The nonorthogonal estimator

Classical fractional factorial designs yield biased estimates of a set of parameters when aliased parameters are nonzero. In the early 1960s Ehrenfeld and Zacks constructed Randomization Procedures I and II to remove this bias from estimation of a subset of parameters of a full factorial experiment. The subset of parameters to be estimated using either of these randomization procedures must have a certain group structure and the sample size must be a multiple of the group size. In this paper, we discuss the nonorthogonal estimator which removes these restrictions while producing unbiased estimates in the case of a two-level experiment. Examples are provided.Fractional replications Unbiased estimators Randomized estimators

Convex Neural Networks Based Reinforcement Learning for Load Frequency Control under Denial of Service Attacks

With the increase in the complexity and informatization of power grids, new challenges, such as access to a large number of distributed energy sources and cyber attacks on power grid control systems, are brought to load-frequency control. As load-frequency control methods, both aggregated distributed energy sources (ADES) and artificial intelligence techniques provide flexible solution strategies to mitigate the frequency deviation of power grids. This paper proposes a load-frequency control strategy of ADES-based reinforcement learning under the consideration of reducing the impact of denial of service (DoS) attacks. Reinforcement learning is used to evaluate the pros and cons of the proposed frequency control strategy. The entire evaluation process is realized by the approximation of convex neural networks. Convex neural networks are used to convert the nonlinear optimization problems of reinforcement learning for long-term performance into the corresponding convex optimization problems. Thus, the local optimum is avoided, the optimization process of the strategy utility function is accelerated, and the response ability of controllers is improved. The stability of power grids and the convergence of convex neural networks under the proposed frequency control strategy are studied by constructing Lyapunov functions to obtain the sufficient conditions for the steady states of ADES and the weight convergence of actor–critic networks. The article uses the IEEE14, IEEE57, and IEEE118 bus testing systems to verify the proposed strategy. Our experimental results confirm that the proposed frequency control strategy can effectively reduce the frequency deviation of power grids under DoS attacks

Expression of WIF-1 in inflammatory bowel disease

The WNT/β-catenin cellular network has been extensively studied in numerous diseases including inflammatory bowel disease (IBD). IBD is a condition that increases the risk of developing colorectal cancer. WIF-1 is an inhibitory protein that acts by blocking the interactions of WNT with its receptor complex, thus leading to downregulation of end products of this pathway. While WIF-1 has been characterized in several cancers, its relationship with IBD has yet to be elucidated. In this study, the expression of WIF-1 in patients with IBD was analyzed in order to provide insights into the pathophysiology and rationale for alternative therapies. Biopsies of both normal and inflamed colonic mucosa from patients with Crohn’s disease or ulcerative colitis were histologically examined for the degree of morphologic changes, immune cell infiltration and presence of WIF-1 through immunohistochemistry. No differences were observed in WIF-1 expression linked to a particular condition, but WIF-1 stain was significantly enhanced in the crypts and lamina propria as inflammation increased in biopsies from patients with both, ulcerative colitis and Crohn’s disease. These findings could give guidance to new therapeutic applications of the WNT/β-catenin system and WIF-1 in IBD

Analysis of the genetic component of systemic sclerosis in Iranian and Turkish populations through a genome-wide association study

Objectives. SSc is an autoimmune disease characterized by alteration of the immune response, vasculopathy and fibrosis. Most genetic studies on SSc have been performed in European-ancestry populations. The aim of this study was to analyse the genetic component of SSc in Middle Eastern patients from Iran and Turkey through a genome-wide association study.Methods. This study analysed data from a total of 834 patients diagnosed with SSc and 1455 healthy controls from Iran and Turkey. DNA was genotyped using high-throughput genotyping platforms. The data generated were imputed using the Michigan Imputation Server, and the Haplotype Reference Consortium as a reference panel. A meta-analysis combining both case-control sets was conducted by the inverse variance method.Results. The highest peak of association belonged to the HLA region in both the Iranian and Turkish populations. Strong and independent associations between the classical alleles HLA-DRB1*11:04 [P = 2.10 x 10(-24), odds ratio (OR) = 3.14] and DPB1*13:01 (P = 5.37 x 10(-14), OR = 5.75) and SSc were observed in the Iranian population. HLA-DRB1*11:04 (P = 4.90 x 10(-11), OR = 2.93) was the only independent signal associated in the Turkish cohort. An omnibus test yielded HLA-DRB1 58 and HLA-DPB1 76 as relevant amino acid positions for this disease. Concerning the meta-analysis, we also identified two associations close to the genome-wide significance level outside the HLA region, corresponding to IRF5-TNPO3 rs17424921-C (P = 1.34 x 10(-7), OR = 1.68) and NFKB1 rs4648133-C (P = 3.11 x 10(-7), OR = 1.47).Conclusion. We identified significant associations in the HLA region and suggestive associations in IRF5-TNPO3 and NFKB1 loci in Iranian and Turkish patients affected by SSc through a genome-wide association study and an extensive HLA analysis