Routing protocols for self-organizing hierarchical ad-hoc wireless networks

—A novel self-organizing hierarchical architecture is proposed for improving the scalability properties of adhoc wireless networks. This paper focuses on the design and evaluation of routing protocols applicable to this class of hierarchical ad-hoc networks. The performance of a hierarchical network with the popular dynamic source routing (DSR) protocol is evaluated and compared with that of a conventional “flat” ad-hoc networks using an ns-2 simulation model. The results for an example sensor network scenario show significant capacity increases with the hierarchical architecture (∼4:1). Alternative routing metrics that account for energy efficiency are also considered briefly, and the effect on user performance and system capacity are given for a specific example

MiR-384 is associated with renal damage in lupus nephritis via regulation of TET3 expression

Purpose: To investigate the correlations between miR-384 expression and renal damage in lupus nephritis (LN).Methods: Lupus nephritis and normal tissues were collected during surgery. The relative miR-384 expression was evaluated by extracting RNA and performing quantitative real time PCR (qRT-PCR) assays. Expression of ten-eleven translocation (TET3) mRNA and protein were measured by qRT-PCR and western blotting, respectively. The 24-h urine protein, serum complement C3, and serum creatinine were determined using commercial enzyme-linked immunosorbent assay (ELISA) kits. TargetScan and luciferase assays were used to validate the binding site for miR-384 and its target mRNA. Relationships among miR-384, TET3, and renal damage were analyzed by Spearman rank-order correlation coefficients.Results: MiR-384 expression increased in LN tissues and was positively correlated with the activity index (AI) and chronicity index of LN, whereas miR-384 expression and serum complement C3 were negatively correlated. Positive correlations were observed between miR-384 expression and 24-h urine protein, serum creatinine, and systemic lupus erythematosus disease AI. TargetScan and luciferaseassays indicated that the TET3 3′-UTR was the direct target of miR-384. MiR-384 upregulation inhibited TET3 mRNA and protein  expression, and was negatively associated with renal damage in LN.Conclusion: MiR-384 upregulation contributes to renal damage in LN by targeting the 3′-UTR of TET3 mRNA, suggesting that miR-384 is a potential biomarker and therapeutic target in LN. Keywords: MiR-384, Renal damage, Lupus nephritis, Ten-eleven translocation, TET

Policy-Based Adaptive Routing in Mobile Ad Hoc Wireless Networks

Abstract-This paper investigates policy-based adaptive routing for mobile ad hoc networks (MANET's), in which routing metric, routing algorithm parameters and/or protocol selection can be controlled in response to observed performance and external service needs. We propose an adaptive routing framework which allows introduction of adjustable parameters and programmable routing modules. Control information is disseminated through the network to exchange state variables, and a global distributed policy manager is responsible for the adaptive operations at nodes of the network. The proposed architecture can support two types of adaptive mechanisms: the first involves switched selection between a set of routing protocols options or metrics, while the second is based on an integrated routing algorithm which incorporates adaptation of key network state parameters such as link speed or congestion. Example algorithms and simulation results are given, which show that adaptive routing help achieve the desired system performance under the dynamically changing network conditions

Preparation and biological activity of the monoclonal antibody against the second extracellular loop of the angiotensin II type 1 receptor

The current study was to prepare a mouse-derived antibody against the angiotensin II type 1 receptor (AT1-mAb) based on monoclonal antibody technology, to provide a foundation for research on AT1-AA-positive diseases. Balb/C mice were actively immunized with the second extracellular loop of the angiotensin II type 1 receptor (AT1R-ECII). Then, mouse spleen lymphocytes were fused with myeloma cells and monoclonal hybridomas that secreted AT1-mAb were generated and cultured, after which those in logarithmic-phase were injected into the abdominal cavity of mice to retrieve the ascites. Highly purified AT1-mAb was isolated from mouse ascites after injection with 1 × 107 hybridomas. A greater amount of AT1-mAb was purified from mouse ascites compared to the cell supernatant of hybridomas. AT1-mAb purified from mouse ascites constricted the thoracic aorta of mice and increased the beat frequency of neonatal rat myocardial cells via the AT1R, identical to the effects of AT1-AA extracted from patients’ sera. Murine blood pressure increased after intravenous injection of AT1-mAb via the tail vein. High purity and good biological activity of AT1-mAb can be obtained from mouse ascites after intraperitoneal injection of monoclonal hybridomas that secrete AT1-mAb. These data provide a simple tool for studying AT1-AA-positive diseases

Estimation of PM2.5 concentrations in China using a spatial back propagation neural network

Methods for estimating the spatial distribution of PM2.5 concentrations have been developed but have not yet been able to effectively include spatial correlation. We report on the development of a spatial back-propagation neural network (S-BPNN) model designed specifically to make such correlations implicit by incorporating a spatial lag variable (SLV) as a virtual input variable. The S-BPNN fits the nonlinear relationship between ground-based air quality monitoring station measurements of PM2.5, satellite observations of aerosol optical depth, meteorological synoptic conditions data and emissions data that include auxiliary geographical parameters such as land use, normalized difference vegetation index, elevation, and population density. We trained and validated the S-BPNN for both yearly and seasonal mean PM2.5 concentrations. In addition, principal components analysis was employed to reduce the dimensionality of the data and a grid of neural network models was run to optimize the model design. The S-BPNN was cross-validated against an analogous but SLV-free BPNN model using the coefficient of determination (R2) and root mean squared error (RMSE) as statistical measures of goodness of fit. The inclusion of the SLV led to demonstrably superior performance of the S-BPNN over the BPNN with R2 values increasing from 0.80 to 0.89 and with the RMSE decreasing from 8.1 to 5.8 μg/m3. The yearly mean PM2.5 concentration in China during the study period was found to be 41.8 μg/m3 and the model estimated spatial distribution was found to exceed Level 2 of the China Ambient Air Quality Standards (CAAQS) enacted in 2012 (>35 μg/m3) in more than 70% of the Chinese territory. The inclusion of spatial correlation upgrades the performance of conventional BPNN models and provides a more accurate estimation of PM2.5 concentrations for air quality monitoring

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

On the scalability of ad hoc wireless networks

This dissertation considers the problem of scaling ad hoc wireless networks now being applied to urban mesh and sensor networks scenarios. Ad hoc networks involve multi-hop communication which has inherent scaling problems in that throughput per node drops as the square root of the number of nodes in the network. We investigate mechanisms for improving performance and scalability of multi-hop wireless networks, with focus on system architecture and routing protocol aspects. First we propose a generalized multi-tier hierarchical hybrid network with three tiers of radio nodes: low-power end-user mobile nodes (MN) at the lowest tier, higher power radio forwarding nodes (FN) that support multi-hop routing at intermediate level, and wired access points (AP) at the highest level. We present an analytical model for the capacity of the proposed network and identify conditions on transmission range and node density for scalability to be maintained. From the derived upper and lower bounds, it is shown that the low-tier capacity increases linearly with the number of FN's, and that the high-tier capacity grows linearly with the number of AP's in the scaling region. The analytically obtained capacity results are validated with detailed system simulations for dense network scenarios. The simulation study also examines the allocation of separate channels to avoid the increased protocol overhead which arises in the single channel case. A heuristic distributed channel assignment algorithm is proposed to achieve conflict-free transmissions in the network. Next, we investigate cross-layer adaptive routing as another type of scaling mechanism. An adaptive routing framework, which allows introduction of adjustable parameters and programmable routing modules, is described. The proposed framework can support various cross-layer mechanisms including those based on integrated routing metrics that incorporate PHY and MAC information. We investigate a PHY/MAC aware routing metric (PARMA) which incorporates physical layer link speed and MAC congestion. Design and implementation of PARMA are outlined, and simulation results for typical multi-rate 802.11 ad hoc network scenarios show that PARMA helps improve throughput and decrease congestion by selecting paths with high bit-rate links while avoiding MAC congestion areas.Ph.D.Includes bibliographical references (p. 113-119)

Scalability and performance evaluation of hierarchical hybrid wireless networks

Abstract—This paper considers the problem of scaling ad hoc wireless networks now being applied to urban mesh and sensor network scenarios. Previous results have shown that the inherent scaling problems of a multihop “flat ” ad hoc wireless network can be improved by a “hybrid network ” with an appropriate proportion of radio nodes with wired network connections. In this work, we generalize the system model to a hierarchical hybrid wireless network with three tiers of radio nodes: low-power end-user mobile nodes (MNs) at the lowest tier, higher power radio forwarding nodes (FNs) that support multihop routing at intermediate level, and wired access points (APs) at the highest level. Scalability properties of the proposed three-tier hierarchical hybrid wireless network are analyzed, leading to an identification of the proportion of FNs and APs as well as transmission range required for linear increase in end-user throughput. In particular, it is shown analytically that in a three-tier hierarchical network with APs, FNs, and MNs, the low-tier capacity increases linearly with, and the high-tier capacity increases linearly with when = ( ) and =O (). This analytical result is validated via ns-2 simulations for an example dense network scenario, and the model is used to study scaling behavior and performance as a function of key parameters such as AP and FN node densities for different traffic patterns and bandwidth allocation at each tier of the network. Index Terms—Ad hoc network, hierarchical wireless network, hybrid network, mesh network, multihop routing, performance analysis, scalability, sensor network, simulation models