Supply chain simulation in a Big Data context: risks and uncertainty analysis

Due to their complex and dynamic nature, Supply Chains are prone to risks that may occur at any time and place. To tackle this problem, simulation can be used. However, such models should use Big Data technologies, in order to provide the level of data and detail contained in the data sources associated to the business processes. In this regard, this paper considered a real case of an automotive electronics Supply chain. Hence, the purpose of this paper is to propose a simulation tool, which uses real industrial data, provided by a Big Data Warehouse, and use such decision-support artifact to test different types of risks. More concretely, risks in the supply and demand end of the network are analyzed. The presented results also demonstrate the possible benefits that can be achieved by using simulation in the analysis of risks in a Supply Chain.This work has been supported by FCT–Fundação para a Ciência e Tec-nologia 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 andHigher Education, through national funds, and co-financed by the European Social Fund(ESF) through the Operational Programme for Human Capital (POCH)

On the use of simulation as a Big Data semantic validator for supply chain management

Simulation stands out as an appropriate method for the Supply Chain Management (SCM) field. Nevertheless, to produce accurate simulations of Supply Chains (SCs), several business processes must be considered. Thus, when using real data in these simulation models, Big Data concepts and technologies become necessary, as the involved data sources generate data at increasing volume, velocity and variety, in what is known as a Big Data context. While developing such solution, several data issues were found, with simulation proving to be more efficient than traditional data profiling techniques in identifying them. Thus, this paper proposes the use of simulation as a semantic validator of the data, proposed a classification for such issues and quantified their impact in the volume of data used in the final achieved solution. This paper concluded that, while SC simulations using Big Data concepts and technologies are within the grasp of organizations, their data models still require considerable improvements, in order to produce perfect mimics of their SCs. In fact, it was also found that simulation can help in identifying and bypassing some of these issues.This work has been supported by 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)

Connective Tissue Growth Factor Overexpression in Cardiomyocytes Promotes Cardiac Hypertrophy and Protection against Pressure Overload

Connective tissue growth factor (CTGF) is a secreted protein that is strongly induced in human and experimental heart failure. CTGF is said to be profibrotic; however, the precise function of CTGF is unclear. We generated transgenic mice and rats with cardiomyocyte-specific CTGF overexpression (CTGF-TG). To investigate CTGF as a fibrosis inducer, we performed morphological and gene expression analyses of CTGF-TG mice and rat hearts under basal conditions and after stimulation with angiotensin II (Ang II) or isoproterenol, respectively. Surprisingly, cardiac tissues of both models did not show increased fibrosis or enhanced gene expression of fibrotic markers. In contrast to controls, Ang II treated CTGF-TG mice displayed preserved cardiac function. However, CTGF-TG mice developed age-dependent cardiac dysfunction at the age of 7 months. CTGF related heart failure was associated with Akt and JNK activation, but not with the induction of natriuretic peptides. Furthermore, cardiomyocytes from CTGF-TG mice showed unaffected cellular contractility and an increased Ca2+ reuptake from sarcoplasmatic reticulum. In an ischemia/reperfusion model CTGF-TG hearts did not differ from controls

Analysis of cannabinoids in oral fluid by liquid chromatography-tandem mass spectrometry

A sensitive method was developed for quantifying a wide range of cannabinoids in oral fluid (OF) by liquid chromatography-tandem mass spectrometry (LC-MS/MS). These cannabinoids include a dagger(9)-tetrahydrocannabinol (THC), 11-hydroxy-a dagger(9)-tetrahydrocannabinol (11-OH-THC), 11-nor-9-carboxy-a dagger(9)-tetrahydrocannabinol (THCCOOH), cannabinol (CBN), cannabidiol (CBD), a dagger(9)-tetrahydrocannabinolic acid A (THC-A), 11-nor-9-carboxy-a dagger(9)-tetrahydrocannabinol glucuronide (THCCOOH-gluc), and a dagger(9)-tetrahydrocannabinol glucuronide (THC-gluc). Samples were collected using a Quantisal (TM) device. The advantages of performing a liquid-liquid extraction (LLE) of KCl-saturated OF using heptane/ethyl acetate versus a solid-phase extraction (SPE) using HLB copolymer columns were determined. Chromatographic separation was achieved in 11.5 min on a Kinetex (TM) column packed with 2.6-mu m core-shell particles. Both positive (THC, 11-OH-THC, CBN, and CBD) and negative (THCCOOH, THC-gluc, THCCOOH-gluc, and THC-A) electrospray ionization modes were employed with multiple reaction monitoring using a high-end AB Sciex API 5000 (TM) triple quadrupole LC-MS/MS system. Unlike SPE, LLE failed to extract THC-gluc and THCCOOH-gluc. However, the LLE method was more sensitive for the detection of THCCOOH than the SPE method, wherein the limit of detection (LOD) and limit of quantification (LOQ) decreased from 100 to 50 pg/ml and from 500 to 80 pg/ml, respectively. The two extraction methods were successfully applied to OF samples collected from volunteers before and after they smoked a homemade cannabis joint. High levels of THC were measured soon after smoking, in addition to significant amounts of THC-A. Other cannabinoids were found in low concentrations. Glucuronide conjugate levels were lower than the method's LOD for most samples. Incubation studies suggest that glucuronides could be enzymatically degraded by glucuronidase prior to OF collectio