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This paper proposes a literature review about the usage of simulation-based optimization tools in hospital environment and, more precisely, for operating rooms management. The usage of simulation, in its various forms, is gaining increasing attention in healthcare management because of its capability of describing the system in a high degree of detail as well as of modelling scenarios with different levels of available resources or uncertainty. In this respect, the contribution of this review study consists of classifying the literature about the topic, delineating the most debated themes and their internal relationships, and identifying the most prominent authors and papers. These results are achieved using a combination of bibliographic and bibliometric tools, commonly adopted in review studies, on a sample of 82 papers. On the basis of the findings, opportunities for future research activities are delineated.

PurposeThe aim of this paper is to explore whether open innovation is emerging in the Italian fashion industry.Design/methodology/approachBased on available studies on innovation and open innovation, we first identified the main facets of open innovation within the industry investigated, such as the process of searching for new ideas, the involvement of external partners in the new product development process and the use of collaboration mechanisms between supply chain partners. Starting from these findings, the authors designed a semi-structured questionnaire that was used as a guideline for 15 case studies, carried out in the Italian fashion industry.FindingsThe outcomes from the case studies allow drawing some conclusions about the emergency of open innovation in the fashion industry and the related patterns.Originality/valueGiven its exploratory nature, this study is expected to start a debate about open innovation in the fashion industry, as well as to encourage future studies in this field.

Supply chain risk management is considered a topic of increasing interest worldwide and its focus has evolved over time. The recent coronavirus pandemic (known as COVID-19) has forced business to handle a new global crisis and rapidly adapt to unexpected challenges. In an attempt to help companies counteract the pandemic risk, as well as to fuel the scientific discussion about this topic, this paper proposes a systematic literature review on risk management and disruptions in the supply chain focusing on quantitative models and paying a particular attention to highlighting the potentials of the studies reviewed for being applied to counteract pandemic emergencies. An appropriate query was made on Scopus and returned, after a manual screening, a useful set of 99 papers that proposed models for supply chain risk management. The relevant aspects of pandemics risk management have been first identified and mapped; then, the studies reviewed have been analysed with the aim of evaluating their suitability of being applied to sanitary crises. In carrying out this review of the literature, the study moves from previous, more general, reviews about risk management and updates them, starting from the lines of research that have been covered in recent years and evaluating their consistency with future research directions emerging also as a consequence of the pandemic crisis. Gaps and limitations of the existing models are identified and future research directions for pandemics risk management are suggested.

Radio frequency identification technology offers various potential benefits compared to the traditional systems of automatic identification, such as barcodes or manual data entry. Thanks to non-contact reading, no need for human intervention and real time information update, that technology increases the speed of identification, material, and information flow and plays an important role in various logistics activities. This is why, since its introduction, radio frequency identification has always been indicated by researchers and practitioners as the technology that will have changed the way of managing logistics and supply chain processes. By means of a systematic literature review on 95 selected papers, this study proposes an examination of radio frequency identification applications targeting the logistics field, with the purpose of categorizing the available knowledge, examining the state-of-the-art solutions and highlighting the key benefits of the technology within the logistics sector. As a result, the trends of the topics treated in studies targeting radio frequency identification in logistics are delineated. Suggestions for future research directions are provided.

Nephronophthisis (NPH) is an autosomal-recessive ciliopathy representing one of the most frequent causes of kidney failure in childhood characterized by a broad clinical and genetic heterogeneity. Applied to one of the worldwide largest cohorts of patients with NPH, genetic analysis encompassing targeted and whole exome sequencing identified disease-causing variants in 600 patients from 496 families with a detection rate of 71%. Of 788 pathogenic variants, 40 known ciliopathy genes were identified. However, the majority of patients (53%) bore biallelic pathogenic variants in NPHP1. NPH-causing gene alterations affected all ciliary modules defined by structural and/or functional subdomains. Seventy six percent of these patients had progressed to kidney failure, of which 18% had an infantile form (under five years) and harbored variants affecting the Inversin compartment or intraflagellar transport complex A. Forty eight percent of patients showed a juvenile (5-15 years) and 34% a late-onset disease (over 15 years), the latter mostly carrying variants belonging to the Transition Zone module. Furthermore, while more than 85% of patients with an infantile form presented with extra-kidney manifestations, it only concerned half of juvenile and late onset cases. Eye involvement represented a predominant feature, followed by cerebellar hypoplasia and other brain abnormalities, liver and skeletal defects. The phenotypic variability was in a large part associated with mutation types, genes and corresponding ciliary modules with hypomorphic variants in ciliary genes playing a role in early steps of ciliogenesis associated with juvenile-to-late onset NPH forms. Thus, our data confirm a considerable proportion of late-onset NPH suggesting an underdiagnosis in adult chronic kidney disease.

C9orf72 repeat expansions are rarely associated with primary progressive aphasias (PPA). In-depth characterization of the linguistic deficits, and the underlying patterns of grey-matter atrophy in PPA associated with the C9orf72 expansions (PPA-C9orf72) are currently lacking. In this study, we comprehensively analyzed a unique series of 16 patients affected by PPA-C9orf72. Eleven patients were issued from two independent French and Finnish cohorts, and five were identified by means of literature review. Voxel-based morphometry (VBM) studies were performed on three of them. This study depicts the spectrum of C9orf72–related aphasic phenotypes, and illustrates their linguistic presentation. The non-fluent/agrammatic variant was the most frequent phenotype in our series (9/16 patients, 56%), with apraxia of speech being the main defining feature. Left frontal lobe atrophy was present in these subjects, peaking in inferior frontal gyrus. Three patients (19%) showed the semantic variant, with progression of atrophy in temporo-polar regions, later involving orbitofrontal cortex. Anterior temporal lobe dysfunction was also particularly relevant in two patients (12.5%) with mixed forms of PPA. Lastly, two patients (12.5%) had unclassifiable PPA with predominating word-finding difficulties. No PPA-C9orf72 patients in our series fulfilled the criteria of the logopenic variant. Importantly, this study underlines the role of C9orf72 mutation in the disruption of the most anterior parts of the language network, including prefrontal and temporo-polar areas. It provides guidelines for C9orf72 testing in PPA patients, with important clinical impact as gene-specific therapies are upcoming.

Neuronal cultures are a prominent experimental tool to understand complex functional organization in neuronal assemblies. However, neurons grown on flat surfaces exhibit a strongly coherent bursting behavior with limited functionality. To approach the functional richness of naturally formed neuronal circuits, here we studied neuronal networks grown on polydimethylsiloxane (PDMS) topographical patterns shaped as either parallel tracks or square valleys. We followed the evolution of spontaneous activity in these cultures along 20 days in vitro using fluorescence calcium imaging. The networks were characterized by rich spatiotemporal activity patterns that comprised from small regions of the culture to its whole extent. Effective connectivity analysis revealed the emergence of spatially compact functional modules that were associated with both the underpinned topographical features and predominant spatiotemporal activity fronts. Our results show the capacity of spatial constraints to mold activity and functional organization, bringing new opportunities to comprehend the structure-function relationship in living neuronal circuits.

since the beginning of 2020, a new virus named COVID-19 has rapidly spread to a global pandemic. The world economy has been strongly affected and early evidence suggests that its impact has involved all the sectors and business functions. In such context, logistics activities have been severely affected by the COVID-19 pandemic because of the introduction of new strict prevention rules; moreover, purchasing behaviours of customers have changed and systems had to rapidly adapt to unexpected events. This paper aims to investigate the impact of the sanitary emergency on logistics activities. A logistic provider specialized in the food and fast moving consumer goods sector has been involved in the research in order to analyse its activities and the main changes caused by the pandemic. A quantitative survey has been conducted, combining numerical data and qualitative answers. Results confirm strong effects on some sectors and an economic loss mainly due to the new procedures adopted to face the emergency.

The vehicle routing problem is one of the most studied NP-hard combinatorial problem. In the food sector, the complexity of the issue grows because of the presence of strict constraints. Taking into account the variability and the restrictions typical of the dairy sector, the aim of this paper is to provide a practical tool for solving the milk collection problem in real scenarios. A heuristic approach has been proposed to determine a feasible solution for a real-life problem, including capacity and time constraints. Two different applications of the Nearest Neighbor algorithm have been modelled and compared with the current system. Different tests have been implemented for evaluating the suitability of the outcomes. Results show that the greedy approach allows for involving less vehicles and reducing the travel time. Moreover, the tool has been proved to be flexible, able to solve routing problems with stochastic times and high supply variability.

Inventory management represents one of the main criticalities that companies have to face. The challenge is twofold: being able to satisfy a demand whose behavior can significantly vary and be unpredictable in order to avoid stock-out situations, whilst limiting excessive stocks and consequently costs. Some factors can complicate this already inherently difficult task. An example is the presence of constraints on the time for storage, which is the typical case for perishable products such as food and beverages, core business of the Italian company subject of the case study described in this paper. To optimize the reorder process in that context, a simulation model was developed for evaluating the potentials of three traditional reordering policies (i.e., Re-Order Point, Re-Order Interval, and (s, S)) to be applied to a set of products managed by the company, including perishable items, and for testing their performance. The items tested were selected through a preliminary ABC analysis, carried out on the volumes handled. A comparison with the current performance of the company’s and that achievable with the optimized policies is proposed.

In every industrial plant and in particular in a Giant Brownfield Oil Plant, asset integrity management plays a crucial role both in day-by-day activities and in future operations, and it helps to maximize the company value. This paper presents an innovative digital tool to monitor, track and manage the Process and Maintenance Override Switch (POS and MOS). It includes email alert, historian tracking and it is the basis of the Management of Change (MOC) process of a giant brown oilfield. This new digital tool relies on the increasing data availability and on the huge opportunity that data democracy enables to production engineers, operators, and plant manager. It combines DCS raw data, event and alarm list, signal condition and inhibits with a storage data tool and the Digital Oilfiled (DOF) to create an Integrated Operation Center (IOC) with a section focusing on barrier panel and asset integrity. Focusing about the POS and MOS system, the tool read the real time data from the Integrated Control & Safety System (ICSS) and store them in the IOC where the data are accessible to all the production, maintenance and HSE personnel. These data are rearranged in order to focus the attention on risks, safety barriers and related mitigation through the entire plant. The IOC will automatically send alert email one hour before the shift ending. Control room supervisor together with the Central Control Room (CCR) operators can check all the POS and MOS tracked during the shift and remove the inhibits that are no necessary to the operations. Thanks to IOC, plant manager and control room supervisor can track new inhibits and report them to the maintenance team or to the production engineers to confirm the proper risk analysis and mitigations actions and initiate the MOC procedure, if needed. MOC are needed to meet the brownfield plant evolution and operating/safety requirements according to internal operations Procedure Instruction (OPI), local and national regulations and international standards. The IOC and the DOF integrate also the alarm list, in order to improve Alarm Management System and Alarm Rationalization/Reduction activities. It highlights the most frequent alarms and create a collaborative environment in which production, maintenance and automation team can work together to reduce the alarm number and frequency. This new digital management tool gives a strong contribution to production engineers, plant manager, CCR supervisor and maintenance team to maximize transparency and safety for people, environment and asset. Focus the attention on the process overrides highlights every moment the barrier status panel of the plant and supports the management of change process in a Giant Brownfield Oil Plant creating a collaborative environment based on data availability and data democracy.

The current oil and gas production scenario is characterized by high market volatility, increasing Energy Efficiency targets and subsequent requirements in operation excellence. This leads to an ever-increasing attention towards more efficient asset management. This paper illustrates the application of Advanced Process Control techniques to beyond-standard targets of process parameters and product specifications, supporting carbon footprint reduction process. The Oil & Gas treatment facility is made of 4 oil and 5 gas process trains with an overall gross production of more than 100 KBOED. An advanced Adaptive Process Control application has been first tested on a Digital Twin and then implemented on one single GOSP (Gas Oil Separation) section. This application has then been extended to all the process trains, including the Gas treatment section. A fully integrated Adaptive Process Control Orchestrator and Dynamic Optimizer has been deployed across the entire site to grant an efficient load management between trains, maximizing hydrocarbon production and the energy efficiency of the asset maintaining every equipment within the proper operating windows. APC deployment on a brownfield upstream facility demonstrated to improve asset efficiency by optimizing performance within design capabilities. Energy consumptions were significantly reduced by product specification prediction and early identification of potential process upsets. A sensible production capacity increase has also been recorded thanks to process stabilization. Results eventually show that in an industry where process optimization by design changes is not always feasible or cost-effective, a well-tuned APC controller can increase asset performance with a minimum investment. Moreover, project delivering didn't require disruption in normal operation nor design changes in existing equipment. Significant results have been obtained in terms of alarms reduction through a standardization of the control philosophy and also in terms of energy/CO2 reduction with an average −15% specific energy and CO2 reduction achieved just in GOSP section. Moreover, APC has demonstrated a critical support to operators during equipment upsets through the "auto-pilot" control of the process trains not affected by the transient. Advanced Process Control is a multiple input – multiple output (MIMO) digital tool that nowadays has never been systematically implemented in upstream facilities. Main reasons are the high volatility of reservoir fluids flowrates and product overspecification that assures safe operations and production continuity. APC changes significantly control-room operator working routine of an upstream production plant. Without APC, operator's experience relies on 1-to-1 relationships between one manipulated variable (MV) and one controlled variable (CV) even if more than one CV is affected by one MV move. Optimization runs are carried out with a frequency lower than a minute and within every run, a move could be assigned to any manipulated variable. APC operator can focus on CV limits assignments, being relieved of smoothing PID loops moves.

SUMMARYNeuronal cultures are a prominent experimental tool to understand complex functional organization in neuronal assemblies. However, neurons grown on flat surfaces exhibit a strongly coherent bursting behavior with limited functionality. To approach the functional richness of naturally formed neuronal circuits, here we studied neuronal networks grown on polydimethylsiloxane (PDMS) topographical patterns shaped as either parallel tracks or square valleys. We followed the evolution of spontaneous activity in these cultures along 20 daysin vitrousing fluorescence calcium imaging. The networks were characterized by rich spatiotemporal activity patterns that comprised from small regions of the culture to its whole extent. Effective connectivity analysis revealed the emergence of spatially compact functional modules that were associated to both the underpinned topographical features and predominant spatiotemporal activity fronts. Our results show the capacity of spatial constraints to mold activity and functional organization, bringing new opportunities to comprehend the structure-function relationship in living neuronal circuits.

Objectives Thyroid biomarkers are fundamental for the diagnosis of thyroid disorders and for the monitoring and treatment of patients with these diseases. The knowledge of biological variation (BV) is important to define analytical performance specifications (APS) and reference change values (RCV). The aim of this study was to deliver BV estimates for thyroid stimulating hormone (TSH), free thyroxine (FT4), free triiodothyronine (FT3), thyroglobulin (TG), and calcitonin (CT). Methods Analyses were performed on serum samples obtained from the European Biological Variation Study population (91 healthy individuals from six European laboratories; 21–69 years) on the Roche Cobas e801 at the San Raffaele Hospital (Milan, Italy). All samples from each individual were evaluated in duplicate within a single run. The BV estimates with 95% CIs were obtained by CV-ANOVA, after analysis of variance homogeneity and outliers. Results The within-subject (CV I ) BV estimates were for TSH 17.7%, FT3 5.0%, FT4 4.8%, TG 10.3, and CT 13.0%, all significantly lower than those reported in the literature. No significant differences were observed for BV estimates between men and women. Conclusions The availability of updated, in the case of CT not previously published, BV estimates for thyroid markers based on the large scale EuBIVAS study allows for refined APS and associated RCV applicable in the diagnosis and management of thyroid and related diseases.

El ependimoma es una neoplasia neuroectodérmica cuya localización principal es infratentorial en niños y espinal en adultos. Solo se han informado unos pocos casos de localización sellar atípica y no existe un protocolo de diagnóstico o manejo estandarizado para estos casos. Se informa un caso poco frecuente de ependimoma sellar en un adulto con deterioro cognitivo y visual. La sospecha clínica de esta entidad, así como la máxima resección quirúrgica segura, pueden permitir un diagnóstico certero y mejorar el abordaje terapéutico. Se necesitan más estudios sobre este tema para evaluar el tratamiento y la supervivencia a largo plazo.

The machine loading (ML) problem of flexible manufacturing systems (FMS) has been recognized as one of the most important planning problems in industry. This study aims to minimize the system unbalance developing a modified binary bat algorithm (MBBA), satisfying the technological constraints such as the availability of machine time and tool slots. The proposed algorithm was implemented in Matlab ® , and to show its application, a case study was conducted on a major Italian company, which manufactures equipment and plants for the food industry. Two scenarios are evaluated to this end: an “AS IS” scenario, reflecting the current configuration of the production system, and a “TO BE” one, in which the MMBA is implemented for improving the system’s performance. For the TO BE scenario, a new sequence of jobs, able to minimise the variance of the total processing time, was determined. The application of the MMBA reveals significant improvements in processing time compared to the current approach used by the company. The results of the TO BE scenario can be used to provide effective indications to operations managers, helping them to identify an alternative strategy to enhance the efficiency of the targeted production system.

Operating rooms management is a critical point in healthcare organizations; inefficient scheduling and allocation of human and physical resources are often present. This study aims to automatically collect data from a real surgical scenario to develop an integrated technological-organizational model that optimizes the operating block resources.Each patient is real-time tracked and located by wearing a bracelet sensor with a unique identifier. Exploiting indoor localization, the software architecture is able to collect the time spent in every steps inside the surgical block. The preliminary results are promising, making the study feasible and functional. Times automatically recorded are much more precise than those collected by humans and reported in the organization's information system. In addition, Machine Learning can exploit the historical data collection to predict the surgery time required for each patient according to the patient’s specific profile. This approach will make it possible to plan short and long-term strategies optimizing the available resources.

Local livestock breeds play an important role in the food security of smallholders in developing countries in the Global South. They are also a reservoir of potentially valuable genes for adaptation of global animal genetic resources. The Creole cattle population from Pasorapa, Bolivia, is threatened by effects of climate change and unplanned crossbreeding. The aim of this study was to assess the current situation in this population and to evaluate factors to be considered before implementing conservation and genetic improvement programs in order to achieve the sustainable development goals 1, 2, 13 and 15, which refer to no poverty, zero hunger, climate change and life on land, respectively. We examined and analyzed the most important elements related to the production system and farmers’ perceptions that could affect the design of such programs. Open-ended and closed-ended questionnaires and interviews were performed with 81 smallholders from 11 communities in Pasorapa. A rearing system based on two stages and animals feeding mainly on native plants during both, involves a strong interaction between the environment and the production system. A survey of farmers’ perceptions about diseases, mortality causes, and selection criteria revealed that farmers in Pasorapa consider coat color an important trait when selecting breeding and replacement animals. Half of all interviewees perceived an association between coat color and traits such as temperament, milk yield, and beef production. In a SWOT analysis we discussed the vulnerability of the system to climate change impacts and the contribution of this traditional system to rural mitigation. Overall, this work revealed the importance of this local ecotype and identified key factors to consider when developing breeding and conservation programs.

We propose a novel phase based analysis with the purpose of quantifying the periodic bursts of activity observed in various neuronal systems. The way bursts are intiated and propagate in a spatial network is still insufficiently characterized. In particular, we investigate here how these spatiotemporal dynamics depend on the mean connection length. We use a simplified description of a neuron’s state as a time varying phase between firings. This leads to a definition of network bursts, that does not depend on the practitioner’s individual judgment as the usage of subjective thresholds and time scales. This allows both an easy and objective characterization of the bursting dynamics, only depending on system’s proper scales. Our approach thus ensures more reliable and reproducible measurements. We here use it to describe the spatiotemporal processes in networks of intrinsically oscillating neurons. The analysis rigorously reveals the role of the mean connectivity length in spatially embedded networks in determining the existence of “leader” neurons during burst initiation, a feature incompletely understood observed in several neuronal cultures experiments. The precise definition of a burst with our method allowed us to rigorously characterize the initiation dynamics of bursts and show how it depends on the mean connectivity length. Although presented with simulations, the methodology can be applied to other forms of neuronal spatiotemporal data. As shown in a preliminary study with MEA recordings, it is not limited to in silico modeling.

The 2030 Agenda of the United Nations includes the objective of setting up sustainable production patterns by pursuing several Sustainable Development Goals. Among them, the "Responsible production and consumption" is a key topic in the food production and is strictly connected with the "Climate action"; the crucial point, however, is how to jointly act on all these aspects and apply them in practice. The waste yearly produced in the food chain represent both an ethical, economic and environmental issue. In particular, as far as the recovery of packaged food waste from retailers is concerned, the valorisation of the wasted meat is an extremely relevant issue. Pet food industries could be interested in valorising this waste fraction to replace meat coming from slaughters in their product recipes. This article evaluates the environmental impact of valorising meat fraction from packaged food waste to produce two different recipes of high quality pet food, called Natura and Pâté. A life cycle assessment of the current scenario (traditional pet food production and landfilling of packaged food waste) and of a new one (pet food production using meat fraction from packaged food waste) is carried out applying the ReCiPe 2016 method of impact assessment. Real data have been taken from retailers and pet food manufacturer. The production of pet food using the meat fraction from packaged food waste generates on average lower environmental impacts if compared to the traditional process, in terms of GWP (-56.40%), water consumption (-22.62%), land use (-87.50%) and fossil resource scarcity (-21.78%). Benefits are interesting even if considering the production of Pâté (-14.66%), for which the traditional production process makes use of some slaughter by-products. The proposed industrial process is demonstrated to be sustainable from an environmental point of view and appears to be in line with Sustainable Development Goals (SDGs) 2, 12 and 13.

Logistics plays an essential role in supply chain management to plan and coordinate the movement of products in a timely, safely and effectively way. The recent term Logistics 4.0 focusses on the specific applications of Industry 4.0 in the area of logistics and was created as an integral part of the Industry 4.0 concept. This study aims to contribute to the state‐of‐the‐art about this topic by analysing and reviewing the scientific literature relating to Industry 4.0 applied to the logistics field. By means of a query on the Scopus database (www.scopus.com), 131 articles were retrieved and judged in line with the research topic. A bibliometric analysis identified the most relevant articles, authors, keywords, countries and journals on this subject. To the best of the authors' knowledge, this is the first systematic review of Logistics 4.0 using bibliometric analysis. Finally, the research gaps identified will provide a reference point that will encourage and guide interested researchers for future study.

Four individuals from two families presented with a multisystemic condition of suspected genetic origin that was diagnosed only after genome analysis. The main phenotypic features were immune system dysregulation (severe immunodeficiency with autoimmunity) and intellectual disability. The four individuals were found to be homozygous for a 4.4 Kb deletion removing exons 20 to 23 (NM_003291.4) of the TPP2 gene, predicting a frameshift with premature termination of the protein. The deletion was located on a shared chromosome 13 haplotype indicating a Swiss founder mutation. Tripeptidyl peptidase 2 (TPP2) is a protease involved in HLA/antigen complex processing and amino acid homeostasis. Biallelic variants in TPP2 have been described in ten individuals with variable features including immune deficiency, autoimmune cytopenias, and intellectual disability or chronic sterile brain inflammation mimicking multiple sclerosis. Our observations further delineate this severe condition not yet included in the OMIM catalog. Timely recognition of TPP2 deficiency is crucial since (1) immune surveillance is needed and hematopoietic stem cell transplantation may be necessary, and (2) for provision of genetic counseling. Additionally, enzyme replacement therapy, as already established for TPP1 deficiency, might be an option in the future. This article is protected by copyright. All rights reserved.

Nowadays, companies are more and more attracted and interested by the possibility of automating processes which can be easily carried out by devices or machines instead of employees, allowing saving in costs, higher productivity and flexibility. Among the most spread ways of automating processes, more precisely in this specific case the flow of materials, the Automated Guided Vehicles (AGVs) stand out. But the main question that everyone asks is the following: is it convenient or not? In this paper, the answer is provided for a company operating in the food context, which intends to automate the transport of raw ingredients from the kitchens where they are produced and prepared to the filling lines; to this end, an economic feasibility study is carried out, taking into account three different levels of automation for three different lines. Results from all the three scenarios demonstrate the convenience in terms of achievable revenues, saved hours and manpower, and will support the management in their operational decisions.

Logistics activities were included in the wave of changes brought with the advent of the fourth industrial revolution. Several applications can be recognized for several activities, aiming all at efficiently optimizing processes and consequently production and volumes. Among them, collaborative robots involved for instance in picking, palletizing or assembly operations are quickly spreading, as also demonstrated by the increase in the number of publications available in literature. In response, this paper presents the results of a bibliometric analysis carried out on 64 scientific papers which deal with this topic within the logistics field. Analysis were made through two different software applications, namely Microsoft Excel™ and VOSviewer. Results are quite optimistic as they delineate great opportunities for collaborative robots to establish their position in the industrial context.

The purpose of this study is to map out the relationship between shared leadership (SL) and Six Sigma (6S) project lifecycle. More specifically, the impact of SL and team members' perceived challenges in each of the five phases of the DMAIC (define, measure, analyze, improve, and control) 6S methodology is studied. Furthermore, general organizational issues that affect both SL development and the 6S model are identified. The results demonstrate that several factors, namely, change management, communication, phase deliverables, coaching style, and decision-making methods, affect usage performance of SL throughout the phases. This study helps managers to look at the 6S projects from an SL perspective and shows how to manage the 6S project lifecycle more efficiently.

This paper addresses the Resilient Food Supply Chain Design (RFSCD) problem, which is the problem of designing a food supply chain that is resilient enough to ensure business operations continuity in the event of risks or disruptions. Based on a graph theory representation of the food supply chain, this paper proposes a bi-objective mixed-integer programming formulation for this problem. The objectives are to (1) maximize the total profit over a one-year time span and (2) minimize the total lead time of the product along the supply chain. To solve the model, an Ant Colony Optimization (ACO) algorithm is presented. The developed model is suitable for adoption for the design of a multi-product resilient food supply chain that makes use of a multiple sourcing policy to deal with unexpected fluctuations of market demand and disruptions in raw materials supply. The adapted ACO algorithm is tested on a case study, referring to the SC of readymade UHT tomato sauce, which is particularly vulnerable to such risks.

Purpose The purpose of this paper is to propose an artificial intelligence-based framework to support decision making in wholesale distribution, with the aim to limit wholesaler out-of-stocks (OOSs) by jointly formulating price policies and forecasting retailer’s demand. Design/methodology/approach The framework is based on the cascade implementation of two artificial neural networks (ANNs) connected in series. The first ANN is used to derive the selling price of the products offered by the wholesaler. This represents one of the inputs of the second ANN that is used to anticipate the retailer’s demand. Both the ANNs make use of several other input parameters and are trained and tested on a real wholesale supply chain. Findings The application of the ANN framework to a real wholesale supply chain shows that the proposed methodology has the potential to decrease economic loss due to OOS occurrence by more than 56 percent. Originality/value The combined use of ANNs is a novelty in supply chain operation management. Moreover, this approach provides wholesalers with an effective tool to issue purchase orders according to more dependable demand forecasts.

In the last few decades, studies have demonstrated the correlation between worker well-being and the performance of production systems. This paper addresses the problem of assigning workers to tasks in a workshop system. In this context, recent researches have focused on the ergonomics assessment, often neglecting the evaluation of the workers’ performance. This study aims to formulate a mixed integer linear programming model to solve the workforce scheduling problem and improve the performance of the system integrating ergonomics and human skills. To overcome the complexity of the combinatorial problem, a constructive heuristic procedure is developed. Moreover, a novel approach is proposed to determine the workers’ skills. Human performance is modelled in terms of the time required to perform consecutive tasks, considering different sequences of tasks. In addition, the model was applied to a real case study to verify its feasibility. Different scenarios are tested, considering different levels of exposure to different risk factors. The results indicate that a limited increase in the makespan enables decreasing the risk level and the achievement of an excellent workload balance among workers in terms of time spent in performing tasks. Moreover, the heuristic procedure has demonstrated to perform well on instances of realistic size, and it could be adapted to many manufacturing systems to solve the problem in real industrial contexts.

Introducción: El propósito de este artículo es describir las principales manifestaciones clínicas, método diagnóstico y tratamiento de elección de una neoplasia intracraneal primaria rara de origen epitelial, benigno con su variante adamantinomatosa propia de la edad pediátrica que es diagnosticada con mayor frecuencia en rangos de edad de 5 a14 años según refiere la revisión de literatura científica internacional. Caso clínico: Se reporta un caso en el cual la paciente no se encuentra dentro de los picos de edad en los que con mayor frecuencia se realiza el diagnóstico de Craneofaringioma adamantinomatoso, es una paciente femenina de 17 años con cefalea y dismenorrea de 6 meses de evolución acompañado de hemianopsia bitemporal que fue sometida a cirugía craneal abierta por abordaje pterional derecho con resección subtotal de la lesión que además se colocó shunt ventrículo peritoneal por hidrocefalia tetraventricular obstructiva que fue desarrollada al año de la cirugía. Conclusiones: La clínica coincide con los síntomas descritos y atribuibles a la compresión y extensión hacia estructuras adyacentes, su presentación fue de lenta evolución, la imagen fue característica de esta variante histológica pediátrica. A pesar de ser una entidad de histología benigna es agresiva por su invasión a estructuras profundas y autonómicas provocando una historia natural incierta y con gran probabilidad de comorbilidades que pueden ser mayores con tratamientos quirúrgicos agresivos.

El objetivo del presente trabajo es describir las manifestaciones clínicas, métodos diagnóstico, manejo terapéutico así como también las características intraoperatorias del quiste epidermoide. Se reporta el caso de paciente masculino de 37 años, que acude por presentar crisis de ausencia, cefalea, diplopía, hipoacusia izquierda y limitación para la deambulación de 6 meses de evolución. Se realiza estudio de resonancia magnética (RM) cerebral en el cual se observa una lesión supra e infratentorial hipointensa con señal semejante a la de líquido cefalorraquídeo (LCR), con escasa captación al contraste y en secuencia T2 se observa hiperintensa. Se realiza tratamiento quirúrgico con resección total con evolución posquirúrgica favorable y sin evidencia de recurrencia a los 2 años.

PurposeThis paper aims to assess and prioritize manufacturing companies in the healthcare industry based on critical success factors (CSFs) of their reverse logistics (RL). The research involves seven medical device companies located in the Tehran Province, Iran.Design/methodology/approachTo identify and prioritize companies based on CSFs of RL, the study proposes a three-phase decision-making framework that integrates the Delphi method, the best-worst method (BWM) and the Additive Ratio Assessment (ARAS) method with Z-numbers. The weights required for this method are obtained by a variant of the BWM based on Z-numbers, denoted as Z-numbers Best-Worst Method, or ZBWM. Since decision-makers face an uncertain environment, Z-numbers, which are a kind of fuzzy numbers, are applied.FindingsFirst, after customizing CSFs by the Delphi method and obtaining 15 CSFs of RL, these are ranked by the hybrid BWM-ARAS method with Z-numbers. Results reveal which company appears to perform best with respect to their RL implementations. Based on this result, healthcare device companies should choose the highest priority company based on the selected RL CSFs and results from using the BWM-ARAS method with Z-numbers.Originality/valueThe contribution of this paper is using a hybrid ARAS-BWM method based on Z-numbers. Each of these methods has some merits compared to other similar methods. The combination of these methods contributes a new approach for prioritizing companies based on RL CSFs with high accuracy and reliability.

KAT5 encodes an essential lysine acetyltransferase, previously called TIP60, which is involved in regulating gene expression, DNA repair, chromatin remodeling, apoptosis, and cell proliferation; but it remains unclear whether variants in this gene cause a genetic disease. Here, we study three individuals with heterozygous de novo missense variants in KAT5 that affect normally invariant residues, with one at the chromodomain (p.Arg53His) and two at or near the acetyl-CoA binding site (p.Cys369Ser and p.Ser413Ala). All three individuals have cerebral malformations, seizures, global developmental delay or intellectual disability, and severe sleep disturbance. Progressive cerebellar atrophy was also noted. Histone acetylation assays with purified variant KAT5 demonstrated that the variants decrease or abolish the ability of the resulting NuA4/TIP60 multi-subunit complexes to acetylate the histone H4 tail in chromatin. Transcriptomic analysis in affected individual fibroblasts showed deregulation of multiple genes that control development. Moreover, there was also upregulated expression of PER1 (a key gene involved in circadian control) in agreement with sleep anomalies in all of the individuals. In conclusion, dominant missense KAT5 variants cause histone acetylation deficiency with transcriptional dysregulation of multiples genes, thereby leading to a neurodevelopmental syndrome with sleep disturbance, cerebellar atrophy, and facial dysmorphisms, and suggesting a recognizable syndrome.

The demand for shorter delivery time, more efficient and automated processes, higher quality and customized products have driven companies towards the fourth industrial revolution. This study aims to contribute to the state of the art by evaluating the main application fields of Industry 4.0 and analyzing the enabling technologies used in these fields. To this end, a bibliographic analysis for Industry 4.0 was first conducted by searching relevant papers with the support of the Scopus database ( www.scopus.com ). Then, an overview on Industry 4.0 was performed with the purpose to deeply understand the context of this study. Finally, the attention moved on the identification of the enabling technologies and the main application areas of Industry 4.0. These latter, as they emerged from the literature, appear to be Logistics 4.0, Automotive, Smart home and Agriculture 4.0.