Miracle-dz/UniFAR-FTUs huggingface dataset:
Brent Crude Oil Price Forecast Utilizing Deep Neural Network Architectures

Brent crude oil is considered as one of the most important sources of crude oil pricing in the worldwide market, and it is used to set the price of two-thirds of the traded crude oil supplies in the world. To predict the price of Brent crude oil, LSTM and Bi-LSTM methods are applied, which are the architecture of the recursive neural network. Initially, the database creates the appropriate data for the period January 2015 to March 2021 from Brent crude oil price signals and daily data from a financial market, and then, the modeling process is performed via the use of MATLAB software. Also, about 90% of the data are for training and the remaining for validation and comparison. Using LSTM and Bi-LSTM neural networks, the network architecture has been worked on, and by adding the number of layers and changing the solvers (SGDM, RMSProp, and Adam), the errors of different models are compared with each other. Nonlinear techniques of artificial neural networks and deep learning were used for modeling. Then, the network architecture was worked on and the model error rate was evaluated by comparing different layers and solvents such as SGDM, RMSProp, and Adam. The superiority of SGDM solvent over others was shown, and finally, it can be mentioned as the superior method of modeling of price forecasting in Brent crude oil field. The results show that the model with two layers of LSTM and SGDM solver has less error and better accuracy.
Measuring Organizational Attractiveness

The war for talent has returned after the Covid pandemic. One way for organizations to win this war is by becoming more attractive than other organizations on the labor market. Previous research has shown that by becoming a high performance organization (HPO), an organization will be seen as ‘a winning team’ for which people like to work. This research evaluates whether organizational attractiveness can be measured by the objective ‘average bottleneck vacancies fulfillment time’ measurement, which measures the time between posting a vacancy on the job market and fulfilling that vacancy. In preparation for a webinar, organized by the Flemish Department of Employment on the attractiveness of organizations, registered respondents were send a survey with which they could indicate the high-performance level of their organization and how long it took for their organization to fulfill its bottleneck vacancies. With a statistical analysis the data was processed to evaluate whether a relationship could be found between the two variables. The research results show that there exists a linear and positive relationship between being an HPO and the time it takes for such a company to fulfill its bottleneck vacancies: increasing the high-performance level of a Flemish for-profit company organization decreases the time it takes to fulfill its bottleneck vacancies.
Trends in K-12 Teacher Agency Research: A Review of Science Education Research

ABSTRACT In-service teachers of science work with unique content and pedagogical experiences within a changing educational landscape. Understanding teacher agency in these circumstances will help researchers understand the actions that these teachers take. The purpose of this meta-analysis was to review how the agency of K-12 in-service teachers of science has been examined empirically in the science education research literature during the period of 2007–2020. Informed by grounded theory, we qualitatively analyzed 48 peer-reviewed articles, which we located using specific search criteria. We identified that science teacher agency is currently conceptualized largely paper-to-paper and without fully attending to the professional and lived experiences, and thus humanity, of science teachers; thereby, creating exciting opportunities for science education researchers to expand on both the breadth and depth around the theorization and operationalization of in-service science teacher agency. Recommendations are addressed.
Statistical analysis of possible trends for extreme floods in northern Sweden

With ongoing climate change, analysis of trends in maximum annual daily river flow is of interest. Flow magnitude and timing during the year were investigated in this study. Observations from 11 unregulated rivers in northern Sweden were analysed, using extreme‐value distributions with time‐dependent parameters. The Mann–Kendall test was used to investigate possible trends. The extreme‐value statistics revealed no significant trends for the stations considered, but the Mann–Kendall test showed a significant upward trend for some stations. For timing of maximum flow (day of the year), the Mann–Kendall test revealed significant downward trends for two stations (with the longest records). This implies that the day of the maximum flow is occurring earlier in the year in northern Sweden.
Accounting for variability in the truth-evaluation of bare epistemic possibility statement

It is hotly debated whose perspective is relevant for defining the truth-value of bare epistemic possibility statements: the utterer or the assessor. Central to this debate are findings on truth-value judgments of ‘might p’ statements in “eavesdropping” scenarios where the statement is appropriately asserted from the point of view of the speaker but does not correspond to how in reality things are. We offer findings from two studies suggesting that in these scenarios English speakers disagree on the truth-value not only of ‘might p’ but also, surprisingly, of bare ‘p’. We argue that underlying this behavior is not a disagreement on the semantic content of the statements but a disagreement on how to interpret the meaning of the adjectives ‘true’ and ‘false’ when applied to a statement uttered by another agent. Specifically, we compare two potential accounts: the first account ascribes to the adjective ‘true’ an ambiguity between a ‘coherent’ sense – a statement uttered by A is true as long as the statement coheres with A’s evidence – and a ‘correspondentist’ sense - a statement as uttered by A is true as long as the statement correspond to reality; the second account treats ‘true’ as having only the correspondentist sense but ascribes to it an inherent relative nature – to decide if a statement as uttered by A is true one has to first decide a perspective (A or the assessor). Lastly, we discuss the implications of the findings for the semantics of epistemic ‘might p’ statements.
Intake of corn stover botanical parts by growing and finishing beef steers

Abstract Single-pass corn stover harvest is a method whereby combine harvester tailings consisting of cob, stalk, leaf, husk, and tassel fractions are collected and baled without coming into contact with soil. The objective was to feed beef steers diets that included a roughage component consisting of harvested corn residue in chopped form from conventional corn stover bales (CST) or single-pass bales (SPB) to assess intake selectivity of corn stover fractions and estimate net energy values of these corn stovers. Whole plant corn silage served as the control roughage in the control diet (CSIL). Steers (n = 90, 5 pens per treatment) were fed during Grow (84 d) and Finish (66 d) trials. Steers sorted through corn stover during both trials and consumed 52.5% of corn stover offered and 40% of cob offered. Intake of SPB cob was 2.6-fold and 3.3-fold greater than CST cob intake (P < 0.01) in Grow and Finish trials, respectively, indicating that when more cob was available, cattle consumed more. During the Grow trial, stover intake tended (P = 0.07) to be lower for SPB and diet dry matter intake (DMI) was less (P ≤ 0.05) for SPB, which may be due to the elevated cob intake by SPB steers. Across treatments, stover DMI was similar in the Grow (1.10 kg per steer per d) and Finish (1.11 kg per steer per d) trials. The proportion (65%) of Fines (<8 mm) consumed from the Grow diet (40% neutral detergent fiber, aNDF) was greater than the Finish diet (25% aNDF; 18% to 31%) and gleaning of concentrate feeds from orts seemed to be more extensive in the Grow diet. Steers consuming Finish diets containing SPB and CST had DMI that were 17% and 18%, respectively, greater (P ≤ 0.05) than CSIL, an indication of compensatory intake. The physical effectiveness factors for stovers fed in the Grow and Finish diets were 0.85 and 0.95, respectively. Estimates for net energy maintenance and net energy gain (NEg), respectively, using National Research Council methods from 2001 were as follows for consumed stovers: SPB (1.09 and 0.54 Mcal/kg) and CST (0.98 and 0.44 Mcal/kg) in the Grow trial, and SPB (0.96 and 0.42 Mcal/kg) and CST (0.95 and 0.40 Mcal/kg) in the Finish trial. Although SPB and CST differ in botanical fraction composition and net intakes of botanical fractions, their energetic contributions to steer performance were very similar. Steers fed the Finish diet (1.25 Mcal performance-adjusted NEg per kg) selected stover botanical components to achieve a diet composition of 25% aNDF.
Occurrence of rice blast disease caused by Magnaporthe oryzae B.Cauch in Jigawa State, Nigeria

The aim of this research was to determine the presence of rice blast disease in the three major rice producing Local Government Areas of Jigawa state (Hadejia, Kaugama and Auyo) in 2020 (Rainy and Dry seasons) with the object of determining the incidence; distribution and severity of the disease. The survey was conducted two times; rainy season and dry season during which at least fifty one (51) rice fields (replicated two times) and selected purposively, were surveyed in each season for blast symptoms. Results of the survey have shown that the disease occurred at varying disease incidences (%) and severities. The disease symptoms appeared more on rice cultivated in Kaugama (16.3%) than in both Auyo (12.6%) and Hadejia (12.5%) Local Government Areas and more in the dry season than in the rainy season thus indicating a significant difference (p<0.05) in the study areas and across the seasons. However, careful observation on the agronomic practices in the three study areas have shown that about 50 % of the fields surveyed in Kaugama were weedy, poorly fertilized, waterlogged and with other disease symptoms such as blight and spots. This might have been the reason for the relatively higher incidence and severity of the disease in Kaugama rice fields. Farmers should be informed of the danger of abandoning rice fields to become bushy as this might cause the disease to escalate to an uncontrollable stage.
Collaboration Handbook Creating Sustaining And Enjoying The Journey

Thank you very much for reading collaboration handbook creating sustaining and enjoying the journey. Maybe you have knowledge that, people have look numerous times for their favorite novels like this collaboration handbook creating sustaining and enjoying the journey, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some harmful bugs inside their computer.
Variability of radon and thoron concentration with type of dwellings in a hilly area

Indoor radon, thoron and progenies are major contributors to the indoor radiation dose which have been measured by our study for different types of dwellings during four seasons of a year. The indoor radon, thoron and progeny levels observed in the present study found to vary with seasons of a year. The average highest radon, thoron and progeny were observed during winter and the corresponding lowest values were observed during summer. The highest 222Rn, 220Rn and progenies concentrations were observed in mud houses and the lowest values were recorded in wooden houses. A good correlation with a correlation coefficient of 0.85 was observed between indoor 222Rn and concentration of its grandparent 238U in underlying soil. A moderate correlation was found between 220Rn and 232Th concentration in underlying soil. The effective dose received by the general public in the present study due to radon and thoron was estimated as 1.43 and 1.13 mSv y−1, respectively. The 222Rn and 220Rn progenies contribute 0.79 and 0.25 mSv y−1, respectively to the annual effective dose received. The inhalation dose received by the general public of the study area due to these airborne isotopes 3.69 mSv y−1 is less than the action limit of International Commission of Radiological Protection (ICRP) (2009).
Detection of Change in Body Motion With Background Construction and Silhouette Orientation: Background Subtraction With GMM

Background subtraction techniques have been widely implemented and improvised to obtain a stable background model. The novelty of the proposed work is to generate a stable background model under dynamic changes in the environmental conditions where a) an improved background subtraction algorithm is proposed based on GMM with EM algorithm for computing granulometry and run faster for the generation of a stable background model; b) Detecting the foreground by curvelet based denoising process with improvised semisoft thresholding techniques with morphological operations; c) background maintenance is done by an adaptive algorithm in which the intensity values are mapped to remove the connected components with less than P pixels. The proposed scheme works for the Spatio-temporal motion of the object in both spatial and temporal modes. The experimental outcome for the proposed model results in the accurate shape analysis of the object in motion thereby dipping the complexity
Klotho Supplementation Reverses Renal Dysfunction and Interstitial Fibrosis in Remnant Kidney

Introduction: While recent investigations show that klotho exerts renoprotective actions, it has not been fully addressed whether klotho protein supplementation reverses renal damage. Methods: The impacts of subcutaneous klotho supplementation on rats with subtotal nephrectomy were examined. Animals were divided into 3 groups: group 1 (short remnant [SR]): remnant kidney for 4 weeks, group 2 (long remnant [LR]): remnant kidney for 12 weeks, and group 3 (klotho supplementation [KL]): klotho protein (20 μg/kg/day) supplementation on the remnant kidney. Blood pressure, blood and urine compositions with conventional methods such as enzyme-linked immunosorbent assay and radioimmunoassay, kidney histology, and renal expressions of various genes were analyzed. In vitro studies were also performed to support in vivo findings. Results: Klotho protein supplementation decreased albuminuria (−43%), systolic blood pressure (−16%), fibroblast growth factor (FGF) 23 (−51%) and serum phosphate levels (−19%), renal angiotensin II concentration (−43%), fibrosis index (−70%), renal expressions of collagen I (−55%), and transforming growth factor β (−59%) (p < 0.05 for all). Klotho supplementation enhanced fractional excretion of phosphate (+45%), glomerular filtration rate (+76%), renal expressions of klotho (+148%), superoxide dismutase (+124%), and bone morphogenetic protein (BMP) 7 (+174%) (p < 0.05 for all). Conclusion: Our data indicated that klotho protein supplementation inactivated renal renin-angiotensin system, reducing blood pressure and albuminuria in remnant kidney. Furthermore, exogenous klotho protein supplementation elevated endogenous klotho expression to increase phosphate excretion with resultant reductions in FGF23 and serum phosphate. Finally, klotho supplementation reversed renal dysfunction and fibrosis in association with improved BMP7 in remnant kidney.
Impact of Foliar Application of Zinc and Biofertilizers on Growth of Sorghum (Sorghum bicolor L.)

The field experiment took place in the Crop Research Farm, Department of Agronomy, SHUATS, Prayagraj, during the Kharif season of 2021. (UP), India. The objective of the experiment is to lessen the use of chemical fertilizers by using techniques of integrated nutrient management efficiently without compromising the nutrient availability to the crop, which ultimately reduces the effect of chemicals used in the agroecosystem. The experiment was set up in a Randomized Block Design with ten treatments, including control, replicated thrice using various biofertilizers. viz., Azospirillum species 25 gram/kilogram seeds, Phosphate solubilizing bacteria 25 g/kg seeds and combination of Azospirillum sp. 25 g/kg seeds + PSB 25 g/kg seeds and foliar application of 0.5% zinc at 30, 50 and 30 + 50 days after sowing per hectare. The research revealed that foliar application of zinc 0.5% at 50 DAS along with seed inoculation by Azospirillum sp. 25 g/kg Seeds + PSB 25 g/kg seeds significantly increased the growth parameters of Sorghum viz., plant height (163.31centimeter), dry matter accumulation (92.71 g), No. of Leaves (12.87), absolute growth rate (1.33 g/plant/day), crop growth rate (44.31 g/m2/day) and leaf area (414.67 cm2).
A review for compact model of graphene field-effect transistors

Graphene has attracted enormous interests due to its unique physical, mechanical, and electrical properties. Specially, graphene-based field-effect transistors (FETs) have evolved rapidly and are now considered as an option for conventional silicon devices. As a critical step in the design cycle of modern IC products, compact model refers to the development of models for integrated semiconductor devices for use in circuit simulations. The purpose of this review is to provide a theoretical description of current compact model of graphene field-effect transistors. Special attention is devoted to the charge sheet model, drift-diffusion model, Boltzmann equation, density of states (DOS), and surface-potential-based compact model. Finally, an outlook of this field is briefly discussed.
A frequency tunable double band-stop resonator with voltage control by varactor diodes

In this paper, a frequency tunable double band-stop resonator (BSR) with voltage control by varactor diodes is suggested. It makes use of a half-wavelength shunt stub as its conventional basic structure, which is replaced by the distributed LC block. Taking advantage of the nonlinear relationship between the frequency and electrical length of the distributed LC block, a dual-band device can be designed easily. With two varactor diodes, the stop-band of the resonator can be easily tuned by controlling the electrical length of the resonator structure. The measurement results show the tuning ranges of the two operating frequencies to be 1.82 GHz to 2.03 GHz and 2.81 GHz to 3.03 GHz, respectively. The entire size of the resonator is 10 mm × 11 mm, which is very compact.
Prediction of the post‐failure behavior of rocks: Combining artificial intelligence and acoustic emission sensing

Acoustic emission (AE) reading is among the most common methods for monitoring the behavior of brittle materials such as rock and concrete. This study uses discrete element method (DEM) simulations to explore the correlations between the pre‐failure AE readings with the post‐failure behavior and residual strength of rock masses. The deep learning (DL) method based on long short‐term memory (LSTM) algorithms has been applied to generate predictive models based on the data from DEM simulations of biaxial compression. The dataset has been populated by varying interparticle friction while keeping bond cohesion constant. Various configurations of the LSTM algorithm were evaluated considering different scenarios for input features (strain, stress, and AE energy records) and a range of values for the key hyperparameters. The prime AI models show promising accuracy in predicting residual strength decay with strain based on pre‐failure patterns in AE readings. The results indicate that the pre‐failure AE indeed encapsulates information about the developing failure mechanisms and the post‐failure response in rocks, which can be captured through artificial intelligence.
The relationship between tethered swimming, anaerobic critical velocity, dry-land strength, and swimming performance

ABSTRACT This study aimed to 1) examine the associations between two swim-specific measures of anaerobic performance and dry-land strength-based variables; 2) study the association between the aforementioned variables with swimming performance and its kinematics; 3) analyse sex-induced differences. Twenty-three regional-national swimmers performed five countermovement-jumps and pull-ups, 50-m front crawl, two 30-s tethered-swimming tests at 0 and 1.124 m·s−1 water flow speed. Moreover, 10, 15, 20, and 25-m maximal front crawl were performed to determine anaerobic critical velocity (AnCV). The AnCV was positively correlated with tethered swimming variables in both conditions and dry-land-based variables in both sexes (p < 0.05). Tethered-swimming variables in both conditions were correlated with pull-ups’ average propulsive force in males (p < 0.05). 50-m swimming performance was positively associated with AnCV, tethered-swimming variables, countermovement-jump height, and pull-ups’ average propulsive force for both sexes (p < 0.05). Stroke rate (SR) was positively associated with AnCV in males and females (p < 0.05). Stroke length was correlated with tethered-swimming variables in males (p < 0.05). Except for SR, males presented higher values than females (p < 0.05). Depending on the conditions of their training environment, coaches might use the AnCV and tethered-swimming variables as interchangeable tools for evaluating anaerobic performance.
Is Deep Learning on Tabular Data Enough? An Assessment

—It is critical to select the model that best fits the situation while analyzing the data. Many scholars on classification and regression issues have offered ensemble techniques on tabular data, as well as other approaches to classification and regression problems (Like Boosting and Logistic Model tree ensembles). Furthermore, various deep learning algorithms have recently been implemented on tabular data, with the authors claiming that deep models outperform Boosting and Model tree approaches. On a range of datasets including historical geographical data, this study compares the new deep models (TabNet, NODE, and DNF-net) against the boosting model (XGBoost) to see if they should be regarded a preferred choice for tabular data. We look at how much tweaking and computation they require, as well as how well they perform based on the metrics evaluation and statistical significance test. According to our study, XGBoost outperforms these deep models across all datasets, including the datasets used in the journals that presented the deep models. We further show that, when compared to deep models, XGBoost requires considerably less tweaking. In addition, we can also confirm that a combination of deep models with XGBoost outperforms XGBoost alone on almost all datasets.
Solving for Scalability From Multi-Band to Multi-Rail Core Networks

The internet heavily relies on optical networks to carry an increasingly growing amount of traffic. This paper analyzes and explores different ways and architectures to efficiently scale terrestrial core optical networks. Discussed and reviewed are several means to increase network capacity and their potential to address the anticipated growth. Finally, a full network simulation allows to gauge the merit of the proposed architectures which allow for a seamless transition between wavelength switched and band or fiber switched core networks while gradually benefiting from the increased cost efficiency of the latter.