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The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates accurate power production prediction for effective scheduling and grid management. This paper presents a comprehensive review conducted with reference to a pioneering, comprehensive, and data-driven framework proposed for solar Photovoltaic (PV) power generation prediction. The systematic and integrating framework comprises three main phases carried out by seven main comprehensive modules for addressing numerous practical difficulties of the prediction task: phase I handles the aspects related to data acquisition (module 1) and manipulation (module 2) in preparation for the development of the prediction scheme; phase II tackles the aspects associated with the development of the prediction model (module 3) and the assessment of its accuracy (module 4), including the quantification of the uncertainty (module 5); and phase III evolves towards enhancing the prediction accuracy by incorporating aspects of context change detection (module 6) and incremental learning when new data become available (module 7). This framework adeptly addresses all facets of solar PV power production prediction, bridging existing gaps and offering a comprehensive solution to inherent challenges. By seamlessly integrating these elements, our approach stands as a robust and versatile tool for enhancing the precision of solar PV power prediction in real-world applications.

Many developing countries suffer from high energy-import dependency and inadequate electrification of rural areas, which aggravates the poverty problem. In this work, Al-Tafilah in Jordan was considered as a case study, where the technical, economic, and environmental benefits of a decentralized hybrid renewable energy system that can match 100% of the city demand were investigated. A tri-hybrid system of wind, solar, and hydropower was integrated with an energy storage system and optimized to maximize the match between the energy demand and production profiles. The optimization aimed at maximizing the renewable energy system (RES) fraction while keeping the levelized cost of electricity (LCOE) equal to the electricity purchase tariff. The techno-economic analysis showed that the optimal system in Al-Tafilah comprises a 28 MW wind system, 75.4 MW PV, and 1 MW hydropower, with a 259 MWh energy storage system, for which a RES fraction of 99% can be achieved, and 47,160 MtCO2 are avoided yearly. This study can be easily extended to other rural cities in Jordan, as they have higher renewable energy system (RES) potential. The presented findings are essential not only for Jordan’s planning and economy-boosting but also for contributing to the ongoing force against climate change.

Electrostatic rotary bell sprayers (ERBSs) are widely used in the automotive industry. In ERBS, atomization is facilitated using centrifugal forces which disintegrate the paint film inside the cup into droplets at the cup edge. The droplets are then transported by the flow of a shaping air (SA) and electrostatic forces to a target surface; the characteristics of these droplets dramatically influence the quality of a painted surface and the painting transfer efficiency. In the current paper, a novel Schlieren-based visualization of the shaping air in the absence of paint droplets was performed during a qualitative investigation to delineate shaping air flow behavior and its interaction with droplets and droplet transport. An infrared thermographic flow visualization (IRFV) method and droplet size measurement were used to complement the Schlieren data for providing insight into shaping air-droplet interactions. The results demonstrated the impact of different operating conditions on the SA flow pattern, and the influence SA has on the secondary atomization and transport of droplets. Hence, these experimental methods combine with a useful tool for optimizing SA configurations that improve spray quality, droplet transport, and the efficiency of ERBS operations.

In this study, we evaluated the fundamental physical behavior during droplet formation and flow from a rotary bell spray in the absence of an electrostatic field. The impact of a wide range of operating parameters of the rotary bell sprayer, such as flow rates, rotational speeds, and spatial positioning, on droplet sizes and size distributions using a three-dimensional (3-D) mapping was studied. The results showed that increasing the rotational speed caused the Sauter mean diameter of the droplets to decrease while increasing flow rate increased the droplet sizes. The rotational speed effect, however, was dominant compared to the effect of flow rate. An increase in droplet size radially away from the cup was noted in the vicinity of the cup, nevertheless, as the lateral distances from the cup and rotational speed were increased, the droplet sizes within the flow field became more uniform. This result is of importance for painting industries, which are looking for optimal target distances for uniform painting appearance. Furthermore, the theoretical formulation was validated with experimental data, which provides a wider range of applicability in terms of environment and parameters that could be tested. This work also provides an abundance of measurements, which can serve as a database for the validation of future droplet disintegration simulations.

Sensitivity to ambient air temperatures, consuming a large amount of fuel, and wasting a significant amount of heat dumped into the ambient atmosphere are three major challenges facing gas turbine power plants. This study was conducted to simultaneously solve all three aforementioned GT problems using solar energy and introducing a new configuration that consists of solar preheating and inlet-air-cooling systems. In this study, air was preheated at a combustion chamber inlet using parabolic trough collectors. Then, inlet air to the compressor was cooled by these collectors by operating an absorption cooling cycle. At the design point conditions, this novel proposed integration resulted in a 6.87% relative increase in generated power and a 10.53% relative decrement in fuel consumption, achieving a 19.45% relative increment in the plant’s thermal efficiency. This was accompanied by a reduction of 0.026 kg/s, 4.2 kg/s, and 0.278 kg/s in CO2, CO, and NOx emissions, respectively. Finally, spider diagrams were employed to assess the impact of the operating parameters on the overall system’s performance and its associated environmental implications.

Autosomal dominant polycystic kidney disease (ADPKD) is an inherited monogenic renal disease characterised by the accumulation of clusters of fluid-filled cysts in the kidneys and is caused by mutations in PKD1 or PKD2 genes. ADPKD genetic diagnosis is complicated by PKD1 pseudogenes located proximal to the original gene with a high degree of homology. The next generation sequencing (NGS) technology including whole exome sequencing (WES) and whole genome sequencing (WGS), is becoming more affordable and its use in the detection of ADPKD mutations for diagnostic and research purposes more widespread. However, how well does NGS technology compare with the Gold standard (Sanger sequencing) in the detection of ADPKD mutations? Is a question that remains to be answered. We have evaluated the efficacy of WES, WGS and targeted enrichment methodologies in detecting ADPKD mutations in the PKD1 and PKD2 genes in patients who were clinically evaluated by ultrasonography and renal function tests. Our results showed that WES detected PKD1 mutations in ADPKD patients with 50% sensitivity, as the reading depth and sequencing quality were low in the duplicated regions of PKD1 (exons 1–32) compared with those of WGS and target enrichment arrays. Our investigation highlights major limitations of WES in ADPKD genetic diagnosis. Enhancing reading depth, quality and sensitivity of WES in the PKD1 duplicated regions (exons 1–32) is crucial for its potential diagnostic or research applications.

This work proposes a new numerical approach for dealing with fractional stochastic differential equations. In particular, a novel three-point fractional formula for approximating the Riemann–Liouville integrator is established, and then it is applied to generate approximate solutions for fractional stochastic differential equations. Such a formula is derived with the use of the generalized Taylor theorem coupled with a recent definition of the definite fractional integral. Our approach is compared with the approximate solution generated by the Euler–Maruyama method and the exact solution for the purpose of verifying our findings.

Friction stir processing (FSP) technology has received reasonable attention in the past two decades to process a wide range of materials such as aluminum, magnesium, titanium, steel, and superalloys. Due to its thermomechanical processing nature, FSP is used to alter grain structure and enhance mechanical and corrosion behavior in a wide range of steels. The refinement in grains and phase transformations achieved in steel after FSP affects hardness, tensile properties, fracture toughness, fatigue crack propagation rate, wear resistance, and corrosion resistance. A number of review papers are available on friction stir welding (FSW) or FSP of nonferrous alloys. In this article, a comprehensive literature review on the FSP/FSW of different types of steels is summarized. Specifically, the influence of friction stir processing parameters such as advancing speed, rotational speed, tool material, etc., on steels’ performance is discussed along with assessment methodologies and recommendations.

BackgroundCancer is one of the most dangerous and widespread diseases in the world today and it has risen to the position of the leading cause of death around the globe in the last few decades. Due to the inherent resistance of many types of cancer to conventional radiotherapy and chemotherapy, it is vital to develop innovative anticancer medications. Recently, a strategy based on nanotechnology has been used to improve the effectiveness of both old and new cancer drugs.ObjectivesThe present study aimed to design and synthesize a series of phenyl-isoxazole–Carboxamide derivatives, evaluate their anticancer properties, and improve the permeability of potent compounds into cancer cells by using a nano-emulgel strategy.MethodsThe coupling reaction of aniline derivatives and isoxazole–Carboxylic acid was used to synthesize a series of isoxazole–Carboxamide derivatives. IR, HRMS, 1H-NMR, and 13C-NMR spectroscopy techniques, characterized all the synthesized compounds. The in-vitro cytotoxic evaluation was performed by using the MTS assay against seven cancer cell lines, including hepatocellular carcinoma (Hep3B and HepG2), cervical adenocarcinoma (HeLa), breast carcinoma (MCF-7), melanoma (B16F1), colorectal adenocarcinoma (Caco-2), and colon adenocarcinoma (Colo205), as well as human hepatic stellate (LX-2) in addition to the normal cell line (Hek293T). A nano-emulgel was developed for the most potent compound, using a self-emulsifying technique.ResultsAll synthesized compounds were found to have potent to moderate activities against B16F1, Colo205, and HepG2 cancer cell lines. The results revealed that the 2a compound has broad spectrum activity against B16F1, Colo205, HepG2, and HeLa cancer cell lines with an IC50 range of 7.55–40.85 µM. Moreover, compound 2e was the most active compound against B16F1 with an IC50 of 0.079 µM compared with Dox (IC50 = 0.056 µM). Nanoemulgel was used to increase the potency of the 2e molecule against this cancer cell line, and the IC50 was reduced to 0.039 µM. The antifibrotic activities were investigated against the LX-2 cell line, and it was found that our synthesized molecules showed better antifibrotic activities at 1 µM than 5-FU, and the cell viability values were 67 and 95%, respectively.ConclusionThis study suggests that a 2e nano-formalized compound is a potential and promising anti-melanoma agent.

This paper establishes a novel fractional-order version of a recently expanded form of the Susceptible-Exposed-Infectious-Recovery (SEIR) Mpox model. This model is investigated by means of demonstrating some significant findings connected with the stability analysis and the vaccination impact, as well. In particular, we analyze the fractional-order Mpox model in terms of its invariant region, boundedness of solution, equilibria, basic reproductive number, and its elasticity. In accordance with an effective vaccine, we study the progression and dynamics of the Mpox disease in compliance with various scenarios of the vaccination ratio through the proposed fractional-order Mpox model. Accordingly, several numerical findings of the proposed model are depicted with the use of two numerical methods; the Fractional Euler Method (FEM) and Modified Fractional Euler Method (MFEM). Such findings demonstrate the influence of the fractional-order values coupled with the vaccination rate on the dynamics of the established disease model.