Gastric pneumatosis associated with preduodenal portal vein, duodenal atresia, and asplenia

An 8-day-old newborn presented with non-bilious vomiting, upper abdominal fullness, and failure to pass meconium. Plain radiographs revealed gastric pneumatosis (GP). At operation, he was found to have a non-obstructive preduodenal portal vein, preampullary duodenal atresia, asplenia, and malrotation. The baby was treated by duodeno-duodenostomy without mobilizing the portal vein and correction of the malrotation according to Ladd's procedure. He made an uneventful recovery and the GP resolved spontaneously. The malformative process was believed to have occurred at or soon after the 5th week of gestation, and the GP probably resulted from intramural air tracking through mucosal tears caused by high intragastric pressure.     

On the Consequences of Information Delays in the Scheduling of Semi-Automated Flexible Machines

Manufacturing systems with varying levels and types of flexibility employ alternative scheduling strategies to exploit flexibility for performance enhancement. Scheduling decisions in manufacturing systems are influenced by time delays due to information handling activities such as information collection, transfer, and processing. More specifically, scheduling strategies implicitly involve information intensive activities that may entail significant time delays for implementation, depending on the extant shop floor automation and integration within a flexible system. These are information delays and we believe that most contemporary flexible systems must inherently cope with some level of information delay when implementing on-line scheduling strategies. This paper conceptualizes the manifestation of information delays in the context of scheduling decisions within flexible systems through the definition of three key delay modes: (i) Mode 1 information-transfer delay; (ii) Mode 2 decision-implementation delay; and (iii) Mode 3 status-review delay. We then stress the need and importance of devising suitable on-line scheduling strategies for countering the effect of information delays by demonstrating the efficacy of a novel scheduling strategy on a single machine. While opening a new scheduling dimension with potential research ramifications, this paper highlights the fact that the concept of information delay can effectively capture the synergism issues related with flexibility, integration, and automation in the context of scheduling decisions within semi-automated flexible systems.     

Contrast enhancement of MRI images using morphological transforms and PSO

Medical imaging plays a crucial role in correct extraction of the significant information for monitoring the patient’s health and providing the quality treatment. A deluge of medical images requires initial interpretation for the presence of any abnormality, however, the correct diagnosis requires the images to be of good quality. To cope with the problem of poor contrast in medical images, this paper presents a method based on morphological transforms to improve the quality of the images. The proposed method incorporates Particle Swarm Optimization to find an optimum value of a parameter which controls the enhancement of the resulting image. The proposed algorithm is executed on a set of MRI images for testing its efficacy. The experimental results are compared in terms of both qualitative and quantitative parameters. The mean opinion score is obtained with the help of experts, which clearly shows the better performance of the proposed method. Furthermore, the parameters like Contrast Improvement Ratio, signal-to-noise ratio, peak signal-to-noise ratio, PL, and Structural Similarity Index are evident of better performance of proposed method when compared with the state-of-the-art methods and few recent methods. The comparison shows that the performance of the proposed method based on morphological transforms incorporating Particle Swarm Optimization is better not only visually but also in terms of other evaluation parameters.

     

A network approach for modeling and design of agile supply chains using a flexibility construct

Agility can be viewed as a need to encourage the enterprise-wide integration of flexible and core competent resources so as to offer value-added product and services in a volatile competitive environment. Since flexibility is considered a property that provides change capabilities of different enterprise-wide resources and processes in time and cost dimensions, supply chain flexibility can be considered a composite state to enterprise-wide resources to meet agility needs. Enterprise modeling frameworks depicting these composite flexibility states are difficult to model because of the complex and tacit interrelationship among system parameters and also because agility thrives on many business objectives. In view of this, the modeling framework presented in this paper is based on analytical network process (ANP) since this methodology can accommodate the complex and tacit interrelationship among factors affecting enterprise agility. The modeling framework forms a three-level network with the goal of attaining agility from the perspective of market, product, and customer as the actors. The goal depends on substrategies that address the characteristics of the three actors. Each of these substrategies further depends on manufacturing, logistic, sourcing, and information technology (IT) flexibility elements of the enterprise supply chain (SC). The research highlights that, under different environmental conditions, enterprises require synergy among appropriate supply chain flexibilities for practising agility. In the present research, the ANP modeling software tool Super Decisions™ has been used for relative prioritization of the supply chain flexibilities. We demonstrate through sensitivity analysis that dynamic conditions do require adjustments in the enterprise-wide flexibility spectrum.

Organizing a virtual manufacturing enterprise: an analytic network process based approach for enterprise flexibility

Virtual manufacturing is a dynamic enterprise structure that will enable future competitiveness in the fast changing business environment. This is made possible through quick IT based integration of flexible and core competent business entities capable of providing value-added product and services. Flexibility elements represent change capabilities of enterprise wide processes and resources in time and cost dimensions. Value chain considerations require synergy among the participating flexible resources. Also decision information synchronization delays need to be managed so that other entity flow processes in the enterprise remain well synchronized. This may require a capability of dynamic changes in flexible structures leading to effective virtual enterprises. There is a need to develop suitable enterprise architectures for virtual enterprises that offer an increasing focus on agility. Infrastructure support for integration of flexible capability to attain synergy among resources is necessary for enterprise agility. We conceptualize virtual manufacturing (VM) as an integrating infrastructure of flexible resources made possible through alliance of enterprises that are individually core competent in specific business function. Such a VM can attain the required cost, flexibility and responsiveness characteristics in its operations to provide solution to the demanding customer in a global dynamic market. Modelling frameworks depicting these composite flexibility states have complex and tacit interrelationship with plural business goals. Analytical network process (ANP) has been used to model the interrelationship of different decision domains with a view to prioritize enterprise wide flexibility dimensions. The ANP modelling framework takes into consideration the interdependency among sub-strategies. We demonstrate through sensitivity analysis that strategic shift is required to accommodate changes due to dynamic condition in the business environment.     

Two-level hedging point control of a manufacturing system with multiple product-types and uncertain demands

This research is motivated by the co-operative production process of networked manufacturing systems (NMS). Manufacturing resource sharing and flexible production scheduling are two features of NMS. For an individual manufacturing system in an NMS, ‘flexible production scheduling’ means that it can produce multiple product-types and the switching of products is quick enough to respond to the demand fluctuation. ‘Manufacturing resource sharing’ means the utilisation of extra production capacity from other manufacturing systems in the NMS. Of course, that will bring extra cost. This paper focuses on the optimal production control problem of such a situation: one manufacturing system, multiple product-types, and uncertain demands. Here, it is assumed that there are two demand-levels for each product-type: the lower one and the higher one. The total normal production capacity is larger than the total lower demands and smaller than the total higher demands. If the total demands cannot be satisfied and the work-in-process (WIP) of all product-types decrease to a certain level, e.g. zero WIP, the extra production capacity may be utilised. For such a system, a new two-level hedging point policy is proposed, in which two hedging points (a higher one and a lower one) are given for each product-type. Different from the prioritised hedging point (PHP) policy which is usually applied to one-machine and multiple part-type systems, our control policy considers all part-types at the same prioritised level and keeps the work-in-process states of all product-types on a straight line in the state space. Thus, the total costs for WIP inventory and the occupation of extra capacity can be obtained in a closed form, which is a function with respect to the hedging points. Then the method for optimising the hedging points is proposed and the special structure of the optimal hedging point is obtained. Numerical experiments verify the optimality and the special structure of the hedging point obtained by our method.     

Electrolyte-induced inversion layer Schottky junction solar cells

A new type of crystalline silicon solar cell is described. Superficially similar to a photoelectrochemical cell a liquid electrolyte creates a depletion (inversion) layer in an n-type silicon wafer, however no regenerative redox couple is present to ferry charge between the silicon and a counter electrode. Instead holes trapped in the electrolyte-induced inversion layer diffuse along the layer until they come to widely spaced grid lines, where they are extracted. The grid lines consist of a single-walled carbon nanotube film etched to cover only a fraction of the n-Si surface. Modeling and simulation shows the inversion layer to be a natural consequence of the device electrostatics. With electronic gating, recently demonstrated to boost the efficiency in related devices, the cell achieves a power conversion efficiency of 12%, exceeding the efficiency of dye sensitized solar cells.     

Maternal corticotropin-releasing hormone levels in the early third trimester predict length of gestation in human pregnancy

OBJECTIVE: Corticotropin releasing hormone, a hypothalamic neuropeptide, plays a major role in regulating pituitary-adrenal function and the physiologic response to stress. During pregnancy corticotropin-releasing hormone is synthesized in large amounts by the placenta and released into the maternal and fetal circulations. Various endocrine, autocrine, and paracrine roles have been suggested for placental corticotropin-releasing hormone. The aim of this study was to prospectively assess the relationship between maternal plasma concentrations of corticotropin-releasing hormone in the early third trimester of pregnancy and the length of gestation in two groups of deliveries, with and without spontaneous labor. STUDY DESIGN: In a sample of 63 women with singleton intrauterine pregnancies, maternal plasma samples were collected between 28 and 30 weeks' gestation and corticotropin-releasing hormone concentrations were determined by radioimmunoassay. Each pregnancy was dated on the basis of last menstrual period and early ultrasonography. Parity, antepartum risk conditions, presence or absence of spontaneous labor, and birth outcomes were abstracted from the medical record. RESULTS: Maternal corticotropin-releasing hormone levels between 28 and 30 weeks' gestation significantly and negatively predicted gestational length (P < .01) after adjustment for antepartum risk. Moreover, subjects who were delivered preterm had significantly higher corticotropin-releasing hormone levels in the early third trimester (P < .01) than did those who were delivered at term. In deliveries preceded by spontaneous onset of labor, maternal third-trimester corticotropin-releasing hormone levels significantly and independently predicted earlier onset of labor (P < .01) and preterm labor (P < .05), whereas in deliveries effected by induction of labor or cesarean delivery, maternal corticotropin-releasing hormone levels were a marker of antepartum risk but not a statistically independent predictor of gestational length. CONCLUSION: These findings support the premise that placental corticotropin-releasing hormone is potentially implicated in the timing of human delivery in at least two ways. First, placental corticotropin-releasing hormone may play a role in the physiology of parturition. Premature or accelerated activation of the placental corticotropin-releasing hormone system, as reflected by precocious elevation of maternal corticotropin-releasing hormone levels, may therefore be associated with earlier onset of spontaneous labor and resultant delivery. Second, placental corticotropin-releasing hormone may be a marker of antepartum risk for preterm delivery and therefore an indirect predictor of earlier delivery. The implications of these findings are discussed in the context of the neuroendocrinology of placental corticotropin-releasing hormone and human parturition. Furthermore, the role of corticotropin-releasing hormone as a possible effector of prenatal stress in producing alterations in the timing of normal delivery is detailed.