Congestion control in resilient packet ring networks

The Resilient Packet Ring (RPR) is a new metro technology; RPR shares SONET\u27s ability in providing fast recovery from link and node failures as well as inherits the cost and simplicity of Ethernet. RPR, like SONET/SDH, is a ring based architecture consisting of two optical rotating rings (uni-directional). In RPR, packets are removed from the ring at the destination so that different segments of the ring can be used at the same time for different flows; as a result, the spatial reuse feature is achieved. Enabling the spatial reuse feature introduces the challenge of guaranteeing fairness among the nodes sharing the same link. The RPR fairness algorithm is comparatively simple, but it poses some critical limitations. One of the major problems is that the amount of bandwidth allocated by the algorithm oscillates severely under unbalanced traffic scenarios. These oscillations are a barrier to achieving spatial reuse and high bandwidth utilization. Moreover, the current RPR standard uses a single FIFO for each class at the ingress point, thus resulting in the head of line blocking problem. On the other hand, RPR uses the shortest path to route the traffic in the dual ring which is inefficient and unfair. In this dissertation, the performance of the existing fairness algorithms and their limitations was investigated. Two bandwidth allocation algorithms were proposed to address the fairness issue. Both algorithms were demonstrated analytically and through simulations were able to achieve fairness and maximize the ring utilization. The Distributed Bandwidth Allocation (DBA) and the Adaptive Bandwidth Allocation (ABA) do not need to maintain information about each node. Instead, they use the local information which makes them scalable for a ring with any number of nodes. The Simple Scheduling Algorithm (SSA) was proposed to avoid the head of line blocking and to maximize the ring utilization at a very low complexity. The SSA algorithm was shown analytically and through simulations to be optimal where the flows achieve their max-mm fair rates at a very low computational complexity. Also, the weighted routing algorithm was proposed to maximize the ring utilization by enabling the RPR nodes to transmit in both rings in a weighted manner. The routing algorithm was demonstrated analytically and through simulations was able to maximize the ring utilization

ModFOLD8: accurate global and local quality estimates for 3D protein models

Methods for estimating the quality of 3D models of proteins are vital tools for driving the acceptance and utility of predicted tertiary structures by the wider bioscience community. Here we describe the significant major updates to ModFOLD, which has maintained its position as a leading server for the prediction of global and local quality of 3D protein models, over the past decade (>20 000 unique external users). ModFOLD8 is the latest version of the server, which combines the strengths of multiple pure-single and quasi-single model methods. Improvements have been made to the web server interface and there has been successive increases in prediction accuracy, which were achieved through integration of newly developed scoring methods and advanced deep learning-based residue contact predictions. Each version of the ModFOLD server has been independently blind tested in the biennial CASP experiments, as well as being continuously evaluated via the CAMEO project. In CASP13 and CASP14, the ModFOLD7 and ModFOLD8 variants ranked among the top 10 quality estimation methods according to almost every official analysis. Prior to CASP14, ModFOLD8 was also applied for the evaluation of SARS-CoV-2 protein models as part of CASP Commons 2020 initiative. The ModFOLD8 server is freely available at: https://www.reading.ac.uk/bioinf/ModFOLD/

Survival Rate of Patients with Cardiothoracic Injuries in Road Traffic Accidents, and their Relationship with ISS, GCS and blood transfusions.

Severe thoracic trauma is one of the major causes of injury-related mortality. In the United States, thoracic trauma results in one-fourth of all trauma deaths. Globally, cardiothoracic trauma is also a major contributor to mortality. The most common cardiothoracic injuries include rib fractures, thoracic vertebral fractures, haemothorax, pneumothorax, flail chest, and lung contusions. The purpose of the present study was to determine the survival rate of patients with cardiovascular injuries in road traffic accidents and its relationship with ISS, GCS and blood transfusions at King Khalid Hospital. This study is a useful addition to the literature, as research in this topic is lacking. A total of 189 patients were transported to the hospital with cardiothoracic injuries during the study period. Data was gathered regarding age, gender, nationality, vehicle user type, anatomical region injured, Intensive Care Unit (ICU) admission, Glasgow Coma Scale (GCS), Injury Severity Score (ISS), blood transfusion, treatment and mortality rate. The neurological status was assessed using the GCS score. Injury Severity Scores were calculated to categorize the injury severity. The mean patient age was 31.81 years, with a peak age of between 21–30 years. Males predominated (93.7%) with a male to female ratio of 15:1. Most of the patients were Saudi nationals (61.3%). Overall mortality was 7.9%. Factors that were significantly associated with mortality were head and neck involvement, ICU admission, age (above 60), treatment delivered, and blood transfusions. Cardiothoracic trauma is associated with a high mortality rate, which may depend on the clinical presentation such as GCS, ISS, degree of shock, pattern of injuries, and associated injuries. Immediate management is vital for patients with life-threatening cardiothoracic trauma, as mortality is high if the diagnosis is missed, wrong or left untreated

The Saudi Critical Care Society practice guidelines on the management of COVID-19 in the ICU: Therapy section

BACKGROUND: The rapid increase in coronavirus disease 2019 (COVID-19) cases during the subsequent waves in Saudi Arabia and other countries prompted the Saudi Critical Care Society (SCCS) to put together a panel of experts to issue evidence-based recommendations for the management of COVID-19 in the intensive care unit (ICU). METHODS: The SCCS COVID-19 panel included 51 experts with expertise in critical care, respirology, infectious disease, epidemiology, emergency medicine, clinical pharmacy, nursing, respiratory therapy, methodology, and health policy. All members completed an electronic conflict of interest disclosure form. The panel addressed 9 questions that are related to the therapy of COVID-19 in the ICU. We identified relevant systematic reviews and clinical trials, then used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach as well as the evidence-to-decision framework (EtD) to assess the quality of evidence and generate recommendations. RESULTS: The SCCS COVID-19 panel issued 12 recommendations on pharmacotherapeutic interventions (immunomodulators, antiviral agents, and anticoagulants) for severe and critical COVID-19, of which 3 were strong recommendations and 9 were weak recommendations. CONCLUSION: The SCCS COVID-19 panel used the GRADE approach to formulate recommendations on therapy for COVID-19 in the ICU. The EtD framework allows adaptation of these recommendations in different contexts. The SCCS guideline committee will update recommendations as new evidence becomes available

Robustness of digitally modulated signal features against variation in HF noise model

<p>Abstract</p> <p>High frequency (HF) band has both military and civilian uses. It can be used either as a primary or backup communication link. Automatic modulation classification (AMC) is of an utmost importance in this band for the purpose of communications monitoring; e.g., signal intelligence and spectrum management. A widely used method for AMC is based on pattern recognition (PR). Such a method has two main steps: feature extraction and classification. The first step is generally performed in the presence of channel noise. Recent studies show that HF noise could be modeled by Gaussian or bi-kappa distributions, depending on day-time. Therefore, it is anticipated that change in noise model will have impact on features extraction stage. In this article, we investigate the robustness of well known digitally modulated signal features against variation in HF noise. Specifically, we consider temporal time domain (TTD) features, higher order cumulants (HOC), and wavelet based features. In addition, we propose new features extracted from the constellation diagram and evaluate their robustness against the change in noise model. This study is targeting 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, and 64QAM modulations, as they are commonly used in HF communications.</p

Differences in the Bacteriome of Smokeless Tobacco Products with Different Oral Carcinogenicity: Compositional and Predicted Functional Analysis

Smokeless tobacco (ST) products vary significantly in their oral carcinogenicity. Much is known about the differences in the chemical, but not the bacterial, constituents of these products. In this study, we explored the composition and function of the bacteriome in ST products from four countries using quantitative polymerase chain reaction (qPCR) and 16S rRNA-based next generation sequencing. The bacterial load (16S rRNA copies/gram) was lowest in Swedish snus (3.4 × 106) and highest in Yemeni shammah (6.6 × 1011). A total of 491 species-level taxa, many of which are potentially novel, belonging to 178 genera and 11 phyla were identified. Species richness and diversity were highest for Swedish snus and lowest for Yemeni shammah. Bacillus, Paenibacillus, and Oceanobacillus spp. were the most abundant in American snuff; species of Pseudomonas, Massilia, Propionibacterium, Puniceispirillum, and Gloeothece predominated in Swedish snus. In Sudanese toombak, Facklamia, Desemzia, Atopostipes, and Lysinibacillus spp. accounted for the majority of the bacteriome. Yemeni shammah exclusively contained Bacillus spp. Functional prediction by phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) showed that genes encoding cadmium/zinc and nickel transport systems were enriched in the presumptively “high carcinogenicity” products. The bacteriome of ST products thus differed qualitatively, quantitatively, and functionally. The relevance of these differences, particularly with respect to nickel and cadmium, to oral carcinogenesis warrants further investigation

Development, Characterization Optimization, and Assessment of Curcumin-Loaded Bioactive Self-Nanoemulsifying Formulations and Their Inhibitory Effects on Human Breast Cancer MCF-7 Cells

Curcumin (CUR) is an attractive polyphenol for its anti-inflammatory, antibacterial, antioxidant, and anticancer properties. Poor solubility in water and sensitivity against sunlight are the most challenging characteristics in the development of CUR for clinical use. The aim is to develop oral lipid-based bioactive self-nanoemulsifying drug delivery systems (Bio-SNEDDSs) for curcumin as a candidate for cancer therapy. Bio-SNEDDSs containing black seed oil, medium-chain mono- and diglycerides, and surfactants were prepared as CUR delivery vehicles. The morphology, droplet size, physical stability, encapsulation efficiency, risk of precipitation, lipid digestion, antioxidant activity, and antimicrobial activity were evaluated for the representative formulations. Finally, an MTT assay was performed on MCF-7 cells to determine the cytotoxic effect of the different formulations. The results showed lower droplet size (28.53 nm) and higher drug-loading (CUR 20 mg, thymoquinone 1.2 mg) for the representative Bio-SNEDDS (black seed oil/Imwitor 988/KolliphorEL (35/15/50) % w/w), along with a transparent appearance upon aqueous dilution. The dynamic dispersion and in-vitro lipolysis data proved that the Bio-SNEDDS was able to keep the CUR in a solubilized form in the gastrointestinal tract. From the antioxidant and antimicrobial studies, it was suggested that the Bio-SNEDDS had the highest activity for disease control. The MTT assay showed that the representative Bio-SNEDDS treatment led to a reduction of cell viability of MCF-7 cells compared to pure CUR and conventional SNEDDSs. A Bio-SNEDDS with elevated entrapment efficiency, antioxidant/antimicrobial activities, and an antiproliferative effect could be the best anticancer drug candidate for potential oral delivery

Proteomic Analysis and Molecular Characterization of Airborne Bioaerosols in Indoor and Outdoor Environment in Al-Qassim Region, Saudi Arabia

There are various sources of microbial air pollution which are seems to be a serious public health problem all over the world. For prevention and control of air pollution caused by airborne bacteria, rapid, sensitive and reliable detection techniques are required. Therefore, our study focused on using MALDI Biotyper (MBT) for rapid recognition of various microbial air pollutants. Five hundred air samples were collected from three localities, including Qassim University (150 samples), Al-Qassim hospitals (250 samples) and poultry slaughter houses (100 samples). All air samples were collected by impactor air sampler from the indoor and outdoor environment. All samples were cultivated on nutrient and blood agar media for two days and a total of 129 isolates were purified for proteomic analysis using MALDI Biotyper (MBT) then confirmed by quantitative polymerase chain reaction (qPCR). One hundred and nineteen (92.25%) isolates were identified by MBT at the species level with a log (score) value ≥2. 000 whereas; 10 (7.75%) isolates were detected at the genus level with score values ranged from 1.7000 to 1.999. The MBT was able to identify 93 (72.10%) gram-positive and 36 (27.90%) gram-negative bacterial isolates. The most common genera were Staphylococcus (n = 43, 33.33%), Escherichia (n = 16, 12.40%), Enterococcus (n = 15, 11.63%) and Bacillus (n = 15, 11.63%). Staphylococcus aureus and Escherichia coli were the most frequently identified species (n = 16, 12.40% for each). In general, we detected 53 (41.10%) various bacterial species in Al-Qassim hospitals, 41 (31.79%) in poultry slaughter houses and 35 (27.13%) in Qassim University. Throughout Al-Qassim region, the air was tainted by numerous environmental microorganisms, and the MBT was positively adjusted for their fast and accurate identification