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The modularization of production plants and their automation in the pharmaceutical and (bio‐)chemical industry is currently gaining attention and is subject of standardization efforts. The combination of modular and monolithic (bio‐)chemical plants and related engineering processes, i.e., hybrid process plants and hybrid engineering, respectively, offers advantages in production flexibility and time to operation. However, combining the different approaches is full of hurdles and unsolved issues. In this paper, hybrid process plants are defined and characterized in a process systems framework. Modeling and simulation requirements are elaborated for the engineering workflow of hybrid process plants. The contribution concludes with summarizing current research topics and pointing to a future research agenda. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to identify the genetic cause for progressive peripheral nerve disease in a Venezuelan family. Despite the growing list of genes associated with Charcot-Marie-Tooth disease, many patients with axonal forms lack a genetic diagnosis.Methods: A pedigree was constructed, based on family clinical data. Next-generation sequencing of mitochondrial DNA (mtDNA) was performed for 6 affected family members. Muscle biopsies from 4 family members were used for analysis of muscle histology and ultrastructure, mtDNA sequencing, and RNA quantification. Ultrastructural studies were performed on sensory nerve biopsies from 2 affected family members.Results: Electrodiagnostic testing showed a motor and sensory axonal polyneuropathy. Pedigree analysis revealed inheritance only through the maternal line, consistent with mitochondrial transmission. Sequencing of mtDNA identified a mutation in the mitochondrial tRNAVal (mt-tRNAVal ) gene, m.1661A>G, present at nearly 100% heteroplasmy, which disrupts a Watson-Crick base pair in the T-stem-loop. Muscle biopsies showed chronic denervation/reinnervation changes, whereas biochemical analysis of electron transport chain (ETC) enzyme activities showed reduction in multiple ETC complexes. Northern blots from skeletal muscle total RNA showed severe reduction in abundance of mt-tRNAVal , and mildly increased mt-tRNAPhe , in subjects compared with unrelated age- and sex-matched controls. Nerve biopsies from 2 affected family members demonstrated ultrastructural mitochondrial abnormalities (hyperplasia, hypertrophy, and crystalline arrays) consistent with a mitochondrial neuropathy.Conclusion: We identify a previously unreported cause of Charcot-Marie-Tooth (CMT) disease, a mutation in the mt-tRNAVal , in a Venezuelan family. This work expands the list of CMT-associated genes from protein-coding genes to a mitochondrial tRNA gene. ANN NEUROL 2020;88:830-842. [ABSTRACT FROM AUTHOR]

The modularization of process plants is regarded as a promising approach to cope with upcoming requirements in the process industry regarding flexibility. Within the Decentralized Intelligence for Modular Assets Project, a concept has been developed to overcome current deficiencies in implementing modular plants and especially their automation. On one hand, the approach considers a clear separation of engineering efforts into plant-independent module engineering and plant-specific integration engineering. On the other hand, the concept provides a method for the fast integration of a module's automation system into a higher level process control system. To do so, each module provides its process functionality in encapsulated services. The core of the integration method is a file-based description of the module including its services, operating screens, and communication variables. The so-called “module-type package” is currently under standardization by different organizations. This paper presents the general approach as well as current results of the standardization efforts. Furthermore, the results are executed on an application demonstrator to allow a practical assessment. Thus, module engineering and integration engineering, as well as corresponding software tools can be demonstrated. [ABSTRACT FROM AUTHOR]

Within the engineering of control code, model-based approaches become more and more important. Basically GRAFCET serves as a suitable modeling language but lacks an exhaustive formal representation of its structure and dynamic behavior since current approaches only consider subclasses of GRAFCET. Within this article the authors depict a systematic approach for an exhaustive formal model of GRAFCET, specifically by taking enclosing steps , forcing orders and time constraints into account. Based on this formal model of GRAFCET a method together with a tool framework are presented allowing for the automatic generation of control code. [ABSTRACT FROM AUTHOR]

Abstract: The correct configuration of the control code is a critical part of every process control system engineering project. To ensure the conformity of the implemented control functions with the customer’s specifications, test activities, e.g., the factory acceptance test (FAT), are conducted in every control engineering project. For the past several years, control code tests have increasingly been carried out on simulation models to increase test coverage and timeliness. Despite the advantages that simulation methods offer, the manual effort for generating an applicable simulation model is still high. To reduce this effort, an automated model generation is proposed in this paper. The models automatically generated by this approach provide a modeling level of detail that matches the requirements for the tests of the control code on the base automation level. Therefore, these models do not need to be as detailed as the high-fidelity models which are used for, e.g., model predictive control (MPC) applications. Within this paper, the authors describe an approach to automatically generate simulation models for control code tests based on given computer aided engineering (CAE) planning documents. [Copyright &y& Elsevier]

The 14th Annual IEEE International Conference on Automation Science and Engineering (CASE 2018) sponsored by the IEEE Robotics and Automation Society (RAS) was held on August 20–24, 2018, in Munich, Germany. IEEE CASE is the flagship automation conference of the IEEE RAS and constitutes the primary forum for cross-industry and multidisciplinary research in automation. Its goal was to provide a broad coverage and dissemination of foundational research in automation among researchers, academics, and practitioners. CASE 2018 was organized by General Chairs Birgit Vogel-Heuser and Bengt Lennartson and Program Chairs Cesare Fantuzzi, Alexander Fay, and Georg Frey. [ABSTRACT FROM AUTHOR]

The modernisation of a control system for a technical plant is always a complex and time consuming task, especially when the technology of the control system changes and control applications have to be ported from the old to the new control system. This paper presents an automatic, knowledge-based approach to address the modernisation problem, which employs a graphical knowledge-based system. The described approach is embedded into a computer program that proved to be useful to significantly reduce engineering costs and plant downtime in the frame of the modernisation of control systems. [Copyright &y& Elsevier]

Cold spraying has emerged as a promising technique for the repair of metallic components. Manipulating the cold spray gun by industrial robots, referred to as robot-guided cold spraying, enables flexible and controlled material deposition. This work proposes a concept for automated planning of robotic cold spray paths and trajectories, enabling effective and efficient material deposition at specified repair locations. The concept incorporates predefined cold spray parameterizations and boundary conditions to provide the best possible material deposition for the individual repair application. The concept begins with the extraction of the volume to be filled. This volume is then sliced into suitable adaptively curved layers and converted into point clouds for path planning. Subsequently, the cold spray path is converted into a trajectory by adding a calculated spray velocity profile to produce the required locally varying layer thicknesses. In addition, simulation of the material deposition and a kinematic analysis of the simulated trajectory are performed. These are utilized as performance indicators for assessing deposit quality and material efficiency, enabling the validation and improvement of the parameterized trajectory. Finally, the implementation of the entire concept is demonstrated by representative use cases. The results demonstrate successful automated path and trajectory planning by the proposed concept, contributing to the overall goal of automated repair of damaged components by cold spraying. [ABSTRACT FROM AUTHOR]

Objective: We determined the effect of perinatally acquired HIV on neurocognition in Myanmar children treated with antiretroviral therapy by comparison to demographically matched seronegative children.Background: Myanmar has one of the highest HIV-1 prevalence rates in Southeast Asia. Studies from other resource-poor countries have shown that HIV-infected children differ in socioeconomic, nutritional and caregiver status compared to normal controls. Some vertically infected orphans in Myanmar reside separately from HIV-uninfected children in separate orphanages, thus the demographic variables of interest are naturally controlled. This study provides a unique evaluation of the neurocognitive effects of HIV in children, with control over key demographic variables. We hypothesized that HIV-infected orphans would perform significantly worse on cognitive indices compared with HIV-negative orphans.Design/methods: A battery of cognitive tests sensitive to HIV-associated impairments in children was administered to 28 perinatally acquired HIV-positive children and 31 HIV-negative children from two orphanages in Myanmar; 21 children from each cohort underwent testing at baseline and again after 12 months.Results: Baseline comparison of the two groups indicated that the HIV-infected children performed poorly across all tests, with significant group differences in executive function, visuospatial reasoning, fine motor dexterity, and visual motor integration. On subsequent testing, both cohorts of children showed improvements across multiple domains, with no significant effect of age at treatment initiation.Conclusions: Our results demonstrate a strong effect of HIV infection on specific neurocognitive deficits in vertically infected children. Understanding viral and host determinants and timing and choice of antiretroviral therapy on cognition will be critical to preventing cognitive impairment of children with HIV. [ABSTRACT FROM AUTHOR]

"Security by design" is the term for shifting cybersecurity considerations from a system's end users to its engineers. To reduce the end users' workload for addressing security during the systems operation phase, security decisions need to be made during engineering, and in a way that is traceable for third parties. However, engineers of cyber-physical systems (CPSs) or, more specifically, industrial control systems (ICSs) typically neither have the security expertise nor time for security engineering. The security-by-design decisions method presented in this work aims to enable them to identify, make, and substantiate security decisions autonomously. Core features of the method are a set of function-based diagrams as well as libraries of typical functions and their security parameters. The method, implemented as a software demonstrator, is validated in a case study with the specialist for safety-related automation solutions HIMA, and the results show that the method enables engineers to identify and make security decisions they may not have made (consciously) otherwise, and quickly and with little security expertise. The method is also well suited to make security-decision-making knowledge available to less experienced engineers. This means that with the security-by-design decisions method, more people can contribute to a CPS's security by design in less time. [ABSTRACT FROM AUTHOR]

Background: INAD is an autosomal recessive neurogenetic disorder caused by biallelic pathogenic variants in PLA2G6. The downstream enzyme, iPLA2, plays a critical role in cell membrane homeostasis by helping to regulate levels of phospholipids. The clinical presentation occurs between 6 months and 3 years with global developmental regression, hypotonia, and progressive spastic tetraparesis. Progression is often rapid, resulting in severe spasticity, visual impairment, and cognitive decline, with many children not surviving past the first decade of life. To date, no accepted tool for assessing the severity of INAD exists; other commonly used scales (e.g. CHOP-INTEND, Modified Ashworth, Hammersmith Functional Motor Scale) do not accurately gauge the current severity of INAD, nor are they sensitive/specific enough to monitor disease progression. Finally, these other scales are not appropriate, because they do not address the combination of CNS, peripheral nerve, and visual pathology that occurs in children with INAD.Methods: We have developed and validated a structured neurological examination for INAD (scored out of 80). The examination includes six main categories of pediatric developmental evaluation: 1) gross motor-and-truncal-stability skills, 2) fine motor skills, 3) bulbar function, 4) ocular function, 5) temporo-frontal function, and, 6) Functional evaluation of the autonomic nervous system. A cohort of patients diagnosed with INAD were followed prospectively to validate the score against disease severity and disease progression.Results: We show significant correlation between the total neurological assessment score and months since symptom onset with a statistically significant (p = 6.7 × 10- 07) correlation between assessment score and disease onset. As hypothesized, the coefficient of months-since-symptom-onset is strongly negative, indicating a negative correlation between total score and months since symptom onset.Conclusion: We have developed and validated a novel neurological assessment score in INAD that demonstrates strong correlation with disease severity and disease progression. [ABSTRACT FROM AUTHOR]

Cyber–physical systems (CPSs) in the manufacturing domain can be deployed to support monitoring and analysis of production systems of a factory in order to improve, support, or automate processes, such as maintenance or scheduling. When a network of CPS is subject to frequent changes, the semantic interoperability between the CPSs is of special interest in order to avoid manual, tedious, and error-prone information model alignments at runtime. Ontologies are a suitable technology to enable semantic interoperability, as they allow the building of information models that lank machine-readable meaning to information, thus enabling CPSs to mutually understand the shared information. The contribution of this article is twofold. First, we present an ontology building method that is tailored toward the needs of CPSs in the manufacturing domain. For this purpose, we introduce the requirements regarding this method and discuss related research concerning ontology building. The method itself is designed to begin with ontological requirements and to yield a formal ontology. As the reuse of ontologies and other information resources (IRs) is crucial to the success of ontology building projects, we put special emphasis on how to reuse IRs in the CPS domain. Second, we present a reusable set of ontology design patterns that have been developed with the aforementioned method in an industrial use case and illustrate their application in the considered industrial environment. The contribution of this article extends the method introduced, as a postconference paper, by a detailed industrial application. Note to Practitioners—With growing digitalization in industry, the exchange and use of manufacturing-related data are becoming increasingly important to improve, support, or automate processes. Thus, it is necessary to combine information from different data sources that have been designed by different vendors and may, therefore, be heterogeneous in structure and semantics. A system that plans a maintenance worker’s daily schedule, for instance, requires information about the status of machines, production plans, and inventory, which resides in other systems, such as programmable logic controllers (PLCs) or databases. When creating such information systems, accessing, searching, and understanding the different data sources is a time-intensive and error-prone procedure due to the heterogeneities of the data sources. Even worse, this procedure has to be repeated for every newly built system and for every newly introduced data source. To allow for eased access, searching, and understanding of these heterogeneous data sources, ontology can be used to integrate all heterogeneous data sources in one schema. This article contributes a method for building such ontologies in the manufacturing domain. Furthermore, a set of ontology design patterns is presented, which can be reused when building ontologies for a domain. [ABSTRACT FROM AUTHOR]

Due to increasing amounts of energy being supplied by intermittent renewable energy sources, future energy systems need to be able to react flexibly to sudden changes. To address this challenge, a large body of research is devoted to improving the utilization of energy flexibility of various types of energy resources on the supply and demand side. This is commonly done by applying mathematical models. The objective of this paper is to review such models and identify common modeling approaches used to quantify and optimize the use of flexible energy resources. The literature review is conducted systematically, encompassing 215 publications that feature 694 models of different energy resources. The main distinction of this work, in comparison to other reviews on the topic of energy flexibility lies in its focus on the mathematical formulation of models of energy resources and the quantification of the models' level of detail. The aim is to identify common modeling approaches and the corresponding research problems they address. The review shows that the majority of research efforts are directed towards the management and optimization of distributed energy resources. The most commonly employed modeling approach involves abstract black-box models with limited levels of detail. Linear programming and meta-heuristics are frequently used to optimize energy flexibility. A critical reflection of the current common practice is conducted and recommendations for future research are formulated. [Display omitted] • Literature review of 215 reports presenting model approaches for energy flexibility. • Categories of research problems identified and deduction of two main research focuses. • Presenting models of common energy resources classified into different model types. • Mostly low level of detail seen in modeling energy flexibility. • Optimization models are used to represent and quantify flexibility. [ABSTRACT FROM AUTHOR]

Automated manufacturing machines in the discrete manufacturing domain frequently face changes in requirements, such as volatile customer demands or changes in product variants. Due to this, machines need to become more flexible to cope with these changing conditions. Therefore, manufacturing machines have to undergo adaptation processes during their operational phase. The adaptation processes might include mechanical, electrical, and software changes. In industrial practice, experts individually perform these adaptation processes without methodological support, which is time-consuming and highly error-prone. This article proposes a systematic approach for supporting the different phases of the adaptation process. The producibility check of a production request based on a suitable skill model of the system is addressed as well as the automatic generation of adaptation options. Furthermore, the article provides concepts for analyzing the impact, effort and benefit of the generated adaptation options. Additionally, a multi agent architecture is presented for the implementation of the proposed adaptation approaches. The entire assistance concept was applied to a lab-size production machine to validate the applicability of the approach. [ABSTRACT FROM AUTHOR]

Background: Dyskinesia is a troublesome complication of long-term dopaminergic medications in Parkinson's disease (PD) patients. Many factors are reported to be associated with dyskinesia in PD.Objective: To investigate the association between sleep quality and dyskinesia in patients with PD.Methods: Four hundred twenty-five patients with PD were enrolled in this study. Demographic information was collected. Unified Parkinson's Disease Rating Scale (UPDRS) and Hoehn and Yahr (H-Y) stage scale were also performed. Epworth Sleepiness Scale (ESS) and Pittsburgh Sleep Quality Index (PSQI) were applied to evaluate daytime sleepiness and overall nighttime sleep quality, respectively, in PD patients.Results: Patients with dyskinesia tended to have a longer duration of disease, higher daily levodopa-equivalent dose (LED), H-Y stage, UPDRS II and PSQI score, and a higher percentage of levodopa treatment than those without dyskinesia. After adjusting for age, sex, age at onset of PD, disease duration, UPDRS I, UPDRS II, UPDRS III, cigarette smoking, use of different antiparkinsonian drugs, phenotype, daily LED, and restless leg syndrome (RLS), PSQI score was still associated with dyskinesia, with corresponding ORs 1.111 (95% CI, 1.004-1.229) as a continuous variable, and 2.469 (95% CI, 1.051-5.800) as a categorical variable, respectively. Further analysis of PSQI components showed that subjective sleep quality and sleep latency were associated with dyskinesia in PD patients.Conclusions: Our data showed that poor nighttime sleep is positively associated with dyskinesia in PD patients. Attention to the management of nighttime sleep quality may be beneficial to dyskinesia in patients with PD. [ABSTRACT FROM AUTHOR]

Communication-based controllers for platooning are often designed for a homogeneous vehicle composition in a normal driving situation. However, in realistic applications, platoons will consist of different vehicles types or brands and thus be heterogeneous, which increases the requirements for safe operation. In addition, controllers designed for the nominal driving situation are not necessarily able to handle disturbances, such as the cut-in of a foreign vehicle or an emergency braking of the entire platoon. The authors' previous work has shown that for different driving situations (e. g. emergency braking or cut-in of a foreign vehicle) different communication topologies can be beneficial in order to control the platoon. In this paper, a concept for switching the communication topology depending on the current driving situation in a heterogeneous vehicle platoon is presented. The concept is applied for coordinated emergency braking, for the startup from standstill and for the cut-in of a foreign vehicle. For these situations, it is shown that varying the communication topology of an otherwise unchanged local controller can prevent collisions within the platoon. Furthermore, improvements can be achieved by considering the different vehicle types and their position in the vehicle string. For the example driving situations, it is shown how suitable communication topologies can be identified. • Novel approach for switching the communication topology based on driving situation. • Consideration of individual dynamic capabilities of each platoon member. • Multiple driving situations examined, namely emergency braking, cut-in and startup. • Various heterogeneous platoon compositions are examined in numerical simulation. • Simulation results demonstrate improvements in performance and safety. [ABSTRACT FROM AUTHOR]

GRAFCET is an advantageous modelling language for the specification of controllers in discrete event systems. It allows for hierarchically structuring a control program's specification based on the elements enclosing steps, partial-Grafcets and forcing orders. A method is already available for the automatic transformation of Grafcets 1 1 “GRAFCET” (in capital letters) refers to the standard and the modelling language in general, whereas a “Grafcet” is a particular model, i.e. one control specification. into PLC code but this method cannot keep the hierarchical structures due to limitations of the PLC language SFC. In this contribution a systematic approach to automatically transform Grafcets into PLC code while retaining the hierarchical structures is described. [ABSTRACT FROM AUTHOR]

Confronted with the need of plant modernization, facility owners and contractors in the process industry invest significant efforts to create digital plant models allowing for simulation and thereby validation of new engineering solutions. Although an important part of the information required for this task already exists in form of legacy engineering documentation, current computer-aided methods for generating digital plant models cannot exploit this source of knowledge owing to the non-computer-interpretable nature of the available information sources. In an effort to bridge the existing gap, this contribution presents a method based on optical recognition and semantic analysis, which is capable of automatically converting legacy engineering documents, specifically piping and instrumentation diagrams, into object-oriented plant descriptions and ultimately into qualitative plant simulation models. Resulting simulation models can serve as a basis to support engineering tasks requiring low-fidelity simulation, such as the validation of base control functions during the factory acceptance test (FAT). [ABSTRACT FROM AUTHOR]

The ongoing conversion of our energy supply encounters a great interest of many different market players that were originally located in different industries. As a consequence, a vast amount of proprietary solutions for “smart” energy applications is flooding the market. This tends to be rather a problem than part of the solution for the systematic development of future energy grids. Here, the absence of necessary unifications and standards blocks further developments that would enable the creation of novel, market-driven and hybrid control solutions for various types of technical systems. To overcome these problems, we present in this article our notion and the definition of a unified autonomous software entity that we call Energy Agent. Based on the energy conservation law and a generalized energy option model, we claim that our Energy Agent approach has the capabilities to enable cross domain interactions between different types of energy systems and networks. Further we will outline a systematic development process for Energy Agents that considers implementation, simulation, test-bed application and a real on-site usage. By taking into account these development stages, we expect to concurrently develop a novel laboratory that enables to competitively test and validate new and hybrid control solutions before they are applied in real systems. [ABSTRACT FROM AUTHOR]

Highlights: [•] The work groups alarms having the same cause in an industrial control system. [•] It uses a model of the plant topology. [•] It reduces the number of alerts presented by an alarm system to an operator. [•] The work is illustrated with industrial control studies. [•] Grouping reduced the alarm messages by 70–80% and provided better information. [Copyright &y& Elsevier]