A General Simulation Framework for Supply Chain Modeling: State of the Art and Case Study

Nowadays there is a large availability of discrete event simulation software that can be easily used in different domains: from industry to supply chain, from healthcare to business management, from training to complex systems design. Simulation engines of commercial discrete event simulation software use specific rules and logics for simulation time and events management. Difficulties and limitations come up when commercial discrete event simulation software are used for modeling complex real world-systems (i.e. supply chains, industrial plants). The objective of this paper is twofold: first a state of the art on commercial discrete event simulation software and an overview on discrete event simulation models development by using general purpose programming languages are presented; then a Supply Chain Order Performance Simulator (SCOPS, developed in C++) for investigating the inventory management problem along the supply chain under different supply chain scenarios is proposed to readers.Comment: International Journal of Computer Science Issues online at http://ijcsi.org/articles/A-General-Simulation-Framework-for-Supply-Chain-Modeling-State-of-the-Art-and-Case-Study.ph

Need (more than) two to Tango: Multiple tools to adapt to changes in oxygen availability

Oxygen is a fundamental element for the life of a large number of living organisms allowing an efficient energetic utilization of substrates. Organisms relying on oxygen evolved complex structures for oxygen delivery and biochemical machineries dealing with its safe utilization and the ability to overcome the potentially harmful consequences of changes in oxygen availability. On fact, cells composing complex Eukaryotic organisms are set to live within an optimum narrow range of oxygen, quite specific for each cell type. Minute modifications of oxygen availability, either positive or negative, induce the expression of specific genes, the major actors of this responses being the transcription factors HIF and Nrf2 that control the attempt to cope with low oxygen (hypoxia) or to either high oxygen or to an oxygen “overflow,” respectively. This review describes the interaction between these two transcription factors and their interaction with the transcription factor NF-kB acting as a pivotal determinant of final cel

A Novel Approach to Fuzzy Clustering based on a Dissimilarity Relation extracted from Data using a TS System

Clustering refers to the process of unsupervised partitioning of a data set based on a dissimilarity measure, which determines the cluster shape. Considering that cluster shapes may change from one cluster to another, it would be of the utmost importance to extract the dissimilarity measure directly from the data by means of a data model. On the other hand, a model construction requires some kind of supervision of the data structure, which is exactly what we look for during clustering. So, the lower the supervision degree used to build the data model, the more it makes sense to resort to a data model for clustering purposes. Conscious of this, we propose to exploit very few pairs of patterns with known dissimilarity to build a TS system which models the dissimilarity relation. Among other things, the rules of the TS system provide an intuitive description of the dissimilarity relation itself. Then we use the TS system to build a dissimilarity matrix which is fed as input to an unsupervised fuzzy relational clustering algorithm, denoted any relation clustering algorithm (ARCA), which partitions the data set based on the proximity of the vectors containing the dissimilarity values between each pattern and all the other patterns in the data set. We show that combining the TS system and the ARCA algorithm allows us to achieve high classification performance on a synthetic data set and on two real data sets. Further, we discuss how the rules of the TS system represent a sort of linguistic description of the dissimilarity relation

Prenatal Exposure to Ethanol Causes Differential Effects in Nerve Growth Factor and its Receptor in the Basal Forebrain of Preweaning and Adult Rats

In this study we investigated nerve growth factor (NGF) levels in the cortex and hippocampus of the offspring of pregnant female Sprague-Dawley rats receiving a single intragastric administration of acute ethanol on the 15th day of gestation and compared them with a control group of rats that received an injection of sucrose. We also examined the distribution of the low-affinity NGF receptor, p75NGFR, on NGF-responsive neurons that are localized in the septum and the nucleus of Meynert, which receive the respective trophic support from the hippocampus and the cortex. In the ethanol-treated group, the results show that at post-natal age 15 days, the NGF septohippocampal pathways were markedly affected. At day 15, the NGF level was significantly higher in the offspring of ethanol-treated rats. By day 40, NGF values in both groups decreased to similar levels. At day 60, however, the NGF level in the ethanol-treated animals decreased to a significantly lower value than that of the control group, which remained essentially unchanged. In parallel, at day 60 the numbers of septal cholinergic neurons expressing p75NGFR were also significantly lower in ethanol-treated rats than in control animals. Because ethanol is known to induce neurological disorders, as well as deficits in cell proliferation and differentiation, the results suggest that one cause of the deleterious effects induced by ethanol is the low availability of NGF during certain stages of postnatal brain development

Life-Threatening Constipation Induced by Intrathecal Baclofen Therapy

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Sustained molecular remission after low dose gemtuzumab-ozogamicin in elderly patients with advanced acute promyelocytic leukemia.

We report here a preliminary experience with gemtuzumab ozogamicin (GO) used at low dosage (3 mg/m2) in 3 elderly patients with acute promyelocytic leukaemia (APL) who presented molecular relapse and were unfit for intensive chemotherapy

Spasticity and Dystonia: A Brief Review

Spasticity and dystonia are two neurological conditions with a broad range of clinical manifestations that can emerge at any age. Although the spasticity and dystonia symptoms are caused by different pathophysiological mechanisms, both of them may cause functional impairment that contributes to a poor quality of life. Spasticity is characterised by a velocity-dependent increase in tonic stretch reflexes with exaggerated tendon jerks, resulting from hyperexcitability of the stretch reflex. It mostly occurs in disorders of the central nervous system (CNS) affecting the upper motor neurons, such as multiple sclerosis, amyotrophic lateral sclerosis, cerebrovascular diseases, cerebral palsy, traumatic brain injury, stroke, and spinal cord injury. Therapeutic options may combine, in various proportions, physical therapy, occupational therapy, self-rehabilitation, the use of orthoses and assistive devices, drug treatment, orthopaedic surgery, and neurosurgery. Dystonia is defined as a syndrome of involuntary movement that manifests as excessive muscle contractions that frequently cause twisting and repetitive movements or abnormal postures. It is often intensified or exacerbated by physical activity, and symptoms may progress into adjacent muscles. Dystonia has many different manifestations and causes, and many different treatment options are available. These options include physical and occupational therapy, oral medications, intramuscular injection of botulinum toxins, and neurosurgical interventions

An adaptive stigmergy-based system for evaluating technological indicator dynamics in the context of smart specialization

Regional innovation is more and more considered an important enabler of welfare. It is no coincidence that the European Commission has started looking at regional peculiarities and dynamics, in order to focus Research and Innovation Strategies for Smart Specialization towards effective investment policies. In this context, this work aims to support policy makers in the analysis of innovation-relevant trends. We exploit a European database of the regional patent application to determine the dynamics of a set of technological innovation indicators. For this purpose, we design and develop a software system for assessing unfolding trends in such indicators. In contrast with conventional knowledge-based design, our approach is biologically-inspired and based on self-organization of information. This means that a functional structure, called track, appears and stays spontaneous at runtime when local dynamism in data occurs. A further prototyping of tracks allows a better distinction of the critical phenomena during unfolding events, with a better assessment of the progressing levels. The proposed mechanism works if structural parameters are correctly tuned for the given historical context. Determining such correct parameters is not a simple task since different indicators may have different dynamics. For this purpose, we adopt an adaptation mechanism based on differential evolution. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach, experimental setting and results

Phenolic Profiles, Antioxidant and Anti-Inflammatory Activities of Hydrodistillation Wastewaters from Five Lamiaceae Species

Distillation is the most widely used method to obtain an essential oil from plant material. The biomass used in the process is returned as a solid residue together with variable amounts of water rich in water-soluble compounds, which currently are not addressed to any further application. The scope of this work was to evaluate the phytochemical composition of wastewaters coming from hydrodistillation (DWWs) of five aromatic plants belonging to the Lamiaceae family, and to assess their in vitro antioxidant and anti-inflammatory activities. The phenolic profiles of the DWWs were determined by HPLC-DAD and HPLC-ESI/MS. Free radical scavenging ability, oxygen radical antioxidant capacity and superoxide dismutase mimetic activity of the samples under study were measured. Moreover, to investigate the anti-inflammatory activity of the DWWs, an in vitro experimental model of intestinal inflammation was used. The DWW samples' phytochemical analysis allowed the identification of 37 phenolic compounds, all exhibiting good antioxidant and anti-inflammatory activity. Our study contributes to the knowledge on the polyphenolic composition of the DWWs of five aromatic plants of the Lamiaceae family. The results highlight the presence of compounds with proven biological activity, and therefore of great interest in the pharmaceutical and nutraceutical fields