A fuzzy data envelopment analysis approach for FMEA

We present a data envelopment analysis approach for determining ranking indices among failure modes in which the typical FMEA parameters are modeled as fuzzy sets. By this approach, inference rules of the IF THEN kind can be bypassed. The proposed approach is applied to a typical PWR auxiliary feedwater system. The results are compared to those obtained by means of: the risk priority numbers, pure fuzzy logic concepts, and finally the DEA-APGF (profiling of severity efficiency) approach. The results demonstrate the potential of the combination of fuzzy logic concepts and data envelopment analysis for this class of problems.     

Fatigue damage accumulation of cold expanded hole in aluminum alloys subjected to block loading

Fatigue damage accumulation of cold expanded hole in aluminum alloys used in land transportation components was investigated. Tests were carried out using pre-cracked SENT specimens and inserting an expanded hole at the crack tip. The degree of the cold expansion was chosen equal to 4.3%. Tests were performed in two and four block loading under constant amplitude. Two sequences were compared.The increasing and the decreasing magnitude were compared. The experimental results were compared to the damage calculated by the Miner's rule and a new simple fatigue damage indicator. This comparison shows that the ‘model of the damage stress’, which take into account of the loading history, yields a good estimation of the experimental results. Moreover, the error is minimized in comparison to the Miner's model.     

TPC-W e-commerce benchmark evaluation

Correctly interpreting benchmark results requires a basic knowledge of the synthetic workload the benchmark uses to determine how well it represents diverse e-commerce applications' real-world workloads. Factors that influence these results include the characteristics of the system under test, the procedures used to execute the tests, and the performance metrics the benchmark generates. TPC-W performs server evaluation in a controlled Internet e-commerce environment that simulates the activities of a business-oriented transactional Web server. The authors used experimental results from their TPC-W implementation to assess the benchmark's behavior, including its granularity and sensitivity to changes in workload and system parameters.     

Coordinated scheduling of production and delivery from multiple plants

This paper deals with the scheduling of orders and vehicle assignment for production and distribution planning in a scenario of no-wait, immediate delivery to the customer site. We first describe the problem and then present an integer programming model that maximizes the weighted value of the orders served. We consider a special case of the problem which can be solved in polinomial time by a minimum cost flow algorithm. Based on this approach we develop a heuristic procedure for the general case. Comparisons with an exact graph-based method attest that our heuristic produces good-quality solutions in short running times.     

Fracture mechanisms and failure processes at stiffener run-outs in polymer matrix composite stiffened elements

This paper describes the fractographic analyses of three stringer run-out designs which had been loaded to failure in tension. The main aims of the investigation were to deduce the failure processes in the elements, and to characterise the effect of local geometry of the stringer run-out on the failure process. The analysis showed that the critical failure mechanism in the elements was the development of +45° ply splitting at the skin surface, initially under mode I dominated intralaminar fracture. However, as these splits grew beneath the stringer foot, the mode II component increased. This led to mixed-mode delamination growth, extending parallel to the +45° ply, at the skin/adhesive interface. Subsequently, the delamination migrated through the skin via ply splits, ultimately reaching the interface between the second and third (−45°/0°) plies, in which it remained until catastrophic failure.

Extending and tapering the stringer foot led to shifting of the site of the +45° ply splitting; this was attributed to in-plane tensile stresses in the skin being inhibited in the modified designs. The reduced out-of-plane support on the stiffener foot in the modified designs led to an increase in the mode I component at the delamination from the stringer tip. It also led to an increase in the degree of multi-plane delamination growth. Based on the fractographic observations, recommendations for modelling the elements were suggested.     

The State‐of‐the‐Art in Predictive Visual Analytics

Predictive analytics embraces an extensive range of techniques including statistical modeling, machine learning, and data mining and is applied in business intelligence, public health, disaster management and response, and many other fields. To date, visualization has been broadly used to support tasks in the predictive analytics pipeline. Primary uses have been in data cleaning, exploratory analysis, and diagnostics. For example, scatterplots and bar charts are used to illustrate class distributions and responses. More recently, extensive visual analytics systems for feature selection, incremental learning, and various prediction tasks have been proposed to support the growing use of complex models, agent‐specific optimization, and comprehensive model comparison and result exploration. Such work is being driven by advances in interactive machine learning and the desire of end‐users to understand and engage with the modeling process. In this state‐of‐the‐art report, we catalogue recent advances in the visualization community for supporting predictive analytics. First, we define the scope of predictive analytics discussed in this article and describe how visual analytics can support predictive analytics tasks in a predictive visual analytics (PVA) pipeline. We then survey the literature and categorize the research with respect to the proposed PVA pipeline. Systems and techniques are evaluated in terms of their supported interactions, and interactions specific to predictive analytics are discussed. We end this report with a discussion of challenges and opportunities for future research in predictive visual analytics.     

The Flavonol Quercitrin Hinders GSK3 Activity and Potentiates the Wnt/β-Catenin Signaling Pathway

The Wnt/β-catenin signaling pathway dictates cell proliferation and differentiation during embryonic development and tissue homeostasis. Its deregulation is associated with many pathological conditions, including neurodegenerative disease, frequently downregulated. The lack of efficient treatment for these diseases, including Alzheimer’s disease (AD), makes Wnt signaling an attractive target for therapies. Interestingly, novel Wnt signaling activating compounds are less frequently described than inhibitors, turning the quest for novel positive modulators even more appealing. In that sense, natural compounds are an outstanding source of potential drug leads. Here, we combine different experimental models, cell-based approaches, neuronal culture assays, and rodent behavior tests with Xenopus laevis phenotypic analysis to characterize quercitrin, a natural compound, as a novel Wnt signaling potentiator. We find that quercitrin potentiates the signaling in a concentration-dependent manner and increases the occurrence of the Xenopus secondary axis phenotype mediated by Xwnt8 injection. Using a GSK3 biosensor, we describe that quercitrin impairs GSK3 activity and increases phosphorylated GSK3β S9 levels. Treatment with XAV939, an inhibitor downstream of GSK3, impairs the quercitrin-mediated effect. Next, we show that quercitrin potentiates the Wnt3a-synaptogenic effect in hippocampal neurons in culture, which is blocked by XAV939. Quercitrin treatment also rescues the hippocampal synapse loss induced by intracerebroventricular injection of amyloid-β oligomers (AβO) in mice. Finally, quercitrin rescues AβO-mediated memory impairment, which is prevented by XAV939. Thus, our study uncovers a novel function for quercitrin as a Wnt/β-catenin signaling potentiator, describes its mechanism of action, and opens new avenues for AD treatments.     

Revealing the Changes in Saliva and Serum Proteins of Pigs with Meningitis Caused by Streptococcus Suis: A Proteomic Approach

Meningitis due to Streptococcus suis causes high mortality and morbidity on pig farms and has increasing zoonotic potential worldwide. Saliva proteome analysis would potentially be useful in elucidating pathophysiological changes and mining for new biomarkers to diagnose and monitor S. suis infection. The objective of this study was to investigate the changes in the salivary and serum proteome profile of piglets with meningitis. The LC-MS/MS TMT proteomic approach was used to analyze saliva and serum samples from 20 male piglets: 10 with meningitis and 10 healthy. In saliva, 11 proteins had higher and 10 had lower relative abundance in piglets with meningitis. The proteins with the highest relative abundance were metavinculin (VCL) and desmocollin-2 (DSC2). Adenosine deaminase (ADA) was selected for validation using a spectrophotometric assay and demonstrated excellent performance in the differentiation between healthy and pigs with meningitis due to S. suis. In serum, the most protruding changes occurred for one SERPIN and haptoglobin (HP). In saliva and serum, the highest number of proteins with altered abundance were linked, via the enrichment analysis, with platelet and neutrophil pathways. Overall, meningitis caused by S. suis resulted in specific proteome changes in saliva and serum, reflecting different pathophysiological mechanisms, and marking new potential biomarkers for this infection.     

In Vitro Study of the Blood–Brain Barrier Transport of Natural Compounds Recovered from Agrifood By-Products and Microalgae

Agrifood by-products and microalgae represent a low-cost and valuable source of bioactive compounds with neuroprotective properties. However, the neuroprotective effectiveness of therapeutic molecules can be limited by their capacity to cross the blood–brain barrier (BBB) and reach the brain. In this research, various green extracts from Robinia pseudoacacia (ASFE), Cyphomandra betacea (T33), Coffea arabica (PPC1), Olea europaea L., (OL-SS), Citrus sinensis (PLE100) by-products and from the microalgae Dunaliella salina (DS) that have demonstrated in vitro neuroprotective potential were submitted to an in vitro BBB permeability and transport assay based on an immortalized human brain microvascular endothelial cells (HBMEC) model. Toxicity and BBB integrity tests were performed, and the transport of target bioactive molecules across the BBB were evaluated after 2 and 4 h of incubation using gas and liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (GC/LC-Q-TOF-MS). The HBMEC-BBB transport assay revealed a high permeability of representative neuroprotective compounds, such as mono- and sesquiterpenoids, phytosterols and some phenolic compounds. The obtained results from the proposed in vitro BBB cellular model provide further evidence of the neuroprotective potential of the target natural extracts, which represent a promising source of functional ingredients to be transferred into food supplements, food additives, or nutraceuticals with scientifically supported neuroprotective claims.