Quality Control Activities Research Articles

B-023 Workflow evaluation of the new Siemens Atellica CI Analyzer

Abstract Background The Atellica® CI Analyzer, Model 1900 is an integrated clinical chemistry and immunoassay analyzer that has the same user interface, general workflow, and planned test menu to that of the larger Atellica® Solution. Atellica CI Analyzer also shares the same reagents and consumables as the Atellica Solution. The purpose of this study was to evaluate workflow performance of the Atellica CI Analyzer in a routine-like clinical laboratory setting. Methods The study was conducted at four international laboratory facilities over a four-month period. Basic throughput of the Atellica CI Analyzer was evaluated at each site by testing quality control (QC) and remnant anonymized patient samples using an 8:2 mixture of chemistry (ion selective electrolytes [IMT], clinical chemistry analytes) and immunochemistry assays. Additionally, the impact of interrupting routine testing for STAT high-sensitivity cardiac troponin samples was also evaluated. Daily, weekly, and monthly maintenance activities were observed, and data collected through direct observations, time and motion studies, and system run logs. Results The Atellica CI Analyzer aspirated patient samples in as little as two minutes (mins) with the time to first result for the mixed assay worklist ranging from 1 to 12 mins from the time of first barcode read. Across the four sites, the time to last result for the mixed assay worklist (average n=495 test results per site) ranged from 52 to 65 mins. The average turn around time (TAT) for high-sensitivity troponin was 9 mins from barcode read. Daily maintenance and QC activities for the Atellica CI Analyzer are comprised of both automated and manual activities. The average daily maintenance hands-on time was 3.6 min, ranging from 1.6 to 6.4 mins across the four sites. Daily QC preparation required <5 mins of hands-on time. The total average hands-on time to complete weekly maintenance for the Atellica CI Analyzer was 7.5 min. Conclusions The Atellica CI Analyzer demonstrated consistent system performance across all four study sites. Implementation of the Atellica CI Analyzer has the potential to increase laboratory efficiency given the minimal hands-on time required for daily and weekly maintenance activities and short TATs.

Deep learning of 3D point clouds for detecting geometric defects in gears

Geometric integrity directly impacts the functionality, reliability, and safety of final manufactured products, making the qualification of parts based on measurements of their geometry a fundamental quality control activity in modern manufacturing. Recent advancements in three-dimensional (3D) metrology technologies have enabled fine-scale inspection of geometric integrity characterized by dimensional accuracy, surface quality, and shape conformity. However, the widespread adoption of high-resolution 3D metrology in manufacturing faces some significant challenges posed by the inherent data structures of 3D point clouds such as high dimensionality, unstructured nature, and sparsity in defective regions. To address these challenges, this paper first creates a “MFGNet-gear” dataset, which is a scalable and comprehensive benchmark dataset comprising 12 part designs with four quality classes for each design. Subsequently, we develop a deep learning model adapted from the PointNet++ architecture to enable automated, end-to-end analysis of 3D point clouds. The model can be configured for different decision-making tasks including part design classification and multi-class geometric defect detection. Implementations of the proposed model on the “MFGNet-gear” dataset achieve accuracies up to 100% in classifying gear designs and up to 85% in four-class quality inspection. Additionally, we systematically investigate the impacts of measurement resolution and precision on the classification performance through a series of case studies. The obtained results highlight the potential of using deep learning methods for automated analysis of 3D point clouds for a variety of quality control tasks beyond gear manufacturing. This study also proposes future research directions, including the development of new deep learning architectures specifically designed for manufacturing 3D point clouds and strategies for adaptive measurement planning.

Development and validation of a deep learning model for detecting signs of tuberculosis on chest radiographs among US-bound immigrants and refugees.

Immigrants and refugees seeking admission to the United States must first undergo an overseas medical exam, overseen by the US Centers for Disease Control and Prevention (CDC), during which all persons ≥15 years old receive a chest x-ray to look for signs of tuberculosis. Although individual screening sites often implement quality control (QC) programs to ensure radiographs are interpreted correctly, the CDC does not currently have a method for conducting similar QC reviews at scale. We obtained digitized chest radiographs collected as part of the overseas immigration medical exam. Using radiographs from applicants 15 years old and older, we trained deep learning models to perform three tasks: identifying abnormal radiographs; identifying abnormal radiographs suggestive of tuberculosis; and identifying the specific findings (e.g., cavities or infiltrates) in abnormal radiographs. We then evaluated the models on both internal and external testing datasets, focusing on two classes of performance metrics: individual-level metrics, like sensitivity and specificity, and sample-level metrics, like accuracy in predicting the prevalence of abnormal radiographs. A total of 152,012 images (one image per applicant; mean applicant age 39 years) were used for model training. On our internal test dataset, our models performed well both in identifying abnormalities suggestive of TB (area under the curve [AUC] of 0.97; 95% confidence interval [CI]: 0.95, 0.98) and in estimating sample-level counts of the same (-2% absolute percentage error; 95% CIC: -8%, 6%). On the external test datasets, our models performed similarly well in identifying both generic abnormalities (AUCs ranging from 0.89 to 0.92) and those suggestive of TB (AUCs from 0.94 to 0.99). This performance was consistent across metrics, including those based on thresholded class predictions, like sensitivity, specificity, and F1 score. Strong performance relative to high-quality radiological reference standards across a variety of datasets suggests our models may make reliable tools for supporting chest radiography QC activities at CDC.

Italian-cluster technical solutions for the Quality-Control tests to the pixel-modules of the ATLAS Inner Tracker for High Luminosity LHC

In the era of high-luminosity LHC the instantaneous luminosity will achieve unprecedented levels, leading to the occurrence of up to 200 proton–proton interactions during a typical bunch crossing. In response to the resulting surge in occupancy, bandwidth demand, and radiation damage, the ATLAS Inner Detector is slated for replacement by an all-silicon system known as the Inner Tracker (ITk). The innermost segment of the ITk will be comprised of a pixel detector, featuring an active area spanning approximately 13 square meters. To address evolving requirements related to radiation hardness, power dissipation, and production yield, multiple silicon sensor technologies will be incorporated across the five barrel and end-cap layers. The ITk detector will be built in different laboratories all around the world. Several institutes are actively involved in the ITk project assembling and testing pre-production modules, that have been constructed to assess their production efficiency. Testing sites perform the so-called quality control (QC) tests. The ITk community defines requirements for QC testing both prototypes and modules, and provides common software tools as well as possible technical solutions. Each laboratory must qualify for the QC activity by demonstrating the chosen solutions are compliant with requirements. In this contribution the relevance of the QC procedures will be outlined, focusing on the custom structures and items developed by the Italian laboratories to improve the quality of the tests and to satisfy the requirements imposed by the Collaboration.

3-Methyl Thiophene-Modified Boron-Doped Diamond (BDD) Electrodes as Efficient Catalysts for Phenol Detection-A Case Study for the Detection of Gallic Acid in Three Specific Tea Types.

Polymer modification has been established as a cost-effective, simple, in situ method for overcoming some of the inherent disadvantages of boron-doped diamond (BDD) electrodes, and its application has been extended to reliable, low-cost environmental monitoring solutions. The present review focuses on modifying BDD electrodes with semi-conductive polymers acting as redox mediators. This article reports on the development of a 3-methyl thiophene-modified boron-doped diamond (BDD/P3MT) sensor for the electrochemical determination of total phenolic compounds (TPCs) in tea samples, using gallic acid (GA) as a marker. GA is a significant polyphenol with various biological activities, making its quantification crucial. Thus, a simple, fast, and sensitive GA sensor was fabricated using the electroanalytical square wave voltammetry (SWV) technique. The sensor utilizes a semi-conductive polymer, 3-methyl thiophene, as a redox mediator to enhance BDD's sensitivity and selectivity. Electrochemical synthesis was used for polymer deposition, allowing for greater purity and avoiding solubility problems. The BDD/P3MT sensor exhibits good electrochemical properties, including rapid charge transfer and a large electrochemical area, enabling GA detection with a limit of detection of 11 mg/L. The sensor's response was correlated with TPCs measured by the Folin-Ciocalteu method. Square wave voltammetry (SWV) showed a good linear relationship between peak currents and GA concentrations in a wide linear range of 3-71 mg/L under optimal conditions. The BDD/P3MT sensor accurately measured TPCs in green tea, rooibos tea, and black tea samples, with green tea exhibiting the highest TPC levels. The results demonstrate the potential of the modified BDD electrode for the rapid and accurate detection of phenolic compounds in tea, with implications for quality control and antioxidant activity assessments. The prolific publications of the past decade have established BDD electrodes as robust BDD sensors for quantifying polyphenols. Fruits, vegetables, nuts, plant-derived beverages such as tea and wine, traditional Eastern remedies and various herbal nutritional supplements contain phenolic chemicals. The safety concerns of contaminated food intake are significant health concerns worldwide, as there exists a critical nexus between food safety, nutrition, and food security. It has been well established that green tea polyphenol consumption promotes positive health effects. Despite their potential benefits, consuming high amounts of these polyphenols has sparked debate due to concerns over potential negative consequences.

Assessment of satisfaction of attendees of healthcare centers in Jordan with community pharmacy services of pharmacies they usually use.

Before extending the range of services provided, maximizing the usefulness of current procedures within community pharmacy settings is needed, as the scope of pharmacy services is evolving in different dimensions. The present study aims to assess the degree of factors affecting the satisfaction of traditional community pharmacy services using population data collected from patients attending academic and public healthcare centers in Jordan. A validated, pretested, and adapted survey instrument has been utilized to assess the satisfaction of contemporary services delivered by community pharmacists in different dimensions. Linear regression analysis evaluated the predictors associated with higher total satisfaction scores with community pharmacy services. The present study included 642 patients attending healthcare centers. Different dimension scores, such as explanation and consideration, scored similarly, with values ranging from 64.5% - 69.7% of the maximum possible score. The mean total scale score was 67.2% of the total possible scores. Using the linear regression analysis, respondents who were satisfied with their treatment plans were likely to have higher satisfaction with community pharmacy services. The increased number of prescription medications and increased age were associated with lower satisfaction with community pharmacy services. Results indicated that healthcare policymakers might be confident in the services within the community pharmacy setting; however, there is always room for more robust quality control activities.

The glycoprotein quality control factor Malectin promotes coronavirus replication and viral protein biogenesis.

Coronaviruses (CoV) rewire host protein homeostasis (proteostasis) networks through interactions between viral nonstructural proteins (nsps) and host factors to promote infection. With the emergence of SARS-CoV-2, it is imperative to characterize host interactors shared across nsp homologs. Using quantitative proteomics and functional genetic screening, we identify conserved proteostasis interactors of nsp2 and nsp4 that serve pro-viral roles during infection of murine hepatitis virus - a model betacoronavirus. We uncover a glycoprotein quality control factor, Malectin (MLEC), which significantly reduces infectious titers when knocked down. During infection, nsp2 interacts with MLEC-associated proteins and the MLEC-interactome is drastically altered, stabilizing association with the Oligosaccheryltransferase (OST) complex, a crucial component of viral glycoprotein production. MLEC promotes viral protein levels and genome replication through its quality control activity. Lastly, we show MLEC promotes SARS-CoV-2 replication. Our results reveal a role for MLEC in mediating CoV infection and identify a potential target for pan-CoV antivirals.

Assessing the setting behavior of ultra-high performance concrete

The setting behavior of ultra-high performance concrete (UHPC) is demonstrably different from that of conventional concrete; thus, tools and guidance extending beyond common test methods such as Vicat and penetration are needed. While UHPC is known for its enhanced mechanical and durability properties, due to the low water and high cementitious contents, UHPC-class materials are prone to early-age autogenous shrinkage. Recognizing that UHPCs are commonly supplied to construction sites as prebagged, proprietary mixes with unknown constituents, and that accurate determination of setting time is crucial in determining the early-age autogenous shrinkage of UHPC-class materials as well as for scheduling construction operations and quality control actions, this study explores alternate test methods such as isothermal calorimetry (ASTM C1679), semi-adiabatic calorimetry (ASTM C1753), autogenous shrinkage (ASTM C1698), chemical shrinkage (ASTM C1608), and dual ring test (American Association of State Highway and Transportation Officials (AASHTO T 363) to evaluate the setting behavior of UHPCs. Setting times obtained using the alternate test methods aligned well with each other and were found to be different than the setting times indicated through standard test methods. Discussion and guidance on the applicability and the use of alternate test methods to determine the setting time of UHPCs for various laboratory and field applications are provided.

Stability indicating high performance thin layer chromatography method development and validation for quantitative determination of tetracycline hydrochloride in tetracycline hydrochloride active pharmaceutical ingredient (API) and its dosage forms

Simple, quick, cost-effective, and environmentally friendly analytical methods for quality assurance and control roles for different medicines, including Tetrcyclines, are most significantly needed. Also, different thin layer chromatography (TLC)-based methods for tetracycline identification exist, but high performance thin layer chromatography methods based on modern state- of- the art equipment are still nonexistent. Thus, in this study, analytical method development and verification were done by high performance thin layer chromatography (HPTLC) (using an automated equipment model) using glass plates coated with silica gel 60 F254 after treating with 10% Na2EDTA. Validation was carried out according to International Council for Harmonization (ICH) guidelines. A mobile phase formed from ethyl acetate, acetonitrile, methanol, and 1% aqueous ammonia in the composition of 4.4:19.6:10:6 volume to volume ratio (V/V) was used. Rf value, percentage recoveries, linearity ranges, limit of detection (LOD), and limit of quantitation (LOQ) for the developed HPTLC method were 0.28, 100.83–106.25%, 160–560 ng/band (r2 values of 0.9999), 31.9 ng/band, and 96.7 ng/band, respectively. The results of the sample assays conducted using the new method and the United States Pharmacopoeia (USP) high performance liquid chromatography (HPLC) method were 91.59% to 108.3% and 90.83% to 102.85%, respectively. The F test for the aforementioned methods was 2.01, which is smaller than the tabulated F value of 5.05 with 5 degrees of freedom at a 95% confidence range, proving that the newly developed HPTLC and HPLC pharmacopoeial methods can be used interchangeably.The newly developed HPTLC method is easy, economical, specific, accurate, and roboust, thus it can be employed in a range of settings that require quality control and assurance activities of tetracycline hydrochloride (TC-HCl) in bulk and ointment dosage forms.

Economic Study of Strengthening of Existing RCC Building

Many structures fail or deteriorate before completion of its intended life span due to poor quality of material used, lack of mix design, poor workmanship, attacked by environmental agencies, etc. Sometimes due to slenderness of column or less reinforcement provided than actual requirements, less depth/thickness provided in flexural members, etc. feels excessive vibration during walking on floor ultimately develops cracks. Strength of such structural elements can be found by using non-destructive tests like Rebound hammer test, ultrasonic pulse velocity test, etc. If strength of existing structural elements is less than desired strength then structural consultant suggested strengthening of structural elements. There are various methods used in strengthening of existing structural elements like pressure grouting, fibre wrapping, chemical treatment, structural steel support, jacketing, etc. But these techniques are very costly and need precise quality control activity. In the present of investigation, strengthening of beam and column elements of a building by ferrocement techniques and steel jacketing were carried out and cost and cost comparison and strength results before and after strengthening are presented. It is observed that the strength og structural by ferrocement technique is cost effective than steel jacketing technique. And also has increase in the strength of RCC elements

Bringing source text quality into the legal translation classroom: training translators to face defective source texts

ABSTRACT Legal translators are routinely faced with defective source texts in their professional practice while being expected to produce effective translations despite such quality issues. Given the high-quality expectations required in legal translation, we have brought this professional reality into the classroom by outlining a quality control activity to allow legal translation trainees to systematise how they deal with defective Spanish administrative source texts. The proposal includes two steps: a translatability assessment and a pre-editing stage of defective administrative source texts. After empirically testing our proposal in the classroom, our initial findings suggest that this approach not only assists trainees to factor in poor source text quality when translating, but also to produce better translations.

Data Management in Multicountry Consortium Studies: The Enterics For Global Health (EFGH) Shigella Surveillance Study Example.

Rigorous data management systems and planning are essential to successful research projects, especially for large, multicountry consortium studies involving partnerships across multiple institutions. Here we describe the development and implementation of data management systems and procedures for the Enterics For Global Health (EFGH) Shigella surveillance study-a 7-country diarrhea surveillance study that will conduct facility-based surveillance concurrent with population-based enumeration and a health care utilization survey to estimate the incidence of Shigella--associated diarrhea in children 6 to 35 months old. The goals of EFGH data management are to utilize the knowledge and experience of consortium members to collect high-quality data and ensure equity in access and decision-making. During the planning phase before study initiation, a working group of representatives from each EFGH country site, the coordination team, and other partners met regularly to develop the data management systems for the study. This resulted in the Data Management Plan, which included selecting REDCap and SurveyCTO as the primary database systems. Consequently, we laid out procedures for data processing and storage, study monitoring and reporting, data quality control and assurance activities, and data access. The data management system and associated real-time visualizations allow for rapid data cleaning activities and progress monitoring and will enable quicker time to analysis. Experiences from this study will contribute toward enriching the sparse landscape of data management methods publications and serve as a case study for future studies seeking to collect and manage data consistently and rigorously while maintaining equitable access to and control of data.

Reliability-oriented product manufacturing quality improvement approach based on R-KQC and DMAIC

ABSTRACT Reliability-oriented product quality improvement is of great significance to assurance the fitness of quality control and management activities in the manufacturing process. A novel reliability-oriented product manufacturing quality improvement approach based on DMAIC (i.e. define, measure, analysis, improvement, control) and driven by reliability-oriented key quality characteristic (R-KQC) is proposed to prevent reliability degradation and improve product fitness quality in the manufacturing process. First, with the manufacturing reliability based on RQR chain taken into consideration, the connotation of R-KQC is defined. Second, a reliability-oriented DMAIC process driven by R-KQC is proposed. The R-KQC identification method based on feature selection and Shaply additive explanations (SHAP) is proposed. In order to improve the quality of manufacturing process effectively, R-KQC improvement method of response surface and R-KQC control method based on time-between-events (TBE) control chart are proposed. Finally, an illustrated example of an insulating base is provided to verify the effectiveness of the proposed approach, the average failure rate of the latest batch is reduced by 37.8%.

Patient‐based real‐time quality control in medical laboratories: On the design and robustness of the moving average control chart with truncation limits

AbstractQuality is an indispensable requirement in medical laboratories, where controls are performed at different phases of the laboratory processes. In the following, we consider the internal quality control activities during the analytical phase of medical laboratories for verifying the test results prior to their release. To monitor the measurement process for errors in the test results, one approach that is considerably attracting the health professionals is patient‐based real‐time quality control. In this respect, real‐time patient test results are monitored, commonly by implementing the Moving Average (MA) control chart with truncation limits. A usual practice is the use of truncation limits to exclude abnormal patient test results from the MA calculations. However, an open issue in the literature is how to determine the width of the truncation limits and the window size in the MA calculations. Furthermore, the distributions of the test results are often nonnormal and difficult to model by personnel having insufficient training in statistics. Consequently, robustness of the performance of the MA control chart to non‐normal distributions of test results is another open topic in the literature. In this study, a detailed robustness analysis is performed by considering various distributions having different shapes. Performance of several MA control chart designs constructed by altering the truncation limits and window sizes are investigated. Based on our simulation results with selected distributions, we conclude that the truncation limits should not be used and a window size of 20 is recommended. Under such a setting, the MA control chart performs similar to its intended performance in terms of false alarms and in detecting systematic errors, hence being robust to non‐normality of the test results.

The knowledge and reuse practices of researchers utilising government health information assets, Victoria, Australia, 2008-2020.

Using government health datasets for secondary purposes is widespread; however, little is known on researchers' knowledge and reuse practices within Australia. To explore researchers' knowledge and experience of governance processes, and their data reuse practices, when using Victorian government health datasets for research between 2008-2020. A cross-sectional quantitative survey was conducted with authors who utilised selected Victorian, Australia, government health datasets for peer-reviewed research published between 2008-2020. Information was collected on researchers': data reuse practices; knowledge of government health information assets; perceptions of data trustworthiness for reuse; and demographic characteristics. When researchers used government health datasets, 45% linked their data, 45% found the data access process easy and 27% found it difficult. Government-curated datasets were significantly more difficult to access compared to other-agency curated datasets (p = 0.009). Many respondents received their data in less than six months (58%), in aggregated or de-identified form (76%). Most reported performing their own data validation checks (70%). To assist in data reuse, almost 71% of researchers utilised (or created) contextual documentation, 69% a data dictionary, and 62% limitations documentation. Almost 20% of respondents were not aware if data quality information existed for the dataset they had accessed. Researchers reported data was managed by custodians with rigorous confidentiality/privacy processes (94%) and good data quality processes (76%), yet half lacked knowledge of what these processes entailed. Many respondents (78%) were unaware if dataset owners had obtained consent from the dataset subjects for research applications of the data. Confidentiality/privacy processes and quality control activities undertaken by data custodians were well-regarded. Many respondents included data linkage to additional government datasets in their research. Ease of data access was variable. Some documentation types were well provided and used, but improvement is required for the provision of data quality statements and limitations documentation. Provision of information on participants' informed consent in a dataset is required.

The Analysis of Understanding in Seismic – Resilient Infrastructure Planning in Vocational Student’s Civil Engineering

The analysis of understanding in Seismic-Resilient Infrastructure Planning among vocational students in civil engineering is indispensable for multifaceted reasons. This study employs a questionnaire validation test as a means of data collection, utilizing questionnaires to gather information. Simple random sampling was applied to select respondents from Medan State Polytechnic students in their 5th and 7th semesters. The questionnaire is designed to assess students' knowledge of earthquake-resistant infrastructure planning. The research is structured into three segments, focusing on the understanding of earthquake resistance management, structural earthquake resistance, and infrastructure earthquake resistance. The aspect of management seismic resilience understanding ranges from 3.22% to 9.65%. The highest understanding is observed in the awareness of quality control activities, the fifth assessment (9.65%). The lowest understanding is in reduce errors in the implementation of earthquake-resistant construction, the nineth assessment (3.22%). The aspect of structure seismic resilience understanding ranges from 2.78% to 9.48%. The highest understanding is observed in threaded reinforcement, the fourth assessment (9.48%). The lowest understanding is in earthquake-resistant house construction, the seventh assessment (2.78%). The aspect of infrastructure seismic resilience understanding ranges from 5.57% to 15.83%., The highest understanding is observed in earthquake-resistant foundations, the second assessment (15.83%). The lowest understanding is in post-disaster assessment approach, the fifth assessment (5.57%). These percentages likely represent the level of comprehension or proficiency of students in each respective aspect, with higher percentages indicating a better understanding. It is crucial to analyze these results collectively and over time to identify trends, strengths, and areas for improvement in the seismic resilience education provided to vocational civil engineering students.

Sentinel laboratory compliance with best practices in Burkina Faso's antimicrobial resistance surveillance network.

Standardising procedures is the best way to harmonise and strengthen the quality of laboratory-based antimicrobial resistance surveillance. Since 2018, Burkina Faso has developed and disseminated the national manual of procedures for performing antibiotic susceptibility tests in sentinel laboratories within its national antimicrobial resistance surveillance network. Our study aimed to assess these sentinel laboratories' compliance with good practices for antibiotics susceptibility tests. Four teams evaluated the antimicrobial resistance sentinel sites laboratories throughout Burkina Faso from 19 to 28 September 2022. Eighteen out of 19 sentinel laboratories were evaluated. A four-member technical committee designed and validated the evaluation tool composed of three Microsoft Excel sheets. The evaluation emphasised quality controls for culture media, antibiotic discs and compliance with antimicrobial susceptibility testing procedures by the laboratories. Excel software was used for data recording and graphs and table design. The free R software version 4.2.0 was used for descriptive statistics. An overall score below 80% was considered noncompliance. Most (83.33%) of the sentinel laboratories conducted at least one quality control activity for culture media, and 66.67% conducted at least one quality control activity for antibiotic discs. Over three-quarters (76.47%) of the laboratories were more than 80% compliant with the modified Kirby Bauer antimicrobial susceptibility testing method. The evaluation revealed the noncompliance of sentinel laboratories with the national procedure manual, particularly in the quality control component. This study has provided baseline data on the sentinel laboratories' compliance with the national antimicrobial susceptibility testing procedures manual, particularly in areas performing quality control checks or meeting quality indicators for culture media and antibiotic discs.

Rehabilitation of RC Structure by Using Ferrocement Jacketing

Many structures fail or deteriorate before completion of its intended life span due to poor quality of material used, lack of mix design, poor workmanship, attacked by environmental agencies, etc. Sometimes due to slenderness of column or less reinforcement provided than actual requirements, less depth/thickness provided in flexural members, etc. feels excessive vibration during walking on floor ultimately develops cracks. Strength of such structural elements can be found by using non-destructive tests like Rebound hammer test, ultrasonic pulse velocity test, etc. If strength of existing structural elements is less than desired strength then structural consultant suggested strengthening of structural elements. There are various methods used in strengthening of existing structural elements like pressure grouting, fibre wrapping, chemical treatment, structural steel support, jacketing, etc. But these techniques are very costly and need precise quality control activity. In the present of investigation, strengthening of beam and column elements of a building by ferrocement techniques and steel jacketing were carried out and cost and cost comparison and strength results before and after strengthening are presented. It is observed that the strength og structural by ferrocement technique is cost effective than steel jacketing technique. And also has increase in the strength of RCC elements

Asbestos detection in construction and demolition waste by different classification methods applied to short-wave infrared hyperspectral images

In this study, different multivariate classification methods were applied to hyperspectral images acquired, in the short-wave infrared range (SWIR: 1000–2500 nm), to define and evaluate quality control actions applied to construction and demolition waste (C&DW) flow streams, with particular reference to the detection of hazardous material as asbestos. Three asbestos fibers classes (i.e., amosite, chrysotile and crocidolite) inside asbestos-containing materials (ACM) were investigated. Samples were divided into two groups: calibration and validation datasets. The acquired hyperspectral images were first explored by Principal Component Analysis (PCA). The following multivariate classification methods were selected in order to verify and compare their efficiency and robustness: Hierarchical Partial Least Squares-Discriminant Analysis (Hi-PLSDA), Principal Component Analysis k-Nearest Neighbors (PCA-kNN) and Error Correcting Output Coding with Support Vector Machines (ECOC-SVM). The classification results obtained for the three models were evaluated by prediction maps and the values of performance parameters (Sensitivity and Specificity). Micro-X-ray fluorescence (micro-XRF) maps confirmed the correctness of classification results. The results demonstrate how SWIR-HSI technology, coupled with multivariate analysis modelling, is a promising approach to develop both “off-line” and “online” fast, reliable and robust quality control strategies, finalized to perform a quick assessment of ACM presence.

Potential of fluorescence fingerprints for fish meat authentication: Differences in freshness evaluation in white and dark meat at frozen state.

As dark meat has a faster deterioration rate and its unintentional mixing occurs during processing, it is crucial to know the status and freshness indicators of dark meat to ensure fishery product quality. In this method, fluorescence fingerprints (FFs) was applied as a rapid and noninvasive quality authentication method to determine differences between white and dark meat in the evaluation of freshness indicators at frozen state. Spotted mackerel (Scomber australasicus) fish chunks with different postmortem conditions (0-40h ice stored) were obtained and frozen. A new generation of fluorescence spectrophotometer (F-7100) was used to acquire FFs of the frozen fish chunks (containing white and dark meat). Adenosine triphosphate metabolites and pH were determined in both white and dark meat using their relevant biochemical methods. Higher K-values in dark meat might be attributed to a higher accumulation rate of inosine (HxR) in dark meat than in white meat. The pH decrease rate in white meat was higher than that in dark meat during postmortem ice storage periods of fish. Principal component analysis of FFs spectra demonstrated clear discrimination (PC1+PC2=91.7%) between white and dark meat of frozen fish due to the influence of freshness parameters based on the fluorescence features of fish meat. Furthermore, partial least squares regression validation models revealed that freshness indicators of white meat could be predicted more accurately at the frozen state than those of dark meat. This method could be applied during the processing of fishery products, thereby facilitating quality control activities and making it a promising authentication tool for the fisheries industries.