Miracle-dz/UniFAR-FTUs huggingface dataset:
Matrix ? Why does Cypher betray Morpheus ? How does the movie end ?

We introduce the MovieQA dataset which aims to evaluate automatic story comprehension from both video and text. The dataset consists of 14,944 questions about 408 movies with high semantic diversity. The questions range from simpler “Who” did “What” to “Whom”, to “Why” and “How” certain events occurred. Each question comes with a set of five possible answers; a correct one and four deceiving answers provided by human annotators. Our dataset is unique in that it contains multiple sources of information – video clips, plots, subtitles, scripts, and DVS [32]. We analyze our data through various statistics and methods. We further extend existing QA techniques to show that question-answering with such open-ended semantics is hard. We make this data set public along with an evaluation benchmark to encourage inspiring work in this challenging domain.
Crop Productivity Enhancement under Soybean Based Cropping System through Harvested Rain Water in Malwa Region

Background: Rainwater harvesting is commonly practiced in areas, where the rainfall is insufficient for crop growing. Due to the intermittent nature of run-off events, it is necessary to store the maximum possible amount of rainwater during the rainy season so that it may be used as irrigation to enhance the crop productivity and farm income under soybean based cropping system.Methods: A study was carried out during 2018-2019 in Indore district of Malwa region. Rainwater harvesting tanks at on station (42´21´2.4m) and on farm (15´11´4m) were constructed for irrigation water availability. Provision of water harvesting tank increased the irrigation water availability (1781m3 and 630m3 respectively) and stored water was managed through various irrigation systems viz. rain gun, drip and flood.Result: It was resulted that the provision of water harvesting tanks enhanced the crop productivity and farm income under soybean based cropping system. Availability of irrigation encouraged the farmers to diversify the cropping pattern (soybean-chickpea, soybean -wheat). It is also clear from the study that even with smaller storage tank and through conjunctive use of ground (1164.2m3) and surface water (596m3), multiple crops (Soybean, potato, sweet corn, chickpea, onion, garlic etc.) can be grown. Soybean-Chickpea cropping system at station gave the net return of 70976 Rs/ha with B: C ratio of 3.15. Soybean-Wheat cropping system at farm gave the net return of 119000 Rs/ha with B:C ratio of 3.38.
Intake and ruminal parameters of goats fed diets supplemented with vegetable oils

ABSTRACT The objective of this study was to evaluate the intake and ruminal parameters of goats fed diets supplemented with vegetable oils. Four rumen-cannulated Saanen goats were allocated to four treatments, which consisted of a control diet and diets with the inclusion of 30 g of canola, sunflower, or soybean oils per kilogram of diet dry matter (DM). The experiment lasted 40 days, which were divided into four 10-day periods. Forage intake was estimated using chromium oxide as an external [. ]
Convolutional Neural Networks based OSA Event Prediction from ECG Scalograms and Spectrograms

In this study, we conducted a comparative analysis of deep convolutional neural network (CNN) models in predicting Obstructive Sleep Apnea (OSA) using electrocardiograms. Unlike other studies in the literature, this study automatically extracts time-frequency features by using CNNs instead of manual feature extraction from ECG recordings. For this purpose, the proposed model generates scalogram and spectrogram representations by transforming preprocessed 30-sec ECG segments from time domain to the frequency domain using Continuous Wavelet Transform (CWT) and Short Time Fourier transform (STFT), respectively. We examined AlexNet, GoogleNet and ResNet18 models in predicting OSA events. The effect of transfer learning on success is also investigated. Based on the observed results, we proposed a new model that is found more effective in estimation. In total, 152 ECG recordings were included in the study for training and evaluation of the models. The prediction using scalograms immediately 30 seconds before potential OSA onsets gave the best performance with 82.30% accuracy, 83.22% sensitivity, 82.27% specificity and 82.95% positive predictive value. On the other hand, the prediction using spectrograms also provided up to 80.13% accuracy and 81.99% sensitivity on prediction. The results show that the proposed CNN model can be used as a good indicator to accurately predict OSA events using ECG signals.
Smart Collaborative Performance-Induced Parameter Identification Algorithms for Synchronous Reluctance Machine Magnetic Model

In rail transit traction, due to the remarkable energy-saving and low-cost characteristics, synchronous reluctance motors (SynRM) may be a potential substitute for traditional AC motors. However, in the parameter extraction of SynRM nonlinear magnetic model, the accuracy and robustness of the metaheuristic algorithm is restricted by the excessive dependence on fitness evaluation. In this paper, a novel probability-driven smart collaborative performance (SCP) is defined to quantify the comprehensive contribution of candidate solution in current population. With the quantitative results of SCP as feedback in-formation, an algorithm updating mechanism with improved evolutionary quality is established. The allocation of computing resources induced by SCP achieves a good balance between exploration and exploitation. Comprehensive experiment results demonstrate better effectiveness of SCP-induced algorithms to the proposed synchronous reluctance machine magnetic model. Accuracy and robustness of the proposed algorithms are ranked first in the comparison result statistics with other well-known algorithms.
CO2 Capture Performance Comparisons of Polyamines at Practical Concentrations for Use as Activators for Methyldiethanolamine for Natural Gas Sweetening

High-performance polyamines, namely, branched polyethylenimine (PEI-B), tetraethylenepentamine (TEPA), and piperazine (PZ), at concentrations of 0.1, 0.3, and 0.5 M were studied for use as activato.
Modelling Methods and Validation Techniques for CFD Simulations of PEM Fuel Cells

The large-scale adoption of fuel cells system for sustainable power generation will require the combined use of both multidimensional models and of dedicated testing techniques, in order to evolve the current technology beyond its present status. This requires an unprecedented understanding of concurrent and interacting fluid dynamics, material and electrochemical processes. In this review article, Polymer Electrolyte Membrane Fuel Cells (PEMFC) are analysed. In the first part, the most common approaches for multi-phase/multi-physics modelling are presented in their governing equations, inherent limitations and accurate materials characterisation for diffusion layers, membrane and catalyst layers. This provides a thorough overview of key aspects to be included in multidimensional CFD models. In the second part, advanced diagnostic techniques are surveyed, indicating testing practices to accurately characterise the cell operation. These can be used to validate models, complementing the conventional observation of the current–voltage curve with key operating parameters, thus defining a joint modelling/testing environment. The two sections complement each other in portraying a unified framework of interrelated physical/chemical processes, laying the foundation of a robust and complete understanding of PEMFC. This is needed to advance the current technology and to consciously use the ever-growing availability of computational resources in the next future.
Determination and optimization of ideal patient candidacy for anterior odontoid screw fixation

Background: Odontoid process fractures are one of the most common spine fractures, especially in patients over age 70. There is still much controversy over the ideal candidate for anterior odontoid screw fixation (AOSF), with outcomes affected by characteristics such as fracture morphology, nonideal body habitus, and osteoporosis. Therefore, this systematic review seeks to discuss the optimal criteria, indications, and adverse postoperative considerations when deciding to pursue AOSF. Methods: This investigation was conducted from experiential recall and article selection performed using the PubMed electronic bibliographic databases. The search yielded 124 articles that were assessed and filtered for relevance. Following the screening of titles and abstracts, 48 articles were deemed significant for final selection. Results: AOSF is often utilized to treat Type IIB odontoid fractures, which has been shown to preserve atlantoaxial motion, limit soft-tissue injuries/blood loss/vertebral artery injury/reduce operative time, provide adequate osteosynthesis, incur immediate spinal stabilization, and allow motion preservation of C1 and C2. However, this technique is limited by patient characteristics such as fracture morphology, transverse ligament rupture, remote injuries, short neck or inability to extend neck, barrel chested, and severe spinal kyphosis, in addition to adverse postoperative outcomes such as dysphagia and vocal cord paralysis. Conclusion: Due to the fact that odontoid fractures have a significant morbidity in elderly population, treatment with AOSF is generally recommended for this population with higher risk for nonoperative fusion. Considerations should be made to achieve fracture stability and fusion, while lowering the risk for operative and postoperative complications.
Dynamic Spatial Durbin Modeling (Case: Percentage of Poor Population in Indonesia 2010-2019)

The dynamic panel model assumes that each observation unit is independent of each other. But sometimes this assumption is violated, so there are spatial effects in the model. This study aimed to make percentage modeling of poverty in Indonesia using the Dynamic Spatial Durbin Model (DSDM). The data used in this study were secondary data obtained from the Statistics Indonesia in the period 2010-2019. The parameter estimation method used in this model was the Maximum Likelihood (ML). According to Moral-Benito, Allison and Williams the ML method has the best performance when used on panel data that has small cross-section data dimensions. The results of this study indicated that spatial dependence, time lag, variables of Poverty Gap Index, Poverty Severity Index and Logarithm of Expenditures per Capita affect poverty in Indonesia significantly. Other results showed that DSDM was able to explain the diversity in models at 95.6 %. This seemed higher when it’s compared to the Spatial Durbin Model (SDM). Thus, the result of the study proved that DSDM is the best model for modelling dynamic poverty data panel in Indonesia during 2010-2019.
The Association Between Obesity, Being Overweight and Socio-economic Status Among School-Age Children Living in Big Cities

Introduction: Obesity has become a serious health concern worldwide. Risk factors of obesity are different in urban and rural areas. The aim of this study was to determine the risk factors related to obesity and being overweight among children in low and high socio-economic groups in a big metropolitan city, Istanbul. Materials and Methods: A cross-sectional study was carried out on 490 schoolage children between 5 and 15 years. Low and high socio-economic groups were determined according to socio-economic status (SES). Socio-demographic characteristics of children were collected from the parents. Results: The effect of having frequent snacks rich in carbonhydrates (p=0,001) and sedentary lifestyles (p=0,001) on BMI was significant in both SES groups. In high SES group, BMI of the <10 years boys was significantly higher than that of the <10 years girls; Boys also had higher BMI at both age groups of either younger or older than 10 years. In low SES group, girls were significantly more overweight than boys. High family income, high paternal BMI and consuming energy rich products increased the obesity risk in children 1,560 times (OR: 1,560, %95 CI: 1,046-2,326), 2,015 times (OR: 2,015, %95 CI: 1,092-3,720), and 4,33 times (OR: 4,330, %95 CI: 2,897-6,472), respectively. Conclusions: As conclusion, high family income, high paternal BMI and consuming energy rich products incre-ased the obesity risk. We suggest that every community has own characteristics but boys tend to have high BMIs in families with high SES.
Determining Beta-Sheet Crystallinity in Fibrous Proteins by Thermal Analysis and Infrared Spectroscopy

We report a study of self-assembled beta-pleated sheets in B. mori silk fibroin films using thermal analysis and infrared spectroscopy. B. mori silk fibroin may stand as an exemplar of fibrous proteins containing crystalline beta-sheets. Materials were prepared from concentrated solutions (2−5 wt % fibroin in water) and then dried to achieve a less ordered state without beta-sheets. Crystallization of beta-pleated sheets was effected either by heating the films above the glass transition temperature (Tg) and holding isothermally or by exposure to methanol. The fractions of secondary structural components including random coils, alpha-helices, beta-pleated sheets, turns, and side chains were evaluated using Fourier self-deconvolution (FSD) of the infrared absorbance spectra. The silk fibroin films were studied thermally using temperature-modulated differential scanning calorimetry (TMDSC) to obtain the reversing heat capacity. The increment of the reversing heat capacity ΔCp0(Tg) at the glass transition fo.
Prediction of human activity intensity using the interactions in physical and social spaces through graph convolutional networks

ABSTRACT Dynamic human activity intensity information is of great importance in many location-based applications. However, two limitations remain in the prediction of human activity intensity. First, it is hard to learn the spatial interaction patterns across scales for predicting human activities. Second, social interaction can help model the activity intensity variation but is rarely considered in the existing literature. To mitigate these limitations, we proposed a novel dynamic activity intensity prediction method with deep learning on graphs using the interactions in both physical and social spaces. In this method, the physical interactions and social interactions between spatial units were integrated into a fused graph convolutional network to model multi-type spatial interaction patterns. The future activity intensity variation was predicted by combining the spatial interaction pattern and the temporal pattern of activity intensity series. The method was verified with a country-scale anonymized mobile phone dataset. The results demonstrated that our proposed deep learning method with combining graph convolutional networks and recurrent neural networks outperformed other baseline approaches. This method enables dynamic human activity intensity prediction from a more spatially and socially integrated perspective, which helps improve the performance of modeling human dynamics.
Sustainable Recycling of High-Strength Concrete as an Alternative to Natural Aggregates in Building Structures

The application of recycled coarse aggregates (RCA) in high-performance concrete (HPC) was analyzed in the article. In the paper, the behavior of HPC with coarse recycled aggregate and natural coarse aggregate (NCA) was compared. Short-term experiments were conducted, including concrete deformation, deflection, load bearing capacity, and cracking of beams. The analysis involved reinforced concrete T-beams made in 100% of RCA or NCA. The studies indicated that the beams with recycled aggregate are characterized by greater deflection and 7.6% lower load bearing capacity in comparison to the beams with NCA. Substitution of coarse natural aggregate with RCA reduced the compressive and tensile strengths by 20 and 26 (%), whereas and the modulus of elasticity was decreased by 15%.
Impactos da Adoção de Infraestruturas de Nuvem no Desenvolvimento de Pesquisas Acadêmicas

Resumo. Este trabalho apresenta uma proposta de estudo que tem como objetivo definir estratégias para racionalizar a adoção de nuvens computacionais para apoio à pesquisa acadêmica, determinando os modelos de custo necessários para implantação de uma solução, atendendo a uma comunidade federada de Instituições de Ensino e Pesquisa (IEP). O enfoque será dado considerando a realidade do Estado do Rio Grande do Sul, com um olhar sobre as vocações de pesquisa de suas instituições e a realidade de financiamentos de projetos. Dentre as contribuições esperadas para este trabalho, está a modelagem de diferentes configurações de nuvem, públicas, privadas ou híbridas, que possam atender as demandas do conjunto de IEPs do estado.
Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA

We selected the COVID-19 outbreak in the state of Oregon, USA as a system for developing a general geographically nuanced epidemiological forecasting model that balances simplicity, realism, and accessibility. Using the life history simulator HexSim, we inserted a mathematical SIRD disease model into a spatially explicit framework, creating a distributed array of linked compartment models. Our spatial model introduced few additional parameters, but casting the SIRD equations into a geographic setting significantly altered the system’s emergent dynamics. Relative to the non-spatial model, our simple spatial model better replicated the record of observed infection rates in Oregon. We also observed that estimates of vaccination efficacy drawn from the non-spatial model tended to be higher than those obtained from models that incorporate geographic variation. Our spatially explicit SIRD simulations of COVID-19 in Oregon suggest that modest additions of spatial complexity can bring considerable realism to a traditional disease model.
Method for Direct Determination of Glassy Phase Dissolution in Hydrating Fly Ash‐Cement System Using X‐ray Diffraction

A method for quantitative X-ray diffraction analysis is developed for direct determination of the glassy phase content of fly ash in a hydrating binary blend of cement and low-calcium, siliceous fly ash. The intensity contributions of the unhydrated glassy phase of fly ash and the amorphous reaction products to the intensity pattern of the total amorphous phase in the hydrating binary blend are obtained by decomposition of the total intensity signature as a sum of component pseudo Voigt (PV) peaks. An experimental program involving binary blends with three different low calcium siliceous fly ashes and two different curing temperatures is reported. The centers of the component PV peaks of the fly ash glassy phase fitted to the overall intensity pattern are found to be invariant. The glassy phase content of hydrating binary blends determined from the XRD method were found to agree well with the values obtained from a selective dissolution method.
Inactivation of Different Salmonella enteriditis Phage Types and Safety and Efficacy of Inactivated Products in Chicken

This study was conducted to inactivate Salmonella enteriditis phage types (SE pt) and to determine the safety and efficacy of inactivated SE pt in chickens. SE pt 1, 3A, 6A, 7, and 35 were inactivated and inoculated (0.20 mL) in 124 chickens divided into 6 groups (CV1, CV3A, CV6A, CV7, CV35, and CV0 as a control). Sampling was conducted on day 14 after inoculation (pi). Eight chickens from each group were separated on day 14 pi for oral challenge with 0.20 mL/chicken (1010 cfu/mL) SE pt 6A and designated CV1C, CV3AC, CV6AC, CV7C, CV35C, and CV0C as control chickens. On days 7 and 14 postchallenge (pc), 4 chickens from every group were sacrificed for sampling. There was no significant difference in the body weight between different groups. In challenged groups, there was no significant association between different tissues and isolation of Salmonella on days 7 and 14 pc. There was significance (p < 0.05) in isolation of Salmonella when CV0C group was compared with other challenged groups. Significance was not observed between different tissues with respect to induction of microscopic changes. Significance was not observed between day 7 pc and day 14 pc with respect to scoring of lesions induced. Clinical signs and gross lesions were also recorded. ELISA was applied. Only in CV3AC group, the mean antibody titer was 1359 on day 14 pc. The conclusion was that inactivated SE pt 3A and 6A were safe and efficacious for protection against Salmonella enteriditis infection in chickens.
The impact of IPSAS adoption on corruption in developing countries

This paper investigates whether the International Public Sector Accounting Standards (IPSAS) is a potential enabler or constrainer of corruption in developing countries. We employ the System Generalised Method of Moments on a sample of 77 developing countries between 2005-2017. We find that IPSAS is negatively and significantly associated with corruption, suggesting that the adoption of IPSAS helps in controlling corruption in developing countries. The results still hold after accounting for IPSAS experience and the adoption of other international accounting standards. However, in further analyses, we find that the negative impact of IPSAS on corruption is more pronounced for countries that have fully adopted the accrual-based IPSAS. This study, therefore, provides evidence to policymakers on why developing countries should adopt IPSAS, especially in the fight against corruption.
Construction of Pillared-Layer MOF as Efficient Visible-Light Photocatalysts for Aqueous Cr(VI) Reduction and Dye Degradation

By using a controllable pillared-layer method, a novel visible-light responsive metal–organic framework (MOF) photocatalyst NNU-36 has been rationally constructed. The synthesized NNU-36 is of broad-range visible light absorption and good chemical stability which are beneficial to its application of photocatalysis. Photocatalytic experiments reveal that NNU-36 is highly efficient for Cr(VI) reduction and dye degradation in aqueous solution under visible light irradiation. Control experiments show that the pH value is vital for Cr(VI) reaction, and meanwhile, the use of hole scavenger of methanol promotes the photocatalytic reduction significantly. It has been also demonstrated that NNU-36 is efficient for dye degradation, in which the introduction of hydrogen peroxide (H2O2) significantly enhances the photocatalytic efficiency of dye degradation. This study illustrates that the introduction of hole scavengers or oxidants in the MOF-mediated photocatalytic reaction is a feasible approach to enhance the cat.