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Simple Summary: The journey of discovering melanoma—the most dangerous type of skin cancer—biomarkers is never-ending. Under that assumption, this study attempts to partially fill a gap in that journey by identifying melanoma-related biomarkers. This research paper studied the genetic and molecular profiling of melanoma. A transcriptome-wide association study (TWAS) was conducted to reveal the significant biomarkers associated with melanoma. A molecular network was constructed to represent the significant interactions between genes and microRNAs (miRNAs). The related biological processes, the enriched pathways, and the associated diseases were identified. The hotspot biomarkers were discovered to elucidate further the mechanism of these genes and miRNAs in melanoma pathogenesis. This work reveals the pathogenesis and biologically important molecular interactions of melanoma and provides new insights into the molecular mechanisms of melanoma. A transcriptome-wide association study (TWAS) was conducted on genome-wide association study (GWAS) summary statistics of malignant melanoma of skin (UK Biobank dataset) and The Cancer Genome Atlas-Skin Cutaneous Melanoma (TCGA-SKCM) gene expression weights to identify melanoma susceptibility genes. The GWAS included 2465 cases and 449,799 controls, while the gene expression testing was conducted on 103 cases. Afterward, a gene enrichment analysis was applied to identify significant TWAS associations. The melanoma's gene–microRNA (miRNA) regulatory network was constructed from the TWAS genes and their corresponding miRNAs. At last, a disease enrichment analysis was conducted on the corresponding miRNAs. The TWAS detected 27 genes associated with melanoma with p-values less than 0.05 (the top three genes are LOC389458 (RBAK), C16orf73 (MEIOB), and EIF3CL). After the joint/conditional test, one gene (AMIGO1) was dropped, resulting in 26 significant genes. The Gene Ontology (GO) biological process associated the extended gene set (76 genes) with protein K11-linked ubiquitination and regulation of cell cycle phase transition. K11-linked ubiquitin chains regulate cell division. Interestingly, the extended gene set was related to different skin cancer subtypes. Moreover, the enriched pathways were nsp1 from SARS-CoV-2 that inhibit translation initiation in the host cell, cell cycle, translation factors, and DNA repair pathways full network. The gene-miRNA regulatory network identified 10 hotspot genes with the top three: TP53, BRCA1, and MDM2; and four hotspot miRNAs: mir-16, mir-15a, mir-125b, and mir-146a. Melanoma was among the top ten diseases associated with the corresponding (106) miRNAs. Our results shed light on melanoma pathogenesis and biologically significant molecular interactions. [ABSTRACT FROM AUTHOR]

Monitoring water quality in urban rivers is crucial for water resource management since point and non-point source pollution remain a major challenge. However, traditional water quality monitoring methods are costly and limited in frequency and spatial coverage. To optimize the monitoring, techniques such as modeling have been proposed. These methods rely on networks of low-cost multiprobes integrated with IoT networks to offer continuous real-time monitoring, with sufficient spatial coverage. But challenges persist in terms of data quality. Here, we propose a framework to verify the reliability and stability of low-cost sensors, focusing on the implementation of multiparameter probes embedding six sensors. Various tests have been developed to validate these sensors. First of all, a calibration check was carried out, indicating good accuracy. We then analyzed the influence of temperature. This revealed that for the conductivity and the oxygen sensors, a temperature compensation was required, and correction coefficients were identified. Temporal stability was verified in the laboratory and in the field (from 3 h to 3 months), which helped identify the frequency of maintenance procedures. To compensate for the sensor drift, weekly calibration and cleaning were required. This paper also explores the feasibility of LoRa technology for real-time data retrieval. However, with the LoRa gateways tested, the communication distance with the sensing device did not exceed 200 m. Based on these results, we propose a validation method to verify and to assure the performance of the low-cost sensors for water quality monitoring. [ABSTRACT FROM AUTHOR]

Disputed supply chains, inappropriate weather and low investment, followed by the Russian invasion of Ukraine, has led to a phenomenal energy crisis, especially in the Horn of Africa. Accordingly, proposing eco-friendly and sustainable solutions to diversify the access of electricity in the Republic of Djibouti, which has no conventional energy resources and is completely energy-dependent on its neighboring countries, has become a must. Therefore, the implementation of sustainable renewable and energy storage systems is nationally prioritized. This paper deals, for the first time, with the exploitation of such an affordable and carbon-free resource to produce hydrogen from wind energy in the rural areas of Nagad and Bara Wein in Djibouti. The production of hydrogen and the relevant CO2 emission reduction using different De Wind D6, Vestas and Nordex wind turbines are displayed while using Alkaline and Proton Exchange Membrane (PEM) electrolyzers. The Bara Wein and Nagad sites had a monthly wind speed above 7 m/s. From the results, the Nordex turbine accompanied with the alkaline electrolyzer provides the most affordable electricity production, approximately 0.0032 $/kWh for both sites; this cost is about one per hundred the actual imported hydroelectric energy price. Through the ecological analysis, the Nordex turbine is the most suitable wind turbine, with a CO2 emission reduction of 363.58 tons for Bara Wein compared to 228.76 tons for Nagad. While integrating the initial cost of wind turbine implementation in the capital investment, the mass and the levelized cost of the produced green hydrogen are estimated as (29.68 tons and 11.48 $/kg) for Bara Wein with corresponding values of (18.68 tons and 18.25 $/kg) for Nagad. [ABSTRACT FROM AUTHOR]

Iron-doped Zinc oxide nanoparticles were produced by the sol-gel combustion method. This study aims to see how iron doping affects the structural, optical, and photocatalytic characteristics of ZnO composites. XRD examined all samples to detect the structural properties and proved that all active materials are a single hexagonal phase. The morphology and particle size were investigated by TEM. Computational Density functional theory (DFT) calculation of the band structure, density of state, and charge distributions for ZnO were investigated in comparison with ZnO dope iron. We reported the application results of ZnO doped Fe for Methylene blue dye removal under photocatalytic degradation effect. The iron concentrations affect the active material's band gap, producing higher photocatalytic performance. The acquired results could be employed to enhance the photocatalytic properties of ZnO. [ABSTRACT FROM AUTHOR]

Changes in climatic circumstances, as well as intermittency, which has a significant impact on the overall energy system output from renewable energy sources (RESs), require the development of control strategies for extracting the maximum power available from RESs. To accomplish this task, several techniques have been developed. An efficient maximum power point tracking (MPPT) technique should be utilized to guarantee that both wind-generation and PV-generation systems provide their full advantages. In this paper, a new MPPT approach with jellyfish search optimization (JSO) is developed; in addition, a unified power-quality conditioner (UPQC) is utilized to enhance the performance of the microgrid (MG) and to solve the power-quality issues for the sensitive load. The MG, which includes a photovoltaic (PV), a wind turbine, and a fuel cell battery, is examined and modeled for uniform and nonuniform wind speed and solar irradiance. A comparison between the developed algorithm and different maximum power tracking algorithms is presented. Additionally, four case studies are carried out to verify the effectiveness of the introduced UPQC in enhancing power-quality problems. The research outcome shows high performance from the developed algorithm when assessed with additional algorithms. MATLAB/Simulink software is utilized for the simulation of the wind, PV, and FC control systems. However, experiment validation tests are given under the same condition of PV irradiation to validate the simulation results. The experimental validation is executed by utilizing the PV module simulation model, threefold, 23 V/2A CO3208-1A with solar altitude emulator CO3208-1B board, and the results are compared to the simulation results. [ABSTRACT FROM AUTHOR]

This paper proposes a design procedure to determine the optimal configuration of multi-degrees of freedom (MDOF) multiple tuned mass dampers (MTMD) to mitigate the global dynamic aeroelastic response of aerospace structures. The computation of the aerodynamic excitations is performed considering two models of atmospheric disturbances, namely, the Power Spectral Density (PSD) modelled with the Davenport Spectrum (DS) and the Tuned Discrete Gust (TDG) with the one-minus cosine profile. In order to determine the optimum sets of MTMD, a Multi-objective design Optimization considering Genetic Algorithm (MOGA) is implemented, where the selected fitness functions for the analysis are the minimization of the total mass of the resonators as well as the concurrent minimization of the peak displacements of a specified structural node in all translational degrees of freedom. A case study is presented to demonstrate the proposed methodology, where the optimal sets of MTMD are determined for the concurrent minimization of the pointing error of a truss-like antenna structure as well as the mass of the considered MTMD. It is found that the placement of the MTMD in the primary reflector of the antenna structure provided a maximum reduction in the pointing error of 62.0% and 39.2%, considering the PSD and the TDG models, respectively. Finally, this paper presents an advanced framework to estimate optimal parameters of MTMD control devices under convoluted loading cases as an initial step towards the use of such passive systems in applications that commonly employ active or semi-active solutions. [ABSTRACT FROM AUTHOR]

Establishing internet access for mobile ad hoc networks (MANET) is a job that is both vital and complex. MANET is used to build a broad range of applications, both commercial and non-commercial, with the majority of these apps obtaining access to internet resources. Since the gateways (GWs) are the central nodes in a MANET's ability to connect to the internet, it is common practice to deploy numerous GWs to increase the capabilities of a MANET. Current routing methods have been adapted and optimized for use with MANET through the use of both conventional routing techniques and tree-based network architectures. Exploring new or tacking-failure GWs also increases network overhead but is essential given that MANET is a dynamic and complicated network. To handle these issues, the work presented in this paper presents a modified gateway discovery approach inspired by the quantum swarm intelligence technique. The suggested approach follows the non-root tree-based GW discovery category to reduce broadcasting in the process of exploring GWs and uses quantum-inspired ant colony optimization (QACO) for constructing new paths. Due to the sequential method of execution of the algorithms, the complexity of ACO grows dramatically with the rise in the number of paths explored and the number of iterations required to obtain better performance. The exploration of a huge optimization problem's solution space may be made much more efficient with the help of quantum parallelization and entanglement of quantum states. Compared to other broad evolutionary algorithms, QACO s have more promise for tackling large-scale issues due to their ability to prevent premature convergence with a simple implementation. The experimental results using benchmarked datasets reveal the feasibility of the suggested approach of improving the processes of exploring new GWs, testing and maintaining existing paths to GWs, exploring different paths to existing GWs, detecting any connection failure in any route, and attempting to fix that failure by discovering an alternative optimal path. Furthermore, the comparative study demonstrates that the utilized QACO is valid and outperforms the discrete binary ACO algorithm (AntHocNet Protocol) in terms of time to discover new GWs (27% improvement on average), time that the recently inserted node takes to discover all GWs (on average, 70% improvement), routing overhead (53% improvement on average), and gateway's overhead (on average, 60% improvement). [ABSTRACT FROM AUTHOR]

The existence of aflatoxin M1 (AFM1) in raw milk results in economic losses and public health risks. This research aims to examine the capability of bentonite to adsorb and/or eliminate AFM1 from various raw milk types. In addition, the effects of numerous bentonites (HAFR 1, 2, 3 and 4) on the nutritional characteristics of the milk were studied. Our findings revealed that goat milk had the highest value of AFM1 (490.30 ng/L) in comparison to other milks. AFM1 adsorption was influenced by applying bentonite (0.5 and 1 g) in a concentration-dependent manner for different time intervals (from 0 to 12 h). The percentage of AFM1 reached the maximum adsorption level after 12 h to 100, 98.5 and 98% for bentonites HAFR 3, 1 and 2, respectively. HAFR 3 (1 g bentonite) presented higher adsorption efficiency than other bentonites used in the phosphate buffer saline (PBS) and milk. Residual levels of AFM1 reached their lowest values of 0 and 1.5 ng/L while using HAFR 3 in PBS and milk, respectively. With regard to the influence of bentonite on the nutritional characteristics of milk, there was an increase in fat, protein and solid non-fat ratio while using HAFR 3 and 4, yet decreased lactose in comparison with the control. Scanning Electron Microscopy and Fourier Transform-Infrared Spectroscopy both identified bentonites as superior AFM1 binders. The results demonstrated that bentonite, particularly HAFR 3, was the most effective adsorbent and could thus be a promising candidate for the decontamination of AFM1 in milk. [ABSTRACT FROM AUTHOR]

The paper presents the Fractional Fourier Transform-Singular Value Decomposition (FRFT-SVD) method for the localization of various power system faults in a 200 km long, 500 kV Egyptian transmission line using sent end-line current signals. Transient simulations are carried out using Alternating Transient Program/Electromagnetic Transient Program (ATP-EMTP), and the outcomes are then examined in MATLAB to carry out a sensitivity analysis against measurement noises, sampling frequency, and fault characteristics. The proposed work employs current fault signals of five distinct kinds at nineteen intermediate points throughout the length of the line. The approach utilized to construct the localizer model is FRFT-SVD. It is much more effortless, precise, and effective. The FRFT-SVD is utilized in this technique to calculate 19 sets of indices of the greatest S value throughout the length of the line. The FRFT-SVD localizer model is also designed to be realistic, with power system noise corrupting fault signals. To generate fault curves, the curve fitting technique is applied to these 19 sets of indices. Reduced chi-squared and modified R-squared criteria are used to choose the best-suited curve. The proposed work results in a very precise localization, with only a 0.0016% average percentage error for fault localization and a maximum percentage error of 0.002% for the 200 km Egyptian transmission line. Finally, this work can be employed as a proper link between the nuclear power plant and the grid. The proposed method is an efficient fault distance estimation method that might contribute to creating a dependable transient-based approach to power system protection. [ABSTRACT FROM AUTHOR]

Although progressive wasting and weakness of respiratory muscles are the prominent hallmarks of Duchenne muscular dystrophy (DMD) and long-COVID (also referred as the post-acute sequelae of COVID-19 syndrome); however, the underlying mechanism(s) leading to respiratory failure in both conditions remain unclear. We put together the latest relevant literature to further understand the plausible mechanism(s) behind diaphragm malfunctioning in COVID-19 and DMD conditions. Previously, we have shown the role of matrix metalloproteinase-9 (MMP9) in skeletal muscle fibrosis via a substantial increase in the levels of tumor necrosis factor-α (TNF-α) employing a DMD mouse model that was crossed-bred with MMP9-knockout (MMP9-KO or MMP9-/-) strain. Interestingly, recent observations from clinical studies show a robust increase in neopterin (NPT) levels during COVID-19 which is often observed in patients having DMD. What seems to be common in both (DMD and COVID-19) is the involvement of neopterin (NPT). We know that NPT is generated by activated white blood cells (WBCs) especially the M1 macrophages in response to inducible nitric oxide synthase (iNOS), tetrahydrobiopterin (BH4), and tetrahydrofolate (FH4) pathways, i.e., folate one-carbon metabolism (FOCM) in conjunction with epigenetics underpinning as an immune surveillance protection. Studies from our laboratory, and others researching DMD and the genetically engineered humanized (hACE2) mice that were administered with the spike protein (SP) of SARS-CoV-2 revealed an increase in the levels of NPT, TNF-α, HDAC, IL-1β, CD147, and MMP9 in the lung tissue of the animals that were subsequently accompanied by fibrosis of the diaphragm depicting a decreased oscillation phenotype. Therefore, it is of interest to understand how regulatory processes such as epigenetics involvement affect DNMT, HDAC, MTHFS, and iNOS that help generate NPT in the long-COVID patients. [ABSTRACT FROM AUTHOR]

The information technology (IT) revolutionization aside with the emergence of COVID-19 have catalyzed cloud-computing services and systems with multiple end-user benefits for online business management, specifically in the accounting discipline. For example, cloud accounting enables the significant reduction of organisational IT investment with flexible access to a large group of scalable resources. The cloud accounting enables small and medium size enterprises (SMEs) to independently engage in fundamental bookkeeping responsibilities rather than hiring external auditors for the same services. As cloud-based accounting adoption remains in the preliminary stage within Jordanian businesses, this study applied the technology, organisation, and environment model to explore cloud accounting among Jordanian SMEs. The study data were gathered from 156 Jordanian SME owners or managers with a structured online survey questionnaire. The recommended study framework encompassed seven determinants that influenced the cloud accounting adoption intention. Resultantly, except Perceived knowledge uncertainty factor, the proposed hypotheses were supported as the aforementioned factors (relative advantages, security concerns, top management support, organizational readiness, competitor's intensity and suppliers computing support) positively and significantly influenced the cloud accounting of Jordanian SMEs. The study outcomes could facilitate IT field decision-makers and practitioners by investigating an actual cloud accounting case based on the essentiality of its application. [ABSTRACT FROM AUTHOR]

This study examines the extent to which the characteristics of the audit committee chair enhance the quality of financial reports and reduce the possibility for companies to receive a modified audit opinion (MAO) from an external auditor. We apply logistic regression to investigate the influence of Audit Committee Chair (ACC) characteristics on the FRQ (FRQ), for a sample of 460 firm-year observations (service and industrial company listed) on the Amman stock exchange for the years 2017–2020. This study uses the MAO as a proxy for Financial Reporting Quality (FRQ). The results of this study confirmed that the characteristics of the chair of the audit committee have significant and clear impacts on the quality and efficiency of financial reports, which is in line with previous studies that have addressed this topic. The results also indicated that researchers, academics, regulators, and policymakers should not look just at the characteristics of audit committees as a whole, given that audit committee chairs have effects on financial reports. This study presents its contribution through experimental demonstration of the characteristics of the chair of the audit committee and how these affect the financial reports of companies. It also provides a guide for benefits for working to provide a basis for organizational procedures, especially those related to the impact on corporate boards and internal and external auditing. [ABSTRACT FROM AUTHOR]

The adoption of big data analytics (BDA) is increasing pace both in practice and in theory, owing to the prospects and its potential advantages. Numerous researchers believe that BDA could provide significant advantages, despite constant battles with the constraints that limit its implementation. Here, we suggest an incorporated model to investigate the drivers and impacts of BDA adoption in the Jordanian hotel industry based on the technology–organisation–environment framework and the resource-based view theory. The suggested model incorporates both the adoption and performance components of BDA into a single model. For data collection, in this study, we used an online questionnaire survey. The research model was verified based on responses from 119 Jordanian hotels. This study yielded two significant findings. First, we discovered that relative advantage, organizational readiness, top management support, and government regulations have a major impact on BDA adoption. The study results also reveal a strong and favourable association between BDA adoption and firm performance. Finally, information sharing was found to have a moderating effect on the association between BDA adoption and firm performance. The data revealed how businesses might increase their BDA adoption for improved firm performance. The present study adds to the limited but growing body of literature investigating the drivers and consequences of technology acceptance. The findings of this study can serve as a resource for scholars and practitioners interested in big data adoption in emerging nations. [ABSTRACT FROM AUTHOR]

The emergence of geospatial big data has opened up new avenues for identifying urban environments. Although both geographic information systems (GIS) and expert systems (ES) have been useful in resolving geographical decision issues, they are not without their own shortcomings. The combination of GIS and ES has gained popularity due to the necessity of boosting the effectiveness of these tools in resolving very difficult spatial decision-making problems. The clustering method generates the functional effects necessary to apply spatial analysis techniques. In a symmetric clustering system, two or more nodes run applications and monitor each other simultaneously. This system is more efficient than an asymmetric system since it utilizes all available hardware and does not maintain a node in a hot standby state. However, it is still a major issue to figure out how to expand and speed up clustering algorithms without sacrificing efficiency. The work presented in this paper introduces an optimized hierarchical distributed k-medoid symmetric clustering algorithm for big data spatial query processing. To increase the k-medoid method's efficiency and create more precise clusters, a hybrid approach combining the k-medoid and Chemical Reaction Optimization (CRO) techniques is presented. CRO is used in this approach to broaden the scope of the optimal medoid and improve clustering by obtaining more accurate data. The suggested paradigm solves the current technique's issue of predicting the accurate clusters' number. The suggested approach includes two phases: in the first phase, the local clusters are built using Apache Spark's parallelism paradigm based on their portion of the whole dataset. In the second phase, the local clusters are merged to create condensed and reliable final clusters. The suggested approach condenses the data provided during aggregation and creates the ideal clusters' number automatically based on the dataset's structures. The suggested approach is robust and delivers high-quality results for spatial query analysis, as shown by experimental results. The proposed model reduces average query latency by 23%. [ABSTRACT FROM AUTHOR]

In the literature, studies have evidenced the efforts adopted by firms to develop digital technology with the hope of achieving sustainable decisions and competitive performance. However, studies have yet to provide an extensive explanation of the mechanisms used by firms in their digital technology adoption to impact and enhance value, particularly among small and medium enterprises (SMEs). In this regard, accounting information has served as a fundamental basis for business decision-making and the extensive use of digital technology has paved the way for the efficiency and effectiveness of accounting functions in modifying information relating to such functions. More specifically, a digital accounting system (DAS) enables the reporting and processing of large transaction amounts and generates the data required for analysis. However, despite these advantages, SMEs have been slow in their adoption and usage of DASs. Accordingly, this study drew upon resource-based view theory and the technology-organization-environment framework to propose an integrated model for examining the determinants and impact of using DAS among SMEs. The proposed model encapsulates the use and performance aspect of DAS. The study utilized a self-administered survey questionnaire as the primary data collection instrument. Data from 183 SMEs in Jordan were analyzed using partial least squares-structural equation modeling. The findings reveal that compatibility, organizational readiness, top management support and government support all had significant effects on DAS usage, which, in turn, had a positive and significant effect on DAS performance. With regard to the moderating effects, COVID-19 was found to have a moderating role on the DAS usage–DAS performance relationship. The study findings explain the way firms can enhance their DAS use to obtain optimum performance, thereby contributing to the literature on the antecedents and effects of using current information technology/information systems. The study recommends that the government of Jordan prepare and carry out a campaign concerning the importance of DASs for SMEs. [ABSTRACT FROM AUTHOR]

In cancer management, drug resistance remains a challenge that reduces the effectiveness of chemotherapy. Several studies have shown that curcumin resensitizes cancer cells to chemotherapeutic drugs to overcome resistance. In the present study, we investigate the potential therapeutic role of curcumin in regulating the proliferation of drug-resistant cancers. Six drug-sensitive (MCF7, HCT116, and A549) and -resistant (MCF7/TH, HCT116R, and A549/ADR) cancer cell lines were treated with curcumin followed by an analysis of cytotoxicity, LDH enzyme, total reactive oxygen species, antioxidant enzymes (SOD and CAT), fibrosis markers (TGF-β1 protein, fibronectin, and hydroxyproline), and expression of cellular apoptotic markers (Bcl-2, Bax, Bax/Bcl-2 ratio, Annexin V, cytochrome c, and caspase-8). Additionally, the expression of cellular SIRT1 was estimated by ELISA and RT-PCR analysis. Curcumin treatment at doses of 2.7–54.3 µM significantly reduced the growth of sensitive and resistant cells as supported with decreased viability and increased cellular LDH enzyme of treated cells compared to controls non-treated cells. Curcumin also at doses of 2.7 and 54.3 µM regulated the fibrogenesis by reducing the expression of fibrotic markers in treated cells. Analysis of apoptotic markers indicated increased Bax, Bax, Bax/Bcl-2 ratio, Annexin V, caspase-8, and cytochrome c expression, while Bcl-2 expressions were significantly reduced. In curcumin-treated cells at 2.7 μM, non-significant change in ROS with significant increase in SOD and CAT activity was observed, whereas an increase in ROS with a reduction in respective antioxidant enzymes were seen at higher concentrations along with significant upregulation of SIRT1. In conclusion, the present study shows that curcumin induces anticancer activity against resistant cancer cell lines in a concentration- and time-dependent manner. The protective activities of curcumin against the growth of cancer cells are mediated by modulating oxidative stress, regulating fibrosis, SIRT1 activation, and inducing cellular apoptosis. Therefore, curcumin could be tested as an auxiliary therapeutic agent to improve the prognosis in patients with resistant cancers. [ABSTRACT FROM AUTHOR]

In the presented study, we developed a nanogold lateral glow immunoassay-based technique (LFI-COVID-19 antigen test) for the detection of SARS-CoV-2 nucleocapsid proteins; the developed LFI-COVID-19 Ag test has been tested for limit of detection (LOD), cross-reactivity and interfering substances, and performance. It was found that the performance of the developed LFI-COVID-19 antigen test when it was evaluated by RT-qPCR indicated 95, 98, and 97% for sensitivity, specificity and accuracy, respectively. This complies with the WHO guidelines. It was concluded that the developed LFI-COVID-19 antigen test is a point of care and an alternative approach to current laboratory methods, especially RT-qPCR. It provides an easy, rapid (within 20 min), and on-site diagnostic tool for COVID-19 infection, and it is a cheap test if it is manufactured on a large scale for commercial use. [ABSTRACT FROM AUTHOR]

The most current highly infectious disease, which has become a global health challenge permeating entire sectors of society, is COVID-19. In the education sector, the transmission of COVID-19 has been curbed through the closure of institutions and the facilitation of online learning. The main objective of this study was to propose an integrated model of the unified theory of acceptance and use of technology combined with the DeLone and McLean model, to examine the influence of quality features, namely, performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC), and social influence (SI), on the intentions and satisfaction of users toward mobile learning (m-learning) use in the context of Saudi learning institutions. The study obtained m-learning user data using an online questionnaire, after which the data were exposed to partial least squares structural equation modeling to test the proposed research model. The findings supported the influence of PE, EE, and FC on intention toward m-learning use but did not support the significant influence of SI. Moreover, system, intention, and user satisfaction were found to positively and significantly influence m-learning-system usage, with system, information, and service quality being top drivers of such user intention and satisfaction. The results reflect the required information concerning the strategies of higher institutions to enhance m-learning-system acceptance among students, with general implications for learning acceptance and usage. [ABSTRACT FROM AUTHOR]

Singularity theory is a significant field of modern mathematical research. The main goal in most problems of singularity theory is to understand the dependence of some objects in analysis and geometry, or physics; or from some other science on parameters. In this paper, we study the singularities of the spherical indicatrix and evolute of space-like ruled surface with space-like ruling. The main method takes advantage of the classical unfolding theorem in singularity theory, which is a classical method to study singularity problems in Euclidean space and Minkowski space. Finally, we provide an example to illustrate our results. [ABSTRACT FROM AUTHOR]

Businesses need accounting information to support their decision-making. In this regard, the extensive use of Information Technology (IT) has enhanced the effectiveness and efficiency of accounting functions that support accounting-related information. Specifically, an enterprise resource planning (ERP) system ensures reporting accuracy, large amounts of transaction processing, and the generation of reports for analysis. Regardless of the numerous benefits that an ERP system provides, small and medium-sized enterprises (SMEs) have yet to catch up with their system usage. Hence, this study draws upon the technology-organisation-environment (TOE) framework to propose an integrated model that includes diffusion of innovation (DOI), institutional factors, and TOE to examine ERP adoption antecedents in the context of SMEs in Jordan. A mixed method is applied in this work, and it uses a self-administered questionnaire survey as the main data collection instrument along with interviews. Quantitative data are obtained from 102 respondents through the questionnaire, after which the research model is validated using SMEs in Jordan. The survey results show that relative advantage, top management support, organisational readiness, training, competitive pressure, government support compatibility, and service provider support significantly influence ERP adoption among the SMEs. The findings are expected to shed light on the way SMEs can enhance their ERP adoption for optimum performance, as well as extend the literature dedicated to the antecedents of information system, IT adoption, and their impact. [ABSTRACT FROM AUTHOR]

In Table 6, the values given in the table for Q10, the median and Q90 of alkylphenols (last seven lines of the tables) were shifted by one line and, thus, were not associated with the right compound. Tables Table 6 Organic micropollutants (group 3) analyzed in the runoff, quantification frequency and range of quantified total EMC concentrations. In Table 7, the values given in the table for Q10 of polybrominated biphenyl ethers (BDE 28 to BDE 153) were shifted by one line and, thus, were not associated with the right compound. [Extracted from the article]

This paper explores the problem of energy-efficient shortest path planning on off-road, natural, real-life terrain for unmanned ground vehicles (UGVs). We present a greedy path planning algorithm based on a composite metric routing approach that combines the energy consumption and distance of the path. In our work, we consider the Terramechanics between the UGV and the terrain soil to account for the wheel sinkage effect, in addition to the terrain slope and soil deformation limitations in the development of the path planning algorithm. As benchmarks for comparison, we use a recent energy-cost minimization approach, in addition to an ant colony optimization (ACO) implementation. Our results indicate that the proposed composite metric routing approach outperforms the state-of-the-art energy-cost minimization method in terms of the resulting path distance, with a negligible increase in energy consumption. Moreover, our results indicate also that the proposed greedy algorithm strongly outperforms the ACO implementation in terms of the quality of the paths obtained and the algorithm running time. In fact, the running time of our proposed algorithm indicates its suitability for large natural terrain graphs with thousands of nodes and tens of thousands of links. [ABSTRACT FROM AUTHOR]

Magnetic-resonant wireless power transfer (WPT) has become a reliable contactless source of power for a wide range of applications. WPT spans different power levels ranging from low-power implantable devices up to high-power electric vehicles (EV) battery charging. The transmission range and efficiency of WPT have been reasonably enhanced by resonating the transmitter and receiver coils at a common frequency. Nevertheless, matching between resonance in the transmitter and receiver is quite cumbersome, particularly in single-transmitter multi-receiver systems. The resonance frequency in transmitter and receiver tank circuits has to be perfectly matched, otherwise power transfer capability is greatly degraded. This paper discusses the mistuning effect of parallel-compensated receivers, and thereof a novel dynamic frequency tuning method and related circuit topology and control is proposed and characterized in the system application. The proposed method is based on the concept of switch-mode gyrator emulating variable lossless inductors oriented to enable self-tunability in WPT receivers. [ABSTRACT FROM AUTHOR]

Urban lakes mitigate the negative impacts on the hydrological cycle and improve the quality of life in cities. Worldwide, the concern increases for the protection and management of urban water bodies. Since the physical-chemical and biological conditions of a small aquatic ecosystem can vary rapidly over time, traditional low frequency measurement approaches (weekly or monthly sampling) limits the knowledge and the transfer of research outcomes to management decision-making. In this context, this paper presents an automatic monitoring system including a full-scale experimental site and a data transfer platform for high-frequency observations (every 5 min) in a small and shallow urban lake (Lake Champs-sur-Marne, Paris, France, 10.3 ha). Lake stratification and mixing periods can be clearly observed, these periods are compared with the dynamic patterns of chlorophyll-a, phycocyanin, dissolved oxygen and pH. The results indicate that the phytoplankton growth corresponds with dissolved oxygen cycles. However, thermal stratification cannot totally explain the entire dynamic patterns of different physical-chemical and ecological variables. Besides, the cyanobacteria is one of the dominating groups of phytoplankton blooms during the lake stratification periods (8 August-29 September 2016). During the cooling mixed period (29 September-19 October 2016), the high concentration of chlorophyll-a is mainly caused by the other phytoplankton species, such as diatoms. Perspectives are discussed in order to apply this observation system for real-time management of water bodies and lakes. [ABSTRACT FROM AUTHOR]

Aging is a naturally occurring process inevitably affecting each living human. The brain is adversely affected by aging with increased risks of developing various neurological disorders. Thus, it is essential to investigate practical approaches that can counteract the impact of aging on the brain. Vitamin K2 (Vit. K2) is a naturally occurring vitamin with reported valuable therapeutic effects. The current study highlights the role of Vit. K2 administration in counteracting age-related changes in the brain using naturally aging rats. Three-month-old rats were assigned to two groups: an ageing control group receiving a drug vehicle and an ageing group orally gavaged with Vit. K2 (30 mg/kg, once daily 5 days per week). Treatment was continued for 17 months. Ten three-month-old rats were used as the adult control. Vit. K2 improved functional performance, reduced social anxiety, depressive-like behavior, and enhanced memory performance with concomitant preservation of hippocampal and cerebral cortex tyrosine hydroxylase expression. Biochemically, Vit. K2 administration restored oxidative-anti-oxidative homeostasis in the brain. Vit. K2 modulated inflammatory signaling, as evidenced by suppression in the brain of NLRP3, caspase-1, Il-1β, TNFα, IL-6, and CD68 expression. Concomitantly, histopathological examination revealed consistent hippocampal and cerebral cortex improvement. Thus, it can be inferred that Vit K2 can slow down age-related changes in the brain associated with modulation of NLRP3/caspase-1/Nrf-2 signaling. [ABSTRACT FROM AUTHOR]

Although runoff from trafficked urban areas is recognized as a potentially significant pathway of micropollutants, runoff pollution remains poorly documented, except for relatively few historical pollutants such as some metals and hydrocarbons. Therefore, in this work, road and parking lot runoff from four sites with contrasting traffic levels were analyzed for a very broad spectrum of molecules and elements. A total of 128 pollutants and micropollutants were monitored, including inorganic (n = 41) and organic (n = 87) pollutants. Both the dissolved and particulate phases were considered. For a reduced number of samples, non-targeted screening by high-resolution mass spectrometry (HRMS) was carried out. For targeted screening, the contamination profiles were quite homogeneous, but the concentrations significantly differed between the different sites. Sites with the highest traffic density exhibited the highest concentrations for polycyclic aromatic hydrocarbons (PAHs), some traffic-related metals, alkylphenols and phthalates. Overall, for most micropollutants, the parking lot runoff exhibited the lowest concentrations, and the specificity of this site was confirmed by its HRMS fingerprint. Non-target screening allowed the sites to be discriminated based on the occurrence of specific compounds. Unlike the results of targeted screening, the HRMS intra-site variability was lower than its inter-site variability. Unknown substances were tentatively identified, either characteristic of each site or ubiquitous of all samples. [ABSTRACT FROM AUTHOR]

Big data (BD) analytics has been increasingly gaining attraction in both practice and theory in light of its opportunities, barriers and expected benefits. In particular, emerging economics view big data analytics as having great importance despite the fact that it has been in a constant struggle with the barriers that prevent its adoption. Thus, this study primarily attempted to determine the drivers of big data analytics in the context of a developing economy, Jordan. The study examined the influence of technological, organizational and environmental factors on big data adoption in the Jordanian SMEs context, using PLS-SEM for the analysis. The empirical results revealed that the relative advantage, complexity, security, top management support, organizational readiness and government support influence the adoption of BD, whilst pressure of competition and compatibility appeared to be of insignificant influence. The findings are expected to contribute to enterprise management and strategic use of data analytics in the present dynamic market environment, for both researcher and practitioner circles concerned with the adoption of big data in developing countries. [ABSTRACT FROM AUTHOR]

Soil salinity is one of the constraints of crop production in Egypt. The aims of this study were to identify genomic regions associated with grain weight and its related traits along with their salinity tolerance indices and to identify the most salinity tolerant and high-yielding genotypes. Therefore, we evaluated an advanced backcross mapping population of barley in newly reclaimed soil under two salinity levels of groundwater aquifers in South of Sinai, Egypt. We detected significant QTL associated with grain weight related attributes and the salinity tolerance index (STI) distributed throughout the whole genome of barley, which can be used to enhance salinity tolerance. Moreover, the markers bPb-3739 (4H, 96.3 cM), AF043094A (5H, 156 cM), bPb-8161 (7H, 2.22 cM), and bPb-5260 (7H, 115.6 cM), were the most important identified genomic regions corresponding to vernalization, dwarfing and dehydrin genes, which are correlated with salinity tolerance. Additionally, the doubled haploid lines SI001, SI043, SI044, SI028, SI242, SI035, and SI005 had the highest STI values based on yield average. The present study demonstrated that wild and elite barley do harbor novel valuable alleles, which can enrich the genetic basis of cultivated barley and improve quantitative agronomic traits under salinity conditions. [ABSTRACT FROM AUTHOR]

Simple Summary: Aspirin-triggered resolvin D1 (AT-RvD1) is biosynthesised by leukocytes as a mechanism to resolve inflammation during infection and/or injury. Emerging studies reveal that AT-RvD1 also has anti-cancer properties associated with stimulating macrophage-mediated clearance of tumour debris. No study to date has investigated how AT-RvD1 influences the neutrophil to lymphocyte ratio (NLR) in lung cancer, an established marker of poor prognosis. The biosynthesis of AT-RvD1 is dependent on the ALOX5 gene, and we reveal that ALOX5 mRNA expression was markedly reduced in lung adenocarcinoma tumours. We next utilised an oncogenic KrasG12D lung adenocarcinoma mouse model to investigate the efficacy of AT-RvD1 in vivo. We show for the first time that AT-RvD1 reduces tumour growth in the lungs of KrasG12D mice and alters the immune landscape in tumours by reducing the NLR. Tumour-associated neutrophils (TANs) can support tumour growth by suppressing cytotoxic lymphocytes. AT-RvD1 is an eicosanoid that can antagonise neutrophil trafficking instigated by ALX/FPR2 ligands such as serum amyloid A (SAA). We aimed to establish whether SAA and ALOX5 expression associates with TANs and investigate the immunomodulatory actions of AT-RvD1 in vivo. MPO-positive neutrophils were quantified in tumour blocks from lung adenocarcinoma (n = 48) and control tissue (n = 20) by IHC. Tumour expression of SAA and ALOX5 were analysed by RTqPCR and an oncogenic KrasG12D lung adenocarcinoma mouse model was used to investigate the in vivo efficacy of AT-RvD1 treatment. ALOX5 expression was markedly reduced in lung adenocarcinoma tumours. The SAA/ALOX5 ratio strongly correlated with TANs and was significantly increased in tumours harbouring an oncogenic KRAS mutation. AT-RvD1 treatment reduced tumour growth in KrasG12D mice, which was accompanied by suppressed cellular proliferation within parenchymal lesions. In addition, AT-RvD1 significantly reduced the neutrophil to lymphocyte ratio (NLR), an established prognostic marker of poor survival in adenocarcinoma. This study identifies a novel molecular signature whereby elevated levels of SAA relative to ALOX5 favour accumulation of TANs. Furthermore, the ALOX5/5-LO enzymatic product, AT-RvD1, markedly reduced the NLR and suppressed tumour growth in KrasG12D mice. [ABSTRACT FROM AUTHOR]

Computed tomography (CT) is a key imaging technique in diagnostic radiology, providing highly sensitive and specific information. While its use has increased dramatically in recent years, the quantity and associated risks of radiation from CT scans present major challenges, particularly in paediatrics. The fundamental principles of radiation protection require that radiation quantities be as low as reasonably achievable and CT use must be justified, particularly for paediatric patients. CT radiation knowledge is a key factor in optimising and minimising radiation risk. The objective of this study was to analyse knowledge level, expertise, and competency regarding CT radiation dose and its hazards in paediatrics among radiologists in Saudi Arabian hospitals. A self-reported, multiple-choice questionnaire assessed the attitudes and opinions of radiologists involved in imaging studies using ionising radiation. Among the total respondents, 65% ± 13.5% had a good comprehension of the dangers of carcinogenicity to the patient resulting from CT scans, with 80% presuming that cancer risks were elevated. However, only 48.5%, 56.5%, and 65% of the respondents were aware of specific radiation risks in head, chest, and abdominal paediatric examinations, respectively. Regular, frequent, and specific training courses are suggested to improve the fundamental knowledge of CT radiation among radiologists and other physicians. [ABSTRACT FROM AUTHOR]

Lung cancer is the leading cause of cancer-related mortality, which histologically is classified into small-cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). NSCLC accounts for approximately 85% of all lung cancer diagnoses, with the majority of patients presenting with lung adenocarcinoma (LAC). KRAS mutations are a major driver of LAC, and are closely related to cigarette smoking, unlike mutations in the epidermal growth factor receptor (EGFR) which arise in never-smokers. Although the past two decades have seen fundamental progress in the treatment and diagnosis of NSCLC, NSCLC still is predominantly diagnosed at an advanced stage when therapeutic interventions are mostly palliative. A disintegrin and metalloproteinase 17 (ADAM17), also known as tumour necrosis factor-α (TNFα)-converting enzyme (TACE), is responsible for the protease-driven shedding of more than 70 membrane-tethered cytokines, growth factors and cell surface receptors. Among these, the soluble interleukin-6 receptor (sIL-6R), which drives pro-inflammatory and pro-tumourigenic IL-6 trans-signaling, along with several EGFR family ligands, are the best characterised. This large repertoire of substrates processed by ADAM17 places it as a pivotal orchestrator of a myriad of physiological and pathological processes associated with the initiation and/or progression of cancer, such as cell proliferation, survival, regeneration, differentiation and inflammation. In this review, we discuss recent research implicating ADAM17 as a key player in the development of LAC, and highlight the potential of ADAM17 inhibition as a promising therapeutic strategy to tackle this deadly malignancy. [ABSTRACT FROM AUTHOR]

A stochastic method for evaluating the in situ mass balance of micropollutants in a stormwater biofilter, accounting for inlet and outlet loads and the evolution of pollutant mass in the filter media (ΔMsoil) at an annual scale, is proposed. In the field context, this type of calculation presents a number of methodological challenges, associated with estimating water quality for unsampled rain events, reconstituting missing or invalidated flow data and accounting for significant uncertainties associated with these estimations and experimental measurements. The method is applied to a biofiltration swale treating road runoff for two trace metals, Cu and Zn and six organic micropollutants: pyrene (Pyr), phenanthrene (Phen), bisphenol-A (BPA), octylphenol (OP), nonylphenol (NP) and bis(2-ethylhexyl) phthalate (DEHP). Pollutant loads were reduced by 27–72%. While organic micropollutants are likely to be lost to degradation or volatilization processes in such systems, dissipation could not be demonstrated for any of the organic micropollutants studied due to emissions from construction materials (case of BPA, OP, NP and DEHP) or high uncertainties in ΔMsoil (case of Pyr and Phen). The necessary conditions for establishing an in situ mass balance demonstrating dissipation, which include acquisition of data associated with all terms over a period long enough that uncertainty propagation is limited and the absence of additional sources of pollutants in the field, are discussed. [ABSTRACT FROM AUTHOR]

Sustainable drainage systems (SuDS) have become a promising solution for increasing imperviousness by reducing water runoff volumes and flow rates, and improving water quality. However, the efficiency of these systems is dependent on soil hydraulic and physical properties, which in turn are spatially variable; however, this variability has been sparsely documented for urban areas, especially for road-side SuDS. In this study, the spatial variability of soil hydraulic properties, along with the uncertainty of these properties due to estimation methods, were investigated for three roadside SuDS in France (Paris region). Estimation methods were based on both in-situ infiltration tests and pedotransfer functions (PTFs). Results show high spatial variability in saturated hydraulic conductivity Ks (up to 160% coefficient of variation), which is dominant relative to uncertainties in PTFs predictions and those induced by experimental errors. Many specific factors might be responsible for this variability, especially in the urban context, such as construction techniques, CaCO3 precipitation, and vegetation development. In order to evaluate the effects of this variability on hydrological performance, a hydrological model of a bioretention cell was tested. Simulations revealed that peak flows and volumes are highly affected by the spatial variability of soil hydraulic properties; notably, vertical variability increases the overflow by 50%. The number of infiltration measurements required to evaluate a representative average Ks with an uncertainty of a factor of two or less was found to be four/eight, depending on the studied site. This study provides considerable insight into the spatial variability of soil hydraulic properties and its implications for hydrological performance of roadside SuDS, as it is based on a sound understanding of both theory and practice. [ABSTRACT FROM AUTHOR]

Although progressive wasting and weakness of respiratory muscles are the prominent hallmarks of Duchenne muscular dystrophy (DMD) and long-COVID (also referred as the post-acute sequelae of COVID-19 syndrome); however, the underlying mechanism(s) leading to respiratory failure in both conditions remain unclear. We put together the latest relevant literature to further understand the plausible mechanism(s) behind diaphragm malfunctioning in COVID-19 and DMD conditions. Previously, we have shown the role of matrix metalloproteinase-9 (MMP9) in skeletal muscle fibrosis via a substantial increase in the levels of tumor necrosis factor-α (TNF-α) employing a DMD mouse model that was crossed-bred with MMP9-knockout (MMP9-KO or MMP9 -/- ) strain. Interestingly, recent observations from clinical studies show a robust increase in neopterin (NPT) levels during COVID-19 which is often observed in patients having DMD. What seems to be common in both (DMD and COVID-19) is the involvement of neopterin (NPT). We know that NPT is generated by activated white blood cells (WBCs) especially the M1 macrophages in response to inducible nitric oxide synthase (iNOS), tetrahydrobiopterin (BH4), and tetrahydrofolate (FH4) pathways, i.e., folate one-carbon metabolism (FOCM) in conjunction with epigenetics underpinning as an immune surveillance protection. Studies from our laboratory, and others researching DMD and the genetically engineered humanized (hACE2) mice that were administered with the spike protein (SP) of SARS-CoV-2 revealed an increase in the levels of NPT, TNF-α, HDAC, IL-1β, CD147, and MMP9 in the lung tissue of the animals that were subsequently accompanied by fibrosis of the diaphragm depicting a decreased oscillation phenotype. Therefore, it is of interest to understand how regulatory processes such as epigenetics involvement affect DNMT, HDAC, MTHFS, and iNOS that help generate NPT in the long-COVID patients.