Miracle-dz/UniFAR-FTUs huggingface dataset:
Altitude on Cartographic Materials and Its Correction According to New Measurement Techniques

Determining the correct height of mountain peaks is vital for tourism, but it is also important as a reference point for devices equipped with GPS (Global Positioning System), e.g., watches or car navigation systems. The peak altitude data are part of geographic and geodetic information. As more modern technologies and equipment become available, their precisions should increase. However, verification of peak heights is usually only conducted for the highest, well-known mountains—lower peaks or mountain passes are rarely verified. Therefore, this study focuses on an investigation of 12 altitude points on a section of the longest and most famous touristic trail in Poland (the Main Beskid Trail), located in the Orava–Żywiec Beskids Mts (Mountains). The aim of this research is to measure and verify the heights of the 12 selected mountain peaks, in addition to evaluating the chosen methods based on the quality of the obtained data and determining their suitability and opportunities for use in further research. Measurements were obtained at the most specific height points—on the 12 highest points of the summits. This study compares two modern measurement techniques: the global navigation satellite system (GNSS) and light detection and ranging (LiDAR). The obtained results were later compared with those widely used on the internet and in printed materials (period covered: 1884–2015). This analysis demonstrates that lesser-known objects are rarely the subject of remeasurement and significant altitude errors may occur, primarily because the heights originated from a source in the past when modern methods were not available. Our findings indicate that the heights of the peaks presented in cartographic materials are inaccurate. The assumed heights should be corrected by direct measurements using modern techniques.
Fusion and Correction of Multi-Source Land Cover Products Based on Spatial Detection and Uncertainty Reasoning Methods in Central Asia

Land cover products are an indispensable data source in land surface process research, and their accuracy directly affects the reliability of related research. Due to the differences in factors such as satellite sensors, the temporal–spatial resolution of remote sensing images, and landcover interpretation technologies, various recently released land cover products are inconsistent, and their accuracy is usually insufficient to meet application requirements. This study, therefore, established a fusion and correction method for multi-source landcover products by combining them with landcover statistics from the Food and Agriculture Organization of the United Nations (FAO), introducing a spatial consistency discrimination technique, and applying an improved Dempster-Shafer evidence fusion method. The five countries in Central Asia were used for a method application and verification assessment. The nine products selected (CCI-LC, CGLS, FROM-GLC, GLCNMO, MCD12Q, GFSAD30, PALSAR, GSWD, and GHS-BUILT) were consistent in time and covered the study area. Based on the interpretation of 1437 high-definition image verification areas, the overall accuracy of the fusion landcover result was 85.32%, and the kappa coefficient was 0.80, which was better than that of the existing comprehensive products. The spatial consistency fusion method had the advantage of an improved statistical fitting, with an overall similarity statistic of 0.999. The improved Dempster-Shafer evidence theory fusion method had an accuracy that was 4.86% higher than the spatial consistency method, and the kappa coefficient increased by 0.07. Combining these two methods improved the consistency of the multi-source data fusion and correction method established in this paper and will also provide more reliable basic data for future research in Central Asia.
A complete basis set model chemistry. II. Open‐shell systems and the total energies of the first‐row atoms

The major source of error in most ab initio calculations of molecular energies is the truncation of the one‐electron basis set. An open‐shell complete basis set (CBS) model chemistry, based on the unrestricted Hartree–Fock (UHF) zero‐order wave function, is defined to include corrections for basis set truncation errors. The total correlation energy for the first‐row atoms is calculated using the unrestricted Mo/ller–Plesset perturbation theory, the quadratic configuration interaction (QCI) method, and the CBS extrapolation. The correlation energies of the atoms He, Li, Be, B, C, N, O, F, and Ne, calculated using atomic pair natural orbital (APNO) basis sets, vary from 85.1% to 95.5% of the experimental correlation energies. However, extrapolation using the asymptotic convergence of the pair natural orbital expansions retrieves from 99.3% to 100.6% of the experimental correlation energies for these atoms. The total extrapolated energies (ESCF+Ecorrelation) are then in agreement with experiment to within ±0.
3d localization and diffusion of proteins in polyelectrolyte multilayers

The interaction of diverse biomaterials with surfaces is more crucial than ever for biomedical applications to ensure efficiency and reproducibility. Very interesting surface materials are micrometer-thick polyelectrolyte multilayers. Not only their surface but also the bulk can be loaded with biomaterials like proteins or DNA for various purposes. Therefore, we established a method to analyze the lateral and vertical distribution of fluorescently labelled proteins of various size and charge in polyelectrolyte films composed of poly(L-lysine) and hyaluronic acid by confocal laser scanning microscopy. This approach enables us to measure the diffusion coefficients of the proteins via fluorescence recovery after photobleaching as a function of their vertical position in the film and facilitates the understanding of molecular interactions in the film with a high resolution in both space and time. As a result, we confirm that protein loading in the film is driven by electrostatic interactions – uncharged dextran molecules of 10 and 500 kDa do not diffuse into the film. Proteins of different sizes (3–11 nm) can diffuse relatively fast (D = 2–4 μm2 s−1) independent of their net charge, indicating complex interpolymer interactions. This approach is a new powerful experimental tool to design the polyelectrolyte multilayers for bio-applications by finding a relationship between intermolecular interactions and mobility and availability of biomolecules to biological samples (e.g. cells) or detection units (e.g. biosensors).
CHLORITE AND BIOTITE WEATHERING BY FULVIC ACID SOLUTIONS IN CLOSED AND OPEN SYSTEMS

The dissolution by dilute fulvic acid (FA) solutions of elements constituting two chlorites and biotite was investigated in closed and open systems. In closed systems, dilute FA solution rapidly dissolved substantial amounts of Si, Al, Fe, Mg, and K (in the case of biotite only) from chamosite and biotite during the first 100 h of contact. Thereafter, the rate of dissolution decreased exponentially with increasing time. Maximal concentrations of elements dissolved were approximately proportional to FA concentrations when these were 0.1% (wt/vol) and lower. In the open systems, relatively fast dissolution rates of Fe-clinochlore and biotite were observed initially (up to 30≈35 days). Following this, the rates slowed to near constancy. If the dissolutions had continued at the constant rates, it would have taken a 0.025% FA solution about 22 yr to dissolve 1 g of Fe-clinochlore and 7.2 yr to dissolve 1 g of biotite. Increases in flow rate from 1 to 3 mL/h increased the rates of dissolution of the elements by.
Response of raspberries to soil nitrogen and boron applications

Abstract Raspberry yield and size were increased by both nitrogen and boron application in field fertilizer studies including a N rate trial (0, 67, 134 and 268 kg N/ha) and a N x B interaction trial (0 and 67 kg N/ha, and 0 and 1 kg B/ha). Yield response to N (11% increase from 134 kg N/ha) was smaller than to B (23% increase from 1 kg B/ha). Both N and B increased berry size. Nitrogen application delayed berry ripening.
Is it time for prenatal chromosomal-microarray analysis to all women? A review of the diagnostic yield in structurally normal fetuses

Purpose of review Chromosomal-microarray analysis (CMA) is the first-tier test in pregnancies with structural malformations. Accumulating data show that pathogenic copy number variants (CNVs) can also be identified in structurally normal fetuses. We set out to summarize the published data on the diagnostic yield of CMA in structurally normal fetuses. Recent findings Six studies summarize a total of 29,612 prenatal CMAs performed in structurally normal fetuses. The incidence of highly penetrant pathogenic/likely pathogenic CNVs is 0.4–2.5%. Variability was demonstrated in the timing of CMA testing and type of CNVs classified as pathogenic. The incidence of variants of uncertain significance is 0.4–5.4%. The prevalence of susceptibility loci is 0.3–0.7% when specified, and the incidence of CNVs associated with late onset disease is 0.1%. Summary With a frequency of abnormal CNVs of 1:40 to 1:250 in structurally normal fetuses, it is recommended that all pregnant women be informed of the possibility to have CMA performed, even in the absence of malformations. Information should also be provided about uncertain and secondary findings.
Synthesis and structure-conductivity relationship of polystyrene-block-poly(vinyl benzyl trimethylammonium) for alkaline anion exchange membrane fuel cells

Block copolymers of polystyrene-b-poly(vinyl benzyl trimethylammonium tetrafluoroborate) (PS-b-[PVBTMA][BF4]) were synthesized by sequential monomer addition using atom transfer radical polymerization. Membranes of the block copolymers were prepared by drop casting from dimethylformamide. Initial evaluation of the microphase separation in these PS-b-[PVBTMA][BF4] materials via SAXS revealed the formation of spherical, cylindrical, and lamellar morphologies. Block copolymers of polystyrene-b-poly(vinyl benzyl trimethylammonium hydroxide) (PS-b-[PVBTMA][OH]) were prepared as polymeric alkaline anion exchange membranes materials by ion exchange from PS-b-[PVBTMA][BF4] with hydroxide in order to investigate the relationship between morphology and ionic conductivity. Studies of humidity [relative humidity (RH)]-dependent conductivity at 80 °C showed that the conductivity increases with increasing humidity. Moreover, the investigation of the temperature-dependent conductivity at RH = 50, 70, and 90% showed a significant effect of grain boundaries in the membranes against the formation of continuous conductive channels, which is an important requirement for achieving high ion conductivity. © 2012 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2013, 51, 1751–1760, 2013
Characterization of erbium-silicided Schottky diode junction

Trap density, lifetime, and the Schottky barrier height of erbium-silicided Schottky diode are evaluated using equivalent circuit method. The extracted trap density, lifetime, and Schottky barrier height for hole are determined as 1.5/spl times/10/sup 13/ traps/cm/sup 2/, 3.75 ms and 0.76 eV, respectively. By using the developed method, the interface of the Schottky diode can be evaluated quantitatively.
Eficiência da escarificação mecânica e biológica na melhoria dos atributos físicos de um latossolo muito argiloso e no incremento do rendimento de soja

Compaction is one of the main causes of yield decreases in agricultural soils. Mechanical chiseling has been suggested to reduce soil compaction in long-term no-tillage systems. Another option to alleviate soil compaction is the use of cover crops, such as forage radish, with a well-developed tap root system and the capacity of growing into soil compacted layers, forming stable biopores and improving the soil physical properties. This study aimed to evaluate the efficiency of a mechanical (chisel plow) and biological (forage radish) soil decompaction method or the combination of both to improve the physical properties of a very clayey texture Oxisol and to increase soybean grain yield under no-tillage. The treatments were: black oat on no-till (NT-O), consortium of forage radish and black oat on no-till (NT-R+O), black oat on chiseled soil (CH-O) and consortium of forage radish and black oat on chiseled soil (CH-R+O). The following properties were evaluated: soil bulk density, macroporosity, microporosity and total porosity in the layers 0-0.05, 0.05-0.10, 0.10-0.15 and 0.15-0.20 m, soil penetration resistance, soil moisture and soil water infiltration at soybean flowering. The winter cover biomass production and soybean yield were also measured. The treatments did not affect the soil bulk density significantly at any of the soil depths. However, the treatments NT-R+O and CH-R+O doubled the mean soil macroporosity values in the 0-0.20 m layer, with more pronounced effects in the upper soil layers. The treatments NT-R+O and CH-R+O reduced soil penetration resistance compared to NT+O, while treatment CH-O had intermediate results. The treatments NT-R+O and CH-R+O increased the accumulated infiltrated water by 44.6 as compared to treatments NT-O and CH-O . The highest soybean yields were observed in the treatment CH-R+O (3.73 Mg ha-1), which did not differ significantly from treatment NT-R+O (3.49 Mg ha-1). The effect of winter mechanical chiseling was temporary and nine months later no soil physical improvements were observed, apart from the increase of total porosity and macroporosity in the 0-0.05 m layer. Biological chiseling increased soil macroporosity, reduced soil penetration resistance and improved soil water infiltration. Mechanical chiseling was only efficient to improve the soil physical conditions when associated with biological chiseling, which prevented soil reconsolidation.
Low-temperature conduction in germanium with disorder caused by extended defects

Investigations were carried out on low-temperature conductivity in the defect band of germanium formed due to the presence of large concentrations of extended defects introduced during high-temperature plastic deformation or irradiation with large integrated fluxes of high-energy neutrons and protons. It has been demonstrated that at relatively low concentrations of dislocations and low temperatures the electrical conductivity in the defect band occurs by hopping. At higher concentrations of dislocations the metal-insulator transition (MIT) takes place in the system of dislocations, the conductivity near the MIT showing a power-law variation, sigma (T) approximately Tx, with x<or=1 in the range 30 to 3*10-2 K. It has also been shown that the dislocation conductivity has a quasi-two-dimensional character. The dynamics of the Coulomb gap variations was studied near the MIT in Ge with a high concentration of radiation defects. The experimental data presented show that Ge with a high concentration of dislocations can be used for simulating some physical phenomena in amorphous and vitreous semiconductors.
Beyond Peak Performance: Comparing the Real Performance of AI-Optimized FPGAs and GPUs

The growing importance and compute demands of artificial intelligence (AI) have led to the emergence of domain-optimized hardware platforms. For example, Nvidia GPUs introduced specialized tensor cores for matrix operations to speed up deep learning (DL) computation, resulting in very high peak throughput up to 130 int8 TOPS in the T4 GPU. Recently, Intel introduced its first AI-optimized 14nm FPGA, the Stratix 10 NX, with in-fabric AI tensor blocks that offer estimated peak performance up to 143 int8 TOPS, comparable to 12nm GPUs. However, what matters in practice is not the peak performance but the actual achievable performance on target workloads. This depends mainly on the utilization of the tensor units, and the system-level overheads to send data to/from the accelerator. This paper presents the first performance evaluation of Intel's AI-optimized FPGA, the Stratix 10 NX, in comparison to the latest accessible AI-optimized GPUs, the Nvidia T4 and V100, on a large suite of real-time DL inference workloads. We enhance a re-implementation of the Brainwave NPU overlay architecture to utilize the FPGA's AI tensor blocks, and develop toolchain support that allows users to program tensor blocks purely through software, without FPGA EDA tools in the loop. We first compare the Stratix 10 NX NPU against Stratix 10 GX/MX versions with no tensor blocks, and then present detailed core compute and system-level performance comparisons to the T4 and V100 GPUs. We show that our enhanced NPU on Stratix 10 NX achieves better tensor block utilization than GPUs, resulting in 24× and 12× average compute speedups over the T4 and V100 GPUs at batch-6. Even with relaxed latency constraints that allow a batch size of 32, we still achieve average speedups of 5× and 2× against T4 and V100 GPUs, respectively. On a system-level, the FPGA's fine-grained flexibility with its integrated 100 Gbps Ethernet allows for remote access at 10× and 2× less system overhead latency than local access to a V100 GPU via 128 Gbps PCIe for short and long sequence RNNs, respectively.
Phase I and II crystals of poly(p‐oxybenzoate). II. Effects of solution polymerization conditions on morphology and crystal structure

In solution polymerized samples of poly(p-oxybenzoate), the fraction of phase II and resultant morphology is affected by polymerization temperature, time, and concentration. The two phases have approximately the same crystal-mesomorph transition temperature (Tk−m) and their morphology cannot be distinguished. Phase II appears to contribute to the coherence of the discs and whisker-discs found for certain solution polymerization conditions. The relationship of the morphology to Tk−m is discussed. © 1999 John Wiley & Sons, Inc. J Polym Sci B: Polym Phys 37: 3532–3551, 1999
How Certain is Your Transformer?

In this work, we consider the problem of uncertainty estimation for Transformer-based models. We investigate the applicability of uncertainty estimates based on dropout usage at the inference stage (Monte Carlo dropout). The series of experiments on natural language understanding tasks shows that the resulting uncertainty estimates improve the quality of detection of error-prone instances. Special attention is paid to the construction of computationally inexpensive estimates via Monte Carlo dropout and Determinantal Point Processes.
Spatio-Temporal Variational Autoencoders

The ubiquitous interest in deep latent variable models within the machine learning community has been fuelled by the development of the variational autoencoder (VAE). VAEs provide a framework for performing fast, scalable inference in deep latent variable models, facilitating their deployment on the large, multi-dimensional and richly structured datasets omnipresent in modern science and engineering. Increasingly large volumes of such data that also exhibit strong dependencies across space and time are arising from a wealth of domains, including environmental, social and earth sciences. Crucial to the advancement of these fields are the tools to effectively model spatio-temporal data. Despite their wide applicability, VAEs are ill-equipped to model such data. At the crux of this inadequacy is a deficiency in the probabilistic model, specifically, the assumption that observations are independent and identically distributed. In contrast to VAEs, Gaussian processes (GPs) are an extremely effective tool for modelling data that exhibits strong dependencies. Unfortunately, the power of GPs necessitates an often undermining computational burden scaling cubically with the number of data points and observed dimensions. This prohibits their application in the large data regime. Furthermore, GPs are comparatively inexpressive relative to ‘deep’ machine learning models, such as the VAE. Whilst the construction of more expressive GPs is possible, this is typically a hand-crafted process which only adds to the computational complexity, unlike the automatic feature learning intrinsic to deep models. This thesis seeks to unify the complementary strengths of VAEs and GPs, forming a novel family of VAEs for the effective modelling of spatio-temporal datasets. The amalgamation of the two models is natural; however, it requires careful consideration of approximate inference techniques to ensure the benefits of each are realised. We establish the theoretical framework for achieving this, paying particular attention to the preservation of structure in the approximate posterior and the principled handling of partially observed data. We provide an extension to the sparse GP literature, developing a scalable technique for the introduction of sparse approximations into our family of spatio-temporal VAEs. Finally, we demonstrate state-of-the-art performance relative to existing multi-output GP models and structured VAEs in a variety of experiments involving spatio-temporal datasets.
THE IMPACT OF MICROFINANCE ON SOCIAL MOBILITY, AN EMPIRICAL EVIDENCE FROM PAKISTAN

The present study was designed to examine the impact of microfinance on social mobility, that how does microfinance change the social mobility from low level to high level. The objective of the study was to analyze the role of microfinance in Social Mobility. Microfinance was perceived to be sustainable mechanism to fight poverty and empower low income households. Loans were micro or very small. It was an economic development tool for eradicating poverty from the society. It also helped pushing low income groups of society in community or organization processes and proved to be a unique blend of financial and social intermediation. The sample of the study comprised of 350 customers from different microfinance banks in Rawalpindi and Islamabad. Khushali bank, Kashf microfinance bank, The First microfinance bank. These were three leading banks operating in Pakistan. The data from the sample was collected through one standardized social mobility scale. It was a likert scale with five response categories; social mobility scale was developed by (Mohammad Arifujjaman Khan & Mohammad Anisur Rahaman, 2007). Results of the study showed that microfinance had great impact on social mobility, and there was a positive relationship existed between microfinance and social mobility, and the results also showed microfinance scheme uplifted social mobility that helped people to enhance their living standardize and provide them financial opportunities. Microfinance was the key strategy that leads to quick revival of economy, increase in living standards, empowerment and social mobility.
Linguistic Choices and Perceptions in Multilingual Spheres: The Case of the Indo-Yemenis

The purpose of this study was to investigate language choice and attitudes among the Indians of Yemen. Two research questions concerning domains of language use and attitudes towards each language guided the study. The eighty-six-participant sample was selected on grounds of convenience where they responded to alanguage questionnaire. Results showed that despite the passage of 170 years of settlement in Aden, the Indian ethnic languages were still alive in several settings most significantly at home. In addition, the Indians of Yemen possessed positive attitudes towards the Indian ethnic languages and towards Arabic.