Miracle-dz/UniFAR-FTUs huggingface dataset:
Compositions, logratios and geostatistics: An application to iron ore

Common implementations of geostatistical methods, kriging and simulation, ignore the fact that geochemical data are usually reported in weight percent, sum to a constant, and are thus compositional in nature. The constant sum implies that rescaling has occurred and this can be shown to produce spurious correlations. Compositional geostatistics is an approach developed to ensure that the constant sum constraint is respected in estimation while removing dependencies on the spurious correlations. This study tests the applicability of this method against the commonly implemented ordinary cokriging method. The sample data are production blast cuttings analyses drawn from a producing iron ore mine in Western Australia. Previous studies using the high spatial density blast hole data and compositional geostatistical approach returned encouraging results, results other practitioners suggested were due to the high spatial density. This assertion is tested through sub-sampling of the initial data to create four subsets of successively lower spatial densities representing densities, spacings, and orientations typical of the different stages of mine development. The same compositional geostatistical approach was then applied to the subsets using jack-knifing to produce estimates at the removed data locations. Although other compositional geostatistical solutions are available, the additive logratio (alr) approach used in this study is the simplest to implement using commercially available software. The advantages of the logratio methodology are the removal of the constant sum constraint, allowing the resulting quantities to range freely within the real space and, importantly, the use of many proven statistical and geostatistical methods. The back transformation of linear combinations of these quantities and associated estimation variances to the constrained sample space is known to be biased; this study used numerical integration by Gauss-Hermite quadrature to overcome this drawback. The Aitchison and Euclidean distances were used to quantify both the univariate and compositional errors between the estimates and original sample values from each estimation method. The errors of each method are analysed using common descriptive and graphical criteria including the standardised residual sum of squares and an assessment of the accuracy and precision. The highest spatial density dataset is equally well vii reproduced by either method. The compositional method is generally more accurate and precise than the conventional method. In general the compositional error analyses favour the compositional techniques, producing more geologically plausible results, and which sum to the required value. The results support the application of the logratio compositional methodology to low spatial density data over the commonly implemented ordinary cokriging.
A comparative study of epidemiological characteristics, treatment outcomes, and mortality among patients undergoing hemodialysis by health insurance types: data from the Korean Renal Data System.

Background The prevalence of end-stage renal disease (ESRD) requiring dialysis has progressively increased. Therefore, to achieve financial stability by managing the increasing numbers of patients undergoing hemodialysis (HD), a fixed-payment system was introduced in 2001 for medical aid (MA) beneficiaries receiving HD in Korea. Methods We identified patients in the Korean Renal Data System that received HD between 2001 and 2017 and stratified them into the following two groups: the National Health Insurance (NHI) and MA groups. Then, we compared the two groups that differed in demographic characteristics, the treatment process and outcomes, and mortality based on health insurance type. Results Among 52,574 patients, the number of patients aged 65 years or older, hypertension was higher in the NHI group, but diabetes was higher in the MA group. Additionally, the MA group had more weekly dialysis sessions, and expensive drugs tended to be used less frequently. Regarding treatment outcomes, including laboratory test results, the MA group achieved significantly lower goals than the NHI group (p < 0.001). Furthermore, the mortality rate per 1,000 persons was 31 and 27 in the MA and NHI groups, respectively, and the mortality rate ratio was 1.2 (95% confidence interval [CI], 1.076-1.230). Moreover, the hazard ratio for mortality was 1.39 (95% CI, 1.30-1.49, p < 0.001) after adjusting for age, sex, causes of ESRD, and comorbidities. Conclusion There were significant differences in the treatment and mortality indicators between the groups. Therefore, policy support should be strengthened to provide better medical services to MA beneficiaries undergoing HD.
Rate, Water Pressure, and Temperature Effects in Landslide Shear Zones

The behavior of slow‐moving landslides is controlled by the residual strength of the shear zone. Despite their mobile state, such slides can often withstand extreme events such as heavy rainfalls and earthquakes. A rate‐hardening in the shear zone is suspected to be one of the main stabilizing factors and has been well investigated, in particular for clayey soils. Soils from steep alpine landslides, on the other hand, are often dominated by silts and sands with various clay contents, and while understanding of their rate dependency is less advanced, it remains critical for the reliable risk assessment. In this article, an improved ring shear apparatus is presented and applied to investigate the rate, pore water pressure, and temperature effects in landslide shear zones. The testing program on samples from two alpine landslides in Switzerland revealed a moderately positive rate effect explaining their mobile state. An achieved insight into the thermo‐hydro‐mechanical processes of fast shearing provides physical evidence to the widely debated hypothesis on the generation of excess pore water pressure due to frictional heating. However, for the tested materials, this effect only occurs after extended shearing and does not lead to a complete loss of shear strength. Based on that and the observed positive rate effects, catastrophic failure seems unlikely for these landslides. At the same time, the results suggest that for less permeable soils, frictional heating may indeed be a source of negative rate effect during very rapid shearing.
Release Mechanism of an Avalanche on a Slope Covered with Bamboo Bushes

The glide of a snow cover on a slope covered with bamboo bushes was simulated so that the bushes’ resistance to glide was quantitatively related to the glide distance and speed. In one case their stalks and leaves were kept in the snow without falling down, in a second case they fell down and lay under the snow. Using the relations obtained, a description was given as to the behavior of a snow cover on a uniform slope as well as the distribution of stress and glide speed immediately before crack formation. Then, a criterion of crack formation was given in terms of glide speed.
Evaluation of Growth, Flowering, and Chlorophyll Fluorescence Responses of Viola cornuta cv. Penny Red Wing according to Spectral Power Distributions

Background and objective: The genus Viola, a member of the Violaceae family, is renowned for its ornamental flower crops. Additionally, Viola species are relatively pest-resistant and easy to manage. They are widely used in gardens, and some of their flowers are even edible. In this study, our focus was on V. cornuta cv. Penny Red Wing (hereinafter referred to as ‘Penny Red Wing’), an experimental plant chosen for its high ornamental value and rapid growth.Methods: We applied a purple light-emitting diode (LED) and three types of white LEDs with varying color temperatures: 3000, 4100, and 6500 K, respectively, as artificial light sources. Notably, a purple LED has a far-red wavelength (700-800 nm) ratio of approximately 17.6% in their spectral power distribution.Results: The findings indicated that several parameters exhibited higher values under purple LED: shoot size parameters, shoot biomass, moisture content of shoots and roots, photochemical reflectance index (PRI), modified chlorophyll absorption ratio index (MCARI), total number of flowers, flower size parameters, scent score, Fv/Fm, and PIABS. However, the 6500 K white LED led to higher evaluations of root length, number of shoots and leaves, root biomass, moisture content of shoots and roots, Fv/Fm, and PIABS. Nevertheless, it was observed that shoot growth was relatively hindered, and the flowering responses were inadequate under the 6500 K white LED, suggesting their unsuitability for the mass production of ‘Penny Red Wing’. Furthermore, the 3000 and 4100 K white LEDs were also deemed unsuitable for cultivating ‘Penny Red Wing’ due to their lower cultivation efficiency.Conclusion: ‘Penny Red Wing’ was evaluated as having superior growth, flowering, and chlorophyll fluorescence responses under purple LED, indicating that the far-red wavelength had a more pronounced effect compared to the green wavelength (500-600 nm). Therefore, we recommend cultivating this cultivar under purple LED, which include the far-red wavelength.
Fast and Accurate Computation of Wireless Power Transfer System Optimal Design Using Particle Swarm Optimization Method

In this article, for the first time, the wireless power transfer (WPT) system achieved optimal design by fast and accurate computation using a particle swarm optimization (PSO). The high power transfer efficiency (PTE) is determined by the dimension of the coil and the other parameters such as the operating frequency and ferrite structures. Therefore, the complex and high-dimensional design parameters of the WPT system have to be determined with optimal coil design. By the conventional FEM electromagnetic (EM) simulation such as Ansys Maxwell, it is impossible to optimize the coil design since it needs a huge amount of running time about several tens of minutes for only one simulation and the EM simulation does not consider the frequency-dependent results. One of the optimization methods, PSO algorithm is a powerful solution to resolve the large computation time and frequency-dependent results using the fast and accurate random data set generator. The results demonstrated that the optimal coil design by the PSO revealed the optimal PTE of the WPT system. Therefore, we can say that the PSO can carry out fast and accurate computation for optimization of the more real cases of WPT system considering the effect by the ferrite.
Deep Hyperspectral Shots: Deep Snap Smooth Wavelet Convolutional Neural Network Shots Ensemble for Hyperspectral Image Classification

The deployment of convolutional neural networks (CNNs) to classify hyperspectral images is extensively discussed in the research study. A number of different algorithms and approaches are applied, including 2-D CNN, 3-D CNN, support vector machine (SVM), regression models, and other state-of-the-art deep learning models, although these methods do not show good performance for hyperspectral image classification. Furthermore, 3-D CNNs require a lot of computational power and are not mainly employed, whereas 2-D CNNs do not constitute multiresolution image processing and exclusively focus on spatial features. However, 3D–2D CNNs aim to incorporate spectral and spatial features, and their efficiency while being evaluated on various datasets tends to be limited. Moreover, a number of deep learning models have been proposed recently, but their performance is still limited. In order to solve these problems, in this article, we propose a novel deep hyperspectral shot, a deep smooth wavelet CNN shots ensemble for hyperspectral image classification. A deep smooth wavelet CNN utilizes layers of wavelet transform to extract spectral features. The computation of a wavelet transform is less intensive as compared to the computation of a 3-D CNN. After that, the extracted spectral features are integrated into 2-D CNN, which generates spatial features, as a result, generates a spatial–spectral feature vector for classification. Furthermore, we introduce the snapshots generation method and employ a cyclic annealing schedule to converge to several local minima along its optimization path and save the models. We build several snapshots of the deep hyperspectral shots model to enhance the performance of our proposed method. We propose the snapshots optimization and ensemble selection approach in order to solve the optimization problem within ensemble creation and further enhance the performance. In addition, we also introduce a novel activation function called Relish to increase spatial–spectral feature propagation and advance for smoother gradients. Overall, we ensemble the snapshots of our proposed method and achieved that can classify multiresolution HSI data with high accuracy. Experiments performed on benchmark datasets, our proposed method, deep hyperspectral shots, achieved overall accuracies of 99.96%, 97.91%, and 99.49% on the Salinas, Indian Pines, and Pavia University datasets against the state-of-the-art methods.
Alleviation of banded leaf and sheath blight disease incidence in maize by bacterial volatile organic compounds and molecular docking of targeted inhibitors in Rhizoctonia solani

Rhizoctonia solani (RS) is a pathogenic fungus that affects maize (Zea mays L.) plants and causes banded leaf and sheath blight (BLSB) with severe consequences leading to significant economic losses. Contrarily, rhizobacteria produce numerous volatile organic compounds (VOCs) that help in devising the environment-friendly mechanism for promoting plant growth and stress alleviation without having physical contact with plants. In the present study, 15 rhizobacterial strains were tested for their antagonism against RS. The antagonistic potential of VOCs of the tested plant growth-promoting rhizobacteria (PGPR) strains ranged from 50% to 80% as compared to the control (without PGPR). Among these 15 strains, the maximum (80%) antagonistic activity was exhibited by Pseudomonas pseudoalcaligenes SRM-16. Thus, the potential of VOCs produced by P. pseudoalcaligenes SRM-16 to alleviate the BLSB disease in maize was evaluated. A pot experiment was conducted under greenhouse conditions to observe the effect of VOCs on disease resistance of BLSB-infected seedlings. Overall, maize seedlings exposed to VOCs showed a significant increase in disease resistance as indicated by a reduced disease score than that of unexposed infected plants. The VOCs-exposed maize exhibited lower (11.6%) disease incidence compared to the non-inoculated maize (14.1%). Moreover, plants exposed to VOCs displayed visible improvements in biomass, photosynthetic pigments, osmoregulation, and plant antioxidant and defense enzyme activities compared to the healthy but unexposed seedlings. Simultaneous application of RS and VOCs enhanced superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), phenylalanine ammonia lyase (PAL), ascorbate peroxidase (APX), and polyphenol oxidase (PPO) activities by 96.7%, 266.6%, 313.7%, 246.6%, 307%, and 149.7%, respectively, in the roots and by 81.6%, 246.4%, 269.5%, 269.6%, 329%, and 137.6%, respectively, in the shoots, relative to those of the control plants. The binding affinity of the VOCs (2-pentylfuran, 2,3-butanediol, and dimethyl disulfide) with CRZ1 and S9 protein receptors of RS was assessed by deploying in silico methods. Overall, 2-pentylfuran exhibited a binding affinity with both the selected receptors of RS, while 2,3-butanediol and dimethyl disulfide were able to bind S9 protein only. Hence, it can be deduced that S9 protein receptors are more likely the target RS receptors of bacterial VOCs to inhibit the proliferation of RS.
The Lexical Density and Experiential Structure of Nominal Groups of the Discussion Section of Skripsis and Research Articles

This research aimed to see the lexical density of the discussion section of three skripsis (SK) and three research articles (RA) and the experiential structure of its nominal groups. Halliday’s lexical density measurement, which divides the number of lexical items by the number of clauses, was used. It was found that SK has a higher lexical density level than RA (8,5 compared to 6,8). The reason is that one of the SK texts repeats dozens of lexical items in one clause, giving it a high lexical density score. If the text were to be ignored, then SK’s lexical density would be lower than RA (5,7 compared to 6,8). SK was found to have fewer nominal groups than RA (236 compared to 255). RA uses classifier and qualifier, which are realized by lexical items, more than SK, while SK leads in numerative, which is often realized by function words. It is concluded that SK, which has lower lexical density, also uses a more ‘simple nominal group structure’ i.e only having one premodifier or postmodifier, and utilizes lexical items in their nominal groups less frequently than RA did.
Modulation of Skin Cancer by the Stimulator of Interferon Genes

Morbidity and mortality from skin cancer continue to rise domestically and globally, and melanoma and non-melanoma skin cancers are a topic of interest in the dermatology and oncology communities. In this review, we summarize the stimulator of interferon genes (STING) pathway, its specific role in the pathogenesis of DNA damage and skin cancer, and STING-specific therapies that may fight both melanoma and non-melanoma skin (NMSC) cancers. Furthermore, we discuss specific portions of the STING pathway that may be used in addition to previously used therapies to provide a synergistic effect in future oncology treatments and discuss the limitations of current STING-based therapies.
Perbedaan model problem based learning dan discovery-inquiry ditinjau dari hasil belajar matematika siswa

Tujuan dari penelitian ini adalah untuk mengetahui apakah terdapat perbedaan hasil belajar dengan menggunakan Model Problem Based Learning (PBL) dan Discovery-Inquiry pada siswa kelas VII di SMP Negeri 5 Malang tahun ajaran 2017/2018. Penelitian ini menggunakan dua kelas yang dipilih dengan menggunakan Teknik Purposive Sampling. Kedua kelas diberikan perlakuan yang bebeda dengan materi yang sama yakni Persamaan Linier Satu Variabel (PLSV). Untuk memperoleh data, peneliti menggunakan tes yang terlebih dahulu dilakukan uji coba instrumen meliputi uji validitas dan uji reliabilitas. Selanjutnya analisis data menggunakan uji normalitas, uji homogenitas, dan uji hipotesis (Independent Sampel T-Test). Hasil penelitian menunjukkan bahwa terdapat perbedaan hasil belajar menggunakan model pembelajaran Problem Based Learning (PBL) dan Discovery-Inquiry pada siswa kelas VII di SMP Negeri 5 Malang tahun ajaran 2017/2018 dengan diperoleh signifikansi<0,05 yaitu 0,013<0,05. Selanjutnya, nilai rata-rata kelas yang menggunakan Model Problem Based Learning (PBL) lebih tinggi dari pada kelas dengan Model Discovery-Inquiry, yaitu dengan nilai rata-rata masing-masing kelas adalah 79,839 dan 71,613. Hal ini menunjukkan bahwa Model Problem Based Learning (PBL) lebih unggul daripada Model Discovery-Inquiry
DDAH1 Protects against Cardiotoxin-Induced Muscle Injury and Regeneration

Nitric oxide (NO) is an important biological signaling molecule affecting muscle regeneration. The activity of NO synthase (NOS) is regulated by dimethylarginine dimethylaminohydrolase 1 (DDAH1) through degradation of the endogenous NOS inhibitor asymmetric dimethylarginine (ADMA). To investigate the role of DDAH1 in muscle injury and regeneration, muscle-specific Ddah1-knockout mice (Ddah1MKO) and their littermates (Ddah1f/f) were used to examine the progress of cardiotoxin (CTX)-induced muscle injury and subsequent muscle regeneration. After CTX injection, Ddah1MKO mice developed more severe muscle injury than Ddah1f/f mice. Muscle regeneration was also delayed in Ddah1MKO mice on Day 5 after CTX injection. These phenomena were associated with higher serum ADMA and LDH levels as well as a great induction of inflammatory response, oxidative stress and cell apoptosis in the gastrocnemius (GA) muscle of Ddah1MKO mice. In the GA muscle of CTX-treated mice, Ddah1 deficiency decreased the protein expression of M-cadherin, myogenin, Bcl-2, peroxiredoxin 3 (PRDX3) and PRDX5, and increased the protein expression of MyoD, TNFα, Il-6, iNOS and Bax. In summary, our data suggest that DDAH1 exerts a protective role in muscle injury and regeneration.
L'origine des verres du désert libyque : un impact météoritique

Libyan Desert Glass (LDG) is a type of natural glass composed of nearly pure silica (98 wt %). On the basis of this composition, a low-temperature process by precipitation from silica-rich water has been suggested. Here we present results which contradict this hypothesis. First, the molecular structure studied by infrared spectrometry is characterized by the absence of OH ions, which are usually found in amorphous silica produced at low temperature. Second, chemical analyses show that the glass is not homogeneous in composition, but shows local enrichments of meteoritic elements with typical chondritic proportions. The only explanation for these observations is that Libyan Desert Glass formed in a meteorite impact on a silica-rich target. The absence of organic remains and the occurrence of pure silica inclusions (lechatelierite) are consistent with this explanation.
Demand of and Access to Health Messages Through Mass Media in the Rural Community of Eastern Ethiopia: A Mixed Method Study

Background The demand for health-related information has increased dramatically in recent years. Media is crucial in reaching health messages to audiences, especially those who are distant and rural. Therefore, the study aimed to assess demands, access, and factors associated with access to health messages through mass media in the rural community of Kersa District of East Hararghe, Eastern Ethiopia. Methods A mixed-methods study was conducted from October 15 to November 20, 2020. A quantitative cross-sectional and a qualitative phenomenological study design were applied. A total of 578 participants were included by using a systematic sampling technique. Collected data were entered into Epidata version 3.1 and analyzed using SPSS version 22.0. A multivariate logistic regression analysis model was used and reported using an adjusted odds ratio (AOR) with a 95% confidence interval (CI). Statistical significance was set at p <0.05. For qualitative, six-focused group discussions (FGDs) were used and then analyzed thematically. Results Overall, the demand of and access to health messages through mass media was 32.5% (95% CI=28.5–34.2%) and 26.6% (95% CI=24.6–28.7%), respectively. Factors such as having electric services (AOR=2.36, 95% CI=2.13–5.41), having a mobile phone (AOR=4.56, 95% CI=4.32–8.73), exposure to TV (AOR=4.73, 95% CI=1.03–11.62), and exposure to social media and printed media (AOR=5.24, 95% CI=1.07–15.63), a preference for programs such as news, current affairs, entertainment, health and educational were 2.37, 9.47, 4.75 and 7.55 times more likely to access health messages (AOR=2.37, 95% CI=1.00–5.61; AOR=9.47, 95% CI=3.54–25.34; AOR=4.75, 95% CI=1.23–18.38; and AOR=7.55, 95% CI=3.12–8.66, respectively). Qualitative findings, participants demand for health messages from health workers, radio, and the main source for accessing the message was the radio. Conclusion Approximately one in every three and one in every four rural communities in the study area had demand, and access to health messages through mass media, respectively. As a result, all stakeholders should emphasize and strengthen expanding methods of reaching health messages using mass media.