A knowledge-based decision support system for the management of parts and tools in FMS

Flexible manufacturing systems (FMS) are very complex systems with large part, tool, and information flows. The aim of this work is to develop a knowledge-based decision support system (KBDSS) for short-term scheduling in FMS strongly influenced by the tool management concept to provide a significant operational control tool for a wide range of machining cells, where a high level of flexibility is demanded, with benefits of more efficient cell utilization, greater tool flow control, and a dependable way of rapidly adjusting short-term production requirements. Development of a knowledge-based system to support the decision making process is justified by the inability of decision makers to diagnose efficiently many of the malfunctions that arise at machine, cell, and entire system levels during manufacturing. In this context, this paper proposes three knowledge-based models to ease the decision making process: an expert production scheduling system, a knowledge-based tool management decision support systems, and a tool management fault diagnosis system. The entire system has been created in a hierarchical manner and comprises more than 400 rules. The expert system (ES) was implemented in a commercial expert system shell, Knowledge Engineering System (KES) Production System (PS).     

Hypergraph Models and Algorithms for Data-Pattern-Based Clustering

In traditional approaches for clustering market basket type data, relations among transactions are modeled according to the items occurring in these transactions. However, an individual item might induce different relations in different contexts. Since such contexts might be captured by interesting patterns in the overall data, we represent each transaction as a set of patterns through modifying the conventional pattern semantics. By clustering the patterns in the dataset, we infer a clustering of the transactions represented this way. For this, we propose a novel hypergraph model to represent the relations among the patterns. Instead of a local measure that depends only on common items among patterns, we propose a global measure that is based on the cooccurences of these patterns in the overall data. The success of existing hypergraph partitioning based algorithms in other domains depends on sparsity of the hypergraph and explicit objective metrics. For this, we propose a two-phase clustering approach for the above hypergraph, which is expected to be dense. In the first phase, the vertices of the hypergraph are merged in a multilevel algorithm to obtain large number of high quality clusters. Here, we propose new quality metrics for merging decisions in hypergraph clustering specifically for this domain. In order to enable the use of existing metrics in the second phase, we introduce a vertex-to-cluster affinity concept to devise a method for constructing a sparse hypergraph based on the obtained clustering. The experiments we have performed show the effectiveness of the proposed framework.     

Power Flattening in ARIES-RS Fusion Breeder Reactor Using Mixed Fuels

This study presents the possibility of the power flattening in the ARIES-RS breeder reactor using mixed (Th,U)C or (Th,U)N fuels. Two different types of mixing, namely, homogeneous mixing (HM) and linear mixing (LM) were used to investigate the uniformity of fission power distribution through the fuel zone. In HM, fraction of uranium content were kept constant in all rows of the fuel zone whereas, in LM the fraction of the uranium were linearly increased from the first to last fuel row in the fuel zone. Neutron transport calculations were performed with the aid of the SCALE4.3 system by solving the Boltzmann transport equation with the XSDRNPM code in 238 neutron groups and a S₈–P₃ approximation. Flat fission power distribution was maintained successfully for the blanket using linearly mixed fuels. However, the fission density profile was not uniform in the blanket with homogeneously mixed fuels. It decreased exponentially form the 1st to 10th fuel row.     

A minisum location problem with regional demand considering farthest Euclidean distances

We consider a continuous multi-facility location-allocation problem that aims to minimize the sum of weighted farthest Euclidean distances between (closed convex) polygonal and/or circular demand regions, and facilities they are assigned to. We show that the single facility version of the problem has a straightforward second-order cone programming formulation and can therefore be efficiently solved to optimality. To solve large size instances, we adapt a multi-dimensional direct search descent algorithm to our problem which is not guaranteed to find the optimal solution. In a special case with circular and rectangular demand regions, this algorithm, if converges, finds the optimal solution. We also apply a simple subgradient method to the problem. Furthermore, we review the algorithms proposed for the problem in the literature and compare all these algorithms in terms of both solution quality and time. Finally, we consider the multi-facility version of the problem and model it as a mixed integer second-order cone programming problem. As this formulation is weak, we use the alternate location-allocation heuristic to solve large size instances.     

Peripheral mRNA Expression and Prognostic Significance of Emotional Stress Biomarkers in Metastatic Breast Cancer Patients

Emotional stress is believed to be associated with increased tumor progression. Stress-induced epigenetic modifications can contribute to the severity of disease and poor prognosis in cancer patients. The current study aimed to investigate the expression profiles along with the prognostic significance of psychological stress-related genes in metastatic breast cancer patients, to rationalize the molecular link between emotional stress and cancer progression. We profiled the expression of selected stress-associated genes (5-HTT, NR3C1, OXTR, and FKBP5) in breast cancer including the stress evaluation of all participants using the Questionnaire on Distress in Cancer Patients–short form (QSC-R10). A survival database, the Kaplan–Meier Plotter, was used to explore the prognostic significance of these genes in breast cancer. Our results showed relatively low expressions of 5-HTT (p = 0.02) and OXTR (p = 0.0387) in metastatic breast cancer patients as compared to the non-metastatic group of patients. The expression of NR3C1 was low in tumor grade III as compared to grade II (p = 0.04). Additionally, the expression of NR3C1 was significantly higher in patients with positive estrogen receptor status. However, no significant difference was found regarding FKBP5 expression in breast cancer. The results suggest a potential implication of these genes in breast cancer pathology and prognosis.     

Heavy metal bioaccumulation by cultivated Agaricus bisporus from artificially enriched substrates

 Cultivated Agaricus bisporus possess the ability to bioaccumulate seven heavy metals (Pb, Cd, Hg, Fe, Cu, Mn, and Zn). The cultivated champignon mushroom A. bisporus was grown in soil composts of 16 different compositions. An edible mushroom, A. bisporus was also cultivated on humic compost artificially fortified with the seven heavy metals at five different concentrations (0.1 mg/kg, 0.5 mg/kg, 1.0 mg/kg, 3.0 mg/kg, and 10.0 mg/kg) and on control substrate (0 mg/kg) on a dry weight basis. The method of measuring bioaccumulation was flame atomic absorption spectrophotometry. Received: 1 October 1997 / Revised version: 19 January 1998     

Effects of Penicillium roqueforti and whey cheese on gross composition,microbiology and proteolysis of mould‐ripened Civil cheese during ripening

Four different types of mould‐ripened Civil cheese were manufactured. A defined (nontoxigenic) strain of a Penicillium roqueforti (SC 509) was used as the secondary starter with and without addition of the whey cheese (Lor); in parallel, secondary starter‐free counterparts were manufactured. Chemical composition, microbiology and proteolysis were studied during the ripening. The incorporation of whey cheese in the manufacture of mould‐ripened Civil cheese altered the gross composition and adversely affected proteolysis in the cheeses. The inoculated P. roqueforti moulds appeared to grow slowly on those cheeses, and little proteolysis was evident in all cheese treatments during the first 90 days of ripening. However, sharp increases in the soluble nitrogen fractions were observed in all cheeses after 90 days. Microbiological analysis showed that the microbial counts in the cheeses were at high levels at the beginning of ripening, while their counts decreased approximately 1–2 log cfu/g towards the end of ripening.     

Occurrence of phthalate metabolites in human urine from several Asian countries

The occurrence of 14 phthalate metabolites was found in human urine samples collected from seven Asian countries: China, India, Japan, Korea, Kuwait, Malaysia, and Vietnam. Phthalate metabolites were found in all samples, indicating widespread exposure of humans to phthalates in these Asian countries. The highest total (the sum of 14 phthalates) phthalate metabolite concentrations were found in samples collected from Kuwait (median: 1050 ng/mL), followed in decreasing order by samples from India (389 ng/mL), China (234 ng/mL), Vietnam (133 ng/mL), Japan (120 ng/mL), Korea (117 ng/mL), and Malaysia (94.9 ng/mL). The creatinine-adjusted median concentrations of total phthalates for urine samples from Kuwait, India, China, Vietnam, Japan, Korea, and Malaysia were 692, 506, 289, 119, 103, 104, and 169 μg/g creatinine, respectively. Monomethyl phthalate (mMP), monoethyl phthalate (mEP), mono (2-isobutyl phthalate) (miBP), mono-n-butyl phthalate (mBP), and metabolites of di-(2-ethylhexyl) phthalate (DEHP) were the dominant compounds, collectively accounting for >95% of the total concentrations in the samples from the seven countries. The profiles of urinary phthalate metabolite concentrations varied among the samples collected from the seven countries. Urine samples from Kuwait contained the highest concentrations of mEP (median: 391 ng/mL), mBP (94.1 ng/mL), and the metabolites of DEHP (202 ng/mL), whereas samples from China and Japan contained the highest concentrations of miBP (50.8 ng/mL) and mMP (17.5 ng/mL), respectively. mEP was the predominant metabolite in urine samples from India and Kuwait (accounting for 49% of the total), mBP and miBP were the predominant compounds in samples from China (52%), and DEHP metabolites were the predominant compounds in samples from Korea (46%) and Vietnam (52%). Based on the urinary concentrations of mEP, mBP, miBP, and DEHP metabolites of the samples from the seven Asian countries, we estimated daily intake rates of diethyl phthalate (DEP), dibutyl phthalate (DBP), and DEHP. The results indicated that people in the seven Asian countries are exposed to DEP, DBP, and DEHP at levels well below the reference doses (RfD) suggested as unsafe by the U.S. Environmental Protection Agency (EPA). The estimated exposure doses to DEHP in Kuwait, however, were above the RfD recommended by the EPA.     

Diversity and functional characteristics of lactic acid bacteria from traditional kefir grains

Traditional kefir grains were collected from distinct parts of Turkey, and their microbial profile was determined. A wide bacterial biota was observed formed by distinct lactic acid bacteria (LAB) in which Lactococcus lactis strains appeared to be dominant. Yeast species were also identified in kefir grains. Significant levels of antifungal and antibacterial activities were monitored in kefir isolates. All tested LAB produced an exopolysaccharide (EPS) containing glucose and galactose, and some strains formed a fructan‐type EPS. Importantly, low levels of antibiotic resistance were observed among the kefir isolates.