Miracle-dz/UniFAR-FTUs huggingface dataset:
ORGANIC AND BIOFERTILIZERS EFFECTS ON THE RHIZOSPHERE MICROBIOME AND SPRING BARLEY PRODUCTIVITY IN NORTHERN KAZAKHSTAN

Organic fertilizers‟ usage enhances crop productivity and improves soil fertility and the surrounding environment in livestock complexes. The presented study assessed the effect of biofertilizers and poultry-based organic fertilizers on rhizospheric microbial diversity, yield attributes, and productivity of spring barley (Hordeum vulgare L.). Conducting field experiments started in 2021 in Northern Kazakhstan's Southern carbonated chernozem of the steppe zone. Poultry manure application had three doses (5, 10, and 15 t ha-1), while four types of biofertilizer of microbial origin consisted of Compo-MIX, Agro-MIX, Agrarka, and Trichodermin-KZ. The poultry-based organic manure resulted in the highest number of nitrogen-fixing bacteria. By treating seeds with biofertilizers, Agrarka and Trichodermin-KZ, the organotrophic bacteria dominated the barley rhizosphere. The seed treatment with Agro-MIX, Trichodermin-KZ, and organic fertilizer (at the rate of 5 and 10 t ha-1) resulted in a predominance of nonsymbiotic nitrogen-fixing bacteria. Combined analysis of variance revealed that, on average, the organic and biofertilizers significantly increased plant viability, 1000-grain weight, and grain productivity. Combined application of poultry manure (10 t ha-1) and biofertilizer Trichodermin- KZ gave the highest average values of grain productivity, i.e., 1,550 and 1,490 kg ha-1 (15.5 and 14.9 quintal ha-1), respectively.
Pythagorean fuzzy analytic hierarchy process to multi-criteria decision making

A numerous approaches have been proposed in the literature to determine the criteria of weight. The weight of criteria is very significant in the process of decision making. One of the outstanding approaches that used to determine weight of criteria is analytic hierarchy process (AHP). This method involves decision makers (DMs) to evaluate the decision to form the pair-wise comparison between criteria and alternatives. In classical AHP, the linguistic variable of pairwise comparison is presented in terms of crisp value. However, this method is not appropriate to present the real situation of the problems because it involved the uncertainty in linguistic judgment. For this reason, AHP has been extended by incorporating the Pythagorean fuzzy sets. In addition, no one has found in the literature proposed how to determine the weight of criteria using AHP under Pythagorean fuzzy sets. In order to solve the MCDM problem, the Pythagorean fuzzy analytic hierarchy process is proposed to determine the criteria weight of the evaluation criteria. Using the linguistic variables, pairwise comparison for evaluation criteria are made to the weights of criteria using Pythagorean fuzzy numbers (PFNs). The proposed method is implemented in the evaluation problem in order to demonstrate its applicability. This study shows that the proposed method provides us with a useful way and a new direction in solving MCDM problems with Pythagorean fuzzy context.A numerous approaches have been proposed in the literature to determine the criteria of weight. The weight of criteria is very significant in the process of decision making. One of the outstanding approaches that used to determine weight of criteria is analytic hierarchy process (AHP). This method involves decision makers (DMs) to evaluate the decision to form the pair-wise comparison between criteria and alternatives. In classical AHP, the linguistic variable of pairwise comparison is presented in terms of crisp value. However, this method is not appropriate to present the real situation of the problems because it involved the uncertainty in linguistic judgment. For this reason, AHP has been extended by incorporating the Pythagorean fuzzy sets. In addition, no one has found in the literature proposed how to determine the weight of criteria using AHP under Pythagorean fuzzy sets. In order to solve the MCDM problem, the Pythagorean fuzzy analytic hierarchy process is proposed to determine the criteria weig.
An inequality for warped product submanifolds of a locally product Riemannian manifold

Recently, Sahin studied the warped product semi-slant submanifolds of locally product Riemannian manifolds. In this paper, we obtain some geometric properties of such submanifolds with an example. Also, we establish a sharp relationship between the squared norm of the second fundamental form and the warping function in terms of the slant angle. The equality case is also considered.
Droplet impact onto moving liquids

From rain drops landing on the ocean to inkjet printing, the impact of droplets onto moving liquid surfaces is a ubiquitous process in nature and in industry. A rich range of phenomena can arise. The behaviour depends on the inertia, the properties of the drops and the relative speeds in the impact zone. While the result ranges from tranquil coalescence to violent splashing, intermediate regimes also occur, including partial and complete bouncing and even ‘surfing’ of the droplet. These regimes are determined by the ratio of the drop and surface velocities and the liquid properties. A regime diagram can be constructed in which distinct dynamical regimes are clearly identified.
Thomas Precession by Uniform Acceleration and Gravity

We determine nonlinear transformations between coordinate systems which are mutually in a constant symmetrical accelerated motion. The maximal acceleration limit follows from the kinematical origin and it is an analogue of the maximal velocity in special relativity. We derive the dependence of mass, length, time, Doppler effect, Cerenkov effect and transition radiation angle on acceleration as an analogue phenomenon in special theory of relativity. The last application of our method is the Thomas precession by uniform acceleration and equivalent gravity with the possible role in modern physics and cosmology.
Spectroscopic and electric dipole properties of Sr+Ar and SrAr systems including high excited states

The spectroscopic properties of the fundamental and several excited states of Sr+Ar and SrAr, Van der Waals systems are investigated by employing an ab initio method in a pseudo-potential approach. The potential energy curves and the spectroscopic parameters are displayed for the 1–10 2Σ+, 1–6 2Π and 1–3 2Δ electronic states of the Sr+Ar molecule and for the 1–6 1Σ+, 1–4 3Σ+, 1–3 1,3Π and 1–3 1,3Δ states of the neutral molecule SrAr. In addition, from these curves, the vibrational levels and their energy spacing are deduced for Σ+, Π and Δ symmetries. The spectra of the permanent and transition dipole moments are studied for the 1,3Σ+ states of SrAr, which are considered to be two-electron systems and 2Σ+ states of the single electron Sr+Ar ion. The spectroscopic parameters obtained for each molecular system are compared with previous theoretical and experimental works. A significant correlation revealed the accuracy of our results.
Adaptive compressed sensing of multi-view videos based on the sparsity estimation

The conventional compressive sensing for videos based on the non-adaptive linear projections, and the measurement times is usually set empirically. As a result, the quality of videos reconstruction is always affected. Firstly, the block-based compressed sensing (BCS) with conventional selection for compressive measurements was described. Then an estimation method for the sparsity of multi-view videos was proposed based on the two dimensional discrete wavelet transform (2D DWT). With an energy threshold given beforehand, the DWT coefficients were processed with both energy normalization and sorting by descending order, and the sparsity of the multi-view video can be achieved by the proportion of dominant coefficients. And finally, the simulation result shows that, the method can estimate the sparsity of video frame effectively, and provides an active basis for the selection of compressive observation times. The result also shows that, since the selection of observation times is based on the sparsity estimated with the energy threshold provided, the proposed method can ensure the reconstruction quality of multi-view videos.
Advances on analysis methods of ginkgo biloba leaf extract

Abstract Ginkgo biloba leaf extract (EGBL) is a valuable herbal extract. The main active ingredients are flavonoids, terpene lactones, organic acids and proanthocyanidins. In recent years, there have been many reports on the detection of the above active ingredients. In this paper, the analysis methods of chemical components in EGBL were reviewed, such as ultraviolet spectrophotometry, high-performance liquid chromatography, and quantitative nuclear magnetic resonance. The analysis methods of ginkgolic acids are also reviewed. Based on the current research progress, three suggestions are provided. Firstly, the quality marker research of EGBL needs to be strengthened. Secondly, more bioassay methods for EGBL quality control should be developed. Thirdly, it is necessary to strengthen the detection of proanthocyanidins in EGBL. GRAPHICAL ABSTRACT
The Model of Good Governance Application Toward Human Resource Management in Buddhist University

Purpose: The aim of this study is to examine a relationship between good governance application and human resource management and propose the model of good governance application for human resource management of Mahamakut Buddhist University. Theoretical framework: Recent literature indicated that good governance application can increase organizational efficiency and effectiveness and help the organization to achieve sustainable growth and development (Burikul, 2003). However, there was a lack of studies that explore how good governance can be applied to improve the processes of human resource management in the university. Design/methodology/approach: We distributed the research questionnaires to 350 employees who work in Mahamakut Buddhist University during May 1, 2021 to June 30, 2021, and received 321 questionnaires. We applied both descriptive and inferential statistics to analyze the collected data. Findings: The results of the study illustrated that good governance application was positively related to human resource management and had an effect on human resource management of Mahamakut Buddhist University. Research, Practical & Social implications: The study indicated that good governance can be implemented in human resource management to gain qualified employees, to improve career advancement, employee satisfaction, life quality of employees, and create organizational justice and sustainable growth of the university. Originality/value: The value of the study is that good governance can improve the processes of human resource management to be transparent, fair, effective and acceptable. An application of good governance leads to sustainable growth and development of the university as a whole.
Feature-Enhanced Deep Learning Network for Digital Elevation Model Super-Resolution

The high-resolution digital elevation model (HR DEM) plays an important role in hydrological analysis, cartographic generalization, and national security. As the main high-precision DEM data supplementary method, DEM super-resolution (DEM SR) based on deep learning has been widely studied. However, its accuracy has fallen into a bottleneck at present, which is more prominent in complex regions. The reason for this issue is that the existing methods are difficult to capture enough local features from the low-resolution input data, and a part of the global information (contour information of long-distance features, such as rivers and ridges) will also be lost in the network transmission process. To resolve this issue, a novel feature-enhanced deep learning network (FEN) is designed in this article. The proposed FEN includes a global feature SR (GFSR) module and a local feature SR (LFSR) module. The former provides global information by using an interpolation method (Kriging), including geographical laws (spatial autocorrelation). The latter fully captures the features in the input data by integrating powerful feature extraction modules and then provides sufficient local features for DEM SR tasks. Thus, DEM SR tasks for complex regions can be realized by integrating the results of GFSR and LFSR modules. Extensive experiments show that FEN achieves state-of-the-art performance in DEM SR tasks facing complex regions. Specifically, compared with the existing DEM SR method (TfaSR, SRResNet, Bicubic, SRCNN, and Kriging), the result by FEN is closer to HR DEM and can retain more local DEM features. Meanwhile, the FEN is more than 20% ahead of other DEM SR methods based on deep learning in elevation accuracy.
Study on the microscopic wear mechanism of nanoparticles sliding stainless steel

In order to reveal the nanoscale friction behavior and wear mechanism of 304 stainless steel during nano particles sliding, this study investigated the effects of sliding velocity and depth on the surface morphology, temperature, mechanical forces, coefficient of friction and sub-surface damage (SSD) of stainless steel by employing molecular dynamics simulations. The results demonstrate that the atoms symmetrically stack on both sides of the sliding grooves during the sliding process. Sliding friction, friction coefficient, defective atoms, phase changing degree and the length of dislocation line increases as the indentation depth of the abrasives, while sliding velocity had little impact on them. Temperature in sliding area and the squeezing effect distinctly increases with the indentation depth the abrasives, which leads more serious damage on the surface of workpiece. The damage layer with a sliding depth of 20 Å can reach about 57.2 Å at a sliding velocity of 100 m s−1, and it has a maximum value of 41.1 Å at a sliding distance of 50 Å. However, increasing sliding velocity can decline the surface SSD layer, which was at a sliding depth of 20 Å. The microscopic atoms evolution presented in the study uncovers the nano-sliding wear mechanism of stainless steel.
Lithium Depletion Boundary Ages of Young Stars: Inconsistencies in Pre-Main Sequence Models

Abstract For proper interpretations of various phenomena in young stars and planetary systems, knowledge of accurate stellar ages is very important. Among a handful of age dating methods commonly used for young (≲500 Myr) stars, lithium depletion boundary (LDB) ages have recently become the most cited and accepted age estimates. However, because of inconsistencies in theoretical evolutionary models, especially for lithium depletion calculations, one has to be cautious in using LDB ages. For a given luminosity, the lithium depletion process is too slow, causing LDB ages to appear older. Various stellar processes affect the surface lithium abundance, and these effects include star spots, accretion history, and magnetic fields. Until we have a self-consistent theoretical evolutionary model for young stars including all relevant stellar effects, caution should be taken when LDB ages are used.
Visualizing Lithium Ion Transport in Solid‐State Li–S Batteries Using 6Li Contrast Enhanced Neutron Imaging

The elucidation of lithium ion transport pathways through a solid electrolyte separator is a vital step toward development of reliable, functional all‐solid‐state batteries. Here, advantage has been taken of the significantly higher neutron attenuation coefficient of one of the most abundant stable isotopes of lithium, 6Li, with respect to that of naturally occurring lithium isotope mixture, to perform neutron imaging on a purpose built all‐solid‐state lithium–sulfur battery. Increasing the 6Li content in the anode while using natural lithium in the solid electrolyte separator and the cathode enhances the contrast such that it is possible to differentiate, during the initial discharge, between the mobile lithium ions diffusing through the cell from the anode and those that are initially located in the solid electrolyte. The sensitivity of neutrons to the different lithium isotopes means that operando neutron radiography allows demonstration of the lithium ion diffusion through the cell while in situ neutron tomography has permitted presentation, in three dimensions, of the distribution of the trapped lithium ions inside the cell in charged and discharged states.
Reliability and Validity of the Turkish Version of Short fom Consumer Need for Uniqueness Scale

Individuals have the desire to differentiate themselves, at least to some extent, from those in their immediate surroundings. This need to stand out from others is often satisfied through the adoption of unique hobbies or by consuming distinct products etc. The concept of “Consumer need for uniqueness” in marketing literature is concerned with the latter form of differentiation, specifically the motivation to consume products that set the individual apart from their peers. In the literature, the concept is measured through scales of varying lengths and types. It is important to examine the validity and reliability of this scales across different cultures, as cultural differences are likely to impact the underlying structure of the concept. In consideration of the benefits of shorter scales, we sought to adapt the short version of the consumer need for uniqueness scale (CNFU-s), developed by Ruvio et al. (2008), to the Turkish context, and to assess its validity and reliability. To that end, we tested the factor structure (via confirmatory factor analysis), construct validity (through relationships with other constructs), and reliability (internal consistency) of the Turkish CNFU-s. Additionally, to examine the relationship between the CNFU-s and other constructs, we investigated the relationship between market mavenism and status consumption, which according to the literature, were expected to have a positive correlation with the CNFU-s (N = 742). The results of the study showed that the factor structure of the Turkish CNFU-s was compatible with the long-original version and the values of fit indices were within acceptable levels. The internal consistency of the CNFU-s was calculated as . 89, indicating that the reliability of the scale was at a satisfactory level. As expected, the CNFU-s was positively associated with market mavenism (r = 0.17) and status consumption (r = 0.23). In conclusion, the Turkish version of the CNFU-s is a measurement tool with evidence to support its psychometric properties and can be utilized in future research studies with Turkish samples.
A New Conceptual Picture of the Trade Wind Transition Layer

The transition layer in the trades has long been observed and simulated, but the physical processes producing its structure remain little investigated. Using extensive observations from the Elucidating the Role of Clouds–Circulation Coupling in Climate (EUREC4A) field campaign, we propose a new conceptual picture of the trade wind transition layer, occurring between the mixed-layer top (around 550 m) and subcloud-layer top (around 700 m). The theory of cloud-free convective boundary layers suggests a transition-layer structure with strong jumps at the mixed-layer top, yet such strong jumps are only observed rarely. Despite cloud-base cloud fraction measured as only 5.3% ± 3.2%, the canonical cloud-free convective boundary layer structure is infrequent and confined to large [O(200) km] cloud-free areas. We show that the majority of cloud bases form within the transition layer, instead of above it, and that the cloud-top height distribution is bimodal, with a first population of very shallow clouds (tops below 1.3 km) and a second population of deeper clouds (extending to 2–3 km depth). We then show that the life cycle of this first cloud population maintains the transition-layer structure. That is, very shallow clouds smooth vertical thermodynamic gradients in the transition layer by a condensation–evaporation mechanism, which is fully coupled to the mixed layer. Inferences from mixed-layer theory and mixing diagrams, moreover, suggest that the observed transition-layer structure does not affect the rate of entrainment mixing, but rather the properties of the air incorporated into the mixed layer, primarily to enhance its rate of moistening. The physical processes producing the structure of the trade wind transition layer, a thin atmospheric layer thought to be important for regulating convection, are not yet well understood. Using extensive observations from a recent field campaign, we find that the cloud-free convective boundary layer structure, with an abrupt discontinuity in thermodynamic variables, is infrequent, despite cloud-base cloud fraction being small. We show that very shallow clouds both forming and dissipating within the transition layer smooth vertical gradients compared to a jump, except in large [O(200) km] cloud-free areas. This condensation–evaporation mechanism, which is fully coupled to the mixed layer, does not appear to affect the rate of entrainment mixing, but rather the properties of air incorporated into the mixed layer.
Depth Extraction from a Single Image Based on Block-Matching and Robust Regression

Predicting scene depth (or geometric information) from single monocular images is a challenging task. This paper addresses such challenging and essentially ill-posed problem by regression on samples for which the depth is known. In this regard, we first retrieve semantically similar RGB and depth pairs from datasets using a deep convolutional activation feature. We show that our framework provides a richer foundation for depth estimation than existing hand-craft representations. Subsequently, an initial estimation is then integrated by block-matching and robust patch regression. It assigns perceptually appropriate depth values to an input query in accordance with a data-driven depth prior. A final post processor aligns depth maps with RGB discontinuities, resulting in visually plausible results. Experiments on the Make 3D and NYU RGB-D datasets show competitive results compared to recent state-of-the-art methods.
Relativistic bulk viscous fluids of Burgers type and their presence in neutron stars

It is well known that a mixture of two chemical components undergoing one chemical reaction is a bulk viscous fluid, where the bulk stress evolves according to the Israel-Stewart theory. Here, we show that a mixture of three independent chemical components undergoing two distinct chemical reactions can also be viewed as a bulk viscous fluid, whose bulk stress now is governed by a second-order differential equation which reproduces the Burgers model for viscoelasticity. This is a rigorous and physically motivated example of a fluid model where the viscous stress does not undergo simple Maxwell-Cattaneo relaxation, and can actually overshoot the Navier–Stokes stress. We show that, if one accounts for muons, neutron star matter is indeed a bulk viscous fluid of Burgers type.
Color and magnitude dependence of galaxy clustering

Abstract A quantitative study of the clustering properties of galaxies in the cosmic web as a function of absolute magnitude and colour is presented using the SDSS Data Release 7 galaxy redshift survey. We compare our results with mock galaxy samples obtained with four different semi-analytical models of galaxy formation imposed on the merger trees of the Millenium simulation.