Miracle-dz/UniFAR-FTUs huggingface dataset:
Purified Na2CrO4–H2SO4: A New Low‐Blank Medium for Re‐Os Dating of Black Shale

The H2SO4–CrO3 method has been widely used in Re‐Os isotope dating of organic‐rich sedimentary rocks. However, the high Re blank of this method inhibits the collection of high‐precision Re‐Os data, especially for organic‐rich sedimentary rocks with low Re and Os mass fractions. Here, we report a new H2SO4–Na2CrO4 method in which the Re blank of the Na2CrO4 reagent can be greatly reduced after efficient purification by acetone. A proportion of 0.6 g Na2CrO4/8 ml H2SO4 was selected as the best digestion combination based on tests of black shales with different organic carbon contents in three digestion media (inverse aqua regia, H2SO4–CrO3, and H2SO4–Na2CrO4). The H2SO4–Na2CrO4 method has an ultra‐low total procedural blank of 1–2 pg for Re and 0.6–1 pg for Os, respectively, which is one order of magnitude lower than the H2SO4–CrO3 method and is comparable with to inverse aqua regia method. The new method was applied to reference material SBC‐1 and two series of black shale samples, and the results were consistent with those obtained via the inverse aqua regia method. These findings confirm the accuracy and feasibility of the H2SO4–Na2CrO4 method, and demonstrate its ability to accurately determine the depositional age of organic‐rich sedimentary rocks with low Re and Os mass fractions.
Investigation of Physical and Motor Characteristics Between University Students Who Participate and Students Who Don’t Participate in Sport Activities

The purpose of this study is to investigate the differences between physical and some motoric characteristics of university students who participate in regular sports training and those who do not. A total of 20 volunteer students, 10 students with an average age of 20.80 ± 1.69 and 10 students with an average age of 19.90 ± 1.45 without any exercise habits were included in the study. Body circumference measurements, vertical-horizontal jump and strength, flexibility, body mass index, body fat ratio, body circumference measurements, vertical-horizontal jump and claw-back-leg strengths, flexibility, peak and average power values of the participant groups were determined and compared. SPSS 20.0 package program was used to analyze the data. Athlete Students' body density, shoulder circumference, chest circumference, biceps (extension-flexion) circumference, average-peak strength, long-vertical jump, hand claw-back-leg strength were determined to be higher than non-athlete students (p<0.05). Besides, students doing sports; body weight, body mass index, body fat ratio and waist circumference measurement averages were found to be lower than non-athletes (p<0.05). As a result; it has been observed that the participation of young students in regular sports educations can be effective in preventing the risk of obesity and increases their motoric characteristics.
Improving the Iraqi Oil Well Cement Properties Using Barolift: an Experimental Investigation

Cement is a major component in oil and gas drilling operations that is used to maintain the integrity of boreholes by preventing the movement of formation fluids through the annular space and outside the casing. In 2019, Iraq National Oil Company ordered all international oil and gas companies which are working in Iraq to use Iraqi cement (made in Iraq) in all Iraqi oil fields; however, the X-ray fluorescence (XRF) and compressive strength results in this study show that this cement is not matching with American Petroleum Institute (API) standards. During this study, barolift was used to improve the properties of Iraqi cement used in oil wells at high pressure and high temperature (HPHT). Barolift (1 g) was added to cement admixture to evaluate its influence on improving the performance of cement, mainly related to the property of toughness. Primarily, the quality and quantity of cement contents were determined using X-ray fluorescence. Experiments were conducted to examine the characteristics of the base cement and the cement system containing 1g of barolift, such as thickening time, free water, compressive strength, and porosity. X-ray diffraction (XRD), scanning electron microscope (SEM), and energy dispersive X-ray spectroscopy (EDS) were conducted for analyzing the microstructure of cement powder. The experimental results showed that barolift acted as a retarder and improved the thickening time, slightly increased the free water, enhanced the mechanical properties, reduced the porosity, and aided in scheming new cement slurry to withstand the HPHT conditions. Microstructure analysis showed that barolift particles blocked the capillaries by filling cement spaces and, thus, a denser and stricter cement network was achieved.
Predictors of school students’ leisure-time physical activity: An extended trans-contextual model using Bayesian path analysis

The present study aimed to examine effects of motivational and social cognition constructs on children’s leisure-time physical activity participation alongside constructs representing implicit processes using an extended trans-contextual model. The study adopted a correlational prospective design. Secondary-school students (N = 502) completed self-report measures of perceived autonomy support from physical education (PE) teachers, autonomous motivation in PE and leisure-time contexts, and social cognition constructs (attitudes, subjective norms, perceived behavioral control), intentions, trait self-control, habits, and past behavior in a leisure-time physical activity context. Five weeks later, students (N = 298) self-reported their leisure-time physical activity participation. Bayesian path analyses supported two key premises of the model: perceived autonomy support was related to autonomous motivation in PE, and autonomous motivation in PE was related to autonomous motivation in leisure time. Indirect effects indicated that both forms of autonomous motivation were related to social cognition constructs and intentions. However, intention was not related to leisure-time physical activity participation, so model variables reflecting motivational processes did not account for substantive variance in physical activity participation. Self-control, attitudes, and past behavior were direct predictors of intentions and leisure-time physical activity participation. There were indirect effects of autonomous motivation in leisure time on intentions and physical activity participation mediated by self-control. Specifying informative priors for key model relations using Bayesian analysis yielded greater precision for some model effects. Findings raise some questions on the predictive validity of constructs from the original trans-contextual model in the current sample, but highlight the value of extending the model to incorporate additional constructs representing non-conscious processes.
Deep Neural Networks Based Weight Approximation and Computation Reuse for 2-D Image Classification

Deep Neural Networks (DNNs) are computationally and memory intensive, which presents a big challenge for hardware, especially for resource-constrained devices such as Internet-of-Things (IoT) nodes. This paper introduces a new method to improve DNNs performance by fusing approximate computing with data reuse techniques for image recognition applications. First, starting from pre trained network, then the DNNs weights are approximated based on the linear and quadratic approximation methods during the retraining phase to reduce the DNN model size and number of arithmetic operations. Then, the DNNs weights are replaced with the linear/quadratic coefficients to execute the inference so that different DNNs weights can be computed using the same coefficients. That leads to a repetition of the weights, which enables the reuse of the DNN sub-computations (computational reuse) and leverages the same data (data reuse) to reduce DNNs computations, memory accesses, and improve energy efficiency, albeit at the cost of increased training time. Complete analysis for MNIST, Fashion MNIST, CIFAR 10, CIFAR 100, and tiny ImageNet datasets is presented for image recognition, where different DNN models are used, including LeNet, ResNet, AlexNet, and VGG16. Our results show that the linear approximation achieves 1211.3×, 21.8×, 700×, and 19.3× on LeNet-5 MNIST, LeNet Fashion MNIST, VGG16 and ResNet-20. respectively, with small accuracy loss. Compared to the state-of-the-art Row Stationary (RS) method, the proposed architecture saved 54% of the total number of adders and multipliers needed. Overall, the proposed approach is suitable for IoT edge devices as it reduces computing complexity, memory size, and memory access with a small impact on accuracy.
The striking endemism pattern of the species-richest snake genus Atractus (Dipsadidae: Serpentes) highlights the hidden diversity in the Andes

The distribution of the highly diversified and species-rich snake genus Atractus was assessed in search for endemism areas. The dataset of 6000 museum specimens was used to run an Endemicity Analyses in order to identify areas of biogeographic relevance for the genus Atractus. By using distinct methodological approaches and modifying the size and shape of grid cells we obtained a better adjustment to each species range, taking into account species distributed along the Andean and Atlantic Forest mountain ranges or certain vegetation constraints. Three scales of endemism were observed: micro endemic areas, represented by three different regions; intermediate sized endemic areas, represented by nine different regions; and macro-endemic areas, represented by four different provinces. Although most assessed regions corroborate well-defined biogeographic units according to the scientific literature, some, mainly located in the Colombian Andes, are not regularly considered in biogeographic syntheses carried out for vertebrates. Methodological approaches, along with a well curated database and taxonomic accuracy, may significantly influence the recovery of endemism areas, mainly considering mountain topography and local niche structure. The results present herein highlight the relevance of three Colombian Cordilleras, in order to completely understand Neotropical biota patterns of distribution. It is important to note that a well-resolved taxonomy represents both the framework and the first step toward a comprehensive biographical synthesis reducing Wallacean shortfalls in biodiversity.
Evolution of Salinity and Water Table Level of the Phreatic Coastal Aquifer of the Emilia Romagna Region (Italy)

The coastal aquifers of the Mediterranean region are highly susceptible to seawater intrusion due to a combination of challenges such as land subsidence, high aquifer permeability, urbanization, drainage, and an unsustainable use of water during the dry summer months. The present study is focused on a statistical analysis of groundwater data to evaluate the spatial changes of water level and electrical conductivity in the coastal phreatic aquifer of the Emilia-Romagna (Northeast Italy) for the period from 2009 to 2018. Data from 35 wells distributed across the entire regional coastal area are used to establish a temporal trend, as well as correlations between salinity, water table level, and rainfall. Water table and salinity distribution maps for the entire study area are discussed regarding surface geology and water management. Most of the wells are in the beach wedge sand unit, which allows for easy connectivity between groundwater and surface water. Surface water and groundwater salinization are enhanced along the surface water bodies connected to the sea. The lowest water table level occurs in the western and northern parts of the study area, because of the semiconfined behavior of the aquifer. Only in the northernmost, close to the Po River, and in the southernmost parts of the study area does the groundwater remain fresh for the whole period considered due to river aquifer recharge. In the rest of the region, the thickness of freshwater lenses, where present, is less than 4.5 m. The existence of a water table level below sea level and high saline water at the bottom of the aquifer in most of the study area suggest that the aquifer is in unstable hydrodynamic conditions and groundwater quality is not fit for human consumption or for irrigation. This study is the first to provide a regional overview of the state of groundwater level and salinization within the coastal aquifer of the Emilia-Romagna Region; it also suggests that, overall, the salinization trend has slightly decreased from 2009 to 2018.
UVStyle-Net: Unsupervised Few-shot Learning of 3D Style Similarity Measure for B-Reps

Boundary Representations (B-Reps) are the industry standard in 3D Computer Aided Design/Manufacturing (CAD/CAM) and industrial design due to their fidelity in representing stylistic details. However, they have been ignored in the 3D style research. Existing 3D style metrics typically operate on meshes or point clouds, and fail to account for end-user subjectivity by adopting fixed definitions of style, either through crowd-sourcing for style labels or hand-crafted features. We propose UVStyle-Net, a style similarity measure for B-Reps that leverages the style signals in the second order statistics of the activations in a pre-trained (unsupervised) 3D encoder, and learns their relative importance to a subjective end-user through few-shot learning. Our approach differs from all existing data-driven 3D style methods since it may be used in completely unsupervised settings, which is desirable given the lack of publicly available labeled B-Rep datasets. More importantly, the few-shot learning accounts for the inherent subjectivity associated with style. We show quantitatively that our proposed method with B-Reps is able to capture stronger style signals than alternative methods on meshes and point clouds despite its significantly greater computational efficiency. We also show it is able to generate meaningful style gradients with respect to the input shape, and that few-shot learning with as few as two positive examples selected by an end-user is sufficient to significantly improve the style measure. Finally, we demonstrate its efficacy on a large unlabeled public dataset of CAD models. Source code and data are available at github.com/AutodeskAILab/UVStyle-Net.
Do language models learn typicality judgments from text?

Building on research arguing for the possibility of conceptual and categorical knowledge acquisition through statistics contained in language, we evaluate predictive language models (LMs) -- informed solely by textual input -- on a prevalent phenomenon in cognitive science: typicality. Inspired by experiments that involve language processing and show robust typicality effects in humans, we propose two tests for LMs. Our first test targets whether typicality modulates LM probabilities in assigning taxonomic category memberships to items. The second test investigates sensitivities to typicality in LMs' probabilities when extending new information about items to their categories. Both tests show modest -- but not completely absent -- correspondence between LMs and humans, suggesting that text-based exposure alone is insufficient to acquire typicality knowledge.
Penetrating Injury from Interpersonal Violence and Related Haemorrhagic Shock Resuscitation Practices in An Urban South African Emergency Medical Service

Introduction Physical injury is a major cause of premature death and/or disability worldwide. South African mortality statistics indicate approximately half of all injury-related deaths were intentional, often from sharp-force injuries. Injury surveillance data for victims of penetrating injury is scarce in low- to middle-income countries with a reliance on mortality data. The aim was to provide an epidemiological description of penetrating injury and the related haemorrhagic shock resuscitation practice in a South African emergency medical service. Methods A prospective, observational, descriptive study was conducted in urban Cape Town. ‘R’ statistical computing was used. Emergency care providers voluntarily documented parameters for mechanism of injury, vital signs, intravenous fluid resuscitation and demographic information for patients with penetrating injury. Results Of 2884 (N) penetrating trauma cases, 143 (n) cases were sampled from providers. The chest (35.7%) and upper-limbs (31.5%) were the most common anatomy for penetrating injuries. The estimated mean crystalloid fluid volume administered for penetrating abdominal and chest injuries was 1010.6 mL and 925.3 mL respectively. A statistically significant association was observed between fluid administration and clinical indications such as systolic and diastolic blood pressure, heart rate, capillary refill time, level of consciousness estimation from the scene of the incident to the hospital after intravenous fluid administration. Most emergency medical service call outs (56%) were likely to occur between 20:00 and 02:00. Conclusion The intravenous fluid management by pre-hospital emergency care providers for patients with penetrating traumatic injuries, do not cohere with hypotensive resuscitative recommendations. Future research must include clinical practice guideline implementation efficacy and pre-hospital surveillance mechanisms. This study informs hospital clinician expectations for penetrating trauma care by pre-hospital providers.
Diatom Algae-Indicators of Water Quality in the Lower Zarafshan River, Uzbekistan

This work is the first, the purpose of which was a comprehensive assessment of the ecological state of the lower reaches of the Zarafshan River using bioindication of water quality by diatoms based on species’ ecological preferences, pollution indices, statistics, and ecological mapping. A total of 198 species and subspecies of diatoms were first identified from 195 samples collected four times a year at six sites in the lower reaches of the Zarafshan River in 2009–2015. The richest species were Cymbella, Navicula, and Nitzschia. Pleurosira laevis, resistant to salinity, was first found in aquatic habitats in Uzbekistan. Bioindicators of nine environmental variables make up 91% of the list. Distribution analysis of variables, pollution indices (SLA—SládečDek index of saprobity), and toxicity indices (WESI—Water Ecosystem State Index) show increases in salinity, turbidity, and decreases in organic pollution downstream. The source of acidification can be the Navoi region. We found an increase in the ability to self-purify with an increase in species richness and abundance of diatoms in the lower part of Zarafshan. Thus, the ecosystem of the studied part of the river successfully copes with the incoming pollution from the middle part of Zarafshan and demonstrates some stability and successful self-purification with a water quality class of 2–3. The first studied lower reaches of the ecosystem of the Zarafshan River using bioindicators, statistics, and ecological mapping show that the problem of aridization in Central Asia does not necessarily lead to degradation of the river ecosystem and an increase in pollution, but with rational water use can improve water quality and self-purification processes. Hence, diatoms can be good indicators of river water quality in a semi-arid region and reflect the climate and anthropogenic load change. We recommend that attention be paid to nutrient and turbidity management and to expand state monitoring points to the lower part of the river up to the Karakul region.
Learning English in the shadows: Taiwanese students’ reflections on their English private tutoring learning experiences

Private tutoring has received increasing research attention as a global phenomenon, but awareness of its impact on students’ language learning and pedagogical discussions is lacking. This study investigated 35 Taiwanese learners’ English private tutoring (EPT) experiences based on their reflections on language learning after finishing their secondary education. A background questionnaire and one-on-one semi-structured interviews were administered to collect participants’ data. The present study found that the participants had complex, inconsistent, and contradictory attitudes toward EPT. Although the interviews revealed the students’ needs that could be met by private tutoring institutions, the students’ reflections on EPT indicated that students were negatively affected in terms of language learning, educational experience, pressure, and values. Moreover, EPT was not considered an effective way to learn to use authentic English to communicate because of its overemphasis on examination skills. The effects of the contextual realities of learning for the purposes of assessment and achievement in language proficiency scores were explored to determine whether these realities undermined the aim of education. This study sheds light on the impact of private tutoring as it has become more than a form of shadow education and has emerged into the mainstream.
Improved Approximation for Longest Common Subsequence over Small Alphabets

This paper investigates the approximability of the Longest Common Subsequence (LCS) problem. The fastest algorithm for solving the LCS problem exactly runs in essentially quadratic time in the length of the input, and it is known that under the Strong Exponential Time Hypothesis the quadratic running time cannot be beaten. There are no such limitations for the approximate computation of the LCS however, except in some limited scenarios. There is also a scarcity of approximation algorithms. When the two given strings are over an alphabet of size $k$, returning the subsequence formed by the most frequent symbol occurring in both strings achieves a $1/k$ approximation for the LCS. It is an open problem whether a better than $1/k$ approximation can be achieved in truly subquadratic time ($O(n^{2-\delta})$ time for constant $\delta>0$). A recent result [Rubinstein and Song SODA'2020] showed that a $1/2+\epsilon$ approximation for the LCS over a binary alphabet is possible in truly subquadratic time, provided the input strings have the same length. In this paper we show that if a $1/2+\epsilon$ approximation (for $\epsilon>0$) is achievable for binary LCS in truly subquadratic time when the input strings can be unequal, then for every constant $k$, there is a truly subquadratic time algorithm that achieves a $1/k+\delta$ approximation for $k$-ary alphabet LCS for some $\delta>0$. Thus the binary case is the hardest. We also show that for every constant $k$, if one is given two strings of \emph{equal} length over a $k$-ary alphabet, one can obtain a $1/k+\epsilon$ approximation for some constant $\epsilon>0$ in truly subquadratic time, thus extending the Rubinstein and Song result to all alphabets of constant size.