Quality Control Procedures Research Articles

SMART quality control analysis of pavement condition data for pavement management applications

Assuring the accuracy and reliability of pavement condition data is crucial for effective decision-making in pavement management. Despite existing data collection protocols, concerns persist regarding data quality. This paper introduces SMART, a systematic statistical method designed to analyze the quality of pavement condition data from field surveys for pavement management applications. SMART employs a structured procedure that expands traditional descriptive statistics by applying interrater reliability statistics combined with bootstrapping methods and Modified Blant Altman diagrams to evaluate data quality. A comparative analysis of interrater statistics, including Cohen’s Kappa (CK), Interclass Correlation (IC), Krippendorff’s Alpha (KA), Percent Agreement (PA), and Weighted Cohen’s Kappa (WCK), is conducted in the research study. As a result, the adoption of KA and Modified Bland-Altman diagrams for data analysis is recommended. KA demonstrates versatility across diverse data types, accommodating nominal, ordinal, interval, and ratio-level data, while Modified Bland-Altman diagrams facilitate data dispersion analysis to visualize possible bias trends for the condition ratings. A case study is presented to demonstrate the applicability of SMART to analyzing Pavement Condition Index (PCI) data provided by the Metropolitan Transportation Commission (MTC) in California. This methodological approach aims to enhance pavement management decisions by ensuring the reliability of condition field survey data through the implementation of robust analytical quality control procedures.

The genetic risk architecture of mucosal melanoma.

10595 Background: Mucosal melanoma (MM) is a rare and aggressive subtype of melanoma. Outcomes for MM are significantly worse than for cutaneous melanoma (CM). While somatic mutations induced by UV radiation are known to cause CM, less is known about environmental and genetic alterations associated with MM. High penetrance alleles have been identified in familial cases of CM but the contribution of germline mutations to development of MM is not understood. Further, whilst population-based risk has been elaborated in CM, little is known for MM. The aim of this study is to characterize the germline genetic architecture of MM from high penetrance alleles to patient population genetics. Methods: A large retrospective cohort of MM patients (n=247) seen at MD Anderson Cancer Center were identified. Demographics, primary tumor sites, and presence of somatic mutations in BRAF, NRAS and KIT were extracted. Germline sequencing was performed on PBMC derived genomic DNA from the cohort using a gene panel of 322 major cancer genes. Frequency of identified germline alleles were compared to expected population control rate based on TOPMED using Fisher’s exact test. For genome wide association analysis (GWAS), genotyping will be performed on the MM cohort and the control group using the Infinium Global Screening Array. Cancer-free controls matched 3:1 based on MM cohort demographics have been assembled from existing case-control studies at MD Anderson. Following standard quality control procedures, we will impute variants from TOPMed using the Michigan Imputation Server. SNPtest v2.5.268 software will be utilized to perform association tests, using a multivariate logistic regression model incorporating gender and principal components. In addition to variants that may surpass a genome-wide significance score, we will inspect results for an enrichment of cancer genes. Results: Median age of MM cohort is 63, female predominant (60%), primarily White (84.6%), with gastrointestinal (36%), genitourinary (34%) and head & neck (30%) being the most common MM subtypes. Characteristics of the cohort were representative of the US MM population. Somatic mutations in KIT (26%) were most common. Germline mutations were found in 10.9% of the cohort, with most common detected variations in MITF (c.G952A:p.E318K) (2.4%) at OR of 13.9 (95%CI 5.0, 30.9), and CHEK2 (c.1100delC:p.T367fs) (1.6%) at OR of 16.4 (4.4, 42.9) compared to population control rate. Conclusions: Our study is the first to demonstrate the distribution of germline mutations in the largest cohort of MM patients. The MITF E318K allele is a known risk factor for CM, while CHEK2 1100delC allele has mixed evidence for conferring CM risk. GWAS data are currently being analyzed and these updated results will be presented in the context of the comprehensive analyses of germline risk alleles in MM patients.

Policy and laboratory practice: How quality control procedures for genetic testing perpetuate biological essentialism and discrimination against transgender, gender diverse, and intersex people.

Transgender, gender diverse, and intersex (TGDI) individuals face significant health disparities due to individual and systemic experiences of discrimination, impacting their access to healthcare. While clinical genetic testing has become increasingly accessible to the general population, the field of clinical genetics perpetuates a narrative of biological essentialism, which creates barriers for TGDI patients. Biological essentialism upholds that sex is a binary, fixed, and innate characteristic, a misconception that has been historically weaponized against the TGDI community in both individual experiences of discrimination and anti-trans legislation, among other systemic forms of oppression. Rejecting this discriminatory framework requires careful consideration of, and changes to, long-established practices that often go unquestioned, such as quality control metrics in genetic testing, in order to improve TGDI patients' outcomes and access to genetic services. The sex-check, comparing an individuals reported sex against their sex chromosomes, is an example of how laboratory genetics practices reinforce the narrative that sex is determined purely by chromosomal composition. Additionally, the sex-check "outs" TGDI people in clinical settings, creating a discriminatory and unsafe environment for these patients. Alternative quality control procedures and inclusive practices, such as clearer delineation of sex and gender on test requisition forms, are proposed to improve TGDI patient experiences. Genetic counselors and other clinical providers have a responsibility to address historical discrimination and advocate for changes to laboratory practice, so as to create affirming experiences for TGDI patients.

Demystifying In Vivo Bioluminescence Imaging of a Chagas Disease Mouse Model for Drug Efficacy Studies.

To control and decrease the public health impact of human protozoan diseases such as Chagas disease, leishmaniasis, and human African trypanosomiasis, expediting the development of new drugs and vaccines is necessary. However, this process is filled with difficulties such as highly complex parasite biology and disease pathogenesis and, as typical for neglected tropical diseases, comparatively limited funding for research and development. Thus, in vitro and in vivo study models that can sufficiently reproduce infection and disease key features while providing rational use of resources are essential for progressing research for these conditions. One example is the in vivo bioluminescence imaging (BLI) mouse model for Chagas disease, which provides highly sensitive detection of long wavelength light generated by Trypanosoma cruzi parasites expressing luciferase. Despite this technique becoming the standard approach for drug efficacy in vivo studies, research groups might still struggle to implement it due to a lack of proper practical training on equipment handling and application of quality control procedures, even when suitable BLI equipment is readily available. Considering this scenario, this protocol aims to guide from planning experiments to data acquisition and analysis, with details that facilitate the implementation of protocols in research groups with little or no experience with BLI, either for Chagas disease or for other infectious disease mouse models.

The Mechanical Properties and Chlorine Resistance of Concrete Based on the Effects of Pouring Interval Time

In practical engineering construction, differences in time intervals during concrete pouring arise due to issues in concrete quality control and construction procedures, thereby affecting the mechanical and durability properties of concrete. This study conducted compressive strength tests, splitting tensile strength tests, and natural immersion tests to investigate the influence of time intervals in layered pouring on the mechanical strength and chloride ion concentration distribution of staged pouring concrete. Additionally, the study elucidated the mechanism by which pouring interval time affects the mechanical properties and resistance to chloride ion erosion of staged pouring concrete at the microstructure level. The results indicate that compared to ordinary concrete specimens, the splitting tensile strength of staged pouring concrete demonstrates a continuous decrease with increasing pouring interval time. The most significant splitting tensile strength decrease occurred at a 24 h interval. The compressive strength of staged pouring concrete initially decreases and then increases with increasing pouring interval time. At a pouring interval time of 12 h, the compressive strength of staged pouring concrete decreased the most. Results from the natural immersion tests demonstrate that chloride ion concentrations at the bonding interface and on both sides of staged pouring concrete increase continuously with the extension of pouring interval time. The chloride ion concentration at the bonding interface is consistently higher than that on both sides, and the difference between them decreases with increasing diffusion depth. The chloride ion concentration difference ΔC was proposed to evaluate the influence of bonding interface performance on chloride ion concentration, which decreases to varying degrees with increasing depth. The findings of this study can provide guidance for the research on the mechanical properties and durability of staged pouring concrete in practical engineering construction, as well as for engineering protective measures.

Assessment of the relationship between gut microbiota and bone mineral density: a two-sample Mendelian randomization study.

Emerging evidence from observational studies and clinical trials suggests a connection between the gut microbiota and variations in bone mineral density (BMD). Nonetheless, the specific association between gut microbiota and BMD alterations at different skeletal sites has not been comprehensively explored. To address this, we employed Genome-Wide Association Study (GWAS) summary statistics from a publicly accessible database, conducting a two-sample Mendelian Randomization analysis to elucidate the potential causal relationship between gut microbiota composition and BMD. This study utilized two distinct thresholds for screening instrumental variables (IVs), followed by an extensive series of quality control procedures to identify IVs that were significantly related to exposure. Gut microbiota were classified into two sets based on hierarchical levels: phylum, class, order, family, and genus. Bone mineral density (BMD) data were systematically collected from four skeletal sites: femoral neck, lumbar spine, forearm, and heel. For Mendelian Randomization (MR) analysis, robust methods including Inverse-Variance Weighting (IVW) and the Wald Ratio Test were employed. Additional analytical tests such as the Outlier Test, Heterogeneity Test, 'Leave-One-Out' Test, and Pleiotropy Test were conducted to assess the impact of horizontal pleiotropy, heterogeneities, and the genetic variation stability of gut microbiota on BMD causal associations. The MR Steiger Directionality Test was applied to exclude studies with potential directional biases. In this two-sample Mendelian randomization analysis, we utilized five sets of exposure GWAS (Genome-Wide Association Studies) summary statistics and four sets of outcome GWAS summary statistics. The initial analysis, applying a threshold of p < 5 × 10-6, identified 48 significant causal relationships between genetic liability in the gut microbiome and bone mineral density (BMD). A subsequent analysis with a more stringent threshold of p < 5 × 10-8 uncovered 14 additional causal relationships. Upon applying the Bonferroni correction, 9 results from the first analysis and 10 from the second remained statistically significant. Our MR analysis revealed a causal relationship between gut microbiota and bone mineral density at all sites, which could lead to discoveries in future mechanistic and clinical studies of microbiota-associated osteoporosis.

Longitudinal assessment of extreme climate events in Kinnaur district, Himachal Pradesh, north-western Himalaya, India.

It is vital to keep an eye on changes in climatic extremes because they set the stage for current and potential future climate, which usually have a reasonable adverse impact on ecosystems and society. The present study examines the variability and trends in precipitation and temperature across seasons in the Kinnaur district, offering valuable insights into the complex dynamics ofthe Himalayan climate. Using Climatic Research Unit gridded Time Series (CRU TS) datasets from 1951 to 2021, the study analyzes the data to produce 28 climate indices based on India Meteorological Department (IMD) convention indices and Expert Team on Climate Change Detection and Indices (ETCCDI). Although there may be considerable variation in climate indices in terms of absolute values within different products, there is consensus in both long-term trends and inter-annual variability. Analysis shows that even within a small area, there is variability in the magnitude and direction of historic temperature trends. Initially, the datawere subjected to rigorous quality control procedures, which involved identifying anomalies. Statistical analysis like trend analysis, employing Mann-Kendall test and Sen's slope estimator, reveal significant (p < 0.05) increase in consecutive dry days (CDD) at 0.03days/year and decrease in consecutive wet days (CWD) at 0.02days/year. Notably, the frequency of heavy precipitation occurrences showed an increasing trend. Changes in precipitation in the Western Himalaya are driven by a complex interplay of orographic effects, monsoonal dynamics, atmospheric circulation patterns, climate change, and localized factors such as topography, atmospheric circulation patterns, moisture sources, land-sea temperature contrasts, and anthropogenic influences. Moreover, in case of temperature indices, there is significant increasing trend observed. Temperature indices indicate a significant annual increase in warm nights (TN90p) at 0.06%/year and warm days (TX90p) at 0.11%/year. Extreme temperature events have been trending upward, with monthly daily maximum temperature (TXx) increasing by 1.5°C yearly. This study enhances our comprehension of the global warming phenomenon and underscores the importance of acknowledging alterations in the water cycle and their repercussions on hydrologic resources, agriculture, and livelihoods in the cold desert of the northwestern Indian Himalaya.

Development of standard operating procedure "Quality control of sodium chloride solution 0.9% (350 ml) for infusion (intra-pharmacy preparation) in pharmacy organizations manufacturing pharmaceuticals"

To develop a standard operating procedure (SOP) for quality control of 0.9% sodium chloride solution (350 ml) for infusion (intra-pharmacy preparation) in accordance with the requirements of the current regulatory documentation. Materials and Methods. Sodium chloride 0.9% sodium chloride solution (350 ml) for infusion (intra-pharmacy preparation) served as the object of the study. The SOP was developed taking into account the requirements of updated regulatory documents used in the field of quality control of medicines: Federal Law No. 61 dated 12.04.2010 "On Circulation of Medicines", Order of the Ministry of Health of the Russian Federation dated 22.05.2023 No. 249n, Order of the Ministry of Health of the Russian Federation dated 22.05.2023 No. 647n dated 31.08.2016, State Pharmacopoeia XV ed. and GOST R 52249-2009. Results. The main stages of the SOP in accordance with the current regulatory documentation are given, reagents, instruments and equipment required for testing are listed, mandatory and sample types of control are indicated. For this dosage form the mandatory controls will be organoleptic, written, control at release, physical and full chemical control. The methods of pH and authenticity tests are described, and the chemistry of qualitative reactions is given. For quantitative determination by the method of argentometry according to Mohr, the method of analysis is given, chemical reactions occurring during titration, the necessary calculations are made: the titer of silver nitrate solution of sodium chloride, the preliminary volume of titrant, the content of sodium chloride in the dosage form in grams. Permissible content limits are given in accordance with OFS.1.8.0001 "Medicinal preparations of pharmacy manufacture". Based on the results of the SOP development, a working instruction for quality control of sodium chloride solution 0.9% (350 ml) for infusion was drawn up. Conclusion. The presented SOP for quality control of sodium chloride solution 0.9% (350 ml) for infusion (intra-pharmacy preparation) describes the requirements for the organization and conditions of testing in assessing the quality of this dosage form and can be implemented in the work of manufacturing pharmacies as a detailed instruction for intra-pharmacy control.

Deciphering smooth muscle cell heterogeneity in atherosclerotic plaques and constructing model: a multi-omics approach with focus on KLF15/IGFBP4 axis

BackgroundRuptured atherosclerotic plaques often precipitate severe ischemic events, such as stroke and myocardial infarction. Unraveling the intricate molecular mechanisms governing vascular smooth muscle cell (VSMC) behavior in plaque stabilization remains a formidable challenge.MethodsIn this study, we leveraged single-cell and transcriptomic datasets from atherosclerotic plaques retrieved from the gene expression omnibus (GEO) database. Employing a combination of single-cell population differential analysis, weighted gene co-expression network analysis (WGCNA), and transcriptome differential analysis techniques, we identified specific genes steering the transformation of VSMCs in atherosclerotic plaques. Diagnostic models were developed and validated through gene intersection, utilizing the least absolute shrinkage and selection operator (LASSO) and random forest (RF) methods. Nomograms for plaque assessment were constructed. Tissue localization and expression validation were performed on specimens from animal models, utilizing immunofluorescence co-localization, western blot, and reverse-transcription quantitative-polymerase chain reaction (RT-qPCR). Various online databases were harnessed to predict transcription factors (TFs) and their interacting compounds, with determination of the cell-specific localization of TF expression using single-cell data.ResultsFollowing rigorous quality control procedures, we obtained a total of 40,953 cells, with 6,261 representing VSMCs. The VSMC population was subsequently clustered into 5 distinct subpopulations. Analyzing inter-subpopulation cellular communication, we focused on the SMC2 and SMC5 subpopulations. Single-cell subpopulation and WGCNA analyses revealed significant module enrichments, notably in collagen-containing extracellular matrix and cell-substrate junctions. Insulin-like growth factor binding protein 4 (IGFBP4), apolipoprotein E (APOE), and cathepsin C (CTSC) were identified as potential diagnostic markers for early and advanced plaques. Notably, gene expression pattern analysis suggested that IGFBP4 might serve as a protective gene, a hypothesis validated through tissue localization and expression analysis. Finally, we predicted TFs capable of binding to IGFBP4, with Krüppel-like family 15 (KLF15) emerging as a prominent candidate showing relative specificity within smooth muscle cells. Predictions about compounds associated with affecting KLF15 expression were also made.ConclusionOur study established a plaque diagnostic and assessment model and analyzed the molecular interaction mechanisms of smooth muscle cells within plaques. Further analysis revealed that the transcription factor KLF15 may regulate the biological behaviors of smooth muscle cells through the KLF15/IGFBP4 axis, thereby influencing the stability of advanced plaques via modulation of the PI3K-AKT signaling pathway. This could potentially serve as a target for plaque stability assessment and therapy, thus driving advancements in the management and treatment of atherosclerotic plaques.

Assessment of fungal species in some spices using molecular study with detection of their mycotoxins using chromatography analysis.

Spices are food flavouring agents that are highly used in Iraq. However, they may be contaminated by toxicogenic fungi and subsequent production of mycotoxins. The aim of this study was to investigate the contamination of commonly used spices with fungi using polymerase chain reaction (PCR) assay and to detect fungal mycotoxin using high-performance liquid chromatography. Thirty-five spices (seven samples from each black pepper, red pepper, turmeric, cumin and ginger) were cultured on an appropriate medium to identify various fungi species. Later on, the toxigenicity of Aspergillus flavus and Aspergillus niger was determined using a PCR assay. The fungal mycotoxins, including aflatoxins and ochratoxins, were then determined through a high-performance liquid chromatography using the validated Quick, Easy, Cheap, Effective, Rugged, and Safe (QuECHERS) method. Aspergillus species were the predominantly isolated fungi, followed by Penicillium and Fusarium. The PCR results indicate the high toxigenicity of A. flavus as 85.7% of the strains had aflQ/aflR genes and 79% had PKS15KS/PKS15C-MeT genes. Regarding mycotoxin contamination in spices, the highest rates of aflatoxins and ochratoxins were found in black pepper (5.913 μg/kg) and red chilli (6.9055 μg/kg), respectively. Spices are susceptible substrates for the growth of mycotoxigenic fungi. Thus, regular effective surveillance and quality control procedures are highly recommended.

A culture-independent nucleic acid diagnostics method for use in the detection and quantification of Burkholderia cepacia complex contamination in aqueous finished pharmaceutical products.

The Burkholderia cepacia complex (Bcc) is the number one bacterial complex associated with contaminated Finished Pharmaceutical Products (FPPs). This has resulted in multiple healthcare related infection morbidity and mortality events in conjunction with significant FPP recalls globally. Current microbiological quality control of FPPs before release for distribution depends on lengthy, laborious, non-specific, traditional culture-dependent methods which lack sensitivity. Here, we present the development of a culture-independent Bcc Nucleic Acid Diagnostic (NAD) method for detecting Bcc contaminants associated with Over-The-Counter aqueous FPPs. The culture-independent Bcc NAD method was validated to be specific for detecting Bcc at different contamination levels from spiked aqueous FPPs. The accuracy in Bcc quantitative measurements was achieved by the high degree of Bcc recovery from aqueous FPPs. The low variation observed between several repeated Bcc quantitative measurements further demonstrated the precision of Bcc quantification in FPPs. The robustness of the culture-independent Bcc NAD method was determined when its accuracy and precision were not significantly affected during testing of numerous aqueous FPP types with different ingredient matrices, antimicrobial preservative components and routes of administration. The culture-independent Bcc NAD method showed an ability to detect Bcc in spiked aqueous FPPs at a concentration of 20 Bcc CFU/mL. The rapid (≤ 4 hours from sample in to result out), robust, culture-independent Bcc NAD method presented provides rigorous test specificity, accuracy, precision, and sensitivity. This method, validated with equivalence to ISO standard ISO/TS 12869:2019, can be a valuable diagnostic tool in supporting microbiological quality control procedures to aid the pharmaceutical industry in preventing Bcc contamination of aqueous FPPs for consumer safety.

Assess The Workload Management Model and Enhanced Quality Control in The Central Sterile Supply Department: A Study Protocol.

Introduction The Central Sterile Supply Department (CSSD) plays a crucial role in ensuring the safety and efficacy of medical instruments and equipment used in healthcare settings. Effective workload management and quality control are essential for maintaining high standards of patient care and minimizing the risk of healthcare-associated infections. This study protocol aims to assess the implementation and impact of a new workload management model and enhanced quality control measures in a CSSD setting. Methods The study will employ a mixed-methods approach, including quantitative analysis of workload data, qualitative interviews with CSSD staff, and observational assessments of workflow and quality control procedures. The workload management model under investigation involves the allocation of resources based on demand patterns and the implementation of scheduling algorithms to optimize staff efficiency. Enhanced quality control measures include the implementation of advanced sterilization technologies, rigorous inspection protocols, and continuous staff training initiatives. Results The study expects to provide insights into the effectiveness of the workload management model in optimizing resource allocation and improving staff productivity. Additionally, it aims to evaluate the impact of enhanced quality control measures on the reliability and safety of instrument sterilization processes. Findings from this study will inform recommendations for further improvements in CSSD operations and contribute to the advancement of best practices in sterile supply management. Conclusion The successful implementation of an effective workload management model and enhanced quality control measures in the CSSD is crucial for maintaining patient safety and ensuring the efficient functioning of healthcare facilities. By systematically evaluating the implementation and impact of these interventions, this study protocol seeks to contribute to the ongoing improvement of CSSD operations and the enhancement of healthcare quality.

Comparison of tau spread in people with Down syndrome versus autosomal-dominant Alzheimer's disease: a cross-sectional study

In people with genetic forms of Alzheimer's disease, such as in Down syndrome and autosomal-dominant Alzheimer's disease, pathological changes specific to Alzheimer's disease (ie, accumulation of amyloid and tau) occur in the brain at a young age, when comorbidities related to ageing are not present. Studies including these cohorts could, therefore, improve our understanding of the early pathogenesis of Alzheimer's disease and be useful when designing preventive interventions targeted at disease pathology or when planning clinical trials. We compared the magnitude, spatial extent, and temporal ordering of tau spread in people with Down syndrome and autosomal-dominant Alzheimer's disease. In this cross-sectional observational study, we included participants (aged ≥25 years) from two cohort studies. First, we collected data from the Dominantly Inherited Alzheimer's Network studies (DIAN-OBS and DIAN-TU), which include carriers of autosomal-dominant Alzheimer's disease genetic mutations and non-carrier familial controls recruited in Australia, Europe, and the USA between 2008 and 2022. Second, we collected data from the Alzheimer Biomarkers Consortium-Down Syndrome study, which includes people with Down syndrome and sibling controls recruited from the UK and USA between 2015 and 2021. Controls from the two studies were combined into a single group of familial controls. All participants had completed structural MRI and tau PET (18F-flortaucipir) imaging. We applied Gaussian mixture modelling to identify regions of high tau PET burden and regions with the earliest changes in tau binding for each cohort separately. We estimated regional tau PET burden as a function of cortical amyloid burden for both cohorts. Finally, we compared the temporal pattern of tau PET burden relative to that of amyloid. We included 137 people with Down syndrome (mean age 38·5 years [SD 8·2], 74 [54%] male, and 63 [46%] female), 49 individuals with autosomal-dominant Alzheimer's disease (mean age 43·9 years [11·2], 22 [45%] male, and 27 [55%] female), and 85 familial controls, pooled from across both studies (mean age 41·5 years [12·1], 28 [33%] male, and 57 [67%] female), who satisfied the PET quality-control procedure for tau-PET imaging processing. 134 (98%) people with Down syndrome, 44 (90%) with autosomal-dominant Alzheimer's disease, and 77 (91%) controls also completed an amyloid PET scan within 3 years of tau PET imaging. Spatially, tau PET burden was observed most frequently in subcortical and medial temporal regions in people with Down syndrome, and within the medial temporal lobe in people with autosomal-dominant Alzheimer's disease. Across the brain, people with Down syndrome had greater concentrations of tau for a given level of amyloid compared with people with autosomal-dominant Alzheimer's disease. Temporally, increases in tau were more strongly associated with increases in amyloid for people with Down syndrome compared with autosomal-dominant Alzheimer's disease. Although the general progression of amyloid followed by tau is similar for people Down syndrome and people with autosomal-dominant Alzheimer's disease, we found subtle differences in the spatial distribution, timing, and magnitude of the tau burden between these two cohorts. These differences might have important implications; differences in the temporal pattern of tau accumulation might influence the timing of drug administration in clinical trials, whereas differences in the spatial pattern and magnitude of tau burden might affect disease progression. None.

The annual update GLODAPv2.2023: the global interior ocean biogeochemical data product

Abstract. The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2023 is an update of the previous version, GLODAPv2.2022 (Lauvset et al., 2022). The major changes are as follows: data from 23 new cruises were added. In addition, a number of changes were made to the data included in GLODAPv2.2022. GLODAPv2.2023 includes measurements from more than 1.4 million water samples from the global oceans collected on 1108 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on the systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 23 new cruises were derived by comparing those data with the data from the 1085 quality-controlled cruises in the GLODAPv2.2022 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2), chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data-handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments. The original data, their documentation, and DOI codes are available at the Ocean Carbon and Acidification Data System of NOAA National Centers for Environmental Information (NCEI), which also provides access to the merged data product. This is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/zyrq-ht66 (Lauvset et al., 2023). These bias-adjusted product files also include significant ancillary and approximated data, which were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2023 methods and provides a broad overview of the secondary quality control procedures and results.

Front glass crack inspection of thin-film solar photovoltaic modules using high-order ultrasonic Lamb waves

Ensuring the structural integrity of solar photovoltaic modules is crucial to maintain power production efficiency and fulfill the anticipated product lifespan. Hence, implementing quality control procedures and structural health monitoring is necessary throughout the stages of manufacture and operation. The ultrasonic examination has some benefits compared to electroluminescence and infrared approaches, namely in identifying mechanical flaws in the front glass. The Lamb waves (LW) method is an auspicious inspection approach among ultrasonic-based methods. This is primarily attributed to its quicker measurement speed than the standard ultrasonic c-scan. The LW method offers an advantage in terms of its ability to provide long-range coverage. The predominant approach in LW inquiry often centers on using fundamental modes within the low-frequency range. Nevertheless, the findings of this investigation demonstrate that the higher-order mode exhibits superior effectiveness for the specific objective of this research, as it displays a higher level of sensitivity towards cracks in the front glass of the module. The current study ultimately showcases the use of the LW scan. A damage indication threshold is determined by the fraction of energy spectral density (ESD) associated with the crack-sensitive mode. This technology effectively produces a comprehensive map of the designated area by comparing the ESD values at various measurement positions with a predetermined threshold. This map provides precise indications of the existence of areas that are affected by cracks.

Ensuring Accuracy: Critical Validation Techniques in Geochemical Analysis for Sustainable Geothermal Energy Development

Geochemical analysis is a critical tool in geothermal exploration, providing valuable insights into reservoir characteristics. However, obtaining accurate and reliable geochemical data requires rigorous validation techniques. This review examines key factors affecting the accuracy of geochemical data and discusses best practices for ensuring quality. Proper sampling methods, including selection of representative locations, use of appropriate equipment, and adherence to robust protocols for sample collection, filtration, preservation, and storage, are essential for maintaining integrity. Analytical techniques must be carefully selected, with regular calibration and standardization of instruments using certified reference materials. Implementing comprehensive quality assurance and quality control procedures, such as analyzing blanks, duplicates, and spike samples, helps monitor precision and accuracy. Data interpretation should consider the complexities of the geological and hydrological settings, integrating multiple lines of evidence. By following established guidelines and continuously updating methods based on emerging technologies and inter-laboratory comparisons, geothermal teams can optimize the reliability of their geochemical data. Accurate and precise geochemical information, when combined with geological, geophysical, and hydrological data, enables informed decision-making and enhances the success of geothermal projects. As geothermal energy gains importance in the transition to sustainable resources, ensuring the accuracy of geochemical analysis will be crucial for effective exploration and development.

Classification of the quality of canine and feline ventrodorsal and dorsoventral thoracic radiographs through machine learning.

Thoracic radiographs are an essential diagnostic tool in companion animal medicine and are frequently used as a part of routine workups in patients presenting for coughing, respiratory distress, cardiovascular diseases, and for staging of neoplasia. Quality control is a critical aspect of radiology practice in preventing misdiagnosis and ensuring consistent, accurate, and reliable diagnostic imaging. Implementing an effective quality control procedure in radiology can impact patient outcomes, facilitate clinical decision-making, and decrease healthcare costs. In this study, a machine learning-based quality classification model is suggested for canine and feline thoracic radiographs captured in both ventrodorsal and dorsoventral positions. The problem of quality classification was divided into collimation, positioning, and exposure, and then an automatic classification method was proposed for each based on deep learning and machine learning. We utilized a dataset of 899 radiographs of dogs and cats. Evaluations using fivefold cross-validation resulted in an F1 score and AUC score of 91.33 (95% CI: 88.37-94.29) and 91.10 (95% CI: 88.16-94.03), respectively. Results indicated that the proposed automatic quality classification has the potential to be implemented in radiology clinics to improve radiograph quality and reduce nondiagnostic images.

Digital transformation of quality management in the construction industry during the execution phase by integration of building information modeling (BIM) and cloud computing

The quality of construction projects significantly impacts social and economic development. However, low quality and project failure often result from factors such as lack of quality procedures, poor communication, task coordination, and inefficient progress monitoring. This research aims to improve the efficiency of the construction phase by creating quality control checklists for processes and enhancing quality management through a collaborative digital environment integrating building information modeling (BIM) and cloud computing. Expert constructive interviews were first conducted to define a construction process quality control procedure to be linked to the 3DBIM model and then transition to a collaborative cloud environment (Autodesk Construction Cloud). An actual instance in Latakia City (Syria) demonstrated that the proposed methodology improves the efficiency and effectiveness of quality management during the implementation phase. It does so by offering a robust database, enhancing on-site quality information extraction from BIM models using smartphones, documenting defects and entering inspection data directly into a shared digital environment, and making it easier to track corrective actions and feedback. This facilitates constant and organized access to current data, reducing errors and rework, saving money and time, and enhancing decision-making speed and effectiveness. The search recommends the necessity of strict laws to adhere to quality procedures and the importance of providing infrastructure for digital transformation in quality management.

Estimating genetic parameters of digital behavior traits and their relationship with production traits in purebred pigs

BackgroundWith the introduction of digital phenotyping and high-throughput data, traits that were previously difficult or impossible to measure directly have become easily accessible, offering the opportunity to enhance the efficiency and rate of genetic gain in animal production. It is of interest to assess how behavioral traits are indirectly related to the production traits during the performance testing period. The aim of this study was to assess the quality of behavior data extracted from day-wise video recordings and estimate the genetic parameters of behavior traits and their phenotypic and genetic correlations with production traits in pigs. Behavior was recorded for 70 days after on-test at about 10 weeks of age and ended at off-test for 2008 female purebred pigs, totaling 119,812 day-wise records. Behavior traits included time spent eating, drinking, laterally lying, sternally lying, sitting, standing, and meters of distance traveled. A quality control procedure was created for algorithm training and adjustment, standardizing recording hours, removing culled animals, and filtering unrealistic records.ResultsProduction traits included average daily gain (ADG), back fat thickness (BF), and loin depth (LD). Single-trait linear models were used to estimate heritabilities of the behavior traits and two-trait linear models were used to estimate genetic correlations between behavior and production traits. The results indicated that all behavior traits are heritable, with heritability estimates ranging from 0.19 to 0.57, and showed low-to-moderate phenotypic and genetic correlations with production traits. Two-trait linear models were also used to compare traits at different intervals of the recording period. To analyze the redundancies in behavior data during the recording period, the averages of various recording time intervals for the behavior and production traits were compared. Overall, the average of the 55- to 68-day recording interval had the strongest phenotypic and genetic correlation estimates with the production traits.ConclusionsDigital phenotyping is a new and low-cost method to record behavior phenotypes, but thorough data cleaning procedures are needed. Evaluating behavioral traits at different time intervals offers a deeper insight into their changes throughout the growth periods and their relationship with production traits, which may be recorded at a less frequent basis.

Aerosol and cloud data processing and optical property retrieval algorithms for the spaceborne ACDL/DQ-1

Abstract. The new-generation atmospheric environment monitoring satellite DQ-1, launched successfully in April 2022, carries the Aerosol and Carbon Detection Lidar (ACDL), which is capable of globally profiling aerosol and cloud optical properties with high accuracy. The ACDL/DQ-1 is a high-spectral-resolution lidar (HSRL) that separates molecular backscatter signals using an iodine filter and has 532 nm polarization detection and dual-wavelength detection at 532 and 1064 nm, which can be utilized to derive aerosol optical properties. The methods have been specifically developed for data processing and optical property retrieval according to the specific characteristics of the ACDL system and are introduced in detail in this paper. Considering the different signal characteristics and different background noise behaviors of each channel during daytime and nighttime, the procedures of data pre-processing, denoising process and quality control are applied to the original measurement signals. The aerosol and cloud optical property products of the ACDL/DQ-1, including the total depolarization ratio, backscatter coefficient, extinction coefficient, lidar ratio and color ratio, can be calculated by the retrieval algorithms presented in this paper. Two measurement cases with use of the ACDL/DQ-1 on 27 June 2022 and the global averaged aerosol optical depth (AOD) from 1 June to 4 August 2022 are provided and analyzed, demonstrating the measurement capability of the ACDL/DQ-1.