Design & investigation of 10x10 gbit/s MDM over hybrid FSO link under different weather conditions and fiber to the home

In this paper, we design and investigate 10-channels of mode division multiplexer (MDM) over hybrid free-space optics (FSO) link in several weather conditions to achieve the maximum possible medium range and fiber to the home (FTTH) for high bandwidth access networks. System capacity can be effectively increased with the use of MDM over hybrid FSO-FTTH. In this study, a 10-channel MDM over FSO-FTTH system has been analyzed in different weather conditions that operate at 1550 nm wavelength. The simulated system has transmitted 100 Gbit/s up for a distance of 3200 meters FSO in superbly clear weather condition. It also transmitted 100 Gbit/s up for a distance of 650 meters FSO during heavy rain. The validation of this study is measures based on eye diagrams bit-error rates (BER) that have been analyzed

Studies on vascular response to full superantigens and superantigen derived peptides:Possible production of novel superantigen variants with less vasodilation effect for tolerable cancer immunotherapy

Superantigens (SAgs) are a class of antigens that cause non-specific activation of T-cells resulting in polyclonal T cell activation and massive cytokine release and causing symptoms similar to sepsis, e.g. hypotension and subsequent hyporeactivity. We investigated the direct effect of SAgs on vascular tone using two recombinant SAgs, SEA and SPEA. The roles of Nitric Oxide (NO) and potentially hyperpolarization, which is dependent on the K + channel activation, were also explored. The data show that SEA and SPEA have direct vasodilatory effects that were in part NO-dependent, but completely dependent on activation of K + channels. Our work also identified the functional regions of one of the superantigens, SPEA, that are involved in causing the vasodilation and possible hypotension. A series of 20 overlapping peptides, spanning the entire sequence of SPEA, were designed and synthesized. The vascular response of each peptide was measured, and the active peptides were identified. Our results implicate the regions, (61–100), (101–140) and (181–220) which cause the vasodilation and possible hypotension effects of SPEA. The data also shows that the peptide 181–220 exert the highest vasodilation effect. This work therefore, demonstrates the direct effect of SAgs on vascular tone and identify the active region causing this vasodilation. We propose that these three peptides could be effective novel antihypertensive drugs. We also overexpressed, in E.coli, four superantigens from codon optimized genes

Production of "biobetter" variants of glucarpidase with enhanced enzyme activity

Glucarpidase, also known as carboxypeptidase G(2), is a Food and Drug Administration-approved enzyme used in targeted cancer strategies such as antibody-directed enzyme prodrug therapy (ADEPT). It is also used in drug detoxification when cancer patients have excessive levels of the anti-cancer agent methotrexate. The application of glucarpidase is limited by its potential immunogenicity and limited catalytic efficiency. To overcome these pitfalls, mutagenesis was applied to the glucarpidase gene of Pseudomonas sp. strain RS-16 to isolate three novels "biobetter" variants with higher specific enzyme activity. DNA sequence analysis of the genes for the variants showed that each had a single point mutation, resulting in the amino acid substitutions: I100 T, G123S and T239 A. K-m, V-max and K-cat measurements confirmed that each variant had increased catalytic efficiency relative to wild type glucarpidase. Additionally, circular dichroism studies indicated that they had a higher alpha-helical content relative to the wild type enzyme. However, three different software packages predicted that they had reduced protein stability, which is consistent with having higher activities as a tradeoff. The novel glucarpidase variants presented in this work could pave the way for more efficient drug detoxification and might allow dose escalation during chemotherapy. They also have the potential to increase the efficiency of ADEPT and to reduce the number of treatment cycles, thereby reducing the risk that patients will develop antibodies to glucarpidase

Present Limits to Heat-Adaptability in Corals and Population-Level Responses to Climate Extremes

Climate change scenarios suggest an increase in tropical ocean temperature by 1–3°C by 2099, potentially killing many coral reefs. But Arabian/Persian Gulf corals already exist in this future thermal environment predicted for most tropical reefs and survived severe bleaching in 2010, one of the hottest years on record. Exposure to 33–35°C was on average twice as long as in non-bleaching years. Gulf corals bleached after exposure to temperatures above 34°C for a total of 8 weeks of which 3 weeks were above 35°C. This is more heat than any other corals can survive, providing an insight into the present limits of holobiont adaptation. We show that average temperatures as well as heat-waves in the Gulf have been increasing, that coral population levels will fluctuate strongly, and reef-building capability will be compromised. This, in combination with ocean acidification and significant local threats posed by rampant coastal development puts even these most heat-adapted corals at risk. WWF considers the Gulf ecoregion as “critically endangered”. We argue here that Gulf corals should be considered for assisted migration to the tropical Indo-Pacific. This would have the double benefit of avoiding local extinction of the world's most heat-adapted holobionts while at the same time introducing their genetic information to populations naïve to such extremes, potentially assisting their survival. Thus, the heat-adaptation acquired by Gulf corals over 6 k, could benefit tropical Indo-Pacific corals who have <100 y until they will experience a similarly harsh climate. Population models suggest that the heat-adapted corals could become dominant on tropical reefs within ∼20 years

Social Internet of Things and New Generation Computing -- A Survey

Social Internet of Things (SIoT) tries to overcome the challenges of Internet of Things (IoT) such as scalability, trust and discovery of resources, by inspiration from social computing. This survey aims to investigate the research done on SIoT from two perspectives including application domain and the integration to the new computing models. For this, a two-dimensional framework is proposed and the projects are investigated, accordingly. The first dimension considers and classifies available research from the application domain perspective and the second dimension performs the same from the integration to new computing models standpoint. The aim is to technically describe SIoT, to classify related research, to foster the dissemination of state-of-the-art, and to discuss open research directions in this field.Comment: IoT, Social computing, Surve

Third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007) in Iran: methods and results on prevalence of diabetes, hypertension, obesity, central obesity, and dyslipidemia

<p>Abstract</p> <p>Background</p> <p>The burden of non-communicable diseases is rising globally. This trend seems to be faster in developing countries of the Middle East. In this study, we presented the latest prevalence rates of a number of important non-communicable diseases and their risk factors in the Iranian population.</p> <p>Methods</p> <p>The results of this study are extracted from the third national Surveillance of Risk Factors of Non-Communicable Diseases (SuRFNCD-2007), conducted in 2007. A total of 5,287 Iranian citizens, aged 15–64 years, were included in this survey. Interviewer-administered questionnaires were applied to collect the data of participants including the demographics, diet, physical activity, smoking, history of hypertension, and history of diabetes. Anthropometric characteristics were measured and serum biochemistry profiles were determined on venous blood samples. Diabetes (fasting plasma glucose ≥ 126 mg/dl), hypertension (systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or use of anti-hypertensive drugs), dyslipidemia (hypertriglyceridemia: triglycerides ≥ 150 mg/dl, hypercholesterolemia: total cholesterol ≥ 200 mg/dl), obesity (body mass index ≥ 30 kg/m²), and central obesity (waist circumference ≥ 80 cm in females and ≥ 94 cm in males) were identified and the national prevalence rates were estimated.</p> <p>Results</p> <p>The prevalence of diabetes, hypertension, obesity, and central obesity was 8.7% (95%CI = 7.4–10.2%), 26.6% (95%CI = 24.4–28.9%), 22.3% (95%CI = 20.2–24.5%), and 53.6% (95%CI = 50.4–56.8%), respectively. The prevalence of hypertriglyceridemia and hypercholesterolemia was 36.4% (95%CI = 34.1–38.9%) and 42.9% (95%CI = 40.4–45.4%), respectively. All of the mentioned prevalence rates were higher among females (except hypertriglyceridemia) and urban residents.</p> <p>Conclusion</p> <p>We documented a strikingly high prevalence of a number of chronic non-communicable diseases and their risk factors among Iranian adults. Urgent preventive interventions should be implemented to combat the growing public health problems in Iran.</p

Artificial intelligence for photovoltaic systems

Photovoltaic systems have gained an extraordinary popularity in the energy generation industry. Despite the benefits, photovoltaic systems still suffer from four main drawbacks, which include low conversion efficiency, intermittent power supply, high fabrication costs and the nonlinearity of the PV system output power. To overcome these issues, various optimization and control techniques have been proposed. However, many authors relied on classical techniques, which were based on intuitive, numerical or analytical methods. More efficient optimization strategies would enhance the performance of the PV systems and decrease the cost of the energy generated. In this chapter, we provide an overview of how Artificial Intelligence (AI) techniques can provide value to photovoltaic systems. Particular attention is devoted to three main areas: (1) Forecasting and modelling of meteorological data, (2) Basic modelling of solar cells and (3) Sizing of photovoltaic systems. This chapter will aim to provide a comparison between conventional techniques and the added benefits of using machine learning methods

Mortality and disability-adjusted life years in North Africa and Middle East attributed to kidney dysfunction : a systematic analysis for the Global Burden of Disease Study 2019

The authors would like to thank the hard work of the staff of the Institute for Health Metrics and Evaluation (IHME) for providing the best possible epidemiologic estimation of diseases in almost all regions and countries of the world, trying to reduce and eliminate poverty of knowledge and information about the diseases globally. Also, the core team authors sincerely thank all the collaborators of the GBD 2019 study who contributed to this study by providing data or a precise review of the manuscript. Publisher Copyright: © The Author(s) 2023. Published by Oxford University Press on behalf of the ERA. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Peer reviewe