Extremophilic bacteria are important groups of extremophilic organisms that have been studied during the last years. They are considered as a source of enzymes due to great diversity and can survive under extreme conditions. Many enzymes produced by these microorganisms are of great importance and have found applications in several industries. Due to their activity and stability under extreme conditions, these enzymes offer new alternatives for current biotechnological and industrial applications. They have a wide range of potential uses and have been a nuclear subject of many different investigations. To date, some of the enzymes produced by extremophilic bacteria are currently being assessed thier industrials applications. Despite, benefits that present these enzymes, their potentials remain largely unexplored. These enzymes pose new opportunities for new line of research, and biotechnological applications. This review provides a summary on diversity and biotechnological and industrial applications of some enzymes produced by extremophilic bacteria.

Hydroxychloroquine, a known antiviral metabolite of chloroquine, is increasingly used along with antibiotic azithromycin for the treatment of COVID-19 infection. In about one month India, the world’s largest manufacturer, delivered hydroxychloroquine for treating COVID-19 to over 50 countries. The therapy is being used across the world both for patients staying at home at the early phase of symptoms, as well as for patients hospitalized. We summarize achievements as of late April 2020, review possible modes of action and suggest avenues for the quick scale-up of production of hydroxychloroquine.

Heavy metals and organic pollutants are ubiquitous environmental pollutants affecting the quality of soil, water and air. Over the past 5 decades, many strategies have been developed for the remediation of polluted water. Strategies involving aquatic plant use are preferable to conventional methods. In this study, an attempt was made to provide a brief review on recent progresses in research and practical applications of phytoremediation for water resources with the following objectives: (1) to discuss the toxicity of toxic chemicals pollution in water to plant, animals and human health (2) to summarise the physicochemical factors affecting removal of toxic chemicals such as heavy metals and organic contaminants in aqueous solutions by aquatic plants; (3) to summarise and compare the removal rates of heavy metals and organic contaminants in aqueous solutions by diverse aquatic plants; and (4) to summarise chemometric models for testing aquatic plant performance. More than 20 aquatic plants specie have been used extensively while duckweed (L. minor), water hyacinth (Eichhornia crassipes), water lettuce (P. stratiotes) are the most common. Overall, chemometrics for performance assessment reported include: Growth rate (GR), Growth rate inhibition (% Inhibition), Metal uptake (MU), translocation/transfer factor (TF), bioconcentration factor (BCF), Percent metal uptake (% MU), Removal capacity (RC) and Tolerance index (TI) while absorption rate have been studied using the sorption kinetics and isotherms models such as pseudo-first-order (PFO), pseudo-second-order (PSO), Freundlich, Langmuir and Temkin. Using modeling and interpretation of adsorption isotherms for performance assessment is particularly good and increases level of accuracy obtained from adsorption processes of contaminant on plant. Conclusion was drawn by highlighting the gap in knowledge and suggesting key future areas of research for scientists and policymakers.

We are witnessing a progressive divestment of some institutions with strong traditions and skills in physical modelling and their consequent impoverishment, to the detriment of numerical modelling. For many reasons, the economic imperatives and the exponential growth of computational means and numerical methods should certainly not be excluded. In this work, we aimed to highlight the new requirements of the recent sophisticated developments in physical modelling, precisely due to the new needs imposed on them by mathematical and numerical modelling and the growing risks in civil construction works. In this context, reflections are reported, justified by scientific and real-world examples, on the need for maintenance and reinforcement of investments in physical modelling, both to support the scientific community and to design buildings of significant economic, social and environmental impact.

The Novel Coronavirus (COVID-19) is a positive-sense single-stranded RNA ((+)ssRNA) virus. The COVID-19 Main Proteases play very important role in the propagation of the Novel Coronavirus (COVID-19). It has already killed more than 8000 people around the world and thousands of people are getting infected every day. Therefore, it is very important to identify a potential inhibitor against COVID-19 Main Proteases to inhibit the propagation of the Novel Coronavirus (COVID-19). We have applied a drug repurposing approach of computational methodology, depending on the synergy of molecular docking and virtual screening techniques, aimed to identify possible potent inhibitors against Novel Coronavirus (COVID-19) from FDA approved antiviral compounds and from the library of active phytochemicals. On the basis of recently resolved COVID-19 Main Protease crystal structure (PDB:6LU7), the library of 100 FDA approved antiviral compounds and 1000 active components of Indian Medicinal Plants extracted for screening against COVID-19 Main Protease. The compounds were further screened using Pyrex virtual screening tool and then best inhibitors, top 19 compounds optimally docked to the COVID-19 Main Protease structure to understand the participation of specific amino acids with inhibitors at active sites. Total 19 best compounds were identified after screening based on their highest binding affinity with respect to the other screened compounds. Out of 19, 6 best compounds were further screened based on their binding affinity and best ADME properties. Nelfinavir exhibited highest binding energy -8.4 kcal/mol and strong stability with the TRP207, ILE281, LEU282, PHE3, PHE291, GLN127, ARG4, GLY283, GLU288, LYS5, LYS137, TYR126, GLY138, TYR126, SER139 and VAL135 amino acid residues of COVID-19 Main Protease participating in the interaction at the binding pocket. In addition to Nelfinavir (-8.4), Rhein (-8.1), Withanolide D (-7.8), Withaferin A (-7.7), Enoxacin (-7.4), and Aloe-emodin (-7.4) also showed good binding affinity and best ADME properties. Our findings suggest that these compounds can be used as potential inhibitors against COVID-19 Main Protease, which could be helpful in inhibiting the propagation of the Novel Coronavirus (COVID-19). Moreover, further in vitro and in vivo validation of these findings would be very helpful to bring these inhibitors to next level study.

Bacteriophages can provide alternative measures for the control of E. coli O157:H7 that is currently an emerging food-borne pathogen of severe public health concern. This study was aimed at characterising E. coli O157:H7 specific phages as potential biocontrol agents for these pathogens. Fifteen phages were isolated and screened against 69 environmental E. coli O157:H7. Only 3 phages displayed broad lytic spectra against environmental shiga toxin-producing E. coli O157:H7 strains. These 3 lytic phages were designated V3, V7 and V8. Subsequent characterization indicated that they displayed very high degree of similarities despite isolation from different locations. Transmission Electron microscopy (TEM) of the phages revealed that they all had isometric heads of about 73 – 77 nm in diameter and short tails ranging from 20 - 25 nm in diameter. Phages V3, V7 and V8 were assigned to the family Podoviridae based on their morphology. Pulsed field gel electrophoresis (PFGE) genome estimation of the 3 phages demonstrated identical genome sizes of ~ 69 nm. The latent periods of these phages were 20 min, 15 min, and 20 min for V3, V7 and V8 respectively while the burst sizes were 374, 349 and 419 PFU/ infected cell respectively. While all the phages were relatively stable over a wide range of salinity, temperatures and pH values, their range of infectivity or lytic profile was rather narrow on environmental E. coli O157:H7 strains isolated from cattle faeces. This study showed that the Podoviridae bacteriophages are the dominant E. coli O57:H7-infecting phages harboured in cattle faeces in the North-West Province of South Africa and due to their favourable characteristics can be exploited in the formulation of phage cocktails for the bio-control of E. coli O157:H7 in meat and other meat products.

This paper gives an overview of the large-scale tectonic styles encountered in orogens worldwide. Thin-skinned and thick-skinned tectonics represent two end member styles recognized in mountain ranges. Both styles are encountered in former passive margins of continental plates. Thick-skinned style including the entire crust and possibly the lithospheric mantle are associated with intracontinental contraction. Delamination of subducting continental crust and horizontal protrusion of upper plate crust into the opening gap occurs in the terminal stage of continent-continent collision. Continental crust thinned prior to contraction is likely to develop relatively thin thrust sheets of crystalline basement. A true thin-skinned type requires a detachment layer of sufficient thickness. Thickness of the décollement layer as well as the mechanical contrast between décollement layer and detached cover control the style of folding and thrusting within the detached cover units. In subduction-related orogens, thin- and thick-skinned deformation may occur several hundreds of kilometers from the plate contact zone. Basin inversion resulting from horizontal contraction may lead to the formation of basement uplifts by the combined reactivation of pre-existing normal faults and initiation of new reverse faults. In most orogens thick-skinned and thin-skinned structures both occur and evolve with a pattern where nappe stacking propagates outward and downward

There has been a growing awareness of the need to implement environmentally friendly operations in the hotel industry, but most studies focus on guest behaviors. Only a few studies investigate employees’ willingness to comply with hotels’ green practices. This study seeks to further the investigation from the human resource perspective. Using alumni from a tourism and hospitality programs, this study collected 233 responses. The study hypothesizes that the employees’ green ability consisting of environmental awareness, environmental knowledge, and environmental skill creates a positive impact on hotels’ green ability. The results indicate that employees contribute approximately a fifth of hotels’ ability to implement greener practices.

Long-haul COVID-19 illness first gained widespread recognition among social support groups and later in scientific and medical communities. This illness is mysterious as it affects COVID-19 survivors at all levels of disease severity, even younger adults and children. While the precise definition may be lacking, the defining symptoms are fatigue, dyspnea, and headache that last for months after hospital discharge. The less typical symptoms may include cognitive impairments, chest and joint pains, myalgia, smell and taste dysfunctions, cough, mood changes, and gastrointestinal and cardiac issues. Presently, there is limited literature discussing the possible pathophysiology, risk factors, and treatments in long-haul COVID-19, which the current review aims to address. In brief, long-haul COVID-19 may be driven by long-term lung and brain damage and unresolved inflammation from multiple sources. The associated risk factors may include female sex, more than five early symptoms, early dyspnea, and specific biomarkers like D-dimer. While only rehabilitation training has been useful for long-haul COVID-19, therapeutics repurposed from mast cell activation syndrome, myalgic encephalomyelitis/chronic fatigue syndrome, and pulmonary fibrosis also hold potential. In sum, this review hopes to provide the current understanding of what is known about long-haul COVID-19.

Coronaviruses are an extensive family of viruses that can cause disease in both animals and humans. The current classification of coronaviruses recognizes 39 species in 27 subgenera that belong to the family Coronaviridae. From those, at least seven coronaviruses are known to cause respiratory infections in humans. Four of these viruses can cause common cold-like symptoms, while others that infect animals can evolve and become infectious to humans. Three recent examples of this viral jumps include SARS CoV, MERS-CoV and SARS CoV-2 virus. They are responsible for causing severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and the most recently discovered coronavirus disease during 2019 (COVID-19).COVID-19, a respiratory disease caused by the SARS-CoV-2 virus, was declared a pandemic by the World Health Organization (WHO) on 11 March 2020. The rapid spread of the disease has taken the scientific and medical community by surprise. Latest figures from 14 April 2020 show more than 2 million people had been infected with the virus, causing more than 120,000 deaths in over 210 countries worldwide. The large amount of information we receive every day concerning this new disease is so abundant and dynamic that medical staff, health authorities, academics and the media are not able to keep up with this new pandemic. In order to offer a clear insight of the extensive literature available, we have conducted a comprehensive literature review of the SARS CoV-2 Virus and the Coronavirus Diseases 2019 (COVID-19).

Wetlands are recognized as one of the world’s most valuable natural resources. With the increasing world population, human demands on wetland resources for agricultural expansion and urban development continue to increase. In addition, global climate change has pronounced impacts on wetland ecosystems through alterations in hydrological regimes. To better manage and conserve wetland resources, we need to know the distribution and extent of wetlands and monitor their dynamic changes. Wetland maps and inventories can provide crucial information for wetland conservation, restoration, and management. Geographic Information System (GIS) and remote sensing technologies have proven to be useful for mapping and monitoring wetland resources. Recent advances in geospatial technologies have greatly increased the availability of remotely sensed imagery with better and finer spatial, temporal, and spectral resolution. This chapter presents an introduction to the uses of GIS and remote sensing technologies for wetland mapping and monitoring. A case study is presented to demonstrate the use of high-resolution light detection and ranging (LiDAR) data and aerial photographs for mapping prairie potholes and surface hydrologic flow pathways.

The emerging use of visualization techniques in pathology and microbiol- ogy has been accelerated by machine learning (ML) approaches towards image preprocessing, classification, and feature extraction in an increasingly complex series of datasets. Modern Convolutional Neural Network (CNN) architectures have developed into an umbrella of vast image reinforcement and recognition methods, including a combined classification-localization of single/multi-object featured images. As a subtype neural network, CNN cre- ates a rapid order of complexity by initially detecting borderlines, edges, and colours in images for dataset construction, eventually capable in mapping intricate objects and conformities. This paper investigates the disparities between Tensorflow object detection APIs, exclusively, Single Shot Detector (SSD) Mobilenet V1 and the Faster RCNN Inception V2 model, to sample computational drawbacks in accuracy-precision vs. real time visualization capabilities. The situation of rapid ML medical image analysis is theoretically framed in regions with limited access to pathology and disease prevention departments (e.g. 3rd world and impoverished countries). Dark field mi- croscopy datasets of an initial 62 XML-JPG annotated training files were processed under Malaria and Syphilis classes. Model trainings were halted as soon as loss values were regularized and converged.

In this working paper we intended to address the emergence of what, potentially, will be a central concept in the very near future, Society 5.0 and that arises politically in (with) following the implementation of the concept of Industry 4.0. Society 5.0 proposes to deepen the potential of the individual-technology relationship in the promotion of the improvement of the quality of life of all people through a super smart society, is an extremely recent concept as a guiding social development that can have a profound impact in societies at all levels, such as quality of life and sustainability. It is a presentation that is based on very recent3 publications, but which also has a prospective component, which always generates some indetermination and uncertainty. Also, for this reason, it is a contribution that seeks above all else to contribute to this very urgent and necessary discussion.

Proteins possess complex three-dimensional structures, and these structures are stable only within specific ranges of temperature which mostly correspond to the temperature ranges of the host organisms. However, few exceptional proteins, called heat-stable proteins, are stable at temperatures that are substantially higher than those tolerated by the host organisms themselves. Most of the heat-stable proteins possess heat stability to perform their functions at high temperatures, but some of them are intrinsically heat-stable due to their structure. Heat-stable proteins are usually divided into three or four groups depending upon the intricacies of their structures and thermal behaviors. Their peculiar property, i.e. heat-stability, makes them very valuable in applications such as polymerase chain reaction, industrial processes requiring high temperature, and protein engineering. Heat-stability also makes it feasible to purify such proteins, from the rest of the heat-labile proteins, using a simple heat-treatment method. Moreover, heat treatment can be used as a combined cell-lysis and protein purification step which, as compared to conventional methods, can result in a higher yield of heat-stable proteins. Furthermore, some special heat-stable proteins, i.e. intrinsically disordered proteins (which include the proteins involved in important neurodegenerative diseases), need heat-treatment step, in some cases, as the only way for their successful purification and study. Hence, this paper provides a first-ever comprehensive review of all major aspects of heat-stable proteins, i.e., their structure, evolution, classification, significance, and heat-treatment mediated purification.

Background: In 80% of patients, COVID-19 presents as mild disease^1,2. 20% of cases develop severe (13%) or critical (6%) illness. More severe forms of COVID-19 present as clinical severe acute respiratory syndrome, but include a T-predominant lymphopenia³, high circulating levels of proinflammatory cytokines and chemokines, accumulation of neutrophils and macrophages in lungs, and immune dysregulation including immunosuppression⁴. Methods: All major SARS-CoV-2 proteins were characterized using an amino acid residue variation analysis method. Results predict that most SARS-CoV-2 proteins are evolutionary constrained, with the exception of the spike (S) protein extended outer surface. Results were interpreted based on known SARS-like coronavirus virology and pathophysiology, with a focus on medical countermeasure development implications. Findings: Non-neutralizing antibodies to variable S domains may enable an alternative infection pathway via Fc receptor-mediated uptake. This may be a gating event for the immune response dysregulation observed in more severe COVID-19 disease. Prior studies involving vaccine candidates for FCoV^5,6 SARS-CoV-1^7-10 and Middle East Respiratory Syndrome coronavirus (MERS-CoV) ¹¹ demonstrate vaccination-induced antibody-dependent enhancement of disease (ADE), including infection of phagocytic antigen presenting cells (APC). T effector cells are believed to play an important role in controlling coronavirus infection; pan-T depletion is present in severe COVID-19 disease³ and may be accelerated by APC infection. Sequence and structural conservation of S motifs suggests that SARS and MERS vaccine ADE risks may foreshadow SARS-CoV-2 S-based vaccine risks. Autophagy inhibitors may reduce APC infection and T-cell depletion^{12 13}. Amino acid residue variation analysis identifies multiple constrained domains suitable as T cell vaccine targets. Evolutionary constraints on proven antiviral drug targets present in SARS-CoV-1 and SARS-CoV-2 may reduce risk of developing antiviral drug escape mutants. Interpretation: Safety testing of COVID-19 S protein-based B cell vaccines in animal models is strongly encouraged prior to clinical trials to reduce risk of ADE upon virus exposure.

Over the past few decades, aircraft Ground Handling Operations (GHO) have been investigated by numerous researchers. Some aspects of GHO have been more focused on than others due to their importance in the GH processes. For instance, GHO performance has been tackled from different perspectives while workers and vehicles allocation suffer from the lack of research in the area. This paper is a literary review of the research that has been conducted in different areas of GHO. It sheds light on GHO performance, resource allocation and scheduling, operations scheduling, vehicle routing, and workers and vehicles allocation.

Liver cirrhosis is a chronic disease that is characterized by the presence of fibrosis and regeneration of nodules in the liver whose consequences are the development of portal hypertension and liver failure. Cirrhosis arises from a wide variety of chronic diseases, which progresses slowly after years or decades. Liver cirrhosis is a public health problem. It is usually associated with viral hepatitis, consumption of alcohol, metabolic syndrome, autoimmune processes, storage diseases, toxic substances, and medications. Cirrhosis is the fourteenth most common cause of death in adults throughout the world, the fourth in Europe and the ninth in the United States. The prevalence of this disease is underestimated because it is symptomatic it is not diagnosed in initial stages, and it usually goes to the decompensated stage at a rate of 5 to 7% per year. We review here the epidemiology, pathophysiology, etiology, and diagnosis of liver cirrhosis.

The Internet of Things (IoT) is one of the most widely used technologies today, and it has a significant effect on our lives in a variety of ways, including social, commercial, and economic aspects. In terms of automation, productivity, and comfort for consumers across a wide range of application areas, from education to smart cities, the present and future IoT technologies hold great promise for improving the overall quality of human life. However, cyber-attacks and threats greatly affect smart applications in the environment of IoT. The traditional IoT security techniques are insufficient with the recent security challenges considering the advanced booming of different kinds of attacks and threats. Utilizing artificial intelligence (AI) expertise, especially machine and deep learning solutions, is the key to delivering a dynamically enhanced and up-to-date security system for the next-generation IoT system. Throughout this article, we present a comprehensive picture on IoT security intelligence, which is built on machine and deep learning technologies that extract insights from raw data to intelligently protect IoT devices against a variety of cyber-attacks. Finally, based on our study, we highlight the associated research issues and future directions within the scope of our study. Overall, this article aspires to serve as a reference point and guide, particularly from a technical standpoint, for cybersecurity experts and researchers working in the context of IoT.

The SARS-CoV-2 high infectivity is due to the functional polybasic furin cleavage site in the S protein. How it was acquired is unknown. There are two challenges to face: (i) an evolutionary model, to fit the origin of the coronavirus; and (ii) a molecular mechanism for the site acquisition. Here we show genomic fingerprints which are specific of Pangolin-CoVs, Bat-SARS-like (CoVZC45, CoVZXC21), bat RatG13 and human SARS-CoV-2 coronaviruses. This, along with phylogenetic analysis, we found that these species have the same evolutionary origin in the bat, including a genetic recombination of S gene between Pangolin-CoV (2017) and RatG13 ancestors. However, this does not explain why SARS-CoV-2 is the only of them with the furin site, which consists in four amino acid (PRRA) motif. The Arginine doublet is encoded by CGGCGG codons. Surprisingly, none of the Arginine doublet of other furin site of viral proteins from several type of viruses, are encoded by the CGGCGG codons. This makes it difficult to consider a virus recombination as mechanism for the PRRA acquisition. The origin of SARS-CoV-2, is the origin of the recognition cleavage site. The bat coronavirus RaTG13 appears to be the closest relative of the SARS-CoV-2, but was isolated in 2013. So, new RatG13 samples would provide insights into the acquisition of the polybasic motif.

The popularity of functional gummies has increased, which is evident from the growing line of functional gummies from almost every nutraceutical companies. Sensory evaluation serves the purpose of determining which brand of functional gummy would capture the largest market share. Texture profile analysis was used to determine the mechanical properties of functional gummies. The brands of functional gummies that came under the scope of this study were denoted as Brand A, B, C, D, E, F and G. Fourier Transform Infrared Spectroscopy was utilised to detect organic material and functional groups in the functional gummies. Texture profile analysis gave valuable insights into the gummies’ mechanical properties which are cohesiveness, springiness, hardness, gumminess, and chewiness. Amongst the gummies that were studied, Brand F gummy has the highest value of cohesiveness of 0.92. Brand A gummy has a high springiness value of 1.0. Brand B gummy possesses the highest value of hardness, gumminess and chewiness of 12 532.2 g, 7617.6 N, and 6256.8 J, respectively. Qualitative sensory evaluation reveals that Brand G gummy has the best aesthetic qualities in terms of colour and appearance. Brand B gummy tastes the best while brand A gummy claims the top spot for gumminess and chewiness. Overall, the respondents in this study preferred brand A gummy over other brands.

Superstition is a belief that is not based on scientific knowledge. Traditional healers usually use superstition in their practices to manage human health problems and diseases; such practices create a conflict with the medical profession and its evidence-based practices. Medical professionals confirm that this kind of practice is not safe to human health as it is done by untrained people (e.g., tradition healers) utilizing unsterilized instruments within unhygienic environments. Most of the cases eventually develop a variety of complications, which are sometimes fatal. Female genital mutilation, uvulectomy, oral mutilation (tooth bud extraction to cure “Ibyinyo”), and eyebrow incisions are examples of the many different types of superstitious practices which occur commonly in different parts of the world. We described how these traditional practices of superstition have been and continue to be performed in various parts of the world, their complications on oral and general health, and the ways such practices hinder modern medical practices. This paper aims to increase the awareness of these superstition-driven traditional and potentially harmful practices by promoting the importance of evidence-based medical practices.

We propose an approach for estimating the error in depth data provided by generic 3D sensors, which are modern devices capable of generating an image (RGB data) and a depth map (distance) or other similar 2.5D structure (e.g. stereo disparity) of the scene. Our approach starts capturing images of a checkerboard pattern devised for the method. Then proceed with the construction of a dense depth map using functions that generally comes with the device SDK (based on disparity or depth). The 2D processing of RGB data is performed next to find the checkerboard corners. Clouds of corner points are finally created (in 3D), over which an RMS error estimation is computed. We come up with a multi-platform system and its verification and evaluation has been done, using the development kit of the board nVIDIA Jetson TK1 with the MS Kinects v1/v2 and the Stereolabs ZED camera. So the main contribution is the error determination procedure that does not need any data set or benchmark, thus relying only on data acquired on-the-fly. With a simple checkerboard, our approach is able to determine the error for any device. Envisioned application is on 3D reconstruction for robotic vision, with a series of 3D vision sensors embarked in robots (UAV of type quadcopter and terrestrial robots) for high-precision map construction, which can be used for sensing and monitoring.

Pipelines are widely used for transportation of hydrocarbon fluids over millions of miles over the world. The structures of the pipelines are designed to withstand several environmental loading conditions to ensure safe and reliable distribution from point of production to the shore or distributions deport. However, leaks in pipeline networks are one of the major causes of innumerable losses in pipeline operators and nature. Incidents of pipeline failure can result in serious ecological disasters, human casualties and financial loss. In order to avoid such menace and maintain safe and reliable pipeline infrastructure, substantial research efforts have been devoted to implementing pipeline leak detection and localisation using different approaches. This paper discusses on pipelines leakage detection technologies and summarises the state-of-the-art achievements. Different leakage detection and localisation in pipeline systems are reviewed and their strengths and weaknesses are highlighted. Comparative performance analysis is performed to provide a guide in determining which leak detection method is appropriate for particular operating settings. In addition, research gaps and open issues for development of reliable pipeline leakage detection systems are discussed.

Over the years, sustainability, impact on the environment, as well as the operation expenditure have been a major concern to the deployment of mobile cellular base stations worldwide. This is because the mobile cellular base stations are known to consume a high percentage of power within the mobile cellular network. Such energy consumption contributes to the emission of Greenhouse Gases (GHG) through the use of conventional diesel generating a set. As a result, the mobile cellular operators are faced with the dilemma of minimising the power consumption, GHG emission, and the operation cost, while improving the Quality of Service of the networks. In attempting to find a solution, this study presents the feasibility and simulation of a solar photovoltaic (PV) with battery hybrid power system (HPS) as a predominant source of power for a specific mobile cellular base station site situated in Soshanguve area of the city of Pretoria, South Africa. It also presents the technical development, showed the environmental advantage and cost benefits of using a solar PV-battery HPS to power a base station site of a 24 hrs daily load of 241.10 kWh/d and the peak load of 20.31 kW as compared to using the HPS of solar PV-diesel generating set-battery. The solar resource pattern for the city of Pretoria was collected from The National Aeronautics and Space Administration and modelled statistically. Thus, the statistical modelling done using solar radiation resource exposure characteristic patterns of Pretoria, South Africa, revealed an average annual daily solar radiation of 5.4645 Wh/m2/d and 0.605 clearness index. The simulation and the design were done using the Hybrid Optimization Model for Electric Renewables and Matlab/Simulink software. The simulation finding shows that the HPS of solar PV-battery combination has about 59.62 % saving on Net Present Cost, Levelized Cost of Energy, and 80.87% saving on Operating cost as against conventional BS powered with Gen Set-Battery.

Diagnosing melanocytic lesions is among the most challenging problems in the practice of pathology. The difficulty of physically masking melanin pigment and the similarity of its color to commonly used chromogens often complicate examination of the cytomorphology and immunohistochemical staining results for tumor cells. Melanin bleach can be very helpful for histopathological diagnosis of heavily pigmented melanocytic lesions. Although various depigmentation methods have been reported, no standardized methods have been developed. This study developed a fully automated platform that incorporates hydrogen peroxide-based melanin depigmentation in an automated immunohistochemical analysis. The utility of the method was tested in one cell block of malignant melanoma cells in pleural effusion, ten ocular melanoma tissue samples, and ten cutaneous melanoma tissue samples. Our results demonstrated that the proposed method, which can be performed in only 3 hours, effectively preserves cell cytomorphology and immunoreactivity. The method is particularly effective for removing melanin pigment to facilitate histopathological examination of cytomorphology and for obtaining an unmasked tissue section for immunohistochemical analysis.

Background: Coronavirus disease 2019 (COVID-19) has emerged as a global threat to human health and disease risk increases with advancing age. The regulation of the ACE2 gene that codes for COVID-19 host receptor ACE2 has been shown to be under epigenetic regulation. Here, we examined whether intensive DNA methylation profiling of the ACE2 gene differed by human host tissue and cell type, gender, and age. Results: Accessing four public datasets, we observed unique human cell-type-specific ACE2 DNA methylation patterns. In human lung tissues, gender differences in DNA methylation at 2 sites related to the ACE2 gene were identified. Further, in freshly isolated airway epithelial cells, DNA methylation near the transcription start site of the ACE2 gene associated with biological age. Conclusion: Epigenetic profiling of host tissue may permit discovery of age and gender-related potential risk factors for COVID-19. How perturbations in ACE2 methylation relate to clinical severity across the ages and gender needs to be determined to guide screening tools and potential epigenetic modification targeting to alleviate COVID-19 morbidity in the elderly.

Structure from Motion with Multi-View Stereo photogrammetry (SfM) is increasingly utilised in geoscience investigations as a cost-effective method of acquiring high resolution (sub-meter) topographic data, but has not been thoroughly tested in gullied savanna systems. The aim of this study was to test the accuracy of topographic models derived from aerial (via an Unmanned Aerial Vehicle, ‘UAV’) and ground-based (via a handheld digital camera, ‘Ground’) SfM in modelling a hillslope gully system in dry-tropical savanna, and to assess the strengths and limitations of the approach at different scales. A UAV survey covered an entire hillslope gully system (0.715 km²), whereas a Ground survey covered a single gully within the broader system (650 m²). SfM topographic models, including Digital Surface Models (DSM) and dense point clouds, were compared against RTK-GPS point data and a pre-existing airborne LiDAR Digital Elevation Model (DEM). Results indicate UAV SfM can deliver topographic models with a resolution and accuracy suitable to define gully systems at a hillslope scale (e.g., 0.1 m resolution with ~ 0.5 – 1.3 m elevation error), while ground-based SfM is more capable of quantifying gully morphology (e.g., 0.01 m resolution with ~ 0.1 m elevation error). Key strengths of SfM for these applications include: the production of high resolution 3D topographic models and ortho-photo mosaics, low survey instrument costs (< $AUD 3,000); and rapid survey time (4 and 2 hours for UAV and Ground survey respectively). Current limitations of SfM include: difficulties in reconstructing vegetated surfaces; uncertainty as to optimal survey and processing designs; and high computational demands. Overall, this study has demonstrated great potential for SfM to be used as a cost-effective tool to aid in the mapping, modelling and management of hillslope gully systems at different scales, in tropical savanna landscapes and elsewhere.

The thyroid gland secretes essential hormones for the growth regulation and the metabolic activity of the body. Thyroid dysfunction includes many conditions that can indirectly affect dental treatments. Therefore, the practitioner must be aware of these pathologies and their signs and symptoms in order to elaborate specific dental treatment plans, thus avoiding any per- and/or postoperative complications. Moreover, the dentist can help in the screening of undiagnosed thyroid dysfunction among patients.

Children’s learning of place value is critical to their future study of mathematics. However, its learning presents a huge challenge for many learners. As result they develop misconceptions and thencommit errors that become an encumbrance to their understanding of place value. It is therefore important to identify these misconceptions and their associated errors early and help children to overcome them. This article reports the findings from literature on what misconceptions learners display in the learning of place value and how they can best be supported to overcome them. The results show that despite the importance of this topic there are limited studies devoted to its research. The dearth of these studies creates a gap in the study of place value.

Graph theory plays significant role in every field of science as well as technology. Every situation can be articulated in terms of suitable graphs by using various approaches of graph theory. Considering the recent pandemic in the world and the precautions taken for prevention of the COVID 19, it is the most appropriate way to exercise the graph models with theoretical as well as practical aspects to control this epidemic. This paper defines the variable set, variable graphs and their types with respect to variable vertex sets and variable edge sets. Depending upon the nature of the pandemic, there are four types of Virus graphs. Virus graph I and III are not so perilous for all living beings. Although, Virus graphs II and IV are extremely hazardous for the harmony of the world. In view of different aspects for expand of pandemic, growth types of virus graphs are divided in 1-1, 1-P and 1-all growth types. The COVID19 initially was in Virus graph-I type, but presently it is in Virus graph-II types. We present the table involving the number of infected people after n days with respect to different values of P and growth rates with I0 = 100. Moreover, the country wise starting dates of stages of the virus graph-I and II are specified. The concept of cut sets is applicable for prevention of COVID19 and the whole world is using the same analogy.

Lean is one of the systematic approach to achieve higher value for organizations through eliminate non-value-added activities. It is an integrated set of tools, techniques, and principles designed to optimize cost, quality and delivery while improving safety. In Vietnam, industry waste management and treatment has become serious issue. The aim of this research is to present the effective of Lean application for industrial wastes collecting and delivery improvement. Through a case study, this paper showed the way of Lean tools and principles applied for wastes management and treatment such as Value Stream Mapping, Pull system, Visual Control, and Andon.... to get benefit on both economic and environment. In addition, the results introduced a good experience for Vietnamese enterprises in cost saving and sustainable development in waste management.

Pain is a natural bioassay for detecting and quantifying biological activities of venoms. The painfulness of stings delivered by ants, wasps, and bees can be easily measured in the field or lab using the stinging insect pain scale that rates the pain intensity from 1 to 4, with 1 being minor pain, and 4 being extreme, debilitating, excruciating pain. The painfulness of stings of 96 species of stinging insects and the lethalities of the venoms of 90 species was determined and utilized for pinpointing future promising directions for investigating venoms having pharmaceutically active principles that could benefit humanity. The findings suggest several under- or unexplored insect venoms worthy of future investigations, including: those that have exceedingly painful venoms, yet with extremely low lethality – tarantula hawk wasps (Pepsis) and velvet ants (Mutillidae); those that have extremely lethal venoms, yet induce very little pain – the ants, Daceton and Tetraponera; and those that have venomous stings and are both painful and lethal – the ants Pogonomyrmex, Paraponera, Myrmecia, Neoponera, and the social wasps Synoeca, Agelaia, and Brachygastra. Taken together, and separately, sting pain and venom lethality point to promising directions for mining of pharmaceutically active components derived from insect venoms.

Clinical rehabilitation and sports performance analysis both require the objectification of movement. Kinovea^© is a free 2D motion analysis software that enables the establishment of kinematics parameters. This low-cost technology has been used in sports sciences, as well as clinical field and research work. Although it has been validated as a tool with which to assess time-related variables, this is not yet the case regarding angular and distance variables. The main objective of this study was to determine the validity and reliability of the Kinovea software in obtaining angular and distance data at different perspectives of 90°, 75°, 60° and 45°. For this purpose, a figure with 29 points was designed (in AutoCAD) and 24 frames analysed. Each frame was examined by three observers who each made two attempts. For each export data item, 20 angles and 20 distance variables were calculated, with intra- and inter-observer reliability also analysed. To evaluate Kinovea reliability and validity a multiple approach was applied involving the following analysis: -systematic error with a two-way ANOVA 2x4; -relative reliability with ICC and CV (95% confidence interval); -absolute reliability with Standard Error. The results thus obtained indicate that the Kinovea software is a valid and reliable tool that is able to measure accurately at distances up to 5 m from the object and at an angle range of 90°–45°. Nevertheless, for optimum results an angle of 90° is suggested.

Background: The incidences of COVID-19 related suicide among adolescents and youths have been reported across the world. There is no cumulative study focusing on nature, patterns, and causative factors that lead to the present investigation. Methods: A purposive sampling of google news between 15 February to 6 July was performed. After excluding duplicate reports, the final list comprised a total of 37-suicide cases across 11 countries. Results: More male suicides were reported (21-cases, i.e., 56.76%), and the mean age of the total victims was 16.6±2.7 years (out of a total of 29-cases). About two-thirds of the suicides were from three countries named India (11-cases), United Kingdom (8-cases), and the USA (6-cases). Out of 23-student victims, 14 were school-going students. Hanging was the most common suicide method accounting in 51.4% of cases. The most common suicide causalities were related to mental sufferings such as depression, loneliness, psychological distress, etc., whereas either online schooling or overwhelming academic distress was placed as the second most risk factors followed by TikTok addiction-related psychological distress, and tested with COVID-19. Conclusion: The finding of the temporal distribution of suicides concerning lockdowns may help in exploring and evolving public measures to prevent/decrease pandemic-related suicides in young people.

This paper deals with the techno-economic study of the hybrid renewable energy system based on energy storage aspect under the form of hydrogen and methane. Indeed, with the intermittency of the renewable energy sources such as photovoltaic and wind energy, several problems of produced energy injection to the power system network can be encountered due to the shortage or the excess of these sources. This situation appeals the use of systems that ensure the stability of network based on the storage of energy surplus into gas using electrolyzer systems, which will be used afterward to cover the eventual shortage. In the present paper, the study of performance of each pathway of methane and hydrogen storage has been performed by the treatment of multiple scenarios via different architecture case studies in an Algerian location. Whereas, the energy produced by the photovoltaic system, the wind energy and the gas micro turbine sources are considered similar in each case. The modeling and simulation of the studied system operation under optimization criteria has been performed in this work, where the main aim is to define the appropriate configuration taking into account the different with low costs of investment, maintenance operation and immediate reactivity with a big storage capacity.

Over the last decade the blockchain technology has emerged to provide solutions to the complexity and privacy challenges of using distributed databases. It reduces the cost for customers by eliminating intermediaries and builds the trust in peer-to-peer communications. Over this time, the concept of blockchain has shifted greatly due to its potential in business growth for enterprises and the rapidly evolving applications in a collaborative smart cities' ecosystem, healthcare, and governance. Many platforms, with different architectures and consensus protocols, have been introduced. Consequently, it becomes challenging for an application developer to choose the right platform. Furthermore, blockchain has misaligned with the goals for efficient green collaborative digital ecosystem. Therefore, it becomes critical to address this gap and to build new frameworks to align blockchain with those goals. In this paper, we discuss the evolution of blockchain architecture and consensus protocols, bringing a retrospective analysis and discussing the rationale of the evolution of the various architectures and protocols, as well as capturing the assumptions conducting to their development and contributions to building collaborative applications. We introduce a classification of those architectures helping developers to choose a suitable platform for applications and providing insights for future research directions in the field to build new frameworks.

Typhoid fever is a communicable disease transmitted by the bacteria Salmonella typhi, related to serotype paratyphi A, B and C. The disease is of a significant health concern in most developing countries especially Cameroon. Objectives: The study aimed at determining the prevalence and associated risk factors of typhoid fever in children ( 0-18 years) attending the “Deo Gratias” hospital in Douala. Method: A hospital base cross sectional study from August to September 2018 was carried out in patients’ age 0-18 years suffering from typhoid fever at the Deo gratias Catholic hospital. Widal slide agglutination test was the diagnostic test used. Positive tested patients were administered questionnaires to evaluate the level of knowledge, attitude and practice toward the disease, as well as their self-management abilities. Data obtained from respondents was analysed by descriptive statistics. One-way ANOVA and means comparison using Tukey’s test (α = 0.05) was performed to check whether the population of respondents differed significantly across risk factor practices. Results were finally presented on bar charts, tables and pie chart. Results: Typhoid fever was more prevalent in females (52.3%) than in males (47.7%), with a high proportion in the ages 5-9 years (38.6%). A significant difference was observed in population of respondents across risk factor practices. Conclusion: Water quality have a great impact on the burden of typhoid fever among children. The identification of risk factors associated to the disease is of great importance in the development of rational control strategies of the disease.

Postdocs who land faculty jobs at research-intensive institutions need to juggle several new large-scale tasks: identifying space and equipment needs for their lab, negotiating the hiring package, outfitting the lab with supplies, building a team, and learning to manage time in ways that can promote productivity and happiness. Here we share tips to help new hires think clearly about each of these tasks.

The proposed research methodology aims to design a generally implementable framework for providing a house owner/member with the immediate notification of an on-going theft (unauthorized access to their premises). For this purpose, a rigorous analysis of existing systems was undertaken to identify research gaps. The problems found with existing systems were that they can only identify the intruder after the theft, or cannot distinguish between human and non-human objects. Wireless Sensors Networks (WSNs) combined with the use of Internet of Things (IoT), Cognitive Internet of Things, Internet of Medical Things, and Cloud Computing are expanding smart home concepts and solutions, and their applications. The primary objective of the present research work was to design and develop IoT and cloud computing based smart home solutions. In addition, we also propose a novel smart home anti-theft system that can detect an intruder, even if they have partially/fully hidden their face using clothing, leather, fiber, or plastic materials. The proposed system can also detect an intruder in the dark using a CCTV camera without night vision facility. The fundamental idea was to design a cost-effective and efficient system for an individual to be able to detect any kind of theft in real-time and provide instant notification of the theft to the house owner. The system also promises to implement home security with large video data handling in real-time.

ChatGPT, a groundbreaking natural language processing technology released just three months ago, has attracted significant attention due to its remarkable capabilities. This AI milestone has urged researchers, industry, decision-makers, and governments to examine this technology, including its implications, threats, and benefits. Despite the short period since its release, several researchers have examined ChatGPT from different perspectives. This paper presents a comprehensive review of ChatGPT, highlighting its technical novelties compared to previous models and analyzing existing research from various perspectives. We followed a rigorous methodology to conduct a critical review of existing research on ChatGPT and developed a taxonomy for the different areas of study. Additionally, we identify future challenges and research trends associated with ChatGPT. Our paper is the first critical review of ChatGPT literature, providing valuable insights for practitioners and policymakers. This paper serves as a reference for researchers seeking to advance research on ChatGPT, including its applications and development.

The emergence of COVID -19 pandemic has severely impacted individuals from all walks of life. The rapid spread of the disease to nearly all parts of the country has posed enormous health, economic, environmental and social challenges to the entire human population. In the absence of any effective drugs and vaccines for treatment, social distancing and other preventive measures are the only alternatives. Lockdown is among one of the options suggested by WHO to reduce spread of the virus. India was quick to close its international borders and enforce the world’s largest COVID lockdown on March 22, 2020. The present study attempts to highlight the impact of imposed nationwide lockdown on society and environment alike along with analysis of lifestyle changes. The study was based on an online survey using a structured questionnaire with over 1000 responders across the country. The pandemic situation demands a certain way of shaping the society to reduce virus spread and safeguard oneself. In this study, we analysed the changes that the society has undergone during lockdown to mitigate the spreading of the infection. We also addressed the changes that have become part of our lives during lockdown – hygiene and health consciousness, work from home (WFM), online teaching, digital shopping, changing internet habits and societal changes.

Pakistan is an important country located in South Asia and ranks the world's sixth most populous country. It has diverse landscapes with their own specific vegetation. The country specific vegetative diversity has a great ecological and economic impact on the conservation of local fauna. It has huge potential for sustainable beekeeping industry if properly exploited. Beekeeping in Pakistan is mainly focused in Khyber Pakhtunkhwa and central and north regions of Punjab provinces but nowadays it is growing rapidly across the country. Honey produced in Pakistan enjoys good repute in the Middle East due to its unique taste and quality. Pakistan exports around 4000 tons of the honey with the worth of about $ 23.00 million to Arab countries every year.

A field experiment was conducted for determination of crop coefficient (KC) and water stress coefficient (Ks) for wheat crop under different salinity levels, during 2015-16. Complete randomized block design of five treatments were considered, i.e., 0.51 dS/m (fresh water) as a control treatment and other four saline water treatments (4, 6, 8 and 10 dS/m), for S1, S2, S3 and S4 with three replications. The results revealed that the water consumed by plants during the different crop growth stages follows the order of FW>S1>S2>S3>S4 salinity levels. According to the obtained results, the calculated values of crop coefficients significantly differed from those suggested by FAO No.56 for the crops. The Ks values clearly differ from one stage to another because the salt stress causes both osmotic stress, due to a decrease in the soil water potential, and ionic stress which the average values of water stress coefficient (Ks) follows this order; FW(1.0)=S1(1.0)>S2(1.0)>S3(0.93)>S4(0.82). Overall, it was found the differences are attributed primarily to specific cultivar, the changes in local climatic conditions and seasonal differences in crop growth patterns. Thus, further studies are essential to determine the crop coefficient values under different variables, to make the best management practice (BMP) in agriculture.

The market of natural and organic cosmetics has been growing in last decades. The increase in interest in this type of product is a consequence of the concern that consumers have been presenting in relation to the environment and health. In addition to the appreciation the use of sustainable ingredients in cosmetic formulations, the consumers are also concerned about pollution caused by the use of plastics, which leads industries to reinvent themselves and rethink about the composition of packaging. The factor that most drives the purchase of natural and organic cosmetics is the fact that the consumer, in addition to contributing to the preservation of the environment, is also using a sustainable product. The growing demand for natural and organic cosmetics results in a concern of the brands with the organic issue, with the decreased use of animal derived ingredients and with the updating the parameters required for certification of a cosmetic as natural or organic. Due to the few studies available in this area, the importance of clarifying the definitions and concepts of natural and organic cosmetics is evident, in order to contribute with accurate information for the cosmetic sector.

Deep learning (DL), which is originated from an artificial neural network (ANN), is one of the major technologies of today's smart cybersecurity systems or policies to function in an intelligent manner. Popular deep learning techniques, such as Multi-layer Perceptron (MLP), Convolutional Neural Network (CNN or ConvNet), Recurrent Neural Network (RNN) or Long Short-Term Memory (LSTM), Self-organizing Map (SOM), Auto-Encoder (AE), Restricted Boltzmann Machine (RBM), Deep Belief Networks (DBN), Generative Adversarial Network (GAN), Deep Transfer Learning (DTL or Deep TL), Deep Reinforcement Learning (DRL or Deep RL), or their ensembles and hybrid approaches can be used to intelligently tackle the diverse cybersecurity issues. In this paper, we aim to present a comprehensive overview from the perspective of these neural networks and deep learning techniques according to today's diverse needs. We also discuss the applicability of these techniques in various cybersecurity tasks such as intrusion detection, identification of malware or botnets, phishing, predicting cyber-attacks, e.g. denial of service (DoS), fraud detection or cyber-anomalies, etc. Finally, we highlight several research issues and future directions within the scope of our study in the field. Overall, the ultimate goal of this paper is to serve as a reference point and guidelines for the academia and professionals in the cyber industries, especially from the deep learning point of view.

Hybrid machine tools combining additive and subtractive processes have arisen as a solution to the increasing manufacture requirements, boosting the potentials of both technologies, while compensating and minimizing their limitations. Nevertheless, the idea of hybrid machines is relatively new and there is a notable lack of knowledge in the field. Therefore, in the present paper, an insight into the advancements of hybrid machines is given, identifying their real capabilities, together with the latest developments from an industrial context. In addition, the current situation and future perspectives of hybrid machines from the point of view of process planning, monitoring and inspection are discussed. Finally, the challenges that must be overcome and the opportunities that the hybrid machines will provide in the forthcoming years are presented.

Wireless communication has proliferated due to the colossal augmentation of smart phones, mobile phones, tablets and laptops etc. Multimedia applications such as live videos, audios, still images, animated graphics and live communications all requires accompaniments of quality of service (QoS) as well as reliable end-to-end transfer of data. Information about the availability of resources in channel is must in order to improve the QoS. QoS can be determined in terms of capacity of channel, available bandwidth (ABW), and bulk transfer capacity (BTC). Bandwidth availability is a key check for improving the QoS in a network. The performance of a multimedia application is directly affected by the bandwidth availability. One of the most important QoS characteristic is ABW at a wireless route and it can be demarcated as least unused capacity of links instituting a network route. Since now there have been many bandwidth estimation techniques are available in the literature to increase the network performance. Bandwidth estimation techniques have been arranged into three leading classifications: i) Active probing bandwidth estimation techniques, ii) Passive bandwidth estimation technique and iii) Model based bandwidth estimation techniques. Each of these techniques are briefly discussed in this paper.

Capital structure decision plays an imperative role in firm’s performance. Recognizing the importance, there has been many studies inspected the rapport of capital structure with performance of firms and findings of those studies are inconclusive. In addition, there is relative deficiency of empirical studies examining the link of capital structure with performance of banks in Bangladesh. This paper attempted to fill this gap. Using panel data of 22 banks for the period of 2005-2014, this study empirically examined the impacts of capital structure on the performance of Bangladeshi banks assessed by return on equity, return on assets and earnings per share. Results from pooled ordinary least square analysis show that there are inverse impacts of capital structure on bank’s performance. Empirical findings of this study is of greater significance for the developing countries like Bangladesh because it will call upon concentration of the bank management and policy makers to pursue such policies to reduce reliance on debt and to accomplish optimal level capital structure. This research also contributes to empirical literatures by reconfirming (or otherwise) findings of previous studies.

Menaquinone-7 is a member of the vitamin K family whose interest has considerably increased over the last decade due to its beneficial role in human health mainly in respect to bone and cardiovascular health leading to a growing use in different nutritional supplement. Menaquinone-7 can be produced by synthesis or fermentation and its purity profile can differ depending on methodologies and extraction procedures. Finished formulation show a large heterogeneity of purity profiles as well as frequent discrepancies in the nominal content compared to the actual title. In the present study we compared purity profiles of different raw material and we related them to stability assay in normal (12months/25°C/60%RH) and accelerated conditions (6 months/40°C/75% RH) in order to test their performance in presence of different common excipients. Results show that higher purity profile correlates with enhanced stability and this could explain title discrepancies found in finished products found on the market worldwide.

In December 2019, a novel coronavirus (SARS-CoV-2) was identified in patients with pneumonia (called COVID-19) in Wuhan, Hubei Province, China. SARS-CoV-2 shares high sequence similarity and uses the same cell entry receptor, angiotensin-converting enzyme 2 (ACE2), as does severe acute respiratory syndrome coronavirus (SARS-CoV). Several studies have provided bioinformatic evidence of potential routes for SARS-CoV-2 infection in respiratory, cardiovascular, digestive and urinary systems. However, whether the reproductive system is a potential target of SARS-CoV-2 infection has not been determined. Here, we investigate the expression pattern of ACE2 in adult human testis at the level of single-cell transcriptomes. The results indicate that ACE2 is predominantly enriched in spermatogonia, Leydig and Sertoli cells. Gene ontology analyses indicate that GO categories associated with viral reproduction and transmission are highly enriched in ACE2-positive spermatogonia while male gamete generation related terms are down-regulated. Cell-cell junction and immunity related GO terms are increased in ACE2-positive Leydig and Sertoli cells, but mitochondria and reproduction related GO terms are decreased. These findings provide evidence that human testes are a potential target of SARS-CoV-2 infection which may have significant impact on our understanding of the pathophysiology of this rapidly spreading disease.

Musyakalah is one of the Arabic linguistic styles included under the category of majaz. This style is commonly used in Al-Quran. The Indonesian translation of Al-Quran is a case where many of the figures of speech are translated literally, thereby causing serious semantic problems. Thus, the research problem of this is formulated with the following questions: 1) How many musyakalah ayahs are there in Al-Quran?; 2) How are the musyakalah ayahs translated, literally (harfiyya) or interpretatively (tafsiriyya)?; 3) How many ayahs are translated literally and how many are translated interpretatively?; and 4) Which translated musyakalah ayahs have the potential to raise semantic and theological problems? The corpus in this research consists of all musyakalah ayahs in Al-Quran and their translation to Indonesian published by the Department of Religious Affairs of Indonesia. The research adopted a descriptive-semantic method. The findings of this research are: 1) There are only eleven ayahs in Al-Quran using musyakalah style, namely: Alhasyr ayah 19, Ali Imran ayah 54, Annaml ayah 50, Alanfal ayah 30, Asysyura ayah 40, Albaqarah ayah 15, Almaidah 116, Aljatsiah ayah 34, Attaubah ayah 79, Annisa ayah 142, and Albaqarah 194; 2) The musyakalah ayahs translated literally are: Aljatsiah 34, Almaidah 116, Asysura 40, Annaml 50, and Alhasyr 19, whereas the musyakalah ayahs translated interpretatively are Albaqarah 194, Annisa 142, Attaubah 79, Albaqarah 15, Alanfal 30, and Ali Imran 54; 3) Of the eleven musyakalah ayahs, only Alhasyr ayah 19 that is translated correctly and does not have the potential of creating misinterpretation. Meanwhile, the interpretation of the other four ayahs can potentially cause misinterpretation or are against the basic principles of Islam. The six remaining ayahs are translated interpretatively and thus do not have the potential to be misinterpreted; 4) The findings suggest that musyakalah ayahs are more appropriately translated interpretatively. Therefore, the following is recommended: 1) Considering the different characteristics of Arabic and Indonesian languages, studies on Al-Quran translation into Indonesian should continuously be carried out; 2) In order to avoid misinterpretation, it is better that the translation of musyakalah ayahs uses tafsiriyya (interpretative) approach; 3) The harfiyya (literal) and tafsiriyya (interpretative) approaches should be developed for other styles beside musyakalah..

In this paper, at first, a color image of a car is taken. Then the image is transformed into a grayscale image. After that, the motion blurring effect is applied to that image according to the image degradation model described in equation 3. The blurring effect can be controlled by a and b components of the model. Then random noise is added in the image via Matlab programming. Many methods can restore the noisy and motion blurred image; particularly in this paper Inverse filtering as well as Wiener filtering are implemented for the restoration purpose. Consequently, both motion blurred and noisy motion blurred images are restored via Inverse filtering as well as Wiener filtering techniques and the comparison is made among them.

Social media has revolutionized the way we communicate and interact with each other. While it has brought many benefits, it has also presented many ethical challenges. Social media platforms have access to an enormous amount of personal data, and there are concerns about how this data is being stored, collected, and used. Users often need to fully understand the risks of sharing sensitive information. Social media platforms have made it easy for fake news to spread rapidly, which can be dangerous and have serious consequences. Misinformation and propaganda can influence people's decisions and beliefs. In this paper, we will analyze the issues and challenges that may arise, and it will be necessary for individuals and society to address these challenges ethically and responsibly.

Measurements of optical properties have been used for decades to study particle distributions in the ocean. They have been found useful to constrain suspended mass concentration as well as particle-related properties such as size, composition, packing (particle porosity or density) and settling velocity. Optical properties, however, provide measurements that are biased, as certain particles (based on size, composition, shape or packing) contribute to a specific property more than others. Here we study this issue both theoretically as well as by contrasting different optical properties collected simultaneously in a bottom boundary layer, to highlight the utility of such measurements as well as the biases we are likely to encounter using different optical properties to study suspended particles. In particular, we investigate the possibility to infer settling velocity from vertical profiles of optical measurements, finding that the effects of aggregation dynamics can seldom be ignored.

Since the first case of 2019 novel coronavirus disease (COVID-19) detected on Jan 30, 2020, in India, the number of cases rapidly increased to 3819 cases including 106 deaths as of 5 April 2020. Taking this into account, in the present work, we are studying a Bats-Hosts-Reservoir-People transmission fractional-order COVID-19 model for simulating the potential transmission with the thought of individual social response and control measures by the government. The real data available about infectious cases from $14^{th}$ March to $26^{th}$ March 2020 is analysed and accordingly various parameters of the model are estimated or fitted. The Picard successive approximation technique and Banach's fixed point theory have been used for verification of the existence and stability criteria of the model. Numerical computations are done utilizing the iterative Laplace transform method. In the end, we illustrate the obtained results graphically. The purpose of this study is to estimate the effectiveness of preventive measures, predicting future outbreaks and potential control strategies using the mathematical model.

This study aims to examine Turkish companies from a sustainability and green innovation point of view. Through this purpose, this research’s objective is to find out relationship between sustainability drivers and green innovation and also to search for green organizational culture’s mediation effect in this relationship. Survey was carried in companies operating in Turkey which were listed among İstanbul Chamber of Industry (ICI) Top 500 companies for last 3 years successively and have ISO14001 Environmental Management Certificate. According to the survey results, it was manifested that factors directing companies to sustainability having a positive relationship with green organizational culture and green innovation. It is found that there is a partial mediation effect of green organizational culture between motivating factors for sustainability and green innovation.

Construction of Pontoons is based on multiple elements, dimensions and weight. The study has addressed about how the industry of the floating reinforcement concrete precast (pontoons) installs in the factory with the combinations of utility, electricity services, and Internet service. The pontoon bridges are successfully installed in the road for transport or sea for shops. The installation process for pontoons is successfully attempted in a balanced situation above surface of the sea to the resistant of floating precast (pontoons) to any ambient effects such as weather conditions, the movement of the waves or any others effects. The findings elaborate that it is not just a military solution. Pontoon installation can significantly serve for civil purposes.

COVID-19 pandemic instigated a digital revolution in academia and higher education. Social distancing, months-long quarantine, as economic shutdown will help the majority of people working in academia and higher education not only to complete their personal transition to the fully functional and operational online tuition, but also to understand that online defences, online entrance and final exams, as well as online academic jobs are as effective and meaningful as those conducted “in real life”. Due to the crisis induced by the coronavirus epidemic, innovations in academia and higher education that would have normally taken several years due to the various contradictory administrative regulations are now introduced promptly in a matter of days. This is a clear example of the Schumpeterian ‘creative destruction’ in making that will forever change the status quo in academia and higher education.

It is common knowledge that increasing CO₂ concentration plays a major role in enhancement of the greenhouse effect and contributes to global warming. The purpose of this study is to complement the conventional and established theory that increased CO₂ concentration due to human emissions causes an increase of temperature, by considering the reverse causality. Since increased temperature causes an increase in CO₂ concentration, the relationship of atmospheric CO₂ and temperature may qualify as belonging to the category of “hen-or-egg” problems, where it is not always clear which of two interrelated events is the cause and which the effect. We examine the relationship of global temperature and atmospheric carbon dioxide concentration at the monthly time step, covering the time interval 1980–2019, in which reliable instrumental measurements are available. While both causality directions exist, the results of our study support the hypothesis that the dominant direction is T → CO₂. Changes in CO₂ follow changes in T by about six months on a monthly scale, or about one year on an annual scale. We attempt to interpret this mechanism by involving biochemical reactions, as at higher temperatures soil respiration, and hence CO₂ emission, are increasing.

Seaweeds are considered as one of the largest biomass producers in marine environment that is rich in bioactive metabolites and a source of natural ingredients for functional foods. The potential antioxidant activity and the potential inhibition of Caco2 cell proliferation, of crude extracts of: Chlorophyta (Ulva lactuca, and Codium tomentosum), Phaeophyta (Cystoseira crinita, Cystoseira stricta, and Sargassum vulgare), and Rhodophyta (Gelidium latifolium, Hypnea musciformis, and Jania rubens) collected from western Libyan coast were evaluated in vitro. The antioxidant activity was determined by reducing power and DPPH assays while cell proliferation, morphological changes and the cell cycle arrest were assessed by MTT, inverted light microscope and flow cytometry methods respectively. The polyphenols and flavonoids rich extracts showed remarkable reducing power and antiradical properties. After exposure of Caco2 cells to; various concentrations of extracts (50, 100,150 and 200 µg/mL) especially from brown algae for 72 h, significantly reduced cell proliferation. The antiproliferative effect of algae extracts was correlated with their polyphenol and flavonoid contents. Cell cycle analysis further showed that cells were arrested in G phases along with an increment in sub-diploidal cell population (sub-G) after extract application. These results imply that seaweeds which are rich in bioactive compounds may be in anticancer drug research programs. However, further investigations are essential to reveal the molecular mechanisms of the anticancer activities of these algae.

Microplastics (of size < 5mm) pollution in our environment is of current concern by researchers, public media and non-governmental organizations. Implications by their presence in aquatic and soil ecosystems have been well studied and documented, but less attention has been paid on airborne microplastics (MPs). Studies concerning airborne microplastics started from 2016 and only a few (n=7) have been published till date. Although, studies may increase in the following years, since air is very important for human survival. Microplastics have been observed in atmospheric fallouts in indoor and outdoor environments using a sampling or vacuum pump, rain sampler and/or particulate fallout collector. Identification and quantification have been carried out by visual, spectroscopic and spectrometric techniques. Factors such as meterological, climatic and anthropogenic influence the distribution and movement of airborne MP. Human exposure may be through inhalation or dermal route with their potential biopersistence and translocation. Ingestion may cause localized inflammation and cancer due to responses by the immune cells, especially in individuals with compromised metabolism and poor clearance mechanisms. Ecological risks involve possible contamination of the ecosystem through a dynamic relationship of MPs in soil, water and air forming a MP contamination cycle. The present review aimed at providing a comprehensive overview of current knowledge or information regarding microplastics in air, identifies gap in knowledge and give suggestions for future research.

ABSTRACT Ethiopia is a developing country, where majority of the population lives in rural areas without access to electricity. 83% of the total population of the country use traditional biomass energy as a basic source of energy. In contrast, the country is endowed with sufficient renewable energy resources which can be used as a standalone electric energy supply system for electrifying remote areas of the country. These resources are mainly micro hydropower and wind which can be used individually or the best combination of one another. The application of hybrid renewable energy system has become an important alternative solution for rural electrification program. The Modeling and control of a hybrid PV-Wind-Hydro DG system is also addressed. Dynamic models for the major system components, namely, wind energy conversion system, PV energy conversion system, hydro, inverter, and overall fuzzy logic controller units are developed. Then, a simulation model for the proposed hybrid power system has been developed using MATLAB /Simulink environment. This is done by creating subsystem sets of the major dynamic component models and then assembling into a single aggregate model. The overall power management strategy for coordinating and/or controlling the different energy sources is also presented in the thesis work. Generally there are 800 households with total electric demand of 71.6KW.To satisfy this demand 52%, 35% and 13% is to be contributed from wind/hydro/solar respectively. To use the power economically fuzzy logic controller is used. The controller monitors the demand and the available sources and then switches to the appropriate power supply according to the written rules. Simulations have been carried out to verify the system dynamic performance using a practical load profile and weather data. The result shows that the overall power management strategy is effective and the load demand is balanced. To complete this work, a grid extension from the closest substation has been compared with hybrid system. Cost of the grid extension is estimated based on the data obtained from EEP office. This is done in order to compare the cost of the designed hybrid power system against the cost of grid extension. The result shows that breakeven grid extension distance to be 23.9km which indicates that grid extension is preferable.

Households and businesses are generating unprecedented levels of electrical and electronic wastes (e-waste), fueled by modernisation and rapid obsolescence. While the challenges imposed by e-waste are similar everywhere in the world, disparities in progress to deal with it exists; with developing nations such as South Africa lagging. The increase in e-waste generation increases the need to formulate strategies to manage it. This paper presents an overview of e-waste management on a global and South African scenarios with a specific case for Cathode Ray Tube (CRT) waste management practices in South Africa. CRTs present the biggest problem for recyclers and policy makers because they contain hazardous elements such as lead and antimony. Common disposal practices have been either landfilling or incineration. The research into the South African practices with regards to CRT waste management showed that there is still more to be done to effectively manage this waste stream. This is despite clear waste regulatory frameworks in the country. However, recent developments have placed e-waste as a priority waste stream, which should lead to intensified efforts in dealing with it. Overall, these efforts should aim to maximise diversion from landfilling and to create value-addition opportunities, leading to social and environmental benefits.

We present an open-source Star Tracker (ST) for Attitude Determination. Our implementation makes use of open source software of common usage in astronomy running on a Raspberry Pi 2 platform. The developed platform is open and available for parties interested in further development. Evaluation of the system showed that the ST is suitable for Cubesats of 2U or larger. The ST platform is capable of solving the Lost-In-Space (LIS) problem. Currently, the average accuracy reached of the algorithm is close to 5 seconds of arc with an average processing time of 75 seconds. However, a average accuracy of about 3 minutes of arc can be reached with 35 seconds in average processing time. We also describe the evaluation procedure, the found conclusions of this procedure, in particular the section of the algorithm where most of the processing time is spent and other possible source of errors not included in this study.

With the breakthrough of modernism, various efforts are undertaken to rationalize architecture and building processes using industrial principles. Few architects explore these as intensively as Walter Gropius, the founder of the Bauhaus. Even before World War One, and increasingly in the interwar years, Gropius and a number of colleagues undertake various experiments which manifest in a series of projects, essays, model houses and Siedlungen. These aim at conceptually different goals, i.e. they follow two different categories of industrial logic: first, a flexible construction kit and, second, an assembly line serial production. This article traces the genesis of these two concepts and analyses their characteristics using these early manifestations. Compared to existing literature, this article takes into account hitherto neglected primary sources as well as technological and construction history aspects—allowing for a distinction based not only on theoretical, but also technological and structural characteristics. This article shows that Gropius succeeds in formulating and exploring the two principles in theory and practice as well as drawing conclusions by the end of the 1920s. With them, he contributed significantly to the rationalization of architecture, and his principles have been picked up and developed further by numerous architects since then.

The City of Meycauayan is considered as one of the most polluted cities in the developing world on the account of industrial discharges of toxic materials to the environment. This work investigated the sources of the heavy metal pollution by analyzing soil and sediment samples for heavy metals (Cr, Hg, Ni, and Pb) together with selected environmental indicators (TN, TOM, and TP) located along the Meycauayan River. Hierarchical cluster analysis (HCA), principal components analysis (PCA), and Pearson correlation analysis (CA) were used to identify the sources of the metals. Results showed delineated locations of severe levels of heavy metal pollution downstream because of the concentration of industrial activities. Cr contributed more than any other heavy metals analyzed due to proliferation of tanneries discharging untreated wastewaters to the river. Significant inputs of Pb and Hg from Pb-acid battery recycling and gold smelting industries were also found. Risk assessments indicated severe levels of heavy metal pollution where industrial activities are concentrated. The mean Cr, Pb, Ni, and Hg in the sampling locations have mean incidences of toxicity of 91.7 %, 53.6 %, 27.7 %, and 70.0 %, respectively. Our study showed a serious need to address heavy metal pollution in Meycauayan.

Agricultural greenhouse is largely answered in the agricultural sphere, despite the shortcomings it has, including overheating during the day and night cooling which sometimes results in the thermal inversion mainly due to its low inertia. The glasshouse dressed chapel is relatively more efficient than the conventional tunnel greenhouse. Its proliferation on the ground is more or less timid because of its relatively high cost[14-22]. Agricultural greenhouse aims to create a favorable microclimate to the requirements of growth and development of culture, from the surrounding weather conditions, produce according to the cropping calendars fruits, vegetables and flower species out of season and widely available along the year. It is defined by its structural and functional architecture, the quality thermal, mechanical and optical of its wall, with its sealing level and the technical and technological accompanying[12-13]. The greenhouse is a very confined environment, where multiple components are exchanged between key stakeholders and them factors are light, temperature and relative humidity[8]. This state of thermal evolution is the level sealing of the cover of its physical characteristics to be transparent to solar, absorbent and reflective of infrared radiation emitted by the enclosure where the solar radiation trapping effect otherwise called "greenhouse effect" and its technical and technological means of air that accompany. The socio-economic analysis of populations in the world leaves appear especially the last two decades of rapid and profound transformations These changes are accompanied by changes in eating habits, mainly characterized by rising consumption spread along the year[14]. To effectively meet this demand, greenhouse-systems have evolved, particularly towards greater control of production conditions (climate, irrigation, ventilation techniques, CO2 supply, etc ...). Technological progress has allowed the development of greenhouses so that they become increasingly sophisticated and of an industrial nature (heating, air conditioning, control, computer, regulation, etc ...). New climate driving techniques have emerged, including the use of control devices from the classic to the use of artificial intelligence[10-11] such as neural networks and / or fuzzy logic, etc... As a result, the greenhouse growers prefer these new technologies while optimizing the investment in the field to effectively meet the supply and demand of these fresh products cheaply and widely available throughout the year.

Aeroponics is a relatively new soilless culture technology, which may produce food in space limited cities or non-arable land with high water use efficiency. The shoot and root growth, root characteristics, mineral contents of two lettuce cultivars were measured in aeroponics, as compared with hydroponics and substrate culture. The results showed that aeroponics remarkably improved the root growth with a significant greater root biomass, root/shoot ratio, and several times higher total root length, root area and root volume. However, the greater root growth did not lead to a better shoot growth compared with hydroponics, due to the limited availability of nutrients and water. It can be concluded that aeroponics systems may be better for high value true root crops production. Further research is necessary to figure out the suitable pressure, droplet size, and misting interval in order to improve the continuously availability of nutrients and water in aeroponics, if it is used to grow crops like lettuce for harvesting above-ground parts.

Towards the investigation and further understanding of the development and propagation of Medicanes, this study explores the forecasting capability of WRF model in case of cyclone “Cleopatra” which affected with extreme rainfall and strong winds Sardinia and Calabria, Italy, in November 2013. This cyclone was unusual in that it developed a warm core but did not fulfill its transformation into a tropical-like cyclone because its core did not expand high enough in the tropospnere. The ERA5 reanalysis dataset was dynamically downscaled from 31 km spatial horizontal resolution to 9 km using WRF model. The methodology consists of; firstly, an extensive physical parameterization schemes sensitivity test and consequently, a short-range ensemble forecasting implementation based on the highest statistical scored physics configuration. All simulation results were validated against surface observations and remote sensing products. Subsequently, the modeled cyclone trajectories are compared to satellite imagery derived from EUMETSAT-SEVIRI gridded data. The findings of the conducted analysis illustrate that ensemble average displays significant difference in performance compared to any of the deterministic runs individually, suggesting that ensemble forecasts will be beneficial in studies assessing cyclonic events in the Mediterranean region.

The need to alleviate the difficulties of abstraction and improve students’ achievement in Physical Geography informed this research. This study investigated the Effects of Mastery Learning Strategy and Learning Retention on Senior Secondary School Students’ Achievement in Physical Geography. The study adopted the quasi experimental non-equivalent pre-test, post-test control group design. The Multi-stage sampling technique at four levels was used to select four co-educational secondary schools in Ganye Educational Zone in Nigeria. The sample for the study was 218 Senior Secondary School two (SS II) students offering Geography from four intact classes in the four selected secondary schools. The instrument used for data collection was “Physical Geography Achievement and Retention Test” (PGART). The reliability of the instrument was established using Kendall tau b statistic. This gave a reliability index of 0.74. Data collected were analyzed using Mann-Whitney U and t-Test. The results showed that Mastery Learning Strategy has the potentials to improve students’ learning outcomes, retention and achievement in all spheres of cognitive domain in Physical Geography better than the Conventional Method. Hence the need to incorporate this teaching strategy during instruction so that learners would be guided to learn meaningfully and be assisted to retain content learnt in Geography.

This paper deals with the design, simulation and implementation of shunt hybrid compensator to maintain the power quality in 3-phase distribution networks feeding different types balanced and unbalanced nonlinear loads. The configuration of the compensator consists of a selective harmonic elimination passive filter, a series connected conventional 6-pulse IGBT inverter, acting as the active filter terminated with a dc link capacitor. The theory and modelling of the compensator based on current harmonic components at the load end and their decomposition in d-q axis frame of reference are utilized in the reference current generation algorithm. Accordingly, the source current waveform is made to follow the reference current waveform using a high frequency carrier based controller. Further, this inner current control loop is supported by a slower outer voltage control loop for sustaining desirable dc link voltage. Performance of the compensator is evaluated through MATLAB simulation covering different types of loads and reduction of harmonic currents and THD at the supply side along with excellent regulation of dc link voltage are confirmed. The performance of a hybrid compensator designed and fabricated using the above principles is evaluated and corroborated with the simulation results.

Mexico´s inhabitants have approximately 7 million dogs and cats as pets, of which there is no accurate information about their environmental impacts as a result of their feeding and comfort requirements. The objective of this study is to compare the environmental footprint between a dog and a cat in a family environment. For this purpose, a life cycle analysis was performed including, among other factors, its feeding and waste management in one year of life. Different environmental indicators including the carbon footprint were considered. It was found that the equivalent CO2 emission of a dog is twice that estimated for a domestic cat and that the main contribution is due to the food production. The ecological footprint that is generated when satisfying the requirements for pet´s well-being impacts in the environment contributes primarily to the carbon footprint.

Culture, gender and religion are closely linked each other’s, profoundly affect the role of each person within the Society, and also affect the ability to access to the health resources. We are now living a worldwide crisis due to the SARS-CoV-2 pandemic. In order to appropriately tackle it, an alliance between science, politics and citizens is needed. In this article, we summarize current evidences of how religions can represent, on one hand, a risk moment for spreading the virus (in relation with overcrowded events), on the other, a precious opportunity to engage people, and in particular minorities, in fighting the pandemic. To win this fight, we need a multicultural approach that takes into account every aspect of human life, and among these religion, which influences so much culture, everyday life and well-being.

This paper investigates the feasibility of a backend design for real-time, multiple-channel processing digital phased array system, particularly for high-performance embedded computing platforms constructed of using general purpose digital signal processors. Frist, we obtained the lab-scale backend performance benchmark from simulating beamforming, pulse compression, and Doppler filtering based on MicroTCA chassis using Serial RapidIO protocol in backplane communication. Next, a field-scale demonstrator of a multifunctional phased array radar is emulated by using the similar configuration. Interestingly, the performance of a barebone design is compared to that of emerging tools that systematically take advantage of parallelism and multicore capabilities, including Open Computing Language.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known to cause 2019-coronavirus disease (COVID-19) pandemic is a zoonotic coronavirus and crosses species to infect human populations, where an efficient transmission of virus occurs human-to-human. Nationwide lockdown is being adopted to stop public transport, keep people at their homes and out of their work, and maintain social distancing. In turn, large geographic areas in the world (including China, Italy, Spain, and USA) has been almost halted. This temporary halt is significantly slashing down the air pollution (air pollutants and warming gases) in most cities across the world. This paper: (i) introduces both COVID-19 and air pollution; (ii) overviews the relation of air pollution with respiratory/lung diseases; (iii) compiles and highlights major data appeared in media and journals reporting lowering of air pollution in major cities those have been highly impacted by the COVID-19; and also (iv) lists the way forward in the present context. Because COVID-19 is an ongoing pandemic and currently far from over, strong conclusions could not be drawn with very limited data at present. The temporary slashed down global air pollution as a result of COVID-19 restrictions are expected to stimulate the researchers, policy makers and governments for the judicious use of resources; thereby minimise the global emissions, and maintain their economies once the pandemic eases. On the other, lifting of the nationwide lockdown and eventual normalisation of the temporarily halted sectors may also reverse the currently COVID-19 pandemic-led significantly slashed down global air pollution that could make the future respiratory health crisis grimmer.

Over the past couple of decades, Global positioning system (GPS) technology has been utilized to collect large-scale data from travel surveys. As the precise spatiotemporal characteristics of travel could be provided by GPS devices, the issues of traditional travel survey, such as misreporting and non-response, could be addressed. Considering the defects of dedicated GPS devices (e.g., need much money to buy devices, forget to take devices to collect data, limit the simple size because of the number of devices, etc.), and the phenomenon that the smartphone is becoming one of necessities of life, there is a great chance for the smartphone to replace dedicated GPS devices. Although, several general reviews have been done about smartphone-based GPS travel survey in the literature review section in some articles, a systematic review from smartphone-based GPS data collection to travel mode detection has none. The included studies were searched from six databases. The purpose of this review is to critically assess the current literature on the existing methodologies of travel mode detection based on GPS raw data collected by smartphones. Meanwhile, according to the systematic comparison among different methods from data-preprocessing to travel mode detection, this paper could carefully provide the Strengths and Weaknesses of existing methods. Furthermore, it is the crucial step to develop the methodologies and applications of GPS raw data collected by smartphones.

This study is aimed at demonstrating application of vegetation spectral techniques for detection and monitoring of impact of oil spills on vegetation. Vegetation spectral reflectance from Landsat 8 data were used in the calculation of five vegetation indices (normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), adjusted resistant vegetation index 2 (ARVI2), green-infrared index (G/NIR) and green-shortwave infrared (G/SWIR) from the spill sites (SS) and non-spill (NSS) sites in 2013 (pre-oil spill), 2014 (oil spill date) and 2015 (post-oil spill) for statistical comparison. The result shows that NDVI, SAVI, ARVI2, G/NIR and G/SWIR indicated certain level difference between vegetation condition at the SS and the NSS were significant with p-value <0.5 in December 2013. In December 2014 vegetation conditions indicated higher level of significant difference between the vegetation at the SS and NSS as follows where NDVI, SAVI and ARVI2 with p-value 0.005, G/NIR - p-value 0.01 and GSWIR p-value 0.05. Similarly, in January 2015 a very significant difference with p-value <0.005. Three indices NDVI, ARVI2 and G/NIR indicated highly significant difference in vegetation conditions with p-value <0.005 between December 2013 and December 2014 at the same sites. Post—spill analysis show that NDVI and ARVI2 indicated low level of significance difference p-value <0.05 suggesting subtle change in vegetation conditions between December 2014 and January 2015. This technique is essential for real time detection, response and monitoring of oil spills from pipelines for mitigation of pollution at the affected sites in the mangrove forest.

In the last decade, the drone market has grown rapidly for both civil and military purposes. Due to their versatility, drones demand is constantly increasing, with several industrial players joining the venture to transfer urban mobility to the air. This has exacerbated the problem of noise pollution, mainly due to the relatively lower altitude of these vehicles and to the proximity of their routes to extremely densely populated areas. In particular, both the aerodynamic and aeroacoustic optimization of the propulsive system and of its interaction with the airframe are key aspects of the design of aerial vehicles for the success or the failure of their mission. The industrial challenge involves finding the best performance in terms of loading, efficiency and weight, and, at the same time, the most silent configuration. For this reason, research has focused on an initial localization of the noise sources and, on further analysis, of the noise generation mechanism, focusing particularly on directivity and scattering. The aim of the present study is to review the noise source mechanisms and the state-of-the-art technologies available in literature for its suppression, focusing especially on the fluid-dynamic aspects of low Reynolds numbers of the propulsive system and on the interaction of the propulsive-system flow with the airframe.

This study presents the validation process of the Questionnaire on Academic Stress in Secondary Education –QASSE-, designed to assess the wide variety of school sources and situations related to academic stress in adolescence, and their relationship with students’ physical and psychological well-being. Participants were 860 Spanish high school students (52.9% girls) with an average age of 14.62 years (SD = 1.8). Through a cross-validation process, EFA and CFA supported QASSE multifactorial structure with four first-order factors -academic overload, interaction with classmates, family pressure, and future-oriented perspective- and a second-order factor of academic stress, showing a significant and intense relationship with adolescents’ psychological and physical well-being. Results also highlight the effects of the gender*educational level interaction on the students’ stress, with girls showing higher levels of stress in the transition courses between educational phases (sophomore and junior years). The QASSE demonstrates good validity and reliability, showing potential for both research and educational application. The results show the high impact of the QASSE dimensions on psychological and physical well-being in adolescence, highlighting its special usefulness for designing and adjusting educational prevention and intervention actions in this area to the students’ specific characteristics and needs

Computational studies suggest that hesperidin, a flavonoid abundant in citrus peel, binding the three main cellular receptors of SARS-CoV-2 virus can act in the prophylaxis and treatment of COVID-19. Herein we urge the uptake of hydrodynamic cavitation industrial-scale reactors based on the low cost, reliable Venturi tube for the extraction of citrus pectin rich in hesperidin (and in other bioflavonoids including naringing) by very fast processing of waste orange peel or waste lemon peel in water only. A device able to process up to 500 kg of waste peels per session, similar to the one lately deployed in Italy for hydrodynamic cavitation-assisted brewing, is capable to provide 36,000 doses of 1000 mg hesperidin per day.

Indwelling urinary catheters are common in healthcare settings and can lead to catheter-associated urinary tract infection (CAUTI). Long-term catheterization causes polymicrobial colonization of the catheter and urine, for which the clinical significance is poorly understood. Through prospective assessment of catheter urine colonization, we identified Enterococcus faecalis and Proteus mirabilis as the most prevalent and persistent co-colonizers. Clinical isolates of both species successfully co-colonized in a murine model of CAUTI, and they were observed to co-localize on catheter biofilms during infection. We further demonstrate that P. mirabilis preferentially adheres to E. faecalis during biofilm formation, and that contact-dependent interactions between E. faecalis and P. mirabilis facilitate establishment of a robust biofilm architecture that enhances antimicrobial resistance for both species. E. faecalis may therefore act as a pioneer species on urinary catheters, establishing an ideal surface for persistent colonization by more traditional pathogens such as P. mirabilis.

The paper makes a critical assessment of urban development in Nigeria against the backdrop of a rapidly changing population and growth rate. The Authors interrogated the effects of development control- mechanisms through the lenses of identified social anomalies in three selected pilot cities of Nigeria (Kaduna, Abuja FCT, and Lagos). Thematic areas examined include, the state of critical infrastructure, population dynamics, urban sprawl, city polarization, transportation, waste management systems, security/crime and economics. The Authors identified structural transformation of three Nigerian cities with focus on the causes and attendant consequences on urban development. The study found that urban growth has over-stretched the state of critical infrastructure in the cities and the mechanisms of development control seem ineffective in stemming unregulated growth, compromises and unplanned ‘development’. The paper noted that the impact of these developments has overstretched the state of critical infrastructure with far-reaching consequences. The authors conclude with some recommendations for strategic planning and sustainable development strategies aimed at mitigating the problems of urban development in Nigeria.

The aim of this work is to compare two softwares (MAUD and TOPAS) based on the Rietveld algorithm and to test the concept of tolerance factor using the dissolution at high temperature of yttrium into BaTiO₃. In general, both softwares give up different values of the crystalline parameters however the trends are similar in most cases but the analysis of the strain and crystallite size in the BaTiO₃ crystals suggests that, in this particular case, MAUD offered results more consistent with the expected behavior. Using the crystalline parameters calculated by Rietveld, the tolerance factor values were obtained and these data suggest even better stability in the crystalline structure than that expected using theoretical parameters. Tolerance factor concept also indicates that Ti⁴⁺ should be preferred.

Noise reduction in medical images is a perplexing undertaking for the researchers in digital image processing. Noise generates maximum critical disturbances as well as touches the medical images quality, ultrasound images in the field of biomedical imaging. The image is normally considered as gathering of data and existence of noises degradation the image quality. It ought to be vital to reestablish the original image noises for accomplishing maximum data from images. Medical images are debased through noise through its transmission and procurement. Image with noise reduce the image contrast and resolution, thereby decreasing the diagnostic values of the medical image. This paper mainly focuses on Gaussian noise, Pepper noise, Uniform noise, Salt and Speckle noise. Different filtering techniques can be adapted for noise declining to improve the visual quality as well as reorganization of images. Here four types of noises have been undertaken and applied on medical images. Besides numerous filtering methods like Gaussian, median, mean and Weiner applied for noise reduction as well as estimate the performance of filter through the parameters like mean square error (MSE), peak signal to noise ratio (PSNR), Average difference value (AD) and Maximum difference value (MD) to diminish the noises without corrupting the medical image data.

The present study was conducted with the aim of analyzing the impact of social networks on political socialization and political participation of political science students of the Islamic Azad University of Tehran, Tehran south branch during 2007-2017. This article is a descriptive-survey research based on the theory of planned behavior and has been done based on random sampling with a population of 280 samples. The findings indicate that 93% of students use social media and spend a significant part of their study hours on social networks, which mainly include Telegram, Instagram, Facebook, Twitter and WhatsApp. The variables related to social networks affect the socialization and political participation of students, and the extent of the impact of social networks on encouraging individuals to participate in the election as a component of political socialization is positive and significant. This finding and other findings are a positive and significant impact of social networks on the attitudes, values ​​and norms, attitudes and behaviors of political science students as a sample population, and thus the hypothesis of this research has been confirmed.

Critical realism emerged from the philosophical writings of Roy Bhaskar, and has evolved into a philosophy of social science research using the model of “dialectical critical realism” (DCR) which begins with the researcher’s assumptions that the structures being researched have a real, ontological grounding which is independent of the researcher. This approach has proved fruitful in British and European social science research, but has had less influence in North America. We outline DCR’s four level model for understanding society and its changing social structures through “the pulse of freedom”. DCR has been used by Marxists, Muslims, Catholics and secular scholars who engage fruitfully in morphogenic dialogues leading to a critical realist understanding of society and social research, which transcends positivist and social constructionist models. Examples of DCR’s application in the fields of childhood research, child abuse, education, and research on organisations are outlined to illustrate the working of this new research paradigm. We are enthusiastic in our advocacy of DCR as a model of qualitative research, and for constructing models of positive social change, and are particularly impressed by the substantive and theoretical expositions of DCR by Priscilla Anderson, Matthew Wilkinson and Margaret Archer, whose work we document and review.

This paper uses panel data to find the determinants of tracking errors in exchange traded funds (ETFs) in the Hong Kong stock market. A comparison of tracking errors between physical and synthetic ETFs also indicates that the synthetic ETFs have higher tracking errors. The magnitude of tracking errors is found to be negatively related to size but positively related to dividend yield, trading volumes of funds, and market risk. However, this study also finds that expense ratio has a negative impact on tracking error, which is not consistent with previous studies, and which this paper addresses.

Cancer cells can acquire a spectrum of stable hybrid epithelial/mesenchymal (E/M) states during epithelial-mesenchymal transition (EMT). Cells in these hybrid E/M phenotypes often combine epithelial and mesenchymal features and tend to migrate collectively commonly as small clusters. Such collectively migrating cancer cells play a pivotal role in seeding metastases and their presence in cancer patients indicates an adverse prognostic factor. Moreover, cancer cells in hybrid E/M phenotypes tend to be more associated with stemness which endows them with tumor-initiation ability and therapy resistance. Most recently, cells undergoing EMT have been shown to promote immune suppression for better survival. A systematic understanding of the emergence of hybrid E/M phenotypes and the connection of EMT with stemness and immune suppression would contribute to more effective therapeutic strategies. In this review, we first discuss recent efforts combining theoretical and experimental approaches to elucidate mechanisms underlying EMT multi-stability (i.e. the existence of multiple stable phenotypes during EMT) and the properties of hybrid E/M phenotypes. Following we discuss non-cell-autonomous regulation of EMT by cell cooperation and extracellular matrix. Afterwards, we discuss various metrics that can be used to quantify EMT spectrum. We further describe possible mechanisms underlying the formation of clusters of circulating tumor cells. Last but not least, we summarize recent systems biology analysis of the role of EMT in the acquisition of stemness and immune suppression.

With the increase of the Artificial Neural Network (ANN), machine learning has taken a forceful twist in recent times. One of the most spectacular kinds of ANN design is the Convolutional Neural Network (CNN). The Convolutional Neural Network (CNN) is a technology that mixes artificial neural networks and up to date deep learning strategies. In deep learning, Convolutional Neural Network is at the center of spectacular advances. This artificial neural network has been applied to several image recognition tasks for decades and attracted the eye of the researchers of the many countries in recent years as the CNN has shown promising performances in several computer vision and machine learning tasks. This paper describes the underlying architecture and various applications of Convolutional Neural Network.

Biological systems are highly regulated. They are also highly resistant to sudden perturbations enabling them to maintain the dynamic equilibrium essential for sustenance of life. This robustness is conferred by regulatory mechanisms that influence the activity of enzymes/proteins within their cellular context, to adapt to changing environmental conditions. However, the initial rules governing the study of enzyme kinetics were tested and implemented for mostly cytosolic enzyme systems that were easy to isolate and/or recombinantly express. Moreover, these enzymes lacked complex regulatory modalities. Now, with academic labs and pharmaceutical companies turning their attention to more complex systems (for instance, multi-protein complexes, oligomeric assemblies, membrane proteins and post-translationally modified proteins), the initial axioms defined by Michaelis-Menten (MM) kinetics are rendered inadequate and the development of a new kind of kinetic analysis to study these systems is required. The current review strives to present an overview of enzyme kinetic mechanisms that are atypical and, oftentimes, do not conform to the classical MM kinetics. Further, it presents initial ideas on the design and analysis of experiments in early drug-discovery for such systems, to enable effective screening and characterisation of small-molecule inhibitors with desirable physiological outcomes.

A multi-tool analytical practice was used for characterization of 16^th century carpet manufactured in Cairo. Mild extraction method with hydrofluoric acid enabled isolation of intact flavonoids and their glycosides, anthraquinones, tannins and indigoids from fibre samples. High-performance liquid chromatography coupled to spectroscopic and mass spectrometric detectors was used for identification of natural dyes present in the historical samples. Weld, young fustic and brazilwood were identified as the dye sources in yellow thread samples. Red fibres have been colored with lac dye, whereas green fibre shades were obtained with indigo and weld. Tannin-containing plant material in combination with indigo and weld were used to obtain brown hue of thread. Four uncommon and thus-far unknown dye components were also found in the historical samples. These compounds probably represent unique fingerprint of dyed threads from this region. Scanning electron microscopy with energy-dispersive X-ray detector (SEM-EDS) and Fourier transformation infrared spectroscopy (FT-IR) were used for identification and characterization of substrates and mordants present in the historical carpet. Carbon and oxygen were detected in large quantities as a part of the wool protein. The presence of aluminum, iron and calcium indicated their usage as mordants. FT-IR analysis showed bands characteristic to woolen fibres and SEM micrographs definite structure of wool.

We report here the synthesis of uniform nanospheres-like silver nanoparticles (AgNPs, 5-10 nm) and the dumbbell-like Fe3O4-Ag hybrid nanoparticles (FeAgNPs, 8-16 nm) by the use of seeding growth method in the presence of oleic acid (OA)/oleylamine (OLA) as surfactants. The antibacterial activity of pure nanoparticles and nanocomposites by monitoring the bacterial lag–log growth has been investigated. The electron transfer from AgNPs to Fe3O4NPs which enhances the biological of silver nanoparticles has been proven by nanoscale Raman spectroscopy. The lamellae structure in the spherulite of FeAgNPs/PE nanocomposites seems play the key role to the antibacterial activity of nanocomposites, which has been proven by nanoscale AFM-IR. An atomic force microscopy coupled with nanoscale infrared microscopy (AFM-IR) is use to highlight the distribution of nanoparticles on the surface of nanocomposite at the nanoscale. The presence of FeAgNPs in PE nanocomposites has a better antibacterial activity than that reinforced by AgNPs due to the faster Ag+ release rate from the Fe3O4-Ag hybrid nanoparticles and the ionization of AgNPs in hybrid nanostructure.

Native plants from the Brazilian Amazon Biome are rich in nutrientes, oils and fats and, therefore, represent a very important regional food resource. Althoung there is a global interest in the nutritional potential of tropical fruits, the potential of Amazonian fruits as source of essential fatty acids is still under exploited, since their composition is still understudied. ¹H Magnetic Resonance Nuclear (¹H NMR) is a robust spectroscopic tool to profile fatty acids components in oils. The objectives of this work were to use ¹H NMR to determine the fatty acids profile and the physicochemical properties of crude oils and fats obtained from fruits of Brazilian Amazon: açaí, ata-brava, bacaba, buriti, buritirana, murici amarelo, murici vermelho, piaçaba braba, tucumanzinho, pupunha red and yellow varieties. Oils were obtained by Soxhlet extraction using hexane as a solvent. After solvent removal by rotoevaporation, the resulting oils and fats were analyzed by ¹H NMR spectroscopy. Unsaturated fatty acids oleic (ω9), linoleic (ω6) and linolenic (ω3) acids were quantified in the oils and their physicochemical properties were determined. It was observed that the oils have predominately ω9 fatty acids, followed by ω6 and ω3 representatives. The physicochemical properties confirmed edibility and good quality of oils and fats present in the aforementioned Amazonian fruits.

Cyanobacteria are an ancient lineage of slow-growing photosynthetic bacteria and a prolific source of natural products with diverse chemical structures and potent biological activities and toxicities. The chemical identification of these compounds remains a major bottleneck. Strategies that can prioritize the most prolific strains and novel compounds are of great interest. Here, we combine chemical analysis and genomics to investigate the chemodiversity of secondary metabolites based on their pattern of distribution within some cyanobacteria. Planktothrix being a cyanobacterial genus known to form blooms worldwide and to produce a broad spectrum of toxins and other bioactive compounds, we applied this combined approach on four closely related strains of Planktothrix. The chemical diversity of the metabolites produced by the four strains was evaluated using an untargeted metabolomics strategy with high-resolution LC-MS. Metabolite profiles were correlated with the potential of metabolite production identified by genomics for the different strains. Although, the Planktothrix strains present a global similarity in term biosynthetic cluster gene for microcystin, aeruginosin and prenylagaramide for example, we found remarkable strain-specific chemo-diversity. Only few of the chemical features were common to the four studied strains. Additionally, the MS/MS data were analyzed using Global Natural Products Social Molecular Networking (GNPS) to identify molecular families of the same biosynthetic origin. In conclusion, we present an efficient integrative strategy for elucidating the chemical diversity of a given genus and link the data obtained from analytical chemistry to biosynthetic genes of cyanobacteria.

Background The World Health Organization has recently recognized Long COVID, calling the international medical community to strengthen research and comprehensive care of patients with this condition. However, if Long COVID pertains to children as well is not yet clear. Methods An anonymous, online survey was developed by an organization of parents of children suffering from persisting symptoms since initial infection. Parents were asked to report signs and symptoms, physical activity and mental health issues. Only children with symptoms persisting for more than four weeks were included. Results 510 children were included (56.3% females) infected between January 2020 and January 2021. At their initial COVID-19 infection, 22 (4.3%) children were hospitalized. Overall, children had persisting COVID-19 for a mean of 8.2 months (SD 3.9). Most frequent symptoms were: Tiredness and weakness (444 patients, 87.1% of sample), Fatigue (410, 80.4%), Headache (401, 78.6%), Abdominal pain (387, 75.9%), Muscle and joint pain (309, 60.6%), Post-exertional malaise (274, 53.7%), rash (267, 52.4%). 484 (94.9%) children had had at least four symptoms. 129 (25.3%) children have suffered constant COVID-19 infection symptoms, 252 (49.4%) have had periods of apparent recovery and then symptoms returning, and 97 (19.0%) had a prolonged period of wellness followed by symptoms. Only 51 (10.0%) children have returned to previous levels of physical activity. Parents reported a significant prevalence of Neuropsychiatric symptoms. Conclusions Our study provides further evidence on Long COVID in children. Symptoms like fatigue, headache, muscle and joint pain, rashes and heart palpitations, and mental health issues like lack of concentration and short memory problems, were particularly frequent and confirm previous observations, suggesting that they may characterize this condition. A better comprehension of Long COVID is urgently needed..

Cloud Computing is a promising and emerging technology that is rapidly being adopted by many IT companies due to a number of benefits that it provides, such as large storage space, low investment cost, virtualization, resource sharing, etc. Users are able to store a vast amount of data and information in the cloud and access it from anywhere, anytime on a pay-per-use basis. Since many users are able to share the data and the resources stored in the cloud, there arises a need to provide access to the data to only those users who are authorized to access it. This can be done through access control schemes which allow the authenticated and authorized users to access the data and deny access to unauthorized users. In this paper, a comprehensive review of all the existing access control schemes has been discussed along with analysis. Keywords: role-based access control, attribute-based access control, attribute-based encryption

The significance of arts incorporated with culture inclusion makes the arts a matter of pressing interest. The arts are vital elements of a healthy society that benefits the nations even in difficult social and economic times. Based on the previous studies this research was conducted for the first time in Pakistan to explore the historical background of public art correlated with cultural and religious ethics. Though, Pakistan has a rich cultural history yet the role of modern public art is new and often used unintentionally. Our findings of different surveys conducted in Pakistan including oldest cities such as Lahore, Peshawar and newly developed, the capital city, Islamabad concluded that Public art has a rich cultural and historical background and the local community are enthusiastically connected to it. Different community groups prefer different types of public art in their surroundings depends on the city’s profile, cultural background, and religious mindset of the local community. Overall, the sculptures and depiction of animated beings are not considering right and debatable among the Pakistani societies. On the other hand, the cultural and historical monuments are highly appreciated and welcomed by the local community of Pakistan. This study may create scope for future estimation and development of public art in Pakistan in association with Islamic laws and cultural norms of the local society.

This research paper is to analyze the planning and design techniques of the tourism complexes in the process of municipalities’ master planning. First, it explains the importance of the tourism industry with the help of theories of scholars and experts. Then, it emphasizes the link between the economic developments of cities/regions with the development of the tourism industry. The innovation of this work is to integrate tourism industry planning and comprehensive regional/ urban planning. The main way of doing this is to plan and design the tourism complexes in the early stages of the master planning of the municipality. Urban land-use policies and locating techniques are suggested through this research. Land-use policies and new urban design models for the regional/urban sustainable development are some of the other handouts in this paper. The outcome of this research is good assistance for engineers, planners, and students of urban and regional development.

Multiple preventive vaccines are being developed to counter the COVID-19 pandemic. The leading candidates have now been evaluated in non-human primates (NHPs) and human Phase 1 and/or Phase 2 clinical trials. Several vaccines have already advanced into Phase 3 efficacy trials, while others will do so before the end of 2020. Here, we summarize what is known of the antibody and T-cell immunogenicity of these vaccines in NHPs and humans. To the extent possible, we compare how the vaccines have performed, taking into account the use of different assays to assess immunogenicity and inconsistencies in how the resulting data are presented. We also summarize the outcome of SARS-CoV-2 challenge experiments in immunized macaques, while noting variations in the protocols used, including but not limited to the virus challenge doses.

The hybrid system is analyzed and optimized to produce electric energy in Non-Interconnected Zones in the Colombian Caribbean region, contributing both to the improvement in the reduction of greenhouse gas emissions and to the rational use of energy. A comparative analysis of the performance of these systems was carried using a dynamic model in real wind and solar data. The model is integrated by a Southwest Wind Power Inc. wind turbine. AIR 403, a proton exchange fuel cell (PEM), an electrolyze, a solar panel and a charge regulator based on PID controllers to manipulate oxygen and hydrogen flows in the cell. The transient responses of the cell voltage, current, and power were obtained for the demand of 200 W for changes in solar radiation and wind speed for all days of the year 2013 in the Ernesto Cortissoz airport, Puerto Bolívar, Alfonso Lopez airport and Simon Bolívar airport, by regulating the flow of hydrogen and oxygen into the fuel cell. The maximum contribution of power generation from the fuel cell was presented for the Simon Bolívar airport in November with a value of 158,358W (9.45%). A multi-objective design optimization under a Pareto front is presented for each place studied to minimize the Levelized Cost of Energy and CO₂ emission, where the objective variables are the number of panel and stack in the PV system and PEM.