fertility when it is necessary to postpone pregnancy. After the advent of vitrification, the results of oocyte cryopreservation were significantly improved compared to conventional slow-freezing. Through these improvements, oocyte cryopreservation was introduced to overcome a decline in fecundity due to an increase in age, and this modality is defined as planned oocyte cryopreservation.Current Concepts: Oocytes cryopreserved through vitrification appear to result in similar clinical pregnancy rates and live birth rates compared to fresh oocytes, though the evidence is still limited. It has been reported that the live birth rate increases when the planned oocyte cryopreservation is performed at a younger age. Obstetrical and neonatal outcomes appear similar between vitrified and fresh oocytes.Discussion and Conclusion: Preliminary data supports planned oocyte cryopreservation as a feasible modality resulting in fertility preservation and subsequent live births. The fact that performing the procedure at a younger age can increase the oocyte yield, oocyte efficacy, and live birth rate can be discussed along with patient consultation. However, as there is still a lack of data on the standardized live birth rate, the number of oocytes to be collected, and the long-term effect on the children; more well-designed studies are needed to improve counseling and decision-making in patients seeking this treatment.
AESTHETIC RATIOS OF FLIGHT - HOW OBSERVER EXPERTISE AND AESTHETIC PERCEPTION ARE RELATED TO WEBSTER FREERUNNING SKILL FLIGHT KINEMATICS

The perception of (motion) aesthetics is related to the circumstances of the object, the observer, and the given context. The central question of this study is whether the perception of motion aesthetics is related to a motor skill’s ratio of flight kinematics and the observer’s sensory-motor experiences. Motor skills, perceived as more aesthetic, are hypothesized to show kinematic flight ratios near the golden ratio. Motor skills, perceived as less aesthetic, are hypothesized to show kinematic flight ratios farther away from the golden ratio. Furthermore, this relationship is hypothesized to be related to the observer’s sensory-motor experience. Therefore, 36 participants (12 freerunning experts, 12 freerunning novices, and 12 laypeople) were asked to indicate their perception of motion aesthetics when watching video sequences of different freerunning performances. The results indicate that kinematic flight ratios and the observer’s sensory-motor experience are related to the aesthetic perception of the freerunning skill. As hypothesized, kinematic ratios of Webster performances perceived as more aesthetic are closer to the golden ratio, and Webster performances perceived as less aesthetic are farther away from the golden ratio; this is significant for expert and novice freerunners, but not for laypeople. Thus, we conclude that the aesthetic perception of complex motor skills is related to kinematic flight ratios and the observer’s sensory-motor expertise. Future work should incorporate such knowledge about kinematic ratios and how to address them during motor skill performances to create and perform aesthetically pleasing complex motor skills.
Effect of Zinc Oxide Nanoparticles on Shelf Life of Commonly Used Vegetables

Most of the harvested fruits and vegetables cannot be stored in natural conditions for satisfactory shelf life duration due to their perishable nature. Applications of nanotechnology to fruits and vegetables shelf life extension may overcome the shortcomings of traditional preservation technologies because nanotechnology has many unique properties. The aim of this study was to examine the effect of zinc oxide nanoparticles (ZnO NPs) synthesized from Nigella sativa extract on shelf life of cucumber and tomato. Nanoparticles were characterized by using UV-Vis spectrophotometry and particle size analyzer. Vegetables were soaked in tap water, distilled water and treated with different concentrations of ZnO NPs (0.05, 0.1, 0.2 and 0.5 g/100 mL). The effect of ZnO NPs on vegetables quality factor like external appearance, weight loss measurement, carotenoid content and total phenolic content was observed. The result showed that ZnO NPs reduced weight loss, delayed disease development and maintained firmness to extend shelf life of vegetables.
Bio-Inspired Autonomous Learning Algorithm With Application to Mobile Robot Obstacle Avoidance

Spiking Neural Networks (SNNs) are often considered the third generation of Artificial Neural Networks (ANNs), owing to their high information processing capability and the accurate simulation of biological neural network behaviors. Though the research for SNNs has been quite active in recent years, there are still some challenges to applying SNNs to various potential applications, especially for robot control. In this study, a biologically inspired autonomous learning algorithm based on reward modulated spike-timing-dependent plasticity is proposed, where a novel rewarding generation mechanism is used to generate the reward signals for both learning and decision-making processes. The proposed learning algorithm is evaluated by a mobile robot obstacle avoidance task and experimental results show that the mobile robot with the proposed algorithm exhibits a good learning ability. The robot can successfully avoid obstacles in the environment after some learning trials. This provides an alternative method to design and apply the bio-inspired robot with autonomous learning capability in the typical robotic task scenario.
A Simple Model of Educated Hand-to-Mouth Consumers

The main goal of this paper is to analyse the role of human capital in the incidence of hand-to-mouth ( HtM ) consumers: those who have no liquid resources. The proposed model is based on a two-asset model by Kaplan, Violante and Weidner [ 2014 ] with an extension to allow for endogenous accumulation of human capital and is confronted with empirical data on US households from the Survey of Consumer Finances (SCF). I show how the HtM status of consumers depends on their innate abilities, time preference and initial resources. Wealthy HtM households, i.e. households with illiquid resources but with little or no liquidity, are more able, more patient and initially richer than poor HtM households. As a consequence, they accumulate more human capital than poor HtM households. For both types of households, their status depends on having a steep income path, which is endogenous because of endogenous human capital accumulation. The correlation of observable characteristics with HtM behaviour may be of interest to
The Potency of Avocado Seeds (”Persea Americana” Mill.) as a Source of Antioxidant Tea

The processing of avocado into avocado juice will produce organic waste, namely avocado skin, and seeds. This potential of organic waste from avocado seeds can be exploited by turning them into tea products. This study employed avocado seed as a source of antioxidants which was made into processed products, namely tea. This research was intended to discover the influence of temperature with avocado seeds on antioxidants as well as the quality of resulting tea products and to determine the best conditions for the drying process of avocado seed tea. This investigation was arranged at the Integrated Lab of Politeknik Indonesia Venezuela and the Laboratory of Banda Aceh Industrial Research and Standardization Center. The experimentation adopted a factorial completely randomized design pattern composed of 2 (two) parameters. The first parameter was avocado seed drying temperature comprising 3 (three) degrees, they were S1 (50°C), S2 (60°C), and S3 (70°C). The second parameter represented the drying time of avocado seeds which comprised 3 (three) degrees, they were L1 (2 hours), L2 (2.5 hours), and L3 (3 hours). Analysis carried out in the research was water, ash value, phenolic content, antioxidant, and sensory (colour, taste, and flavour). From the research, it was shown that the drying temperature was influenced by the moisture content, ash content, and antioxidant activity of avocado seed tea, while the drying time and the treatments of those parameters made an impact on total phenol. The best quality avocado seed tea was obtained from a drying temperature of 50°C along with a length of drying of 2 hours.