Miracle-dz/UniFAR-FTUs huggingface dataset:
Coherent motions in the outer region of turbulent boundary layers

The technique of simultaneous hot‐wire anemometry and flow visualization has been used to determine the average characteristics of two important scales of motion in the outer region of turbulent boundary layers: large scale motions (average length 1.6δ), and ’’typical eddy’’ motions (average streamwise length approximately 200 ν/u τ). Results showed that the Reynolds number dependent ’’typical eddies’’ produced most of the Reynolds stress in the outer half of the layer at R ϑ≈1200, and that they are formed on the upstream side of large scale motions at all Reynolds numbers investigated. This phase relationship explains the scaling of the frequency of occurrence of outer layer bursts (which are identified with ’’typical eddies’’) on the free stream velocity and overall boundary layer thickness, although it is found that the lengths of the ’’typical eddies’’ scale on inner layer variables. In the log region, roughly one‐half of the large scale motions sampled had zone‐averaged streamwise velocity defects. Ensemble averaged results showed that they were associated with significant Reynolds stress contributions. A structural model showing the phase relationship of ’’typical eddies’’ and large scale motions is presented.
Think Inside the Box: Investigating the Consequences of Everyday Physical Opt-Out Strategies for Mindful Smartphone Use

Absent-minded smartphone use has become a catalyst for digital stress. It is often triggered by the mere presence of the device itself, inciting physical opt-out solutions with potentially severe drawbacks. Consequently, there is a need to explore the design dimensions and entailing limitations of physical opt-out methods, especially for everyday use. Informed through expert interviews and online questionnaires, we designed a proof of concept prototype that creates a physical barrier between users and their smartphones while maintaining ease of access. We evaluated our prototype concept in a two-week in-the-wild study, surfacing known benefits of physical opt-out strategies, such as encouraging reflection and supporting deliberate breaks. Although we reduced absent-minded use for users with a high predisposition, drawbacks such as Fear of Missing Out (FoMO) remain. Our work highlights that finding the appropriate amount of physical separation is essential when designing opt-out strategies for digital wellbeing.
Study of Manifold Geometry using Non-Negative Kernel Graphs.

ENG: Given the increasing amounts of data being measured and recorded, effective dimensionality reduction systems have become necessary for a wide variety of tasks. A dataset can be characterized by its geometrical properties, including its point density, curvature, and dimensionality. In this context, the intrinsic dimension (ID) refers to the minimum number of parameters required to characterize a dataset. Many tools have been proposed for the estimation of ID, and the ones that achieve the best results are narrowly focused on solving this goal. These highly specialized estimators don’t allow for the interpretation of the local geometry of the data in other aspects besides ID. Moreover, methods that do make this possible are not able to estimate ID reliably. We propose the use of non-negative kernel (NNK) graphs, an approach to graph construction that characterizes the local geometry of the data, to study the dimension and shape of data manifolds at multiple scales. We propose the use of a series of properties related to NNK graphs to gain insight into manifold datasets. In particular, we look at the number of neighbors in an NNK graph, the dimension of the low-rank approximations for both K -nearest neighbor (KNN) and NNK graphs, the diameter of the polytopes defined by NNK graphs, and the principal angles between the low-rank approximations of NNK graphs. Moreover, we study these properties at multiple scales using an algorithm that makes data sparse by merging points based on a choice of similarity. By using similarity based on local NNK neighborhoods we can subsample datasets preserving the geometrical properties of the initial dataset.
Monthly Electricity Generatıon Forecast in Solar Power Plants with LSTM 1

Today, with the intensive use of electrical devices, the need for electricity has increased. Fossil fuels are generally used to meet this need. However, considering the damage caused by fossil fuels to the environment, governments make various incentives for renewable energy sources. The incentives of countries for solar power plants are quite large. Recently, there are many investors who want to build solar power plants. The sunshine duration of our country is quite high. And the fact that the climatic conditions are efficient for the generation of electricity attracts many investors. However, the installation of these power plants is quite costly. It is possible to predict the amortization periods of these costs with the ever-developing artificial intelligence technology. In this study, the energy data to be produced in the future is estimated by using real solar power plant data with machine learning algorithms. Data, take from solar power plants owned by Humartaş Energy company. In the study, predictions and analyses were made using the LSTM (Long Short-Term Memory) method, which is one of the artificial neural networks. The error rate of the study between 1% and 15%. It is foreseen that studies will also be implemented with other renewable energy sources such as wind, geothermal, hydraulic energy data in the coming stages.
Charging times for dust particles in plasma

The charging time for grains of micrometre size is studied theoretically with some selected parameters to match the environment of space plasmas. Two models are considered: when the grain is isolated and when the grain density increases so that the spherical capacitor model and consequently the intersection of the grain Debye spheres is applied. The analysis shows that for both models the charging time is a strong function of plasma electron temperature. The proximity of the neighbouring grains has an effect on both the grain capacitance and the potential difference due to the depletion of the electron population in the plasma. There is one value for the characteristic grain separation at which the charging time is the same for selected values of the grain charge, and there is also an inversion point at a certain value of the grain charge.
Asymmetry in Okun’s Law Revisited: New evidence on cyclical unemployment–cyclical output trade-oﬀ in the Free State Province using NARDL model.

Since 1994, the ineffectiveness of adopted pro-growth policies to reduce the persistently high unemployment rate in the Free State (FS) province has become a conundrum for policymakers, begging the questions: Is Okun’s law that predicts an inverse unemployment-output relationship exists in the FS province? If so, what is the nature of Okun’s relationship? This paper re-examines the asymmetric unemployment–output tradeoff employing the nonlinear autoregressive distributed lag (NARDL) modelling framework. Cyclical components of unemployment and output are generated from annual data covering the period 1994-2019, using Hodrick-Prescott and Corbae-Ouliaris filters. We controlled for structural breaks and performed a sensitivity analysis on the models estimated. Irrespective of the filtering method, our results confirm asymmetric Okun’s relationship among variables in both the long-and-short run. The negative and statistically significant coefficient on changes of the positive cyclical output reveals that a 1% rise in cyclical output could lower cyclical unemployment between –0.87 to – 0.70 percentage points, reliant on a sustained economic expansion. Estimated long-run coefficients of changes in the positive cyclical output show that an economic upswing between 1.88% and 2.03% would lower unemployment by 1%, in the FS province, consistent with the accepted 2:1 ratio for Okun’s law in the empirical literature. We also find significant contemporaneous effects of changes in cyclical output on cyclical unemployment, where a 1% increase (decrease) in one-period lagged positive (negative) cyclical output reduces (increases) cyclical unemployment between –0.52 and –0.41 (+0.99 and +0.56) percentages points. The detection of these asymmetries explains the failure of the enacted policies to successfully reduce the prevalent high unemployment rate in the FS province. Based on these findings, some apt remedial actions are suggested to policymakers.
Robust Estimation of Mean Squared Error of Small Area Estimators

Abstract A well-known model, due to Fay and Herriot, for estimating small area (domain) means, μ i , is considered. Given μ i 's, it is assumed that the survey estimators, y i , are independent with means μ i and known variances Di, i = 1, …, t. Further, the μ i 's are assumed to be independent with means x′iβ and unknown variance A, where x i is a vector of benchmark variables related to μ i and β is a vector of regression parameters. An empirical best linear unbiased prediction (EBLUP) estimator or an empirical linear Bayes estimator, t i (Â, y), of μ i is obtained. It is shown that an estimator of mean squared error (MSE) of t t (Â, y), derived by Prasad and Rao under normality of μ i and y i given μ i , is robust with respect to nonnormality of the μ i 's. Specifically, it is shown that the Prasad–Rao estimator of MSE is correct to terms of order O(t −1) for large t, assuming only certain moment conditions on the μ i 's and normally distributed survey errors. Results of a simulation study on the accur.
Snow cover variability and change in mountainous regions of Bulgaria, 1931-2000

An investigation of change in snow cover (maximum depth and snow cover duration) over the 1931-2000 period was carried out at sixteen climate stations located in mountainous areas of Bulgaria. The mountain climate has been characterized by widespread warming and decreased winter precipitation over this period. However, there was no evidence of similar large-scale reductions in snow depth or snow cover duration: some sites showed significant decreases in snow cover, some no change, while others showed significant increases. Further analysis is required to understand the reasons for the varied response of snow cover to a changing climate.
Polycrystalline silicon carbide films deposited by low‐power radio‐frequency plasma decomposition of SiF4‐CF4‐H2 gas mixtures

Polycrystalline silicon carbide thin films have been deposited on amorphous substrates by radio‐frequency plasma‐assisted decomposition of tetrafluoro silane, tetrafluoro methane, and hydrogen gas mixtures using low‐power density and deposition temperatures. The material is shown to possess the α‐SiC structure using transmission electron microscopy. It has highly visible transmittance and exhibits bands due to silicon carbide as well as fluorine bonded to carbon and silicon in the infrared transmission spectra. It is easily doped, both types showing high conductivity (∼10 S/cm) and Hall mobility [∼10 cm2/(V s)] for either carrier type. The conductivity is seen to be independent of thickness down to ∼10 nm when deposited on glass. This behavior and the dependence of both structural and electronic properties on deposition parameters is discussed in terms of the chemical reactions in gas phase and on the growth surface.
Big-Bang nucleosynthesis with updated nuclear data

Primordial nucleosynthesis is one of the three evidences for the Big-Bang model together with the expansion of the Universe and the Cosmic Microwave Background. There is a good global agreement over a range of nine orders of magnitude between abundances of 4He, D, 3He and 7Li deduced from observations and calculated primordial nucleosynthesis. This comparison was used to determine the baryonic density of the Universe. For this purpose, it is now superseded by the analysis of the Cosmic Microwave Background (CMB) radiation anisotropies. Big-Bang nucleosynthesis remains, nevertheless, a valuable tool to probe the physics of the early Universe. However, the yet unexplained, discrepancy between the calculated and observed lithium primordial abundances, has not been reduced, neither by recent nuclear physics experiments, nor by new observations.
Vorticity, Momentum and Divergence Budgets of Synoptic-Scale Wave Disturbances in the Tropical Eastern Atlantic

Abstract The budgets of vorticity, momentum and divergence are evaluated for the average synoptic-scale wave composited by Thompson et al. (1979) from Phase III data of the GARP Atlantic Tropical Experiment (GATE). The data are analyzed into a Phase III mean component and a time-varying wave component. The geopotential field which is required for the momentum and divergence budgets is obtained from vertical integration of the hydrostatic equation. It is found that nonlinear terms in all wave budgets tend to be small, so that the disturbances are governed by linear dynamics. In contrast with the composite wave analyzed by Shapiro (1978), the waves are not approximately advected by the horizontal wind. Accelerations have the same amplitude as the Coriolis force in the momentum balances of the disturbances, indicating that the disturbances are not quasi-geostrophic. However, thermal wind balance appears to be a good approximation for the mean zonal wind. None of the usual simplifications to the divergence eq.
Journal of Quantitative Analysis in Sports Using Tree Ensembles to Analyze National Baseball Hall of Fame Voting Patterns : An Application to Discrimination in BBWAA Voting

We predict the induction of Major League Baseball hitters and pitchers into the National Baseball Hall of Fame by the Baseball Writers’ Association of America. We employ a Random Forest algorithm for binary classification, improving upon past models with a simplistic input approach. Our results suggest that the random forest technique is a fruitful line of research with prediction in the sports world. We find an error rate as low as 0.91% in our most accurate forest, with no out-of-bag Error higher than 2.6% in any tree ensemble. We extend the results to an examination of the possibility of discrimination with respect to BBWAA voting, finding little evidence for exclusions based on race.
Artificial Intelligence-Assisted Meta-Analysis of the Frequency of ACE I/D Polymorphisms in Centenarians and Other Long-Lived Individuals

Current research on the angiotensin-converting-enzyme (ACE) gene has yielded controversial results on whether different ACE polymorphisms are linked with human longevity. ACE polymorphisms are a risk factor for Alzheimer's disease and age-onset diseases that may contribute to the mortality of older people. Our goal is to consolidate existing studies with assistance from artificial intelligence and machine-learning-assisted software to come to a more precise understanding of the role of the ACE gene in human longevity. The I (insertion) and D (deletion) polymorphisms in the intron are correlated with the levels of circulating ACE; homozygous D (DD) is high and homozygous I (II) is low. Here, we performed a detailed meta-analysis of the I and D polymorphisms using centenarians (100+ years old), long-lived subjects (85+ years old), and control groups. ACE genotype distribution was analyzed across a total of 2,054 centenarians and 12,074 controls, as well as 1,367 long-lived subjects between the ages of 85-99, using the inverse variance and random effects methods. The ACE DD genotype was found to be favored in centenarians (OR: 1.41 [95% CI: 1.19-1.67], P < 0.0001) with a heterogeneity of 32%, and the II genotype slightly favored the control groups (OR: 0.81 [95% CI: 0.66-0.98], P = 0.03) with a heterogeneity of 28%, corroborating results from previous meta-analyses. Novel to our meta-analysis, the ID genotype was found to be favored in control groups (OR: 0.86 [95% CI: 0.76-0.97], P = 0.01) with a heterogeneity of 0%. The long-lived group showed a similar positive association between the DD genotype and longevity (OR: 1.34 [95% CI: 1.21-1.48, P < 0.0001) and a negative association between the II genotype and longevity (OR: 0.79 [95% CI: 0.70-0.88], P < 0.0001). The long-lived ID genotype did not show significant findings (OR: 0.93 [95% CI: 0.84-1.02], P = 0.79). In conclusion, the results suggest a significant positive association of the DD genotype with human longevity. However, despite the previous study, the results do not confirm a positive association of the ID genotype with human longevity. We suggest a few paradoxical observations: (1) inhibition of ACE can increase longevity in model systems from nematodes to mammals, seemingly opposite to the finding in humans; (2) exceptional longevity associated with homozygous DD is also associated age-related diseases with higher mortality risks in homozygous DD. We discuss ACE, longevity, and age-related diseases.
ENTROPY SCALING IN ION–ION COLLISIONS AT AGS AND SPS ENERGIES

Analysis of the experimental data on nucleus–nucleus collisions at AGS and SPS energies reveals that entropy produced in a limited and full phase-space increases with increasing beam energy and mass of the colliding nuclei. The analysis of the data and corresponding mixed event samples, carried out by considering the particles emitted in the forward and backward hemispheres separately, indicates the presence of clusterization and correlations amongst the produced particles. It is also observed that the total entropy produced in a limited pseudorapidity bin, when normalized to the maximum rapidity in the center of mass frame, is essentially independent of projectile and target masses as well as beam energy, indicating thereby presence of a kind of entropy scaling. The observed scaling is also nicely reproduced by the Monte Carlo models, AMPT and FRITIOF. Furthermore, results of the analysis of the mixed events reveal that the observed entropy scaling is a distinguishable feature of the data rather than a manifestation of the statistics.
EGFR-Targeted Cellular Delivery of Therapeutic Nucleic Acids Mediated by Boron Clusters

New boron carriers with high boron content and targeted cancer-cell delivery are considered the first choice for boron neutron capture therapy (BNCT) for cancer treatment. Previously, we have shown that composites of antisense oligonucleotide and boron clusters are functional nanoparticles for the downregulation of expression of epidermal growth factor receptor (EGFR) and can be loaded into EGFR-overexpressing cancer cells without a transfection factor. In this study, we hypothesize that free cellular uptake is mediated by binding and activation of the EGFR by boron clusters. Proteomic analysis of proteins pulled-down from various EGFR-overexpressing cancer cells using short oligonucleotide probes, conjugated to 1,2-dicarba-closo-dodecaborane (1,2-DCDDB, [C2B10H12]) and [(3,3′-Iron-1,2,1′,2′-dicarbollide)−] (FESAN, [Fe(C2B9H11)2]−), evidenced that boron cage binds to EGFR subdomains. Moreover, inductively coupled plasma mass spectrometry (ICP MS) and fluorescence microscopy analyses confirmed that FESANs-highly decorated B-ASOs were efficiently delivered and internalized by EGFR-overexpressing cells. Antisense reduction of EGFR in A431 and U87-MG cells resulted in decreased boron accumulation compared to control cells, indicating that cellular uptake of B-ASOs is related to EGFR-dependent internalization. The data obtained suggest that EGFR-mediated cellular uptake of B-ASO represents a novel strategy for cellular delivery of therapeutic nucleic acids (and possibly other medicines) conjugated to boron clusters.
Conventional vs. Drug-Eluting Beads Transarterial Chemoembolization for Unresectable Hepatocellular Carcinoma—A Propensity Score Weighted Comparison of Efficacy and Safety

Simple Summary Transarterial chemoembolization (TACE) is a guideline-approved, minimally invasive therapy for unresectable hepatocellular carcinoma (HCC). This study investigated the efficacy and safety of two frequently performed types of TACE that are currently used interchangeably. The statistical method of propensity score weighting was used to reduce bias in the results based on baseline differences and make the groups as comparable as possible. In a large cohort of 370 HCC patients, no significant difference in overall survival was observed between the two TACE groups and adverse advents occurred with similar frequency in both groups. However, conventional TACE showed superior efficacy in patients with infiltrative disease, whereas drug-eluting beads TACE was more effective in nodular tumors. These findings suggest that tumor morphology and distribution on baseline imaging can inform decisions on the type of TACE that the individual patient would benefit from the most. Abstract This study compared the efficacy and safety of conventional transarterial chemoembolization (cTACE) with drug-eluting beads (DEB)-TACE in patients with unresectable hepatocellular carcinoma (HCC). This retrospective analysis included 370 patients with HCC treated with cTACE (n = 248) or DEB-TACE (n = 122) (January 2000–July 2014). Overall survival (OS) was assessed using uni- and multivariate Cox proportional hazards models and Kaplan-Meier analysis. Additionally, baseline imaging was assessed, and clinical and laboratory toxicities were recorded. Propensity score weighting via a generalized boosted model was applied to account for group heterogeneity. There was no significant difference in OS between cTACE (20 months) and DEB-TACE patients (24.3 months, ratio 1.271, 95% confidence interval 0.876–1.69; p = 0.392). However, in patients with infiltrative disease, cTACE achieved longer OS (25.1 months) compared to DEB-TACE (9.2 months, ratio 0.366, 0.191–0.702; p = 0.003), whereas DEB-TACE proved more effective in nodular disease (39.4 months) than cTACE (18 months, ratio 0.458, 0.308–0681; p = 0.007). Adverse events occurred with similar frequency, except for abdominal pain, which was observed more frequently after DEB-TACE (101/116; 87.1%) than cTACE (119/157; 75.8%; p = 0.02). In conclusion, these findings suggest that tumor morphology and distribution should be used as parameters to inform decisions on the selection of embolic materials for TACE for a more personalized treatment planning in patients with unresectable HCC.
Hydrogeochemical Response of Cave Drips to Precipitation during Rainfall in a Karst Desertification Region: A Case Study of Shijiangjun Cave, South China

Exploring the hydrogeochemistry of cave drip water and its response to precipitation events in karst rocky desertification regions is of great significance to the paleoenvironment reconstruction of the karst desertification process using speleothem. We selected three perennial drip sites in the Shijiangjun Cave, located in Guizhou Province, Southwest China, and carried out high-frequency monitoring and sampling during two rainfalls from 22 to 25 May 2016. The major hydrogeochemical parameters of drip water and their relationships with karst desertification were analyzed. The results show that the hydrogeochemistry of the drip water in the Shijiangjun Cave, characterized by HCO3-Ca·Mg, was dominated by the dissolution of calcareous dolomite. The three drip sites were classified into the delayed response type (W1) and the rapid response type (W2 and W3) based on the response speed of the drip water indicators to precipitation, which were highly influenced by the piston effect and precipitation dilution, respectively. Furthermore, the response sensitivity of the drip water indicators to precipitation was constrained by the desertification degree in the rainy season, specifically, the faster response appeared in the higher desertification degree area. It is essential to select appropriate drip sites and establish an applicable indicator system for the evolutional history reconstruction of karst desertification using speleothems.