ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Moving beyond velocity derivatives; using global positioning system data to extract sequential movement patterns at different levels of rugby league match-play

This study aims to (a) quantify the movement patterns during rugby league match-play and (b) identify if differences exist by levels of competition within the movement patterns and units through the sequential movement pattern (SMP) algorithm. Global Positioning System data were analysed from three competition levels; four Super League regular (regular-SL), three Super League (semi-)Finals (final-SL) and four international rugby league (international) matches. The SMP framework extracted movement pattern data for each athlete within the dataset. Between competition levels, differences were analysed using linear discriminant analysis (LDA). Movement patterns were decomposed into their composite movement units; then Kruskal-Wallis rank-sum and Dunn post-hoc were used to show differences. The SMP algorithm found 121 movement patterns comprised mainly of "walk" and "jog" based movement units. The LDA had an accuracy score of 0.81, showing good separation between competition levels. Linear discriminant 1 and 2 explained 86% and 14% of the variance. The Kruskal-Wallis found differences between competition levels for 9 of 17 movement units. Differences were primarily present between regular-SL and international with other combinations showing less differences. Movement units which showed significant differences between competition levels were mainly composed of low velocities with mixed acceleration and turning angles. The SMP algorithm found 121 movement patterns across all levels of rugby league match-play, of which, 9 were found to show significant differences between competition levels. Of these nine, all showed significant differences present between international and domestic, whereas only four found differences present within the domestic levels. This study shows the SMP algorithm can be used to differentiate between levels of rugby league and that higher levels of competition may have greater velocity demands.Highlights This study shows that movement patterns and movement units can be used to investigate team sports through the application of the SMP frameworkOne hundred and twenty-one movement patterns were found to be present within rugby league match-play, with the walk- and jog-based movement units most prevalent. No movement pattern was unique to a single competition level.Further analysis revealed that the majority of movement units analysed had significant differences between international and domestic rugby league, whereas only four movement units (i.e. f,m,n,q) had significant differences within the two domestic rugby league levels.International rugby league had higher occurrences of the movement patterns consisting of higher velocity movement units (ie. T,S,y). This suggests that international rugby league players may need greater high velocity exposure in training.
Assessment of parabolic trough solar collector assisted solar still at various saline water mediums via energy, exergy, exergoeconomic, and enviroeconomic approaches

The performance of parabolic trough solar collector (PTC) coupled with single slope solar still at various water mediums is assessed based on productivity, energy, exergy, exergoeconomic, and enviroeconomic methodologies and also Energy payback time. Six solar still systems are considered; conventional solar still (CSS), CSS coupled with PTC (CSS + PTC), CSS contains steel wire mesh in the basin (CSS + WM), CSS contains wire mesh and coupled with PTC (CSS + WM + PTC), CSS contains sand in the basin (CSS + SD), and CSS contains sand and integrated with PTC (CSS + SD + PTC). Experiments are conducted under hot and cold climate conditions of Sohag city, Egypt. Findings show that the maximum freshwater yield in summer is achieved in case of CSS + SD + PTC with an increase of 1.21% compared to CSS and 102.1% compared to CSS + SD + PTC in winter. The maximum increase of the energy and exergy output per year compared to CSS is achieved in case of CSS + SD + PTC of 216.6% and 325%, respectively. Incorporation PTC with the still for all studied water mediums is found promising in terms of energy payback time, cost and freshwater yield compared to CSS without PTC. The exergoeconomic and environmental parameters of the active systems are found more effective related to those of passive systems. (C) 2020 Elsevier Ltd. All rights reserved.
Performance optimization through response surface methodology of an integrated biomass gasification based combined heat and power plant employing solid oxide fuel cell and externally fired gas turbine

Efficient energy utilization from renewable energy sources can resolve multidimensional problems of environ-mental pollution, energy security and reduction in conventional fossil fuel reserves. In this circumstance, bio-mass-based energy systems can play an important role. In this study, modeling and analysis of an advanced integrated co-generation system comprising of a biomass gasifier, a solid oxide fuel cell module and a heat recovery steam generator have been carried out for generating power and process heat. The proposed system has been evaluated through exergetic and economic methods. Furthermore, response surface methodology has been applied for the multi-objective optimization of the system. Current density, pressure ratio of the secondary air compressor and saturation pressure of steam at the heat recovery steam generator are considered as the inputs for predicting the optimum performance parameters i.e., exergy efficiency, levelized cost of energy and levelized cost of exergy. Regression models, generated from the analysis of variance tool, are found to have a very high degree of accuracy for the exergy efficiency, levelized cost of energy and levelized cost of exergy. The optimal levels of the current density, pressure ratio and saturation pressure of steam are found to be 5101.01 A/m(2), 4 and 12 bar, respectively. At this optimum condition, exergy efficiency, levelized cost of energy and levelized cost of exergy of the cogeneration system are 46.58%, 0.0454 $/kWh and 0.0657$/kWh, respectively. Composite de-sirability is found to be on the higher side (around 0.90), which indicate that the setting seems to attain fa-vorable results for all the responses as a whole.
A new measure of Italian hidden energy poverty

As highlighted by European policymakers and academic research, the global economic crisis of 2008 emphasized the energy poverty phenomenon. A number of households have had to considerably reduce their energy expenditure but the traditional criteria adopted to calculate energy poverty are not able to measure their number. Placed in this framework, the paper aims to define a new measure of hidden energy poverty suitable to identify which Italian households restrain their energy consumption due to their inability to afford energy services. A review of the available energy poverty metrics supports the definition of a new indicator that is able to include hidden energy-poor consumers considering some key peculiarities such as the poor energy efficiency of buildings, the poverty situation, low energy consumption and sensitivity to the climate. Using data from the Household Budget Survey provided by the Italian National Institute of Statistics in 2018, the newly identified indicator supports the assessment of the percentage of Italian households in hidden energy poverty and supplies useful insight to policymakers in their effort to support vulnerable consumers.
Coupling of economic growth and reduction in carbon emissions at the efficiency level: Evidence from China

Our work provides a comprehensive investigation of the coupling between the efficiency of economic growth and the efficiency of carbon emissions reduction in China, and makes a distinction between the coupling over the long-run and the short-run. Our estimates suggested significant evidence of coupling between economic growth and efficiency in carbon emissions reduction in the long-run, but China's economic growth still increased carbon emissions at the aggregate level. In the short-run, coupling effects were different across provinces that were at different stages of economic development. Provinces with low- and high-stages of development saw positive short-run coupling, but provinces at the intermediate stage of development saw the contrary, which resulted in an obvious "U" shaped relationship between short-run coupling effects and real GDP per capita. Finally, our findings provide an economic rationale for differentiated low-carbon policies. (C) 2020 Elsevier Ltd. All rights reserved.
Chronic subdural haematoma: the role of peri-operative medicine in a common form of reversible brain injury

Epidemiological studies project a significant rise in cases of chronic subdural haematoma over the next 20 years. Patients with this condition are frequently older and medically complex, with baseline characteristics that may increase peri-operative risk. The intra-operative period is only a small portion of a patient's total hospital stay, with a majority of patients in the United Kingdom transferred between institutions for their surgical and rehabilitative care. Definitive management remains surgical, but peri-operative challenges exist which resonate with other surgical cohorts where multidisciplinary working has become the gold standard. These include shared decision-making, medical optimisation, the management of peri-operative anticoagulation and the identification of key points of equipoise for examination in the future trials. In this narrative review, we use a stereotyped patient journey to provide context to the recent literature, highlighting where multidisciplinary expertise may be required to optimise patient care and maximise the benefits of surgical management. We discuss the triage, pre-operative optimisation, intra-operative management and immediate postoperative care of patients undergoing surgery for a chronic subdural haematoma. We also discuss where adjunctive medical management may be indicated. In so doing, we present the current and emerging evidence base for the role of an integrated peri-operative medicine team in the care of patients with a chronic subdural haematoma.
Investigating the EKC hypothesis for China: the role of economic complexity on ecological footprint

This empirical study aims to test the validity of the environmental Kuznets curve (EKC) hypothesis for China within the framework of (Narayan and Narayan Energy Policy 38(1):661-666, 2010) approach. To this end, the study employs a recently developed Fourier ARDL procedure and time-varying causality test over the period 1965-2016 to analyze the short- and long-term relationships between economic growth, economic complexity index, energy consumption, and ecological footprint. The findings of the Fourier ARDL procedure confirm the existence of cointegration among the series. Moreover, the results of this study demonstrate that energy consumption and ecological complexity increase ecological footprint in both the short- and long term. However, the short-term elasticity of economic growth is smaller than the long-term elasticity, implying that the EKC hypothesis is not valid for China. This finding is robust as it is confirmed by the time-varying causality test. The overall results illustrate that economic complexity has an increasing impact on ecological footprint, and economic growth is not effective to solve environmental problems in China. Therefore, the Chinese government should encourage a more environmentally friendly production process and cleaner technologies in exports to reduce environmental pollution.
Valuing wetland ecosystem services based on benefit transfer: A meta-analysis of China wetland studies

While wetlands contribute significantly to ecosystem services, their nature as a public good implies that the public sector, rather than the market, values their conservation, utilization, and trade-offs among various ecosystem services. Thus, the valuation of wetlands and their ecosystem services is important for policy makers. This study conducts a meta-analysis of valuation research on China's wetlands based on 133 independent studies involving 146 cases published during 2000-2017. The study evaluates the weight of different factors in the existing valuation results, discusses the errors of benefit transfer, and applies the benefit transfer method to evaluate the ecosystem services of Yancheng wetland in Jiangsu province. The primary results are as follows. Wetland size influences wetland service valuation results most significantly. The value of all ecosystem services increases as wetland area increases with an average elasticity of 0.83. Factors such as economic and social development level, wetland type, research time, literature source, and valuation methods have impacts only on several individual service types. It is feasible to apply the meta-analysis results to benefit transfer. Compared with the per unit area value model, which is more stable in transfer errors, the wetland service value has better goodness of fit. Therefore,in conducting benefit transfer, the wetland service value models are suggested. (C) 2020 Elsevier Ltd. All rights reserved.
Is negativity bias intuitive for liberals and conservatives?

Previous research suggests that conservatives (right-wingers) tend to show more negativity bias than liberals (left-wingers) in several tasks. However, the majority of these studies are based on correlational findings and do not provide information on the cognitive underpinnings of this tendency. The current research investigated whether intuition promotes negativity bias and mitigates the ideological asymmetry in this domain in three underrepresented, non-western samples (Turkey). In line with the previous literature, we defined negativity bias as the tendency to interpret ambiguous faces as threatening. The results of the lab experiment revealed that negativity bias increases under high-cognitive load overall. In addition, this effect was moderated by the participants' political orientation (Experiment 1). In other words, when their cognitive resources were depleted, liberals became more like conservatives in terms of negativity bias. However, we failed to conceptually replicate this effect using time-limit manipulations in two online preregistered experiments during the COVID-19 pandemic, where the baseline negativity bias is thought to be already at peak. Thus, the findings provide no strong evidence for the idea that intuition promotes negativity bias and that liberals use cognitive effort to avoid this perceptual bias.
Role of mesonephric contribution to mouse testicular development revisited

The role of the mesonephros in testicular development was re-evaluated by growing embryonic day 11.5 (E11.5) mouse testes devoid of mesonephros for 8-21 days in vivo under the renal capsule of castrated male athymic nude mice. This method provides improved growth conditions relative to previous studies based upon short-term (4-7 days) organ culture. Meticulous controls involved wholemount examination of dissected E11.5 mouse testes as well as serial sections of dissected E11.5 mouse testes which were indeed shown to be devoid of mesonephros. As expected, grafts of E11.5 mouse testes with mesonephros attached formed seminiferous tubules and also contained mesonephric derivatives. Grafts of E11.5 mouse testes without associated mesonephros also formed seminiferous tubules and never contained mesonephric derivatives. The consistent absence of mesonephric derivatives in grafts of E11.5 mouse testes grafted alone is further proof of the complete removal of the mesonephros from the E11.5 mouse testes. The testicular tissues that developed in grafts of E11.5 mouse testes alone contained canalized seminiferous tubules composed of Sox9-positive Sertoli cells as well as GENA-positive germ cells. The seminiferous tubules were surrounded by α-actin-positive myoid cells, and the interstitial space contained 3βHSD-1-positive Leydig cells. Grafts of E11.5 GFP mouse testes into wild-type hosts developed GFP-positive vasculature indicating that E11.5 mouse testes contain vascular precursors. These results indicate that the E11.5 mouse testis contains precursor cells for Sertoli cells, Leydig cells, myoid cells and vasculature whose development and differentiation are independent of cells migrating from the E11.5 mesonephros.
The financial development-environmental degradation nexus in the United Arab Emirates: the importance of growth, globalization and structural breaks

This article revisits the nexus between financial development and environmental degradation by incorporating economic growth, electricity consumption and economic globalization in the CO2 emissions function for the period 1975Q(I)-2014Q(IV) in the United Arab Emirates. We apply structural break and cointegration tests to examine unit root and cointegration between the variables. Further, the article also uses the Toda-Yamamoto causality test to investigate the causal relationship between the variables and tests the linkages of the robustness of causality by following the innovative accounting approach. Our empirical analysis shows cointegration between the series. Financial development increases CO2 emissions. Economic growth is positively linked with environmental degradation. Electricity consumption improves environmental quality. Economic globalization affects CO2 emissions negatively. The relationship between financial development and CO2 emissions is U-shaped and inverted N-shaped. Further, financial development leads to environmental degradation, and environmental degradation in turn leads to financial development in the Granger sense.
Classifier Fusion for Detection of COVID-19 from CT Scans

The coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. COVID-19 is found to be the most infectious disease in last few decades. This disease has infected millions of people worldwide. The inadequate availability and the limited sensitivity of the testing kits have motivated the clinicians and the scientist to use Computer Tomography (CT) scans to screen COVID-19. Recent advances in technology and the availability of deep learning approaches have proved to be very promising in detecting COVID-19 with increased accuracy. However, deep learning approaches require a huge labeled training dataset, and the current availability of benchmark COVID-19 data is still small. For the limited training data scenario, the CNN usually overfits after several iterations. Hence, in this work, we have investigated different pre-trained network architectures with transfer learning for COVID-19 detection that can work even on a small medical imaging dataset. Various variants of the pre-trained ResNet model, namely ResNet18, ResNet50, and ResNet101, are investigated in the current paper for the detection of COVID-19. The experimental results reveal that transfer learned ResNet50 model outperformed other models by achieving a recall of 98.80% and an F1-score of 98.41%. To further improvise the results, the activations from different layers of best performing model are also explored for the detection using the support vector machine, logistic regression and K-nearest neighbor classifiers. Moreover, a classifier fusion strategy is also proposed that fuses the predictions from the different classifiers via majority voting. Experimental results reveal that via using learned image features and classification fusion strategy, the recall, and F1-score have improvised to 99.20% and 99.40%.
Combined multi-objective optimization and robustness analysis framework for building integrated energy system under uncertainty

The optimal design of building integrated energy system is sensitive to the variation of uncertain parameters. For addressing the tradeoff of uncertainty and optimality-robustness, this study proposes a combined multi-objective optimization and robustness analysis framework for optimal design of building integrated energy system. The proposed framework includes two parts. In the optimization part, on the basis of scenario generation for capturing the uncertainties of renewable energy sources and energy demands, two-stage multi-objective stochastic mixed-integer nonlinear programming is conducted to optimize the system's economic and environmental objectives. Two decision-making methods are introduced to identify the final optimum solution from the obtained Pareto frontier. In the robustness-analysis part, a combined Monte Carlo simulation and optimization method is implemented to verify the robustness of the optimal solutions. The two parts of the framework are integrated to investigate the case of a hotel in Beijing, China. The results indicate that compared with the stochastic model, the deterministic model underestimates the annual total cost. Achieving economic and environmental optimum is conflicting and needs a trade-off through decision making. Moreover, in the robustness analysis, an acceptable robustness value is identified, considering both the selected objectives and the operation constraints' probability of failure. The Shannon-entropy-based final optimum solution exhibits the best comprehensive performance, with an annual total cost of $695 x 10(3)/year, an annual carbon emissions of 2100 tons/year, and an 8.81% probability of failure.
Designing hydro-energy led economic growth for pollution abatement: evidence from BRICS

Overutilized hydro-energy production through non-sustainable mode is detrimental for both the economy and the environment. Intermittent consumption of hydro-energy from non-sustainable production methods may induce deleterious impacts in terms of rapid pollution in the economy. This paper investigates the impacts of hydro-power consumption upon pollution for 5 BRICS countries from 1965 to 2019. Our balanced panel model shows that infrequent usages of hydro-power consumption led to more pollution over the year. This relation is also further explained by considering several macroeconomic factors, in the context of the growth scenario. Our empirical findings show that an increase in population and consequent rise in per capita income have exhibited positive impacts on pollution. Even, improved industrialized led production and investment in these economies contribute heavily towards pollution and declined environmental standards. Our results further state that intermittent usages of natural resources by population in terms of rising ecological footprint have resulted in higher emission intensity over the year. These findings underscore how rising hydro-power energy consumption has led to the rising pollution amidst the growth scenario in BRICS economies.