Synthetic Data-Enhanced Deep Learning For Quality Control Of Automated Welding Processes

Automotive production systems are designed to produce large quantities in high quality and short throughput times and are therefore organized as line production. This places high quality requirements on the joining processes in automotive body shops, in which automated, robot-guided welding is a key process. The quality of these thermal joining processes depends on various physical and chemical influencing factors, whose interactions cannot be explicitly modelled. This leads to enormous quality assurance efforts in several quality control loops, which may include visual inspections, non-destructive testing of samples to assess the internal structure and destructive testing of samples for the assessment of mechanical properties such as tensile strength. Due to the increasing availability of data in automated processes and the complexity of welding processes, the application of Deep Learning has a great potential to reduce quality control efforts in automotive body shops. Using Deep Learning to leverage process data and accurately predict quality parameters in welding processes is investigated in research, yet model training requires a large, balanced and annotated dataset, whose generation is time and cost intensive, particularly for production data. However, there are generative AI methods such as Generative Adversarial Networks (GANs) that are able to generate synthetic data and thus offer the potential to generate a large amount of annotated production data with relatively little effort. This paper presents a systematic approach to evaluate the potential of incorporating synthetic data in a real-world production dataset to improve quality control using Deep Learning. The approach is validated for the analysis of real-world ultrasound images of resistance spot welding (RSW) processes from the automotive industry. Different Deep Learning architectures to generate synthetic data are compared. Results show that adding synthetic data to the training dataset can improve the accuracy of Deep Learning models for quality monitoring in welding processes

Sex-Specific Differences in Shoaling Affect Parasite Transmission in Guppies

Background: Individuals have to trade-off the costs and benefits of group membership during shoaling behaviour. Shoaling can increase the risk of parasite transmission, but this cost has rarely been quantified experimentally. Guppies (Poecilia reticulata) are a model system for behavioural studies, and they are commonly infected by gyrodactylid parasites, notorious fish pathogens that are directly transmitted between guppy hosts. Methodology/Principal Findings:Parasite transmission in single sex shoals of male and female guppies were observed using an experimental infection of Gyrodactylus turnbulli. Parasite transmission was affected by sex-specific differences in host behaviour, and significantly more parasites were transmitted when fish had more frequent and more prolonged contact with each other. Females shoaled significantly more than males and had a four times higher risk to contract an infection. Conclusions/Significance: Intersexual differences in host behaviours such as shoaling are driven by differences in natural and sexual selection experienced by both sexes. Here we show that the potential benefits of an increased shoaling tendency are traded off against increased risks of contracting an infectious parasite in a group-living species

Risk of Childhood Cancers Associated with Residence in Agriculturally Intense Areas in the United States

Background: The potential for widespread exposure to agricultural pesticides through drift during application raises concerns about possible health effects to exposed children living in areas of high agricultural activity. Objectives: We evaluated whether residence in a county with greater agricultural activity was associated with risk of developing cancer in children \u3c 15 years of age. Methods: Incidence data for U.S. children 0–14 years of age diagnosed with cancer between 1995 and 2001 were provided by member registries of the North American Association of Central Cancer Registries. We determined percent cropland for each county using agricultural census data, and used the overall study distribution to classify agriculturally intense counties. We estimated odds ratios and 95% confidence intervals for all ages and 5-year age groups for total cancers and selected cancer sites using logistic regression. Results: Our study results showed statistically significant increased risk estimates for many types of childhood cancers associated with residence at diagnosis in counties having a moderate to high level of agricultural activity, with a remarkably consistent dose–response effect seen for counties having ≥ 60% of the total county acreage devoted to farming. Risk for different cancers varied by type of crop. Conclusions: Although interpretation is limited by the ecologic design, in this study we were able to evaluate rarer childhood cancers across a diverse agricultural topography. The findings of this exploratory study support a continued interest in the possible impact of long-term, low-level pesticide exposure in communities located in agriculturally intense areas

Magnetic resonance imaging evidence for presymptomatic change in thalamus and caudate in familial Alzheimer’s disease

Amyloid imaging studies of presymptomatic familial Alzheimer’s disease have revealed the striatum and thalamus to be the earliest sites of amyloid deposition. This study aimed to investigate whether there are associated volume and diffusivity changes in these subcortical structures during the presymptomatic and symptomatic stages of familial Alzheimer’s disease. As the thalamus and striatum are involved in neural networks subserving complex cognitive and behavioural functions, we also examined the diffusion characteristics in connecting white matter tracts. A cohort of 20 presenilin 1 mutation carriers underwent volumetric and diffusion tensor magnetic resonance imaging, neuropsychological and clinical assessments; 10 were symptomatic, 10 were presymptomatic and on average 5.6 years younger than their expected age at onset; 20 healthy control subjects were also studied. We conducted region of interest analyses of volume and diffusivity changes in the thalamus, caudate, putamen and hippocampus and examined diffusion behaviour in the white matter tracts of interest (fornix, cingulum and corpus callosum). Voxel-based morphometry and tract-based spatial statistics were also used to provide unbiased whole-brain analyses of group differences in volume and diffusion indices, respectively. We found that reduced volumes of the left thalamus and bilateral caudate were evident at a presymptomatic stage, together with increased fractional anisotropy of bilateral thalamus and left caudate. Although no significant hippocampal volume loss was evident presymptomatically, reduced mean diffusivity was observed in the right hippocampus and reduced mean and axial diffusivity in the right cingulum. In contrast, symptomatic mutation carriers showed increased mean, axial and in particular radial diffusivity, with reduced fractional anisotropy, in all of the white matter tracts of interest. The symptomatic group also showed atrophy and increased mean diffusivity in all of the subcortical grey matter regions of interest, with increased fractional anisotropy in bilateral putamen. We propose that axonal injury may be an early event in presymptomatic Alzheimer’s disease, causing an initial fall in axial and mean diffusivity, which then increases with loss of axonal density. The selective degeneration of long-coursing white matter tracts, with relative preservation of short interneurons, may account for the increase in fractional anisotropy that is seen in the thalamus and caudate presymptomatically. It may be owing to their dense connectivity that imaging changes are seen first in the thalamus and striatum, which then progress to involve other regions in a vulnerable neuronal network

Human α2β1HI CD133+VE epithelial prostate stem cells express low levels of active androgen receptor

Stem cells are thought to be the cell of origin in malignant transformation in many tissues, but their role in human prostate carcinogenesis continues to be debated. One of the conflicts with this model is that cancer stem cells have been described to lack androgen receptor (AR) expression, which is of established importance in prostate cancer initiation and progression. We re-examined the expression patterns of AR within adult prostate epithelial differentiation using an optimised sensitive and specific approach examining transcript, protein and AR regulated gene expression. Highly enriched populations were isolated consisting of stem (α(2)β(1)(HI) CD133(+VE)), transiently amplifying (α(2)β(1)(HI) CD133(-VE)) and terminally differentiated (α(2)β(1)(LOW) CD133(-VE)) cells. AR transcript and protein expression was confirmed in α(2)β(1)(HI) CD133(+VE) and CD133(-VE) progenitor cells. Flow cytometry confirmed that median (±SD) fraction of cells expressing AR were 77% (±6%) in α(2)β(1)(HI) CD133(+VE) stem cells and 68% (±12%) in α(2)β(1)(HI) CD133(-VE) transiently amplifying cells. However, 3-fold lower levels of total AR protein expression (peak and median immunofluorescence) were present in α(2)β(1)(HI) CD133(+VE) stem cells compared with differentiated cells. This finding was confirmed with dual immunostaining of prostate sections for AR and CD133, which again demonstrated low levels of AR within basal CD133(+VE) cells. Activity of the AR was confirmed in prostate progenitor cells by the expression of low levels of the AR regulated genes PSA, KLK2 and TMPRSS2. The confirmation of AR expression in prostate progenitor cells allows integration of the cancer stem cell theory with the established models of prostate cancer initiation based on a functional AR. Further study of specific AR functions in prostate stem and differentiated cells may highlight novel mechanisms of prostate homeostasis and insights into tumourigenesis

Splenic artery embolization in a woman with bleeding gastric varices and splenic vein thrombosis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Gastric variceal bleeding due to splenic vein thrombosis is a life-threatening situation and is often difficult to manage by endoscopy. In the worst cases, an emergency splenectomy may be required to stop variceal bleeding.</p> <p>Case presentation</p> <p>We report the case of a 60-year-old Caucasian woman with bleeding gastric varices secondary to splenic vein thrombosis treated by splenic artery embolization. Successful embolization was performed by depositing coils into the splenic artery resulting in cessation of variceal bleeding. After embolization there was no recurrence of bleeding.</p> <p>Conclusion</p> <p>Splenic artery embolization can be an effective and definite treatment for variceal bleeding secondary to splenic vein thrombosis.</p

Non-Fermi-liquid d-wave metal phase of strongly interacting electrons

Developing a theoretical framework for conducting electronic fluids qualitatively distinct from those described by Landau's Fermi-liquid theory is of central importance to many outstanding problems in condensed matter physics. One such problem is that, above the transition temperature and near optimal doping, high-transition-temperature copper-oxide superconductors exhibit `strange metal' behaviour that is inconsistent with being a traditional Landau Fermi liquid. Indeed, a microscopic theory of a strange-metal quantum phase could shed new light on the interesting low-temperature behaviour in the pseudogap regime and on the d-wave superconductor itself. Here we present a theory for a specific example of a strange metal---the 'd-wave metal'. Using variational wavefunctions, gauge theoretic arguments, and ultimately large-scale density matrix renormalization group calculations, we show that this remarkable quantum phase is the ground state of a reasonable microscopic Hamiltonian---the usual t-J model with electron kinetic energy $t$ and two-spin exchange $J$ supplemented with a frustrated electron `ring-exchange' term, which we here examine extensively on the square lattice two-leg ladder. These findings constitute an explicit theoretical example of a genuine non-Fermi-liquid metal existing as the ground state of a realistic model.Comment: 22 pages, 12 figures: 6 pages, 7 figures of main text + 16 pages, 5 figures of Supplementary Information; this is approximately the version published in Nature, minus various subedits in the main tex

Characterisation of feline renal cortical fibroblast cultures and their transcriptional response to transforming growth factor beta 1

Chronic kidney disease (CKD) is common in geriatric cats, and the most prevalent pathology is chronic tubulointerstitial inflammation and fibrosis. The cell type predominantly responsible for the production of extra-cellular matrix in renal fibrosis is the myofibroblast, and fibroblast to myofibroblast differentiation is probably a crucial event. The cytokine TGF-β1 is reportedly the most important regulator of myofibroblastic differentiation in other species. The aim of this study was to isolate and characterise renal fibroblasts from cadaverous kidney tissue of cats with and without CKD, and to investigate the transcriptional response to TGF-β1

Fast X-Ray Fluorescence Microtomography of Hydrated Biological Samples

Metals and metalloids play a key role in plant and other biological systems as some of them are essential to living organisms and all can be toxic at high concentrations. It is therefore important to understand how they are accumulated, complexed and transported within plants. In situ imaging of metal distribution at physiological relevant concentrations in highly hydrated biological systems is technically challenging. In the case of roots, this is mainly due to the possibility of artifacts arising during sample preparation such as cross sectioning. Synchrotron x-ray fluorescence microtomography has been used to obtain virtual cross sections of elemental distributions. However, traditionally this technique requires long data acquisition times. This has prohibited its application to highly hydrated biological samples which suffer both radiation damage and dehydration during extended analysis. However, recent advances in fast detectors coupled with powerful data acquisition approaches and suitable sample preparation methods can circumvent this problem. We demonstrate the heightened potential of this technique by imaging the distribution of nickel and zinc in hydrated plant roots. Although 3D tomography was still impeded by radiation damage, we successfully collected 2D tomograms of hydrated plant roots exposed to environmentally relevant metal concentrations for short periods of time. To our knowledge, this is the first published example of the possibilities offered by a new generation of fast fluorescence detectors to investigate metal and metalloid distribution in radiation-sensitive, biological samples