Systematic adjustment of the joining time in pulsed laser beam welding of aluminum-copper joints by means of a closed-loop control

Electric mobility has become increasingly important in recent years. For this purpose, the use of copper is essential due to its electrical properties. In order to save weight and costs, copper is replaced by aluminum in many electrical conductors.In this paper, the required joining time for pulsed laser beam welding of aluminum-copper joints is investigated to minimize the mixing of both materials. By using an external controller and photodiodes, it was possible to develop a real-time pulse control laser welding process based on process emissions. The spectral emission was used to detect when the lower joining partner is reached during the deep welding process. The control enables the adjustment of different joining times, on the one hand by a signal drop of the spectral emission, on the other hand by a specific time. The laser pulse was terminated between 500 - 800 [my]s after reaching this event. This led to differences in process conditions, resulting in significant changes in mechanical properties. In this way, a decisive influence was exerted on the resulting joining zone. The interaction duration and the work piece transition are of primary interest. By comparing the results with high-speed recordings in the half-section set-up, the resulting mechanisms can be identified. It could be shown that the breakup time have an high impact for the shear tensile force and the welding depth. A Change in the breakup time of 40 [my]s could lead to high changes in the tensile shear force

Laser-assisted joining of AISI 304 thin sheets with polymers

Laser-assisted metal-polymer joining gains importance in several applications due to the possibility of a direct connection between both materials. Aside from lightweight construction, a direct metal-polymer connection shows a high economic potential especially in large series production, e.g. domestic appliances. Based on this motivation, laser-assisted simultaneous joining of AISI 304 thin sheets (0.3…1.0 mm, X5CrNi18-10) with unreinforced polypropylene (PP) as well as acrylonitrile butadiene styrene (ABS) is carried out. Starting from a generally valid process description based on the energy per sheet thickness, the distortion as well as the mechanical properties are examined, whereby up to 17.4 MPa are reached and the tensile shear strength drops by at least 15 % during alternating climate test (-20…75 °C, 40…75 % rel. humidity). Further investigations under cyclic load showed, that long life fatigue strength (5∙106 cycles) is achieved at about 47 % of the initial tensile shear strength

Process control by real-time pulse shaping in laser beam welding of different material combinations

Joining of metallic material combinations with limited solubility is a challenging task. Because of low solubility, such material combinations lead to the formation of intermetallic compounds (IMC) during common weld bath. IMC then lead to increased hardness and brittleness. Generally, these properties are undesirable and the aim is to reduce intermetallics to a minimum. In this contribution, a process control by real-time pulse shaping is realized, whereby the power is adjusted in each individual pulse. The material-specific emissions are continuously detected by photodiodes and used as control variable. By equipping the photodiodes with band-pass filters, the wavelength can be selected in a material-dependent manner. The control loop including data processing and pulse shaping as well as the connection to the power supply of the laser beam source is realized by a novel system in less than 10 µs. This enables laser welding of different metals with a nearly constant penetration depth at the boundary layer and, therefore, the limitation of IMC

Acoustic process monitoring in laser beam welding

Structure-borne acoustic emission (AE) measurement shows major advantages regarding quality assurance and process control in industrial applications. In this paper, laser beam welding of steel and aluminum was carried out under varying process parameters (welding speed, focal position) in order to provide data by means of structure-borne AE and simultaneously high-speed video recordings. The analysis is based on conventionally (e.g. filtering, autocorrelation, spectrograms) as well as machine learning methods (convolutional neural nets) and showed promising results with respect to the use of structure-borne AE for process monitoring using the example of spatter formation

On the Impact of Cross-Domain Data on German Language Models

Traditionally, large language models have been either trained on general web crawls or domain-specific data. However, recent successes of generative large language models, have shed light on the benefits of cross-domain datasets. To examine the significance of prioritizing data diversity over quality, we present a German dataset comprising texts from five domains, along with another dataset aimed at containing high-quality data. Through training a series of models ranging between 122M and 750M parameters on both datasets, we conduct a comprehensive benchmark on multiple downstream tasks. Our findings demonstrate that the models trained on the cross-domain dataset outperform those trained on quality data alone, leading to improvements up to $4.45\%$ over the previous state-of-the-art. The models are available at https://huggingface.co/ikim-uk-essenComment: 13 pages, 1 figure, accepted at Findings of the Association for Computational Linguistics: EMNLP 202

Systemic sclerosis-associated pulmonary hypertension: why disease-specific composite endpoints are needed

Pulmonary arterial hypertension (PAH) is a serious complication of systemic sclerosis (SSc). In clinical trials PAH-SSc has been grouped with other forms, including idiopathic PAH. The primary endpoint for most pivotal studies was improvement in exercise capacity. However, composite clinical endpoints that better reflect long-term outcome may be more meaningful. We discuss potential endpoints and consider why the same measures may not be appropriate for both idiopathic PAH and PAH-SSc due to inherent differences in clinical outcome and management strategies of these two forms of PAH. Failure to take this into account may compromise progress in managing PAH in SSc

SARS-CoV-2 surveillance in households with and without asthmatic/allergic children: The Human Epidemiology and Response to SARS-CoV-2 study (HEROS)

Rationale: Whether children and people with asthma and allergic diseases are at increased risk for SARS-CoV-2 infection is not known. Neither is their role in household transmission. Methods: Biweekly nasal sample collections and weekly surveys were conducted to identify incident SARS-CoV-2 infections among children (\u3c13 \u3eyears) and teenagers (13-21 years) enrolled in asthma/allergic disease focused cohorts, and their household members, from May 2020-February 2021. Probability of subject/household infections and household transmissions were calculated using time-to-event analyses, and factors associated with infection and transmission risk using regression analyses. Results: Household (N=1,394) and subject (N=4,142) SARS-CoV-2 infection probability was 25.8% and 14.0%, respectively, and was similar for children (14.0%,CI:8.0-19.6%), teenagers (12.1%,CI:8.2-15.9%), and adults (14.0%,CI:9.5-18.4%). Infections were symptomatic in 24.5% of children, 41.2% of teenagers, and 62.5% of adults. Exposure to both symptomatic (aHR=87.39,CI:58.02-131.63) and asymptomatic (aHR=27.80,CI:17.16–45.03) infected household members was a risk factor for infection. Food allergy was associated with decreased infection risk (aHR=0.50,CI:0.32-0.81), but asthma was not (aHR=1.04,CI:0.73-1.46). Household infection risk was associated with attending in-person school (aHR=1.67,CI:1.09-2.57). Household secondary attack rate was 57.7%. Decreased risk of household transmission was associated with teen age, lower BMI, and lower viral load. Conclusions: Asthma does not increase risk of SARS-CoV-2 infection, while food allergy is protective. SARS-CoV-2 infection risk in children is similar to that of teenagers and adults. SARS-CoV-2 transmission risk and secondary attack rate is much higher than previously estimated in households with children, likely driven by the high frequency of asymptomatic childhood infections

The contribution of insects to global forest deadwood decomposition

The amount of carbon stored in deadwood is equivalent to about 8 per cent of the global forest carbon stocks. The decomposition of deadwood is largely governed by climate with decomposer groups—such as microorganisms and insects—contributing to variations in the decomposition rates. At the global scale, the contribution of insects to the decomposition of deadwood and carbon release remains poorly understood. Here we present a field experiment of wood decomposition across 55 forest sites and 6 continents. We find that the deadwood decomposition rates increase with temperature, and the strongest temperature effect is found at high precipitation levels. Precipitation affects the decomposition rates negatively at low temperatures and positively at high temperatures. As a net effect—including the direct consumption by insects and indirect effects through interactions with microorganisms—insects accelerate the decomposition in tropical forests (3.9% median mass loss per year). In temperate and boreal forests, we find weak positive and negative effects with a median mass loss of 0.9 per cent and −0.1 per cent per year, respectively. Furthermore, we apply the experimentally derived decomposition function to a global map of deadwood carbon synthesized from empirical and remote-sensing data, obtaining an estimate of 10.9 ± 3.2 petagram of carbon per year released from deadwood globally, with 93 per cent originating from tropical forests. Globally, the net effect of insects may account for 29 per cent of the carbon flux from deadwood, which suggests a functional importance of insects in the decomposition of deadwood and the carbon cycle

SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues.

There is pressing urgency to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2), which causes the disease COVID-19. SARS-CoV-2 spike (S) protein binds angiotensin-converting enzyme 2 (ACE2), and in concert with host proteases, principally transmembrane serine protease 2 (TMPRSS2), promotes cellular entry. The cell subsets targeted by SARS-CoV-2 in host tissues and the factors that regulate ACE2 expression remain unknown. Here, we leverage human, non-human primate, and mouse single-cell RNA-sequencing (scRNA-seq) datasets across health and disease to uncover putative targets of SARS-CoV-2 among tissue-resident cell subsets. We identify ACE2 and TMPRSS2 co-expressing cells within lung type II pneumocytes, ileal absorptive enterocytes, and nasal goblet secretory cells. Strikingly, we discovered that ACE2 is a human interferon-stimulated gene (ISG) in vitro using airway epithelial cells and extend our findings to in vivo viral infections. Our data suggest that SARS-CoV-2 could exploit species-specific interferon-driven upregulation of ACE2, a tissue-protective mediator during lung injury, to enhance infection

REQUITE: A prospective multicentre cohort study of patients undergoing radiotherapy for breast, lung or prostate cancer

Purpose: REQUITE aimed to establish a resource for multi-national validation of models and biomarkers that predict risk of late toxicity following radiotherapy. The purpose of this article is to provide summary descriptive data. Methods: An international, prospective cohort study recruited cancer patients in 26 hospitals in eight countries between April 2014 and March 2017. Target recruitment was 5300 patients. Eligible patients had breast, prostate or lung cancer and planned potentially curable radiotherapy. Radiotherapy was prescribed according to local regimens, but centres used standardised data collection forms. Pre-treatment blood samples were collected. Patients were followed for a minimum of 12 (lung) or 24 (breast/prostate) months and summary descriptive statistics were generated. Results: The study recruited 2069 breast (99% of target), 1808 prostate (86%) and 561 lung (51%) cancer patients. The centralised, accessible database includes: physician-(47,025 forms) and patient-(54,901) reported outcomes; 11,563 breast photos; 17,107 DICOMs and 12,684 DVHs. Imputed genotype data are available for 4223 patients with European ancestry (1948 breast, 1728 prostate, 547 lung). Radiation-induced lymphocyte apoptosis (RILA) assay data are available for 1319 patients. DNA (n = 4409) and PAXgene tubes (n = 3039) are stored in the centralised biobank. Example prevalences of 2-year (1-year for lung) grade >= 2 CTCAE toxicities are 13% atrophy (breast), 3% rectal bleeding (prostate) and 27% dyspnoea (lung). Conclusion: The comprehensive centralised database and linked biobank is a valuable resource for the radiotherapy community for validating predictive models and biomarkers. Patient summary: Up to half of cancer patients undergo radiation therapy and irradiation of surrounding healthy tissue is unavoidable. Damage to healthy tissue can affect short-and long-term quality-of-life. Not all patients are equally sensitive to radiation "damage" but it is not possible at the moment to identify those who are. REQUITE was established with the aim of trying to understand more about how we could predict radiation sensitivity. The purpose of this paper is to provide an overview and summary of the data and material available. In the REQUITE study 4400 breast, prostate and lung cancer patients filled out questionnaires and donated blood. A large amount of data was collected in the same way. With all these data and samples a database and biobank were created that showed it is possible to collect this kind of information in a standardised way across countries. In the future, our database and linked biobank will be a resource for research and validation of clinical predictors and models of radiation sensitivity. REQUITE will also enable a better understanding of how many people suffer with radiotherapy toxicity