An Introduction to Statistical Learning (with Applications in R), Gareth James,Daniela Witten,Trevor Hastie and Robert Tibshirani著, Springer, 2013年8月, 430pp., 価格 59.99〓, ISBN 978-1-4614-7137-0

Input—Output Economics. By Wassily Leontief. New York and London, Oxford University Press, 1966. ix, 257 p. 914″. 60s.

Input-Output Economics.

On the sustainable perishable food supply chain network design:A dairy products case to achieve sustainable development goals

Developing methods to assemble nanomaterials into macroscopic scaffolds is of critical significance at the current stage of nanotechnology. However, the complications of the fabrication methods impede the widespread usages of newly developed materials even with the superior properties in many cases. Here, we demonstrate the feasibility of a highly-efficient and potentially-continuous fiber-spinning method to produce high-performance carbon nanotube (CNT) fiber (CNTF). The processing time is <1 min from synthesis of CNTs to fabrication of highly densified and aligned CNTFs. CNTFs that are fabricated by the developed spinning method are ultra-lightweight, strong (specific tensile strength = 4.08 ± 0.25 Ntex−1), stiff (specific tensile modulus = 187.5 ± 7.4 Ntex−1), electrically conductive (2,270 S m2kg−1), and highly flexible (knot efficiency = 48 ± 15%), so they are suitable for various high-value fabric-based applications. The tensile strength of a carbon nanotube fiber is predicted to increase as its constituent nanotubes become more perfectly and densely aligned. Here, the authors present an optimized direct-spinning and chlorosulfonic acid densification method to rapidly produce carbon nanotube fibers with excellent mechanical and electrical properties.

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Direct spinning and densification method for high-performance carbon nanotube fibers.

Introduction The negative impacts of COVID-19 have rippled through every facet of society. Understanding the multidimensional impacts of this pandemic is crucial to identify the most critical needs and to inform targeted interventions. This population survey study aimed to investigate the acute phase of the COVID-19 outbreak in terms of perceived threats and concerns, occupational and financial impacts, social impacts and stress between 3 April and 15 May 2020. Methods 6040 participants are included in this report. A multivariate linear regression model was used to identify factors associated with stress changes (as measured by the Cohen’s Perceived Stress Scale (PSS)) relative to pre-outbreak retrospective estimates. Results On average, PSS scores increased from low stress levels before the outbreak to moderate stress levels during the outbreak (p Conclusion Cross-sectional analyses showed a significant increase from low to moderate stress during the COVID-19 outbreak. Identified modifiable factors associated with increased stress may be informative for intervention development. Trial registration number NCT04369690; Results.

https://bmjopen.bmj.com/content/bmjopen/10/12/e043805.full.pdf

Social, financial and psychological stress during an emerging pandemic: observations from a population survey in the acute phase of COVID-19.

Application of Machine Learning to support production planning of a food industry in the context of waste generation under uncertainty

The current economic crisis is reflected in lower capacity expansion or even capacity contraction, closing of distant activities and reduction of lead time. However, the locations of suppliers are strongly connected with the quality of agricultural products. The transportation from distant locations can largely affect the food production business in all aspects. The article presents how the Extended Material Requirements Planning (EMRP) model enables to evaluate perturbations in lead time and temperature, and shows how distant growing areas of agricultural products, and, as a result, transportation lead times play a crucial role in the net present value calculation. In this paper, we show the impact of choosing a less distant site for growing of agricultural products, and overlapping the transportation and quarantine lead times on decreasing the perishability, hence increasing the added value in multi-level food assembly systems. Also, a case study of Spanish baby food industry is presented, using the principles of the well-developed EMRP Theory.

Location and lead-time perturbations in multi-level assembly systems of perishable goods in Spanish baby food logistics

This chapter addresses a fundamental issue in Multi-Criteria Decision-Making (MCDM) problems consisting in how to model complex scenarios. It starts by defining complex scenarios and examines the hierarchical structure followed by the AHP method, considered not suitable for modelling them, as well as their relationship with the decision-maker. It provides a hierarchical structure where it can be seen the impossibility in modelling certain characteristics, that may be fundamental in a scenario.

Eloy Hontoria

Papers

Application of Machine Learning to support production planning of a food industry in the context of waste generation under uncertainty

Location and lead-time perturbations in multi-level assembly systems of perishable goods in Spanish baby food logistics

The Hierarchical Structure

Strategic Approach in Multi-Criteria Decision Making

Uses and Limitations of the AHP Method: A Non-Mathematical and Rational Analysis