Inventory Management Performance in Indian Machine Tool SMEs: What factors do influence them

These instructions give on basic guidelines for preparing papers for the IEEM 2008 Proceedings. Inventory Management (IM) plays a decisive role in the enhancement of efficiency for manufacturing enterprise competitiveness. Therefore, major manufacturing industries are following inventory management practices as a strategy to improve efficiency and achieve competitiveness. However, the spread of inventory management culture among Small and Medium Enterprises (SMEs) is limited due to lack of initiation, expertise and financial limitations in developed countries, leave alone developing countries.With this backdrop, this paper makes an attempt to ascertain the factors which influence the IM performance of SMEs in the machine tools industry of Bangalore, India. This issue is probed based on primary data gathered from 91 SMEs. The paper brings out that two sets of factors namely organizational support and external pressure have a positive impact on the inventory performance of SMEs.

Weakening of the Gram-negative bacterial outer membrane - A tool for increasing microbiological safety

Gram-negative bacteria are harmful in various surroundings. In the food industy their metabolites are potential cause of spoilage and this group also includes many severe or potential pathogens, such as Salmonella. Due to their ability to produce biofilms Gram-negative bacteria also cause problems in many industrial processes as well as in clinical surroundings. Control of Gram-negative bacteria is hampered by the outer membrane (OM) in the outermost layer of the cells. This layer is an intrinsic barrier for many hydrophobic agents and macromolecules. Permeabilizers are compounds that weaken OM and can thus increase the activity of antimicrobials by facililating entry of hydrophobic compounds and macromolecules into the cell where they can reach their target sites and inhibit or destroy cellular functions. The work described in this thesis shows that lactic acid acts as a permeabilizer and destabilizes the OM of Gram-negative bacteria. In addition, organic acids present in berriers, i.e. malic, sorbic and benzoic acid, were shown to weaken the OM of Gram-negative bacteria. Organic acids can poteniate the antimicrobial activity of other compounds. Microbial colonic degradation products of plant-derived phenolic compounds (3,4-dihydroxyphenylacetic acid, 3-hydroxyphenylacetic acid, 3,4-dihydroxyphenylpropionic acid, 4-hydroxyphenylpropionic acid, 3-phenylpropionic acid and 3-hydroxyphenylpropionic acid) efficiently destabilized OM of Salmonella. The studies increase our understanding of the mechanism of action of the classical chelator, ethylenediaminetetra-acetic acid (EDTA). In addition, the results indicate that the biocidic activity of benzalkonium chloride against Pseudomonas can be increased by combined use with polyethylenimine (PEI). In addition to PEI, several other potential permeabilizers, such as succimer, were shown to destabilize the OM of Gram-negative bacteria. Furthermore, combination of the results obtained from various permeability assays (e.g. uptake of a hydrophobic probe, sensitization to hydrophobic antibiotics and detergents, release of lipopolysaccharide (LPS) and LPS-specific fatty acids) with atomic force microscopy (AFM) image results increases our knowledge of the action of permeabilizers.

Evaluation of ELISA coupled with Western blot as a surveillance tool for Trichinella infection in wild boar (Sus scrofa)

Trichinella surveillance in wildlife relies on muscle digestion of large samples which are logistically difficult to store and transport in remote and tropical regions as well as labour-intensive to process. Serological methods such as enzyme-linked immunosorbent assays (ELISAs) offer rapid, cost-effective alternatives for surveillance but should be paired with additional tests because of the high false-positive rates encountered in wildlife. We investigated the utility of ELISAs coupled with Western blot (WB) in providing evidence of Trichinella exposure or infection in wild boar. Serum samples were collected from 673 wild boar from a high- and low-risk region for Trichinella introduction within mainland Australia, which is considered Trichinella-free. Sera were examined using both an 'in-house' and a commercially available indirect-ELISA that used excretory secretory (E/S) antigens. Cut-off values for positive results were determined using sera from the low-risk population. All wild boar from the high-risk region (352) and 139/321 (43.3%) of the wild boar from the low-risk region were tested by artificial digestion. Testing by Western blot using E/S antigens, and a Trichinella-specific real-time PCR was also carried out on all ELISA-positive samples. The two ELISAs correctly classified all positive controls as well as one naturally infected wild boar from Gabba Island in the Torres Strait. In both the high- and low-risk populations, the ELISA results showed substantial agreement (k-value = 0.66) that increased to very good (k-value = 0.82) when WB-positive only samples were compared. The results of testing sera collected from the Australian mainland showed the Trichinella seroprevalence was 3.5% (95% C.I. 0.0-8.0) and 2.3% (95% C.I. 0.0-5.6) using the in-house and commercial ELISA coupled with WB respectively. These estimates were significantly higher (P < 0.05) than the artificial digestion estimate of 0.0% (95% C.I. 0.0-1.1). Real-time PCR testing of muscle from seropositive animals did not detect Trichinella DNA in any mainland animals, but did reveal the presence of a second larvae-positive wild boar on Gabba Island, supporting its utility as an alternative, highly sensitive method in muscle examination. The serology results suggest Australian wildlife may have been exposed to Trichinella parasites. However, because of the possibility of non-specific reactions with other parasitic infections, more work using well-defined cohorts of positive and negative samples is required. Even if the specificity of the ELISAs is proven to be low, their ability to correctly classify the small number of true positive sera in this study indicates utility in screening wild boar populations for reactive sera which can be followed up with additional testing. (C) 2013 Elsevier B.V. All rights reserved.

Validity of a self-report recall tool for estimating sedentary behaviour in adults

BACKGROUND Sedentary behavior is continuing to emerge as an important target for health promotion. The purpose of this study was to determine the validity of a self-report use of time recall tool, the Multimedia Activity Recall for Children and Adults (MARCA) in estimating time spent sitting/lying, compared with a device-based measure. METHODS Fifty-eight participants (48% female, [mean±standard deviation] 28±7.4 years of age, 23.9±3.05 kg/m2) wore an activPAL device for 24-h and the following day completed the MARCA. Pearson correlation coefficients (r) were used to analyse convergent validity of the adult MARCA compared with activPAL estimates of total sitting/lying time. Agreement was examined using Bland-Altman plots. RESULTS According to activPAL estimates, participants spent 10.4 hr/day [standard deviation (SD)=2.06] sitting or lying down while awake. The correlation between MARCA and activPAL estimates of total sit/lie time was r=0.77 (95% confidence interval = 0.64-0.86; p<0.001). Bland-Altman analyses revealed a mean bias of +0.59 hr/day with moderately wide limits of agreement (-2.35 hours to +3.53 hr/day). CONCLUSIONS This study found a moderate to strong agreement between the adult MARCA and the activPAL, suggesting that the MARCA is an appropriate tool for the measurement of time spent sitting or lying down in an adult population.

Infrared spectroscopy as a rapid tool to detect methylglyoxal and antibacterial activity in Australian honeys

Methylglyoxal (2-oxopropanal) is a compound known to contribute to the non-peroxide antimicrobial activity of honeys. The feasibility of using infrared spectroscopy as a predictive tool for honey antibacterial activity and methylglyoxal content was assessed. A linear relationship was found between methylglyoxal content (279–1755 mg/kg) in Leptospermum polygalifolium honeys and bacterial inhibition for Escherichiacoli (R2 = 0.80) and Staphylococcusaureus (R2 = 0.64). A good prediction of methylglyoxal (R2 0.75) content in honey was achieved using spectroscopic data from the mid infrared (MIR) range in combination with partial least squares regression. These results indicate that robust predictive equations could be developed using MIR for commercial application where the prediction of bacterial inhibition is needed to ‘value’ honeys with methylglyoxal contents in excess of 200 mg/kg.

Exploring the Potential Impacts of Climate Variability on Spring Wheat Yield with the APSIM Decision Support Tool

Assessing the impacts of climate variability on agricultural productivity at regional, national or global scale is essential for defining adaptation and mitigation strategies. We explore in this study the potential changes in spring wheat yields at Swift Current and Melfort, Canada, for different sowing windows under projected climate scenarios (i.e., the representative concentration pathways, RCP4.5 and RCP8.5). First, the APSIM model was calibrated and evaluated at the study sites using data from long term experimental field plots. Then, the impacts of change in sowing dates on final yield were assessed over the 2030-2099 period with a 1990-2009 baseline period of observed yield data, assuming that other crop management practices remained unchanged. Results showed that the performance of APSIM was quite satisfactory with an index of agreement of 0.80, R2 of 0.54, and mean absolute error (MAE) and root mean square error (RMSE) of 529 kg/ha and 1023 kg/ha, respectively (MAE = 476 kg/ha and RMSE = 684 kg/ha in calibration phase). Under the projected climate conditions, a general trend in yield loss was observed regardless of the sowing window, with a range from -24 to -94 depending on the site and the RCP, and noticeable losses during the 2060s and beyond (increasing CO2 effects being excluded). Smallest yield losses obtained through earlier possible sowing date (i.e., mid-April) under the projected future climate suggested that this option might be explored for mitigating possible adverse impacts of climate variability. Our findings could therefore serve as a basis for using APSIM as a decision support tool for adaptation/mitigation options under potential climate variability within Western Canada.

A network forensics tool for precise data packet capture and replay in cyber-physical systems

Network data packet capture and replay capabilities are basic requirements for forensic analysis of faults and security-related anomalies, as well as for testing and development. Cyber-physical networks, in which data packets are used to monitor and control physical devices, must operate within strict timing constraints, in order to match the hardware devices' characteristics. Standard network monitoring tools are unsuitable for such systems because they cannot guarantee to capture all data packets, may introduce their own traffic into the network, and cannot reliably reproduce the original timing of data packets. Here we present a high-speed network forensics tool specifically designed for capturing and replaying data traffic in Supervisory Control and Data Acquisition systems. Unlike general-purpose "packet capture" tools it does not affect the observed network's data traffic and guarantees that the original packet ordering is preserved. Most importantly, it allows replay of network traffic precisely matching its original timing. The tool was implemented by developing novel user interface and back-end software for a special-purpose network interface card. Experimental results show a clear improvement in data capture and replay capabilities over standard network monitoring methods and general-purpose forensics solutions.

Meltdown - a tool for classification and analysis of DSF data

An application that translates raw thermal melt curve data into more easily assimilated knowledge is described. This program, called ‘Meltdown’, performs a number of data remediation steps before classifying melt curves and estimating melting temperatures. The final output is a report that summarizes the results of a differential scanning fluorimetry experiment. Meltdown uses a Bayesian classification scheme, enabling reproducible identification of various trends commonly found in DSF datasets. The goal of Meltdown is not to replace human analysis of the raw data, but to provide a sensible interpretation of the data to make this useful experimental technique accessible to naïve users, as well as providing a starting point for detailed analyses by more experienced users.

The Gerbera cDNA Microarray: A Tool for Large-Scale Identification of Genes Involved in Flower Development

During the past ten years, large-scale transcript analysis using microarrays has become a powerful tool to identify and predict functions for new genes. It allows simultaneous monitoring of the expression of thousands of genes and has become a routinely used tool in laboratories worldwide. Microarray analysis will, together with other functional genomics tools, take us closer to understanding the functions of all genes in genomes of living organisms. Flower development is a genetically regulated process which has mostly been studied in the traditional model species Arabidopsis thaliana, Antirrhinum majus and Petunia hybrida. The molecular mechanisms behind flower development in them are partly applicable in other plant systems. However, not all biological phenomena can be approached with just a few model systems. In order to understand and apply the knowledge to ecologically and economically important plants, other species also need to be studied. Sequencing of 17 000 ESTs from nine different cDNA libraries of the ornamental plant Gerbera hybrida made it possible to construct a cDNA microarray with 9000 probes. The probes of the microarray represent all different ESTs in the database. From the gerbera ESTs 20% were unique to gerbera while 373 were specific to the Asteraceae family of flowering plants. Gerbera has composite inflorescences with three different types of flowers that vary from each other morphologically. The marginal ray flowers are large, often pigmented and female, while the central disc flowers are smaller and more radially symmetrical perfect flowers. Intermediate trans flowers are similar to ray flowers but smaller in size. This feature together with the molecular tools applied to gerbera, make gerbera a unique system in comparison to the common model plants with only a single kind of flowers in their inflorescence. In the first part of this thesis, conditions for gerbera microarray analysis were optimised including experimental design, sample preparation and hybridization, as well as data analysis and verification. Moreover, in the first study, the flower and flower organ-specific genes were identified. After the reliability and reproducibility of the method were confirmed, the microarrays were utilized to investigate transcriptional differences between ray and disc flowers. This study revealed novel information about the morphological development as well as the transcriptional regulation of early stages of development in various flower types of gerbera. The most interesting finding was differential expression of MADS-box genes, suggesting the existence of flower type-specific regulatory complexes in the specification of different types of flowers. The gerbera microarray was further used to profile changes in expression during petal development. Gerbera ray flower petals are large, which makes them an ideal model to study organogenesis. Six different stages were compared and specifically analysed. Expression profiles of genes related to cell structure and growth implied that during stage two, cells divide, a process which is marked by expression of histones, cyclins and tubulins. Stage 4 was found to be a transition stage between cell division and expansion and by stage 6 cells had stopped division and instead underwent expansion. Interestingly, at the last analysed stage, stage 9, when cells did not grow any more, the highest number of upregulated genes was detected. The gerbera microarray is a fully-functioning tool for large-scale studies of flower development and correlation with real-time RT-PCR results show that it is also highly sensitive and reliable. Gene expression data presented here will be a source for gene expression mining or marker gene discovery in the future studies that will be performed in the Gerbera Laboratory. The publicly available data will also serve the plant research community world-wide.

An open source service oriented Mobile Business Intelligence Tool (MBIT)

Corporate executives require relevant and intelligent business information in real-time to take strategic decisions. They require the freedom to access this information anywhere and anytime. There is a need to extend this functionality beyond the office and on the fingertips of the decision makers. Mobile Business Intelligence Tool (MBIT) aims to provide these features in a flexible and cost-efficient manner. This paper describes the detailed architecture of MBIT to overcome the limitations of existing mobile business intelligence tools. Further, a detailed implementation framework is presented to realize the design. This research highlights the benefits of using service oriented architecture to design flexible and platform independent mobile business applications. © 2009 IEEE.

Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques

In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.