Miracle-dz/UniFAR-FTUs huggingface dataset:
Post Impact Hydrothermal Activity. Thermodynamic Simulations on the Chicxulub Crater and Habitability Assessment.

Large asteroid and comet impacts on terrestrial planets and moons deliver vast amounts of heat that drive hydrothermal activity. Such hydrothermal processes subsequently raise probabilities for life evolution beneath planetary surfaces in the Solar System. We use the Chicxulub crater setting to model the thermodynamic evolution of the impact induced hydrothermal system. Data from the recent M0077A borehole samples of the IODP 364 Expedition and other seismic, magnetic and gravity surveys constrain our model inputs. As the impact induced central melt sheet gradually cools and crystallizes, it allows fluids to flow through it. Rock permeability is the determining factor of fluid circulation and lifetimes of hydrothermal systems. According to the assumed permeability, we found that the hydrothermal upwellings at Chicxulub were active for more than 2 Myr. Furthermore, the distributions of temperature and water mass flux along the Chicxulub crater and its annular trough allow us to proceed with the thermodynamic modelling of the geochemical reaction paths and to investigate potential energy metabolism pathways. Through this model, we assess habitability at the Chicxulub crater by (hyper) thermophiles / thermoacidophiles for the period of the impact-induced hydrothermal activity. As a result, we favor the application of the suggested model to habitability scenarios of fresh impact craters in the Solar System.
CLEP_A_200454 383..395

Eva N Glassou 1,2 Kaja KE Kjørholt Torben B Hansen 1 Alma B Pedersen 3 1University clinic for hand, hip and knee surgery, Regional Hospital West Jutland, Aarhus University, Holstebro 7500, Denmark; 2Department of Quality, Regional Hospital West Jutland, Holstebro 7500, Denmark; 3Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus N 8200, Denmark Purpose: We examined the association between delay in surgery and hospital-treated infections in hip fracture patients with and without known comorbidities. Patients and methods: All hip fracture patients aged ≥65 years registered in the Danish Multidisciplinary Hip Fracture Registry from 2005 to 2016 were included (n=72,520). Delay in surgery was defined as the time in hours from admission to surgery and was divided into 3 groups (12, 24 and 48 hrs). The outcomes were hospital-treated pneumonia, urinary tract infection and reoperation due to infection 0–30 days after surgery. As a measure of comorbidity, we used the Charlson Comorbidity Index (CCI): none (no registered comorbidities prior to the fracture), medium (1–2 points) and high (≥3 points). Results: Overall, there was an association between a delay of 12 hrs and pneumonia. A delay of 12 hrs was associated with an increased risk of pneumonia in patients with no comorbidities (adjusted hazard ratio (HR) 1.20, confidence interval (CI) 1.03–1.40) and a delay of 24 hrs was associated with an increased risk of pneumonia in patients with a medium level of comorbidity (HR 1.12, CI (1.02–1.23)). Overall, delay was associated with reoperation due to infection, particularly among patients with comorbidities, although the confidence intervals of some of the estimates were wide. A delay of 48 hrs was associated with an increased risk of reoperation due to infection in patients with a high level of comorbidity (HR 2.36, CI 1.19–4.69). Conclusion: Delay in surgery was associated with an increased risk of hospital-treated pneumonia and reoperations due to infection within 30 days of surgery. The number of postoperative hospital-treated infections within 30 days may be reduced by continuously targeting pre-, perand postoperative optimization not only for patients with high level of comorbidity but also for hip fracture patients without known comorbidities prior to surgery.
Diverseresource-usestrategies ina large-bodied marinepredatorguild : evidencefromdifferentialuseof resourcesubsidiesandintraspecific isotopicvariation

Observations of resource-use dynamics are sparse for higher trophic level species in marine systems, but important given their role in driving the distribution and functional roles of species. For a guild comprised of 7 large-bodied shark species captured in Florida Bay, we used multitissue stable isotope analysis to evaluate the extent of resource-use diversity within and between 2 time periods. We examined: (1) variation in community-wide isotopic niche structure across time (i.e. Layman’s community metrics); (2) variation in species’ trophic position; (3) reliance upon dominant resource pools (inland mangroves vs. coastal neritic [i.e. seagrass and/or reef-associated prey]; and (4) patterns of intraspecific isotopic variation across species (i.e. standard ellipse area, ellipse eccentricity E, ellipse inclination θ, and total isotopic overlap). Community-wide isotopic niche characteristics varied with tissue type, suggesting temporal plasticity in community resource use. Our novel approach integrating multiple isotopic baselines resulted in consistently high trophic position estimates (>5.0), but the utilization of available resource subsidies varied with species and tissue type. Whole blood suggested recent use of inland mangrove-derived prey resources, while fin tissue suggested differential use of both inland mangroves and coastal neritic-derived subsidies. Our results suggest that sharks display dynamic resource use in space and time, with limited functional complementarity across species. The adoption of diverse resource-use strategies, both within and among species, could facilitate the co-occurrence of large-bodied predator species and underscores the role of sharks as vectors of ecosystem connectivity.
Tax Administration vs. Tax Rates: Evidence from Corporate Taxation in Indonesia

Developing countries collect a far lower share of GDP in taxes than richer countries. This paper asks whether changes in tax administration and tax rates can nevertheless raise substantial additional revenue – and if so, which approach is most effective. We study corporate taxation in Indonesia, where the government implemented two reforms that differentially affected firms. First, we show that increasing tax administration intensity by moving the top firms in each region into “Medium-Sized Taxpayer Offices,” with much higher staff-to-taxpayer ratios, more than doubled tax revenue from affected firms over six years, with increasing impacts over time. Second, using non-linear changes to the corporate income tax schedule, we estimate an elasticity of taxable income of 0.59, which implies that the revenue-maximizing rate is almost double the current rate. The increased revenue from improvements in tax administration is equivalent to raising the marginal corporate tax rate on affected firms by about 23 percentage points. We suggest one reason improved tax administration was so effective was that it flattened the relationship between firm size and enforcement, removing the additional “enforcement tax” on large firms. On net, our results suggest that improving tax administration can have significant returns for developing country governments. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber. org.
Theory and Culture : Using Focus Groups to Uncover Parameters of Influence

The fact that learners’ perceptions of success and failure in foreign language learning can be influenced by their own culture is an idea put forward by studies on Attribution Theory. However, these studies have generally relied on assumptions about the cultures investigated, resulting in inconsistent findings mainly due to stereotyping. In order to avoid making subjective inferences on cultural parameters of specific groups of people, simply on the basis that they share the same geographical space, a number of focus groups were used to sound out a sample of research subjects selected according to nationality, level of English proficiency, age, and place of education. Data from the focus groups were analysed using constant comparative analysis in the light of social constructivism. The specific cultural parameters that emerged will serve to create a questionnaire as part of a large project for the investigation of both culture and attributions.
The LSO/KSO Hα prominence catalogue: cross-calibration of data

We present work on the extension of the homogeneous prominence catalogue created for the epoch 1967 – 2009 at the Lomnicky Peak Observatory (LSO) by incorporating new data acquired at the Kanzelhöhe Observatory for Solar and Environmental Research (KSO). We use data of 20 Hα prominences observed almost simultaneously at both observatories during four days in August/September 2009 to analyze the significance of differences of the determined parameters used in the Hα prominence catalogue. A reduction of the data from KSO and adaptation of the resulting parameters to fit the parameters of the LSO catalogue confirm that no special homogenization is needed to create a common catalogue data set. Thus, we justified that the LSO catalogue could be extended onward in the future using a more comprehensive database of observations from KSO.
Pre-Diagnosis of Hypertension Using Artificial Neural Network

s Artificial Neural Networks (ANNs) play a vital role in the medical field in solving various health problems like acute diseases and even other mild diseases. Earlier diagnosis of hypertension saves enormous lives, failing which may lead to other sever problems causing sudden fatal end. This paper deals with Artificial Neural Networks solving the problems of diagnosing hypertension using Back-Propagation learning algorithm. The network is constructed using various factors which are classified into some categories, to be trained tested and validated using the respective data sets. For construction, an input layer, a hidden layer and an output layer are used. Eight inputs have been given to the network and the network is trained with one hidden layer and one output layer. The back-propagation neural network model is systematically trained and with data sets.
Traf fi c Fatalities , 1985 – 2014 , and Their Relationship to Medical Marijuana Laws

Objectives.To determine the association ofmedicalmarijuana laws (MMLs)with traffic fatality rates. Methods. Using data from the 1985–2014 Fatality Analysis Reporting System, we examined the association between MMLs and traffic fatalities in multilevel regression models while controlling for contemporaneous secular trends. We examined this association separately for each state enacting MMLs. We also evaluated the association between marijuana dispensaries and traffic fatalities. Results.On average, MML states had lower traffic fatality rates than non-MML states. Medical marijuana laws were associated with immediate reductions in traffic fatalities in those aged 15 to 24 and 25 to 44 years, and with additional yearly gradual reductions in those aged 25 to 44 years. However, state-specific results showed that only 7 states experienced post-MML reductions. Dispensaries were also associatedwith traffic fatality reductions in those aged 25 to 44 years. Conclusions. Both MMLs and dispensaries were associated with reductions in traffic fatalities, especially among those aged 25 to 44 years. State-specific analysis showed heterogeneity of theMML–traffic fatalities association, suggestingmoderation by other local factors. These findings could influence policy decisions on the enactment or repealing of MMLs and how they are implemented. (Am J Public Health. 2017;107:336– 342. doi:10.2105/AJPH.2016.303577)
Association of the heart fatty acid-binding protein gene with quality of carcass and meat traits in pigs

The heart fatty acid-binding protein (HFABP) gene was sequenced in parental animals of a F2 crossing of boars of the Brazilian native Piau breed with commercial sows (Landrace x Large White x Pietrain). Primers used for PCR were designed to amplify four exons of the gene. The PCR products were sequenced and compared with the GenBank sequences. Differences between the generated sequences and the GenBank sequences were observed for both genetic groups. A total of 246 F2 animals were genotyped using the Hinf I restriction enzyme. Two genotypes were identified, 198 being animals HH and 48 Hh. The Hinf I SNP was significantly associated with weights of loin (bone-in) (P<0.05), jowl (P<0.05), sirloin (P<0.10), and kidneys (P<0.01). These results showed the potential of the H–FABP gene in marker-assisted selection programs for carcass traits in pigs.
Evaluation of the impact of extrinsic rewards on user engagement in a health promotion context

Despite the many mHealth solutions available, it remains unclear what their success factors are. Specifically, there has been controversy on the effectiveness of extrinsic rewards. This study evaluates two design elements of an mHealth solution – i.e., social proof and tangible rewards – and their impact on user engagement. During a four-week campaign, a sample of 143 university staff members engaged in a health promotion campaign. Participants were randomly distributed over one of three treatment groups. It was found that the introduction of a sufficiently meaningful, unexpected, and customized extrinsic reward can engage participants significantly more in a health promotion context.
Improving Cuneiform Language Identification with BERT

We describe the systems developed by the National Research Council Canada for the Cuneiform Language Identification (CLI) shared task at the 2019 VarDial evaluation campaign. We compare a state-of-the-art baseline relying on character n-grams and a traditional statistical classifier, a voting ensemble of classifiers, and a deep learning approach using a Transformer network. We describe how these systems were trained, and analyze the impact of some preprocessing and model estimation decisions. The deep neural network achieved 77% accuracy on the test data, which turned out to be the best performance at the CLI evaluation, establishing a new state-of-the-art for cuneiform language identification.
Association of GSTM 1 , GSTT 1 and CYP 2 E 1 Gene Polymorphisms with Antituberculosis Drug Induced Hepatotoxicity in North Indian Population

Background and Aims: Antituberculosis drug-induced hepatotoxicity (anti-TB-DIH) is a growing problem of serious concern in many countries around the world. Drug metabolizing enzymes have been proposed to play an influential role in the pathogenesis of anti-TB-DIH. Therefore, the main aim of this study was to investigate the possible association of GSTM1, GSTT1 and CYP2E1 gene polymorphisms with anti-TB-DIH. Methods: A prospective case-control study was conducted in 244 North Indian TB patients receiving anti-TB treatment. These patients were prospectively followed up both clinically and biochemically, before and during the treatment period, for the diagnosis of anti-TB-DIH. The frequencies of GSTM1, GSTT1 and CYP2E1 gene polymorphisms were determined from genomic DNA, utilizing multiplex polymerase chain reaction and restriction fragment length polymorphism methods respectively. Logistic regression analysis was used to determine the association between gene polymorphisms and anti-TB-DIH. Results: Anti-TB-DIH developed in 35 patients (cases). Out of 209 patients (without anti-TB-DIH), only 100 were taken as controls. As a result of genotype analysis, the frequencies of GSTM1 and GSTT1 null genotypes were found to be higher in cases as compared to controls. However, statistically significant difference was observed only for GSTT1 (Adjusted-OR=2.39; 95%CI=1.06-5.39; P=0.04). Further, combined effects of these two gene polymorphisms on the risk of anti-TB-DIH were analysed. However, the effects were insignificant. Also, no significant difference was reported in the frequencies of three genotypes (C1/C1, C1/C2 and C2/C2) of CYP2E1 between cases and controls. Conclusions: GSTT1 null polymorphism may be a potential risk factor for anti-TB-DIH in North Indian TB patients.
SIAMESE NEURAL NETWORK BASED APPEARANCE MODEL FOR MULTI-TARGET TRACKING

An appearance model plays a crucial rule in multi-target tracking. In traditional approaches, the two steps of appearance modeling i.e visual representation and statistically similarity measure are modeled separately. Visual representation is achieved either through hand-crafted features or deep features and statically similarity is measure through a cross entropy loss function. A loss function based on crossentropy (KL-divergence, mutual information) find closely related probability distribution for the targets. However, if the targets have similar visual representation, it ends up mixing the targets. To tackle this problem, we come up with a synergetic appearance model named Single Shot Appearance Model based on Siamese neural network. The network is trained with a contrastive loss function for finding the similarity between different targets in a single shot. The input to the network is two target patches and based on their similarity, a contrastive score is output by the network. The proposed model is evaluated on accumulative dissimilarity metric on three datasets. Quantitatively, promising results are achieved against three baseline methods.
SPECTROFLUOROMETRIC STUDIES OF THE EFFECT OF ZnO NANOPARTICLES ON BOVINE SERUM ALBUMIN

The study of protein nanoparticle interaction is very important for designing and fabricating nano composites which have potential medical applications. Bovine serum albumin (BSA), a major water soluble protein has wide range of physiological functions. In biomedical applications nanostructured metal oxides such as ZnO, TiO2 have drawn great attention for further studies as they are very safe to human beings and also for animals. Therefore, the interaction between BSA and ZnO nanoparticles (nps) and the effect of ZnO nps on the conformation of BSA has been analyzed by various spectroscopic techniques. The BSA-ZnO np conjugate made significant changes in BSA fluorescence emission parameters and thus confirmed the conformational changes.
Effectiveness in Teaching Methodology: An Evidence on School-Based Assessment Implementation

The main issue of newly adopted school-based assessment (SBA) in Malaysian education system in both primary and secondary school is the transition in adapting new system which affect teachers’ daily workload. This study will look upon the differences among teaching principles from developed countries such as Netherlands, Korea, United Kingdom, United States of America has long implemented SBA in their education system and proposed an improvement to the current teaching methodology so that the SBA implementation could be applied successfully in the future. This research focused findings of a study about effectiveness in teaching methodology among Malay language teachers’ on SBA implementation. The effectiveness of teaching methodology in the study was limited to three main objectives to: investigate whether teachers need any advanced training to increase teaching principles; investigate how effective teaching skills and assessment process needs to be emphasized; and investigate how the teachers deal with existing challenges while implementing the SBA. The methodology of study was qualitative in nature and data were collected from teachers in one of secondary schools in Seremban district with two teachers as a respondent. A total of two female teachers were involved as a respondent in the study. An interview was used as a study. The findings of this study showed teachers need to update their skills and knowledge continuously about learning and teaching with additional resources. On effective teaching, teachers must also continually refine their conceptual, pedagogical skills, classroom management, assessment and curriculum. Teachers need deep understanding of their subject area and a range of knowledge of effective strategies and practices that support student learning. The authorities must provide external learning opportunities for the teachers to implement school-based work that is enriched with ideas and knowledge from outside the school.
Fast CU Depth Decision for HEVC Using Neural Networks

This paper presents a coding unit (CU) depth-decision algorithm using neural networks to reduce the computational overhead of High Efficiency Video Coding (HEVC). The coding tree unit (CTU) of HEVC has a quad-tree structure, and its computational complexity is considerably high because it searches an optimal CU depth from the upper to lower depth recursively and exhaustively. In the proposed method, neural networks are used to predict the CTU depth. A database for neural networks is constructed, which considers both the image and encoding properties of the CU. It consists of the image data representing the image value of the CU, the vector data based on the encoding information of the CU, and the labels indicating whether the CU is divided. By using both properties of the CU, high test accuracy can be achieved. It is completely separated from the test sequence used for encoding and can be configured to use a sequence with various resolutions, motions, and contents for diverse CUs. We also design a neural-network architecture and perform training. The architecture consists of the convolution and pooling layers for analyzing the image property of the CU. The feature map is concatenated with the vector data and trained by fully connected layers in order to analyze the encoding property of the CU. Finally, a fast CU depth-decision algorithm is designed based on the trained neural networks. When the result of the neural network inference with the current CU depth is non-split, the operation on the lower CU depth is skipped. The experimental results show that the proposed method can reduce the computational overhead by 61.77% on average, and by a maximum of 73.45% with 3.91% Bjøntegaard-Difference-bitrate (BD rate) degradation.
Adsorption of methylene blue and malachite green dyes from aqueous solution by soya bean seed powder-equilibrium isothermal modeling

This study was aimed at using soya bean seed powder (SSP) as a potential adsorbent to remove methylene blue (MB) and malachite green (MG) dyes from aqueous solution. The SSP powder was used without any modification. In a batch adsorption system as a function of pH, contact time, adsorbent dose, and initial concentration of dyes was evaluated. Maximum removal of MB and MG dyes were observed at pH 6.0 and 5.0 respectively. The equilibrium uptake was increased with an increase in the initial dye concentration in the solution. Adsorption kinetic data were properly fitted with the pseudo second order kinetic model. The experimental isotherms data were analysed using Langmuir and Freundlich isotherm equations. The best fit was obtained by the Langmuir model with high correlation co efficient R2 = 0.9962, R2= 0.9998 with a maximum monolayer adsorption capacity of 149.25 mg/g for Methylene Blue and 232.55 mg/g for Malachite Green. The adsorbent was analysed by using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM) for determination of functional groups and surface morphology respectively.