Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization by X-ray powder diffraction of alpha lipoic acid

Alpha lipoic acid (ALA) C8H14O2S2 is a naturally occurring compound that is synthesized in small amounts by plants and animals, including humans. ALA is covalently bound to specific proteins, which function as cofactors for several important mitochondrial enzyme complexes and studies suggest that they might help with type 2 diabetes. In the Cambridge Structural Database, there are four entries related to this compound: two for lipoic acid and two for complexes. In the Powder Diffraction File-4, two experimental unindexed patterns are reported. The material crystallizes in a monoclinic crystal system, space group P21/a and cell parameters a = 9.237 (1) Å, b = 9.960 (1) Å, c = 11.787 (2) Å, β = 109.13 (1)°, and V = 1024.6 (2) Å3.
Immunogenetic Epidemiology of Dementia and Parkinson’s Disease in 14 Continental European Countries: Shared Human Leukocyte Antigen (HLA) Profiles

Human leukocyte antigen (HLA), which is critically involved in immune response to foreign antigens and in autoimmunity, has been implicated in dementia and Parkinson’s disease. Here we report on the correlations between the population frequencies of 127 HLA Class I and II alleles and the population prevalence of dementia and Parkinson’s disease in 14 Continental Western European countries, extending previous work1,2. We used these correlations to construct and compare HLA profiles for each disease3. We found that (a) the HLA profiles of the two diseases were significantly correlated across both HLA Class I and Class II alleles, (b) negative (“protective”) HLA-disease correlations did not differ significantly for either HLA class, but (c) positive (“susceptibility”) HLAdisease correlations were significantly higher in dementia than in Parkinson’s disease for both HLA classes of alleles. These findings indicate that (a) dementia and Parkinson’s disease share immunogenetic HLA-related mechanisms, (b) HLA-related protective mechanisms (presumably against pathogens) do not differ between the two diseases, but (c) HLA-related susceptibility mechanisms (presumably underlying autoimmunity) are significantly stronger in dementia than in Parkinson’s disease. Immunogenetic Epidemiology of Dementia and Parkinson’s Disease in 14 Continental European Countries: Shared Human Leukocyte Antigen (HLA) Profiles Lisa M. James1,2,3, Apostolos P. Georgopoulos1,2,3,4* 1The HLA Research Group, Brain Sciences Center, Department of Veterans Affairs Health Care System, Minneapolis, MN, 55417, USA 2Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN 55455, USA 3Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN 55455, USA 4Department of Neurology, University of Minnesota Medical School, Minneapolis, MN 55455, USA
Characterization of Genetic Diversity in Dhofari Wild Gazelles

Wild gazelles are scattered in most of the arid and semi-arid areas of the Sultanate of Oman particularly in valleys, mountains and sandy zones of Rub' al Khali desert. Recently, gazelles’ populations have been facing reduction in the numbers. Consequently, gradual loss of genetic diversity is inevitable. This loss is considered one of the main threats that attribute to a loss of habitat and may lead to gazelle extinction. Till now, little is known about the status of the genetic diversity of the wild Dhofari gazelle. This project aimed to determine the extent of inbreeding, population structure and genetic diversity in the Dhofari gazelles’ populations. DNA was extracted from gazelles’ fecal samples using the human stool DNA extraction protocol. Following extraction, four microsatellite nuclear markers were used to calculate the level of inbreeding, population differentiation and genetic diversity. PCR inhibitors were significantly removed by the addition of Bovine Serum Albumin (BSA) and dimethyl sulfoxide (DMSO). The mean inbreeding for the population was 0.228 for all loci with a standard error of 0.09. It is therefore postulated that Dhofari gazelles are generally undergoing gradual inbreeding which could lead to lack of fitness in future generations. The genetic differentiation (Fst) ranged between 0.071 (between Gara and Stom) and 0.231 (between Gara and Ayon). On the other hand, the Fst estimate between Solot (most distant) versus other Dhofari gazelles populations (pooled together) was 3.7%. Principle Components Analysis clustered Ayon and Gara populations apart from one another and closer to Stom while placing Solot further than all other populations which is in agreement with the Fst results and the geographical distribution. In conclusion, the results of this preliminary study will provide insight towards the conservation of wild gazelles in Dhofar. This is the first study to report the genetic diversity and status of wild Gazelles and provides a reference point for future studies assessing their genetic diversity and variability.
Fiscal effects of interlocal collaboration: evidence from Nebraska counties

ABSTRACT The fiscal effects of interlocal collaboration, a growing method of service delivery, remain inconclusive. We analysed the revenue and expenditure effects of collaboration arrangements as a whole and in six service areas for counties in the U.S. state of Nebraska over the period 2013–2018. Our analyses reveal that counties with a higher number of interlocal collaborations had lower total per capita revenues and expenditures, but higher property taxes. Lower per capita revenues and expenditures appear to be the result of collaboration in service areas that include general government purposes. Interlocal collaboration related to health and human services activities, however, resulted in higher per capita spending and revenues, suggesting that the primary goal of collaborating in these activities may not be cost savings.
Narrating plastics governance: policy narratives in the European plastics strategy

ABSTRACT The European Union (EU) aspires to be an important global agenda-setter on how to treat and regulate the growing plastics problem. We present an analysis of the plastic policy narratives shaping European plastics governance, in particular through the European Commission’s Plastics Strategy. Our aim is to first uncover the policy narratives at play, and then examine how actors make use of those narratives through strategic construction. Based on interviews with key stakeholders and document analysis, we identify four narratives: fossil feedstock dependency, resource inefficiency, pollution, and toxicity. We find that the resource inefficiency and pollution narratives figure most prominently in European plastics governance, and that the circular economy is being advanced as a policy solution that cuts across the different narratives. However, surface agreement on the need for ‘circularity’ hides deeper-lying ideological divisions over what exactly the circular economy means and the different directions this implies for plastics governance.
Data Mining Classification Algorithms for Analyzing Soil Data

Rapid changes are occurring in our global ecosystem, and stresses on human well-being, such as climate regulation and food production, are increasing, soil is a critical component of agriculture. The project aims to use Data Mining (DM) classification techniques to predict soil data. Analysis DM classification strategies such as k-Nearest-Neighbors (k-NN), Random-Forest (RF), Decision-Tree (DT) and Naïve-Bayes (NB) are used to predict soil type. These classifier algorithms are used to extract information from soil data. The main purpose of using these classifiers is to find the optimal machine learning classifier in the soil classification. in this paper we are applying some algorithms of DM and machine learning on the data set that we collected by using Weka program, then we compare the experimental result with other papers that worked like our work. According to the experimental results, the highest accuracy is k-NN has of 84 % when compared to the NB (69.23%), DT and RF (53.85 %). As a result, it outperforms the other classifiers. The findings imply that k-NN could be useful for accurate soil type classification in the agricultural domain.
Is perception probabilistic? Clarifying the definitions

A fundamental question for perception research is what sensory information is available for decision making, or, stated differently, what is the output of perception. One answer that has emerged in the last two decades is that perception is probabilistic, meaning that the brain represents probability distributions over world states. However, despite the apparent simplicity of this statement, there are substantial disagreements on exactly what probabilistic perception is and how it should be tested. In this adversarial collaboration, two proponents (Jehee and Denison) and two skeptics (Rahnev and Block) of probabilistic perception deliberate on the terms of the debate and present arguments for or against the notion that perception is probabilistic. We believe that this collaboration helps clarify the critical issues that need to be considered but that further work is required to reach consensus.
COMPARISION OF THREE DIGESTION METHODS FOR SOIL ARSENIC DETERMINATION. APPLICATION FOR HO CHI MINH CITY SOIL ARSENIC ANALYSIS

For soil arsenic detennination, the accuracy is crucial. To attain the accuracy, it is necessary to compare different methods, evaluate their appropriateness and apply them to analyze various local soil types. The results of this study show that: (1) for total soil arsenic determination, the method using microwave with HF has the higher recovery and accuracy rates in comparision with those of normaland reverse-aqua regia methods. (2) when applying the method using microwave with HF for soils of Hochiminh City, there are no statistically significant differences in As concentrations resulted from sandy soil sample analysis. But, for clay soil sample, As concentrations are method-dependent and increased following the sequence: normal aqua regia < reversed aqua regia < microwave. In average, As concentrations in different soil groups, decreased following the sequence: saline acidic sulphate> alluvial> acidic SUlphate> regosol >degraded grey> yellowish brown ferrasol. When compared with Vietnamese standards (TCVN 7209:2002) As concentrations in most soil samples are lower.
A fatigue crack growth life prediction model for metal matrix nanocomposites: contribution of strengthening factors

The nanocomposite materials acquired more attention in industries due to high strength, stiffness, and fatigue life. Fatigue behaviour is an important aspect in metal matrix nanocomposites (MMNCs) and needs to be investigated. In the proposed model, the low cycle fatigue (LCF) behaviour of MMNCs is considered as a localized damage development (i.e. fatigue crack growth) phenomenon under cyclic loading. The actual degradation takes place within the fatigue damage zone (FDZ) that lies very near to the crack-tip and dominates the whole LCF behaviour. The strengthening factors considered in the present study include: Orowan strengthening effect, dislocation density of matrix, load-bearing reinforcement effect, the porosity and microstructural properties of the MMNCs. For validation, the proposed model has been explored to fit on several reported experimental data sets and it is found to offer good prediction and statistically in agreement with the data. Further, to observe the impact of various model parameters, sensitivity analysis has also been performed and reported that a small change in cyclic strength coefficient resulted the maximum deviation and the change in porosity the least. The presented investigations in this work, represents detailed model development and sensitivity analysis of fatigue crack growth life of MMNCs.