Improved Decision-Making through a DEMATEL and Fuzzy Cognitive Maps-Based Framework

The decision-making process is highly demanding. There has been an increasing tendency to incorporate human thinking, individual experience about a problem, and pure mathematical approaches. Here, a novel integrated approach is investigated and proposed to develop an advanced hybrid decision-support system based on the decision-making trial and evaluation laboratory (DEMATEL) and fuzzy cognitive maps (FCMs). Indeed, knowledge acquisition and elicitation may present distortions and difficulties finding a consensus and an interpretation. Thus, the proposed combined approach aims to examine in depth the potential to improve FCMs' outcomes by integrating FCM with the DEMATEL approach. The combined methodology achieves at avoiding some of the drawbacks, such as the lack of a standardized FCM theoretical model. Thus, it provides advanced comparative analysis and results in better interpretation of the decision-making process. It is highlighted that the traditional FCM approach does not allow distinguishing the whole number of defined scenarios, in contrast to the hybrid one presented here, which increases the ability of users to make correct decisions. Combining the two approaches provides new capabilities to FCMs in grouping experts' knowledge, while the DEMATEL approach contributes to refining the strength of concepts' connections

Deciding a multicriteria decision-making (Mcdm) method to prioritize maintenance work orders of hydroelectric power plants

The current global competitive scenario and the increase in complexity and automation of equipment and systems demand better results from maintenance management in organizations. As maintenance resources are limited, prioritizing maintenance activities is essential to allocate them properly and to meet maintenance management objectives. In the face of these challenges, multicriteria decision-making (MCDM) methods are commonly used in organizations to support decision-making. Nevertheless, selecting a suitable MCDM method for maintenance planning can be complicated given the diversity of methods and their strengths and weaknesses. In this context, this paper proposes a novel knowledge-based method for deciding a multicriteria decision-making (MCDM) method to prioritize maintenance work orders of hydroelectric plants. As the main novel contribution, it translates the intrinsic characteristics of the main MCDM methods into questions related to maintenance planning to guide the recommendation of a suitable MCDM method for organizations through a decision tree diagram. This approach was applied to a maintenance case study of a hydroelectric power plant in order to demonstrate its use and contribute to its understanding. These findings contribute to maintenance management in selecting an MCDM method aligned with the context of its maintenance planning for the prioritization of maintenance work orders

Designing an Efficient Production System: A Case Study of a Clothing Company

This paper is based on a discrete-event simulation model and reproduces the sewing department of a clothing company involved in the fashion industry. It aims to quantitatively assess the effects of different production configurations on flow time and production In particular, the production phases of men’s jackets are examined. Eight configurations are evaluated, stemming from the combination of two parameters: batch size and number of machines. For each configuration, the flow time, the production capacity and the waiting time are computed. A subsequent Design of Experiment (DoE) analysis has been performed on these configurations, with the aim of identifying significant single and combined effects of the above parameters on the results observed. The goal is to obtain improvements in the production process. The data provided by the simulation is used in order to make a critical analysis of the system production and leads to the formation of proposals for the improvement of the lay-out

U and Th content in the Central Apennines continental crust: a contribution to the determination of the geo-neutrinos flux at LNGS

The regional contribution to the geo-neutrino signal at Gran Sasso National Laboratory (LNGS) was determined based on a detailed geological, geochemical and geophysical study of the region. U and Th abundances of more than 50 samples representative of the main lithotypes belonging to the Mesozoic and Cenozoic sedimentary cover were analyzed. Sedimentary rocks were grouped into four main "Reservoirs" based on similar paleogeographic conditions and mineralogy. Basement rocks do not outcrop in the area. Thus U and Th in the Upper and Lower Crust of Valsugana and Ivrea-Verbano areas were analyzed. Based on geological and geophysical properties, relative abundances of the various reservoirs were calculated and used to obtain the weighted U and Th abundances for each of the three geological layers (Sedimentary Cover, Upper and Lower Crust). Using the available seismic profile as well as the stratigraphic records from a number of exploration wells, a 3D modelling was developed over an area of 2^{\circ}x2^{\circ} down to the Moho depth, for a total volume of about 1.2x10^6 km^3. This model allowed us to determine the volume of the various geological layers and eventually integrate the Th and U contents of the whole crust beneath LNGS. On this base the local contribution to the geo-neutrino flux (S) was calculated and added to the contribution given by the rest of the world, yielding a Refined Reference Model prediction for the geo-neutrino signal in the Borexino detector at LNGS: S(U) = (28.7 \pm 3.9) TNU and S(Th) = (7.5 \pm 1.0) TNU. An excess over the total flux of about 4 TNU was previously obtained by Mantovani et al. (2004) who calculated, based on general worldwide assumptions, a signal of 40.5 TNU. The considerable thickness of the sedimentary rocks, almost predominantly represented by U- and Th- poor carbonatic rocks in the area near LNGS, is responsible for this difference.Comment: 45 pages, 5 figures, 12 tables; accepted for publication in GC

Passive immunotherapy for N-truncated tau ameliorates the cognitive deficits in two mouse AD models

Clinical and neuropathological studies have shown that tau pathology better correlates with the severity of dementia than amyloid plaque burden, making tau an attractive target for the cure of Alzheimer\u2019s disease. We have explored whether passive immunization with the 12A12 monoclonal antibody (26\u201336aa of tau protein) could improve the Alzheimer\u2019s disease phenotype of two well-established mouse models, Tg2576 and 3xTg mice. 12A12 is a cleavage-specific monoclonal antibody which selectively binds the pathologically relevant neurotoxic NH226-230 fragment (i.e. NH2htau) of tau protein without cross-reacting with its full-length physiological form(s). We found out that intravenous administration of 12A12 monoclonal antibody into symptomatic (6 months old) animals: (i) reaches the hippocampus in its biologically active (antigen-binding competent) form and successfully neutralizes its target; (ii) reduces both pathological tau and amyloid precursor protein/amyloid\u3b2 metabolisms involved in early disease-associated synaptic deterioration; (iii) improves episodic-like type of learning/memory skills in hippocampal-based novel object recognition and object place recognition behavioural tasks; (iv) restores the specific up-regulation of the activity-regulated cytoskeleton-associated protein involved in consolidation of experience-dependent synaptic plasticity; (v) relieves the loss of dendritic spine connectivity in pyramidal hippocampal CA1 neurons; (vi) rescues the Alzheimer\u2019s disease-related electrophysiological deficits in hippocampal long-term potentiation at the CA3-CA1 synapses; and (vii) mitigates the neuroinflammatory response (reactive gliosis). These findings indicate that the 20\u201322 kDa NH2-terminal tau fragment is crucial target for Alzheimer\u2019s disease therapy and prospect immunotherapy with 12A12 monoclonal antibody as safe (normal tau-preserving), beneficial approach in contrasting the early Amyloid\u3b2-dependent and independent neuropathological and cognitive alterations in affected subject

Inhibition of Notch3 signalling induces rhabdomyosarcoma cell differentiation promoting p38 phosphorylation and p21Cip1 expression and hampers tumour cell growth in vitro and in vivo

Rhabdomyosarcoma (RMS) is a paediatric soft-tissue sarcoma arising from skeletal muscle precursors coexpressing markers of proliferation and differentiation. Inducers of myogenic differentiation suppress RMS tumourigenic phenotype. The Notch target gene HES1 is upregulated in RMS and prevents tumour cell differentiation in a Notch-dependent manner. However, Notch receptors regulating this phenomenon are unknown. In agreement with data in RMS primary tumours, we show here that the Notch3 receptor is overexpressed in RMS cell lines versus normal myoblasts. Notch3-targeted downregulation in RMS cells induces hyper-phosphorylation of p38 and Akt essential for myogenesis, resulting in the differentiation of tumour cells into multinucleated myotubes expressing Myosin Heavy Chain. These phenomena are associated to a marked decrease in HES1 expression, an increase in p21Cip1 level and the accumulation of RMS cells in the G1 phase. HES1-forced overexpression in RMS cells reverses, at least in part, the pro-differentiative effects of Notch3 downregulation. Notch3 depletion also reduces the tumourigenic potential of RMS cells both in vitro and in vivo. These results indicate that downregulation of Notch3 is sufficient to force RMS cells into completing a correct full myogenic program providing evidence that it contributes, partially through HES1 sustained expression, to their malignant phenotype. Moreover, they suggest Notch3 as a novel potential target in human RMS