ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Valuation of air pollution externalities: comparative assessment of economic damage and emission reduction under COVID-19 lockdown

Air pollution (AP) is one of the major causes of health risks as it leads to widespread morbidity and mortality each year. Its environmental impacts include acid rains, reduced visibility, but more importantly and significantly, it affects human health. The price tag of not managing AP is seen in the rise of chronic obstructive pulmonary disease (COPD), cardiovascular disease, and respiratory ailments like asthma and chronic bronchitis. But as the world battles the corona pandemic, COVID-19 lockdown has abruptly halted human activity, leading to a significant reduction in AP levels. The effect of this reduction is captured by reduced cases of morbidity and mortality associated with air pollution. The current study aims to monetarily quantify the decline in health impacts due to reduced AP levels under lockdown scenario, as against business as usual, for four cities-Delhi, London, Paris, and Wuhan. The exposure assessment with respect to pollutants like particulate matter (PM(2.5)and PM10), NO2, and SO(2)are evaluated. Value of statistical life (VSL), cost of illness (CoI), and per capita income (PCI) for disability-adjusted life years (DALY) are used to monetize the health impacts for the year 2019 and 2020, considering the respective period of COVID-19 lockdown of four cities. The preventive benefits related to reduced AP due to lockdown is evaluated in comparison to economic damage sustained by these four cities. This helps in understanding the magnitude of actual damage and brings out a more holistic picture of the damages related to lockdown.
Diagnostic protocols and newer treatment modalities for cluster headache

Cluster Headaches are one of the most arguably severe forms of primary headache syndrome that affects humans. Although it is relatively uncommon, it has a significant impact on the quality of life. It is a multifactorial disease that has risk factors ranging from seasonal changes, lifestyle habits to genetics. It occurs in 2 forms- Episodic and Chronic, each having its well-defined Diagnostic Criteria. Moreover, Cluster Headache has an exhaustive list of options for both Preventive and Abortive treatment. This article focuses on Cluster Headache, its pathophysiology, risk factors, differentials, and its diverse treatment modalities. In this study, an all-language literature search was conducted on Medline, Cochrane, Embase, and Google Scholar till October 2021. The following search strings and Medical Subject Headings (MeSH) terms were used: "Cluster Headache," "Triptans," "Neuromodulation," and "Migraine." We explored the literature on Cluster Headache for its epidemiology, pathophysiology, the role of various genes and how they bring about the disease as well as its episodic and chronic variants, and treatment options. Although we have a wide variety of options for Preventive and Abortive therapy, newer more effective pharmacological and non-pharmacological interventions are being developed, and must be integrated into new treatment protocols.
Cerebellar Microstructural Abnormalities in Parkinson's Disease: a Systematic Review of Diffusion Tensor Imaging Studies

Diffusion tensor imaging (DTI) is now having a strong momentum in research to evaluate the neural fibers of the CNS. This technique can study white matter (WM) microstructure in neurodegenerative disorders, including Parkinson's disease (PD). Previous neuroimaging studies have suggested cerebellar involvement in the pathogenesis of PD, and these cerebellum alterations can correlate with PD symptoms and stages. Using the PRISMA 2020 framework, PubMed and EMBASE were searched to retrieve relevant articles. Our search revealed 472 articles. After screening titles and abstracts, and full-text review, and implementing the inclusion criteria, 68 papers were selected for synthesis. Reviewing the selected studies revealed that the patterns of reduction in cerebellum WM integrity, assessed by fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity measures can differ symptoms and stages of PD. Cerebellar diffusion tensor imaging (DTI) changes in PD patients with "postural instability and gait difficulty" are significantly different from "tremor dominant" PD patients. Freezing of the gate is strongly related to cerebellar involvement depicted by DTI. The "reduced cognition," "visual disturbances," "sleep disorders," "depression," and "olfactory dysfunction" are not related to cerebellum microstructural changes on DTI, while "impulsive-compulsive behavior" can be linked to cerebellar WM alteration. Finally, higher PD stages and longer disease duration are associated with cerebellum white matter alteration depicted by DTI. Depiction of cerebellar white matter involvement in PD is feasible by DTI. There is an association with disease duration and severity and several clinical presentations with DTI findings. This clinical-imaging association may eventually improve disease management.
Effect of magnetized water on blood indices and histomorphometric parameters of intestinal sections of Japanese quail

A two-way experimental design was used to demonstrate the physiological effects of magnetized water and sex on blood indices and histomorphometric parameters of Japanese quail intestine sections. Red blood cell count (RBCs), packed cell volume (PCV), hemoglobin concentration (Hb), thrombocytes, white blood cell count (WBCs), and WBC differentiation were investigated. A total of 450 unsexed Japanese quail were randomized into three groups (45/replicate; 3 replicates; 135/group). As a monitoring group, the first group was given untreated tap water to drink. The two others were consumed magnetized water that were subjected to an electrical magnetic field with a power of 1 Tesla (10,000 Gauss) and 2 Tesla (20,000 Gauss), respectively. The treatments had a significant (p ≤ 0.05) effect on thrombocytes and Hb. Sex showed significant (p ≤ 0.05) differences for RBCs and PCV at 42 days of age. At different ages, significant effects were observed on histomorphometric parameters of the Japanese quail intestinal tract. It may be inferred that the influence of magnetized water, up to 1 Tesla, was positive on the haematological and histomorphometric parameters of the Japanese quail intestinal tract by augmenting the haematological measurements, which were within a normal range and increasing the surface area of the villus.
Cry1Ac Protoxin Confers Antitumor Adjuvant Effect in a Triple-Negative Breast Cancer Mouse Model by Improving Tumor Immunity

The Cry1Ac protoxin from Bacillus thuringiensis is a systemic and mucosal adjuvant, able to confer protective immunity in different infection murine models and induce both Th1 and TCD8+ cytotoxic lymphocyte responses, which are required to induce antitumor immunity. The Cry1Ac toxin, despite having not being characterized as an adjuvant, has also proved to be immunogenic and able to activate macrophages. Here, we investigated the potential antitumor adjuvant effect conferred by the Cry1Ac protoxin and Cry1Ac toxin in a triple negative breast cancer (TNBC) murine model. First, we evaluated the ability of Cry1Ac proteins to improve dendritic cell (DC) activation and cellular response through intraperitoneal (i.p.) coadministration with the 4T1 cellular lysate. Mice coadministered with the Cry1Ac protoxin showed an increase in the number and activation of CD11c+MHCII- and CD11c+MHCII+low in the peritoneal cavity and an increase in DC activation (CD11c+MHCII+) in the spleen. Cry1Ac protoxin increased the proliferation of TCD4+ and TCD8+ lymphocytes in the spleen and mesenteric lymph nodes (MLN), while the Cry1Ac toxin only increased the proliferation of TCD4+ and TCD8+ in the MLN. Remarkably, when tested in the in vivo TNBC mouse model, prophylactic immunizations with 4T1 lysates plus the Cry1Ac protoxin protected mice from developing tumors. The antitumor effect conferred by the Cry1Ac protoxin also increased specific cytotoxic T cell responses, and prevented the typical tumor-related decrease of T cells (TCD3+ and TCD4+) as well the increase of myeloid-derived suppressor cells (MDSC) in spleen. Also in the tumor microenvironment of mice coadministered twice with Cry1Ac protoxin immunological improvements were found such as reductions in immunosupressive populations (T regulatory lymphocytes and MDSC) along with increases in macrophages upregulating CD86. These results show a differential antitumor adjuvant capability of Cry1Ac proteins, highlighting the ability of Cry1Ac protoxin to enhance local and systemic tumor immunity in TNBC. Finally, using a therapeutic approach, we evaluated the coadministration of Cry1Ac protoxin with doxorubicin. A significant reduction in tumor volume and lung metastasis was found, with increased intratumoral levels of tumor necrosis factor-α and IL-6 with respect to the vehicle group, further supporting its antitumor applicability.
Vector mosquito image classification using novel RIFS feature selection and machine learning models for disease epidemiology

Every year about one million people die due to diseases transmitted by mosquitoes. The infection is transmitted to a person when an infected mosquito stings, injecting the saliva into the human body. The best possible way to prevent a mosquito-borne infection till date is to save the humans from exposure to mosquito bites. This study proposes a Machine Learning (ML) and Deep Learning based system to detect the presence of two critical disease spreading classes of mosquitoes such as the Aedes and Culex. The proposed system will effectively aid in epidemiology to design evidence-based policies and decisions by analyzing the risks and transmission. The study proposes an effective methodology for the classification of mosquitoes using ML and CNN models. The novel RIFS has been introduced which integrates two types of feature selection techniques - the ROI-based image filtering and the wrappers-based FFS technique. Comparative analysis of various ML and deep learning models has been performed to determine the most appropriate model applicable based on their performance metrics as well as computational needs. Results prove that ETC outperformed among the all applied ML model by providing 0.992 accuracy while VVG16 has outperformed other CNN models by giving 0.986 of accuracy.
Energy, exergy and exergoenvironmental analyses of a sugarcane bagasse power cogeneration system

One of the strategies to reduce the environmental impacts associated with electricity is to employ renewable resources such as biomass or even waste. However, the evaluation of the sustainability of a power plant depends on the development of several analyses, which should encompass thermodynamic and environmental parameters. Energy, exergy, and exergoenvironmental assessments are carried out for a sugarcane bagasse cogeneration system, along with a Life Cycle Assessment for the Brazilian sugarcane bagasse, employing the Ecoindicator 99 method. The specific environmental impacts of electricity and steam are 6.023 mPt/MJ and 4.038 mPt/MJ, respectively, and the boiler feed pump and radiator presented the highest average environmental impact per exergy of fuel and product, respectively. The component with the highest exergoenvironmental factor was the furnace (60.32%), demonstrating margins for benefits in the formation of pollutants and destruction of exergy. Exergoenvironmental assessments can be utilized to support the adoption of more efficient (although more complex) cogeneration systems, especially in the aftermath of the COVID-19 crisis.
Uneven energy transitions: Understanding continued energy peripheralization in rural communities

This paper problematizes the uneven nature of low carbon energy transitions in the context of uneven geographical development and core/periphery asymmetries. It explores the impacts of transition for peripheral communities lacking political power and agglomerative advantages. While decentralised developments that emerge with energy transition promise to bring new opportunities to remote areas, factors of economic and political inequalities render those opportunities socially and spatially segregated. Exploring experiences of rural and exurban communities in South Wales, the paper establishes links between low carbon transition and its actually existing implications on the ground. It demonstrates that even if having an abundance of natural resource and physical space to harness low carbon energy, many rural communities are trapped in the chronic positions of energy peripheralization.
Renewable energy and environmental quality: A second-generation panel evidence from the Sub Saharan Africa (SSA) countries

This study employs dynamic panel data for 34 Sub Saharan Africa (SSA) countries for the period 1984-2016 to estimate the effects of renewable energy on environmental quality measured by three indicators, namely, per capita CO2 emissions, energy intensity (EI) and Aggregate National Savings (ANS). The study leveraged a battery of second-generation econometric tests and estimation and causality methods to obtain the coefficients between the regressed and the regressors. Results reveal that use of renewable energy reduces CO2 emissions and energy intensity while it enhances ANS. Economic growth still seems to be expensive for the region as it stimulates CO2 emissions. However, it has a positive effect on ANS. As expected, fossil fuels exacerbate CO(2 )emissions and energy intensity. FDI is found to be detrimental for the environment of SSA region with its positive significant coefficient on CO2 emissions. Financial development is reported to reduce CO2 emissions. Some causal links between variables are also noted.
Landslide Characterization Applying Sentinel-1 Images and InSAR Technique: The Muyubao Landslide in the Three Gorges Reservoir Area, China

Landslides are a common natural hazard that causes casualties and unprecedented economic losses every year, especially in vulnerable developing countries. Considering the high cost of in-situ monitoring equipment and the sparse coverage of monitoring points, the Sentinel-1 images and Interferometric Synthetic Aperture Radar (InSAR) technique were used to conduct landslide monitoring and analysis. The Muyubao landslide in the Three Gorges Reservoir area in China was taken as a case study. A total of 37 images from March 2016 to September 2017 were collected, and the displacement time series were extracted using the Stanford Method for Persistent Scatterer (StaMPS) small baselines subset method. The comparison to global positioning system monitoring results indicated that the InSAR processing of the Muyubao landslide was accurate and reliable. Combined with the field investigation, the deformation evolution and its response to triggering factors were analyzed. During this monitoring period, the creeping process of the Muyubao landslide showed obvious spatiotemporal deformation differences. The changes in the reservoir water level were the trigger of the Muyubao landslide, and its deformation mainly occurred during the fluctuation period and high-water level period of the reservoir.
The relationship between innovation and sustainability: A meta-analytic study

The objective of this study is to analyze the effects of innovation on the performance of organizational sustainability, as well as on the environmental, economic and social dimensions. The search was done using various data collection sources, such as Scopus, WoS, Science Direct, Emerald, Sage, Wiley Online Library and Proquest. The research findings indicate that innovation positively impacts sustainability performance. The strongest and most favorable correlations occurred between economic innovation and sustainability performance and between environmental innovation and sustainability performance. Thus, the main contributions of the study are associated with: a) the existence of a positive and strong relationship between innovation and sustainability performance; b) evidence of innovation effect size on sustainability performance (combined effect size coefficient at r = 0.529 (p-value <0.000)); c) an identification of the gaps in the scientific literature evaluating the effect of innovation on the sustainability of organizations; and d) the fail-safe Rosenthal value is 37,800, which indicates that the number of unpublished documents required to make the observed effect size insignificant is too large. Future studies can advance with meta analyzes that adopt moderating and mediating constructions to assess the relationship between innovation and performance in sustainability. (C) 2020 Elsevier Ltd. All rights reserved.
Strength and durability performance of geopolymer binder of ambient cured alkali-activated MSW rejected waste and GGBFS mixes

Municipal solid waste (MSW) is being generated every day, and its safe disposal is one of the major environmental challenges nowadays. The main focus of this research is to examine the usability of the soil-like inorganic component of MSW, named MSW rejected waste, as a geopolymer binder. In this study, the effect of mutual replacement of MSW rejected waste with ground granulated blast furnace slag (GGBFS) at 10% interval on the synthesis of geopolymer binder with reference to density, alkali concentration, and curing period is studied by conducting compressive strength, permeability, and durability tests. The design of mixes follows, according to their pre-determined compaction parameters, optimum moisture content, and maximum dry density. The curing conditions were found to be significant in affecting the properties of the geopolymer. The effect of acid environment on strength properties of geopolymer mixes has also been studied. The unconfined compressive strength, pulse wave velocity, water absorption, and microstructural analysis have been performed on designed mixes to identify the optimized design of the mixtures. Results showed that the strength increased with the increment of GGBFS percentage and increment of concentration of sodium hydroxide (NaOH) up to 8 M.
Dual Role of Mo6 S8 in Polysulfide Conversion and Shuttle for Mg-S Batteries

Magnesium-Sulfur batteries are one of most appealing options among the post-lithium battery systems due to its potentially high energy density, safe and sustainable electrode materials. The major practical challenges are originated from the soluble magnesium polysulfide intermediates and their shuttling between the electrodes, which cause high overpotentials, low sulfur utilization, and poor Coulombic efficiency. Herein, a functional Mo6 S8 modified separator is designed to effectively address these issues. Both the experimental results and density functional theory calculations show that the electrochemically active Mo6 S8 layer has a superior adsorption capability of polysulfides and simultaneously acts as a mediator to accelerate the polysulfide conversion kinetics. Remarkably, the magnesium-sulfur cell assembled with the functional separator delivers a high specific energy density (942.9 mA h g-1 in the 1st cycle) and can be cycled at 0.2 C for 200 cycles with a Coulombic efficiency of 96%. This work demonstrates a new design concept toward high-performance metal-sulfur batteries.
Using a self-adaptive grey fractional weighted model to forecast Jiangsu's electricity consumption in China

The remarkable prediction performance of electricity consumption has always assumed particular importance for electric power utility planning and economic development. On account of the complexity and uncertainty of the electricity system, this paper establishes a self-adaptive grey fractional weighted model to predict Jiangsu's electricity consumption, which efficiently enhances the prediction quality of electricity consumption. This newly constructed grey model introduces the fractional weighted coefficients to design a novel initial condition. Compared with the old one in the conventional grey models, the newly optimized initial condition has a flexible structure, which has advantages in capturing the dynamic characteristics of the electricity consumption observations. In addition, to further promote the forecasting precision, the adjustable fractional weighted coefficients and corresponding time parameter of the initial condition are estimated by utilizing the Particle Swarm Algorithm (PSO). Furthermore, five competing models are employed to forecast Jiangsu's electricity consumption in China, which certifies the validity of the established model. Experimental results illustrate that the newly designed model has significant advantages over other five competing models. According to the forecasted results, electricity consumption in Jiangsu Province is expected to reach 6778 billion kilowatt-hours in 2020, while the growth rate will fall down by 1.11%. Therefore, several proposals are made for decision-makers. (C) 2019 Elsevier Ltd. All rights reserved.
Activity of Ligustrum vulgare L extracts against acute pancreatitis in murine models by regulation of p38 MAPK and NF-κB signaling pathways

Pancreatitis is a fatal disease associated with significant mortality and morbidity. At present, no specific treatment is available for pancreatitis and the patients are mainly treated with supportive medication. The need for specific antipancreatitic chemotherapy is an urgent medical obligation. In the current study, protective effects of the methanolic extract of the Ligustrum vulgare berries were investigated in the rat model of acute pancreatitis. Acute pancreatitis (AP) was induced in the male Sprague-Dawley (SD) rats by cerulein injection. Fruit extract of L. vulgare L extract was prepared using the methanol. Treatment effects of L. vulgare were evaluated in AP rats. Serum levels of lipase, amylase, proinflamatory cytokines (TNF-α, IL-6, TL-1β), lipid peroxidase (LPO), myeloperoxidase (MPO) were determined. Histological changes in the pancreas were assessed. L. vulgare treatment prevented the increase in serum amylase and lipase levels, reduced the disease progression in pancreas, and reduced the serum levels of tumour necrosis factor (TNF)-α, interleukin (IL)-6, and IL-1β in AP rats. Moreover, L. vulgare significantly suppressed pancreatic edema, inhibited oxidative damage (MPO activity and SOD activity), and inhibited the expression of NF-κB/p65 and activation (phosphorylation) of the inhibitor of NF-κB (IκBα) and p38 MAPKs. Histological examinations showed that L. vulgare significantly reduced the inflammatory and fibrotic changes. The results indicated the potent pancreato-protective effects of L. vulgare in AP.