Identifying cause-and-effect relationships of manufacturing errors using sequence-to-sequence learning

In car-body production the pre-formed sheet metal parts of the body are assembled on fully-automated production lines. The body passes through multiple stations in succession, and is processed according to the order requirements. The timely completion of orders depends on the individual station-based operations concluding within their scheduled cycle times. If an error occurs in one station, it can have a knock-on effect, resulting in delays on the downstream stations. To the best of our knowledge, there exist no methods for automatically distinguishing between source and knock-on errors in this setting, as well as establishing a causal relation between them. Utilizing real-time information about conditions collected by a production data acquisition system, we propose a novel vehicle manufacturing analysis system, which uses deep learning to establish a link between source and knock-on errors. We benchmark three sequence-to-sequence models, and introduce a novel composite time-weighted action metric for evaluating models in this context. We evaluate our framework on a real-world car production dataset recorded by Volkswagen Commercial Vehicles. Surprisingly we find that 71.68% of sequences contain either a source or knock-on error. With respect to seq2seq model training, we find that the Transformer demonstrates a better performance compared to LSTM and GRU in this domain, in particular when the prediction range with respect to the durations of future actions is increased

The impact and significance of tephra deposition on a Holocene forest environment in the North Cascades, Washington, USA.

© 2016 Elsevier Ltd. High-resolution palaeoecological analyses (stratigraphy, tephra geochemistry, radiocarbon dating, pollen and ordination) were used to reconstruct a Holocene vegetation history of a watershed in the Pacific Northwest of America to evaluate the effects and duration of tephra deposition on a forest environment and the significance of these effects compared to long-term trends. Three tephra deposits were detected and evaluated: MLF-T158 and MLC-T324 from the climactic eruption of Mount Mazama, MLC-T480 from a Late Pleistocene eruption of Mount Mazama and MLC-T485 from a Glacier Peak eruption. Records were examined from both the centre and fringe of the basin to elucidate regional and local effects. The significance of tephra impacts independent of underlying long-term trends was confirmed using partial redundancy analysis. Tephra deposition from the climactic eruption of Mount Mazama approximately 7600 cal. years BP caused a significant local impact, reflected in the fringe location by changes to open habitat vegetation (Cyperaceae and Poaceae) and changes in aquatic macrophytes (Myriophyllum spicatum, Potamogeton, Equisetum and the alga Pediastrum). There was no significant impact of the climactic Mazama tephra or other tephras detected on the pollen record of the central core. Changes in this core are potentially climate driven. Overall, significant tephra fall was demonstrated through high resolution analyses indicating a local effect on the terrestrial and aquatic environment, but there was no significant impact on the regional forest dependent of underlying environmental changes

Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria

The persuasiveness of genomic evidence has pressured scientific agencies to supplement or replace well-established methodologies to inform public health and food safety decision-making. This study of 52 epidemiologically defined Listeria monocytogenes isolates, collected between 1981 and 2011, including nine outbreaks, was undertaken (1) to characterize their phylogenetic relationship at finished genome-level resolution, (2) to elucidate the underlying genetic diversity within an endemic subtype, CC8, and (3) to re-evaluate the genetic relationship and epidemiology of a CC8-delimited outbreak in Canada in 2008. Genomes representing Canadian Listeria outbreaks between 1981 and 2010 were closed and manually annotated. Single nucleotide variants (SNVs) and horizontally acquired traits were used to generate phylogenomic models. Phylogenomic relationships were congruent with classical subtyping and epidemiology, except for CC8 outbreaks, wherein the distribution of SNV and prophages revealed multiple co-evolving lineages. Chronophyletic reconstruction of CC8 evolution indicates that prophage-related genetic changes among CC8 strains manifest as PFGE subtype reversions, obscuring the relationship between CC8 isolates, and complicating the public health interpretation of subtyping data, even at maximum genome resolution. The size of the shared genome interrogated did not change the genetic relationship measured between highly related isolates near the tips of the phylogenetic tree, illustrating the robustness of these approaches for routine public health applications where the focus is recent ancestry. The possibility exists for temporally and epidemiologically distinct events to appear related even at maximum genome resolution, highlighting the continued importance of epidemiological evidence

The Fermi-LAT Light Curve Repository

The Fermi Large Area Telescope (LAT) light curve repository (LCR) is a publicly available, continually updated library of gamma-ray light curves of variable Fermi-LAT sources generated over multiple timescales. The Fermi-LAT LCR aims to provide publication-quality light curves binned on timescales of 3 days, 7 days, and 30 days for 1525 sources deemed variable in the source catalog of the first 10 years of Fermi-LAT observations. The repository consists of light curves generated through full likelihood analyses that model the sources and the surrounding region, providing fluxes and photon indices for each time bin. The LCR is intended as a resource for the time-domain and multi-messenger communities by allowing users to quickly search LAT data to identify correlated variability and flaring emission episodes from gamma-ray sources. We describe the sample selection and analysis employed by the LCR and provide an overview of the associated data access portal.Comment: Accepted for publication in ApJ Supplement Serie

Verbundprojekt: IIP-Ecosphere - Next Level Ecosphere for Intelligent Industrial Production

Künstliche Intelligenz (KI) wird in der Produktion als wichtige Zukunftstechnologie gesehen. Ihre Anwendung im konkreten Produktionskontext stellt jedoch viele Unternehmen vor erhebliche Herausforderungen. Ziel des IIP-Ecosphere Projekts war es daher ein neuartiges Ökosystem – die Next Level Ecosphere for Intelligent Industrial Production (IIP-Ecosphere) – aufzubauen, welches die Nutzung von KI erleichtert und vorantreibt und damit zum Erreichen einer „nächste Ebene“ in der intelligenten Produktion beiträgt. Im Projekt wurden hierfür vielfältige Aktivitäten durchgeführt: In vier Think Tanks wurden innovative Methoden in den Bereichen KI-Methoden, Plattformen, Data Sharing und KI-Geschäftsmodelle erforscht und entwickelt. Beiträge des KI-Accelerators wie der KI-Lösungskatalog und KI-Services zielen auf die Beschleunigung der Umsetzung von KI-Lösungen ab. Zudem wurden vier größere Demonstratoren für die Anwendung innovativer KI-Methoden in realen Produktionskontexten mit namhaften Unternehmen als Blueprints erfolgreich umgesetzt ebenso wie vier kleinere, dynamisch im Projekt definierte Demonstratoren mit externen Partnern. Die Sichtbarkeit und Vernetzung wurden durch zwei Regional Innovation Hubs vorangetrieben, die unter anderem Arbeitskreise und vielfältige Events organisiert haben. Zudem wurden die Ergebnisse des Projekts mit größeren Demonstratoren auf drei wichtigen Messen (Hannover Messe 2022 und 2023, EMO 2023) eine Vielzahl von Unternehmen vorgeführt. Im Ergebnis ist ein Ökosystem – die IIP-Ecosphere - entstanden mit starker Vernetzung der Partner, reichem Erfahrungsschatz und wichtigen Diensten, Lösungen und Assets. Zudem resultieren aus den Aktivitäten im Projekt vielfältige weitere Ergebnisse, welche in Unternehmen genutzt, wissenschaftlich publiziert und in neuen Projekten weiterentwickelt werden. Besondere Erwähnung als Ergebnis des Projekts verdient die flexible und anpassbare open source IIoT-Plattform (Industrie 4.0 Plattform), die im Projekt auf der Grundlage der Anforderungen von Unternehmen konzipiert, entwickelt sowie erfolgreich erprobt wurde und unter dem Branding oktoflow-Plattform nach Projektende weiterentwickelt und verwertet wird. Datei-Upload durch TIBArtificial intelligence (AI) is considered an important future technology in production. However, its application in a specific production context is a challenging task for many companies. The aim of the IIP-Ecosphere project was, therefore, to build an innovative ecosystem - the Next Level Ecosphere for Intelligent Industrial Production (IIP-Ecosphere) - which facilitates and advances the use of AI and thus contributes to reaching a "next level" in intelligent production. A variety of activities were carried out in the project: innovative methods in the areas of AI methods, platforms, data sharing and AI business models were researched and developed in four think tanks. Contributions from the AI Accelerator aim to accelerate the implementation of AI solutions. In addition, four larger demonstrators for the application of innovative AI methods in real production contexts were successfully developed as blueprints with well-known companies, and four smaller, dynamically defined demonstrators were implemented with external partners. Visibility and networking were promoted by two Regional Innovation Hubs, which, among other things, organized working groups and a variety of events. In addition, the results of the project were demonstrated to various companies with larger demonstrators at three important trade fairs (Hannover Messe 2022 and 2023, EMO 2023). The project result is an ecosystem - the IIP-Ecosphere - with a strong network of partners, a wealth of experience and important services, solutions, and assets. In addition, the activities in the project produced in a variety of other results, which are used in companies, published scientifically and further developed in new projects. One of these results is worth a special mention: the flexible and customizable open source IIoT platform (Industry 4.0 platform), which was designed, developed, and successfully tested in the project based on the requirements of companies. It will be further developed and exploited under the branding “oktoflow platform” after the end of the project

Volcanic impacts on the Holocene vegetation history of Britain and Ireland? A review and meta-analysis of the pollen evidence

Volcanic ash layers show that the products of Icelandic volcanism reached Britain and Ireland many times during the Holocene. Historical records suggest that at least one eruption, that of Laki in a.d. 1783, was associated with impacts on vegetation. These results raise the question: did Icelandic volcanism affect the Holocene vegetation history of Britain and Ireland? Several studies have used pollen data to address this issue but no clear consensus has been reached. We re-analyse the palynological data using constrained ordination with various representations of potential volcanic impacts. We find that the palynological evidence for volcanic impacts on vegetation is weak but suggest that this is a case of absence of evidence and is not necessarily evidence of absence of impact. To increase the chances of identifying volcanic impacts, future studies need to maximise temporal resolution, replicate results, and investigate a greater number of tephras in a broader range of locations, including more studies from lake sediments

COP-AF

Background Higher levels of inflammatory biomarkers are associated with an increased risk of perioperative atrial fibrillation (AF) and myocardial injury after noncardiac surgery (MINS). Colchicine is an anti-inflammatory drug that may prevent these complications. Methods We performed an international, randomised trial at 45 sites in 11 countries. Patients aged ≥55 years and undergoing major noncardiac thoracic surgery were randomised to receive oral colchicine 0·5mg twice daily or matching placebo, starting within four hours before surgery and continuing for ten days. Healthcare providers, patients, data collectors, and adjudicators were blinded to treatment assignment. The co-primary outcomes were clinically important perioperative AF and MINS during 14 days of follow-up. This trial is registered at ClinicalTrials.gov (NCT03310125). Findings We enrolled 3209 patients between February 14, 2018, and June 27, 2023. Clinically important AF developed in 103 of 1608 (6·4%) patients assigned to colchicine, and 120 of 1601 (7·5%) patients assigned to placebo, hazard ratio (HR) 0·85 (95% confidence interval [CI] 0·65-1·10), absolute risk reduction (ARR) 1·1%, 95% CI -0·7-2·8, p=0.22. MINS occurred in 295 (18·3%) patients assigned to colchicine, and 325 (20·3%) patients assigned to placebo, HR 0·89 (95% CI 0·76-1·05), ARR 2·0%, 95% CI -0·8-4·7, p=0.16. Non-infectious diarrhoea was more common in the colchicine group, 134 (8·3%) versus 38 (2·4%) events, HR 3·64 (95% CI 2·54-5·22), but did not prolong median length of hospital stay and led to only one readmission.. Interpretation In patients undergoing major noncardiac thoracic surgery, administration of colchicine did not significantly reduce the incidence of the co-primary outcomes clinically important AF or MINS. While colchicine increased the risk of mostly benign non-infectious diarrhoea, there was an encouraging trend of fewer cardiovascular events with colchicine that requires further research.Canadian Institutes of Health Research, Accelerating Clinical Trials Consortium, and others

Estimating the Poverty Impacts of Trade Liberalization

As a new round of World Trade Organization negotiations is being launched with greater emphasis on developing country participation, a body of literature is emerging which quantifies how international trade affects the poor in developing countries. This survey summarizes and classifies thirty-five studies from this literature into four methodological categories: cross-country regression, partial-equilibrium/cost-of-living analysis, general-equilibrium simulation, and micro-macro synthesis. These categories encompass a broad range of methodologies in current use. The continuum of approaches is bounded on one end by econometric analysis of household expenditure data, which is the traditional domain of poverty specialists, and sometimes labeled the “bottom-up” approach. On the other end of the continuum are computable general equilibrium models based on national accounts data, or what might be called the “top-down” approach. Another feature of several recent trade/poverty studies – and one of the primary conclusions to emerge from the October 2000 Conference on Poverty and the International Economy sponsored by Globkom and the World Bank – is recognition that factor markets are perhaps the most important linkage between trade and poverty, since households tend to be much more specialized in income than they are in consumption. Meanwhile, survey data on the income sources of developing-country households has become increasingly available. As a result, this survey gives particular emphasis to the means by which studies address factor market linkages between trade and poverty. The general conclusion is that any analysis of trade and poverty needs to be informed by both the bottom-up and top-down perspectives. Indeed, recent “two-step” micro-macro studies sequentially link these two types of frameworks, such that general equilibrium mechanisms are incorporated along with detailed household survey information. Another methodology similar in spirit and also increasingly used involves the incorporation of large numbers of surveyed households into a general-equilibrium simulation model. Although most of these studies have so far been limited to a single region, these approaches can be readily adapted for multi-region modeling so that trade-poverty comparisons can be made across countries within a consistent framework

International Cross Section Estimates of Demand for Use in the GTAP Model

The making of projections often requires an economy-wide perspective, and the estimation of consumer demands at the international level. In this paper, an implicit, directly additive demand system (AIDADS) is estimated using cross-country data on consumer expenditures from the International Comparison Program (ICP), and then from Global Trade Analysis Project (GTAP) data. The two data sets are found to produce results that are quite consistent despite their differing origins, and the fact that the former is based on consumer goods that embody wholesale/retail margins, while margin demands are treated separately in GTAP. Given the similarity of the results, the estimation based on GTAP data is favored because it is readily matched to input-output based production and trade data, and provides valuable new information concerning how aggregate margin expenditures are related to per capita income