A Graph Theoretic Approach for Analysis and Design of Community Wireless Networks

Community Wireless Networks (CWNs) have recently emerged as a top priority for many communities world-wide to access the information highway and bridge the digital divide. There are many factors that contribute to the development and the sustainability of a successful CWN. These factors include traditional technical network parameters in addition to several social and economic parameters. This paper proposes a two-graph model for describing CWNs. The proposed graph model uses well established graph concepts to depict the key factors needed to be addressed when analyzing and designing CWN. We show how the two graphs; the social network graph and the wireless network graph are used to model CWN factors. We also show how the proposed model was used in a case study to support the Omaha Wireless project. We argue that having such a quantitative model represents a significant step towards better understanding of CWN and advancing this timely research area

A Content-Based Pricing Model for Municipal and Community Wireless Networks

The escalation of municipal and community wireless networks (CWNs) has raised many questions about the most suitable business model, funding instrument, and service pricing policy for a specific community. Unlike traditional Internet service providers, these networks provide wireless Internet access for the purpose of boosting the social and economic development of the community at large. Therefore, such projects need customized business models and pricing policies in order to achieve these objectives. We propose a content-based pricing model where the price of wireless applications is an increasing function of the used bandwidth and a decreasing function of the provided packet delay. We used the Opnet simulation tool to validate the proposed pricing model. The simulation results show that network operators may charge users only for audio and video applications because of the high bandwidth they use compared to data applications. The proposed pricing solution considers the social and economic objectives of CWNs

Brown macroalgae as bio-indicators for heavy metals pollution of Al-Jubail coastal area of Saudi Arabia

Wastes from both industrial and domestic sources, as well as habitat destruction have a substantial impact on the coastal environments. It causes serious problems in many countries and for several seas and oceans which leads to the extinction of several plant and animal species. Many water resources are no longer suitable for drinking or for agriculture as a result of pollution. The main aim of this study was to investigate the efficiency of four brown macroalage as bioindicators for toxic heavy metals (manganese (Mn), copper (Cu), zinc (Zn), arsenite (As), cadmium (Cd), and lead (Pb)) along Al-jubail industrial city coast at Persian Gulf (Saudi Arabia). Brown macroalage samples were collected from three different sites in three time points, January, March and May, 2010. The four collected brown macroalgae were identified as Sargassum angustifolium, Sargassum boveanum, Sargassum latifolium, and Padina gymnospora. The algal samples were cleaned using sea water and distilled water, dried, and the concentrations of various toxic metals were determined. The average concentrations of Mn, Co, Ni and Cd were within the expected limits of un-contaminated areas. However, the results indicate the high level of Zn ion accumulation in all tested brown algae, showing highest concentration in S. angustifolium > P. gymnospora > S. latifolium > S. boveanum with highest Zn concentration of 991 ± 49.1, 988 ± 47.5, 980 ± 44.2, and 911 ± 39.7 µg g-1 dry weights, respectively. In addition, Cu was detected at high concentration of 92.1 ± 3.7 ìg g-1 dry weight in S. boveanum. These results clearly indicate the high pollution levels of Al-jubail industrial city coast with Zn and Cu toxic heavy metals, which is mostly due to uncontrolled disposal of industrial waste into coastal area. Furthermore, the consistency of Zn concentrations in all tested brown algae indicated the efficiency of the tested algae, including P. gymnospora, S. angustifolium, S. latifolium, and S. boveanum, for bioaccumulation and bio-monitoring studies of Zn.Key words: Brown algae, heavy metals, bio-indicators, Sargassum sp., Padina sp

Seismic Anisotropy and Subduction-Induced Mantle Fabrics beneath the Arabian and Nubian Plates Adjacent to the Red Sea

For most continental areas, the mechanisms leading to mantle fabrics responsible for the observed anisotropy remain ambiguous, partially due to the lack of sufficient spatial coverage of reliable seismological observations. Here we report the first joint analysis of shear-wave splitting measurements obtained at stations on the Arabian and Nubian Plates adjacent to the Red Sea. More than 1100 pairs of high-quality splitting parameters show dominantly N-S fast orientations at all 47 stations and larger-than-normal splitting times beneath the Afro-Arabian Dome (AAD). The uniformly N-S fast orientations and large splitting times up to 1.5 s are inconsistent with significant contributions from the lithosphere, which is about 50–80 km thick beneath the AAD and even thinner beneath the Red Sea. The results can best be explained by simple shear between the lithosphere and the asthenosphere associated with northward subduction of the African/Arabian Plates over the past 150 Ma

A new low molecular mass alkaline cyclodextrin glucanotransferase from Amphibacillus sp. NRC-WN isolated from an Egyptian soda lake

Background: Cyclodextrin glucanotransferase (CGTase) is one of the most industrially important enzymes used in the commercial production of cyclodextrins (CDs). Alkaliphilic bacteria have attracted much interest in the last few decades because of their ability to produce extracellular enzymes that are active and stable at high pH values. Here, we report the isolation of a new CGTase from alkaliphilic bacteria collected from Egyptian soda lakes and describe the purification and biochemical characterization of this CGTase. Results: Screening for CGTase-producing alkaliphilic bacteria from sediment and water samples collected from Egyptian soda lakes located in the Wadi Natrun valley resulted in the isolation of a potent CGTase-producing alkaliphilic bacterial strain, designated NRC-WN. Strain NRC-WN was belonging to genus Amplibacullus by 16S rDNA sequence analysis (similarity: ca. 98%). Among the tested nitrogen and carbon sources, peptone (0.15%, w/v) and soluble starch (0.4%, w/v) allowed maximal CGTase production by Amphibacillus sp. NRC-WN. CGTase was successfully purified from Amphibacillus sp. NRC-WN up to 159.7-fold through a combination of starch adsorption and anion exchange chromatography, resulting in a yield of 84.7%. SDS-PAGE analysis indicated that the enzyme was purified to homogeneity and revealed an estimated molecular mass of 36 kDa, which makes it one of the smallest CGTases reported in the literature. The purified enzyme exhibited maximum activity at 50oC and was stable up to 70oC, retaining 93% of its initial activity after treatment for 1 hr. Furthermore, Ca2+ ions (10 mM) significantly enhanced the thermal stability of the CGTase. The purified enzyme was active and stable over a wide pH range, showing maximal activity at pH 9.5. The enzyme was significantly stimulated by Zn2+, Ca2+ and Co2+ but was completely inhibited in the presence of Fe3+ and mercaptoethanol. The Km and Vmax values of the purified CGTase were estimated to be 0.0434 mg/ml and 3,333.3 mg \u3b2-CD/ml/min, respectively. \u3b2-CD was the predominant product of starch degradation by the Amphibacillus sp. NRC-WN CGTase, followed by \u3b1-and \u3b3-CDs. Conclusions: A new low molecular mass alkaline CGTase was purified from a newly identified alkaliphilic Amphibacillus sp. NRC-WN isolate from the Egyptian soda lakes. The enzyme showed promising thermal and pH stability and a high affinity toward starch as a natural substrate

Clinical and organizational factors associated with mortality during the peak of first COVID-19 wave: the global UNITE-COVID study

Purpose: To accommodate the unprecedented number of critically ill patients with pneumonia caused by coronavirus disease 2019 (COVID-19) expansion of the capacity of intensive care unit (ICU) to clinical areas not previously used for critical care was necessary. We describe the global burden of COVID-19 admissions and the clinical and organizational characteristics associated with outcomes in critically ill COVID-19 patients. Methods: Multicenter, international, point prevalence study, including adult patients with SARS-CoV-2 infection confirmed by polymerase chain reaction (PCR) and a diagnosis of COVID-19 admitted to ICU between February 15th and May 15th, 2020. Results: 4994 patients from 280 ICUs in 46 countries were included. Included ICUs increased their total capacity from 4931 to 7630 beds, deploying personnel from other areas. Overall, 1986 (39.8%) patients were admitted to surge capacity beds. Invasive ventilation at admission was present in 2325 (46.5%) patients and was required during ICU stay in 85.8% of patients. 60-day mortality was 33.9% (IQR across units: 20%–50%) and ICU mortality 32.7%. Older age, invasive mechanical ventilation, and acute kidney injury (AKI) were associated with increased mortality. These associations were also confirmed specifically in mechanically ventilated patients. Admission to surge capacity beds was not associated with mortality, even after controlling for other factors. Conclusions: ICUs responded to the increase in COVID-19 patients by increasing bed availability and staff, admitting up to 40% of patients in surge capacity beds. Although mortality in this population was high, admission to a surge capacity bed was not associated with increased mortality. Older age, invasive mechanical ventilation, and AKI were identified as the strongest predictors of mortality

Recent development of respiratory rate measurement technologies

Respiratory rate (RR) is an important physiological parameter whose abnormity has been regarded as an important indicator of serious illness. In order to make RR monitoring simple to do, reliable and accurate, many different methods have been proposed for such automatic monitoring. According to the theory of respiratory rate extraction, methods are categorized into three modalities: extracting RR from other physiological signals, RR measurement based on respiratory movements, and RR measurement based on airflow. The merits and limitations of each method are highlighted and discussed. In addition, current works are summarized to suggest key directions for the development of future RR monitoring methodologies

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

An Efficient Accounting Architecture for QoS-aware Internet Traffic

The widespread usage of Internet-based applications and the large diversity of these applications, particularly in terms of Quality of Service (QoS) requirements, necessitate developing a QoS-aware Internet accounting architecture. Developing such a architecture has grown to be increasingly essential for service pricing, cost recovery, resource management, and network analysis. This paper proposes an efficient Internet accounting architecture that employs various packet, flow, link, and end-to-end QoS parameters in a way that allows for a simple and practical implementation. With the help of the proposed architecture, a number of eBusiness applications and advanced network-tracking techniques can be efficiently developed