Universities of the Kyrgyz Republic on the Web: accessibility and usability

Universal Access in the Information Society - Today the Internet is the easiest way to find information about any kind of organization, and the first impression about an organization is almost...     

Competitiveness analysis of automotive industry in Turkey using Bayesian networks

The purpose of this study is to analyze the relations between the factors that enable national competitive advantage and the establishment of competitive superiority in automotive industry through a comprehensive analytical model. Bayesian networks (BN) are used to investigate the associations of different factors in the automotive industry which lead to competitive advantage. The results of the study focus on building a road map for the automotive sector policy makers in their way to improve the competitiveness through scenario analysis. Using the probabilistic dependency structure of the Bayesian network all of the variables in the model can be estimated. Thus, with the proposed model the automotive industry can be analyzed as a whole system and not only in terms of single variables. Findings of the model indicate that technological developments in automotive industry can alter the nature of competition in this industry.     

Comparison of antioxidant capacity and phenolic composition of peel and flesh of some apple varieties

BACKGROUND: Apples contain a large concentration of phenolic compounds, dependent on factors such as cultivar, harvest, storage conditions, and processing. This study aims to identify the essential phenolic compounds present in various apple varieties, to measure their total antioxidant capacity (TAC) with the CUPRAC (cupric ion reducing antioxidant capacity) and ABTS (2,2′‐azino‐bis(3‐ethylbenzothiazoline‐6‐sulfonate)) methods, and to correlate their TAC values with HPLC findings. RESULTS: The order of TAC (mmol Trolox g^?1 fresh weight) of apple peels determined with the CUPRAC method was: Granny Smith > Amasya > Sky Spur > Ervin Spur > King Luscious ≥ Arap Kizi ≥ Lutz Golden. The theoretically calculated TAC values of HPLC‐quantified compounds, with the aid of the combined HPLC‐CUPRAC method, accounted for 18.4–33.5% of the experimentally observed CUPRAC capacity of peel extracts and 19.5–56.3% of flesh extracts, depending on apple variety. CONCLUSION: In synthetic samples of apple antioxidants, the CUPRAC‐TAC values of constituents, identified and analyzed by HPLC, proved to be additive, enabling measurement of the cooperative action of antioxidants using the proposed methodology. Apple peel showed higher contents of phenolics and therefore higher TAC than apple flesh, confirming the health benefit of the consumption of apples together with peel. © 2012 Society of Chemical Industry     

Comparison of total antioxidant capacity and phenolic composition of some apple juices with combined HPLC–CUPRAC assay

It was aimed in this study to identify and quantify various constituents (particularly phenolics) of apple juice and to quantitatively compare the total antioxidant capacities of juices obtained from apple varieties grown in Turkey.     

An investigation into the formation of fumaric acid in apple juice concentrates

 In this study, apples inoculated with pure cultures of Rhizopus stolonifer, Penicillium expansum and Lactobacillus plantarum were utilised as the raw material to produce apple juice concentrate. The effects of microorganisms and various processing treatments on the fumaric acid, lactic acid and patulin contents of apple juice were investigated. R. stolonifer was found to be the most responsible causative agent of fumaric acid and lactic acid. L. plantarum also produced certain amounts of lactic acid, but not as much as R. stolonifer. L. plantarum caused a significant decrease in L-malic acid content indicating the occurrence of malolactic fermentation. During this complicated biochemical pathway, a small amount of fumaric acid was also formed by L. plantarum. P. expansum produced only patulin, but did not affect the fumaric acid and lactic acid contents. Fumaric acid contents of the samples decreased throughout the processing steps excepting evaporation. The fumaric acid contents of the samples increased just after evaporation depending on the heat applied. The patulin and lactic acid contents of the samples also showed a decreasing trend throughout processing. However, L. plantarum caused a significant increase in lactic acid content just after depectinization depending on whether the appropriate time-temperature conditions for incubation were available during depectinization. Received: 3 November 1998 / Revised version: 4 January 1999     

Factors affecting opportunity of worksharing as a dynamic line balancing mechanism

We consider the problem of optimal worksharing between two adjacent workers each of whom processes a fixed task in addition to their shared task(s). We use a Markov Decision Process (MDP) model to compute optimal policies and provide a benchmark for evaluating threshold policy heuristics. Our approach differs from previous studies of dynamic line balancing in that we focus on system architecture factors that affect the performance improvement opportunity possible through worksharing relative to a traditional static worker allocations, as well as practical heuristics for worksharing. We find that three such factors are significant whether we use an optimal or a heuristic control policy: ability to preempt the shared task, granularity of the shared task and overall variability of the task times. Understanding the role of these factors in a given production environment provides a means for determining where and how worksharing can have significant logistical benefits.     

Hostility,driving anger,and dangerous driving: The emerging role of hemispheric preference

Background

Various studies have implicated psychosocial variables (e.g., hostility) in risk of dangerous driving and traffic accidents. However, whether these variables are related to more basic neurobiological factors, and whether such associations have implications for the modification of psychosocial risk factors in the context of driving, have not been examined in depth. This study examined the relationship between hemispheric preference (HP), hostility and self-reported dangerous driving, and the ability to affect driving anger via hemisphere activating cognitive exercises (HACE).

Methods

In Study 1, 254 Turkish students completed questionnaires of hostility, HP and driving behavior. In Study 2, we conducted a “proof of concept” experimental study, and tested effects of left, right and neutral HACE on driving anger, by exposing N = 650 Turkish students to written scenarios including either logical (left hemisphere), visuo-spatial (right hemisphere) or “mild doses” of both types of contents (control).

Results

In Study 1, left-HP was associated with higher hostility and with more dangerous driving, and hostility mediated the relationship between L-HP and reported driving behavior. In Study 2, only right-HACE led to immediate significant reductions in self-reported driving anger.

Conclusions

Left-HP is related to hostility and to dangerous driving, and it may be possible to partly reduce driving anger by right-HACE. Future studies must replicate these findings with objective measures, more enduring interventions and longer follow-ups.     

Using an optimized queueing network model to support wafer fab design

We develop an Optimized Queueing Network (OQNet) capacity planning tool for supporting the design of new and reconfigured semiconductor fabrication facilities that makes use of queueing network approximations and an optimization routine. The basic problem addressed by this tool is to minimize the facility cost required to meet specified volume and cycle time targets. Features common to semiconductor environments, such as batch processes, re-entrant flows, multiple product classes, and machine setups, are incorporated into the model. Comparisons with simulation show that the queueing and other approximations are reasonably accurate. Tests of the optimization routine demonstrate that it can find good solutions quickly.