Big Data Analytics for Crisis Management From an Information Processing Theory Perspective: A Multimethodological Study

COVID-19 pandemic has created disruptions and risks in global supply chains. Big data analytics (BDA) has emerged in recent years as a potential solution for provisioning predictive and pre-emptive information to companies in order to preplan and mitigate the impacts of such risks. The focus of this article is to gain insights into how BDA can help companies combat a crisis like COVID-19 via a multimethodological scientific study. The advent of a crisis like COVID-19 brings with it uncertainties, and information processing theory (IPT) provides a perspective on the ways to deal with such uncertainties. We use IPT, in conjunction with the Crisis Management Theory, to lay the foundation of the article. After establishing the theoretical basis, we conduct two surveys towards supply chain managers, one before and one after the onset of the COVID-19 pandemic in India. We follow it up with qualitative interviews to gain further insights. The application of multiple methods helps ensure the triangulation of results and, hence, enhances the research rigor. Our research finds that although the current adoption of BDA in the Indian industry has not grown to a statistically significant level, there are serious future plans for the industry to adopt BDA for crisis management. The interviews also highlight the current status of adoption and the growth of BDA in the Indian industry. The article interestingly identifies that the traditional barriers to implementing new technologies (like BDA for crisis management) are no longer present in the current times. The COVID-19 pandemic has hence accelerated technology adoption and at the same time uncovered some BDA implementation challenges in practice (e.g., a lack of data scientists)

Enhancing Fashion Sustainability Through a Data Systemic Approach

Today everyday life is characterized by the interaction with an ever-increasing flow of digital data. The research aims to analyze the fashion industry as a data-driven enterprise in which the correlation of data characterized by greater information power and higher quality gives the chance to make a more informed decision making that lead to undertaking better and more sustainable actions in all the value chain. Data, in this focus, could have the power of increasing the efficiency of the system and reducing its impact at the same time, creating a new model that is not only able to improve environmental, economic and social sustainability but also communicative, enabling a more human-centered products and services designing. This research highlights the importance of giving an integrated and holistic perspective through a data systemic approach to deal with a complex and fragmented sustainable problem, proposing an information flow strategy that makes accessible information improving transparency and traceability. This paper presents several case studies that show how data-oriented projects can contribute some benefits to a fashion system that has environmental sustainability as its priority, but also that the lack of correlation of all these strategies is not yet able to generate and lead to a systemic change

Green product development under competition: A study of the fashion apparel industry

Motivated by the observed industrial issues, we analytically develop a fashion supply chain consisting of one manufacturer and two competing retailers and investigate how retail competition and consumer returns affect green product development in fashion apparel. In the basic model, that is, the pure “product greenness level” game, we find that the optimal greenness level of the fashion product decreases along with the level of market competition. This finding implies that a more competitive market leads to a lower optimal greenness level. We also identify that when the consumer return rate increases, the optimal product greenness level is substantially reduced. In the extended model with joint decisions on greenness and pricing, we find that the optimal product greenness level for the whole channel is always higher in the scenario when both retailers charge a higher retail price than in the case with a lower retail price. As such, the underdevelopment of green fashion products is a result of fashion industry features, such as an extremely competitive environment for green product development, relatively low retail prices for fashion products, and high consumer return rates. Therefore, fashion companies should join a co-opetition game for the green product market and simultaneously enhance their efficiency in managing consumer returns. To support our analytical findings, we conduct extensive industrial interviews with various representative companies. Based on this multi-methodological approach (MMA), this paper generates practice-relevant managerial insights that not only contribute to the literature, but also act as valuable references for industrialists

Determining Principal Component Cardinality through the Principle of Minimum Description Length

PCA (Principal Component Analysis) and its variants areubiquitous techniques for matrix dimension reduction and reduced-dimensionlatent-factor extraction. One significant challenge in using PCA, is thechoice of the number of principal components. The information-theoreticMDL (Minimum Description Length) principle gives objective compression-based criteria for model selection, but it is difficult to analytically applyits modern definition - NML (Normalized Maximum Likelihood) - to theproblem of PCA. This work shows a general reduction of NML prob-lems to lower-dimension problems. Applying this reduction, it boundsthe NML of PCA, by terms of the NML of linear regression, which areknown.Comment: LOD 201

时尚的艺术变脸——时尚产业艺术潮之解析

2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Sales rebate contracts in fashion supply chains

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Prevalence of albuminuria and cardiovascular risk profile in a referred cohort of patients with type 2 diabetes: An Asian perspective

Background: Microalbuminuria (MA) is a risk marker for diabetic nephropathy and cardiovascular (CV) disease (CVD) in patients with diabetes. This study aimed to describe the prevalence of albuminuria, CV risk factors, and treatments for renal and CV protection in an Asian population with type 2 diabetes. Methods: This cross-sectional study conducted in eight Asian countries enrolled normotensive/hypertensive adults with type 2 diabetes without known proteinuria and/or non-diabetic kidney disease. Exclusion criteria were type 1 diabetes, menstruation, pregnancy, and acute fever. A single random urinary albumin/creatinine test was carried out in all patients. Results: Of 8,561 patients, 14% had diabetic retinopathy, and 17% and 21% had history of CV disease and smoking, respectively. Normoalbuminuria was seen in 44%, MA in 44%, and macroalbuminuria in 12%. Target glycosylated hemoglobin (HbA1c) (<7%) was reached in only 37% of 3,834 patients with available values. Diabetes was managed by diet alone in 6%, while others received oral hypoglycemic drugs and/or insulin. In total, 75% did not reach target blood pressure (BP) of ≤130/80 mm Hg. Antihypertensive drugs were prescribed to 52%, with the number of drugs increasing as the level of systolic BP increased. Drugs blocking the renin-angiotensin system were most commonly prescribed, followed by calcium channel blockers. Lipid-lowering drugs and anticoagulant/antiplatelet agents were used in about 30% and 25% of patients, respectively. Conclusions: Asian patients with type 2 diabetes had a high prevalence of MA and reduced kidney function. Furthermore, BP and HbA1c control was only achieved in a minority of patients. Aggressive risk management by administration of reno- and cardioprotective treatments is urgently needed. © 2008 Mary Ann Liebert, Inc.published_or_final_versio

An approximate model for cancellous bone screw fixation

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2013 Taylor & Francis.This paper presents a finite element (FE) model to identify parameters that affect the performance of an improved cancellous bone screw fixation technique, and hence potentially improve fracture treatment. In cancellous bone of low apparent density, it can be difficult to achieve adequate screw fixation and hence provide stable fracture fixation that enables bone healing. Data from predictive FE models indicate that cements can have a significant potential to improve screw holding power in cancellous bone. These FE models are used to demonstrate the key parameters that determine pull-out strength in a variety of screw, bone and cement set-ups, and to compare the effectiveness of different configurations. The paper concludes that significant advantages, up to an order of magnitude, in screw pull-out strength in cancellous bone might be gained by the appropriate use of a currently approved calcium phosphate cement

Environment influences on the aromatic character of nucleobases and amino acids

Geometric (HOMA) and magnetic (NICS) indices of aromaticity were estimated for aromatic rings of amino acids and nucleobases. Cartesian coordinates were taken directly either from PDB files deposited in public databases at the finest resolution available (≤1.5 Å), or from structures resulting from full gradient geometry optimization in a hybrid QM/MM approach. Significant environmental effects imposing alterations of HOMA values were noted for all aromatic rings analysed. Furthermore, even extra fine resolution (≤1.0 Å) is not sufficient for direct estimation of HOMA values based on Cartesian coordinates provided by PDB files. The values of mean bond errors seem to be much higher than the 0.05 Å often reported for PDB files. The use of quantum chemistry geometry optimization is strongly advised; even a simple QM/MM model comprising only the aromatic substructure within the QM region and the rest of biomolecule treated classically within the MM framework proved to be a promising means of describing aromaticity inside native environments. According to the results presented, three consequences of the interaction with the environment can be observed that induce changes in structural and magnetic indices of aromaticity. First, broad ranges of HOMA or NICS values are usually obtained for different conformations of nearest neighborhood. Next, these values and their means can differ significantly from those characterising isolated monomers. The most significant increase in aromaticities is expected for the six-membered rings of guanine, thymine and cytosine. The same trend was also noticed for all amino acids inside proteins but this effect was much smaller, reaching the highest value for the five-membered ring of tryptophan. Explicit water solutions impose similar changes on HOMA and NICS distributions. Thus, environment effects of protein, DNA and even explicit water molecules are non-negligible sources of aromaticity changes appearing in the rings of nucleobases and aromatic amino acids residues

Preconditioning of mesenchymal stromal cells with low-intensity ultrasound: influence on chondrogenesis and directed SOX9 signaling pathways

Background: Continuous low-intensity ultrasound (cLIUS) facilitates the chondrogenic differentiation of human mesenchymal stromal cells (MSCs) in the absence of exogenously added transforming growth factor-beta (TGFβ) by upregulating the expression of transcription factor SOX9, a master regulator of chondrogenesis. The present study evaluated the molecular events associated with the signaling pathways impacting SOX9 gene and protein expression under cLIUS. Methods: Human bone marrow-derived MSCs were exposed to cLIUS stimulation at 14 kPa (5 MHz, 2.5 Vpp) for 5 min. The gene and protein expression of SOX9 was evaluated. The specificity of SOX9 upregulation under cLIUS was determined by treating the MSCs with small molecule inhibitors of select signaling molecules, followed by cLIUS treatment. Signaling events regulating SOX9 expression under cLIUS were analyzed by gene expression, immunofluorescence staining, and western blotting. Results: cLIUS upregulated the gene expression of SOX9 and enhanced the nuclear localization of SOX9 protein when compared to non-cLIUS-stimulated control. cLIUS was noted to enhance the phosphorylation of the signaling molecule ERK1/2. Inhibition of MEK/ERK1/2 by PD98059 resulted in the effective abrogation of cLIUS-induced SOX9 expression, indicating that cLIUS-induced SOX9 upregulation was dependent on the phosphorylation of ERK1/2. Inhibition of integrin and TRPV4, the upstream cell-surface effectors of ERK1/2, did not inhibit the phosphorylation of ERK1/2 and therefore did not abrogate cLIUS-induced SOX9 expression, thereby suggesting the involvement of other mechanoreceptors. Consequently, the effect of cLIUS on the actin cytoskeleton, a mechanosensitive receptor regulating SOX9, was evaluated. Diffused and disrupted actin fibers observed in MSCs under cLIUS closely resembled actin disruption by treatment with cytoskeletal drug Y27632, which is known to increase the gene expression of SOX9. The upregulation of SOX9 under cLIUS was, therefore, related to cLIUS-induced actin reorganization. SOX9 upregulation induced by actin reorganization was also found to be dependent on the phosphorylation of ERK1/2. Conclusions: Collectively, preconditioning of MSCs by cLIUS resulted in the nuclear localization of SOX9, phosphorylation of ERK1/2 and disruption of actin filaments, and the expression of SOX9 was dependent on the phosphorylation of ERK1/2 under cLIUS