Microscale Audits of the Built Environment and the Challenges for Pedestrians in 4 Residential Areas in Oman.

Background: Ensuring a livable and healthy built environment that addresses challenges of climate change and the pandemic of noncommunicable diseases should include creating an environment support of physical activity. This study aims to build local evidence on improving the residential areas by assessing the built environment of 4 residential areas in Oman.

Methods: This study uses the Microscale Audit of Pedestrian Streetscapes-Mini, a 15-item tool with 4 subscales (destinations and land use, aesthetics, pedestrian infrastructure, and crossings/traffic safety), to conduct environmental audits of 4 areas in Barka and Nizwa, Oman.

In-silico and in-vitro studies to identify potential inhibitors of SARS-CoV-2 spike protein from Omani medicinal plants.

In the quest for novel therapeutic agents against SARS-CoV-2, the proposed study explores the potential of traditional Omani medicinal plants, focusing on the efficacy of natural ligands against the virus's Spike protein. Among 437 identified medicinal plants across Oman, 47 species that are documented for their traditional use in treating respiratory infections, with 30 species' ligands available were chosen for analysis. Molecular docking was performed using Autodock Vina on these ligands, yielding 406 unique ligands post-duplication removal.

Environmental impact assessment of different power generation strategies in Oman: A comparative life-cycle analysis.

This paper presents a comparative environmental impact assessment considering different power generation strategies in Oman. The Life-Cycle Assessment (LCA) methodology, and the OpenLCA tool, were employed in carrying out comprehensive analysis, and evaluation of the various environmental aspects in filling the research gap, by replacing conventional diesel generators with natural gas alternatives in Oman. The obtained results indicate that utilizing natural gas significantly reduces environmental impacts, including a decrease in global warming potential to 2.

Tapping into haloalkaliphilic bacteria for sustainable agriculture in treated wastewater: insights into genomic fitness and environmental adaptation.

The increasing salinity and alkalinity of soils pose a global challenge, particularly in arid regions such as Tunisia, where about 50% of lands are sensitive to soil salinization. Anthropogenic activities, including the use of treated wastewater (TWW) for irrigation, exacerbate these issues. Haloalkaliphilic bacteria, adapted to TWW conditions and exhibiting plant-growth promotion (PGP) and biocontrol traits, could offer solutions.

S211 as a microbial cell factory for direct bioconversion of waste cooking oil into medium-chain-length polyhydroxyalkanoates.

The present study examines the use of waste cooking oil (WCO) as a substrate for medium-chain-length polyhydroxyalkanoates (mcl-PHA) production by S211. The genome analysis revealed that the S211 strain has a mcl-PHA cluster () encoding two class II PHA synthases (PhaC1 and PhaC2) separated by a PHA depolymerase (PhaZ), a transcriptional activator (PhaD) and two phasin-like proteins (PhaFI). Genomic annotation also identified a gene encoding family I.

Impact of mitigating obesity, smoking, and physical inactivity on type 2 diabetes mellitus burden in Oman: insights from mathematical modeling.

Introduction: To estimate the impact of reducing obesity, smoking, and physical inactivity (PIA) prevalence, and of introducing physical activity (PA) as an explicit intervention, on the prevalence, incidence, and mortality of type 2 diabetes mellitus (T2DM) in Oman.

Research Design And Methods: A deterministic population-level mathematical model was employed to investigate the impact of different scenarios for reducing T2DM risk factors on T2DM epidemiology. The model was stratified by sex, age group, risk factor status, T2DM status, and intervention status and parameterized with nationally representative data.

Brucella pituitosa strain BU72, a new hydrocarbonoclastic bacterium through exopolysaccharide-based surfactant production.

Hydrocarbon and heavy metal pollution are amongst the most severe and prevalent environmental problems due to their toxicity and persistence. Bioremediation using microorganisms is considered one of the most effective ways to treat polluted sites. In the present study, we unveil the bioremediation potential of Brucella pituitosa strain BU72.

PlantMedOman: an online database for Oman's medicinal plants.

The Sultanate of Oman has a rich biodiversity, particularly in medicinal plants, and plays a crucial role in traditional healthcare practices. However, the wealth of knowledge about these plants is scattered across various literature, making it challenging for researchers, practitioners, and the public to access comprehensive information. Therefore, the availability of a centralized, user-friendly online database to catalog Oman's medicinal plants is of great importance.

Removal of heavy metal ions from wastewater using two-dimensional transition metal carbides.

Water is an indispensable material for human life. Unfortunately, the development of industrial activities has reduced the quality of water resources in the world. Meantime, heavy metals are an important factor in water pollution due to their toxicity.

CdInSe@chitosan heterojunction nanocomposite with ultrahigh photocatalytic activity under sunlight driven photodegradation of organic pollutants.

This research focused on synthesizing a CdInSe@Ch nanocomposite by doping CdInSe into chitosan using a photolysis assisted ultrasonic process. The aim was to enhance the photodegradation efficiency of ofloxacin and 2,4-dichlorophenoxyacetic acid under sunlight. The synthesized CdInSe@Ch nanocomposite was investigated via different techniques, including XRD, XPS, FTIR, TEM, DSC, TGA, UV-Vis and PL.

CovMediScanX: A medical imaging solution for COVID-19 diagnosis from chest X-ray images.

Introduction: Radiologists have extensively employed the interpretation of chest X-rays (CXR) to identify visual markers indicative of COVID-19 infection, offering an alternative approach for the screening of infected individuals. This research article presents CovMediScanX, a deep learning-based framework designed for a rapid and automated diagnosis of COVID-19 from CXR scan images.

Methods: The proposed approach encompasses gathering and preprocessing CXR image datasets, training deep learning-based custom-made Convolutional Neural Network (CNN), pre-trained and hybrid transfer learning models, identifying the highest-performing model based on key evaluation metrics, and embedding this model into a web interface called CovMediScanX, designed for radiologists to detect the COVID-19 status in new CXR images.

Persistence of Symptoms Following Hospitalization for COVID-19 in Oman: A Bidirectional Observational Study.

Objectives: This study sought to assess the prevalence of persistent COVID-19-related symptoms in patients with mild, severe, and critical disease.

Methods: We conducted a bidirectional cohort observational study that included all adult patients ≥ 18 years, admitted to Armed Forces Hospital, Muscat between July 2020 and June 2022, with COVID-19 infection and discharged alive. Patients were requested to attend outpatient clinic at weeks six and 12 post-discharge, where they filled out a questionnaire and underwent a chest X-ray.

A Context-Aware, Computer-Vision-Based Approach for the Detection of Taxi Street-Hailing Scenes from Video Streams.

With the increasing deployment of autonomous taxis in different cities around the world, recent studies have stressed the importance of developing new methods, models and tools for intuitive human-autonomous taxis interactions (HATIs). Street hailing is one example, where passengers would hail an autonomous taxi by simply waving a hand, exactly like they do for manned taxis. However, automated taxi street-hailing recognition has been explored to a very limited extent.

Construct validity of the physical activity neighborhood environment scale-Oman.

Aims: This study aims to examine the construct validity of Physical Activity Neighborhoods Environment Scales, Oman (PANES-O), and compare the subjective perceptions with objective measures in Muscat, the capital area of Oman.

Methods: Walkability index scores using GIS maps were calculated for 35 study areas in Muscat based on which five low and 5 high walkable study areas were randomly selected. A community survey was then conducted in November 2020 in each study area using the 16-item PANES-O instrument to measure the participants' perception of neighborhood density, land use mix, infrastructure, safety, aesthetics, and street connectivity.

From complexity to evolution: Mapping resilience management practices in the hospitality industry during the COVID-19 crisis.

The COVID-19 pandemic has severely affected the hospitality industry. Many have treated the crisis as a temporary shock. However, there are those who see it as a turning point.

Cost benefit analysis for green hydrogen production from treated effluent: The case study of Oman.

Recently, the management of water and wastewater is gaining attention worldwide as a way of conserving the natural resources on the planet. The traditional wastewater treatment in Oman is such that the treated effluent produced is only reused for unfeasible purposes such as landscape irrigation, cooling, or disposed of in the sea. Introducing more progressive reuse applications can result in achieving a circular economy by considering treated effluent as a source of producing new products.

High-Performance Solar Steam Generator Using Low-Cost Biomass Waste Photothermal Material and Engineering of the Structure.

In this work, high-performance, low-cost, environmentally friendly multilayered solar steam generation systems are fabricated by engineering the structure and using a biomass photothermal material. Remarkably, the biomass photothermal material is extracted from the pyrolysis waste of linseed (flax) grains. The introduced system desalinates water using solar energy as the renewable source of energy, and its light absorber is from the waste of a renewable source.

Identification, molecular docking, and kinetic studies of six novel angiotensin-I-converting enzyme (ACE) inhibitory peptides derived from Kenaf (Hibiscus cannabinus L.) seed.

Kenaf (Hibiscus cannabinus L.) seed is a valuable protein source that could be used to prepare protein hydrolysates with antihypertensive properties. However, the potential of using kenaf seeds for health food and pharmaceutical applications has not been fully exploited.

Hierarchical Analysis Process for Belief Management in Internet of Drones.

Group awareness is playing a major role in the efficiency of mission planning and decision-making processes, particularly those involving spatially distributed collaborative entities. The performance of this concept has remarkably increased with the advent of the Internet of Things (IoT). Indeed, a myriad of innovative devices are being extensively deployed to collaboratively recognize and track events, objects, and activities of interest.

A new vaccine supply chain network under COVID-19 conditions considering system dynamic: Artificial intelligence algorithms.

With the discovery of the COVID-19 vaccine, what has always been worrying the decision-makers is related to the distribution management, the vaccination centers' location, and the inventory control of all types of vaccines. As the COVID-19 vaccine is highly demanded, planning for its fair distribution is a must. University is one of the most densely populated areas in a city, so it is critical to vaccinate university students so that the spread of this virus is curbed.

A possibilistic-robust-fuzzy programming model for designing a game theory based blood supply chain network.

This paper presents a bi-level blood supply chain network under uncertainty during the COVID-19 pandemic outbreak using a Stackelberg game theory technique. A new two-phase bi-level mixed-integer linear programming model is developed in which the total costs are minimized and the utility of donors is maximized. To cope with the uncertain nature of some of the input parameters, a novel mixed possibilistic-robust-fuzzy programming approach is developed.

A new humanitarian relief logistic network for multi-objective optimization under stochastic programming.

Millions of affected people and thousands of victims are consequences of earthquakes, every year. Therefore, it is necessary to prepare a proper preparedness and response planning. The objectives of this paper are ) minimizing the expected value of the total costs of relief supply chain, ) minimizing the maximum number of unsatisfied demands for relief staff and ) minimizing the total probability of unsuccessful evacuation in routes.

Extremophilic Bacterium G11 as a Cell Factory for Poly-3-Hydroxybutyrate-co-3-Hydroxyvalerate Copolymer's Production.

Microbial polyhydroxyalkanoates (PHA) are biodegradable and biocompatible bio-based polyesters, which are used in various applications including packaging, medical and coating materials. In this study, an extremophilic hydrocarbonoclastic bacterium, previously isolated from saline sediment in the Tunisian desert, has been investigated for PHA production. The accumulation of intracellular PHA granules in G11 was detected by Nile blue A staining of the colonies.