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This research examined the impact of foreign direct investment, natural resources, renewable energy consumption, and economic growth on environmental degradation in BRICS, developing, developed, and global countries for the time period from 1991 to 2018 by using dynamic fixed effect model, GMM, and system GMM estimators. The examined results indicate that FDI causes environmental degradation in BRICS and developing countries while in developed countries, FDI helps environmental degradation reduction. The empirical results indicate that fuel resources and renewable energy consumption help to reduce the environment degradation in BRICS, developing, developed, and global countries while ore and metal resources cause environment degradation improvement in developed countries. Total natural resources (coal, oil, natural gas, and mineral rents) and economic growth are the main factors that boost the environmental degradation in BRICS, developing, developed, and global countries. Based on the examined results, policies are suggested for BRICS, developing, developed, and global countries. It is suggested that policy makers in these countries not only reply to protect environmental degradation but also support the growth of fuel resources, ore, and metal resource and total natural resources.

The amount of surface soil moisture (SSM) is a crucial ecohydrological natural resource that regulates important land surface processes. It affects critical land–atmospheric phenomena, including the division of energy and water (infiltration, runoff, and evaporation), that impacts the effectiveness of agricultural output (sensible and latent heat fluxes and surface air temperature). Despite its significance, there are several difficulties in making precise measurements, monitoring, and interpreting SSM at high spatial and temporal resolutions. The current study critically reviews the methods and procedures for calculating SSM and the variables influencing measurement accuracy and applicability under different fields, climates, and operational conditions. For laboratory and field measurements, this study divides SSM estimate strategies into (i) direct and (ii) indirect procedures. The accuracy and applicability of a technique depends on the environment and the resources at hand. Comparative research is geographically restricted, although precise and economical—direct measuring techniques like the gravimetric method are time-consuming and destructive. In contrast, indirect methods are more expensive and do not produce measurements at the spatial scale but produce precise data on a temporal scale. While measuring SSM across more significant regions, ground-penetrating radar and remote sensing methods are susceptible to errors caused by overlapping data and atmospheric factors. On the other hand, soft computing techniques like machine/deep learning are quite handy for estimating SSM without any technical or laborious procedures. We determine that factors, e.g., topography, soil type, vegetation, climate change, groundwater level, depth of soil, etc., primarily influence the SSM measurements. Different techniques have been put into practice for various practical situations, although comparisons between them are not available frequently in publications. Each method offers a unique set of potential advantages and disadvantages. The most accurate way of identifying the best soil moisture technique is the value selection method (VSM). The neutron probe is preferable to the FDR or TDR sensor for measuring soil moisture. Remote sensing techniques have filled the need for large-scale, highly spatiotemporal soil moisture monitoring. Through self-learning capabilities in data-scarce areas, machine/deep learning approaches facilitate soil moisture measurement and prediction.

Blockchain technology (BCT) has emerged in the last decade and added a lot of interest in the healthcare sector. The purpose of this systematic literature review (SLR) is to explore the potential paradigm shift in healthcare utilizing BCT. The study is compiled by reviewing research articles published in nine well-reputed venues such as IEEE Xplore, ACM Digital Library, Springs Link, Scopus, Taylor & Francis, Science Direct, PsycINFO, Ovid Medline, and MDPI between January 2016 to August 2021. A total of 1,192 research studies were identified out of which 51 articles were selected based on inclusion criteria for this SLR that presents the modern information on the recent implications and gaps in the use of BCT for enhancing the healthcare procedures. According to the outcomes, BCT is being applied to design the novel and advanced interventions to enrich the current protocol of managing, distributing, and processing clinical records and personal medical information. BCT is enduring the conceptual development in the healthcare domain, where it has summed up the substantial elements through better and enhanced efficiency, technological innovation, access control, data privacy, and security. A framework is developed to address the probable field where future researchers can add considerable value, such as data protection, system architecture, and regulatory compliance. Finally, this SLR concludes that the upcoming research can support the pervasive implementation of BCT to address the critical dilemmas related to health diagnostics, enhancing the patient healthcare process in remote monitoring or emergencies, data integrity, and avoiding fraud.

Highlighting the importance of artificial intelligence and machine learning approaches in engineering and fluid mechanics problems, especially in heat transfer applications is main goal of the presented article. With the advancement in Artificial Intelligence (AI) and Machine Learning (ML) techniques, the computational efficiency and accuracy of numerical results are enhanced. The theme of the study is to use machine learning techniques to examine the thermal analysis of MHD boundary layer flow of Eyring-Powell Hybrid Nanofluid (EPHNFs) passing a horizontal cylinder embedded in a porous medium with heat source/sink and viscous dissipation effects. The considered base fluid is water (H2O) and hybrid nanoparticles titanium oxide (TiO2) and Copper oxide (CuO). The governing flow equations are nonlinear PDEs. Non-similar system of PDEs are obtained with efficient conversion variables. The dimensionless PDEs are truncated using a local non-similarity approach up to third level and numerical solution is evaluated using MATLAB built-in-function bvp4c. Artificial Neural Networks (ANNs) simulation approach is used to trained the networks to predict the solution behavior. Thermal boundary layer improves with the enhancement in the value of Rd. The accuracy and reliability of ANNs predicted solution is addressed with computation of correlation index and residual analysis. The RMSE is evaluated [0.04892, 0.0007597, 0.0007596, 0.01546, 0.008871, 0.01686] for various scenarios. It is observed that when concentration of hybrid nanoparticles increases then thermal characteristics of the Eyring-Powell Hybrid Nanofluid (EPHNFs) passing a horizontal cylinder.

Background Soil pollution by petroleum hydrocarbons (PHCs) reduces yield by changing the physico-chemical properties of soil and plants due to PHCs’ biotoxicity and persistence. Thus, removing PHCs from the soil is crucial for ecological sustainability. Microbes-assisted phytoremediation is an economical and eco-friendly solution. The current work aimed to develop and use bacterial consortia (BC) for PHCs degradation and plant growth enhancement in hydrocarbon-contaminated soil. Initially, the enriched microbial cultures (that were prepared from PHCs-contaminated soils from five distinct regions) were obtained via screening through microcosm experiments. Afterward, two best microbial cultures were tested for PHCs degradation under various temperature and pH ranges. After culture optimization, isolation and characterization of bacterial strains were done to construct two BC. These constructed BC were tested in a pot experiment for hydrocarbons degradation and chickpea growth in PHCs contaminated soil. Results Findings revealed that PHCs exerted significant phytotoxic effects on chickpea growth and physiology when cultivated in PHCs contaminated soil, reducing agronomic and physiological traits by 13–29% and 12–43%, respectively. However, in the presence of BC, the phytotoxic impacts of PHCs on chickpea plants were reduced, resulting in up to 24 − 35% improvement in agronomic and physiological characteristics as compared to un-inoculated contaminated controls. Furthermore, the bacterial consortia boosted chickpea’s nutritional absorption and antioxidant mechanism. Most importantly, chickpea plants phytoremediated 52% of the initial PHCs concentration; however, adding BC1 and BC2 with chickpea plants further increased this removal and remediated 74% and 80% of the initial PHCs concentration, respectively. Conclusion In general, BC2 outperformed BC1 (with few exceptions) in promoting plant growth and PHCs elimination. Therefore, using multi-trait BC for PHCs degradation and plant growth improvement under PHCs stress may be an efficient and environmentally friendly strategy to deal with PHCs pollution and toxicity.

Binary fatty acid mixture-based solid lipid nanoparticles (SLNs) were prepared for delivery of diacerein, a novel disease-modifying osteoarthritis drug, with and without simultaneously loaded gold nanoparticles (GNPs). In order to optimize SLNs for temperature-responsive release, lipid mixtures were prepared using different ratios of solid (stearic acid or lauric acid) and liquid (oleic acid) fatty acids. SLNs were prepared by microemulsification (53 nm), hot melt encapsulation (10.4 nm), and a solvent emulsification-evaporation technique (7.8 nm). The physicochemical characteristics of SLNs were studied by Zetasizer, Fourier transform infrared, and X-ray diffraction analysis. High encapsulation of diacerein was achieved with diacerein-loaded and simultaneously GNP-diacerein-loaded SLNs. In vitro dissolution studies revealed a sustained release pattern for diacerein over 72 hours for diacerein-loaded SLNs and 12 hours for GNP-diacerein-loaded SLNs. An increase in diacerein payload increased the release time of diacerein while GNPs decreased it. In addition, rapid release of diacerein over 4 hours was observed at 40°C (melting point of optimized fatty acid mixture), demonstrating that these binary SLNs could be used for thermoresponsive drug delivery. Kinetic modeling indicated that drug release followed zero order and Higuchi diffusion models (R(2)>0.9), while the Korsmeyer-Peppas model predicted a diffusion release mechanism (n<0.5).

Cyclosporine A (CsA) is an exceptional immunosuppressant used for the treatment of immune disorders. Niosomal vesicles are promising drug carriers that are formed by self-association of nonionic surfactants and cholesterol in an aqueous phase. The objective of the study was to formulate combined nonionic surfactant based vesicles and to evaluate their in vitro characterization, release studies and in vivo studies. Five niosomal formulations (F to F ) were prepared using the thin film hydration method. The molar ratio of cholesterol and non-ionic surfactant taken was 1:1. In formulation F , the combination of surfactants Span 20 and Brij 35 was used. The niosomes were characterized by zeta sizer and SEM for particle size analysis, in vitro drug release and stability studies. The pharmacokinetic studies were conducted on healthy albino rabbits. The size of niosome was found in the range of 427.1 nm to 972.3 nm. SEM image of optimized formulations F exhibit the spherical nature of niosomal vesicles. DSC thermograms of niosomal formulations exhibited a broadened endothermic peak. The stability study exhibited that all formulations are stable and negligible change of vesicle size and entrapment was observed with time. The percentage drug release was significantly higher as compared to CsA plain dispersion for all niosomal formulations at pH 1.2 and 7.4. The release kinetic behavior showed that all preparations were best described by zero order and can release active ingredient in a sustained manner. The pharmacokinetic data showed the test formulation (F10) possessed greater bioavailability as compared to the reference formulation (CsA aqueous dispersion). The formulation F demonstrated a comparatively more delayed rate of release with enhanced dissolution as compared to a single surfactant scheme. The F formulation can be a remarkable nanotechnology for prolonged delivery of CsA orally with improved dissolution profile and bioavailability.

Developing countries are facing the problem of environmental degradation. Environmental degradation is caused by the use of non-renewable energy consumptions for economic growth but the consequences of environmental degradation cannot be ignored. This primary purpose of this study is to investigate the nexus between energy consumption, economic growth and CO2 emission in Pakistan by using annual time series data from 1965 to 2015. The estimated results of ARDL indicate that energy consumption and economic growth increase the CO2 emissions in Pakistan both in short run and long run. Based on the estimated results it is recommended that policy maker in Pakistan should adopt and promote such renewable energy sources that will help to meet the increased demand for energy by replacing old traditional energy sources such as coal, gas, and oil. Renewable energy sources are reusable that can reduce the CO2 emissions and also ensure sustainable economic development of Pakistan.

Microalgae have recently attracted considerable interest worldwide, due to their extensive application potential in the renewable energy, biopharmaceutical, and nutraceutical industries. Microalgae are renewable, sustainable, and economical sources of biofuels, bioactive medicinal products, and food ingredients. Several microalgae species have been investigated for their potential as value-added products with remarkable pharmacological and biological qualities. As biofuels, they are a perfect substitute to liquid fossil fuels with respect to cost, renewability, and environmental concerns. Microalgae have a significant ability to convert atmospheric CO 2 to useful products such as carbohydrates, lipids, and other bioactive metabolites. Although microalgae are feasible sources for bioenergy and biopharmaceuticals in general, some limitations and challenges remain, which must be overcome to upgrade the technology from pilot-phase to industrial level. The most challenging and crucial issues are enhancing microalgae growth rate and product synthesis, dewatering algae culture for biomass production, pretreating biomass, and optimizing the fermentation process in case of algal bioethanol production. The present review describes the advantages of microalgae for the production of biofuels and various bioactive compounds and discusses culturing parameters.