Whole tumor RNA-sequencing and deconvolution reveal a clinically-prognostic PTEN/PI3K-regulated glioma transcriptional signature

The concept that solid tumors are maintained by a productive interplay between neoplastic and non-neoplastic elements has gained traction with the demonstration that stromal fibroblasts and immune system cells dictate cancer development and progression. While less studied, brain tumor (glioma) biology is likewise influenced by non-neoplastic immune system cells (macrophages and microglia) which interact with neoplastic glioma cells to create a unique physiological state (glioma ecosystem) distinct from that found in the normal tissue. To explore this neoplastic ground state, we leveraged several preclinical mouse models of neurofibromatosis type 1 (NF1) optic glioma, a low-grade astrocytoma whose formation and maintenance requires productive interactions between non-neoplastic and neoplastic cells, and employed whole tumor RNA-sequencing and mathematical deconvolution strategies to characterize this low-grade glioma ecosystem as an aggregate of cellular and acellular elements. Using this approach, we demonstrate that optic gliomas generated by altering the germlin

Characterisation of Al corrosion and its impact on the mechanical performance of composite cement wasteforms by the acoustic emission technique

In this study acoustic emission (AE) non-destructive method was used to evaluate the mechanical performance of cementitious wasteforms with encapsulated Al waste. AE waves generated as a result of Al corrosion in small-size blast furnace slag/ordinary Portland cement wasteforms were recorded and analysed. The basic principles of the conventional parameter-based AE approach and signal-based analysis were combined to establish a relationship between recorded AE signals and different interactions between the Al and the encapsulating cement matrix. The AE technique was shown as a potential and valuable tool for a new area of application related to monitoring and inspection of the mechanical stability of cementitious wasteforms with encapsulated metallic wastes such as Al

A Survey on Systems Integration in the Energy Automation Domain through OPC Interface

[Abstract] The Object Linking and Embedding for Process Control (OPC) interface provides an effective means to exchange data between automation-related entities, both hardware and software. Since its creation, it has been profusely used not only for industrial scenarios but also for other spheres, among which energy automation is an important scope. In order to portray the relevance of such protocol, this paper presents a survey of applications of OPC communication to manage systems integration in the context of energy automationJunta de Extremadura; GR1815

Improved control and monitor two different PLC using LabVIEW and NI-OPC server

This paper proposes an improved control and monitors between two different PLCs, the Mitsubishi, and Omron. The main advantage is interoperability and communication between both PLC. The use of NI OPC server as the software interface reached interoperability and communication. There were developed two field applications to test interoperability. Laboratory virtual instrument engineering workbench (LabVIEW) uses as the software application for creating the user interface to control and monitor. This improvement show OPC server technology solves data compatibility issue between different driver controller’s and reducing development cost. Regardless of whether there are more than two different PLCs, it's enough to use the NI OPC server. So the benefit of the NI OPC server is not limited to two types of PLC used right now but can also use the other manufacturers. Besides, the improvement of the previous study is the use of the LabVIEW makes data from the OPC server displayed more realistic. The use of LabVIEW allows additional monitoring functions, one of which is LabVIEW vision. Data utilization becomes more flexible, and so it can use for more complex purposes. It is envisaged that this is very useful for Integrator engineer to implement this method in industrial automatio

A distributed framework for the control and cooperation of heterogeneous mobile robots in smart factories.

Doctoral Degree. University of KwaZulu-Natal, Durban.The present consumer market is driven by the mass customisation of products. Manufacturers are now challenged with the problem of not being able to capture market share and gain higher profits by producing large volumes of the same product to a mass market. Some businesses have implemented mass customisation manufacturing (MCM) techniques as a solution to this problem, where customised products are produced rapidly while keeping the costs at a mass production level. In addition to this, the arrival of the fourth industrial revolution (Industry 4.0) enables the possibility of establishing the decentralised intelligence of embedded devices to detect and respond to real-time variations in the MCM factory. One of the key pillars in the Industry 4.0, smart factory concept is Advanced Robotics. This includes cooperation and control within multiple heterogeneous robot networks, which increases flexibility in the smart factory and enables the ability to rapidly reconfigure systems to adapt to variations in consumer product demand. Another benefit in these systems is the reduction of production bottleneck conditions where robot services must be coordinated efficiently so that high levels of productivity are maintained. This study focuses on the research, design and development of a distributed framework that would aid researchers in implementing algorithms for controlling the task goals of heterogeneous mobile robots, to achieve robot cooperation and reduce bottlenecks in a production environment. The framework can be used as a toolkit by the end-user for developing advanced algorithms that can be simulated before being deployed in an actual system, thereby fast prototyping the system integration process. Keywords: Cooperation, heterogeneity, multiple mobile robots, Industry 4.0, smart factory, manufacturing, middleware, ROS, OPC, framework

Accessing and Interpreting OPC UA Event Traces based on Semantic Process Descriptions

The analysis of event data from production systems is the basis for many applications associated with Industry 4.0. However, heterogeneous and disjoint data is common in this domain. As a consequence, contextual information of an event might be incomplete or improperly interpreted which results in suboptimal analysis results. This paper proposes an approach to access a production systems' event data based on the event data's context (such as the product type, process type or process parameters). The approach extracts filtered event logs from a database system by combining: 1) a semantic model of a production system's hierarchical structure, 2) a formalized process description and 3) an OPC UA information model. As a proof of concept we demonstrate our approach using a sample server based on OPC UA for Machinery Companion Specifications.Comment: Copyright 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Towards a Service-Oriented Architecture for Production Planning and Control: A Comprehensive Review and Novel Approach

The trends of shorter product lifecycles, customized products, and volatile market environments require manufacturers to reconfigure their production increasingly frequent to maintain competitiveness and customer satisfaction. More frequent reconfigurations, however, are linked to increased efforts in production planning and control (PPC). This poses a challenge for manufacturers, especially in regard of demographic change and shortage of qualified labour, since many tasks in PPC are performed manually by domain experts. Following the paradigm of software-defined manufacturing, this paper targets to enable a higher degree of automation and interoperability in PPC by applying the concepts of service-oriented architecture. As a result, production planners are empowered to orchestrate tasks in PPC without consideration of underlying implementation details. At first, it is investigated how tasks in PPC can be represented as services with the aim of encapsulation and reusability. Secondly, a software architecture based on asset administration shells is presented that allows connection to production data sources and enables integration and usage of such PPC services. In this sense, an approach for mapping asset administrations shells to OpenAPI Specifications is proposed for interoperable and semantic integration of existing services and legacy systems. Lastly, challenges and potential solutions for data integration are discussed considering the present heterogeneity of data sources in manufacturing

A Knowledge Graph Based Integration Approach for Industry 4.0

The fourth industrial revolution, Industry 4.0 (I40) aims at creating smart factories employing among others Cyber-Physical Systems (CPS), Internet of Things (IoT) and Artificial Intelligence (AI). Realizing smart factories according to the I40 vision requires intelligent human-to-machine and machine-to-machine communication. To achieve this communication, CPS along with their data need to be described and interoperability conflicts arising from various representations need to be resolved. For establishing interoperability, industry communities have created standards and standardization frameworks. Standards describe main properties of entities, systems, and processes, as well as interactions among them. Standardization frameworks classify, align, and integrate industrial standards according to their purposes and features. Despite being published by official international organizations, different standards may contain divergent definitions for similar entities. Further, when utilizing the same standard for the design of a CPS, different views can generate interoperability conflicts. Albeit expressive, standardization frameworks may represent divergent categorizations of the same standard to some extent, interoperability conflicts need to be resolved to support effective and efficient communication in smart factories. To achieve interoperability, data need to be semantically integrated and existing conflicts conciliated. This problem has been extensively studied in the literature. Obtained results can be applied to general integration problems. However, current approaches fail to consider specific interoperability conflicts that occur between entities in I40 scenarios. In this thesis, we tackle the problem of semantic data integration in I40 scenarios. A knowledge graphbased approach allowing for the integration of entities in I40 while considering their semantics is presented. To achieve this integration, there are challenges to be addressed on different conceptual levels. Firstly, defining mappings between standards and standardization frameworks; secondly, representing knowledge of entities in I40 scenarios described by standards; thirdly, integrating perspectives of CPS design while solving semantic heterogeneity issues; and finally, determining real industry applications for the presented approach. We first devise a knowledge-driven approach allowing for the integration of standards and standardization frameworks into an Industry 4.0 knowledge graph (I40KG). The standards ontology is used for representing the main properties of standards and standardization frameworks, as well as relationships among them. The I40KG permits to integrate standards and standardization frameworks while solving specific semantic heterogeneity conflicts in the domain. Further, we semantically describe standards in knowledge graphs. To this end, standards of core importance for I40 scenarios are considered, i.e., the Reference Architectural Model for I40 (RAMI4.0), AutomationML, and the Supply Chain Operation Reference Model (SCOR). In addition, different perspectives of entities describing CPS are integrated into the knowledge graphs. To evaluate the proposed methods, we rely on empirical evaluations as well as on the development of concrete use cases. The attained results provide evidence that a knowledge graph approach enables the effective data integration of entities in I40 scenarios while solving semantic interoperability conflicts, thus empowering the communication in smart factories

Single-cell RNA Sequencing (scRNA-seq) Exploratory Analyses to Investigate Aging-dependent Changes and Regional Heterogeneity in Glial Cells

My thesis project research consisted of single-cell RNA-sequencing and bioinformatics using R programming and Neuroscience Multi-omic Data Archive (NeMO) Analytics to examine the impact of aging, brain region, and other variables on the genotypes and phenotypes of oligodendrocytes (OLGs) and oligodendrocyte precursor cells (OPCs). The overarching goal was to increase understanding of glial cell fate and function. After determining bioinformatical findings, follow-up wet-bench experiments were performed to validate results. RNA in situ hybridization and immunohistochemistry were performed to confirm differential gene expression across cell types and brain regions. These experiments also revealed any changes in oligodendrocyte (OLG) development and maturation with the loss of the gene of interest (Choi et al., 2018). The conclusions impact the broader neurobioinformatics field, specifically revolving around the relationship between neural-glial cell interactions and neurodegenerative diseases