Perform Quality Control Research Articles

Slow improvement to the archiving quality of open datasets shared by researchers in ecology and evolution.

Many leading journals in ecology and evolution now mandate open data upon publication. Yet, there is very little oversight to ensure the completeness and reusability of archived datasets, and we currently have a poor understanding of the factors associated with high-quality data sharing. We assessed 362 open datasets linked to first- or senior-authored papers published by 100 principal investigators (PIs) in the fields of ecology and evolution over a period of 7 years to identify predictors of data completeness and reusability (data archiving quality). Datasets scored low on these metrics: 56.4% were complete and 45.9% were reusable. Data reusability, but not completeness, was slightly higher for more recently archived datasets and PIs with less seniority. Journal open data policy, PI gender and PI corresponding author status were unrelated to data archiving quality. However, PI identity explained a large proportion of the variance in data completeness (27.8%) and reusability (22.0%), indicating consistent inter-individual differences in data sharing practices by PIs across time and contexts. Several PIs consistently shared data of either high or low archiving quality, but most PIs were inconsistent in how well they shared. One explanation for the high intra-individual variation we observed is that PIs often conduct research through students and postdoctoral researchers, who may be responsible for the data collection, curation and archiving. Levels of data literacy vary among trainees and PIs may not regularly perform quality control over archived files. Our findings suggest that research data management training and culture within a PI's group are likely to be more important determinants of data archiving quality than other factors such as a journal's open data policy. Greater incentives and training for individual researchers at all career stages could improve data sharing practices and enhance data transparency and reusability.

Сучасні погляди на фізичну реабілітацію хворих на остеоартроз колінного суглоба

The purpose of the study was to study the main programs of physical rehabilitation in osteoarthritis of the knee joints based on an analytical analysis of current literature data. Materials and methods. Analytical and bibliosemantic methods were used in the research. Results and discussion. Treatment for osteoarthritis of the knee begins with conservative methods and moves to surgical treatment options when conservative treatment fails. Although drugs can help slow the progression of the pathology of inflammatory conditions, nevertheless, physical rehabilitation of patients is important for patients with any pathology of the knee joint. The main tasks contributing to the achievement of the goal of physical rehabilitation of patients with knee osteoarthritis are their integration into a quality social life, improving health and quality of life, lengthening the asymptomatic period. Although there is currently insufficient evidence to recommend one form of exercise instead of another, patients are likely to benefit from as specific advice as possible rather than simply encouraging exercise. Given the wide range of sound factual exercises that effectively reduce the intensity of pain and improve motor function in osteoarthritis, all patients should be encouraged to consider a particular type of exercise as a central part of their treatment plan. Individual approach to an individual patient is more effective and controls the correctness and regularity of exercise better. The article discusses in detail the methods of teaching patients and the effectiveness of patients performing physical exercises at home. These techniques have demonstrated a reduction in the severity of pain and an improvement in the functional mobility of the knee joints. Conclusion. Consequently, physical exercises help to reduce the severity of pain in the knee joints and improve functional mobility in osteoarthritis. The treatment of osteoarthritis requires a comprehensive and individualized approach to the patient. When choosing treatment methods, one should take into account the form and degree of neglect of osteoarthritis, concomitant diseases, as well as the availability of this therapy and the wishes of the patient. Education on the topic of the disease and its treatment options is the main element of therapeutic tactics. The use of remote patient education technologies in the context of the COVID-19 pandemic, quality control of exercise performance shows a decrease in the burden on primary care physicians and improves disease control. Multidisciplinary teams consisting of a rheumatologist, orthopedist, physiotherapist and psychologist must supervise patients

DARQ: Deep learning of quality control for stereotaxic registration of human brain MRI to the T1w MNI-ICBM 152 template

Linear registration to stereotaxic space is a common first step in many automated image-processing tools for analysis of human brain MRI scans. This step is crucial for the success of the subsequent image-processing steps. Several well-established algorithms are commonly used in the field of neuroimaging for this task, but none have a 100% success rate. Manual assessment of the registration is commonly used as part of quality control. To reduce the burden of this time-consuming step, we propose Deep Automated Registration Qc (DARQ), a fully automatic quality control method based on deep learning that can replace the human rater and accurately perform quality control assessment for stereotaxic registration of T1w brain scans.In a recently published study from our group comparing linear registration methods, we used a database of 9325 MRI scans and 64476 registrations from several publicly available datasets and applied seven linear registration tools to them. In this study, the resulting images that were assessed and labeled by a human rater are used to train a deep neural network to detect cases when registration failed. We further validated the results on an independent dataset of patients with multiple sclerosis, with manual QC labels available (n=1200).In terms of agreement with a manual rater, our automated QC method was able to achieve 89% accuracy and 85% true negative rate (equivalently 15% false positive rate) in detecting scans that should pass quality control in a balanced cross-validation experiments, and 96.1% accuracy and 95.5% true negative rate (or 4.5% FPR) when evaluated in a balanced independent sample, similar to manual QC rater (test-retest accuracy of 93%).The results show that DARQ is robust, fast, accurate, and generalizable in detecting failure in linear stereotaxic registrations and can substantially reduce QC time (by a factor of 20 or more) when processing large datasets.

Angong Niuhuang Wan reduces hemorrhagic transformation and mortality in ischemic stroke rats with delayed thrombolysis: involvement of peroxynitrite-mediated MMP-9 activation

BackgroundHemorrhagic transformation (HT) is a common complication of delayed tissue plasminogen activator (t-PA) treatment for ischemic stroke. Peroxynitrite plays an important role in the breakdown of blood–brain barrier (BBB) and the development of HT. We tested the hypothesis that Angong Niuhuang Wan (AGNHW), a traditional Chinese medicinal formula, could be used in conjunction with t-PA to protect the BBB, minimize HT, and improve neurological function by suppressing peroxynitrite-mediated matrix metalloproteinase-9 (MMP-9) activation.MethodsWe first performed quality control study and chemical identification of AGNHW by using UPLC. In animal experiments, male Sprague–Dawley rats were subjected to 5 h of middle cerebral artery occlusion (MCAO) followed by 19 h of reperfusion plus t-PA infusion (10 mg/kg) at 5 h of cerebral ischemia. AGNHW (257 mg/kg) was given orally at 2 h after MCAO. Hemorrhagic transformation was measured using hemorrhagic scores and hemoglobin levels in ischemic brains. Evans blue leakage was utilized to assess the severity of the blood–brain barrier (BBB) damage. The modified neurologic severity score (mNSS) test was used to assess neurological functions. Peroxynitrite and superoxide was detected by using fluorescent probes. MMP-9 activity and expression were examined by gelatin zymography and immunostaining. The antioxidant effects were also studied by using brain microvascular endothelial b.End3 cells exposed to 5 h of oxygen and glucose deprivation (OGD) plus 5 h of reoxygenation with t-PA treatment (20 µg/ml).ResultsAGNHW significantly reduced the BBB damage, brain edema, reduced hemorrhagic transformation, enhanced neurological function, and reduced mortality rate in the ischemic stroke rats with t-PA treatment. AGNHW reduced peroxynitrite and superoxide in vivo and in vitro and six active chemical compounds were identified from AGNHW with peroxynitrite scavenging activity. Furthermore, AGNHW inhibited MMP-9 activity, and preserved tight junction protein claudin-5 and collagen IV in the ischemic brains.ConclusionAGNHW could be a potential adjuvant therapy with t-PA to protect the BBB integrity, reduce HT, and improve therapeutic outcome in ischemic stroke treatment via inhibiting peroxynitrite-mediated MMP-9 activation.Graphical

Automated Recognition of Macro Downburst Using Doppler Weather Radar

In light of the macro downburst’s ground divergent flow field characteristics and high reflectivity, this paper proposes an algorithm for identifying the downburst area using a Doppler weather radar low-level radial velocity and reflectivity factor (abbreviated as reflectivity, the same below). To binarize the radial velocity, perform quality control on the radial velocity and reflectivity, then combine the reflectivity and the radial velocity threshold. Following that, use the Eight-Neighborhood method to retrieve the positive and negative velocity connected regions and perform the connected regions. The positive and negative velocity pairs are then matched, and the zero Doppler velocity line between the positive and negative velocity pairs is extracted, followed by the center recognition of the positive and negative velocity downburst areas. The data of downbursts detected by Doppler radar in Jinan, Shandong Province, are used for algorithm verification in this paper. The results show that the proposed algorithm can detect the macro downburst area and identify the downburst center.

Conservation Rates of Breast and Axilla Indicate the Quality of Surgical Management of the Early-Stage Breast Cancer Patient

Background: Multidisciplinary care in quality-assured specialized Brest Centre (BC) is nowadays considered optimal management of breast cancer and is associated with better patient outcomes. Modern breast cancer surgery should provide optimal oncological outcomes and preserve the quality of life. European Society of Breast Cancer Specialists (EUSOMA) set up the minimum requirements for a specialized BC and a set of 15 mandatory quality indicator (Q.I.) benchmarks for BC certification purposes. Six Q.I. are intended for breast cancer surgery quality assessment. Methods: In BC of Clinical Hospital Centre Rijeka, data were collected retrospectively for 2019 and prospectively thereafter in a clinical register, encrypted according to the EUSOMA instructions and uploaded into collective EUSOMA database. Following database validation, all Q.I. were calculated for our BC for 3 consecutive years. In addition, a comprehensive on-site audit was performed in 2021 for all services included in breast cancer management in Rijeka. Results: All mandatory surgical Q.I. were above the EUSOMA benchmarks in all 3 years. Non-compliance with EUSOMA recommendations were reported as major, minor, recommendations and observations. For BC surgical department, no major or minor non-conformities were reported. At the national level, mastectomy rates were above the permitted EUSOMA benchmark in 4 consecutive years. Conclusion: We have voluntarily initiated and performed quality control of our BC. The certificate obtained is a confirmation of the high quality of care. Concerning the mastectomy rate in Croatia, other centres should consider quality evaluation to determine the status of detected suboptimal surgical management.

Applying probabilistic material flow analysis for quality control and management of waste recycling in steelmaking

In modern steelmaking, multiple processes comprise a continuous manufacturing system, but not all phosphorus content data are connected or integrated into a holistic and systematic database. Disconnected data hinder the improvement of material management and resource efficiency in the industry. The objective of this study was to establish a method to evaluate material flows, reduce uncertainty, and perform quality control for waste recycling in the steelmaking industry. The results indicate that 10% of the phosphorus input is present in the final products, 30% accumulates in the slags, and more than 60% of the total mass remains in the processes. Comparing the material flow analysis results obtained using static and probabilistic approaches, the partition ratio of the phosphorus content in slags changes from 24.07% to 40.78%, but that in processes changes from 49.10% to 68.05%. This indicates that the variations in phosphorus content in slags and processes might affect the effectiveness of slag recycling and might increase the resource consumption required to maintain the quality of final products. The probability of forming substandard products in the baseline scenario is 0.43. Adopting a 50% removal rate, the probabilities of forming substandard products are reduced to 0.36 (waste removal scenario), 0.38 (slag reduction scenario), and 0.31 (raw material treatment scenario). The performance of raw material treatment and waste removal is more efficient for quality control. The method used in this study can be applied to evaluate the possible outcomes of waste recycling and reduce the probability of forming substandard products.

Effect of washing on quality, breathability performance and reusability of disposable face masks

Disposable face masks are among the personal protective equipment (PPE) that highly contribute to protecting people in the context of the current COVID-19 pandemic. Health authorities recommend wearing a mask as a barrier measure to limit the spread of viral respiratory diseases. During the first waves of the pandemic, besides professional high-quality PPE, decontaminated disposable mask reuse and homemade cloth masks were allowed due to scarcities. This work introduces a simple method based on-time history of the differential pressure, and an easy to use the setup for the testing of different kinds of respiratory protective masks for the purposes of quality control and evaluation of air permeability performance. The standard mask testing method and the new proposed approach were then used to evaluate the effect of machine washing on the widely used type of disposable masks; namely the surgical (medical) face masks. The objective is to determine the number of acceptable washing cycles that this kind of mask can withstand before losing its performance in terms of breathability and airflow resistance. Other quality characteristics such as material (fibres) degradation and hydrophobicity are investigated. Degradation mechanisms due to washing cycles for the different mask constituent layers were studied by scanning electron microscopy (SEM) imaging. This work is an attempt to contribute to the determination of the reusability threshold of general-purpose disposable surgical type face masks thereby contributing to the reduction of environmental concerns. Results in terms of the studied above parameters suggest limiting the reuse of standard type surgical masks to only one machine washing cycle.

16S rRNA sequencing-based evaluation of the protective effects of Hua-Zhuo-Jie-Du on rats with chronic atrophic gastritis

BackgroundDisturbance of the intestinal flora is a pathogenic factor for chronic atrophic gastritis (CAG). Hua-Zhuo-Jie-Du (HZJD) has been shown to be an effective Chinese herbal preparation for treating CAG. However, the effects of HZJD on the intestinal flora of CAG is unclear. In this study, we probed the regulating effects of HZJD on intestinal microbes in CAG rats using 16S rRNA gene sequencing.MethodsHigh-performance liquid chromatography (HPLC) analysis was used to perform quality control of HZJD preparations. We then administered 1-methyl-3-nitro-1-nitrosoguanidine (200 μg/ml) to Sprague–Dawley rats to establish a CAG model. HZJD and vitacoenzyme were administered orally to these rats over a 10 week period. Hematoxylin and eosin (H&E) staining was performed to observe the histopathology of CAG rats. A rarefaction curve, species accumulation curve, Chao1 index, and ACE index were calculated to assess the alpha diversity. Principal component analysis (PCA), non-metric multi-dimensional scaling (NMDS), and unweighted pair group method with arithmetic mean (UPGMA) were conducted to examine the beta diversity. The LEfSe method was used to identify differential bacteria. Differential function analysis used PCA based on KEGG function prediction.ResultsHPLC showed that our HZJD preparation method was feasible. H&E staining showed that HZJD significantly improved the pathological state of the gastric mucosa in CAG rats. The rarefaction curve and species accumulation curve showed that the sequencing data were reasonable. The Chao1 and ACE indices were significantly increased in CAG rats compared to the N group. Following HZJD and vitacoenzyme treatment, the Chao1 and ACE indices were decreased. PCA, NMDS, and UPGMA results showed that the M group was separated from the N, HZJD, and V groups, and LEfSe results showed that the relative abundance of Akkermansia, Oscillospira, Prevotella, and CF231 were significantly higher in the N group. Proteobacteria and Escherichia were significantly enriched in the M group, Allobaculum, Bacteroides, Jeotgalicoccus, Corynebacterium, and Sporosarcina were significantly enriched in the V group, and Firmicutes, Lactobacillus, and Turicibacter were significantly enriched in the HZJD group.ConclusionHZJD exhibited a therapeutic effect on the intestinal flora of CAG rats.

Standardization of spirometry updated in China and international: comparison and interpretation of the key updates

Standardization of spirometry was jointly updated by the American Thoracic Society (ATS) and the European Respiratory Society (ERS) in 2019. Similar technical standards for spirometry recommended by the Chinese Thoracic Society (CTS) and/or the Chinese Association of Chest Physicians (CACP) are widely used in China. We compared the key similarities and differences of these recommendations and interpreted the key updates. The ATS/ERS 2019 updates expanded the scope of indications for spirometry and recommended the contraindications based on the pathophysiological perspective, while contraindications recommended by the CTS were based on the severity of contraindications. ISO 26782∶2009 standards were applied by the ATS/ERS 2019 to evaluate the performance quality (reliance for accuracy, repeatability, etc.) of spirometers, while standards adopted 24/26 waves suggested by the ATS 1994 was used by the CTS. The ATS/ERS 2019 also included the performance quality control criteria for 3-L calibration syringe, operator training and attainment and maintenance of competency, grade"U", system warning messages, instructions to patients, and standardized operator comments. Some of these criteria in the CTS were not explained in detail. However, the CTS/CACP emphasized that the spirometry record should report the indices of forced inspiratory phase and small airway function, those are not clearly required in the ATS/ERS 2019. In comparison, the ATS/ERS 2019 has stricter criteria for FEV1 and FVC acceptability than the CTS and more detailed explanations. Those outstanding parts are worth referencing for the updated version of the CTS in the future, while the criteria that combine our own conditions need to be retained and popularized.

Single-Cell Transcriptome Integration Analysis Reveals the Correlation Between Mesenchymal Stromal Cells and Fibroblasts.

Background: Mesenchymal stromal cells (MSCs) and fibroblasts show similar morphology, surface marker expression, and proliferation, differentiation, and immunomodulatory capacities. These similarities not only blur their cell identities but also limit their application. Methods: We performed single-cell transcriptome sequencing of the human umbilical cord and foreskin MSCs (HuMSCs and FSMSCs) and extracted the single-cell transcriptome data of the bone marrow and adipose MSCs (BMSCs and ADMSCs) from the Gene Expression Omnibus (GEO) database. Then, we performed quality control, batch effect correction, integration, and clustering analysis of the integrated single-cell transcriptome data from the HuMSCs, FMSCs, BMSCs, and ADMSCs. The cell subsets were annotated based on the surface marker phenotypes for the MSCs (CD105 + , CD90 +, CD73 +, CD45 −, CD34 −, CD19 −, HLA-DRA −, and CD11b −), fibroblasts (VIM +, PECAM1 −, CD34 −, CD45 −, EPCAM −, and MYH11 −), and pericytes (CD146 +, PDGFRB +, PECAM1 −, CD34 −, and CD45 −). The expression levels of common fibroblast markers (ACTA2, FAP, PDGFRA, PDGFRB, S100A4, FN1, COL1A1, POSTN, DCN, COL1A2, FBLN2, COL1A2, DES, and CDH11) were also analyzed in all cell subsets. Finally, the gene expression profiles, differentiation status, and the enrichment status of various gene sets and regulons were compared between the cell subsets. Results: We demonstrated 15 distinct cell subsets in the integrated single-cell transcriptome sequencing data. Surface marker annotation demonstrated the MSC phenotype in 12 of the 15 cell subsets. C10 and C14 subsets demonstrated both the MSC and pericyte phenotypes. All 15 cell subsets demonstrated the fibroblast phenotype. C8, C12, and C13 subsets exclusively demonstrated the fibroblast phenotype. We identified 3,275 differentially expressed genes, 305 enriched gene sets, and 34 enriched regulons between the 15 cell subsets. The cell subsets that exclusively demonstrated the fibroblast phenotype represented less primitive and more differentiated cell types. Conclusion: Cell subsets with the MSC phenotype also demonstrated the fibroblast phenotype, but cell subsets with the fibroblast phenotype did not necessarily demonstrate the MSC phenotype, suggesting that MSCs represented a subclass of fibroblasts. We also demonstrated that the MSCs and fibroblasts represented highly heterogeneous populations with distinct cell subsets, which could be identified based on the differentially enriched gene sets and regulons that specify proliferating, differentiating, metabolic, and/or immunomodulatory functions.

Standardization and implementation of fluorescence molecular endoscopy in the clinic.

.Significance: Near-infrared fluorescence molecular endoscopy (NIR-FME) is an innovative technique allowing for in vivo visualization of molecular processes in hollow organs. Despite its potential for clinical translation, NIR-FME still faces challenges, for example, the lack of consensus in performing quality control and standardization of procedures and systems. This may hamper the clinical approval of the technology by authorities and its acceptance by endoscopists. Until now, several clinical trials using NIR-FME have been performed. However, most of these trials had different study designs, making comparison difficult.Aim: We describe the need for standardization in NIR-FME, provide a pathway for setting up a standardized clinical study, and describe future perspectives for NIR-FME.Body: Standardization is challenging due to many parameters. Invariable parameters refer to the hardware specifications. Variable parameters refer to movement or tissue optical properties. Phantoms can be of aid when defining the influence of these variables or when standardizing a procedure.Conclusion: There is a need for standardization in NIR-FME and hurdles still need to be overcome before a widespread clinical implementation of NIR-FME can be realized. When these hurdles are overcome, clinical outcomes can be compared and systems can be benchmarked, enabling clinical implementation.

The Stabilization Control of the Railroad Track

An important area in the repair and maintenance of railway tracks is the development of digital technologies for monitoring the parameters of track machinery operation. Currently, digital monitoring systems are being introduced on the JSC "Russian Railways" network to ensure control over track machinery operation, which transmit information on machinery operation or on the current condition of units and aggregates in real time.In accordance with the requirements of JSC "Russian Railways" when carrying out repair and track works at railway transport infrastructure facilities, operational quality control of work performance is required. The control consists in ensuring the absence of hidden defects affecting the long-term stability of the track during the reconstruction and repair of the railway track. Automation of control functions is widely used in the world practice, but for their use it is necessary to have evaluation criteria for transmitted data. The approach proposed in the article to assess the quality of ballast layer compaction makes it possible to organize monitoring of the functioning parameters of track facilities, affecting the quality of work, and thereby will reduce the number of unscheduled track repairs carried out due to improper operation and maintenance of equipment.

TULIP: An RNA-seq-based Primary Tumor Type Prediction Tool Using Convolutional Neural Networks.

With cancer as one of the leading causes of death worldwide, accurate primary tumor type prediction is critical in identifying genetic factors that can inhibit or slow tumor progression. There have been efforts to categorize primary tumor types with gene expression data using machine learning, and more recently with deep learning, in the last several years. In this paper, we developed four 1-dimensional (1D) Convolutional Neural Network (CNN) models to classify RNA-seq count data as one of 17 highly represented primary tumor types or 32 primary tumor types regardless of imbalanced representation. Additionally, we adapted the models to take as input either all Ensembl genes (60,483) or protein coding genes only (19,758). Unlike previous work, we avoided selection bias by not filtering genes based on expression values. RNA-seq count data expressed as FPKM-UQ of 9,025 and 10,940 samples from The Cancer Genome Atlas (TCGA) were downloaded from the Genomic Data Commons (GDC) corresponding to 17 and 32 primary tumor types respectively for training and validating the models. All 4 1D-CNN models had an overall accuracy of 94.7% to 97.6% on the test dataset. Further evaluation indicates that the models with protein coding genes only as features performed with better accuracy compared to the models with all Ensembl genes for both 17 and 32 primary tumor types. For all models, the accuracy by primary tumor type was above 80% for most primary tumor types. We packaged all 4 models as a Python-based deep learning classification tool called TULIP (TUmor CLassIfication Predictor) for performing quality control on primary tumor samples and characterizing cancer samples of unknown tumor type. Further optimization of the models is needed to improve the accuracy of certain primary tumor types.

Producing High-Quality Single Nucleotide Polymorphism Data for Genome-Wide Association Studies.

Single-nucleotide polymorphisms (SNPs) have become the primary type of molecular genetic marker used in a diverse range of genetic and genomic studies. SNPs can be used to identify genomic regions linked to traits such as disease in genome-wide association studies, to understand population structure and diversity, or to understand mechanisms of genome evolution. One of the first steps of any SNP-based workflow, following SNP discovery, is quality control of SNP data. The protocol described here details how to perform quality control on SNP data to minimise errors in downstream analysis.

Analysis of Microbiomes Using Free Web-Based Tools in Online and In-Person Undergraduate Science Courses

Our understanding of microbiomes, or the collection of microorganisms and their genes in a given environment, has been revolutionized by technological and computational advances. However, many undergraduate students do not get hands-on experiences with processing, analyzing, or interpreting these types of datasets. Recent global events have increased the need for effective educational activities that can be performed virtually and remotely. Here, we present a module that introduces STEM undergraduates to the bioinformatic and statistical analyses of bacterial communities using a combination of free, web-based data processing software. These lessons allow students to engage with the studies of microbiomes; gain valuable experiences processing large, high-throughput datasets; and practice their science communication skills. The lessons presented here walk students through two web-based platforms. The first (<em>DNA Subway</em>) is an easy-to-use wrapper of the popular QIIME (pronounced &ldquo;chime&rdquo;) pipeline, which performs quality control analysis of the raw sequence data and outputs a community matrix file with assigned bacterial taxonomies. The second, <em>ranacapa</em>, is an R Shiny App that allows students to compare microbial communities, perform statistical analyses and visualize community data. Students may communicate their findings with a written final report or oral presentation. While the lessons presented here use a sample dataset based on the gut-microbiome of the bean beetle (<em>Callosobruchus maculatus</em>), the materials are easily modified to use original next-generation amplicon sequence data from any host or environment. Additionally, options for alternative datasets are also provided facilitating flexibility within the curriculum. <em>Primary Image:</em> Insects are an excellent example of a tractable biological system to study the relationship between an organism and its microbiome. Little is currently known about the gut-microbiome of many insects, such as the bean beetle (<em>Callosobruchus maculatus</em>).

Evolution of magnetic properties during tempering

Quality control in heat treatment of steel is often conducted after the treatment. Failure to confine within the specified range of mechanical properties may lead to wasted energy and production resources. Performing quality control in-line in the heat treatment process allows for early detection and possibility to react to changes in the process. The prospects of utilizing the change in the electromagnetic (EM) properties of steel, as means for quality control, are investigated in this paper. The focus is on the tempering process of hardened SS2244 (42CrMoS4) steel. The tempering takes the hardness of the steel from approximately 600 HV down to around 400 HV. The EM signature of the steel is recorded during the tempering process. This is later compared with results from more traditional means of material characterization, such as laser scanning microscopy, X-ray diffractometry and Vickers microhardness measurement. This initial study shows clear indications of precise detection of the hardness through EM properties during the tempering process of selected material.

CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications

In recent years, the collection and utilisation of crowdsourced data has gained attention in atmospheric sciences and citizen weather stations (CWS), i.e., privately-owned weather stations whose owners share their data publicly via the internet, have become increasingly popular. This is particularly the case for cities, where traditional measurement networks are sparse. Rigorous quality control (QC) of CWS data is essential prior to any application. In this study, we present the QC package “CrowdQC+,” which identifies and removes faulty air-temperature (ta) data from crowdsourced CWS data sets, i.e., data from several tens to thousands of CWS. The package is a further development of the existing package “CrowdQC.” While QC levels and functionalities of the predecessor are kept, CrowdQC+ extends it to increase QC performance, enhance applicability, and increase user-friendliness. Firstly, two new QC levels are introduced. The first implements a spatial QC that mainly addresses radiation errors, the second a temporal correction of the data regarding sensor-response time. Secondly, new functionalities aim at making the package more flexible to apply to data sets of different lengths and sizes, enabling also near-real time application. Thirdly, additional helper functions increase user-friendliness of the package. As its predecessor, CrowdQC+ does not require reference meteorological data. The performance of the new package is tested with two 1-year data sets of CWS data from hundreds of “Netatmo” CWS in the cities of Amsterdam, Netherlands, and Toulouse, France. Quality-controlled data are compared with data from networks of professionally-operated weather stations (PRWS). Results show that the new package effectively removes faulty data from both data sets, leading to lower deviations between CWS and PRWS compared to its predecessor. It is further shown that CrowdQC+ leads to robust results for CWS networks of different sizes/densities. Further development of the package could include testing the suitability of CrowdQC+ for other variables than ta, such as air pressure or specific humidity, testing it on data sets from other background climates such as tropical or desert cities, and to incorporate added filter functionalities for further improvement. Overall, CrowdQC+ could lead the way to utilise CWS data in world-wide urban climate applications.

The digitisation and commercial licensing of local television news as a model for preservation and access: A case study

Since 2014, the Special Collections Department of the University of North Texas Libraries (UNTL) has worked to digitise over 60 years’ worth of historical film and video and provide online digital access to news programming that was originally broadcast under the name WBAP-TV, and later NBC 5/KXAS-TV. Revenue from commercial licensing is expected to contribute an increasingly significant percentage of the funding needed to make the collection fully digitally accessible. This paper looks briefly at the history of the NBC5 news collection and examines the workflows required to prepare film and video for digitisation, perform quality control on digital files, and apply metadata keywords and content description to make footage easier for easily filmmakers to discover online. The paper will also discuss the licensing workflows in place at UNTL and how footage has been licensed for use in a variety of projects.

Medical image segmentation automatic quality control: A multi-dimensional approach.

In clinical applications, using erroneous segmentations of medical images can have dramatic consequences. Current approaches dedicated to medical image segmentation automatic quality control do not predict segmentation quality at slice-level (2D), resulting in sub-optimal evaluations. Our 2D-based deep learning method simultaneously performs quality control at 2D-level and 3D-level for cardiovascular MR image segmentations. We compared it with 3D approaches by training both on 36,540 (2D) / 3842 (3D) samples to predict Dice Similarity Coefficients (DSC) for 4 different structures from the left ventricle, i.e., trabeculations (LVT), myocardium (LVM), papillary muscles (LVPM) and blood (LVC). The 2D-based method outperformed the 3D method. At the 2D-level, the mean absolute errors (MAEs) of the DSC predictions for 3823 samples, were 0.02, 0.02, 0.05 and 0.02 for LVM, LVC, LVT and LVPM, respectively. At the 3D-level, for 402 samples, the corresponding MAEs were 0.02, 0.01, 0.02 and 0.04. The method was validated in a clinical practice evaluation against semi-qualitative scores provided by expert cardiologists for 1016 subjects of the UK BioBank. Finally, we provided evidence that a multi-level QC could be used to enhance clinical measurements derived from image segmentations.