Exploring geographical dispersion in Thailand-based food supply chain (FSC)

Purpose: The purpose of this paper is to explore the key influential factors and their implications on food supply chain (FSC) location decisions from a Thailand-based manufacturer's view. Design/methodology/approach: In total, 21 case studies were conducted with eight Thailand-based food manufacturers. In each case, key influential factors were observed along with their implications on upstream and downstream FSC location decisions. Data were collected through semi-structured interviews and documentations. Data reduction and data display in tables were used to help data analysis of the case studies. Findings: This exploratory research found that, in the food industry, FSC geographical dispersion pattern could be determined by four factors: perishability, value density, economic-political forces, and technological forces. Technological forces were found as an enabler for FSC geographical dispersion whereas the other three factors could be both barriers and enablers. The implications of these four influential factors drive FSC towards four key patterns of FSC geographical dispersion: local supply chain (SC), supply-proximity SC, market-proximity SC, and international SC. Additionally, the strategy of the firm was found to also be an influential factor in determining FSC geographical dispersion. Research limitations/implications: Despite conducting 21 cases, the findings in this research are based on a relatively small sample, given the large size of the industry. More case evidence from a broader range of food product market and supply items, particularly ones that have significantly different patterns of FSC geographical dispersions would have been insightful. The consideration of additional influential factors such as labour movement between developing countries, currency fluctuations and labour costs, would also enrich the framework as well as improve the quality and validity of the research findings. The different strategies employed by the case companies and their implications on FSC location decisions should also be further investigated along with cases outside Thailand, to provide a more comprehensive view of FSC geographical location decisions. Practical implications: This paper provides insights how FSC is geographically located in both supply-side and demand-side from a manufacturing firm's view. The findings can also provide SC managers and researchers a better understanding of their FSCs. Originality/value: This research bridges the existing gap in the literature, explaining the geographical dispersion of SC particularly in the food industry where the characteristics are very specific, by exploring the internationalization ability of Thailand-based FSC and generalizing the key influential factors - perishability (lead time), value density, economic-political forces, market opportunities, and technological advancements. Four key patterns of FSC internationalization emerged from the case studies. © Emerald Group Publishing Limited.

Virulent Salmonella enterica infections can be exacerbated by concomitant infection of the host with a live attenuated S. enterica vaccine via Toll-like receptor 4-dependent interleukin-10 production with the involvement of both TRIF and MyD88.

During systemic disease in mice, Salmonella enterica grows intracellularly within discrete foci of infection in the spleen and liver. In concomitant infections, foci containing different S. enterica strains are spatially separated. We have investigated whether functional interactions between bacterial populations within the same host can occur despite the known spatial separation of the foci and independence of growth of salmonellae residing in different foci. In this study we have demonstrated that bacterial numbers of virulent S. enterica serovar Typhimurium C5 strain in mouse tissues can be increased by the presence of the attenuated aroA S. Typhimurium SL3261 vaccine strain in the same tissue. Disease exacerbation does not require simultaneous coinjection of the attenuated bacteria. SL3261 can be administered up to 48 hr after or 24 hr before the administration of C5 and still determine higher tissue numbers of the virulent bacteria. This indicates that intravenous administration of a S. enterica vaccine strain could potentially exacerbate an established infection with wild-type bacteria. These data also suggest that the severity of an infection with a virulent S. enterica strain can be increased by the prior administration of a live attenuated vaccine strain if infection occurs within 48 hr of vaccination. Exacerbation of the growth of C5 requires Toll-like receptor 4-dependent interleukin-10 production with the involvement of both Toll/interleukin-1 receptor-domain-containing adaptor inducing interferon-beta and myeloid differentiation factor 88.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

RFID Tag Location Systems

We describe a methods of locating an RFID tag. One method comprises: transmitting tag location signals from a plurality of different transmit antennas, wherein said antennas are spaced apart by more than a near field limit distance at a frequency of a said signal; receiving a corresponding plurality of receiving return signals from said tag; and processing said tag return signals to determine a range to said tag; wherein said transmitting comprises transmitting at a plurality of different frequencies; wherein said processing comprises determining a phase difference at said plurality of different frequencies to determine said range, and wherein said determining of said phase difference determines a phase difference between either i) two or more of said transmit signals resulting in a maxima in the returned signal RSSI or ii) a first transmit signal and its corresponding return signal; and wherein said determining of said range to said tag uses said return signals weighted responsive to a respective received signal strength of the return signal. Further data which may be used for averaging may be generated by using the above techniques along with changes in the polarisation state of the transmit and receive antennas and/or physical reconfiguration of the antennas (e.g. switch the transmit and receive elements).

A dependent partition-valued process for multitask clustering and time evolving network modelling

The fundamental aim of clustering algorithms is to partition data points. We consider tasks where the discovered partition is allowed to vary with some covariate such as space or time. One approach would be to use fragmentation-coagulation processes, but these, being Markov processes, are restricted to linear or tree structured covariate spaces. We define a partition-valued process on an arbitrary covariate space using Gaussian processes. We use the process to construct a multitask clustering model which partitions datapoints in a similar way across multiple data sources, and a time series model of network data which allows cluster assignments to vary over time. We describe sampling algorithms for inference and apply our method to defining cancer subtypes based on different types of cellular characteristics, finding regulatory modules from gene expression data from multiple human populations, and discovering time varying community structure in a social network.

Magnetic shielding properties of high- Tc superconducting hollow cylinders: Model combining experimental data for axial and transverse magnetic field configurations

Magnetic shielding efficiency was measured on high- Tc superconducting hollow cylinders subjected to either an axial or a transverse magnetic field in a large range of field sweep rates, dBapp/dt. The behaviour of the superconductor was modelled in order to reproduce the main features of the field penetration curves by using a minimum number of free parameters suitable for both magnetic field orientations. The field penetration measurements were carried out on Pb-doped Bi-2223 tubes at 77K by applying linearly increasing magnetic fields with a constant sweep rate ranging between 10νTs-1 and 10mTs-1 for both directions of the applied magnetic field. The experimental curves of the internal field versus the applied field, Bin(Bapp), show that, at a given sweep rate, the magnetic field for which the penetration occurs, Blim, is lower for the transverse configuration than for the axial configuration. A power law dependence with large exponent, n′, is found between Blim and dBapp/dt. The values of n′ are nearly the same for both configurations. We show that the main features of the curves B in(Bapp) can be reproduced using a simple 2D model, based on the method of Brandt, involving a E(J) power law with an n-exponent and a field-dependent critical current density, Jc(B), (following the Kim model: Jc = Jc0(1+B/B1)-1). In particular, a linear relationship between the measured n′-exponents and the n-exponent of the E(J) power law is suggested by taking into account the field dependence of the critical current density. Differences between the axial and the transverse shielding properties can be simply attributed to demagnetizing fields. © 2009 IOP Publishing Ltd.

Slowness: an objective for spike-timing-dependent plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.

Systematic misregistration and the statistical analysis of surface data.

Spatial normalisation is a key element of statistical parametric mapping and related techniques for analysing cohort statistics on voxel arrays and surfaces. The normalisation process involves aligning each individual specimen to a template using some sort of registration algorithm. Any misregistration will result in data being mapped onto the template at the wrong location. At best, this will introduce spatial imprecision into the subsequent statistical analysis. At worst, when the misregistration varies systematically with a covariate of interest, it may lead to false statistical inference. Since misregistration generally depends on the specimen's shape, we investigate here the effect of allowing for shape as a confound in the statistical analysis, with shape represented by the dominant modes of variation observed in the cohort. In a series of experiments on synthetic surface data, we demonstrate how allowing for shape can reveal true effects that were previously masked by systematic misregistration, and also guard against misinterpreting systematic misregistration as a true effect. We introduce some heuristics for disentangling misregistration effects from true effects, and demonstrate the approach's practical utility in a case study of the cortical bone distribution in 268 human femurs.

Strength correlations of cement-mixed soils using data mapping

Development of comparisons and correlations between the unconfined compressive strength (UCS) and the undrained triaxial compressive strength, qu, is essential for generalising performance and optimising the design of cement-stabilised soils. This paper introduces current work in collecting and collating data from a number of research projects involving both laboratory strength tests performed on identical cement-stabilised soil samples. The research project on cement-stabilised Singapore marine clays at the National University of Singapore has been used as an example to explain the work on comparing and correlating results from both tests by normalising data and constructing contour plots. The effect of variables on strength comparison and correlations was evaluated. The variation in strength correlations was found to be dependent on a number of factors including: soil properties, cement content, curing time and stress, total water/cement ratio, confining stress and strain rate. The results showed that at ~ 100 kPa confining stress, UCS and qu, had similar magnitudes. Correlations between strengths and other design variables are discussed and presented.