Miracle-dz/UniFAR-FTUs huggingface dataset:
Accuracy improvements of local GPS coordinates measured with LEA -6 GPS receiver modules by using software techniques

: In this study, a GPS receiver module LEA-6 was deployed to measure the longitude and latitude of a static point on the ground in the open air. These measurement values are stored in 1-dimensional arrays in computer memory. Additionally, a top-grade GPS position recorder called iP90Pro with a very high-level positioning accuracy was employed to be used as a reference for LEA-6 module measurements. Various software techniques such as regression analysis, moving averaging algorithms, (MA), offsetting, and polynomial curve fitting was deployed on the measured raw longitude and latitude values of the LEA-6 module. As a result, the accuracy levels of these values are improved to the levels of the iP90Pro device. A mathematical analysis was carried out and formulas were developed for longitude and latitude values to bring the accuracy levels of a commercial average-grade GPS module to the accuracy levels of a top-grade GPS module.
SUMA PSICOLÓGICA

Introduction: The relationship that socio-familial and non-cognitive variables have on students in regards to their academic performance is a very important element for success in Secondary Education. In this study the influence of non-cognitive variables (academic self-concept, self-efficacy and perceived family affective support) and socio-familial variables (educational level and expectations of each parent) on the academic performance of sec - ondary school students were analysed. Method: Students were grouped according to their accumulated socio-familial risk index (at-risk students, n = 305; not-at-risk students, n = 991). To measure the variables, the scales What do you think of yourself, General Self-Efficacy and Perceived Family Support were used. Socio-family variables were measured with an ad hoc questionnaire, and academic performance with the end-of-course evaluation scores. Results: The receiver operating characteristic curve showed a decrease in students’ academic performance from three or more accumulated risks. Structural Equation Modelling (SEM) was per - formed for each group. The results showed that for at-risk students, academic performance was mainly determined by two variables: academic self-concept and self-concept; in contrast to the not-at-risk students in which self-efficacy was the one that had the greatest effect on performance. In both groups, the parents’ expectations were the family variable with the highest incidence being performance, although, for the at-risk group, the effect was greater. Conclusions: The relevance of the identification of non-cognitive and socio-familial variables on the academic performance of at-risk students in regards to secondary education due to socio-familial factors is discussed.
GOCE and Future Gravity Missions for Geothermal Energy Exploitation

Geothermal energy is a valuable renewable energy source the exploitation of which contributes to the worldwide reduction of consumption of fossil fuels oil and gas. The exploitation of geothermal energy is facilitated where the thermal gradient is higher than average leading to increased surface heat flow. Apart from the hydrologic circulation properties which depend on rock fractures and are important due to the heat transportation from the hotter layers to the surface, essential properties that increase the thermal gradient are crustal thinning and radiogenic heat producing rocks. Crustal thickness and rock composition form the link to the exploration with the satellite derived gravity field, because both induce subsurface mass changes that generate observable gravity anomalies. The recognition of gravity as a useful investigation tool for geothermal energy lead to a cooperation with ESA and the International Renewable Energy Agency (IRENA) that included the GOCE derived gravity field in the online geothermal energy investigation tool of the IRENA database. The relation between the gravity field products as the free air gravity anomaly, the Bouguer and isostatic anomalies and the heat flow values is though not straightforward and has not a unique relationship. It is complicated by the fact that it depends on the geodynamical context, on the geologic context and the age of the crustal rocks. Globally the geological context and geodynamical history of an area is known close to everywhere, so that a specific known relationship between gravity and geothermal potential can be applied. In this study we show the results of a systematic analysis of the problem, including some simulations of the key factors. The study relies on the data of GOCE and the resolution and accuracy of this satellite. We also give conclusions on the improved exploration power of a gravity mission with higher spatial resolution and reduced data error, as could be achieved in principle by flying an atom interferometer sensor on board a satellite.
International Reserves Management and Capital Mobility in a Volatile World: Policy Considerations and a Case Study of Korea

This paper characterizes the precautionary demand for international reserves driven by the attempt to reduce the incidence of costly output decline induced by sudden reversal of short-term capital flows. It validates the main predictions of the precautionary approach by investigating changes in the patterns of international reserves in Korea in the aftermath of the 1997-8 crisis. This crisis provides an interesting case study, especially because of the rapid rise in Korea’s financial integration in the aftermath of the East- Asian crisis, where foreigners’ shareholding has increased to 40% of total Korean market capitalization. We show that the crisis led to structural change in the hoarding of international reserves, and that the Korean monetary authority gives much greater attention to a broader notion of ‘hot money,’ inclusive of short-term debt and foreigners’ shareholding.
Effect of multicomponent aqueous plant extracts on the growth and biochemical composition of Mentha arvensis L. and Centella asiatica L.

: The present study aimed to analyze the effect of different concentrations of aqueous extracts of Tephrosia purpurea, Ipomea carnea, Trianthema portulacastrum, and Tithonia diversifolia on Centella asiatica and Allium cepa , Solanum tuberosum and Calotropis gigantia on Mentha arvensis respectively. Extracts of 5%, 10%, 20% & 50% concentrations were prepared and fertigated by pot experiments. Results of this study showed that extracts of T.purpurea (50%), I. carnea (10% & 20%), T. portulacastrum (10%, 20%& 50%) and T. diversifolia (5% &10%) enhanced the growth of C. asiatica when compared to the control. Calotropis extract ( 15%) enhanced the growth of M. arvensis and lowest growth was recorded in onion peel extract (5%). T. diversifolia extract at lowest concentration (5%&10%) increased the leaf surface area (38.8±0.4cm 2 ), petiole length (17.6±0.6cm) and fresh (120.6±2.0g) & dry weight (52.4±0.5g). Lower concentrations of T. purpurea (5% &10%) and higher concentrations of I. carnea (50%) inhibited the growth, number of leaf, leaf surface area (3.8±0.7cm 2 ), petiole length (2.63±0.3cm) and fresh (10.8±1.7g) & dry weight (3.1±0.7g) in Centella asiatica and Calotropis extract (15% concentration) on M. arvensis increased the number of leaves (57±3), leaf surface area (12.7±0.9 ) , shoot length (39±2 cm 2 ) and total fresh weight (170±1.5g) when compared to the control. Significant reduction existed in all the parameters at higher concentrations of the extracts used
Clínica y Salud

The purpose of this research was to examine the role of fatigue, depression, and personality traits in males with and without multiple sclerosis (MS) and to investigate the influence of age and the numbers of years of education on these constructs. Participants were 30 males with MS and 30 males without MS from Shiraz City, Iran, who were selected following a sampling method. The Fatigue Severity Scale (FSS), the Beck Depression Inventory (BDI), the NEO Personality Inventory-Revised (NEO PI-R)
Phased Diploid Genome Assembly with Single Molecule Real-Time Sequencing

While genome assembly projects have been successful in a number of haploid or inbred species, one of the current main challenges is assembling non-inbred or rearranged heterozygous genomes. To address this critical need, we introduce the open-source FALCON and FALCON-Unzip algorithms (https://github.com/PacificBiosciences/FALCON/) to assemble Single Molecule Real-Time (SMRT®) Sequencing data into highly accurate, contiguous, and correctly phased diploid genomes. We demonstrate the quality of this approach by assembling new reference sequences for three heterozygous samples, including an F1 hybrid of the model species Arabidopsis thaliana, the widely cultivated V. vinifera cv. Cabernet Sauvignon, and the coral fungus Clavicorona pyxidata that have challenged short-read assembly approaches. The FALCON-based assemblies were substantially more contiguous and complete than alternate short or long-read approaches. The phased diploid assembly enabled the study of haplotype structures and heterozygosities between the homologous chromosomes, including identifying widespread heterozygous structural variations within the coding sequences. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi. org/10.1101/056887 doi: bioRxiv preprint first posted online Jun. 3, 2016;
Estimating evapotranspiration from solar radiation

An analysis of water shortages for municipal and industrial, and (project type) irrigation uses is presented. The investigation was undertaken to compile data on water shortages for these uses and to establish general practical guides for use in planning studies by governmental agencies and consulting firms. It is concluded that shortages of any magnitude should not be permitted in studies in which water is to be supplied for municipal and industrial purposes. In regard to irrigation, no firm guides and limitations based entirely on water shortages are recommended. In determining the feasibility of irrigation, economic analyses will be made, on a project by project basis, that will consider reduced crop yields due to water shortages. Desirable limits on water shortages for irrigation in planning work are considered to be as follows: Maximum average annual for 50-yr period, 3%; maximum for a single year, 50%; maximum for two consecutive years (total), 70%; and maximum shortage years, 27%.
E ﬃ cient Passivation and Low Resistivity for p + ‑ Si/TiO 2 Contact by Atomic Layer Deposition

: The monolithic, two-terminal (2-T) perovskite/silicon tandem solar cell is a promising candidate to increase the power conversion e ﬃ ciency beyond the theoretical limit of 29.4% for crystalline silicon solar cells. To achieve a high-e ﬃ ciency 2-T tandem, it is critical to have an interface that can connect the bottom and top subcells together so that both e ﬃ cient passivation and good electrical contact are achieved. The majority of works done to date in this area, applied an intermediate layer as the recombination layer between perovskite and silicon, which incurs higher manufacturing costs and an additional processing step. Here we demonstrate a unique and straightforward interlayer-free approach to passivating highly boron-doped low-resistivity n-Si using a thin layer of TiO 2 fabricated by atomic layer deposition (ALD) and a suitable pretreatment of the silicon surface. The passivation of this ﬁ lm is found to be superior to that of thermally grown SiO 2 formed at high temperatures over 700 ° C. The TiO X layer leads to a su ﬃ ciently low contact resistance of 0.45 Ω · cm 2 and high-quality passivation with a recombination current density ( J 0 ) of 152 fA/cm 2 . The structure is applicable to both perovskite/Si tandems and single-junction Si solar cells.
Financial Portfolio And Economic Growth In Colombia. An Error Correction Model Summary

The purpose of this paper is to analyze the relationship between economic growth and Colombian financial portfolio quality institutions during the second decade of the 21st century for forecasting purposes, by means of an econometric error correction model using quarterly information for the period between 2011-I and 2020-III, both of gross domestic product and of the gross and past-due portfolio of financial institutions. The estimation of the model was executed using the econometric program Eviews 10 with the intervention of two variables. The first one consists of the seasonally natural logarithm adjusted gross domestic product [LPIBD] and the second corresponds to the portfolio quality indicator defined as the ratio of the past-due portfolio to the gross portfolio [INCALID]. The results reveal that the variables are integrated of order 1 and are co-integrated, making it possible to estimate the model with three lags, which added to the unidirectional causality in the Granger sense, allowed predicting the portfolio quality of financial institutions for the fourth quarter of 2020 and establishing the short-and long-term dynamics.
An evolutionary explanation of the value premium puzzle

As early as 1934 Graham and Dodd conjectured that excess returns from value investment originate from a tendency of stock prices to converge towards a fundamental value. This paper confirms their insights within the evolutionary finance model of Evstigneev et al. (Econ Theory 27:449–468, (Evstigneev et al. 2006)). Our empirical results show the predictive power of the evolutionary benchmark valuation for the relative market capitalization and its dynamics in the sample of firms listed in the Dow Jones Industrial Average index in 1981–2009.
Benchmarking Distribution Shift in Tabular Data with TableShift

Robustness to distribution shift has become a growing concern for text and image models as they transition from research subjects to deployment in the real world. However, high-quality benchmarks for distribution shift in tabular machine learning tasks are still lacking despite the widespread real-world use of tabular data and differences in the models used for tabular data in comparison to text and images. As a consequence, the robustness of tabular models to distribution shift is poorly understood. To address this issue, we introduce TableShift, a distribution shift benchmark for tabular data. TableShift contains 15 binary classification tasks in total, each with an associated shift, and includes a diverse set of data sources, prediction targets, and distribution shifts. The benchmark covers domains including finance, education, public policy, healthcare, and civic participation, and is accessible using only a few lines of Python code via the TableShift API. We conduct a large-scale study comparing several state-of-the-art tabular data models alongside robust learning and domain generalization methods on the benchmark tasks. Our study demonstrates (1) a linear trend between in-distribution (ID) and out-of-distribution (OOD) accuracy; (2) domain robustness methods can reduce shift gaps but at the cost of reduced ID accuracy; (3) a strong relationship between shift gap (difference between ID and OOD performance) and shifts in the label distribution. The benchmark data, Python package, model implementations, and more information about TableShift are available at https://github.com/mlfoundations/tableshift and https://tableshift.org .
Comparative efficacy of PG and Ovaprim in Induced Breeding of Kalibaus ( Labeo calbasu ) for Conservation and Aquaculture

: A field and laboratory experiment on comparative efficacy of two inducing hormones (PG and Ovaprim) were conducted on induced breeding of endangered Kalibaus ( Labeo calbasu ). Three breeding trails were accomplished for each of the inducing hormone. The average weight of brood fish was 1518.47±129.28 g and sex ratio were maintained 1:1 for the breeding purpose. Four female fishes for each treatment were given initial doses of 1 mg, 1 mg and 2 mg with resolving doses of 4 mg, 6 mg and 7 mg of PG extract per kg body weight respectively as T , T and T . On the other hand, four female fishes for each treatment were given doses 1 2 3 of 0.4 ml, 0.5 ml and 0.6 ml of Ovaprim per kg body weight as T , T and T . In case of T , T and T . four male 4
Examining Empowering Leadership's Impact on Trust and Employee Voice Behavior: A PLS SEM Model Analysis

The purpose of the study is to determine the influence of supportive leadership, voice behavior of supervisor on voice behavior of employees on in Pharmaceutical industry of Pakistan. Moreover, second objective of this study is to determine the role of trust in supervisor as a mediator between supportive leadership, voice behavior of supervisor and voice behavior of employee. The data was collected through survey questionnaire by spreading among employees working at pharmaceutical companies in Karachi, Pakistan. Total 180 sample data was analyzed and that delivered statistical results of developed hypotheses by observing previous studies. SPSS and PLS-SEM, statistical technique will use to test the hypotheses. The result found that supportive leadership and perceived voice behavior has positive affect on employee voice behavior. Further, supportive leadership has positive impact on employee voice behavior. In addition, trust in supervision positively mediates the relationship between perceived voice behavior of supervisor, supportive leadership and employee voice behavior.
Metacognitive Pedagogy And Prospective Teachers' Science Identity: An Experimental Study

Metacognitive pedagogies are the classroom instructional strategies facilitating learning. Science identity is a lens for analyzing the motivation and learning of students. Multiple types of research are available on science identity; however, the research on the science identity of prospective teachers' was rarely focused. Therefore, this study was conducted to examine the effect of metacognitive pedagogy on Prospective teachers' science identity. A sample of fifty-eight (58) prospective teachers enrolled in a public sector university participated in this experimental study. The study sample was randomly divided into experimental and control groups based on their previous scientific results. The control group was taught with the traditional teaching method. Further, the treatment group was taught with metacognitive pedagogy using mind maps, small group discussion, and writing reflections for sixteen weeks per the university schedule. Data were collected using a science identity questionnaire. NCSS 2022 was used to analyze the data. The results concluded that metacognitive pedagogy remained significant in the prospective teachers' science identity. It is recommended that prospective teachers be taught metacognitively to enhance their outputs in terms of science identity, which is a significant factor in academic achievements. They may become effective science teachers and build a new generation with a solid scientific background.
: Gifted students’ poetry comics and the crafting of “nerd identities”

This article reports on a study of how a class of fifteen-and sixteen-year-old gifted high school students “mixed” the media of poetry and comics to unveil and interrogate (what they called) their “nerd identities. ” Both co-authors constructed and co-taught a class within a literature-based comics course that led students through various writing processes that focused on the visual and textual properties of poetry and comics. Researchers asked: How may gifted students use poetry and comics to write about identity? How can the mixing of poetry and comics contribute to media literacy education? Using their poetry comics to connect their “nerd identities” to superheroes, students reported seeing parallels between the trials and tribulations of superhero origin stories and their own “gifted” identity.
Generative adversarial networks: Foundations and applications

In statistical signal processing and machine learning, an open issue has been how to obtain a generative model that can produce samples from high-dimensional data distributions such as images and speeches. Generative adversarial networks (GANs) have emerged as a powerful framework that provides clues to solving this problem. A GAN is composed of two networks: a generator that transforms noise variables to data space and a discriminator that discriminates real and generated data. These two networks are optimized using a min-max game: the generator attempts to deceive the discriminator by generating data indistinguishable from the real data, while the discriminator attempts not to be deceived by the generator by finding the best discrimination between real and generated data. This novel framework enables the implicit estimation of a data distribution and enables the generator to generate high-fidelity data that are almost indistinguishable from real data. This beneficial and powerful property has attracted a great deal of attention, and a wide range of research, from basic research to practical applications, has been recently conducted. In this paper, I summarize these studies and explain the foundations and applications of GANs. Specifically, I first clarify the relation between GANs and other deep generative models then provide the theory of GANs with numerical formula. Next, I introduce recent advances in GANs and describe the impressive applications that are highly related to acoustic and speech signal processing. Finally, I conclude this paper by mentioning future directions.
ASSESSMENT OF FEEDING PRACTICES AND PERFORMANCE OF DAIRY CATTLE IN KIBAHA DISTRICT, TANZANIA

Two studies were carried out in Kibaha District to investigate feeding practices and performance of dairy cattle kept by smallholder farmers. In experiment 1, formal survey which aimed at assessing the existing feeding practices, performance and constraints, involved 30 dairy farmers from 3 wards. In experiment 2, twenty four (24) lactating cows from two wards, that is 12 cows from each ward, were monitored for one month where intakes and milk yield were measured. In experiment 1; the performance in terms of reproduction and milk yield of cows under both zero and full grazing, was low during wet and dry seasons. Major constraints identified were nutritional related causes by the existing feeding practices. In experiment 2, the overall percentages of crude protein (CP), in vitro dry matter digestibility (IVDMD), neutral detergent fibre (NDF), calcium (Ca), Phosphorus (P) and overall means of Metabolizable energy (ME MJ) contents of mixed forages under full grazing were 6.18, 48.01, 73.58, 0.25, 0.16 and 6.88, while those under zero grazing were 6.09, 49.08, 74.2, 0.24, 0.18 and 7.02, respectively. The overall daily nutrient intakes (g/ kgW) of zero grazed cows were 120, 7.48, 0.26, 0.21 and 0.86 MJ for DM, CP, Ca, P and ME respectively. The daily milk yield of lactating cows under full grazing and zero grazing systems measured during monitoring experiment were 5.45 and 6.59 l/cow, respectively. Production performance of dairy cattle observed during wet season was suboptimal, probably due to underfeeding attributed by lack of adequate supplementation. It is, therefore proposed to supplement the animals with concentrate that will supply 41.6 MJ, 1012g CP, 38g Ca, and 22g P per cow/ day for optimal milk