Knowledge and information flows in supply chains: A study on pharmaceutical companies

A great deal of attention in the supply chain management literature is devoted to study material and demand information flows and their coordination. But in many situations, supply chains may convey information from different nature, they may be an important channel companies have to deliver knowledge, or specifically, technical information to the market. This paper studies the technical flow and highlights its particular requirements. Drawing upon a qualitative field research, it studies pharmaceutical companies, since those companies face a very specific challenge: consumers do not have discretion over their choices, ethical drugs must be prescribed by physicians to be bought and used by final consumers. Technical information flow is rich, and must be redundant and early delivered at multiple points. Thus, apart from the regular material channel where products and order information flow, those companies build a specialized information channel, developed to communicate to those who need it to create demand. Conclusions can be extended to supply chains where products and services are complex and decision makers must be clearly informed about technology-related information. (C) 2009 Elsevier B.V. All rights reserved.

Information theoretic interpretation of frequency domain connectivity measures

In order to provide adequate multivariate measures of information flow between neural structures, modified expressions of partial directed coherence (PDC) and directed transfer function (DTF), two popular multivariate connectivity measures employed in neuroscience, are introduced and their formal relationship to mutual information rates are proved.

Anticipation of pain enhances the nociceptive transmission and functional connectivity within pain network in rats

Background: Expectation is a very potent pain modulator in both humans and animals. There is evidence that pain transmission neurons are modulated by expectation preceding painful stimuli. Nonetheless, few studies have examined the influence of pain expectation on the pain-related neuronal activity and the functional connectivity within the central nociceptive network. Results: This study used a tone-laser conditioning paradigm to establish the pain expectation in rats, and simultaneously recorded the anterior cingulate cortex (ACC), the medial dorsal thalamus (MD), and the primary somatosensory cortex (SI) to investigate the effect of pain expectation on laser-induced neuronal responses. Cross-correlation and partial directed coherence analysis were used to determine the functional interactions within and between the recorded areas during nociceptive transmission. The results showed that under anticipation condition, the neuronal activity to the auditory cue was significantly increased in the ACC area, whereas those to actual noxious stimuli were enhanced in all the recorded areas. Furthermore, neuronal correlations within and between these areas were significantly increased under conditions of expectation compared to those under non-expectation conditions, indicating an enhanced synchronization of neural activity within the pain network. In addition, information flow from the medial (ACC and MD) to the lateral (SI cortex) pain pathway increased, suggesting that the emotion-related neural circuits may modulate the neuronal activity in the somatosensory pathway during nociceptive transmission. Conclusion: These results demonstrate that the nociceptive processing in both medial and lateral pain systems is modulated by the expectation of pain.

Communication structure of cortical networks

Large-scale cortical networks exhibit characteristic topological properties that shape communication between brain regions and global cortical dynamics. Analysis of complex networks allows the description of connectedness, distance, clustering, and centrality that reveal different aspects of how the network's nodes communicate. Here, we focus on a novel analysis of complex walks in a series of mammalian cortical networks that model potential dynamics of information flow between individual brain regions. We introduce two new measures called absorption and driftness. Absorption is the average length of random walks between any two nodes, and takes into account all paths that may diffuse activity throughout the network. Driftness is the ratio between absorption and the corresponding shortest path length. For a given node of the network, we also define four related measurements, namely in-and out-absorption as well as in-and out-driftness, as the averages of the corresponding measures from all nodes to that node, and from that node to all nodes, respectively. We find that the cat thalamo-cortical system incorporates features of two classic network topologies, Erdos-Renyi graphs with respect to in-absorption and in-driftness, and configuration models with respect to out-absorption and out-driftness. Moreover, taken together these four measures separate the network nodes based on broad functional roles (visual, auditory, somatomotor, and frontolimbic).

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Gamma band oscillations under influence of bromazepam during a sensorimotor integration task: An EEG coherence study

The goal of the present study was to explore the dynamics of the gamma band using the coherence of the quantitative electroencephalography (qEEG) in a sensorimotor integration task and the influence of the neuromodulator bromazepam on the band behavior. Our hypothesis is that the needs of the typewriting task will demand the coupling of different brain areas, and that the gamma band will promote the binding of information. It is also expected that the neuromodulator will modify this coupling. The sample was composed of 39 healthy subjects. We used a randomized double-blind design and divided subjects into three groups: placebo (n = 13), bromazepam 3 mg (n = 13) and bromazepam 6 mg (n = 13). The two-way ANOVA analysis demonstrated a main effect for the factors condition (i.e., C4-CZ electrode pair) and moment (i.e., C3-CZ, C3-C4 and C4-CZ pairs of electrodes). We propose that the gamma band plays an important role in the binding among several brain areas in complex motor tasks and that each hemisphere is influenced in a different manner by the neuromodulator. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Opinion dynamics of learning agents: does seeking consensus lead to disagreement?

We study opinion dynamics in a population of interacting adaptive agents voting on a set of issues represented by vectors. We consider agents who can classify issues into one of two categories and can arrive at their opinions using an adaptive algorithm. Adaptation comes from learning and the information for the learning process comes from interacting with other neighboring agents and trying to change the internal state in order to concur with their opinions. The change in the internal state is driven by the information contained in the issue and in the opinion of the other agent. We present results in a simple yet rich context where each agent uses a Boolean perceptron to state their opinion. If the update occurs with information asynchronously exchanged among pairs of agents, then the typical case, if the number of issues is kept small, is the evolution into a society torn by the emergence of factions with extreme opposite beliefs. This occurs even when seeking consensus with agents with opposite opinions. If the number of issues is large, the dynamics becomes trapped, the society does not evolve into factions and a distribution of moderate opinions is observed. The synchronous case is technically simpler and is studied by formulating the problem in terms of differential equations that describe the evolution of order parameters that measure the consensus between pairs of agents. We show that for a large number of issues and unidirectional information flow, global consensus is a fixed point; however, the approach to this consensus is glassy for large societies.

Disorder-based graphene spintronics

The use of the spin of the electron as the ultimate logic bit-in what has been dubbed spintronics-can lead to a novel way of thinking about information flow. At the same time single-layer graphene has been the subject of intense research due to its potential application in nanoscale electronics. While defects can significantly alter the electronic properties of nanoscopic systems, the lack of control can lead to seemingly deleterious effects arising from the random arrangement of such impurities. Here we demonstrate, using ab initio density functional theory and non-equilibrium Green`s functions calculations, that it is possible to obtain perfect spin selectivity in doped graphene nanoribbons to produce a perfect spin filter. We show that initially unpolarized electrons entering the system give rise to 100% polarization of the current due to random disorder. This effect is explained in terms of different localization lengths for each spin channel which leads to a new mechanism for the spin filtering effect that is disorder-driven.

The game of contacts: Estimating the social visibility of groups

Estimating the sizes of hard-to-count populations is a challenging and important problem that occurs frequently in social science, public health, and public policy. This problem is particularly pressing in HIV/AIDS research because estimates of the sizes of the most at-risk populations-illicit drug users, men who have sex with men, and sex workers-are needed for designing, evaluating, and funding programs to curb the spread of the disease. A promising new approach in this area is the network scale-up method, which uses information about the personal networks of respondents to make population size estimates. However, if the target population has low social visibility, as is likely to be the case in HIV/AIDS research, scale-up estimates will be too low. In this paper we develop a game-like activity that we call the game of contacts in order to estimate the social visibility of groups, and report results from a study of heavy drug users in Curitiba, Brazil (n = 294). The game produced estimates of social visibility that were consistent with qualitative expectations but of surprising magnitude. Further, a number of checks suggest that the data are high-quality. While motivated by the specific problem of population size estimation, our method could be used by researchers more broadly and adds to long-standing efforts to combine the richness of social network analysis with the power and scale of sample surveys. (C) 2010 Elsevier B.V. All rights reserved.

Evaluation of flow regimes in a semi-cylindrical spouted bed through statistical, mutual information, spectral and Hurst`s analysis

Hydrodynamic studies were conducted in a semi-cylindrical spouted bed column of diameter 150 mm, height 1000 mm, conical base included angle of 60 degrees and inlet orifice diameter 25 mm. Pressure transducers at several axial positions were used to obtain pressure fluctuation time series with 1.2 and 2.4 mm glass beads at U/U-ms from 0.3 to 1.6, and static bed depths from 150 to 600 mm. The conditions covered several flow regimes (fixed bed, incipient spouting, stable spouting, pulsating spouting, slugging, bubble spouting and fluidization). Images of the system dynamics were also acquired through the transparent walls with a digital camera. The data were analyzed via statistical, mutual information theory, spectral and Hurst`s Rescaled Range methods to assess the potential of these methods to characterize the spouting quality. The results indicate that these methods have potential for monitoring spouted bed operation.

Simplified flow cytometric assay to detect minimal residual disease in childhood with acute lymphoblastic leukemia

The detection of minimal residual disease (MRD) is an important prognostic factor in childhood acute lymphoblastic leukemia (ALL) providing crucial information on the response to treatment and risk of relapse. However, the high cost of these techniques restricts their use in countries with limited resources. Thus, we prospectively studied the use of flow cytometry (FC) with a simplified 3-color assay and a limited antibody panel to detect MRD in the bone marrow (BM) and peripheral blood (PB) of children with ALL. BM and PB samples from 40 children with ALL were analyzed on days (d) 14 and 28 during induction and in weeks 24-30 of maintenance therapy. Detectable MRD was defined as > 0.01% cells expressing the aberrant immunophenotype as characterized at diagnosis among total events in the sample. A total of 87% of the patients had an aberrant immunophenotype at diagnosis. On d14, 56% of the BM and 43% of the PB samples had detectable MRD. On d28, this decreased to 45% and 31%, respectively. The percentage of cells with the aberrant phenotype was similar in both BM and PB in T-ALL but about 10 times higher in the BM of patients with B-cell-precursor ALL. Moreover, MRD was detected in the BM of patients in complete morphological remission (44% on d14 and 39% on d28). MRD was not significantly associated to gender, age, initial white blood cell count or cell lineage. This FC assay is feasible, affordable and readily applicable to detect MRD in centers with limited resources.

Single interface flow analysis with accuracy assessment

Single interface flow systems (SIFA) present some noteworthy advantages when compared to other flow systems, such as a simpler configuration, a more straightforward operation and control and an undemanding optimisation routine. Moreover, the plain reaction zone establishment, which relies strictly on the mutual inter-dispersion of the adjoining solutions, could be exploited to set up multiple sequential reaction schemes providing supplementary information regarding the species under determination. In this context, strategies for accuracy assessment could be favourably implemented. To this end, the sample could be processed by two quasi-independent analytical methods and the final result would be calculated after considering the two different methods. Intrinsically more precise and accurate results would be then gathered. In order to demonstrate the feasibility of the approach, a SIFA system with spectrophotometric detection was designed for the determination of lansoprazole in pharmaceutical formulations. Two reaction interfaces with two distinct pi-acceptors, chloranilic acid (CIA) and 2,3-dichloro-5,6-dicyano-p-benzoquinone (DDQ) were implemented. Linear working concentration ranges between 2.71 x 10(-4) to 8.12 x 10(-4) mol L(-1) and 2.17 x 10(-4) to 8.12 x 10(-4) mol L(-1) were obtained for DDQ and CIA methods, respectively. When compared with the results furnished by the reference procedure, the results showed relative deviations lower than 2.7%. Furthermore. the repeatability was good, with r.s.d. lower than 3.8% and 4.7% for DDQ and CIA methods, respectively. Determination rate was about 30 h(-1). (C) 2009 Elsevier B.V. All rights reserved.

Sequential injections as an alternative to gradient exploitation for implementing differential kinetic analysis in a flow injection system

A novel flow-based strategy for implementing simultaneous determinations of different chemical species reacting with the same reagent(s) at different rates is proposed and applied to the spectrophotometric catalytic determination of iron and vanadium in Fe-V alloys. The method relies on the influence of Fe(II) and V(IV) on the rate of the iodide oxidation by Cr(VI) under acidic conditions, the Jones reducing agent is then needed Three different plugs of the sample are sequentially inserted into an acidic KI reagent carrier stream, and a confluent Cr(VI) solution is added downstream Overlap between the inserted plugs leads to a complex sample zone with several regions of maximal and minimal absorbance values. Measurements performed on these regions reveal the different degrees of reaction development and tend to be more precise Data are treated by multivariate calibration involving the PLS algorithm The proposed system is very simple and rugged Two latent variables carried out ca 95% of the analytical information and the results are in agreement with ICP-OES. (C) 2010 Elsevier B V. All rights reserved.

DEVELOPMENT OF STATIC MIXERS FOR MISCIBLE FLUIDS IN LAMINAR FLOW WITH THE USE OF COMPUTATIONAL FLUID DYNAMICS (CFD)

Static mixers with improved performance were developed from CFD simulations in a stepwise approach. The relevant geometric features of simple mixer designs and the corresponding mixing mechanisms-laminar shear, elongational flow, and distributive mixing-were identified first. This information was used to formulate guidelines for the development of new geometries. The solid elements of the static mixer should: (a) provide restrictions to the flow; (b) deflect the flow; (c) be sequentially rotated around the flow direction to provide symmetry; (d) extend from the center of the pipe to the vicinity of the walls to avoid short-circuiting; and (e) distribute and remix the flow. Based on these guidelines, two improved mixer designs were developed: the DS A-I mixer has a good mixing efficiency and an acceptable pressure drop; the Fins 35 degrees mixer is more efficient and compact, but requires a larger pressure drop. Their performance indicates that their use is possible on industrial applications.

Assessment of flow in perforating arteries during intracranial aneurysm surgery using intraoperative near-infrared indocyanine green videoangiography

OBJECTIVE: Perforating arteries are commonly involved during the surgical dissection and clipping of intracranial aneurysms. Occlusion of perforating arteries is responsible for ischemic infarction and poor outcome. The goal of this study is to describe the usefulness of near-infrared indocyanine green videoangiography (ICGA) for the intraoperative assessment of blood flow in perforating arteries that are visible in the surgical field during clipping of intracranial aneurysms. In addition, we analyzed the incidence of perforating vessels involved during the aneurysm surgery and the incidence of ischemic infarct caused by compromised small arteries. METHODS: Sixty patients with 64 aneurysms were surgically treated and prospectively included in this study. Intraoperative ICGA was performed using a surgical microscope (Carl Zeiss Co., Oberkochen, Germany) with integrated ICGA technology. The presence and involvement of perforating arteries were analyzed in the microsurgical field during surgical dissection and clip application. Assessment of vascular patency after clipping was also investigated. Only those small arteries that were not visible on preoperative digital subtraction angiography were considered for analysis. RESULTS: The ICGA was able to visualize flow in all patients in whom perforating vessels were found in the microscope field. Among 36 patients whose perforating vessels were visible on ICGA, 11 (30%) presented a close relation between the aneurysm and perforating arteries. In one (9%) of these 11 patients, ICGA showed occlusion of a P1 perforating artery after clip application, which led to immediate correction of the clip confirmed by immediate reestablishment of flow visible with ICGA without clinical consequences. Four patients (6.7%) presented with postoperative perforating artery infarct, three of whom had perforating arteries that were not visible or distant from the aneurysm. CONCLUSION: The involvement of perforating arteries during clip application for aneurysm occlusion is a usual finding. Intraoperative ICGA may provide visual information with regard to the patency of these small vessels.