138 research outputs found

    Method for Semi-Automated Improvement of Smart Factories Using Synthetic Data and Cause-Effect-Relationships

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    Smart factories, driven by the integration of automation and digital technologies, have revolutionized industrial production by enhancing efficiency, productivity, and flexibility. However, the optimization and continuous improvement of these complex systems present numerous challenges, especially when real-world data collection is time-consuming, expensive, or limited. In this paper, we propose a novel method for semi-automated improvement of smart factories using synthetic data and cause-effect-relations, while incorporating the aspect of self-organization. The method leverages the power of synthetic data generation techniques to create representative datasets that mimic the behaviour of real-world manufacturing systems. These synthetic datasets serve together with the cause-and-effect relationships as a valuable resource for factory optimization, as they enable extensive experimentation and analysis without the constraints of limited or costly real-world data. Furthermore, the method embraces the concept of self-organization within smart factories. By allowing the system to adapt and optimize itself based on feedback from the synthetic data, cause-effect-relationships, the factory can dynamically reconfigure and adjust its processes. To facilitate the improvement process, the method integrates the synthetic data with advanced analytics and machine learning algorithms as well as and the cause-and-effect relationships. This synergy between human expertise and technological advancements represents a compelling path towards a truly optimized smart factory of the future

    Approach For Autonomous Control Of Intralogistics Considering Deterministic And Probabilistic Material Demand Information In Flexible Production Systems

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    In today's dynamic production landscape, flexible and resilient production systems are essential to meet the constant changes in internal product and production requirements as well as external market and customer demands. To meet these challenges, various flexible and resilient production system approaches offer the necessary structural, process-related and technological flexibility and resilience. However, the intralogistics material provision within these complex production systems is challenging due to increasing degrees of freedom and uncertainties caused by emerging turbulence, which has even risen very sharply in recent years due to global instability. This makes it difficult to coordinate material demands and material provision in the production system precisely regarding location and quantity. This paper presents a comprehensive approach for determining the material requirements and autonomously executing the corresponding material provision processes in a complex production system, which considers both deterministic and probabilistic information about the material demand’s location, quantity, and time. Utilizing autonomous control in intralogistics decentralizes complexity management in flexible production systems by transferring decision-making and process execution tasks to the system elements. For the development and verification of the comprehensive approach, an experimental research study was pursued based on a flexible production system, including simulation and practical experiments. Defining the deterministic and probabilistic material demands is based on the Monte Carlo method for carrying out simulation experiments with parameter variation. The autonomously controlled, target size-optimized execution of material provision to fulfil the determined material demands is based on an agent-based modelling and control approach for manual and automated intralogistics transport resources. The study showed that improved logistics performance (throughput time and adherence to schedules) can be achieved in flexible production systems in the event of turbulences by considering deterministic and probabilistic material demand information together with autonomous control of material provision

    Durchblick im Variantendschungel : visuelle Assistenzsysteme als FlexibilitÀtshebel auf dem Shop Floor

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    Die steigende Personalisierbarkeit von Produkten fuhrt zu einem wachsenden Variantenspektrum in der Fertigung. Nicht zuletzt aufgrund der damit einhergehenden ProduktionskomplexitĂ€t und den hohen Wandlungsanforderungen an die Montage werden viele komplexe StĂŒckgĂŒter weiterhin ĂŒberwiegend manuell montiert. Visuelle Assistenzsysteme geben den Mitarbeitern die nötige HandlungsunterstĂŒtzung, wenn kein Produkt dem anderen gleicht und damit das Fehlerpotenzial steigt

    Genes and gene clusters related to genotype and drought induced variation in saccharification potential, lignin content, and wood anatomical traits in Populus nigra:Saccharification, Wood Anatomy and Gene Clusters

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    Wood is a renewable resource that can be employed for the production of second generation biofuels by enzymatic saccharification and subsequent fermentation. Knowledge on how the saccharification potential is affected by genotype-related variation of wood traits and drought is scarce. Here, we used three Populus nigra genotypes from habitats differing in water availability to (i) investigate the relationships between wood anatomy, lignin content and saccharification and (ii) identify genes and co-expressed gene clusters related to genotype and drought-induced variation in wood traits and saccharification potential. The three poplar genotypes differed in wood anatomy, lignin content and saccharification potential. Drought resulted in reduced cambial activity, decreased vessel and fibre lumina, and increased the saccharification potential. The saccharification potential was unrelated to lignin content as well as to most wood anatomical traits. RNA sequencing of the developing xylem revealed that 1.5% of the analysed genes were differentially expressed in response to drought, while 67% differed among the genotypes. Weighted gene correlation network analysis identified modules of co-expressed genes correlated with saccharification potential. These modules were enriched in gene ontology terms related to cell wall polysaccharide biosynthesis and modification and vesicle transport, but not to lignin biosynthesis. Among the most strongly saccharification-correlated genes, those with regulatory functions, especially kinases were prominent. We further identified transcription factors whose transcript abundances differed among genotypes, and which were co45 regulated with genes for biosynthesis and modifications of hemicelluloses and pectin. Overall, our study suggests that the regulation of pectin and hemicellulose metabolism is a promising target for improving wood quality of second generation bioenergy crops. The causal relationship of the identified genes and pathways with saccharification potential needs to be validated in further experiments.publishersversionPeer reviewe

    Integration of molecular functions at the ecosystemic level: breakthroughs and future goals of environmental genomics and post-genomics

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    Environmental genomics and genome-wide expression approaches deal with large-scale sequence-based information obtained from environmental samples, at organismal, population or community levels. To date, environmental genomics, transcriptomics and proteomics are arguably the most powerful approaches to discover completely novel ecological functions and to link organismal capabilities, organism–environment interactions, functional diversity, ecosystem processes, evolution and Earth history. Thus, environmental genomics is not merely a toolbox of new technologies but also a source of novel ecological concepts and hypotheses. By removing previous dichotomies between ecophysiology, population ecology, community ecology and ecosystem functioning, environmental genomics enables the integration of sequence-based information into higher ecological and evolutionary levels. However, environmental genomics, along with transcriptomics and proteomics, must involve pluridisciplinary research, such as new developments in bioinformatics, in order to integrate high-throughput molecular biology techniques into ecology. In this review, the validity of environmental genomics and post-genomics for studying ecosystem functioning is discussed in terms of major advances and expectations, as well as in terms of potential hurdles and limitations. Novel avenues for improving the use of these approaches to test theory-driven ecological hypotheses are also explored

    Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma

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    Burkitt lymphoma (BL) is the most common B-cell lymphoma in children. Within the International Cancer Genome Consortium (ICGC), we performed whole genome and transcriptome sequencing of 39 sporadic BL. Here, we unravel interaction of structural, mutational, and transcriptional changes, which contribute to MYC oncogene dysregulation together with the pathognomonic IG-MYC translocation. Moreover, by mapping IGH translocation breakpoints, we provide evidence that the precursor of at least a subset of BL is a B-cell poised to express IGHA. We describe the landscape of mutations, structural variants, and mutational processes, and identified a series of driver genes in the pathogenesis of BL, which can be targeted by various mechanisms, including IG-non MYC translocations, germline and somatic mutations, fusion transcripts, and alternative splicing

    The genomic and transcriptional landscape of primary central nervous system lymphoma

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    Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Molecular drivers of PCNSL have not been fully elucidated. Here, we profile and compare the whole-genome and transcriptome landscape of 51 CNS lymphomas (CNSL) to 39 follicular lymphoma and 36 DLBCL cases outside the CNS. We find recurrent mutations in JAK-STAT, NFkB, and B-cell receptor signaling pathways, including hallmark mutations in MYD88 L265P (67%) and CD79B (63%), and CDKN2A deletions (83%). PCNSLs exhibit significantly more focal deletions of HLA-D (6p21) locus as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis are significantly enriched in PCNSL. TERT gene expression is significantly higher in PCNSL compared to activated B-cell (ABC)-DLBCL. Transcriptome analysis clearly distinguishes PCNSL and systemic DLBCL into distinct molecular subtypes. Epstein-Barr virus (EBV)+ CNSL cases lack recurrent mutational hotspots apart from IG and HLA-DRB loci. We show that PCNSL can be clearly distinguished from DLBCL, having distinct expression profiles, IG expression and translocation patterns, as well as specific combinations of genetic alterations

    Clinical and virological characteristics of hospitalised COVID-19 patients in a German tertiary care centre during the first wave of the SARS-CoV-2 pandemic: a prospective observational study

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    Purpose: Adequate patient allocation is pivotal for optimal resource management in strained healthcare systems, and requires detailed knowledge of clinical and virological disease trajectories. The purpose of this work was to identify risk factors associated with need for invasive mechanical ventilation (IMV), to analyse viral kinetics in patients with and without IMV and to provide a comprehensive description of clinical course. Methods: A cohort of 168 hospitalised adult COVID-19 patients enrolled in a prospective observational study at a large European tertiary care centre was analysed. Results: Forty-four per cent (71/161) of patients required invasive mechanical ventilation (IMV). Shorter duration of symptoms before admission (aOR 1.22 per day less, 95% CI 1.10-1.37, p < 0.01) and history of hypertension (aOR 5.55, 95% CI 2.00-16.82, p < 0.01) were associated with need for IMV. Patients on IMV had higher maximal concentrations, slower decline rates, and longer shedding of SARS-CoV-2 than non-IMV patients (33 days, IQR 26-46.75, vs 18 days, IQR 16-46.75, respectively, p < 0.01). Median duration of hospitalisation was 9 days (IQR 6-15.5) for non-IMV and 49.5 days (IQR 36.8-82.5) for IMV patients. Conclusions: Our results indicate a short duration of symptoms before admission as a risk factor for severe disease that merits further investigation and different viral load kinetics in severely affected patients. Median duration of hospitalisation of IMV patients was longer than described for acute respiratory distress syndrome unrelated to COVID-19

    More than smell - COVID-19 is associated with severe impairment of smell, taste, and chemesthesis

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    Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, generally lacked quantitative measurements, were mostly restricted to data from single countries. Here, we report the development, implementation and initial results of a multi-lingual, international questionnaire to assess self-reported quantity and quality of perception in three distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, 8 other, ages 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change+/-100) revealed a mean reduction of smell (-79.7+/- 28.7, mean+/- SD), taste (-69.0+/- 32.6), and chemesthetic (-37.3+/- 36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell, but also affects taste and chemesthesis. The multimodal impact of COVID-19 and lack of perceived nasal obstruction suggest that SARS-CoV-2 infection may disrupt sensory-neural mechanisms
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