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A turbulent plane jet impinging on a slotted surface is simulated using Large Eddy Simulation LES. The Reynolds number, based on the jet-exit velocity and width, is equal to 5435. The slotted surface is placed at a distance equal to four times the jet-exit width. Three computational grids were used to assess the accuracy of the LES simulations conducted. The interaction effects of the jet with the slot propagate away from the slot region and manifest into pressure perturbations. Interesting phenomena were observed when linking the dynamic flow features upstream and downstream of the slotted surface. LES predicted three dominant frequencies at different points from time signals of velocities and pressure. The dominant frequency of the pressure field, away from the slot, corresponds to that of coherent vortices which follow a trajectory that is far from being deviated towards the wall jet or into the slot of the impingement wall completely. Among these turbulent structures of interest, pairs of opposite, but in phase, vortices are responsible for promoting the occurrence of the throttling phenomenon. The characteristic frequencies of the pressure field are similar upstream and downstream of the impingement wall. The peaks of the fluctuating pressures, away from the slot, correlate well with the minimum flow rate through the slot which correspond to the throttling phenomenon.

Numerical computation of thermally developing laminar flow of viscoelastic FENE-P fluids flowing between two stationary parallel plates is investigated using the finite element technique. The influence of the effect of the solvent contribution as well as the fluid rheology on the flow field and heat transfer enhancement is investigated for the case of imposed constant wall heat flux and neglected viscous dissipation. Numerical results for flow field are compared first against available analytical solutions with and without inclusion of the solvent contribution. The obtained results for the viscoelastic case show that increasing Weissenberg number (We) leads to an increase in Nusselt number (Nu) while high values of the extensibility parameter (L2) decrease the Nusselt number. Fully developed Nusselt number values for FENE-P fluids flowing between two fixed parallel plates are obtained for several values of polymer concentration and the study confirms quantitatively that polymer concentration enhances heat transfer rates in FENE-P fluids.

This study investigates the impact of formal institutional factors on public sector efficiency, focusing on environmental and healthcare performance—two of the most widely examined sectors in the public administration literature. The empirical analysis is based on a panel of 139 countries—33 developed and 106 developing—covering the period from 2012 to 2020. The analysis adopts a three-stage methodological framework comprising: (a) Bayesian Data Envelopment Analysis (DEA) to estimate efficiency scores, (b) Principal Component Analysis (PCA) to construct a composite Public Sector Efficiency Index, and (c) a two-step Generalized Method of Moments (GMM) approach to evaluate the influence of institutional variables, country classification (developed vs. developing), and their interactions on public sector efficiency. The findings highlight the importance of sustained efforts to reduce CO₂ emissions and manage healthcare expenditures effectively. The results underscore the critical role of strengthening formal institutions and enhancing the Human Development Index (HDI) to improve public sector efficiency.

Sabkhas are hypersaline, mineral-rich, supratidal mudflats that harbor microbes that are adapted to high salt concentration. Sabkha microbial diversity is generally studied for their community composition, but less is known about their genetic structure and heterogeneity. In this study, we analyzed a coastal sabkha for its microbial composition using 16S rDNA and whole metagenome, as well as for its population genetic structure. Our 16S rDNA analysis show high alpha diversity in both inner and edge sabkha than outer sabkha. Beta diversity result showed similar kind of microbial composition between inner and edge sabkha, while outer sabkha samples show different microbial composition. At phylum level, Bacteroidetes (~ 22 to 34%), Euryarchaeota (~ 18 to ~ 30%), unclassified bacteria (~ 24 to ~ 35%), Actinobacteria (~ 0.01 to ~ 11%) and Cyanobacteria (less than 1%) are predominantly found in both inside and edge sabkha regions, whereas Proteobacteria (~ 92 to ~ 97%) and Parcubacteria (~ 1 to ~ 2%) are predominately found in outer sabkha. Our 225 metagenomes assembly from this study showed similar bacterial community profile as observed in 16S rDNA-based analysis. From the assembled genomes, we found important genes that are involved in biogeochemical cycles and secondary metabolite biosynthesis. We observed a dynamic, thriving ecosystem that engages in metabolic activity that shapes biogeochemical structure via carbon fixation, nitrogen, and sulfur cycling. Our results show varying degrees of horizontal gene transfers (HGT) and homologous recombination, which correlates with the observed high diversity for these populations. Moreover, our pairwise population differentiation (Fst) for the abundance of species across the salinity gradient of sabkhas identified genes with strong allelic differentiation, lower diversity and elevated nonsynonymous to synonymous ratio of variants, which suggest selective sweeps for those gene variants. We conclude that the process of HGT, combined with recombination and gene specific selection, constitute the driver of genetic variation in bacterial population along a salinity gradient in the unique sabkha ecosystem.

Process intensification (PI) is playing a key role in alleviating the challenge of reducing carbon footprint of many chemical processes and bringing down their development costs. Over the years, many PI technologies have been investigated with rotating packed bed (RPB) technology receiving much of the attention for its potential of significant intensification in terms of capital expenditure, operating costs, and hardware size. In this study, microscale CFD simulations of a rotating packed bed were conducted, and the results were validated with experimental data. The results show the strong relation between the reverse flow at the packing outer periphery and the gas maldistribution factor. The latter is mainly caused by the accelerating flow in the outer cavity. Inside the wire mesh packing, the gas flow is found to be almost fully uniform for nearly half of the total packing depth. Also, turbulent kinetic energy (TKE) levels at the packing outer edge are strongly linked to the slip tangential velocity component, while at its inner edge, they depend mainly on the radial packing velocity. The so-called gas end effect zone is detected by observing the TKE profiles near the packing outer edge. The latter accounts for less than 10% of the total packing depth. The validity of the widely used porous media model in RPBs’ packing for both radial and tangential directions is confirmed by the obtained results, but this excludes the packing inner and outer edges. In the inner cavity region, gas exhibits two distinctive behaviors and transits from free vortex flow to swirling flow as the flow becomes close to the vortex core. As a result of this transition, the increase in shear stress accelerates the decrease in the gas tangential velocity in the vortex core and help speed up the favorable pressure gradient and flow establishment beyond the vortex core.

This study evaluated the effectiveness of the amplicon RX post-PCR clean-up kit in enhancing trace DNA profile recovery from forensic casework samples amplified using the GlobalFiler PCR amplification kit. The impact of post-PCR clean-up on allele recovery and signal intensity was assessed in both trace casework samples and control samples across a range of DNA concentrations. The results showed that the amplicon RX method significantly improved allele recovery compared to the 29-cycle protocol ( p  = 8.30 × 10 −12 ) and achieved slightly better results than the 30-cycle protocol ( p  = 0.019). Additionally, the Amplicon RX method demonstrated a significant increase in signal intensity ( p  = 2.70 × 10 −4 ), reflecting improved sensitivity in detecting trace DNA profiles compared to the 30-cycle protocol. In the evaluation of control samples, the amplicon RX method consistently outperformed both the 29- and 30-cycle protocols, especially at lower DNA concentrations (D3: 0.001 ng/µL). While the performance of all methods declined at the lowest concentration (D4: 0.0001 ng/µL), the Amplicon RX method still demonstrated superior allele recovery ( p  = 0.014 compared to 29 cycles; p  = 0.011 compared to 30 cycles). Therefore, the Amplicon RX method should be widely adopted in forensic laboratories to enhance the analysis of extremely low-template and compromised samples. These findings highlight the potential of the amplicon RX post-PCR clean-up kit to improve trace DNA analysis in forensic casework. Further research is recommended to validate these results and explore its broader application in forensic DNA analysis, particularly in complex DNA mixtures and extremely low-template samples.

Herein, we describe the first consistent regiospecific reaction of isothiocyanates with a variety of substituted N-arylcyanothioformamides in a 1:1 molar ratio to generate a series of imidazolidineiminodithiones decorated with a multitude of functional groups on both aromatic rings. The reaction is carried out at room temperature using a 20 mol% catalytic amount of triethylamine with DMF as the solvent to selectively form the mentioned products with exclusive regioselectivity. The methodology features wide substrate scope, no requirement for chromatography, and good to high reaction yields. The products were isolated by simple ether/brine extraction and the structures were verified by multinuclear NMR spectroscopy and high accuracy mass measurements. The first conclusive molecular structure elucidation of the observed regioisomer was established by single-crystal X-ray diffraction analysis. Likewise, the tautomer of the N-arylcyanothioformamide reactant was proven by X-ray diffraction analysis. Density functional theory computations at the B3LYP-D4/def2-TZVP level in implicit DMF solvent were conducted to support the noted regiochemical outcome and proposed mechanism.

The current situation of the unprecedented COVID-19 pandemic leverages Artificial Intelligence (AI) as an innovative tool for addressing the evolving clinical challenges. An example is utilizing Machine Learning (ML) models-a subfield of AI that take advantage of observational data/Electronic Health Records (EHRs) to support clinical decision-making for COVID-19 cases. This study aimed to evaluate the clinical characteristics and risk factors for COVID-19 patients in the United Arab Emirates utilizing EHRs and ML for survival analysis models. We tested various ML models for survival analysis in this work we trained those models using a different subset of features extracted by several feature selection methods. Finally, the best model was evaluated and interpreted using goodness-of-fit based on calibration curves,Partial Dependence Plots and concordance index. The risk of severe disease increases with elevated levels of C-reactive protein, ferritin, lactate dehydrogenase, Modified Early Warning Score, respiratory rate and troponin. The risk also increases with hypokalemia, oxygen desaturation and lower estimated glomerular filtration rate and hypocalcemia and lymphopenia. Analyzing clinical data using AI models can provide vital information for clinician to measure the risk of morbidity and mortality of COVID-19 patients. Further validation is crucial to implement the model in real clinical settings.

Little is known about depressive symptoms among adolescents in the United Arab Emirates (UAE). This study aimed to identify the prevalence of depression and its association with self-esteem, individual, parental and family factors among adolescents aged 12 to 18 in UAE. Six hundred adolescents, aged 12 to 18 years were recruited from 4 of 111 schools in a cross-sectional study. We administered Beck Depression Inventory Scale and Rosenberg Self-esteem Scale to measure self-report symptoms of depression and self-esteem. We used multiple linear regression to identify significant predictors of depression. Over 86% of the identified sample participated to the survey. The mean age of the sample was 14.3 (±1.3) with an excess of girls (61%). Depressive symptoms were detected in 17.2% (95% CI 14.2-20.7). There was an inverse relationship between self-esteem scores and depressive symptoms. Positive predictors of depressive symptoms, having controlled for age, gender, and ethnicity included experiencing neglect, being verbally abused in school, having no monthly allowance to spend in school, a history of physical morbidities requiring treatment, being a current or past smoker and a low family income. The high prevalence of depressive symptoms measured in this survey suggests a significant public health problem among adolescents in the UAE. Public health interventions aimed at facilitating education and early detection and potential treatment of depressive symptoms are a priority in the region.

Microbes have inhabited the earth for hundreds of millions of years longer than humans. The microbiota–gut–brain axis (MGBA) represents a bidirectional communication pathway. These communications occur between the central nervous system (CNS), the enteric nervous system (ENS), and the emotional and cognitive centres of the brain. The field of research on the gut–brain axis has grown significantly during the past two decades. Signalling occurs between the gut microbiota and the brain through the neural, endocrine, immune, and humoral pathways. A substantial body of evidence indicates that the MGBA plays a pivotal role in various neurological diseases. These include Alzheimer’s disease (AD), autism spectrum disorder (ASD), Rett syndrome, attention deficit hyperactivity disorder (ADHD), non-Alzheimer’s neurodegeneration and dementias, fronto-temporal lobe dementia (FTLD), Wilson–Konovalov disease (WD), multisystem atrophy (MSA), Huntington’s chorea (HC), Parkinson’s disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), temporal lobe epilepsy (TLE), depression, and schizophrenia (SCZ). Furthermore, the bidirectional correlation between therapeutics and the gut–brain axis will be discussed. Conversely, the mood of delivery, exercise, psychotropic agents, stress, and neurologic drugs can influence the MGBA. By understanding the MGBA, it may be possible to facilitate research into microbial-based interventions and therapeutic strategies for neurological diseases.