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Huge quantities of harvest wastes that are generated from agricultural practices at every farming season in Nigeria are not put into significant use. As an attempt towards adopting these abundant by-products as bioenergy resources for electricity generation, yearly quantities of both cocoa and kolanut harvest residues were estimated in this study. Hygroscopic natures and moisture contents of the two, and their blends, were also analyzed and compared. It was estimated that approximately 681,000 tons and 90,000 tons of cocoa and kolanut husks respectively, are produced in the country annually. While the proximate analyses showed that the sample made of 100% cocoa waste had the least volatile matter and moisture contents in addition to having highest fixed ash and fixed carbon contents, the reverse was the case with the sample made of 100% kolanut waste composition. From the ultimate analyses, however, the latter appears to possess the best characteristic (highest hydrogen and least oxygen contents), but its highest nitrogen content is a pointer to its exhibition of poor thermal property. The gross calorific contents of the samples were, therefore employed for definitive determination of their thermoelectric potentials and these gave higher heating values of 15.19 MJ/kg and 13.87 MJ/kg respectively, with the blends having their values within this range in proportionality to the mass percentage of kolanut husk in the blends. In addition to the two wastes exhibiting good energy characteristics, the study concludes that their blending offers benefit of reduction in ash content. At the optimal blend of equal composition of the two materials (50%CPH/50%KPH), it was estimated that 29,000 MW of electricity is accruable from the wastes., Highlights • Cocoa and kolanut harvest wastes of 681,000 and 90,000 tons respectively, are generated in Nigeria annually. • HHVs of the two agro-residues are 15.19 and 13.87 MJ/kg respectively, with their blends having values within this range. • The optimal blend composition of the two agro-residues has electric power generation potential estimated at 29,000 MW., Agro-wastes, biofuel materials, cocoa pod husk, kolanut pod husk, biomass blends, electrification.

The problem of environmental pollution in today's world is not just a problem for the country or a specific territory. This research was conducted with the aim of investigating the environmental behavior of Iranian citizens. The present study was carried out using meta-analysis method on the performed studies (1998–2018) on pro-environmental behavior Papers related to the subject were gathered with the keywords for environmental behavior and environmental support behavior through searching on Magiran, SID, Scopus, Medline (PubMed) and Science-direct databases. Heterogeneity of studies was obtained using the I2 index, and data were analyzed in the comprehensive meta-analysis software. In 21 papers submitted to the meta-analysis process, 10 papers in the score range 20–100 (A) and 11 papers in the score range 1–5 (B), the total number of samples entered into the study was 3670 in the age range of 15–87 year scores (A), 4413 in the age range of 10–70 year scores (B). The overall mean and standard deviation of the environmental behavior (A) based on a meta-analysis of 50.4 ± 3.1 (44.56%–2.5%: 95% confidence limit) and in the score range 1–5 (B), 3.4 ± 0.18 (3.05%–5.7%, 95% confidence limit), were obtained. The effect of sample size and the publication issue of studies based on meta-regression in order to investigate the effect of heterogeneity in studies. The mean increases in each interval from 1 to 5, with an increase in sample size; in both intervals with an increase in the publication issue, the mean scores increase (P < 0.05). According to Mata-analysis results, the environmental behavior of Iranian citizens in both study intervals, is about average the global mean index of environmental performance., Environmental support behavior, Iran, Meta-analysis, Systematic review, Pro-environmental behavior.

Academic institutions worldwide have had to adapt their methods of teaching and assessment due to COVID-19. In many Spanish universities exams moved online, affording students with opportunities to breach academic integrity that were not previously available to them. This paper uses the emerging research method of search engine data analysis to investigate the extent of requests for exam cheating information in Spain in the time period surrounding adjustments for the pandemic. The Internet data analytics technique is one that the paper proposes should be used more widely as an academic integrity research method. For this study, search engine activity data on exam cheating in Spain was collected and analysed for the five-year period between 2016 and 2020 inclusive. The data suggests that students are searching for information about ways to cheat in exams, including how to create cheat sheets. Most strikingly, the results show a significant increase in requests for information on cheating on online exams during the COVID-19 timeframe and the Spanish lockdown period. Based on the findings, academic institutions in other regions should be wary about the opportunities that their students have to commit exam fraud., Assessment; Exam cheating; Academic integrity; Spain; COVID-19.

The paper focuses on collection of information on recent multifaceted usage of biomass materials with critical examination on its sustainability. The use of biomass is becoming popular, with wide global acceptance as it is considered as green technology. The use of biomass products across industrial parallels, the material combination and production processes were elucidated in this paper. Biomass materials are seen as affordable alternative to conventional materials for domestic and industrial applications. The multifaceted use of biomass, which includes, energy generation, metallurgical applications, construction purposes, reinforcement in metal matrix composite, microelectromechanical system, biochemical and traditional medicine were discussed. This underscores the need to develop a sustainable plan to meet with its diverse usage to be beyond laboratory efforts. This paper examined whether the availability of biomass can sustain its multifaceted usage or not. It also examined the modalities to ensure sustainable use of biomass. Different policies were highlighted and discussed in line with continuous multifaceted use of biomass., Biomass; Multifaceted; Construction; Energy; Traditional medicine; Direct reduced iron; Metal matrix composite

Ghana produces over 50% of its electrical energy demands from fossil-fuelled thermal plants. To increase the proportion of renewable energy in the national energy generation, a Renewable Energy Master Plan (REMP) which seeks, among others, to shift the country's national energy generation capacity towards more renewable energy sources has been developed. The REMP noted that inadequate data on renewable energy sources such as wind is one of the challenges to achieving this target. In this regard, this paper assessed the open-source Weather Research and Forecasting Model, as a tool for generating wind resource data. The WRF model is often used to downscale meteorological datasets for wind resources assessments. However, due to diverse model options, performance assessments are required to establish the accuracy and suitability of a model configuration for an application in an area. This paper assessed the performance of a Weather Research and Forecasting Model configuration that is based on previous verification studies. In evaluation, data accuracy benchmarks were generally met by the downscaled wind data. A wind map that was generated was observed to be generally accurate and better than the previous 2001 wind map for Ghana. It is presumed that the configuration is suitable for wind mapping activities for the coastal areas in Ghana, and probably neighbouring countries. However, for downscaling time-series data, further studies are recommended., Wind mapping; Wind resources assessment; WRF; Dynamic downscaling; Ghana; West African coast.

The essence of this paper is to analyse the ripple effects caused from the intertwining and complex relationship between the relational and structural dimensions of social capital on the US based Kick starter projects’ outcomes. This will be measured based on real time data collected from the Kick starter. com in form of 1157 projects organised in the structure of the number of backers, amount of time taken to fund the projects and the converted amount pledged towards the projects, as classified according to various project categories and geographical locations. This research applies qualitative and quantitative statistical analysis methods as well as data mining techniques; k-Nearest Neighbour, Naive Bayes and Decision Tree Algorithms. The results from this research confirm that relational social capital i.e. the number of backers involved in the projects, has significantly strong and positive impact on the converted amount pledged towards a project and the project outcome. This paper also offers a feasible decision-making model that will be used by the entrepreneurs in the future to determine which type of project categories an entrepreneur can choose to host and the project outcome., Social capital theory dimensions; Crowdfunding; k-nearest neighbor; Naive Bayes; Decision tree algorithm.

For decades now, a lot of radio wave path loss propagation models have been developed for predictions across different environmental terrains. Amongst these models, empirical models are practically the most popular due to their ease of application. However, their prediction accuracies are not as high as required. Therefore, extensive path loss measurement data are needed to develop novel measurement-oriented path loss models with suitable correction factors for varied frequency, capturing both local terrain and clutter information, this have been found to be relatively expensive. In this paper, a large-scale radio propagation path loss measurement campaign was conducted across the VHF and UHF frequencies. A multi-transmitter propagation set-up was employed to measure the strengths of radio signals from seven broadcasting transmitters (operating at 89.30, 103.5, 203.25, 479.25, 615.25, 559.25 and 695.25 MHz respectively) at various locations covering a distance of 145.5 km within Nigerian urban environments. The measurement procedure deployed ensured that the data obtained strictly reflect the shadowing effects on radio signal propagation by filtering out the small-scale fading components. The paper also, examines the feasibilities of applying Kriging method to predict distanced-based path losses in the VHF and UHF bands. This method was introduced to minimize the cost of measurements, analysis and predictions of path losses in built-up propagation environments., Path loss measurement, Kriging Interpolation Method, prediction model, radio propagation

Transporting natural gas across different locations require compressor stations to provide the pressure needed to keep the gas moving. This paper presents a model for matching the gas turbine and gas compressor power required under different environmental conditions to support the continuous gas transmission across other locations. The trans-Saharan gas pipeline (TSGP) project proposed to transport gas from Nigeria to Algeria has been used as a case study in this paper. The TSGP project is a Nigerian Government initiative to rejig its gas development and transportation infrastructure to meet its internal and external market demand. The numerical method used in this paper integrates the effect of the ambient temperature in the power matching of the gas turbine and gas compressors. There are 18 compressor stations across the TSGP network, and compressor station 2 is used as the reference point. The daily temperature fluctuation is segmented into hours of the day, emphasising considerable ambient temperature variation at 3:00 h, 9:00 h, 15:00 h. One benefit of the model against others in the open literature is accounting for changes in the ambient temperature along the pipeline network and gas compression stations. Accounting for changes in ambient temperature provides accuracy to near real-life operational experience for gas distribution via pipelines. The model also accounts for variations in turbine entry temperature (TET) to compensate for changes in the ambient conditions to meet the power requirements of the gas turbine and the gas compressor. The results show that for every 1% increase in ambient temperature, a 3.5% increase in power is required to drive the gas compressor and a 1% decrease in gas turbine output power. The effect of the 1% increase in ambient would require a 3.5% increase in TET to meet both the gas turbine and gas compressor requirement., Gas compressor; Gas turbine; Ambient temperature; Power matching; Pipeline.

Nowadays, recognizing the current situation and forecasting the desired status of spatial analysis of infrastructures regarding security and defense considerations is of great importance. Besides, the use of approaches such as futures studies and its simultaneous application with GIS has the most fundamental contribution to the field of decision-making and appropriate planning method in studies on the spatial defense planning. Accordingly, this paper aims to evaluate the spatial distribution of regional infrastructures in the northeast of Iran using a passive defense approach. In this regard, a descriptive-analytical research methodology, library-documentary studies, and statistical surveys were used in the model framework along with software (Mic Mac and Scenario Wizard) and system analysis (GIS) to achieve the research objective. The statistical population of the study was defined in two human and spatial scales. The entire geographical space of Khorasan Razavi province made the spatial scale. On the human scale, 40 experts (n = 15) and elites (n = 25) in the field of this study were selected as the statistical sample using a purposive non-random model. It is noteworthy that all of the subjects had the required scientific and executive knowledge. According to the total research indicators, the vulnerable zones of the study area could be distinguished into five categories of areas with very high (7.33%), high (16.52%), moderate (29.78%), low (16.94%), and very low (29.4%) vulnerability. Also, according to the results, the density and dispersion patterns of the study area infrastructures were concentrated, clustered, and randomly self-clustered, respectively. In the meantime, factors such as legal, policy, and institutional infrastructure criteria were identified as key drivers influencing the spatial distribution of the province infrastructures. Therefore, it is possible to realize the future models in three scenarios of high desirability (green status), acceptable (yellow status), and crisis (red status). Finally, the paper concludes with some suggestions to increase the desirability of infrastructures in Khorasan Razavi province., Spatial futures studies; Passive defense; Regional infrastructure; Regional development.

Parking allocation has become a major problem in modern cities for which numerous smart parking systems (SPS) have been developed. This paper aims to provide comprehensive study, comparison and extensive analysis of SPSs in terms of technological approach, sensors utilized, networking technologies, user interface, computational approaches, and service provided. Moreover, the paper fills up the research gap by providing a clear insight into the suitability of SPSs in various environmental conditions and highlights their advantages/disadvantages. The extensive comparison among multiple aspects of SPSs would enable researchers, designers, and policymakers to identify the best suited SPS and understand the current trends in this sector., Smart parking system; Internet of things; Wireless sensor network; VANET; Sensor; Image processing; Smartphone application; Web application; Machine learning; Neural networks

Airborne droplets and contaminated surfaces are the main routes for the epidemic virus outbreak that causes the novel coronavirus. To reduce virus spread, people wear face masks and gloves daily, which massively increases the amount of waste generated in the environment. Also, the inappropriate disposal of used masks and gloves in communities may boost the spread of the novel coronavirus. However, no studies have been conducted to evaluate a public perception regarding the management of generated masks and gloves during the global health threat. Therefore, this paper proposes a study of public awareness, attitudes, and practices towards gloves and masks generated during the novel coronavirus pandemic in Saudi Arabia. The study showed that most of the participants (74%) have adequate awareness regarding the proper way to dispose of used masks and gloves, with 76% showing positive attitudes toward waste management. Gender shows a significant correlation with the regulations of medical waste collection and disposal (r = 0.169, p = 0.0001), and the consideration of the effective disposal of COVID-19 waste management as a collective responsibility of the community (r = 0.158, p = 0.0001). Also, the study shows that the majority of participants were aware on the availability of regulations for the collection and disposal of biomedical waste. Moreover, it demonstrates that public awareness regarding the attitude and measures taken by regional municipalities to reduce the spread of coronavirus has a significant positive correlation (r = 0.279, p = 0.0001). The study further recognized that the effective management of contagious wastes significantly protects the public against the improper practices of wastes disposal generated during the novel coronavirus pandemic., public perception; community perception; environmental impact; masks and gloves generated during the novel corona virus pandemic; medical waste management; novel coronavirus; novel coronavirus outbreaks

The article investigates the Covid-19 pandemic related changes in the demand for insurance services in the Unites States due to business interruptions by employing panel vector autoregression models to a dynamic panel data set of 50 states and District of Columbia for three periods of time: 01 January, 2004 to 28 June, 2020; 01 January, 2004 to January 21, 2020 (pre-Covid period); January 22, 2020 to June 28, 2020 (Covid-period). This paper is the first attempt to obtain estimates by applying Google Trends with a search key word “Business Interruption Insurance”. The data was collected and reduced to a single scale by US states within the widest possible time span. Google Trends Hits and Initial Claims for Unemployment Insurance Benefits are used as endogenous variables in the built models. In the constructed models, the impact of the exogenous variable New Covid Cases is compared with that of over US billion-dollar natural disasters. The impulse responses show a positive relationship between the Google Trends Hits and Initial Claims with the Covid-factor having a significant impact on the responses. The conducted analyses reveal that the demand for insurance services due to the Covid-19 outbreak in the United States can be expected to increase 2–6 times, with the total amount of the incurred costs for the economy due to the virus ranging from 0.3 to 7 percent of the US-2019 GDP. The results lay the foundation for recommending the insurance market participants to lobby for adoption of public-private protection schemes being able to secure a more efficient response to the pandemic-related losses that may occur in the future., Business interruption insurance; Unemployment insurance; Covid; Google Trends; Catastrophes, PVAR.

Following a theory of strategic positioning perspective, this paper aims to explore the operating context in which dimensions of the macro-environment factors are likely to enhance Small and Medium Enterprise's (SMEs) intentions to invest in the Ghana's’ downstream oil and gas sector. Specifically, macro environment model has been developed wherein an important exogenous context (supply chain resilience) variable has been considered and studied its moderating effect on the relationship between macro environment dimensions and intentions to invest. The study also, examined the conditional effect of micro environment dimensions on intention to invest at different levels of supply chain resilience. Using Partial Least Square method we analyze cross sectional data across Ghana's SMEs spectrum between the periods 2017–2018. Our indicative evidence suggests that political factors, economic factors, environmental factors and technological factors are related to SMEs intentions to invest in the down stream oil and gas. Moreover, the research findings revealed that supply chain resilience moderated the relationship between macroenvironment dimensions and intention to invest. The link between macro environment dimensions and intention to invest was strengthened via the interaction effect of supply chain resilience. These robust results are consistent with the theory of strategic positioning. Overall, our results are akin to policy makers agenda to create enabling macro environment to improve local businesses participation in the Ghanaian oil and gas value chain. Besides, the findings will assist SMEs owners and managers in their decisi ons to invest in the downstream oil and gas sector by strengthening investment capability at different levels of Supply chain resilience., Downstream oil and gas; Ghana; Investment intention; Non-renewable energy PLS.

Agricultural soils need monitoring systems to address pesticide risks for humans and the environment. The purpose of this paper was to obtain leaching risk maps of the pesticides imidacloprid, lambda-cyhalothrin, and chlorpyrifos in agricultural soil under an onion (Allium cepa L.) crop in Tibasosa, Boyacá, Colombia. This was obtained by studying the soil types in the area, analyzing the behavior of pollutants in the soil profile, using a delay factor and an attenuation factor to finally include GIS allowing visualization of the areas of greater potential risk in the study area., Leaching; Partition coefficient; Imidacloprid; Lambda-cyhalothrin; Chlorpyrifos; Potential risk.

Highlights • Double Generative Adversarial Networks for Image Enhancement and Super Resolution. • Improving the accuracy of LPR systems using image super resolution., License Plate Recognition (LPR) is an important implemented application of Artificial Intelligence (AI) and deep learning in the past decades. However, due to the low image quality caused by the fast movement of vehicles and low-quality analogue cameras, many plate numbers cannot be recognised accurately by LPR models. To solve this issue, we propose a new deep learning architecture called D_GAN_ESR (Double Generative Adversarial Networks for Image Enhancement and Super Resolution) used for effective image denoising and super-resolution for license plate images. In this paper, we show the limitation of the existing networks for image enhancement and image super-resolution. Furthermore, a feature-based evaluation metric called Peak Signal to Noise Ratio Features (PSNR-F) is used to evaluate and compare performance between different methods. It is shown that the use of PSNR-F has a better performance indicator than the classical PSNR-pixel-to-pixel (PSNR-pixel) evaluation metric. The results show that using D_GAN_ESR to enhance the license plate images increases the LPR accuracy from 30% to 78% when blur images are used and increases the accuracy from 59% to 74.5% when low-quality images are used., Graphical abstract, Image Super Resolution; Image Enhancement; LPR

Biomass and fossil fuels are mostly used in rural areas of developing countries for cooking. These energy resources have negative impacts on the environment and human health mainly due to deforestation and greenhouse gas emissions. A cleaner and environmentally-friendly form of cooking is solar cooking using the sun's energy. Parabolic solar cookers perform better than other solar cookers such as box solar cookers since higher temperatures are achieved in a shorter duration. These higher temperatures allow most types of cooking processes such as; boiling, frying, roasting, and baking to be possible. The major problem with most conventional solar cookers is that cooking is not possible during off-sunshine periods. Integrating solar cookers with thermal energy storage (TES) makes cooking during off-sunshine periods possible. This paper presents a comprehensive review of parabolic solar cookers with TES which is a sustainable cooking solution for developing countries. Previous work on both parabolic trough and parabolic dish solar cookers with TES is presented. Solar cookers with storage are classified according to the two main types of TES technologies which are; sensible heat thermal energy storage (SHTES) and latent heat thermal energy storage (LHTES). The main conclusions of the review are that; parabolic dish solar cookers with TES are more common than parabolic trough cookers, more studies have been done using latent heat storage as compared to sensible heat storage, limited modelling work has been presented, most of the parabolic cookers used aluminum sheets as the reflecting material, large scale experimental studies are limited and fewer studies tackled the techno-economic and socio-economic aspects. The review also highlights research gaps on parabolic solar cookers with TES in terms of the modelling, combined TES (sensible and latent heat), different reflector materials, large-scale experimental setups, and techno-economic and socio-economic analyses. Other important aspects to consider for parabolic solar cookers with TES include; the choice of sensible or latent heat storage materials, environmental impact, types of food to be cooked, and social acceptance., Concentrating solar cooker, Latent heat, Sensible heat, Thermal energy storage, Parabolic dish cooker, Parabolic trough cooker.

This paper studies the determinants of why low-income households in Ireland abandon energy efficiency retrofit applications using administrative data from a targeted energy efficiency grant. By applying for the scheme, the applicants overcome any financial barriers for undertaking retrofits and demonstrate their willingness to improve the energy efficiency of their dwellings. Hence this study contributes to the scarce literature on non-financial barriers preventing low-income households from undertaking energy efficiency retrofits. Contrary to previous findings, we find that the higher the number of retrofits to be implemented, the lower the probability of households abandoning their applications. We also find that planning to undertake retrofits such as ventilation, which can significantly improve the health and safety standards of the dwelling, is associated with a higher probability of abandonment. Both findings indicate the presence of key behavioural and informational barriers which prevent low-income households from fully comprehending the purpose or benefits of proposed energy efficient retrofits. Our findings also suggest that higher grant expenditure on dwellings with poor pre-works energy efficiency rating and on retrofits such as attic insulation and heating system upgrades may have the highest energy efficiency improvements per unit of expenditure. Within the constraints of limited budgets for retrofit grant supports, this research can inform the redesign of grant schemes to achieve the greatest aggregate improvements in residential building energy efficiency., Energy efficiency; Energy retrofits; Retrofit intensity; Vulnerable households; Abandonments

This paper investigates the determinants of and trends in credit demand and credit constraints of households with respect to both formal and informal financial institutions in Ghana. Trends and explanatory factors over 1992–2013 using pooled data from four Ghana Living Standards Surveys are analysed using the Heckman Probit model. Estimates for the full population reveal that tertiary education is a significant determinant of both credit requests (positively) and credit constraints (negatively). In the rural population, household heads that were widowed or separated and those that lived below the poverty line are more likely to request credit and also more likely to experience credit constraints. In the urban population, the aged are less likely to request credit but more likely to experience credit constraints. The policy implication is that financial inclusion measures targeted to people living below the poverty line, the widowed and separated in rural communities are needed to respond to their relatively high demand for credit services and overcome their exclusion from access to credit that could help in generating income to reduce poverty. The sex of a household head is significant for binding credit constraints in the full population and the urban sample, but not significant in the rural sample. Surprisingly, the study finds a decline in the proportion of households requesting credit in the full population as well as rural and urban areas, indicating increasing self-exclusion., Credit demand, Credit constraints, Ghana, Financial institutions, Financial Inclusion

The academic sectors are badly affected by the COVID-19 pandemic globally. The studies regarding the implications of COVID-19 in education in Nepal were minimal, thus, this paper aims to highlight the impacts of the pandemic on the education sector of Nepal. It is revealed that the Nepalese academia has been facing problems due to lack of adequate and appropriate sustainable infrastructure for the online system, including skilled human resources. In addition, limited internet facilities in remote and rural areas were the other challenging tasks for virtual academic activities. Therefore, the concerned stakeholders should provide necessary services and appropriate strategies for virtual means of the education system to compensate the repercussion caused by the pandemic. This study could be helpful to identify the critical needs emerged due to the pandemic at present and in future and also contribute to adopt appropriate policy for the revival of educational institutions., COVID-19; Pandemic; Virtual education; Online education, Nepal.

The increasing development of transaction technology investment in the financial sector of the national economy especially Automated Teller Machine (ATM) in Ethiopia banking industry is below customers demand. The availability and deployment of ATM in Ethiopia is low-level compared to the fast growing urban population. Thence, the prime objective of this paper is to evaluate the determinants of ATM deployment in commercial banks of Ethiopia. In order to achieve the objective, panel data was gathered from thirteen Ethiopian commercial banks for the sampled time period beginning from 2012 to 2016. This study used descriptive statistics and panel data econometric regression analysis to analyze the data collected. The random effect model was employed as a reasonable fit model for this study and interpretations of estimates were made based on this model. The result of the descriptive analysis indicated that the trend of ATM deployment in commercial banks of Ethiopia was rising over the sample time period. The results investigated from random effect model indicated that that bank size, bank profitability and deposit ratio were statistically significant and had positive impact on ATM deployment. Meanwhile, cost efficiency and number of branches had statistical insignificant relationship with ATM deployment in Ethiopian commercial banks. Based on these findings, it is recommended that the commercial banks of Ethiopia or any concerned body need to envisage the bank size, bank profitability and deposit ratio in introducing and expansion of ATM and any other electronic form of payments., Automated teller machine (ATM); Commercial banks of Ethiopia; Deployment.

The localization and quantification of endothelial progenitor cells (EPCs) are controversial. Circulating CD34 + cells in blood have been identified as EPCs and as biomarkers of cardiovascular disease. We discuss in this paper the current data describing differential phenotype and behavior in vitro of CD34 positive cells from the circulation and adipose tissue (AT). We also describe in brief our own findings from CD34 + cells isolated from leukopheresis cones derived from healthy platelet donors and from patients undergoing bariatric surgery. We conclude that CD34 + cells in blood and in AT are different in antigenic profile and behavior in culture. The findings described assert that CD34 + cells detected in blood previously identified as biomarkers of cardiovascular disease are predominantly HPCs rather than EPCs, and that true CD34 + EPCs can be readily identified and extracted from AT, supportive of the current evidence which suggests EPCs are resident in the tissue vasculature., Endothelial progenitor cells; Hematopoietic progenitor cells; Adipose tissue, Peripheral blood; Flow cytometry; Cell culture.

India has proven to be one of the most diverse and dynamic economic regions in the world. Its industry focuses predominantly on the service sector and immediate economic growth seems to steer India into the economic superpower. India's unique business landscape is felt at a regional level, where massive urbanization has become an unavoidable consequence of population growth and spatial allocation to the economic hubs of metropolitan cities. Mumbai, one of the world's largest cities, represents a unique combination of a diverse economic landscape and the growth of a megacity. The role of Mumbai in India's growth is of crucial importance for India's business landscape. This paper explores the massive urbanization processes of Mumbai's peri-urban areas and compares urban sprawl with the location of its business landscape. A spatial accounting methodology based on the proximity of Mumbai's different economic hubs will be used to measure the underlying pattern of the Mumbai region, concerning past and present urbanization, and the effect of this urbanization process has on the possible location of businesses. This business-urban ecosystem perspective will be implemented by a spatial analysis on the correlation between urban compactness and urban footprints, in relation to business concentration and its spatiotemporal evolution over the last hundred years., data science, Self-organizing maps, spatial regressions, GIS.

Outlier scanpaths identification is a crucial preliminary step in designing visual software, digital media analysis, radiology training and clustering participants in eye-tracking experiments. However, the task is challenging due to the visual irregularity of the scanpath shapes and the difficulty in dimensionality reduction due to geometric complexity. Conventional approaches have used heat maps to exclude scanpaths that lack a similarity pattern. However, the typically-used packages, such as ScanMatch and MultiMatch often generate discordant results when outlier identification is done empirically. This paper introduces a novel outlier evaluation approach by integrating the fractal dimension (FD), capturing the geometrical complexity of patterns, as an additional parameter with the heat map. This additional parameter is used to evaluate the degree of influence of a scanpath within a dataset. More specifically, the 2D Cartesian coordinates of a scanpath are fitted to a space filling 1D fractal curve to characterise its temporal FD. The FDs of the scanpaths are then compared to match their geometric complexity to one another. The findings indicate that the FD can be a beneficial additional parameter when evaluating the candidacy of poorly matching scanpaths as outliers and performs better at identifying unusual scanpaths than using other methods, including scanpath matching, Jaccard, or bounding box methods alone., Higuchi fractal dimension; Visual scanpath; Hilbert curve; Outlier; Computational neuroscience

Whenever the term "Gender" is mentioned, many readily attribute it to the womenfolk who, in many societies, are challenged and often put in a disadvantaged position concerning the men. As a result, many women empowerment programs are being championed to cushion the effects of this subjugation on women. This paper attempts to look into gender and understand what has been in existence concerning gender roles, especially for females, and how it contributes to development. It is also important to note that development is not something that happens in space or the product of eventualities but a concrete phenomenon that requires all to achieve. There is a specific role to play by both men and women to attain African development. Therefore, gender issues with all that relates to it can impinge on societal development. The secondary data collection was used by empirically engaging literature and British council report in tracing how Gender inequality began to be perceived. The study applied the theory of recognition by Axel Honneth and the functionalist approach in explaining the issues of gender and how it can engender development if adequately handled. It was discovered that if both genders are correctly appreciated with each playing their role, not discriminating or demeaning any position, the resultant effect will not only result in development; instead, sustainable development will be attained., Development; Gender; Gender roles; Gender inequality; Sustainable development.

Background The act of worshipping in mosque is often not only considered to be one of the factors causing the transmission of coronavirus disease 2019 (covid-19), but also a contributing factor to health protocol violations. Against this backdrop, the purpose of this paper is to examine the application of the Islamic principle of ḥifẓ al-nafs (protection of life) in the practice of worshipping at the Nurul Iman mosque as it relates to the prevention of transmission of covid-19. Methods This research uses a sociology of law perspective to the connection and the dynamics between the adoption of the principle of ḥifẓ al-nafs and the implementation of worship at the Nurul Iman mosque. As a case study, the data collection technique used includes interviews, observation, documentation reviews, and triangulation techniques, while the analysis technique used content analysis techniques. Results The application of the principle of ḥifẓ al-nafs (protection of life) in the practices of worship at the Nurul Iman mosque have proven to be in accordance with health protocols and at the same time all members of the mosque congregation have been free from the transmission of covid-19. From an Islamic needs framework perspective, in the context of Covid-19 pandemic, the application of the ḥifẓ al-nafs principle at this mosque is a considered primary necessity (ḍarūriyyāt) in that it protects life while providing spiritual continuity of collective religious worshipping, hence integrating the community together within a health and sanctity of life paradigm during this challenging time. Equally important, this research also challenges the thesis of the direct linkage between worshipping in mosque and Covid-19 transmission. Conclusion the application of the principle of ḥifẓ al-nafs in the practices of worship in mosque has demonstrably shown that the congragants levels of health consciousness has increased and that they have also been kept safe. In essence, the effective contextualization of Islamic principle is able to provide the twin benefits of health and spirituality.

Mining companies use environmental sustainability reporting to inform their stakeholders about their position in relation to environmental sustainability. This paper explores how these companies include topics related to the environment and its protection in their annual reports. The 100 largest mining companies listed on the Australian Stock Exchange (ASX) were included in the research sample, using market capitalisation as the size indicator. The investigation was performed by means of quantitative and qualitative content analysis of annual reports to identify relevant keyword occurrences. Results revealed that topics related to protection of the environment, emissions, carbon footprint, and climate change are addressed in companies’ annual reports. In line with research in other industries, this study confirmed that the intensity of communication about these topics varies with company size. A new methodology was developed to assess the extent to which mining companies inform the stakeholders about their environmental protection initiatives and to address the limited applicability of the GRI G3 disclosure checklist for sustainability reporting, thereby enhancing the theory of social licence to operate., Environmental sustainability reporting, Mining companies, Mining sector, Social licence to operate, Stakeholder relationships.

Since the emergence of urban planning science at the beginning of 20th century, urban disruption as innovation is highly connected to the urban planning framework, it goes along in responding urban problem, in conjunction with the civilization development, from innovation in terms of planning process and field survey in the early 20th century to the use of information and communication technology (ICT) as analytical planning tools in 2010s. The emergence of Coworking Spaces in Bandung, a capital city of West Java where many universities were founded, and a place for youth scholarship and creativity, is an appropriate location to be used as a case study. This paper aims to analyze spatial patterns and linkages with local features, using kernel density and also somer's d association analysis to determine the presence, strength, and direction of the relationship asymmetrically. This is important to analyze the emergence of Coworking Spaces as a part of urban disruption process in promoting city centre vitality while the advance of technology, service sector expansion, liveable building design become primary focus of globally Coworking Spaces discourses., Coworking spaces, Urban disruption, Spatial patterns, Agglomeration economies, Bandung city.

This paper examines impacts of adoption of wheat chickpea double cropping on yield and farm income of smallholder rural farmers in Becho district, South West Shewa Zone, Oromia Region, Ethiopia. The study used cross-sectional data collected from 203 smallholder farm households selected randomly through two-stage stratified random sampling technique. Propensity score matching was employed to analyze the impacts of adoption on yield and farm income. The result showed that adoption of wheat-chickpea double cropping has significant impact on yield and farm income of the group of adopter households compared to the group of non-adopters. With regard to yield, adopters harvested average wheat yield of 2120 kg/ha, while the non-adopters harvested average wheat yield of 1420 kg/ha. In addition, the treated households earned average annual farm income of about 709.125 Euro per year from sale of both wheat and chickpea as adopters; while the non-adopters earned average farm income of 129 Euro from sale of wheat. These results imply that scaling out of wheat-chickpea double cropping contributes to food security and rural livelihood improvement through yield and farm income increment. Hence, encouraging farmers towards adoption of wheat-chickpea double cropping is essential for improving livelihoods of rural households by properly addressing factors such as access to improved seeds, training on double cropping, involvement in non-farm income activities, access to broad bed maker (BBM), ownership of tropical livestock unit (TLU) and access to fertilizer., Wheat, Chickpea, Adoption, Double cropping, Impacts, Yield, Farm income.

Big data analytics and artificial intelligence are revolutionizing the global healthcare industry. As the world accumulates unfathomable volumes of data and health technology grows more and more critical to the advancement of medicine, policymakers and regulators are faced with tough challenges around data security and data privacy. This paper reviews existing regulatory frameworks for artificial intelligence-based medical devices and health data privacy in Bangladesh. The study is legal research employing a comparative approach where data is collected from primary and secondary legal materials and filtered based on policies relating to medical data privacy and medical device regulation of Bangladesh. Such policies are then compared with benchmark policies of the European Union and the USA to test the adequacy of the present regulatory framework of Bangladesh and identify the gaps in the current regulation. The study highlights the gaps in policy and regulation in Bangladesh that are hampering the widespread adoption of big data analytics and artificial intelligence in the industry. Despite the vast benefits that big data would bring to Bangladesh's healthcare industry, it lacks the proper data governance and legal framework necessary to gain consumer trust and move forward. Policymakers and regulators must work collaboratively with clinicians, patients and industry to adopt a new regulatory framework that harnesses the potential of big data but ensures adequate privacy and security of personal data. The article opens valuable insight to regulators, academicians, researchers and legal practitioners regarding the present regulatory loopholes in Bangladesh involving exploiting the promise of big data in the medical field. The study concludes with the recommendation for future research into the area of privacy as it relates to artificial intelligence-based medical devices should consult the patients' perspective by employing quantitative analysis research methodology., Big data, Artificial intelligence, Data privacy, Data protection, Health information, Medical device regulation, Healthcare policy.

This paper assesses the impact of resource accessibility, seed sources and varietal diversification on the production efficiency of Sri Lankan rice growers using farm and household level survey data. The empirical results show that there are opportunities for average Sri Lankan rice farmers to further improve production efficiency by up to 30%. Among the variables, those related to resource accessibility, age, migration, income sources and agricultural training are all found to affect production efficiency. Furthermore, we find that households relying only on their own saved seeds are less efficient compared to those who had purchased seeds from markets. In addition, this study indicates that varietal diversification significantly reduces production efficiency., Technical efficiency, Rice farmers, Stochastic frontier analysis, Determinants, Sri Lanka.

Assessing landform vulnerability to soil erosion is crucial for improved sustainable land use planning and management. In the Loess Plateau of the Northern Shaanxi Province of China, soil erosion has been reported as a major threat to sustainable land management and impacts on driving the socio-economic benefits that can be accrued from the landforms. Several studies especially on Erosion Potential Mapping (EPM) in the region have been conducted but the role of the fractal dimension (FD) of the terrain features has been limited. In this study, the paper assessed the role of fractal terrain features on the overall EPM. The Analytical Hierarchical Process (AHP) was adopted using 6 criteria, FD of the terrain, Land Use Land Cover, Slope, Elevation, Geomorphology and Flow Accumulation. These were developed in a Geographic Information System (GIS) framework. Eight Scales (8) were evaluated in order to select the best Scale with the lowest Consistency Ratio (CR) and the Minimum Relative Error (MRE). The results from this study shows that fractal features of terrain when integrated with the rest of the criteria produced a reliable EPM for the study area. The absence of the FD also gives unrealistic results for the EPM. The EPM with FD distribution recorded 29.4% for low erosion potential whereas EPM without FD recorded 46.7%. A larger portion of the Shaanxi province (70%) is found to be at a higher risk of erosion. Therefore, it is hoped that the findings from this research would further boost the integration of fractals into EPM in China and similar regions across the World. The study further recommends that sustainable soil management measures are put in place to reduce the erosion risk in the province to protect the natural ecological habitat., Erosion Potential Mapping, Consistency Ratio, AHP, Flow Accumulation.

Machine learning (ML) methods can be leveraged to prevent the spread of deadly infectious disease outbreak (e.g., COVID-19). This can be done by applying machine learning methods in predicting and detecting the deadly infectious disease. Most reviews did not discuss about the machine learning algorithms, datasets and performance measurements used for various applications in predicting and detecting the deadly infectious disease. In contrast, this paper outlines the literature review based on two major ways (e.g., prediction, detection) to limit the spread of deadly disease outbreaks. Hence, this study aims to investigate the state of the art, challenges and future works of leveraging ML methods to detect and predict deadly disease outbreaks according to two categories mentioned earlier. Specifically, this study provides a review on various approaches (e.g., individual and ensemble models), types of datasets, parameters or variables and performance measures used in the previous works. The literature review included all articles from journals and conference proceedings published from 2010 through 2020 in Scopus indexed databases using the search terms Predicting Disease Outbreaks and/or Detecting Disease using Machine Learning. The findings from this review focus on commonly used machine learning approaches, challenges and future works to limit the spread of deadly disease outbreaks through preventions and detections., Machine learning; Infectious disease; Disease outbreak; Prediction; Detection

Background The spread of COVID-19 creates disruption, uncertainty, complexity, and ambiguity in all organizations. People are the primary asset of any organization and help achieve their goals. Accordingly, to manage human resources sustainably, the organizational strategy review is an appropriate retort. Objective The purpose of this comprehensive review study is to identify unknown challenges, strategies, and unusual decisions related to human resource management other than clinical organizations during the COVID-19 pandemic. Methods The study applied a narrative review approach dissection based on organizations' human resource management strategies to combat the COVID-19 impacts. The review study conducted published literature research through the electronic databases at Web of Science, PubMed, Scopus, PsycINFO, and LISTA. The study extracted 1281 articles from the mentioned databases from November 2021 to the first quarter of 2021. This study reviewed selected papers, included 15 relevant articles, and removed duplicates according to inclusion and exclusion criteria. Finally, the study developed a conceptual framework of human resource management strategies based on the literature findings to fight against the COVID-19 pandemic. Results The COVID-19 pandemic posed numerous adverse consequences, such as economic shock, global health crisis, change in social behaviors, and challenges at the organization level to continue business operations. Besides, the strategies included flexibility, strengthening internal efficiency, talent acquisition, and making innovative changes based on organizational assessment and needs for smooth business activities. Conclusion The appropriate human resource management strategies implementations would increase employees’ mental well-being, satisfaction, productivity, motivation, and health safety at the workplace., Human resource management; COVID-19 adverse consequences; Novel coronavirus; Pandemic, Infectious disease, SARS-CoV-2 virus; Abrupt global challenges; Innovative HR strategy.

Toxoplasma gondii (T. gondii) is one of the most pervasive neurotropic pathogens causing different lesions in a wide variety of mammals as intermediate hosts, including humans. It is estimated that one-third of the world population is infected with T. gondii; however, for a long time, there has been much interest in the examination of the possible role of this parasite in the development of mental disorders, such as Alzheimer's disease (AD). T. gondii may play a role in the progression of AD using mechanisms, such as the induction of the host's immune responses, inflammation of the central nervous system (CNS), alteration in the levels of neurotransmitters, and activation of indoleamine-2,3-dyoxigenase. This paper presents an appraisal of the literature, reports, and studies that seek to the possible role of T. gondii in the development of AD. For achieving the purpose of the current study, a search of six English databases (PubMed, ScienceDirect, Web of Science, Scopus, ProQuest, and Google Scholar) was performed. The results support the involvement of T. gondii in the induction and development of AD. Indeed, T. gondii can be considered a risk factor for the development of AD and requires the special attention of specialists and patients. Furthermore, the results of this study may contribute to prevent or delay the progress of AD worldwide. Therefore, it is required to carry out further studies in order to better perceive the parasitic mechanisms in the progression of AD., Alzheimer, toxoplasmosis, risk factors, neurotransmitter, cytokine

This paper explains the effects of bus numbering using a load-flow study to investigate the Nigerian 330 kV radial transmission networks. The objectives of this research include the Newton-Raphson-based load-flow analysis and verification of power losses. The simulation of the load-flow analysis is carried out using the software of Power World Simulator and MATLAB, while verification of power losses is simulated with only MATLAB software. The Nigerian 330-kV transmission lines used in this study are radial and are overloaded; thus, it has been subjected to numerous studies covering many areas as to how improvements can be made. All these studies aimed at increasing the efficiency of the network and reduce real and reactive power losses. In this study, analysis is carried out on the failure to convergence; the result of load-flow as obtained for the 28-bus power system of the Nigerian 330-kV network using two different bus identification numbering sequence types. The results of the Newton-Raphson load-flow solution in Power World Simulator and MATLAB platform obtained for each of the two bus identification types revealed the convergence failure in one identification model numbering type. This result's inconsistency further necessitated the study of load-flow analysis on the Nigerian 330-kV network for other different bus identification numbering types as reviewed from past work for case studies. The same bus data and transmission line data obtained from PHCN are used for all the bus numbering model types generated in the study. The results revealed variations in the real and reactive power losses and the number of iterations in solving each case. Besides, the study discovered that the failure in convergence comes from the power solution method's failure (software) used, hence, a code-based platform should be used for verification., Bus identification number, Convergent failure and line losses, MATLAB, Newton-Raphson method, Power World Simulator.

Housing cooperatives are the organizations among others, which have played important roles in meeting the housing needs of people. In Nigeria, housing finance is through the formal and informal institutions; and personal residences accounted between 75 and 90 per cent of household wealth, that represents between 3 and 6 times their annual income. Finance is an important determinant of success and failure of housing ownership. It, therefore, becomes very necessary to identify viable sources of funding that can promote house-ownership. This paper examined the activities of Cooperative Societies in the provision of funds for house ownership in Nigeria with a focus on Akure. In the conduct of the social survey for the study; two sets of questionnaire were used. The first set of the questionnaire focused on House-owners and 683 sampled houses-owners were administered with the questionnaire in Akure. The second set of questionnaire was administered on the government officers' in-charge of the administration of the cooperative societies in Akure. The answers to the questions in the questionnaire were adequately supplied. The data were subjected to statistical analysis. The findings revealed among others that the main sources of funding house buildings were through personal savings and Cooperative Societies among others. It recommended that prospective house-owners should be encouraged to form and patronise Cooperative Societies as a reliable source for the housing loan., Cooperative society, House-ownership, Housing finance, Mortgage