ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Modelling water yield with the InVEST model in a data scarce region of northwest China

The Bosten Lake basin is an important arid region of northwest China, and has exhibited a declining trend in both lake area and level of water during recent decades. Reliable information on water yield, an important attribute of available water resources in a region, is vital to assess the potential for socio-economic development. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model is applied here to simulate water yield in the Bosten Lake basin. The spatial and temporal dynamics of water yield, and the response of water yield to land use and precipitation change, are analysed for the period 1985 to 2015. The results show that, overall, water yield increased during 1985-2015, and that the magnitude of change was greater in the eastern part of the region. The water yield capacity, positively correlated with precipitation, is highest under grassland vegetation and lowest in cultivated and unused land. The paper demonstrates that statistical downscaling and climate reanalysis data can be used in the InVEST model to improve the accuracy of simulated water yield in data scarce regions.
Production, purification and characterization of a novel antithrombotic and anticoagulant serine protease from food grade microorganism Neurospora crassa

A novel thrombolytic enzyme was produced by food grade microorganism Neurospora crassa using agro-industrial by-products as substrates. Process parameters were optimized using Plackett-Berman and Box-Benhken design. Under the optimized fermentation conditions, high fibrinolytic activity of 403.59 U/mL was obtained. It was purified with a specific activity of 3572.4 U/mg by ammonium sulfate precipitation and SP Sepharose chromatography. The molecular weight of the enzyme was approximately 32 kDa. It exhibited maximum activity at 40 °C and pH 7.4. Its activity was enhanced by Cu2+, Na+, Zn2+, and completely inhibited by phenylmethanesulfonyl fluoride, soybean trypsin inhibitor, aprotinin, which indicates it could be a serine protease. The enzyme could degrade fibrin clot directly without the need of plasminogen activator, and effectively cleaved Aα, Bβ, γ chains of fibrinogen. It could inhibit the formation of blood clots in vitro and acts as an anticoagulant. Compared to heparin the purified enzyme showed extended anticoagulant activity. Blood clots were dissolved effectively and dissolution rate was increased with time. Based on these results, this novel enzyme has the potential to be developed as a thrombolytic agent.
The changing landscape of relapsed and/or refractory multiple myeloma (MM): fundamentals and controversies

The increase in the number of therapeutic alternatives for both newly diagnosed and relapsed/refractory multiple myeloma (RRMM) patients has widened the clinical scenario, leading to a level of complexity that no algorithm has been able to cover up to date. At present, this complexity increases due to the wide variety of clinical situations found in MM patients before they reach the status of relapsed/refractory disease. These different backgrounds may include primary refractoriness, early relapse after completion of first-line therapy with latest-generation agents, or very late relapse after chemotherapy or autologous transplantation. It is also important to bear in mind that many patient profiles are not fully represented in the main randomized clinical trials (RCT), and this further complicates treatment decision-making. In RRMM patients, the choice of previously unused drugs and the number and duration of previous therapeutic regimens until progression has a greater impact on treatment efficacy than the adverse biological characteristics of MM itself. In addition to proteasome inhibitors, immunomodulatory drugs, anti-CD38 antibodies and corticosteroids, a new generation of drugs such as XPO inhibitors, BCL-2 inhibitors, new alkylators and, above all, immunotherapy based on conjugated anti-BCMA antibodies and CAR-T cells, have been developed to fight RRMM. This comprehensive review addresses the fundamentals and controversies regarding RRMM, and discusses the main aspects of management and treatment. The basis for the clinical management of RRMM (complexity of clinical scenarios, key factors to consider before choosing an appropriate treatment, or when to treat), the arsenal of new drugs with no cross resistance with previously administered standard first line regimens (main phase 3 clinical trials), the future outlook including the usefulness of abandoned resources, together with the controversies surrounding the clinical management of RRMM patients will be reviewed in detail.
The impact of energy price on CO2 emissions in China: A spatial econometric analysis

Excessive greenhouse gas emissions pose a global environmental concern. This paper examines the impact of energy price on China's CO2 emissions based on an extended STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) structural human ecology model. We utilize Chinese provincial data from 2002 to 2016 and apply the spatial panel data techniques to explicitly consider spatial correlations and spillover effects between observations. Our results show that energy price has a significant negative impact on China's CO2 emissions after controlling for other economic and energy market factors and spatial correlations of these variables. We identify a significant direct impact of the focal province's price change on CO2 emissions and an indirect effect exerted by energy price changes in adjacent provinces. Such spatial spillover effects are also observed in other determinants identified in the extended STIRPAT model. We also document a path dependent pattern in China's provincial CO2 emissions with last period CO2 emissions influencing the current CO2 emission levels. Our results show that the negative impact of energy price on CO2 emissions remains qualitatively the same after incorporating the influence of previous period CO2 emissions. Our results are also robust to the inclusion of lagged energy price measures, alternative spatial economic models, and alternative spatial weight matrices. Overall, our paper highlights the role of energy market in curbing CO2 emissions and promoting sustainable economic development. (C) 2019 Elsevier B.V. All rights reserved.
Analysis on the carbon emission peaks of China's industrial, building, transport, and agricultural sectors

Carbon emission peak has become a focus of political and academic concern in global community since the launch of Kyoto Protocol. China, as the largest carbon emitter, has committed to reaching the carbon peak by 2030 in Paris Agreement. This ambitious national goal requires the endeavors of individual sectors, particularly those carbon-intensive ones. Predicting the sectoral peaks under current endeavors and understanding driving forces for the carbon emission changes in the past years are substantial for guiding the allocation of the country's future efforts. In the past studies contextualized in China, the prediction of its carbon peaks seldom appeared at the sectoral level, which is considered as a research gap. Therefore, this study predicts the peaks at four carbon pillar sectors (i.e. industrial, building, transport and agricultural sectors) and identifies the driving forces for the carbon emission changes of them. This study hypothesized Carbon Kuznets curve (CKC) as the theoretical model for predicting the peaks and used Logarithmic mean Divisia index (LMDI) as the method to identify the driving forces. The results show that the carbon emission in the country will peak in 2036, six years later than the agreed year. The lateness of the national peak can be attributed to the significant lateness of three pillar sectors' peaks, occurring in 2031 for the industrial sector, 2035 for the building sector, 2043 for the transport sector, peak for the agricultural sector occurs four years earlier in 2026 though. Furthermore, the results show that carbon emission is significantly driven by the booming economic output and inhibited by decreasing energy intensity, but the slight fluctuation of energy structure plays a minor role in the four sectors. Policy adjustments are proposed for effectively and efficiently urging the on-time occurrence of the national peak. (C) 2019 Elsevier B.V. All rights reserved.
PCM integrated glass in glass tube solar collector for low and medium temperature applications: Thermodynamic & techno-economic approach

In present work, techno-economic and thermodynamic analysis of an ETC with/without PCM has been undertaken. The results approved that for all selected flow rates, ETC/S obtained higher energy and exergy efficiencies in comparison to the ETC/WS design. The maximum attained value of average daily energy efficiency for ETC/S and ETC/WS was 78.36% and 54.10% respectively with a high flow rate (24 L/h). Also, at this flow rate, ETC/S and ETC/WS attained peak value of average daily exergy efficiency of 23.15% and 20.06% respectively. The average daily energy efficiency of ETC/S was found to be 53.46%, 30.87%, and 44.85% higher in comparison to ETC/WS for low (8 L/h), medium (16 L/h) and high (24 L/h) flow rate respectively. Hence, the integration of SA (stearic acid) as energy storage material with HP-ETC not only stored the thermal energy but also enhanced the system performance. Furthermore, the techno-economic study revealed that the cost of production of hot water by ETC/S has been found to be lowest compared with ETC/WS and electric geyser. This analysis showed that ETC/S system has a promising potential in terms of supply of hot water from low to medium temperature range at a cheaper rate at lower payback period. (C) 2020 Elsevier Ltd. All rights reserved.
Co-Occurrence of Reading and Writing Difficulties: The Application of the Interactive Dynamic Literacy Model

This article presents the application of the interactive dynamic literacy (IDL) model (Kim, 2020b) toward understanding difficulties in learning to read and write. According to the IDL model, reading and writing are part of communicative acts that draw on largely shared processes and skills as well as unique processes and skills. As such, reading and writing are dissociable but interdependent systems that have hierarchical, interactive, and dynamic relations. These key tenets of the IDL model are applied to the disruption of reading and writing development to explain co-occurrence of reading-writing difficulties using a single framework. The following hypotheses are presented: (a) co-occurrence between word reading and spelling and handwriting difficulties; (b) co-occurrence of dyslexia with written composition difficulties; (c) co-occurrence between reading comprehension and written composition difficulties; (d) co-occurrence of language difficulties with reading difficulties and writing difficulties; (e) co-occurrence of reading, writing, and language difficulties with weak domain-general skills or executive functions such as working memory and attentional control (including attention-deficit/ hyperactivity disorder [ADHD]); and (f) multiple pathways for reading and writing difficulties. Implications are discussed.
Comprehensive Management of Cardiovascular Risk Factors for Adults With Type 2 Diabetes: A Scientific Statement From the American Heart Association

Cardiovascular disease remains the leading cause of death in patients with diabetes. Cardiovascular disease in diabetes is multifactorial, and control of the cardiovascular risk factors leads to substantial reductions in cardiovascular events. The 2015 American Heart Association and American Diabetes Association scientific statement, "Update on Prevention of Cardiovascular Disease in Adults With Type 2 Diabetes Mellitus in Light of Recent Evidence," highlighted the importance of modifying various risk factors responsible for cardiovascular disease in diabetes. At the time, there was limited evidence to suggest that glucose-lowering medications reduce the risk of cardiovascular events. At present, several large randomized controlled trials with newer antihyperglycemic agents have been completed, demonstrating cardiovascular safety and reduction in cardiovascular outcomes, including cardiovascular death, myocardial infarction, stroke, and heart failure. This AHA scientific statement update focuses on (1) the evidence and clinical utility of newer antihyperglycemic agents in improving glycemic control and reducing cardiovascular events in diabetes; (2) the impact of blood pressure control on cardiovascular events in diabetes; and (3) the role of newer lipid-lowering therapies in comprehensive cardiovascular risk management in adults with diabetes. This scientific statement addresses the continued importance of lifestyle interventions, pharmacological therapy, and surgical interventions to curb the epidemic of obesity and metabolic syndrome, important precursors of prediabetes, diabetes, and comorbid cardiovascular disease. Last, this scientific statement explores the critical importance of the social determinants of health and health equity in the continuum of care in diabetes and cardiovascular disease.
Risk management in distributed wind energy implementing Analytic Hierarchy Process

Distributed wind power has received growing attention in recent years. However, high risks remain in its investigation, which severely hindered its development. This study attempts to gather and identify risk factors in distributed wind power through literature reviews and rank the risks based on expert opinions. Based on previous literature, we classified risk for distributed wind power investment into four types, namely the political risks, economic risks, social risks, and technical risks. Analytic Hierarchy Process (AHP) method is used to assess risks in the life cycle of the distributed wind farm. Political, Economic, Social and Technical methodology as the criteria hierarchy is introduced to classify the identified risks as the sub-criteria hierarchy in the AHP model. The result shows that the risk of changes in electricity price policy is the most critical impact on the distributed wind power system to obtain sustainable development and make profits. Therefore, the government needs to provide a long-term vision of electricity price policy to promote the development of distributed wind projects. (C) 2020 Elsevier Ltd. All rights reserved.
Optimization of the utilization of deep borehole heat exchangers

Deep-borehole heat exchangers (DBHE) are generally coaxial pipes installed in deep boreholes and has become an alternative approach to utilize geothermal energy. Since the performance of the DBHE system can be affected by several parameters, it is important to optimize the design of parameters for the DBHE. In this paper, based on the analytical method, we carried out the sensitivity analysis of DBHE design parameters, including outer pipe diameter, inner pipe diameter, flow rate, outer pipe materials, grout materials, and borehole depth during continuous operation for 4 months. The sensitivity analysis results indicate that the heat extraction rate can be significantly affected by outer pipe diameter, borehole depth, and flow rate. The effects of grout materials, inner pipe diameter and outer pipe materials are of second-order. Finally, an optimization method based on the lowest Average Energy Cost index was proposed to optimize these DBHE design parameters under different geological conditions. Given the cost in this study, a combination scheme of all the optimal parameters is given for different depth wells under different geological conditions.
Incorporating synthetic aperture radar and optical images to investigate the annual dynamics of anthropogenic impervious surface at large scale

The area, distribution, and temporal dynamics of anthropogenic impervious surface (AIS) at large scale are significant for environmental, ecological and socio-economic studies. Remote sensing has become an important tool for monitoring large scale AIS, while it remains challenging for accurate extraction of AIS using optical datasets alone due to the high diversity of land covers over large scale. Previous studies indicated the complementary use of synthetic aperture radar (SAR) to improve the AIS estimation, while most of them were limited to local and small scales. The potential of SAR for large scale AIS mapping is still uncertain and under-explored. In this study, first, a machine learning framework incorporating both optical and SAR data based on Google Earth Engine platform was developed for mapping and analyzing the annual dynamics of AIS in China. Feature-level fusion for SAR and optical data across large scale was tested applicable considering the backscattering coefficients, texture measures and spectral characteristics. Improved accuracy (averaged 2% increased overall accuracy and averaged 4% increased Kappa coefficient) and better delineation between the bright impervious surface and bare land was observed comparing with using optical data alone. Second, comprehensive assessment was conducted using high-resolution samples from Google Earth, census data from China Statistic Yearbook and benchmark datasets from the GlobeLand30 and GHSL, demonstrating the feasibility and reliability of the proposed method and results. Last but not the least, we analyzed the spatial and temporal patterns of AIS in China from national, regional and provincial levels.
Exploring the effect of economic and environment factors on PM2.5 concentration: A case study of the Beijing-Tianjin-Hebei region

Air pollution, especially haze pollution is a serious environment problem that directly affects the sustainable development in China. Identifying the key factors affecting PM2.5 concentration and the interaction mechanism between them through quantitative analysis can greatly help a city devise PM2.5 pollution control strategy. Using the geographical detector model, we quantitative measured 13 cities in the Beijing-Tianjin-Hebei region's social factors and their interaction impacts on PM2.5 concentration in 2016. In the analysis process, factor analysis method is used to separate the factors preliminary. According to the results, the factors mainly divided into two categories, i.e. economic factor and environment factor. R&D ranks top in the studied cities in terms of factor detection results, presenting closely relationship between PM2.5 concentration and R&D. We also find the interaction between any two factors all enhance impact on PM2.5 concentration than any one alone. This study provided a scientific basic and guidance for measure the driving degree of social factors and their interaction effects.
The dynamics of dominance: open questions, challenges and solutions

Although social hierarchies are recognized as dynamic systems, they are typically treated as static entities for practical reasons. Here, we ask what we can learn from a dynamical view of dominance, and provide a research agenda for the next decades. We identify five broad questions at the individual, dyadic and group levels, exploring the causes and consequences of individual changes in rank, the dynamics underlying dyadic dominance relationships, and the origins and impacts of social instability. Although challenges remain, we propose avenues for overcoming them. We suggest distinguishing between different types of social mobility to provide conceptual clarity about hierarchy dynamics at the individual level, and emphasize the need to explore how these dynamic processes produce dominance trajectories over individual lifespans and impact selection on status-seeking behaviour. At the dyadic level, there is scope for deeper exploration of decision-making processes leading to observed interactions, and how stable but malleable relationships emerge from these interactions. Across scales, model systems where rank is manipulable will be extremely useful for testing hypotheses about dominance dynamics. Long-term individual-based studies will also be critical for understanding the impact of rare events, and for interrogating dynamics that unfold over lifetimes and generations. This article is part of the theme issue 'The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies'.
Influence of Scion/Rootstock reciprocal effects on post-harvest and metabolomics regulation in stored peaches

Peach is an important stone fruit crop cultivated at commercial scale in Pakistan. While, appropriate selection of rootstock has significant impact on the quality of peach fruit. Therefore, in the current study the influence of three rootstocks viz. 'GF-677', 'Peshawar Local' and 'Swat Local' were evaluated on the quality of 'Flordaking' peaches following cold storage during two consecutive years. The fruit from these rootstocks were kept at 0 °C for five weeks were studied for various fruit physical (weight loss, colour, firmness) and biochemical (pH, soluble solids content (SSC), titratable acidity (TA), SSC:TA ratio, fruit juice pH, sugars (total, reducing and non-reducing sugars), ascorbic acid (vitamin C) and free radicals scavenging activities) were evaluated. During both years, fruit harvested form trees grafted on 'GF-677' exhibited reduced fruit weight loss, changes in Chroma (C*) and highest fruit firmness, Lightness (L*), ascorbic acid contents and radical scavenging activities as compared to fruit harvested from tree grafted on other rootstocks. In conclusion, the post-harvest quality of scion 'Flordaking' peach fruit was significantly influenced and best quality can be obtained when it is grafted on 'GF-677' rootstock.
Effects of urban forms on CO2 emissions in China from a multi-perspective analysis

Effectively evaluating the effects of urban forms on CO2 emissions has become a hot topic in socioeconomic sustainable development; however, few studies have been able to explore the urban form-CO2 emission relationships from a multi-perspective view. Here, we attempted to analyze the relationships between urban forms and CO2 emissions in 264 Chinese cities, with explicit consideration of the government policies, urban area size, population size, and economic structure. First, urban forms were calculated using the urban land derived from multiple-source remote sensing data. Second, we collected and processed CO2 emissions and three control variables. Finally, a correlation analysis was implemented to explore whether and to what extent the spatial patterns of urban forms were associated with CO2 emissions. The results show that urban form irregularity had a more significant impact on CO2 emissions in low-carbon pilot cities than in non-pilot cities. The impact of the complexity of urban forms on CO2 emissions was relatively significant in the small- and large-sized cities than in the medium-sized cities. Moreover, urban form complexity had a significant correlation with CO2 emissions in all of the cities, the level of which basically increased with the population size. This study provides scientific bases for use in policy-making to prepare effective policies for developing a low-carbon economy with consideration of the associations between urban forms and CO2 emissions in different scenarios.