A logistic regression model for microalbuminuria prediction in overweight male population

Background: Obesity promotes progression to microalbuminuria and increases the risk of chronic kidney disease. Current protocols of screening microalbuminuria are not recommended for the overweight or obese.

Design and Methods: A cross-sectional study was conducted. The relationship between metabolic risk factors and microalbuminuria was investigated. A regression model based on metabolic risk factors was developed and evaluated for predicting microalbuminuria in the overweight or obese.

Results: The prevalence of MA reached up to 17.6% in Chinese overweight men. Obesity, hypertension, hyperglycemia and hyperuricemia were the important risk factors for microalbuminuria in the overweight. The area under ROC curves of the regression model based on the risk factors was 0.82 in predicting microalbuminuria, meanwhile, a decision threshold of 0.2 was found for predicting microalbuminuria with a sensitivity of 67.4% and specificity of 79.0%, and a global predictive value of 75.7%. A decision threshold of 0.1 was chosen for screening microalbuminuria with a sensitivity of 90.0% and specificity of 56.5%, and a global predictive value of 61.7%.

Conclusions: The prediction model was an effective tool for screening microalbuminuria by using routine data among overweight populations

Experimental Study of Pressure Loss in a 5 × 5–Rod Bundle With the Mixing Vane Spacer Grid

Axial and lateral pressure loss in a 5 × 5 rod–bundle with a split-type mixing vane spacer grid was experimentally measured using differential pressure transmitters at different sub-channel Reynolds numbers (Re) and orienting angles. The geometrical parameters of the 5 × 5–rod bundle are as follows: they have the same diameter (D = 9.5 mm) and pitch (p = 12.6 mm) as those of real fuel rods of a typical pressurized water reactor (PWR), with a sub-channel hydraulic diameter (D$_{h}$) of 11.78 mm. The characteristics and resistance models of pressure loss are discussed. The main axial pressure loss is caused by the spacer grid, and the spacer grid generates additional wall friction pressure loss downstream of the spacer grid. The lateral pressure loss shows strong correlations with orienting angles and distance from the spacer grid. The lateral pressure loss shows a sudden burst in the mixing vanes region and a slight augmentation at z = 3D$_{h}$. After 3D$_{h}$, the lateral pressure loss decays in an exponential way with distance from the spacer grid, and it becomes constant quickly at z = 20D$_{h}$

Rate effect of liquid infiltration into mesoporous materials

Rate effect of liquid infiltration in mesopores is associated with both liquid viscosity and the solid–liquid interfacial effect.</p

Cadenes de Markov aplicades als sistemes bonus-malus

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2018, Director: Josep Vives i Santa Eulàlia i M. Mercè Claramunt Bielsa[en] Insurance world is reinventing itself every time there are new technologies or people meet new needs. People want fair prices in accordance with their needs, but is it easy to give a price of a service that none knows how much could cost? This degree project studies Markov chains to apply them in Bonus-Malus Systems (BMS). Firstly, we will study how BMS works. Secondly, an analysis of some tools to compare different BMS will be carry out. Finally, we will see some doubts and questions that professionals face when they create and optimize it

Survivable Virtual Infrastructure Mapping in Virtualized Data Centers

In a virtualized data center, survivability can be enhanced by creating redundant VMs as backup for VMs such that after VM or server failures, affected services can be quickly switched over to backup VMs. To enable flexible and efficient resource management, we propose to use a service-aware approach in which multiple correlated Virtual Machines (VMs) and their backups are grouped together to form a Survivable Virtual Infrastructure (SVI) for a service or a tenant. A fundamental problem in such a system is to determine how to map each SVI to a physical data center network such that operational costs are minimized subject to the constraints that each VM’s resource requirements are met and bandwidth demands between VMs can be guaranteed before and after failures. This problem can be naturally divided into two sub-problems: VM Placement (VMP) and Virtual Link Mapping (VLM). We present a general optimization framework for this mapping problem. Then we present an efficient algorithm for the VMP subproblem as well as a polynomial-time algorithm that optimally solves the VLM subproblem, which can be used as subroutines in the framework. We also present an effective heuristic algorithm that jointly solves the two subproblems. It has been shown by extensive simulation results based on the real VM data traces collected from the green data center at Syracuse University that compared with the First Fit Descending (FFD) and single shortest path based baseline algorithm, both our VMP+VLM algorithm and joint algorithm significantly reduce the reserved bandwidth, and yield comparable results in terms of the number of active servers

Association between polymorphism of TGFA Taq I and cleft Lip and/or palate: a meta-analysis

BACKGROUND: Cleft lip and palate (CL/P) is one of the most common malformations in humans. Transforming growth factor alpha (TGFA) is a well characterized mammalian growth factor which might contribute to the development of CL/P. This meta-analysis aimed to summarize the association between the TGFA Taq I polymorphisms and CL/P. METHODS: We retrieved the relevant articles from PubMed, EMBASE, ISI Web of Science and SCOPUS databases. Studies were selected using specific inclusion and exclusion criteria. The odds ratios (ORs) and their 95% confidence intervals (95% CIs) were calculated to assess the association between TGFA Taq I polymorphism and CL/P risk. Meta-analyses were performed on the total data set and separately for the major ethnic groups, disease type and source of control. All analyses were performed using the Stata software. RESULTS: Twenty articles were included in the present analysis. There is a significant association between the TGFA Taq I polymorphism and CL/P (C1C2 vs C1C1: OR = 1.67, 95% CI = 1.23-2.25, C2C2 + C1C2 vs C1C1C1: OR = 1.52, 95% CI = 1.15-2.01; C2 vs C1:OR = 1.41, 95% CI = 1.12-1.78). Stratified analyses suggested that the TGFA Taq I polymorphism was significantly associated with CL/P in Caucasians (C1C2 vs C1C1: OR = 1.95, 95% CI = 1.34-2.86; C2C2 + C1C2 vs C1C1: OR = 1.68, 95% CI = 1.18-2.38; C2 vs V1: OR = 1.52, 95% CI = 1.14 -2.02). CONCLUSION: TGFA Taq I polymorphism may be associated with the risk of CL/P

Dual Auction Mechanism for Transaction Forwarding and Validation in Complex Wireless Blockchain Network

In traditional blockchain networks, transaction fees are only allocated to full nodes (i.e., miners) regardless of the contribution of forwarding behaviors of light nodes. However, the lack of forwarding incentive reduces the willingness of light nodes to relay transactions, especially in the energy-constrained Mobile Ad Hoc Network (MANET). This paper proposes a novel dual auction mechanism to allocate transaction fees for forwarding and validation behaviors in the wireless blockchain network. The dual auction mechanism consists of two auction models: the forwarding auction and the validation auction. In the forwarding auction, forwarding nodes use Generalized First Price (GFP) auction to choose transactions to forward. Besides, forwarding nodes adjust the forwarding probability through a no-regret algorithm to improve efficiency. In the validation auction, full nodes select transactions using Vickrey-Clarke-Grove (VCG) mechanism to construct the block. We prove that the designed dual auction mechanism is Incentive Compatibility (IC), Individual Rationality (IR), and Computational Efficiency (CE). Especially, we derive the upper bound of the social welfare difference between the social optimal auction and our proposed one. Extensive simulation results demonstrate that the proposed dual auction mechanism decreases energy and spectrum resource consumption and effectively improves social welfare without sacrificing the throughput and the security of the wireless blockchain network

Altering intracellular pH reveals the kinetic basis of intraburst gating in the CFTR Cl− channel

KEY POINTS: The cystic fibrosis transmembrane conductance regulator (CFTR), which is defective in the genetic disease cystic fibrosis (CF), forms a gated pathway for chloride movement regulated by intracellular ATP. To understand better CFTR function, we investigated the regulation of channel openings by intracellular pH. We found that short‐lived channel closures during channel openings represent subtle changes in the structure of CFTR that are regulated by intracellular pH, in part, at ATP‐binding site 1 formed by the nucleotide‐binding domains. Our results provide a framework for future studies to understand better the regulation of channel openings, the dysfunction of CFTR in CF and the action of drugs that repair CFTR gating defects. ABSTRACT: Cystic fibrosis transmembrane conductance regulator (CFTR) is an ATP‐gated Cl(−) channel defective in the genetic disease cystic fibrosis (CF). The gating behaviour of CFTR is characterized by bursts of channel openings interrupted by brief, flickery closures, separated by long closures between bursts. Entry to and exit from an open burst is controlled by the interaction of ATP with two ATP‐binding sites, sites 1 and 2, in CFTR. To understand better the kinetic basis of CFTR intraburst gating, we investigated the single‐channel activity of human CFTR at different intracellular pH (pH(i)) values. When compared with the control (pH(i) 7.3), acidifying pH(i) to 6.3 or alkalinizing pH(i) to 8.3 and 8.8 caused small reductions in the open‐time constant (τ(o)) of wild‐type CFTR. By contrast, the fast closed‐time constant (τ(cf)), which describes the short‐lived closures that interrupt open bursts, was greatly increased at pH(i) 5.8 and 6.3. To analyse intraburst kinetics, we used linear three‐state gating schemes. All data were satisfactorily modelled by the C(1) ↔ O ↔ C(2) kinetic scheme. Changing the intracellular ATP concentration was without effect on τ(o), τ(cf) and their responses to pH(i) changes. However, mutations that disrupt the interaction of ATP with ATP‐binding site 1, including K464A, D572N and the CF‐associated mutation G1349D all abolished the prolongation of τ(cf) at pH(i) 6.3. Taken together, our data suggest that the regulation of CFTR intraburst gating is distinct from the ATP‐dependent mechanism that controls channel opening and closing. However, our data also suggest that ATP‐binding site 1 modulates intraburst gating

Experience-driven Networking: A Deep Reinforcement Learning based Approach

Modern communication networks have become very complicated and highly dynamic, which makes them hard to model, predict and control. In this paper, we develop a novel experience-driven approach that can learn to well control a communication network from its own experience rather than an accurate mathematical model, just as a human learns a new skill (such as driving, swimming, etc). Specifically, we, for the first time, propose to leverage emerging Deep Reinforcement Learning (DRL) for enabling model-free control in communication networks; and present a novel and highly effective DRL-based control framework, DRL-TE, for a fundamental networking problem: Traffic Engineering (TE). The proposed framework maximizes a widely-used utility function by jointly learning network environment and its dynamics, and making decisions under the guidance of powerful Deep Neural Networks (DNNs). We propose two new techniques, TE-aware exploration and actor-critic-based prioritized experience replay, to optimize the general DRL framework particularly for TE. To validate and evaluate the proposed framework, we implemented it in ns-3, and tested it comprehensively with both representative and randomly generated network topologies. Extensive packet-level simulation results show that 1) compared to several widely-used baseline methods, DRL-TE significantly reduces end-to-end delay and consistently improves the network utility, while offering better or comparable throughput; 2) DRL-TE is robust to network changes; and 3) DRL-TE consistently outperforms a state-ofthe-art DRL method (for continuous control), Deep Deterministic Policy Gradient (DDPG), which, however, does not offer satisfying performance.Comment: 9 pages, 12 figures, paper is accepted as a conference paper at IEEE Infocom 201