A fuzzy group decision-making model to measure resiliency in a food supply chain: A case study in Spain

The concept of supply chain management (SCM) has transformed and evolved beyond the simple rationality of benefit and economic viewpoints. With changing societal requirements in terms of the global risk-based economy, SCMs should be resilient and flexible to handle risk and quickly respond to disruptions. A food supply chain (FSC) is a critical global supply chain network due to its crucial role in meeting the growing consumer demand for edible products. Any disruptions and risks in FSC management (FSCM) may lead to irrecoverable and costly consequences; therefore, the resiliency of key players in the food SCM is very important. In this regard, this paper develops a decision-making model using the best worst method (BWM) and fuzzy measurement of alternatives and ranking according to compromise solution (fuzzy MARCOS) to measure the resiliency of key players in the FSCM with respect to different resiliency and risk factors. Sensitivity analysis tests to examine the reliability of the model are conducted. A case study of the agricultural FSCM of Andalusia Province of Spain is used to investigate the practicability of the proposed model. The results indicate that natural disasters and water system failures are two important risk factors with the highest weight coefficients, and excessive inventory was determined to be the least important risk factor. Moreover, supermarkets and wholesalers are determined to be the most resilient players in the FSCM of Andalusia Province of Spain

A gain-of-function mutation of STAT1: A novel genetic factor contributing to chronic mucocutaneous candidiasis

Heterozygous gain-of-function (GOF) mutations in the signal transducer and activator of transcription 1 (STAT1) have increasingly been identified as a genetic cause of autosomal-dominant (AD) chronic mucocutaneous candidiasis (CMC). In this article, we describe a 33-year-old man who experienced chronic refractory candidiasis, recurrent otitis media, and pneumonia resulting in bronchiectasis, severe oral and esophageal candidiases with strictures associated with hypothyroidism and immune hemolytic anemia. His son also suffered from persistent candidiasis, chronic diarrhea, poor weight gain, and pneumonia that resulted in his demise because of sepsis. The immunological workup showed that an inverse CD4/CD8 ratio and serum immunoglobulins were all within normal ranges. The laboratory data revealed failure in response to Candida lymphocyte transformation test. In addition, by Sanger sequencing method, we found a heterozygous mutation, Thr385Met (T385M), located in the DNA-binding domain of STAT1, which was previously shown to be GOF. These findings illustrate the broad and variable clinical phenotype of heterozygous STAT1 GOF mutations. However, more clinical information and phenotype–genotype studies are required to define the clinical phenotype caused by AD STAT1 GOF

Modified Block-Pulse Functions Scheme for Solve of Two-Dimensional Stochastic Integral Equations

In this paper, two-dimensional modified block-pulse functions (2D-MBPFs) method is introduced for approximate solution of 2D-linear stochastic Volterra-Fredholm integral equations so the ordinary and stochastic operrational matrices of integration are utilized to reduce the computation of such equations into some algebraic equations. Convergence analysis of this method is discussed. Finally an illustrative example is given to show the accuracy of the proposed method so the results of it is compared with the block-pulse functions (BPFs) method

Double-Shield TBM Performance Analysis in Clay Formation: A Case Study in Iran

The Konjancham conveyance tunnel is a part of the tropical water conveyance plan that is designed to transfer water to both Kermanshah and Ilam provinces in Iran. The second part of this tunnel (KT-2) is a 12 kilometers long with a diameter of 5.56 meters that is being bored using a double-shield TBM (DS-TBM) machine. The tunnel is excavated in both Aghajari and Lahbari formations, including claystone, siltstone, and sandstone. In this study, an overview of the basics of the project, including geology, engineering geology, hydrogeology, as well as the characteristics of the tunnel and the TBM, have been reviewed, firstly. Then, the field performance of the TBM is analyzed by focusing on the geological conditions and the functional parameters of the machine such as thrust force and RPM. Finally, the wear of the disc cutters was analyzed as one of the important issues in the boring process

Nonlinear genetic-based model for supplier selection: A comparative study

Evaluation and selection of candidate suppliers has become a major decision in business activities around the world. In this paper, a new hybrid approach based on integration of Gene Expression Programming (GEP) with Data Envelopment Analysis (DEA) (DEA-GEP) is presented to overcome the supplier selection problem. First, suppliers’ efficiencies are obtained through applying DEA. Then, the suppliers’ related data are utilized to train GEP to find the best trained DEA-GEP algorithm for predicting efficiency score of Decision Making Units (DMUs). The aforementioned data is also used to train Artificial Neural Network (ANN) to predict efficiency scores of DMUs. The proposed hybrid DEA-GEP is compared to integrated approach of Artificial Neural Network with Data Envelopment Analysis (DEA-ANN) to support the validity of the proposed model. The obtained results clearly show that the model based on GEP not only is more accurate than the DEA-ANN model, but also presents a mathematical function for efficiency score based on input and output data set. Finally, a real-life supplier selection problem is presented to show the applicability of the proposed hybrid DEA-GEP model.Sin financiación3.244 JCR (2017) Q1, 31/353 EconomicsUE

Green sourcing in the era of industry 4.0: towards green and digitalized competitive advantages

Purpose: In the last decade, sustainable sourcing decision has gained tremendous attention due to the increasing governmental restrictions and public attentiveness. This decision involves diverse sets of classical and environmental parameters, which are originated from a complex, ambiguous and inconsistent decision-making environment. Arguably, supply chain management is fronting the next industrial revolution, which is named industry 4.0, due to the fast advance of digitalization. Considering the latter's rapid growth, current supplier selection models are, or it will, inefficient to assign the level of priority of each supplier among a set of suppliers, and therefore, more advanced models merging “recipes” of sustainability and industry 4.0 ingenuities are required. Yet, no research work found towards a digitalized, along with sustainability's target, sourcing. Design/methodology/approach: A new framework for green and digitalized sourcing is developed. Thereafter, a hybrid decision-making approach is developed that utilizes (1) fuzzy preference programming (FPP) to decide the importance of one supplier attribute over another and (2) multi-objective optimization on the basis of ratio analysis (MOORA) to prioritize suppliers based on fuzzy performance rating. The proposed approach is implemented in consultation with the procurement department of a food processing company willing to develop a greener supply chain in the era of industry 4.0. Findings: The proposed approach is capable to recognize the most important evaluation criteria, explain the ambiguity of experts' expressions and having better discrimination power to assess suppliers on operational efficiency and environmental and digitalization criteria, and henceforth enhances the quality of the sourcing process. Sensitivity analysis is performed to help managers for model approval. Moreover, this work presents the first attempt towards green and digitalized supplier selection. It paves the way towards further development in the modelling and optimization of sourcing in the era of industry 4.0. Originality/value: Competitive supply chain management needs efficient purchasing and production activities since they represent its core, and this arises the necessity for a strategic adaptation and alignment with the requirement of industry 4.0. The latter implies alterations in the avenue firms operate and shape their activities and processes. In the context of supplier selection, this would involve the way supplier assessed and selected. This work is originally initiated based on a joint collaboration with a food company. A hybrid decision-making approach is proposed to evaluate and select suppliers considering operational efficiency, environmental criteria and digitalization initiatives towards digitalized and green supplier selection (DG-SS). To this end, supply chain management in the era of sustainability and digitalization are discussed

Sustainable supplier selection in construction industry through hybrid fuzzy-based approaches

Due to increase in the public and stakeholders’ awareness regarding economic, environ-mental, and social issues, the construction industry tends to follow the sustainability policies and practices in supply chain management. Hence, one of the most crucial aspects for a construction company in this regard is sustainable supplier selection, and, to this end, an accurate and reliable model is required. In this paper a hybrid fuzzy best-worst method and fuzzy inference system model is developed for sustainable supplier selection. In the first phase of this study, after determining 19 criteria in three main aspects, the final weight of each aspect and criterion is obtained using fuzzy best-worst method approach. In the second phase, the most sustainable supplier is selected by run-ning the weighted fuzzy inference system both in aspect and criterion level, providing more accurate results compared to the use of other available models. Finally, two different tests are employed to validate the results and evaluate the robustness of the proposed model. The novel developed model enables the decision-maker to simulate the decision-making process, reduce the calculations loads, consider a large number of criteria in decision making, and resolve the inherited uncertainties in experts’ responses

From variant of uncertain significance to likely pathogenic in two siblings with atypical RAG2 Deficiency: a case report and review of the literature

Abstract Background Severe combined immunodeficiencies (SCIDs) are hereditary disorders characterized by impaired T and B cell function, resulting in significant immune system dysfunction. Recombination-activating gene (RAG) mutations account for a substantial proportion of SCID cases. Here, we present two sibling cases of SCID caused by a novel RAG2 gene mutation. Case Presentation The index case was an 8-year-old boy who had a history of recurring infections. After a comprehensive immunological workup, the initial diagnosis of agammaglobulinemia was revised to combined immunodeficiency (CID). The patient underwent hematopoietic stem cell transplantation (HSCT) but succumbed to cytomegalovirus (CMV) infection. His brother, a 4-month-old boy, presented with CMV chorioretinitis. Leaky SCID was diagnosed based on genetic tests and immunological findings. The patient received appropriate treatment and was considered for HSCT. Both siblings had a homozygous RAG2 gene variant, with the first case classified as a variant of uncertain significance (VUS). The presence of the same mutation in the second brother, and the clinical phenotype, supports considering the mutation as likely pathogenic. Conclusions This case report highlights a novel RAG2 gene mutation associated with CID. The classification of a VUS may evolve with accumulating evidence, and additional studies are warranted to establish its pathogenicity. Proper communication between genetic counselors and immunologists, accurate documentation of patient information, increased public awareness, and precise utilization of genetic techniques are essential for optimal patient management

Cystic fibrosis and congenital adrenal hyperplasia: A rare occurrence with diagnostic dilemmas, similarities and contradictions

Cystic fibrosis (CF) is a hereditary syndrome composed of exocrine gland dysfunction involving multiple systems which if untreated may result in chronic respiratory infections, pancreatic enzyme deficiency and failure to thrive. The association between CF and other inherited diseases or congenital anomalies is rare. We describe a rare case of CF with concomitant congenital adrenal hyperplasia (CAH). 21- Hydroxylase deficiency accounts for most CAH cases. Varity in clinical phenotypes depends on the amount of enzymatic activity which in turn depends on different combination of gene mutations. The genes of CAH and CF are located in different locations. The chance of these diseases coexisting in our patient would be a rare combination. However, such a case will be more frequent in our population than others because of consanguineous marriage and common ancestors. There are diagnostic difficulties, similarities and contradictions between two diseases and they are pointed out

Periodic Severe Angioedema without Exogenous Hormone Exposure

Hereditary angioedema (HAE) is characterized by recurrent attacks of skin and mucosal swelling in any part of the body including the digestive and respiratory tract which generally improve spontaneously within 12-72 hours. The underlying mechanism in HAE is related to bradykinin dysregulation which causes these attacks not to respond to common treatment strategies including epinephrine/corticosteroid or adrenaline. There are several types of HAE with different etiology but with the same clinical picture. Type 1 is due to the deficiency of C1 Inhibitor (C1-INH) protein and type 2 is related to dysfunctional C1-INH protein. The third type of HAE which comprises the minority of cases is associated with the normal amount and function of C1-INH protein. The presented case in this report was a 15-years old girl with a history of spontaneous angioedema attacks from the age of 14. The frequency of attacks was initially every two months but consequently increased to every two weeks after using some hormonal medications for ovarian cyst. Each episode has lasted around 10 days without any symptoms in between. Complement studies including C4, C1q, and C1-INH protein, both quantitative and qualitative, were reported as normal. A genetic assessment revealed a mutation in the exon 9 on the gene related to factor XII, hence the diagnosis of HAE type 3 was confirmed. This was a rare type of angioedema with normal amount and function of C1-INH protein which is predominantly seen in women during periods of imbalanced estrogen increments like pregnancy, lactation, and menopause, and hence it is responsive to hormonal manipulation strategies such as the use of progesterone containing medications.