Bayesian estimation based on vague lifetime data

In Classical Bayesian approach, estimation of lifetime data usually is dealing with precise information. However, in real world, some informations about an underlying system might be imprecise and represented in the form of vague quantities. In these situations, we need to generalize classical methods to vague environment for studying and analyzing the systems of interest. In this paper, we propose the Bayesian estimation of failure rate and mean time to failure based on vague set theory in the case of complete and censored data sets. To employ the Bayesian approach, model parameters are assumed to be vague random variables with vague prior distributions. This approach will be used to induce the vague Bayes estimate of failure rate and mean time to failure by introducing and applying a theorem called “Resolution Identity” for vague sets. In order to evaluate the membership degrees of vague Bayesian estimate for these quantities, a computational procedure is investigated. In the proposed method, the original problem is transformed into a nonlinear programming problem which is then divided into eight subproblems to simplifying computations.     

A co-classification approach to learning from multilingual corpora

We address the problem of learning text categorization from a corpus of multilingual documents. We propose a multiview learning, co-regularization approach, in which we consider each language as a separate source, and minimize a joint loss that combines monolingual classification losses in each language while ensuring consistency of the categorization across languages. We derive training algorithms for logistic regression and boosting, and show that the resulting categorizers outperform models trained independently on each language, and even, most of the times, models trained on the joint bilingual data. Experiments are carried out on a multilingual extension of the RCV2 corpus, which is available for benchmarking.     

A theory of mode of action of azolylalkylquinolines as DNA binding agents using automated flexible ligand docking

Azolylalkylquinolines (AAQs) are a family of quinolines with varying degrees of cytotoxic activity (comparable or moderately superior to adriamycin in some cases) developed in the past decade in our group where their exact mode of action is still unclear. In this study the most probable DNA binding mode of AAQs was investigated employing a novel flexible ligand docking approach by using AutoDock 3.0. Forty-nine AAQs with known experimental inhibitory activity were docked onto d(CGCAAATTTGCG)(2), d(CGATCG)(2) and d(CGCG)(2) oligonucleotides retrieved from the Protein Data Bank (PDB IDs: 102D, 1D12 and 1D32, respectively) as the representatives of the three plausible models of interactions between chemotherapeutic agents and DNA (groove binding, groove binding plus intercalation and bisintercalation, respectively). Good correlation (r(2)=0.64) between calculated binding energies and experimental inhibitory activities was obtained using groove binding plus intercalation model for phenyl-azolylalkylquinoline (PAAQ) series. Our findings show that the most probable mode of action of PAAQs as DNA binding agents is via intercalation of quinolinic moiety between CG base pairs with linker chain and azole moiety binding to the minor groove.     

Cluster Size Optimization in Sensor Networks with Decentralized Cluster-Based Protocols

Network lifetime and energy-efficiency are viewed as the dominating considerations in designing cluster-based communication protocols for wireless sensor networks. This paper analytically provides the optimal cluster size that minimizes the total energy expenditure in such networks, where all sensors communicate data through their elected cluster heads to the base station in a decentralized fashion. LEACH, LEACH-Coverage, and DBS comprise three cluster-based protocols investigated in this paper that do not require any centralized support from a certain node. The analytical outcomes are given in the form of closed-form expressions for various widely-used network configurations. Extensive simulations on different networks are used to confirm the expectations based on the analytical results. To obtain a thorough understanding of the results, cluster number variability problem is identified and inspected from the energy consumption point of view.     

Association between antiinflammatory cytokine,IL‐10, and sleep quality in patients on maintenance hemodialysis

Elevated proinflammatory cytokines have been attributed to poor sleep quality in patients receiving hemodialysis. This is the first investigation about the relationship between sleep quality and circulating levels of antiinflammatory markers in these patients. A total of 72 patients who were receiving maintenance hemodialysis were enrolled in this cross‐sectional study. The Pittsburgh Sleep Quality Index (PSQI) was used to measure sleep quality. Patients were divided into two groups: good sleepers (PSQI score < 5) and poor sleepers (PSQI score ≥ 5). Assessments were made for serum biochemical parameters (albumin, parathyroid hormone), inflammatory (interleukin [IL]‐6, tumor necrosis factor‐alpha [TNF‐α], and high‐sensitivity c‐reactive protein [hs‐CRP] ) and antiinflammatory (IL‐10) markers. Fifty‐four patients (75%) were classified as poor sleepers. Poor sleepers showed significantly lower levels of serum IL‐10 and higher serum triglyceride and parathyroid hormone concentrations. These patients were more likely to have more comorbidities. The global PSQI score was significantly correlated with serum IL‐10 (p = 0.03) and triglyceride levels (p = 0.01). Multivariate logistic regression analysis showed a direct correlation between PSQI and having comorbidities (p = 0.011, odds ratio [OR] = 3.918; confidence interval 95% [CI] = 2.742–19.031), between PSQI and serum triglyceride (p = 0.027, OR = 1.027 [95% CI = 1.007–1.048] ), and an inverse correlation between PSQI and serum IL‐10 level (p = 0.021, OR = 0.424 [95% CI = 0.195–0.922]). Reduced circulating levels of the antiinflammatory cytokine IL‐10 were significantly associated with poor sleep quality in hemodialysis patients. Factors including serum IL‐10 and triglyceride concentrations and having comorbidities may predict patients prone to poor sleep quality.     

Joint optimisation of transmission and waiting times in cognitive radio

Transmission time optimisation is one of the key considerations of cognitive network design. There are many studies in cognitive radio networks (CRNs) focusing on finding the best transmission time for secondary users (SUs) to maximise transmission or energy efficiency. While longer sensing duration leads to a higher sensing accuracy and causes less interference, the SU spends less time for transmission and more energy on sensing spectrum. On the other hand, when the transmission duration becomes longer, although the SU has more opportunities to access the channel, it may encounter higher interference due to primary user (PU) returns and the probability of collision becomes higher. In this article, in a decentralised slotted protocol for CRN, the SU spectrum access is proved as a renewal process, then the interference due to PU return during SU transmission, the missed opportunities due to waiting for the channel to become idle and the energy consumed by the SU in the whole spectrum access process including idling energy, transmission energy and sensing energy consumption are formulated and integrated into newly defined efficiency to obtain the optimum transmission time and waiting time.     

Cardiac motion and deformation recovery from MRI: a review

Magnetic resonance imaging (MRI) is a highly advanced and sophisticated imaging modality for cardiac motion tracking and analysis, capable of providing 3D analysis of global and regional cardiac function with great accuracy and reproducibility. In the past few years, numerous efforts have been devoted to cardiac motion recovery and deformation analysis from MR image sequences. Many approaches have been proposed for tracking cardiac motion and for computing deformation parameters and mechanical properties of the heart from a variety of cardiac MR imaging techniques. In this paper, an updated and critical review of cardiac motion tracking methods including major references and those proposed in the past ten years is provided. The MR imaging and analysis techniques surveyed are based on cine MRI, tagged MRI, phase contrast MRI, DENSE, and SENC. This paper can serve as a tutorial for new researchers entering the field.     

The Effect of Silicon Percentage and Shot Peening Operation on Mechanical Properties of Hadfield Steel Containing 17% Manganese

Protection of Metals and Physical Chemistry of Surfaces - The present study examines the effect of shot peening on the wear behavior of austenitic high- manganese steels in both low and high...     

Measurements of jet flows impinging into a channel containing a rod bundle using dynamic PIV

In this investigation, full-field velocity profiles of jet flows impinging into a rod bundle were measured using Particle Image Velocimetry (PIV) technique in a facility with Matched-Index of Refraction. The test section consisted of a 1 m long rectangular channel with a cross-sectional area of 76.2 × 76.2 mm². Water was pumped through either single or double jets located on the top wall of the channel. The Reynolds numbers of the inlet jets were varied from 4470 to 13,400. Inside the channel adjacent to the inlet jets, a rod bundle was configured with 29 staggered tubes of 10.67 mm outside diameter (O.D.). The time-resolved velocity fields were obtained for regions within the rod bundle from which the vorticity fields and the turbulent characteristics of those regions were calculated. The results are useful for developing new models to help predict the flow patterns in the lower plenum of Gas Cooled Reactors.     

Postpartum depression and vitamin D: A systematic review

Postpartum depression (PPD) is a prevalent mood disorder estimated to affect 20%–40% of women worldwide after childbirth. In recent studies, the effect of vitamin D on prevention of mood disorders and depression has been investigated, but it is still unclear how vitamin D may affect PPD. The evidence on the relevance between vitamin D deficiency and PPD is inconsistent, and assessment of the recent literature has not previously been carried out. Moreover, there are few clinical studies on PPD and vitamin D supplementation. Five studies have so far assessed the relationship between the levels of vitamin D and PPD. Findings from cohort studies suggest that vitamin-D deficiency is related to the incidence of PPD and vitamin D may play a significant role in the recovery of women with PPD, but it is uncertain whether these actions are the effect of vitamin D on the function of hypothalamic-pituitary-adrenal (HPA) axis, the levels of estradiol, serotonin, pro-inflammatory cytokines, and/or of other mechanisms involved in PPD.