A Proposal of Standardised Data Model for Cloud Manufacturing Collaborative Networks

[EN] The growing amount of data to be handled by collaborative networks raises the need of introducing innovative solutions to fulfil the lack of affordable tools, especially for Small and Medium-Sized Enterprises, to manage and exchange data. The European H2020 Project Cloud Collaborative Manufacturing Networks develops and offers a structured data model, called Standardised Tables, as an organised framework to jointly work with existing databases to manage big data collected from different industries belonging to the CNs. The information of the Standardised Tables will be mainly used with optimisation and collaboration purposes. The paper describes an application of the Standardised Tables in one of the pilots of the aforementioned project, the automotive industry pilot, for solving the collaborative problem of a Materials Requirement Plan.The research leading to these results is in the frame of the “Cloud Collaborative Manufacturing Networks” (C2NET) project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 636909.Andres, B.; Sanchis, R.; Poler, R.; Saari, L. (2017). A Proposal of Standardised Data Model for Cloud Manufacturing Collaborative Networks. IFIP Advances in Information and Communication Technology. 560:77-85. https://doi.org/10.1007/978-3-319-65151-4_7S7785560Andres, B., Poler, R.: Models, guidelines and tools for the integration of collaborative processes in non-hierarchical manufacturing networks: a review. Int. J. Comput. Integr. Manuf. 2(29), 166–201 (2016)Zikopoulos, P., Eaton, C.: Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGraw-Hill Osborne Media, New York (2011)Zhou, B., Wang, S., Xi, L.: Data model design for manufacturing execution system. J. Manuf. Technol. Manag. 16(8), 909–935 (2005)Steven, W.: Getting the MES model – methods for system analysis. ISA Trans. 35(2), 95–103 (1996)Reda, A.: Extracting the extended entity-relationship model from a legacy relational database. Inf. Syst. 28(6), 597–618 (2003)Teorey, T.J., Yang, D., Fry, J.P.: A logical design methodology for relational database using the extended entity-relationship model. ACM Comput. Surv. 18(2), 197–222 (1986)Victor, M., Arie, S.: Representing extended entity-relationship structures in relational databases: a modular approach. ACM Trans. Database Syst. 17(3), 423–464 (1992)CORDIS Europa, Factories of the Future, H2020-EU.2.1.5.1. - Technologies for Factories of the Future (2014)H2020 Project C2NET (2015). http://cordis.europa.eu/project/rcn/193440_en.htmlAndres, B., Sanchis, R., Poler, R.: A cloud platform to support collaboration in supply networks. Int. J. Prod. Manag. Eng. 4(1), 5–13 (2016)APICS, “SCOR Framework,” Supply Chain Operations Reference model (SCOR) (2017)Orbegozo, A., Andres, B., Mula, J., Lauras, M., Monteiro, C., Malheiro, M.: An overview of optimization models for integrated replenishment and producction planning decisions. In: Building Bridges Between Researchers and Practitioners. Book of Abstracts of the International Joint Conference CIO-ICIEOM-IISE-AIM (IJC2016), p. 68 (2016)Andres, B., Poler, R., Saari, L., Arana, J., Benaches, J.V., Salazar, J.: Optimization models to support decision-making in collaborative networks: a review. In: Building Bridges Between Researchers and Practitioners. Book of Abstracts of the International Joint Conference CIO-ICIEOM-IISE-AIM (IJC2016), p. 70 (2016)Andres, B., Sanchis, R., Lamothe, J., Saari, L., Hauser, F.: Combined models for production and distribution planning in a supply chain. In: Building Bridges Between Researchers and Practitioners. Book of Abstracts of the International Joint Conference CIO-ICIEOM-IISE-AIM (IJC2016), p. 71 (2016

Relay of affective stimuli from amygdala to thalamus parallels sensory pathways

The amygdala, the emotional sensor of the brain, is strongly connected with the posterior orbitofrontal cortex (pOFC), forming a pathway activated by reward learning. In addition, the amygdala innervates neurons in the mediodorsal thalamic nucleus (MD) that project to pOFC, forming a second, indirect route for the amygdala to inuence the pOFC sector of the prefrontal cortex. The indirect pathway that connects the amygdala and pOFC through the thalamus may be similar to sensory pathways connecting peripheral receptors with sensory cortices through sensory relay thalamic nuclei. The indirect pathway is morphologically distinct from the direct pathway; amygdalar pathway terminals in MD are larger than those in the pOFC, and likely derive from separate neuronal populations in the amygdala (Timbie and Barbas, Society for Neuroscience, 2013; J Neurosci, 2015). The synaptic interactions and potential specializations of amygdalar terminals in MD have not yet been described in comparison to other thalamic afferents. We addressed this issue by labeling amygdalar axons in MD in rhesus monkeys and compared them with retinal axons terminating in the lateral geniculate nucleus (LGN). We studied axon terminations in MD and LGN using serial section electron microscopy and analyzed pre- and post-synaptic elements by morphology. All amygdalar terminals in MD and retinal ganglion terminals in LGN contained multiple mitochondria, and were classed as round, large (RL) boutons. Amygdalar and retinal RL boutons contained excitatory type vesicles and formed several asymmetric (excitatory) synapses with dendrites of thalamocortical relay neurons and dendrites of inhibitory interneurons. In a significant proportion of these multi-synaptic arrangements, the inhibitory dendrites contained vesicles and formed symmetric synapses with the dendrite of the thalamocortical neuron. These novel findings reveal that amygdalar terminals in MD form synaptic triads, reminiscent of those found in sensory thalamic relay nuclei, like LGN. Our findings suggest that amygdalar inputs to MD can drive signals to cortex, ensuring efficient transmission of salient emotional information, akin to sensory thalamic relays.Published versio

Greening Big Data Networks: Velocity Impact

The authors investigate the impact of big data's velocity on greening IP over WDM networks. They classify the processing velocity of big data into two modes: expedited-data and relaxed-data modes. Expedited-data demands higher amount of computational resources to reduce the execution time compared with the relaxed-data. They developed a mixed integer linear programming model to progressively process big data at strategic locations, dubbed processing nodes (PNs), built into the network along the path from the source to the destination. The extracted information from the raw traffic is smaller in volume compared with the original traffic each time the data is processed, hence, reducing network power consumption. The results showed that up to 60% network power saving is achieved when nearly 100% of the data required relaxed processing. In contrast, only 15% of network power saving is gained when nearly 100% of the data required expedited processing. The authors obtained around 33% power saving in the mixed modes (i.e. when ∼50% of the data is processed in the relaxed mode and 50% of the data is processed in expedited mode), compared with the classical approach where all the processing is achieved inside the centralised data centres only

State-Dependent Architecture of Thalamic Reticular Subnetworks

Behavioral state is known to influence interactions between thalamus and cortex, which are important for sensation, action, and cognition. The thalamic reticular nucleus (TRN) is hypothesized to regulate thalamo-cortical interactions, but the underlying functional architecture of this process and its state dependence are unknown. By combining the first TRN ensemble recording with psychophysics and connectivity-based optogenetic tagging, we found reticular circuits to be composed of distinct subnetworks. While activity of limbic-projecting TRN neurons positively correlates with arousal, sensory-projecting neurons participate in spindles and show elevated synchrony by slow waves during sleep. Sensory-projecting neurons are suppressed by attentional states, demonstrating that their gating of thalamo-cortical interactions is matched to behavioral state. Bidirectional manipulation of attentional performance was achieved through subnetwork-specific optogenetic stimulation. Together, our findings provide evidence for differential inhibition of thalamic nuclei across brain states, where the TRN separately controls external sensory and internal limbic processing facilitating normal cognitive function.National Institute of Neurological Disorders and Stroke (U.S.) (NIH Pathway to Independence Career Award K99 NS 078115)Brain & Behavior Research Foundation (Young Investigator Award)National Institutes of Health (U.S.) ( Transformative R01 Award TR01-GM10498)National Institutes of Health (U.S.) (Grant R01-MH061976

Does \u2018bigger\u2019mean \u2018better\u2019? Pitfalls and shortcuts associated with big data for social research

\u2018Big data is here to stay.\u2019 This key statement has a double value: is an assumption as well as the reason why a theoretical reflection is needed. Furthermore, Big data is something that is gaining visibility and success in social sciences even, overcoming the division between humanities and computer sciences. In this contribution some considerations on the presence and the certain persistence of Big data as a socio-technical assemblage will be outlined. Therefore, the intriguing opportunities for social research linked to such interaction between practices and technological development will be developed. However, despite a promissory rhetoric, fostered by several scholars since the birth of Big data as a labelled concept, some risks are just around the corner. The claims for the methodological power of bigger and bigger datasets, as well as increasing speed in analysis and data collection, are creating a real hype in social research. Peculiar attention is needed in order to avoid some pitfalls. These risks will be analysed for what concerns the validity of the research results \u2018obtained through Big data. After a pars distruens, this contribution will conclude with a pars construens; assuming the previous critiques, a mixed methods research design approach will be described as a general proposal with the objective of stimulating a debate on the integration of Big data in complex research projecting

Parallel Driving and Modulatory Pathways Link the Prefrontal Cortex and Thalamus

Pathways linking the thalamus and cortex mediate our daily shifts from states of attention to quiet rest, or sleep, yet little is known about their architecture in high-order neural systems associated with cognition, emotion and action. We provide novel evidence for neurochemical and synaptic specificity of two complementary circuits linking one such system, the prefrontal cortex with the ventral anterior thalamic nucleus in primates. One circuit originated from the neurochemical group of parvalbumin-positive thalamic neurons and projected focally through large terminals to the middle cortical layers, resembling ‘drivers’ in sensory pathways. Parvalbumin thalamic neurons, in turn, were innervated by small ‘modulatory’ type cortical terminals, forming asymmetric (presumed excitatory) synapses at thalamic sites enriched with the specialized metabotropic glutamate receptors. A second circuit had a complementary organization: it originated from the neurochemical group of calbindin-positive thalamic neurons and terminated through small ‘modulatory’ terminals over long distances in the superficial prefrontal layers. Calbindin thalamic neurons, in turn, were innervated by prefrontal axons through small and large terminals that formed asymmetric synapses preferentially at sites with ionotropic glutamate receptors, consistent with a driving pathway. The largely parallel thalamo-cortical pathways terminated among distinct and laminar-specific neurochemical classes of inhibitory neurons that differ markedly in inhibitory control. The balance of activation of these parallel circuits that link a high-order association cortex with the thalamus may allow shifts to different states of consciousness, in processes that are disrupted in psychiatric diseases

Supply chain hybrid simulation: From Big Data to distributions and approaches comparison

The uncertainty and variability of Supply Chains paves the way for simulation to be employed to mitigate such risks. Due to the amounts of data generated by the systems used to manage relevant Supply Chain processes, it is widely recognized that Big Data technologies may bring benefits to Supply Chain simulation models. Nevertheless, a simulation model should also consider statistical distributions, which allow it to be used for purposes such as testing risk scenarios or for prediction. However, when Supply Chains are complex and of huge-scale, performing distribution fitting may not be feasible, which often results in users focusing on subsets of problems or selecting samples of elements, such as suppliers or materials. This paper proposed a hybrid simulation model that runs using data stored in a Big Data Warehouse, statistical distributions or a combination of both approaches. The results show that the former approach brings benefits to the simulations and is essential when setting the model to run based on statistical distributions. Furthermore, this paper also compared these approaches, emphasizing the pros and cons of each, as well as their differences in computational requirements, hence establishing a milestone for future researches in this domain.This work has been supported by national funds through FCT -Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2019 and by the Doctoral scholarship PDE/BDE/114566/2016 funded by FCT, the Portuguese Ministry of Science, Technology and Higher Education, through national funds, and co-financed by the European Social Fund (ESF) through the Operational Programme for Human Capital (POCH)

On the Dynamics of Closed-Loop Supply Chains under Remanufacturing Lead Time Variability

Remanufacturing practices in closed-loop supply chains (CLSCs) are often characterised by highly variable lead times due to the uncertain quality of returns. However, the impact of such variability on the dynamic benefits derived from adopting circular economy models remains largely unknown in the closed-loop literature. To fill the gap, this work analyses the Bullwhip and inventory performance of a multi-echelon CLSC with variable remanufacturing lead times under different scenarios of return rate and information transparency in the remanufacturing process. Our results reveal that ignoring such variability generally leads to an overestimation of the dynamic performance of CLSCs. We observe that enabling information transparency generally reduces order and inventory variability, but it may have negative effects on average inventory if the duration of the remanufacturing process is highly variable. Our findings result in useful and innovative recommendations for companies wishing to mitigate the negative consequences of lead time variability in CLSCs

A novel Netrin-1-sensitive mechanism promotes local SNARE-mediated exocytosis during axon branching

Developmental axon branching dramatically increases synaptic capacity and neuronal surface area. Netrin-1 promotes branching and synaptogenesis, but the mechanism by which Netrin-1 stimulates plasma membrane expansion is unknown. We demonstrate that SNARE-mediated exocytosis is a prerequisite for axon branching and identify the E3 ubiquitin ligase TRIM9 as a critical catalytic link between Netrin-1 and exocytic SNARE machinery in murine cortical neurons. TRIM9 ligase activity promotes SNARE-mediated vesicle fusion and axon branching in a Netrin-dependent manner. We identified a direct interaction between TRIM9 and the Netrin-1 receptor DCC as well as a Netrin-1–sensitive interaction between TRIM9 and the SNARE component SNAP25. The interaction with SNAP25 negatively regulates SNARE-mediated exocytosis and axon branching in the absence of Netrin-1. Deletion of TRIM9 elevated exocytosis in vitro and increased axon branching in vitro and in vivo. Our data provide a novel model for the spatial regulation of axon branching by Netrin-1, in which localized plasma membrane expansion occurs via TRIM9-dependent regulation of SNARE-mediated vesicle fusion.American Heart Association (Fellowship 0615692T)National Institutes of Health (U.S.) (Grant GM68678

Survey of advances and challenges in intelligent autonomy for distributed cyber-physical systems

With the evolution of the Internet of things and smart cities, a new trend of the Internet of simulation has emerged to utilise the technologies of cloud, edge, fog computing, and high-performance computing for design and analysis of complex cyber-physical systems using simulation. These technologies although being applied to the domains of big data and deep learning are not adequate to cope with the scale and complexity of emerging connected, smart, and autonomous systems. This study explores the existing state-of-the-art in automating, augmenting, and integrating systems across the domains of smart cities, autonomous vehicles, energy efficiency, smart manufacturing in Industry 4.0, and healthcare. This is expanded to look at existing computational infrastructure and how it can be used to support these applications. A detailed review is presented of advances in approaches providing and supporting intelligence as a service. Finally, some of the remaining challenges due to the explosion of data streams; issues of safety and security; and others related to big data, a model of reality, augmentation of systems, and computation are examined