Improve Quality Control Research Articles

Improving Quality Control Measures in the Dairy Industry: Utilizing Dynamics of Dirt Resistance Factor (Rd) Value and Time of Effective Bacterial Contamination Prevention

The number of customer complaints related to decreased quality of dairy products was the background of this study. Objective: (i) examined the effect of the highest dirt resistance factor (Rd) on the number of bacterial contaminants in finished goods; (ii) examine the effect of time on the growth of bacterial contaminants in the fouling layer of UHT pipes when not in operation. The research method was based on the mathematical derivation of the formation process of Rd in the form of an equation. Bacterial species were analyzed using the Operation Taxonomic Unit (OTU) with 16S rRNA. The ANOVA test was used to determine the mean value, standard deviation and the Tukey LSD post hoc test to see the difference in heat balance and bacterial growth. Findings: (i) During the UHT sterilization process, the Rd value (0.0205 h.Ft2.F.Btu-1) had an impact on total bacterial contamination >20 Cfu.mL-1; (ii) In the event of engine damage or malfunction of the heater on the UHT. Time had a significant effect (p<0.05) on the number of lactic acid bacteria in the fouling layer in UHT pipes. Conclusion: The study recommends a sanitation schedule every 110 minutes (± 2 hours) or Rd value around 0.0205 h.Ft2.F.Btu-1.

A single-step microdistillation procedure for the determination of total vicinal diketones in beers

Vicinal diketones (VDK) strongly affect the quality of beers, as they are responsible for off-flavors and deterioration markers, which are recognized as safe for humans when ingested but are toxic when inhaled. Thus, their determination is required in both the production process and the final beverage. A novel approach for determining the total VDK content in beers using microdistillation as a simple approach for sample pretreatment is proposed. The lab-made microdistillation apparatus consists of a capped Falcon® tube with the sample at the bottom and the acceptor solution inside a suspended Eppendorf® tube. The sample is heated (90 °C, 20 min) to volatilize the analytes, which are collected from the headspace by an acceptor-derivatizing solution (o-phenylenediamine in acid medium), and the product is determined by ultraviolet spectrophotometry. Under conditions optimized by experimental design, a linear response was achieved from 0.05 to 1.00 mg L-1 diacetyl, with a coefficient of variation (n = 11) and limit of detection (95 % confidence level) estimated at 4.3 % and 0.01 mg L-1 diacetyl, respectively. The procedure requires as low as 40 μg of o-phenylenediamine, 1.7 μL of 37 % (v/v) hydrochloric acid, and 5000 μL of sample, generating only 5400 μL of waste per determination. It allows for the simultaneous analysis of 10 samples, a capability not previously reported in the literature. Results obtained for Ale and Lager beers using the proposed and reference procedures agreed at a 95 % confidence level. Therefore, the current proposal is a reliable and environmentally friendly alternative for the rapid determination of VDKs in beer, contributing to improved quality control in both the process and final products of the brewing industry.

Advanced analysis and construction techniques for long-span spatial structures in steel engineering

This paper explores advanced analysis methods and construction techniques for long-span spatial structures in steel engineering. It delves into the principles of the Direct Analysis Method (DAM), emphasizing equilibrium, compatibility, plasticity, and stability, as well as load path and redundancy considerations. The DAM provides a robust framework for analyzing complex steel structures, ensuring stability, resilience, and efficiency. Furthermore, the paper discusses modeling techniques, including Finite Element Analysis (FEA), dynamic analysis, and nonlinear analysis, highlighting their significance in optimizing design solutions and predicting structural behavior under diverse loading conditions. Practical considerations in material selection, connection design, and construction are addressed, focusing on enhancing performance, durability, and constructability. Prefabrication and modular construction techniques are explored as effective strategies for accelerating project schedules, improving quality control, and enhancing site safety. Through a comprehensive review of literature and case studies, this paper provides valuable insights for engineers and researchers involved in the design and construction of long-span spatial structures in steel engineering.

Applying Blockchain, Causal Loop Diagrams, and the Analytical Hierarchy Process to Enhance Fifth-Generation Ceramic Antenna Manufacturing: A Technology–Organization–Environment Framework Approach

This study used a technology–organization–environment (TOE) framework as the primary analytical tool to explore the burgeoning capabilities of blockchain technology in the area of 5G ceramic antenna development. A causal loop diagram (CLD) analysis is used to further clarify the complex dynamics and feedback mechanisms, and the impact of blockchain on the design, production, and deployment phases of ceramic antennas, which play a pivotal role in the development of 5G communications, is studied. We found that blockchain’s unique features, including its immutable ledger and decentralized architecture, have the potential to significantly improve the transparency, security, and efficiency of the ceramic antenna manufacturing process. Technology (T), organization (O), and environment (E) were used as the top factors, and the subfactors of TOE were selected and analyzed using the Analytic Hierarchy Process (AHP) by CLD. The AHP analysis was used to evaluate the relative importance of various internal and external factors affecting the adoption of blockchain technology. The integration of the TOE framework with AHP and CLD provides a comprehensive analytical tool that enhances the understanding of the complex dynamics in the 5G ceramic antenna manufacturing process. This methodological approach not only clarifies the interactions between technological, organizational, and environmental factors but also facilitates strategic decision-making through a structured evaluation of these factors. The AHP analysis showed that technical factors are the most important in the TOE analysis of 5G ceramic antenna manufacturing, with a weight of 0.427, which indicates the important role of technical factors in the development of ceramic antenna production. In addition, environmental and organizational factors were given weights of 0.302 and 0.271, respectively, confirming the importance of technological innovation and internal process optimization. In the subfactor of Technology (T), ‘Blockchain Technology’ has the highest ranking among the subfactors, with a global weight value of 0.129, emphasizing the importance of blockchain technology. This study explored the technical and organizational complexities of introducing blockchain technology into the 5G ceramic antenna manufacturing industry and, through an in-depth investigation of the potential benefits of such integration, it aims to propose new approaches to improve quality control and manufacturing efficiency. The research findings aim to contribute to the sustainable growth of the telecommunications industry by providing strategic recommendations for the application of blockchain technology in the production of 5G ceramic antennas.

Rapid chemical characterization and pharmacological mechanism of Fining Granules in the treatment of chronic bronchitis based on UHPLC–Q-exactive orbitrap mass spectrometer and network pharmacology

BackgroundSenecio cannabifolius Less. is a perennial herb belonging to the Compositae family that has been used in traditional medicine as an antitussive and expectorant for treating chronic bronchitis and acute respiratory infections. Traditionally, Feining Granules are prepared from water extracts of the raw plant material. However, the chemical composition and pharmacological mechanisms of Feining Granules have not been thoroughly investigated. MethodsA systematic strategy for the rapid detection and identification of the constituents of Feining Granules was developed using ultrahigh-performance liquid chromatography–quadrupole-exactive orbitrap mass spectrometry (MS) with parallel reaction monitoring. ResultsOverall, 162 compounds, including flavonoids, alkaloids, organic acids, and others, were identified unambiguously and tentatively by comparing the retention times and MS fragmentation with reference standards and literature data. Ninety-nine of these were reported for the first time to the best of our knowledge. Network pharmacology suggests that Feining Granules can be used to treat chronic bronchitis as they contain active components associated with the ALB, VEGFA, and SRC target genes influenced by HIF-1, VEGF, and other signaling pathways. ConclusionThese results provide information that can help understand the effective substances of S. cannabifolius Less. and improve quality control.

Physics-Informed Approximation of Internal Thermal History for Surface Deformation Predictions in Wire Arc Directed Energy Deposition

Abstract This work presents a physics-informed fusion methodology for deformation detection using multi-sensor thermal data. A challenge with additive manufacturing (AM) is that abnormalities commonly occur due to rapid changes in the thermal gradient. Different non-destructive in-situ thermal sensors capture parts of the thermal history but are limited by the visible temperature spectrum and sensor field of view of the fabrication process. Various sensors mitigate problems with the loss of thermal history information; however, it brings forth challenges with integrating different data streams and the need to interpolate the internal thermal history. This study develops a thermal data-informed heat flux methodology that fills the gap in fusing numerical temperature approximation with data-driven knowledge of the surface of additive manufactured components. First, this study fuses infrared (IR) thermal data complexities during the AM process with the Goldak double ellipsoidal heat flux to model the energy input into the component. Second, a thermal physics-informed model input (PIMI) is created with thermal data-informed heat flux to capture internal thermal history. Lastly, a regression convolutional neural network (CNN) captures the relationship between the three-dimensional thermal gradient and the resulting surface deformation. The rapid thermal gradient formation and identification of deformation is a key step toward using thermal history data and machine learning to improve quality control in AM. The proposed surface deformation detection model achieved an mean squared error of 1.14 mm and an R2 of 0.89 in the case study when fabricating thin-walled structures.

Electronic Technologies for Quality Control in the Biscuit Manufacturing Process

By 2030, the biscuit industry may go global due to advancements in electronic tools like eNose, eTongue, and eVision. This shift is governed by precision, productiveness, and regulatory compliance. Ultimately, the automation increase is driven by this consequence. This article will critically look at the issues and benefits arising within the biscuit production field after the shift towards the use of electronic control systems. It analyses the present situation and figures out the ineffectiveness on the part of conventional tools in solving the problem as it currently exists and shows how electronic instruments can be better in aiding visual and sensory inspections. While there have been remarkable achievements, these are persisting, of course, and they include high investment costs, specific skills requirements, and less flexibility when adapting to different production conditions. Without thorough research and development, the challenges in the production of the electronic control systems will still stand and no technology will be created to resolve the problems of the system. This study further reaffirms the need for the invention of modern and improved quality control processes for biscuit manufacturing plants. Through identifying previous methods and approaches and, the advantageous features of each, as well as highlighting shortcomings of current quality control strategies, this paper serves as an effective driving force for the future evolution and further improvement of quality control practices during biscuit production. Comprehensive product evaluation is attended to by employed approaches that analyse future benefits and opportunities as well as drawbacks and risks of the application of electronic quality control systems in the biscuit industry.

An inversion-based clustering approach for complex clusters

BackgroundThe choice of an appropriate similarity measure plays a pivotal role in the effectiveness of clustering algorithms. However, many conventional measures rely solely on feature values to evaluate the similarity between objects to be clustered. Furthermore, the assumption of feature independence, while valid in certain scenarios, does not hold true for all real-world problems. Hence, considering alternative similarity measures that account for inter-dependencies among features can enhance the effectiveness of clustering in various applications.MethodsIn this paper, we present the Inv measure, a novel similarity measure founded on the concept of inversion. The Inv measure considers the significance of features, the values of all object features, and the feature values of other objects, leading to a comprehensive and precise evaluation of similarity. To assess the performance of our proposed clustering approach that incorporates the Inv measure, we evaluate it on simulated data using the adjusted Rand index.ResultsThe simulation results strongly indicate that inversion-based clustering outperforms other methods in scenarios where clusters are complex, i.e., apparently highly overlapped. This showcases the practicality and effectiveness of the proposed approach, making it a valuable choice for applications that involve complex clusters across various domains.ConclusionsThe inversion-based clustering approach may hold significant value in the healthcare industry, offering possible benefits in tasks like hospital ranking, treatment improvement, and high-risk patient identification. In social media analysis, it may prove valuable for trend detection, sentiment analysis, and user profiling. E-commerce may be able to utilize the approach for product recommendation and customer segmentation. The manufacturing sector may benefit from improved quality control, process optimization, and predictive maintenance. Additionally, the approach may be applied to traffic management and fleet optimization in the transportation domain. Its versatility and effectiveness make it a promising solution for diverse fields, providing valuable insights and optimization opportunities for complex and dynamic data analysis tasks.

459. Reducing Errors in Clinical Trials: The Importance of Acknowledging Human Error and Improving Quality Control

459. Reducing Errors in Clinical Trials: The Importance of Acknowledging Human Error and Improving Quality Control

A STUDY ON QUALITY CONTROL AND WASTE MANAGEMENT PROCESS IN MODERN BREAD COMPANY

The modern bread industry faces challenges in maintaining stringent quality control standards while effectively managing waste. This study aims to explore and propose strategies to enhance quality control and waste management processes in modern bread companies, contributing to their sustainability and competitiveness. Utilizing a mixed-methods approach, data will be collected through surveys, interviews, and case studies from multiple modern bread companies. The research will investigate current quality control practices, waste management systems, and their associated challenges. Additionally, the study will identify industry best practices and technological innovations in quality control and waste management. The findings will inform the development of a comprehensive framework for improving quality control and waste management processes tailored to the specific needs of modern bread companies. This framework will encompass strategies for optimizing production processes, implementing advanced quality control measures, and adopting sustainable waste management practices. Moreover, the study will address the integration of digital technologies and data analytics to enhance monitoring and decision-making in quality control and waste management. The proposed framework aims to enhance product quality, reduce waste generation, and minimize environmental impact, thereby contributing to the overall sustainability and profitability of modern bread companies. The research outcomes will provide valuable insights and actionable recommendations for industry practitioners, policymakers, and stakeholders involved in the bread manufacturing sector. Keywords: Quality Control, Waste Management, Bread Industry, Sustainability, Digital Technologies, Production Optimization, Environmental Impact, Competitiveness.

State market surveillance of non-food products in Ukraine: analysis of the decision of the Constitutional Court of Ukraine № 9-r(ii)/2023 dated November 1, 2023 in case № 3-53/2022(126/22)

The article analyzes the problem of state market supervision of non-food products in Ukraine. Problematic aspects of administrative and economic responsibility for putting into circulation products that do not meet the established requirements are considered. The decision of the Constitutional Court of Ukraine No 9-р(ii)/2023 of November 1, 2023 in case No 3-53/2022(126/22) and the separate opinion of the judge of the Constitutional Court of Ukraine G.V. Yurovskaya were analyzed on this issue. It is noted that strengthening consumer protection and improving quality control and safety of products and services are important tasks for any country, including Ukraine. And the creation of an effective legislative mechanism that guarantees consumer rights and determines the responsibility of enterprises for the quality and safety of products stimulates the development of entrepreneurship and competitiveness in the market, which in turn helps to improve the investment climate and ensures a balanced development of the economy. The process of improving legislation on the protection of consumer rights is considered. It has been proven that legislative changes in this area were aimed at reducing corruption risks in the field of monitoring compliance with requirements for the quality and safety of products and services, and the increase in fines for product distributors who did not provide the necessary documentation for supplier identification was aimed at creating economic conditions at which it will be unprofitable to trade products without proper documents. Attention has been drawn to the possibility of establishing absolutely defined and (or) non-alternative sanctions in acts of public legislation in the case when the subject of law enforcement is a government body other than a court. A balance between clarity of sanctions and flexibility in their application has been proven to help ensure fairness and efficiency of the legal system.

PROBLEMATIC ASPECTS OF DETERMINING FIRE PROTECTION OF WOOD

Annually, fires inflict huge losses to both business entities of various forms of ownership and the state overall. According to analytical data for nine months of 2023, 2212 fires occurred in Ukraine at objects of different forms of ownership subject to state supervision (control) in technogenic and fire safety. Many researchers confirm that fire protection of wood is an effective prophylactic measure. However, there are significant factors influencing the reduction of its efficiency directly and also factors that do not affect the efficiency of fire protection directly but provide an objective determination of the quality of fire protection. One of the factors in objectively determining the quality of fire protection is verifying the fire protection compliance. This study aims to determine the causes and patterns of improper fire protection of wooden building structures with fire-retardant solutions (lower than stated in the manufacturer’s regulations). The analysis of recent research and publications shows that the issue of verifying the compliance of fire protection of wooden structures directly after the works in Ukraine has not been studied. Many modern fire protection solutions on the Ukrainian market require improved quality control methods. The existent system of verification of the compliance of fire protection has substantial defects and does not give a possibility to define objectively the quality of fire protection. Precise terminology is absent in normative acts, the methods described for verifying fire protection are not up-to-date, and the regulatory documents for fireproof solutions, in most cases, do not contain the necessary information for quality control. Improvement of verification of the compliance of fire protection of the exploited wood is a necessity at all stages, beginning from determining correct terminology and actualisation of the Rules of fire protection to developing effective methods of verification taking into account the features of modern fireproof solutions. Keywords: fire protection of wood, fire protection compliance verification, fire protection rules, wood impregnation.

Investigation into the state of cure of elastomers through nanoindentation

A novel nanoindentation procedure was developed for measuring the mechanical properties of elastomers as they exhibit surface tackiness. A small dynamic load was superimposed to a larger static deformation after a dwell time for allowing stress relaxation. The outcomes of measurements on a fully crosslinked filled acrylonitrile butadiene rubber (NBR) were analyzed to verify the reliability of this procedure. This method was then employed to investigate the mechanical properties of the same elastomer cured at different temperatures and times by injection molding. As expected, a change from viscoplastic to viscoelastic behavior due to the formation of chemical crosslinks over curing time was found, and mechanical properties plateaus were reached more rapidly at higher manufacturing temperatures. The results were then compared with compression set data: similar trends were detected for the loss factor and the compression set, both decreasing down to a plateau level. Overall, the proposed method demonstrated the ability to recognize undercured regions in elastomer samples - particularly through the determination of the loss factor (tanδ) - and may represent a new tool for improving quality control for the rubber industry.

Identification of supply chain risks in the tobacco products industry in Pasuruan Regency using the supply chain operations reference (SCOR) and house of risk (HoR) model approaches

Introduction: This research aims to identify types of risks and sources of risks, analyze risk priority levels, and formulate mitigation strategies for the tobacco products industry supply chain in Pasuruan Regency. Methods: This research was conducted at the tobacco products industry PT. XZ in Pasuruan Regency. Respondents focused on company managers (focal firms), namely product development, raw material management, research and development pilot plant and tobacco clue management who knew about supply chain risks. Supply chain network integration uses a snowball method approach. Data collection methods use primary and secondary data. At the interview stage, the Delphi method was used to identify risk events and risk sources. Furthermore, the results of the interview were identified using the Supply Chain Operation Reverence (SCOR) and House of Risk (HoR) models. Results: There are 39 risk events and risk agents in the IHT in Pasuruan Regency. There are eight risk priority levels for tobacco supply chain risk agents using the SCOR approach and the Pareto diagram, namely workers not paying attention, problems with machines, high rainfall/high rainfall, production machines need to be repaired, workers' skills are not good, production machines are old, handling bad goods, and errors in the machine. Conclusion: The results of the IHT supply chain risk mitigation strategy formulation are tightening the use of work SOPs, checking production machines regularly, strengthening information between agents and factories, checking machines every 4 hours, conducting worker training, using Google Maps technology in delivering goods, cleaning machines, maintaining product quality, drying/air-drying tobacco leaves, improving quality control during transactions with farmers, and increasing coordination with the Government.

Hi-C metagenomics facilitate comparative genome analysis of bacteria and yeast from spontaneous beer and cider

Sequence-based analysis of fermented foods and beverages' microbiomes offers insights into their impact on taste and consumer health. High-throughput metagenomics provide detailed taxonomic and functional community profiling, but bacterial and yeast genome reconstruction and mobile genetic elements tracking are to be improved.We established a pipeline for exploring fermented foods microbiomes using metagenomics coupled with chromosome conformation capture (Hi-C metagenomics). The approach was applied to analyze a collection of spontaneously fermented beers and ciders (n = 12). The Hi-C reads were used to reconstruct the metagenome-assembled genomes (MAGs) of bacteria and yeasts facilitating subsequent comparative genomic analysis, assembly scaffolding and exploration of “plasmid-bacteria” links. For a subset of beverages, yeasts were isolated and characterized phenotypically.The reconstructed Hi-C MAGs primarily belonged to the Lactobacillaceae family in beers, along with Acetobacteraceae and Enterobacteriaceae in ciders, exhibiting improved quality compared to conventional metagenomic MAGs. Comparative genomic analysis of Lactobacillaceae Hi-C MAGs revealed clustering by niche and suggested genetic determinants of survival and probiotic potential. For Pediococcus damnosus, Hi-C-based networks of contigs enabled linking bacteria with plasmids. Analyzing phylogeny and accessory genes in the context of known reference genomes offered insights into the niche specialization of beer lactobacilli. The subspecies-level diversity of cider Tatumella spp. was disentangled using a Hi-C-based graph. We obtained highly complete yeast Hi-C MAGs primarily represented by Brettanomyces and Saccharomyces, with Hi-C-facilitated chromosome-level genome assembly for the former.Utilizing Hi-C metagenomics to unravel the genomic content of individual species can provide a deeper understanding of the ecological interactions within the food microbiome, aid in bioprospecting beneficial microorganisms, improving quality control and improving innovative fermented products.

Abstract 7024: Development of quality control methods for reliable NGS measurement of methylation in cfDNA

Abstract Background and Purpose: Reliable measurement of circulating free genomic DNA (cfDNA) methylation patterns promises a means for cancer early detection as well as treatment response. Use of Next Generation Sequencing (NGS) methods to measure the cfDNA methylome across a large number of potentially methylated CpG sites may enable earlier detection by overcoming stochastic sampling associated with the small specimens obtainable by a blood draw. Wide-spread adoption of these methods for clinical diagnostic applications will be facilitated through improved quality controls that increase reliability. The goal of this study is to assess the performance of the SNAQ-SEQ™ method as a means to establish a limit of detection (LOD) for measurement of methylation at each targeted CpG site. For this purpose, we used test materials that were developed by the National Institute for Standards and Technology (NIST) to mimic methylated cfDNA. Methods: NIST test materials were formulated by physically shearing cell line gDNA then subjecting it to size separation to mimic a size distribution similar to that observed in cfDNA, then mixing sheared DNA in its “native” state of methylation with sheared DNA that was in vitro methylated. Non-sheared NIST test materials also were assessed in these studies. Synthetic spike-in internal standards (IS) were combined with NIST test materials and the combined samples were bisulfite converted, then subjected to PCR-amplicon library preparation. Libraries were sequenced on an Illumina MiSeq instrument and bioinformatic analysis was conducted using the Qiagen CLC Workbench. Results and Conclusions: In initial testing of an off-the-shelf IS for a region of the SOX2 gene, average methylation (preserved C) across 14 targeted CpG sites was 16.4% (0.5%-50%) in the “native” NIST non-sheared sample. This was consistent with the 11.6% methylation across all of SOX2 measured by the NIST. In contrast, in IS corresponding to the targeted SOX2 region the average preserved C was 0.32% (0.03%-0.5%). Use of synthetic internal standards enabled determination of LOD for each individual methylated site, controlling for all known sources of technical error, including inefficient bisulfite conversion, nucleotide substitution error, and alignment error. Studies are now underway that use the NIST test materials to measure methylation at five targets known to be altered in cfDNA from lung cancer subjects, SOX2, CDO1, TAC1, SOX17, and HOXA7. Citation Format: James C. Willey, Erin L. Crawford, Daniel J. Craig, Thomas M. Morrison, Hua-Jun He, James G. Herman. Development of quality control methods for reliable NGS measurement of methylation in cfDNA [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 7024.

Blending access-based services and triadic frameworks: an empirical evaluation of Packaging-as-a-Service

PurposeRecently emerged Packaging-as-a-Service (PaaS) systems adopt aspects of access-based services and triadic frameworks, which have typically been treated as conceptually separate. The purpose of this paper is to investigate the implications of blending the two in what we call “access-based triadic systems,” by empirically evaluating intentions to adopt PaaS systems for takeaway food among restaurants and consumers.Design/methodology/approachWe derived relevant attributes of PaaS systems from a qualitative pre-study with restaurants and consumers. Next, we conducted two factorial survey experiments with restaurants (N = 176) and consumers (N = 245) in Germany to quantitatively test the effects of those system attributes on their adoption intentions.FindingsThis paper highlights that the role of access-based triadic system providers as both the owners of shared assets and the operators of a triadic system is associated with a novel set of challenges and opportunities: System providers need to attract a critical mass of business and end customers while balancing asset protection and system complexity. At the same time, asset ownership introduces opportunities for improved quality control and differentiation from competition.Originality/valueConceptually, this paper extends research on access-based services and triadic frameworks by describing an unexplored hybrid form of non-ownership consumption we call “access-based triadic systems.” Empirically, this paper addresses the need to account for the demands of two distinct target groups in triadic systems and demonstrates how factorial survey experiments can be leveraged in this field.

Transforming Big Data into AI-ready data for nutrition and obesity research.

Big Data are increasingly used in obesity and nutrition research to gain new insights and derive personalized guidance; however, this data in raw form are often not usable. Substantial preprocessing, which requires machine learning (ML), human judgment, and specialized software, is required to transform Big Data into artificial intelligence (AI)- and ML-ready data. These preprocessing steps are the most complex part of the entire modeling pipeline. Understanding the complexity of these steps by the end user is critical for reducing misunderstanding, faulty interpretation, and erroneous downstream conclusions. We reviewed three popular obesity/nutrition Big Data sources: microbiome, metabolomics, and accelerometry. The preprocessing pipelines, specialized software, challenges, and how decisions impact final AI- and ML-ready products were detailed. Opportunities for advances to improve quality control, speed of preprocessing, and intelligent end user consumption were presented. Big Data have the exciting potential for identifying new modifiable factors that impact obesity research. However, to ensure accurate interpretation of conclusions arising from Big Data, the choices involved in preparing AI- and ML-ready data need to be transparent to investigators and clinicians relying on the conclusions.

Advanced Computer Vision and AI Techniques for Nano-Scale Quality Control in Aerospace Manufacturing

This paper examines the integration of advanced computer vision (CV) techniques and Artificial Intelligence (AI) algorithms to improve quality control (QC) for nano-scale manufacturing processes in the space industry. As nanotechnology is regularly used in the space industry for manufacturing electromechanical components such as NEMS (Nanoelectromechanical Systems), solar panels, and energy storage devices, it's becoming increasingly important to detect defects or imperfections in one of those systems to prevent the loss of life and a costly catastrophe. In order to help mediate this issue, this paper will discuss the methods and processes that can be implemented to capture and analyze nano-scale images and data in order to detect possible flaws in the components.

Development of regional pharmacy intravenous admixture services data reporting and analysis platform for enhanced quality control ability

BackgroundPharmacy intravenous admixture service (PIVAS) center has emerged as an important department of hospitals as it can improve occupational protection and ensure the safety and effectiveness of intravenous infusions. However, there is little research on the standardized capability and risk evaluation of PIVAS by using modern information technology. In this research, we established Regional Pharmacy Intravenous Admixture Services Data Reporting and Analysis Platform (RPDRAP) to improve quality control ability for PIVAS management. RPDRAP including evaluation matrix for quality control monitoring. The construction of platform is based on guidelines for the Construction and Management of PIVAS and management specifications of PIVAS in China.MethodsRPDRAP was established in 2018. This platform comprises a data collection system and a data analysis system. The data collection system consists of 67 data items. Data collection relied on online platforms through data acquisition module. The collected data were analyzed using a model with 20 indicators within the data analysis system. Fifteen hospitals, public comprehensive healthcare facilities with more than 500 beds, participated in the platform’s application evaluation.ResultsThe study revealed significant differences in PIVAS total score, supervisors, and workload between 2020 and 2022. The platform’s application results demonstrated improvements in personnel management, work efficiency, and infection control within these PIVAS. Although statistical significance was observed in only 8 out of the 25 items, most of the scores showed an increase, with a small portion remaining unchanged and no decline in scores.ConclusionsThis platform can be recommended for PIVAS homogeneous and regional efficient management. The use of this platform not only improves the quality control ability of PIVAS but also enables the management department to quickly grasp the current situation and characteristics of each PIVAS through standardized data collection and analysis.