Perform Quality Control Research Articles

A MIL-based approach for welding defect classification

Welding quality plays a prominent role in many fabrication processes, such as those in the automotive, aerospace, shipbuilding, and electronics industries. Deep learning facilitates the automatic classification of welding quality using non-invasive techniques such as X-rays, thermal imaging, and ultrasonic techniques. In this study, we investigate the ability of deep learning to detect welding quality directly from the welded workpieces. Typically, good and bad weld samples can be seen together along with surrounding material as a background, which makes traditional classification based using computer vision difficult. Therefore, we propose a new framework based on Multiple Instance Learning (MIL) that reveals the distribution of each small piece of the image and serves as an effective guide for welding quality classification. Furthermore, a new collection of welding image datasets is developed to verify the baseline model and our proposed method. The results show that our proposed method is effective in classifying welding quality in welding workpiece images and identifying welding features in each small section of the welding area in workpiece images. This study demonstrates the effectiveness of incorporating MIL in weakly supervised welding quality classification and reveals the potential for performing quality control on welding in industrial pipelines automatically.

SWQC: Efficient sequencing data quality control on the next-generation sunway platform

Sequencing data quality control can significantly prevent low-quality data from impacting downstream applications in bioinformatics. The enormous growth of biological sequencing data in recent years introduces new challenges to the efficiency of quality control processes and motivates the need for fast implementations on modern compute systems. The powerful next-generation heterogeneous Sunway platform holds significant potential for addressing this challenge. However, there are currently no dedicated quality control applications that can fully utilize its computational power. To bridge this gap, we introduce SWQC, a novel quality control application specifically designed for the Sunway platform. We present an efficient distributed FASTQ I/O framework for Sunway-based workstations and supercomputers to take advantage of fast SSDs and the parallel file system. In order to support both process-level and thread-level (CPE-level) parallelism to leverage the computational power, we refactor and optimize all standard quality control modules for the heterogeneous Sunway architecture. When using a single node, SWQC achieves speedups between 2 and 40 over highly optimized quality control applications executed on a high-end 48-core AMD server. Additionally, when using 16 nodes, SWQC achieves parallel efficiencies of 70% (for reading and writing a single file) and 95% (for reading one file and writing split files) compared to a single node. Overall, SWQC is able to perform quality control operations for a 140GB FASTQ file within only 70 s using a single Sunway node. It is publicly available at https://github.com/RabbitBio/SWQC.

3t-seq: automatic gene expression analysis of single-copy genes, transposable elements, and tRNAs from RNA-seq data.

RNA sequencing is the gold-standard method to quantify transcriptomic changes between two conditions. The overwhelming majority of data analysis methods available are focused on polyadenylated RNA transcribed from single-copy genes and overlook transcripts from repeated sequences such as transposable elements (TEs). These self-autonomous genetic elements are increasingly studied, and specialized tools designed to handle multimapping sequencing reads are available. Transfer RNAs are transcribed by RNA polymerase III and are essential for protein translation. There is a need for integrated software that is able to analyze multiple types of RNA. Here, we present 3t-seq, a Snakemake pipeline for integrated differential expression analysis of transcripts from single-copy genes, TEs, and tRNA. 3t-seq produces an accessible report and easy-to-use results for downstream analysis starting from raw sequencing data and performing quality control, genome mapping, gene expression quantification, and statistical testing. It implements three methods to quantify TEs expression and one for tRNA genes. It provides an easy-to-configure method to manage software dependencies that lets the user focus on results. 3t-seq is released under MIT license and is available at https://github.com/boulardlab/3t-seq.

RNA sequencing reveals transcriptomic changes in PC-12 cells following plasminogen activator, tissue type overexpression.

Pheochromocytoma and paraganglioma, collectively known as PPGL, are categorized as neuroendocrine tumors with the potential for malignancy. Plasminogen activator, tissue type (PLAT) is a protein encoding gene that encodes tissue-type plasminogen activator, which converts plasminogen to plasmin. There is limited research on the association between PLAT and PPGL. Previous studies have only found that the expression level of PLAT protein is significantly increased in PPGL with deficient blood supply, and its role in the occurrence and progression of PPGL remains unclear and needs further clarification. The purpose of this study is to provide some new clues to elucidate the role of PLAT in PPGL, in order to better guide future research directions. The PC-12 cell line was selected for this study, and lentivirus transfection technology was used to construct control and PLAT overexpression cell models. Transcriptomic information of PLAT regulation in PC-12 cells was obtained through RNA sequencing, and differentially expressed genes (DEGs) were screened using bioinformatics methods. The physiological functions and related signaling pathways of these genes were analyzed. After validating the overexpression cell model and performing quality control analysis on the transcriptome sequencing data, DEGs were identified. The Gene Ontology (GO) functional enrichment analysis of DEGs revealed significant enrichment in 46 GO functions, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed significant enrichment in seven pathways. It was found that these genes were significantly enriched in functional pathways associated with mitochondrial respiratory chain and energy metabolism. This study provides some insights into the role of PLAT in pheochromocytoma and suggests directions for further research on its involvement in tumor development and angiogenesis. However, the specific regulatory mechanisms still require further validation.

Toward field-scale groundwater pumping and improved groundwater management using remote sensing and climate data

Groundwater overdraft in the western United States has prompted water managers to develop groundwater management plans that include mandatory reporting of groundwater pumping (GP). However, most irrigation systems in this region are not equipped with irrigation water flow meters to record GP and performing quality control of the available metered GP data is difficult due to the scarcity of reliable secondary GP estimates. We hypothesize that Landsat-based actual evapotranspiration (ET) estimates from OpenET can be used to predict GP and aid in quality control of the metered GP data. The objectives of this study are to: 1) pair OpenET estimates of consumptive use (Net ET, i.e., actual ET less effective precipitation) and metered annual GP data from Diamond Valley, Nevada, and Harney Basin, Oregon; 2) evaluate linear regression and machine learning models to establish the GP vs Net ET relationship; and 3) compare GP estimates at the field- and basin-scales. Results from using a bootstrapping technique showed that the mean absolute errors and root mean square errors for field-scale GP depth are ∼11 % and ∼14 % across Diamond Valley and Harney Basin based on the OpenET ensemble mean, which showed the highest skill among all the OpenET ET models. Moreover, the regression models explained 50 %-70 % variance in GP depth and ∼90 % variance in GP volumes. Our GP volume estimates are also within 7 % and 17 % of the total reported and measured volumes in Diamond Valley and Harney Basin, respectively, and the estimated average irrigation efficiency of 87 % aligns with known center-pivot system efficiencies. Additionally, the OpenET ensemble proves to be useful for identifying discrepancies in metered GP data, which are subsequently flagged as outliers. Results from this study illustrate usefulness of satellite-based ET estimates for estimating GP and metered GP data quality control and have the potential to help estimate historical GP.

Detection of Piston Ring Deficiency in The Assembly of Automotive Ball Joint and Tie Rod End Parts

In today's intensely competitive environment, businesses strive to optimize production efficiency to reduce costs, increase profitability, and ensure customer satisfaction. This focus on efficiency and quality enables businesses to operate more effectively, gain a competitive advantage in the market, and move towards sustainable growth. This study uses image processing techniques to detect missing segments in the assembly of ball joints automatically. In the automotive industry, performing quality control of critical components before assembly and detecting and classifying the defective ones is essential. Many quality control methods can be applied with existing technologies. This paper proposes an automatic real-time control based on image processing techniques to detect ball joint missing segments, a common defect in the automotive industry. In the company, operators perform defect detection by visual inspection. In this system, production continues in cases where the operator cannot detect the defect. This system aims to detect the errors made by the operator during the assembly operations and provide instant feedback. The developed system uses OpenCV library algorithms that are highly accurate in detecting defects in manual assembly processes so that missing components are removed from the production chain, and production quality is significantly improved. Accuracy is over 94% when identifying missing segments, about 30% better than traditional methods. In tests, 1200 ball joints were run through the system, resulting in 1150 defects being correctly identified and removed from the production line. Accuracy is high thanks to the application of various image processing techniques such as grayscale conversion, edge detection, and shape recognition. This also provides real-time feedback to the operator so the system can reduce detection and response time from 15 seconds to 5 seconds. This increases production speed and reduces the error rate in manual assembly processes by 20%. This paper also highlights the potential of image processing technology in manufacturing. It will contribute to improved quality control mechanisms to increase the reliability and efficiency of production lines in the automotive industry.

Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis

Single-cell multiomic analysis of the epigenome, transcriptome, and proteome allows for comprehensive characterization of the molecular circuitry that underpins cell identity and state. However, the holistic interpretation of such datasets presents a challenge given a paucity of approaches for systematic, joint evaluation of different modalities. Here, we present Panpipes, a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale. Panpipes allows reliable and customizable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations.

ASSESSING THE POTENTIAL PUBLIC HEALTH RISK OF Clostridium botulinum TOXIN GENES IN CANNED FOOD : A LABORATORY EXPERIENCE IN TÜRKİYE

Due to the ability to synthesize a highly potent neurotoxin, Clostridium botulinum poses an important risk to food safety. Foodborne botulism is a neuroparalytic disease caused by the ingestion of neurotoxins produced by Clostridium botulinum. Botulism commonly occurs as a result of consuming canned foods. In this study, the aim was to investigate the presence of C. botulinum and detect the genes producing A, B, E, and F toxins in C. botulinum isolates in homemade and commercial canned foods using the rapid, sensitive, and reliable Real-Time PCR technique. A total of 81 canned samples were collected, including 51 commercial and 30 homemade cans. The canned samples were initially enriched in tryptone peptone glucose yeast (TPGY) medium. Subsequently, DNA isolation was performed using the foodproof® StarPrep Two Kit. After the isolation process, Real-Time PCR was conducted using the foodproof® Clostridium botulinum Detection LyoKit and 5’ Nuclease (Biotecon, R60240) kit. Only 2 samples tested positive among all the samples. Both positive samples were identified to contain neurotoxin type A. They were both commercial canned foods—one was a mixed vegetable garnish, and the other was roasted red pepper. Both positive samples were packaged in glass containers. Consequently, it was concluded that commercially available canned foods in Turkey could still pose a potential risk to public health due to the presence of C. botulinum. Therefore, it was recommended to perform quality control analyses through food inspections in companies involved in canned food production and sales.

IMPLEMENTATION OF MEWMA CHART USING TIME SERIES MODEL FOR MONITORING THE WHITE CRISTAL SUGAR QUALITY

The basic assumption of implementing a control chart is that the observed process values should be normally distributed and independent. However, the production process at the factory is carried out repeatedly with the same machine, so there is a possibility that the observation data is not independent and the resulting control chart becomes inaccurate. Therefore, a time series model approach is needed to create an accurate control chart. This study aims to conduct statistical quality control of white crystal sugar (WCS) production at Madukismo Sugar Factory (MSF) Yogyakarta to maintain product stability and quality according to the standards. MSF performs quality control on WCS products with several quality characteristic variables, including drying shrinkage (%), grain size (mm), polarization, and color of sugar solution (ICUMSA). This study is only limited to the four quality characteristics with research data in the form of secondary data from the MSF QC Laboratory. The data used were WCS quality characteristics from May 9 - July 16, 2022. The four characteristics influence each other, so a MEWMA control chart is used. This study found autocorrelation between observations so that time series modeling was carried out and resulted in VARIMA (1,1,2) as the best time series model. While the implementation of the MEWMA chart shows uncontrollable results with an optimal weighting value λ of 0.8. For process capability, the results show that the process is capable.

A holistic analysis of Chinese sponge city cases by region: Using PLS-SEM models to understand key factors impacting LID performance

Sponge city is a national sustainable stormwater management program proposed by the Chinese government to deal with urban water issues (e.g., flooding, poor water quality) brought on by climate change and urbanization. Various strategies for sponge city construction are required since environmental constraints differ regionally across the country. To identify regional variations, reveal the inner links between externalities and design elements in sponge city construction, and offer practical suggestions, efforts in two directions are made based on the data of 68 sponge city cases around China: 1) discussing design parameters of four Low Impact Development (LID) facilities, including bioretention cell, permeable pavement, grass swale, and sunken green space, under four regionalization maps of hydrologic, climatic, landform and soil texture factors, and 2) building a holistic Partial Least Squares-Structural Equation Modelling (PLS-SEM) model illustrating the relationship between local characteristics, LID system design, and LID system performance in sponge city construction. The results show that: 1) rainfall and landform factors have great impact on LID facilities design, as their depths tend to be higher in water rich areas and coastal areas. 2) LID types and areas are positively influenced (+0.745) by the total area and permeable portion of a project, while the LID system performance (water quantity and quality control) is negatively impacted (−0.407) by the rainfall amount and clay fraction. 3) comprehensive LIDs choice instead of single LID facility shows more significant effect on improving LID system performance. It is recommended to establish different design standards and assessment indexing systems tailored to local environment when constructing sponge city projects.

Acute Exercise Alters Skeletal Muscle DNA Methylation in Sedentary Participants

Skeletal muscle is a highly plastic tissue, adapting its structure and metabolism in response to various stimuli like exercise. This study aimed to determine the plasticity of skeletal muscle DNA methylation in response to an acute exercise bout in volunteers with a range of insulin sensitivities. We studied 14 sedentary participants (7 male/7 female): age = 34.5 ± 3.1 years, body mass index = 29.3 ± 1.9 kg/m2 and HbA1c = 5.3 ± 0.1 %. We performed VO2peak tests to determine exercise capacity (VO2peak = 25.5 ± 1.6 mL per Kg per minute) and euglycemic hyperinsulinemic clamps (Rd value = 5.9 ± 0.8 mg per Kg per minute) with vastus lateralis muscle biopsies before and 30 minutes after a single 48-minute exercise bout. We extracted DNA from the muscle biopsies and performed reduced representation bisulfite sequencing. After performing quality control on the sequencing data, 1,034,947 sites were included for downstream analyses. MethylSig analysis revealed 17,030 differentially methylated cytosines (DMC), 9,020 increased and 8,010 decreased. To identify biologically meaningful DMCs, we used a mean change of >10%, which resulted in 1,179 and 1,436 increased and decreased sites, respectively. Pathway analysis of the increased DMCs revealed an enrichment in efferocytosis, leukocyte transendothelial migration, and FOXO-mediated transcription of oxidative stress pathways. In addition, pathway analysis of the decreased DMCs revealed an enrichment in metabolic (type 2 diabetes/ PI3K-Akt signaling), actin cytoskeleton, integrin/extracellular matrix and calcium signaling pathways. Our study reveals that an acute exercise bout induces alterations in the DNA methylation of skeletal muscle, impacting specific pathways in individuals with varying degrees of insulin sensitivity. Notably, our findings underscore the remarkable plasticity of skeletal muscle tissue. This research was funded by the National Institutes of Health, grant number R01DK094013 (Dawn Coletta). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Prenatal ultrasound diagnosis and quality control of fetal nuchal translucency.

In clinical ultrasound examinations, it is challenging to perform quality control on the images of each fetal nuchal translucency (NT) and crown-rump length (CRL). However, small measurement differences can increase the probability of false-positive or false-negative diagnosis. Therefore, it is necessary to establish a quality control system for fetal NT examination. This study aims to control the quality of fetal NT and CRL measurements, evaluate the accuracy of ultrasound physicians in early pregnancy NT measurements, and analyze the impact of increased fetal structure screening on the detection rate of chromosomal abnormalities. Data were collected from cases before and after 12 months of NT examination quality control, with 2 214 before quality control and 2 538 cases after quality control. Three quality control data metrics were analyzed: NT multiple of median (NT-MoM), standard deviation (SD) of log10MoM [(SD) log10MoM], and the slope of NT on CRL (SNC). The performance of NT measurements was monitored through the individual CRL NT-MoM within the 0.9-1.1 MoM range of the normal median curve, while grouped based on different years of experience (<3 years, 3-6 years, >6 years), and NT-MoM values among these groups were compared. Data on NT thickening, structural anomalies, and chromosomal abnormalities were retrospectively analyzed during the quality control period. According to the curve equation of the American NTQR project group, the NT-MoM value before quality control was 0.921 7 MoM, the (SD) log10MoM value was 0.091 92, and the SNC value was 12.20%. After quality control, the NT-MoM value was 0.948 3 MoM, the (SD) log10MoM value was 0.094 81, and the SNC value was 11.43%. The comparison of NT-MoM values before and after quality control showed a statistically significant difference (P<0.000 1). The comparison of NT-MoM values measured by ultrasound physicians with different years of experience before and after quality control also showed statistically significant differences (P<0.000 1). The NT-MoM values for the 3-6 years and >6 years groups were higher after quality control (P<0.05), while the <3 years group showed no significant difference before and after quality control (P>0.05). After quality control, cases of NT thickening without significant structural abnormalities accounted for 19.05%, NT thickening with structural abnormalities accounted for 47.62%, and NT normal with structural abnormalities accounted for 33.33%. There were 36 cases of fetal heart abnormalities, accounting for 20.34% of the total abnormality rate, with a positive rate of 36% in chromosome tests. After quality control, ultrasound physicians measure NT more accurately, but differences among measurements remain. Measurements by experienced ultrasound physicians are closer to expected values, usually lower than expected. Monitoring fetal NT and CRL measurements helps improve measurement accuracy. Increasing structural screening during NT examinations, especially for the fetal heart, enhances the detection rate of chromosomal abnormalities.

The status of nuclear medicine in China: the first official national survey.

The National Nuclear Medicine Quality Control Center of China conducted the first official survey to investigate the nationwide situation of nuclear medicine in 2020. The survey aimed to unveil the current nuclear medicine situation and its quality control in China. The web-based survey was conducted and the data was collected via the National Clinical Improvement System (NCIS) of China from 1st April to 31st May 2021. A total of 808 institutes across 30 provinces responded to the national survey. For human resources, there are 4460 physicians, 3077 technologists, 339 physicists, and 309 radiochemists. There are 887 single-photon imaging instruments, including 823 SPECT or SPECT/CT, and 365 PET instruments including 314 PET/CT. Six hundred twenty-four institutes perform SPECT examinations and 319 institutes perform PET examinations. 60% of SPECT scans are bone scintigraphy. A total of 97% of PET scans use an [18F]F-FDG tracer. Furthermore, 587 institutes provide radionuclide therapy services but only 280 institutes have admission rooms. The top three radionuclide therapies are [131I] therapy of hyperthyroidism with 546 institutes, [89Sr] therapy of bone metastasis with 400 institutes, and [131I] therapy of differentiated thyroid cancer with 286 institutes. Finally, for the frequency of equipment quality control per year, there are about 67 times self-test within the department for SPECT instruments and 111 times for PET instruments on average in each province. There are about three failures of SPECT and five failures of PET on average per year in each province. There are 408 institutes (of 624 SPECT institutes) performing quality control of SPECT radiopharmaceuticals, 216 (of 319) for PET radiopharmaceuticals, and 373 (of 587) for radionuclide therapy. These results of the first official survey towards current status of nuclear medicine in China are the foundation for the establishment of the quality control management system.

Intelligent Detection and Odor Recognition of Cigarette Packaging Paper Boxes Based on a Homemade Electronic Nose.

The printing process of box packaging paper can generate volatile organic compounds, resulting in odors that impact product quality and health. An efficient, objective, and cost-effective detection method is urgently needed. We utilized a self-developed electronic nose system to test four different cigarette packaging paper samples. Employing multivariate statistical methods like Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Statistical Quality Control (SQC), and Similarity-based Independent Modeling of Class Analogy (SIMCA), we analyzed and processed the collected data. Comprehensive evaluation and quality control models were constructed to assess sample stability and distinguish odors. Results indicate that our electronic nose system rapidly detects odors and effectively performs quality control. By establishing models for quality stability control, we successfully identified samples with acceptable quality and those with odors. To further validate the system's performance and extend its applications, we collected two types of cigarette packaging paper samples with odor data. Using data augmentation techniques, we expanded the dataset and achieved an accuracy rate of 0.9938 through classification and discrimination. This highlights the significant potential of our self-developed electronic nose system in recognizing cigarette packaging paper odors and odorous samples.

Abstract 4959: Immunopipe: A comprehensive and flexible scRNA-seq and scTCR-seq data analysis pipeline

Abstract Introduction: Single-cell RNA-sequencing (scRNA-seq) pairing with single-cell T-Cell-Receptor-sequencing (scTCR-seq) enables profiling of gene expression and TCR repertoires in individual T cells, elevating our understanding of T-cell-mediated immunity. Here, we present immunopipe, a comprehensive and flexible pipeline (https://github.com/pwwang/immunopipe) for analyzing the paired data. Besides the command-line tool, it offers a user-friendly web interface that allows users with varying programming expertise to configure, initiate, and monitor the pipeline. By combining extensive functionality with ease of use, immunopipe empowers users to unlock valuable insights from the data, which notably advances our understanding of immune response and fosters the development of innovative immunotherapies. Results: Immunopipe is a comprehensive analytical pipeline for scRNA-seq and scTCR-seq data, offering various modules leveraging existing tools and novel methods to ensure data quality and enable downstream analytics. It performs quality control for scRNA-seq data, clusters cells based on gene expression to facilitate the identification of cell populations and provides insights into T-cell heterogeneity and functional diversity through T-cell selection and clustering. Enrichment analysis identifies markers and pathways for T-cell characterization. Our automated T-cell annotation tool annotates cell types accurately and hierarchically. For scTCR-seq data, immunopipe analyzes TCR clones, including clonality, diversity, gene usage, and repertoire overlap. Clone residency analysis examines the presence of clones across samples. Integrative analyses combine scRNA-seq and scTCR-seq data, providing a comprehensive understanding of the cellular landscape. Immunopipe incorporates diverse cell group information to analyze T-cell populations, which enables granular perspectives of the data for comprehensive insights. Immunopipe offers a flexible platform, allowing users to customize the analyses as needed. It supports both core and optional analyses through configuration, where users have control over the adjustable parameters. The pipeline relies on cell grouping information that can be referenced from metadata or modified to generate new variables for analysis and data filtering. Immunopipe can be executed locally or on scheduler platforms, and a docker image is provided for compatibility and simplified installation. It also offers a web interface that facilitates configuration, execution monitoring, and access to results. Conclusion: Immunopipe is a flexible and user-friendly pipeline for analyzing scRNA-seq and scTCR-seq data. It empowers researchers to gain valuable insights that could enhance the understanding of immune responses and facilitate the development of innovative immunotherapies. Citation Format: Panwen Wang, Haidong Dong, Yue Yu, Shuwen Zhang, Zhifu Sun, Jean-Pierre A. Kocher, Junwen Wang, Lin Yi, Ying Li. Immunopipe: A comprehensive and flexible scRNA-seq and scTCR-seq data analysis pipeline [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4959.

Dementias Platform UK: Bringing genetics into life.

The Dementias Platform UK (DPUK) Data Portal is a data repository bringing together a wide range of cohorts. Neurodegenerative dementias are a group of diseases with highly heterogeneous pathology and an overlapping genetic component that is poorly understood. The DPUK collection of independent cohorts can facilitate research in neurodegeneration by combining their genetic and phenotypic data. For genetic data processing, pipelines were generated to perform quality control analysis, genetic imputation, and polygenic risk score (PRS) derivation with six genome-wide association studies of neurodegenerative diseases. Pipelines were applied to five cohorts. The data processing pipelines, research-ready imputed genetic data, and PRS scores are now available on the DPUK platform and can be accessed upon request though the DPUK application process. Harmonizing genome-wide data for multiple datasets increases scientific opportunity and allows the wider research community to access and process data at scale and pace.

Real-Time Gated Proton Therapy: Commissioning and Clinical Workflow for the Hitachi System

PurposeTo describe the commissioning of real-time gated proton therapy (RGPT) and the establishment of an appropriate clinical workflow for the treatment of patients. Materials and MethodsHitachi PROBEAT provides pencil beam scanning proton therapy with an advanced onboard imaging system including real-time fluoroscopy. RGPT utilizes a matching score to provide instantaneous system performance feedback and quality control for patient safety. The CIRS Dynamic System combined with a Thorax Phantom or plastic water was utilized to mimic target motion. The OCTAVIUS was utilized to measure end-to-end dosimetric accuracy for a moving target across a range of simulated situations. Using this dosimetric data, the gating threshold was carefully evaluated and selected based on the intended treatment sites and planning techniques. An image-guidance workflow was developed and applied to patient treatment. ResultsDosimetric data demonstrated that proton plan delivery uncertainty could be within 2 mm for a moving target. The dose delivery to a moving target could pass 3%/3 mm gamma analysis following the commissioning process and application of the clinical workflow detailed in this manuscript. A clinical workflow was established and successfully applied to patient treatment utilizing RGPT. Prostate cancer patients with implanted platinum fiducial markers were treated with RGPT. Their target motion and gating signal data were available for intrafraction motion analysis. ConclusionReal-time gated proton therapy with the Hitachi System has been fully investigated and commissioned for clinical application. RGPT can provide advanced and reliable real-time image guidance to enhance patient safety and inform important treatment planning parameters, such as planning target volume margins and uncertainty parameters for robust plan optimization. RGPT improved the treatment of patients with prostate cancer in situations where intrafraction motion is more than defined tolerance.

First implementation of quality control procedures on selected X-ray machines in South of Benin

Abstract Introduction: The use of X-ray equipment for medical diagnostic radiography procedures has increased due to advances and complexity of radiological procedures. Achieving good image quality while keeping exposure of workers, public and patient exposure to an acceptable level has become a prerequisite for the radiology department in order to comply with best international practices. The aim of this study was to undertake quality control measurement of seven (7) diagnostic radiography equipment in the south of Benin, the first of its kind. Material and methods: Multifunction detector (Piranha) and beam alignment test tool were used to perform quality control tests on seven (7) X-ray units. The method used as well as the interpretation of the results was based on the American Association of Physicists in Medicine (AAPM), United States Food and Drug Administration (FDA), Healing Arts Radiation Protection (HARP), Institute of Physics and Engineering in Medicine (IPEM), International Atomic Energy Agency (IAEA) and Canadian Safety code 35 (S.C 35) recommendations. Results: The quality control results showed that all X-ray equipment investigated were within standard limits for accuracy of exposure time below 10 ms; reproducibility of kVp, exposure time and dose output; specific dose-kVp2 linearity; and specific dose-mAs linearity. Five (5) out of seven (7) diagnostic X-ray machines passed quality control tests such as X-ray beam alignment, exposure time above 10 ms and kVp accuracy. One (1) X-ray machine failed the quality control test of beam filtration at 70 kVp and above. Conclusions: The findings of this study have provided baseline data for other radiology departments to embark on similar QA/QC activities, and also explore options for optimization of patient dose. However, there is a need to extend the study to cover more diagnostic X-ray machines throughout the country. It is anticipated that this would ultimately assist in improving radiation protection and safety during medical diagnostic radiological procedures.

Quantifying Infiltration for Quality Control in Printed Mesoscopic Perovskite Solar Cells: A Microscopic Perspective.

Mesoscopic carbon-based perovskite solar cells (CPSCs) are often cited as a potential frontrunner to perovskite commercialization. Infiltration, the extent to which perovskite fills the mesoporous scaffold, is critical for optimum performance and stability. However, infiltration data are usually presented as qualitative photographic comparisons of samples with extreme infiltration variation. This work examines how small infiltration defects impact performance using an optical microscopy examination of the base TiO2 layer to identify issues and develop targeted techniques for infiltration enhancement. Critically, the uninfiltrated area at the base of the stack was found to correlate well with PCE across multiple batches of varied print quality and ZrO2 thickness. Through reduction of mesh mark defects and improvement of print quality in the ZrO2 and carbon layers, a champion PCE of 15.01% is attained. It follows that this facile, multiscaled, nondestructive technique could enable targeted performance enhancement and quality control in future scale-up initiatives.

Genomic and Phylogenetic Characterisation of SARS-CoV-2 Genomes Isolated in Patients from Lambayeque Region, Peru.

this study aims to identify and characterise genomic and phylogenetically isolated SARS-CoV-2 viral isolates in patients from Lambayeque, Peru. Nasopharyngeal swabs were taken from patients from the Almanzor Aguinaga Asenjo Hospital, Chiclayo, Lambayeque, Peru, which had been considered mild, moderate, and severe cases of COVID-19. Patients had to have tested positive for COVID-19, using a positive RT-PCR for SARS-CoV-2. Subsequently, the SARS-CoV-2 complete viral genome sequencing was carried out using Illumina MiSeq®. The sequences obtained from the sequence were analysed in Nextclade V1.10.0 to assign the corresponding clades, identify mutations in the SARS-CoV-2 genes and perform quality control of the sequences obtained. All sequences were aligned using MAFFT v7.471. The SARS-CoV-2 isolate Wuhan NC 045512.2 was used as a reference sequence to analyse mutations at the amino acid level. The construction of the phylogenetic tree model was achieved with IQ-TREE v1.6.12. It was determined that during the period from December 2020 to January 2021, the lineages s C.14, C.33, B.1.1.485, B.1.1, B.1.1.1, and B.1.111 circulated, with lineage C.14 being the most predominant at 76.7% (n = 23/30). These lineages were classified in clade 20D mainly and also within clades 20B and 20A. On the contrary, the variants found in the second batch of samples of the period from September to October 2021 were Delta (72.7%), Gamma (13.6%), Mu (4.6%), and Lambda (9.1%), distributed between clades 20J, 21G, 21H, 21J, and 21I. This study reveals updated information on the viral genomics of SARS-CoV-2 in the Lambayeque region, Peru, which is crucial to understanding the origins and dispersion of the virus and provides information on viral pathogenicity, transmission and epidemiology.