Quality Attributes Research Articles

Carboxymethyl cellulose based edible nanocomposite coating with tunable functionalities and the application on the preservation of postharvest Satsuma mandarin fruit

This study introduces an innovative carboxymethyl cellulose (CMC)-based edible nanocomposite coating, with two-dimensional layered double hydroxide nanosheets (2D LDH-NSs) and shellac, engineered to address challenges in fruit preservation. The synergistic integration of shellac and LDH-NS into the CMC matrix is strategically designed with tunable functionalities, encompassing wettability, gas barrier, and tensile properties. Our findings reveal that incorporating shellac and LDH-NS significantly improves the coating's wettability on the mandarin fruit surface, thus bolstering its adherence and uniformity, alongside enhancing its water vapor barrier efficacy and influencing the oxygen permeability. The application of this novel edible nanocomposite coating on Satsuma mandarin (Citrus unshiu Marc.) fruits has yielded promising outcomes in prolonging postharvest shelf life while preserving essential quality attributes, including peel surface morphology, weight loss, hardness, color retention, and nutritional values. Our work signifies a significant leap forward for the edible coating technology and bolsters the postharvest preservation of perishable fruits.

In-line porosity and hardness monitoring of tablets by means of optical coherence tomography

In-line monitoring of critical quality attributes (CQAs) during a tableting process is an essential step toward a real-time release strategy. Such CQAs can be the tablet mass, the API content, dissolution, hardness and tensile strength. Since dissolution testing is laborious and time-consuming and cannot be performed in-line, it is desirable to replace dissolution testing with predictive models based on other CQAs that affect the dissolution characteristics, such as the tablet porosity and hardness. Traditionally, porosity is determined offline via gas adsorption methods or other techniques, such as Terahertz spectroscopy or gas in scattering media absorption spectroscopy. Tablet hardness is typically established using a hardness tester. While these destructive tests can readily be performed at-line, they have limited applicability in in-line settings for a high-percentage inspection. Optical coherence tomography (OCT) has recently been proposed as a possible tool for determining quality attributes. This work describes the first application of OCT for the prediction of tablet porosity and hardness. OCT measurements of tablets produced in a ConsiGma 25™ tableting line and a Stylcam 200R compaction simulator in several compaction force settings were performed and correlated with the porosity and hardness. It was demonstrated that OCT can easily be installed in-line and provide real-time information about critical material attributes. These insights confirm the applicability of OCT as a real-time quality control tool and its potential to replace time-consuming and destructive offline measurements.

HOSPITAL SERVICE QUALITY AND CUSTOMER TRUST TOWARDS PATIENT SATISFACTION IN GENERATION MZ

According to Law Number 17 of 2023 of the Republic of Indonesia, health efforts, health resources, and health management are required to improve public health to the highest possible standard. Indonesian hospitals should provide patients with a degree of service excellence as supplied by medical, paramedical, and medical support staff. This research aims to understand, explore, and analyze based on empirically investigating the dimensions or attributes of service quality and evaluate the importance of variance attributes for Gen MZ patients at Hospital B. This quantitative study examines the relationship between service quality and brand trust (independent variable) towards patient satisfaction (dependent variable) in Gen MZ at Hospital B. This research was conducted from January to March 7, 2024; it involved 122 Generation MZ patients using non-probability purposive sampling to represent the population. Result shows that the similar levels of satisfaction and trust between Generations M and Z at Hospital B may be due to the hospital's standardized, high-quality services. This consistency ensures that both generations have comparable experiences. Additionally, Hospital B's effective use of technology, such as hospital apps and online medical information access, meets and exceeds the expectations of both groups.

Agronomic biofortification of tomatoes with iron enhances growth, yield and quality

ABSTRACT Agronomic biofortification with iron (Fe) in tomatoes has emerged as a promising strategy to combat global iron deficiency. Iron is essential for human health and plays a critical role in the growth and development of crops. This study aimed to determine the optimal dose of Fe for tomato biofortification and assess its impact on its growth, yield and quality attributes, particularly the fruit’s Fe content. A greenhouse experiment was conducted using tomato hybrids Sandal and Sahel, applying Fe foliar treatments at concentrations of 0, 1, 3, 6 and 9 mM Fe per plant. The results demonstrated that foliar application of 6 mM Fe significantly enhanced the tomato’s growth, yield and quality, while markedly increasing the fruit’s Fe content to 30.07 and 34.1 mg kg−1 in Sandal and Sahel hybrids, respectively. These values were substantially higher than those of the control treatment with Fe contents of 14.77 and 15.0 mg kg−1, respectively. However, higher doses of Fe (> 6 mM Fe per plant) showed adverse effects on growth, yield, and quality. Foliar application of iron proved an effective and economical solution, readily integrated into commercial tomato production, offering farmers a practical method to produce Fe-biofortified tomatoes and combat iron deficiency-linked malnutrition.

Environmental Quality, Extreme Heat, and Healthcare Expenditures

Although the effects of the environment on human health are well-established, the literature on the relationship between the quality of the environment and expenditures on healthcare is relatively sparse and disjointed. In this study, the Environmental Quality Index developed by the Environmental Protection Agency and heatwave days were compared against per capita Medicare spending at the county level. A general additive model with a Markov Random Field smoothing term was used for the analysis to ensure that spatial dependence did not undermine model results. The Environmental Quality Index was found to hold a statistically significant (p < 0.05), multifaceted nonlinear association with spending, as was the average seasonal maximum heat index. The same was not true of heatwave days, however. In a secondary analysis on the individual domains of the index, the social and built environment components were significantly related to spending, but the air, water, and land domains were not. These results provide initial support for the simultaneous benefits of healthcare financing systems to mitigate some dimensions of poor environmental quality and consistently high air temperatures.

Effective Synthesis of mRNA during In Vitro Transcription with Fewer Impurities Produced.

The remarkable efficacy of COVID-19 vaccines has established mRNA as a highly promising biomedical technology. However, the adequate application of mRNA therapeutics necessitates additional measures to mitigate the inherent immunogenicity, which is predominantly caused by dsRNA. As a byproduct of the in vitro transcription of mRNA, dsRNA was reported to be originated through several distinct mechanisms, including the extension of 3' loop-back hairpins, the extension of hybridized abortive transcripts, and promoter-independent transcription. The intricate mechanisms involved pose a dilemma as the reduction in dsRNA results in a concomitant decrease in other critical quality attributes of mRNA. Here, we demonstrate that the promoter binding motifs of T7 RNA polymerase directly impact the production of promoter-independent transcription-based dsRNA. Specifically, the G753A mutation significantly reduces the formation of dsRNA byproducts, which can further combine with modified nucleotides to enhance the effectiveness of dsRNA mitigation and with previously reported high-integrity mutation K389A to minimize side effects. Accordingly, the present study reports a cost-effective approach to synthesize high-purity, less immunostimulatory mRNA by using an engineered T7 RNA polymerase mutant.

Analytical Performance of a Multiplexed Microarray Assay for Rapid Identification and Quantification of a Multivalent mRNA Vaccine.

mRNA vaccines were highly effective in response to the COVID-19 pandemic, making them an attractive platform to address cancers and other infectious diseases. Many new mRNA vaccines in development are multivalent, which represents a difficulty for the standard assays commonly used to characterize the critical quality attributes of monovalent formulations. Here, we present a multiplexed analytical tool with nucleic acid microarray technology using the VaxArray platform that measures the identity and quantity of mono- and multivalent mixtures of naked mRNA and mRNA encapsulated in lipid nanoparticle formulations in under 2 h without any additional preparation steps, such as extraction or RT-PCR. Using a quadrivalent mixture of encapsulated mRNA constructs that encode for four unique proteins in a vaccine formulation, the VaxArray mRNA assay was demonstrated to be highly specific for each mRNA with sensitivity < 1 µg/mL. The quantification of individual mRNAs within the lipid nanoparticle mixture resulted in a precision of ≤10% RSD and an accuracy of 100 ± 9%.

Spectral reconstruction from RGB image to hyperspectral image: Take the detection of glutamic acid index in beef as an example

The use of spectral reconstruction (SR) to recovery RGB images to full-scene hyperspectral image (HSI) is an important measure to achieve real-time and low-cost HSI applications. Taking the detection of glutamic acid index for 360 beef samples as an example, the feasibility of using 11 state-of-the-art reconstruction algorithms to achieve RGB to HSI in complex food systems was investigated. The multivariate correlation analysis was used to prove that RGB is a projection of three-channel comprehensive coverage wide-band information. The comprehensive quality attributes (PSNR-Params-FLOPS) was proposed to determine the optimal reconstruction model (MST++, MST, MIRNet, and MPRNet). Moreover, SSIM values and t-SNE were introduced to evaluate the consistency of the reconstruction results. Finally, Lightweight Transformer was used to establish the detection models of Raw-HSI, RGB and SR-HSI for the prediction of glutamic acid index for beef. The results showed that the MST++ model exhibited the best performance in SR, with RMSE, PSNR, and SSIM values of 0.015, 36.70, and 0.9253, respectively. Meanwhile, the prediction effect of MST++ (R2P = 0.8422 and RPD = 2.46) reconstructed was close to the Raw-HSI (R2P = 0.8526 and RPD = 2.69). The results provide practical application scenarios and detailed analysis ideas for RGB-to-HSI.

Real-time monitoring of integrated continuous granulation/drying line system “LaVortex®” for the pharmaceutical manufacturing of acetaminophen oral dosage formulations using near-infrared spectroscopy

Granules for tableting were continuously manufactured using a fully flow-type continuous wet-granulation and drying (CGD) line system, “LaVortex®.” The raw material powder containing standard excipients and 28.8 % acetaminophen was mixed with a binder liquid (pure water), continuously wet-granulated, and dried for 600 s under 20 different granulation/drying process conditions, and the process was monitored in real-time using near-infrared (NIR) spectroscopy. Twenty granulation/drying process conditions, varying across three parameters, namely added binding water rate, agitation blades and container rotational rates, and hot drying air flow rate, were applied. Training datasets from NIR spectroscopy stably measured during the CGD process were used to construct calibration models to predict the various critical quality attributes (CQAs) of granules, such as residual moisture content, median particle size, angle of repose, and tablet hardness, using partial least squares regression (PLSR). Optimal calibration models were validated using the NIR spectroscopy test dataset. The actual granule CQA profiles evaluated using the NIR/PLSR method were almost constant up to 600 s at the end of production depending on the critical process parameters (CPPs), except for fluctuations in the initial process. These results indicate that tableting granules with various pharmaceutical properties could be obtained continuously depending on CQAs, such as the rate of water addition. Additionally, changes in CQAs could be continuously monitored by the NIR/PLSR method. Furthermore, CGD granules with various characteristic CQAs can be continuously manufactured by controlling CPPs, such as agitation blades and tube rotation rates in the agitating granulation process and drying air flow rate in the drying process under NIR spectroscopy.

The influence of tangibility, reliability and responsibility on the financial performance of banks with mediating role of customer satisfaction

The study explores the relationship between customer satisfaction and the financial performance of banks, focusing on mediating factors. This study aims to investigate in detail the impact of responsibility, tangibility, and reliability on banks’ financial performance, with a particular emphasis on the mediating function of customer satisfaction. The primary objectives are to analyze how these service quality dimensions influence customer satisfaction and, subsequently, financial outcomes. The research is grounded in the theory that higher levels of customer satisfaction lead to improved financial performance through increased loyalty. Using Employing Partial Least Squares Structural Equation Modelling (PLS-SEM), the study analyzes data collected from commercial bank clients in Kazakhstan over a four-month period, from November 2023 to February 2024. The dataset includes responses from approximately 200 participants, ensuring demographic representation through a stratified random sampling method. Hypotheses regarding customer satisfaction, reliability, responsibility, and tangibility were tested. Findings reveal a significant positive relationship between customer satisfaction and financial performance, indicating that higher satisfaction levels contribute to improved financial outcomes for banks. These findings highlight the multidimensional nature of customer satisfaction and underscore the importance of addressing various factors to enhance financial performance in the banking sector. This study contributes theoretical insights and practical implications for banks aiming to optimize their financial performance through customer-centric strategies.

Evolution of performance in the water and sewage sector in Brazil: a robust directional Benefit-of-the-Doubt assessment of municipalities from Santa Catarina state

AbstractThe water supply and sewage sector (WSS) is essential for promoting health and providing the population with drinking water and the adequate disposal of effluents. Assessing the evolution of performance in WSS allows for highlighting the best and worst results achieved, identifying benchmarks, and pinpointing sources of improvement for water services. Brazil has a large population and immense freshwater reserves that are unevenly distributed throughout the territory. This situation emanates a challenge that requires the efficient management of water resources. This study develops a composite indicator framework based on the robust Benefit-of-the-Doubt (BoD) approach to estimate the performance of municipalities of the Brazilian State of Santa Catarina from 2009 to 2021, considering financial, operational, and quality dimensions associated with the provision of WSS services. Subsequently, the Global Malmquist Index (GMI) is applied to assess the performance evolution of the municipalities over time. The BoD results enable the quantification of the relative contribution of each sub-indicator to the performance score, allowing the assessment of the strengths and weaknesses of each municipality. The GMI results show an average performance loss of 3.3% in Santa Catarina state and considerable variability among municipalities, with scores ranging from losses of 54.2% to gains of 109.3% in the period analysed.

Contextual and psychological factors in using recycled stormwater for residential purposes: a case study from Taiyuan, China

ABSTRACT This paper reviewed the managed aquifer recharge (MAR) practices around the world and explored urban residents' attitudes towards using stormwater recycled through MAR for residential uses in a Chinese socio-cultural context. The exploration was conducted from both contextual and psychological perspectives based on two established theories. The moderating effect of gender on residents' attitudes was tested. The results showed that most respondents supported using recycled stormwater for residential purposes but demonstrated hesitance in using recycled stormwater for uses that present proximity to human contact, which normally requires connecting the water to their house. Regarding the water quality attributes such as the colour, odour, and salt content of recycled stormwater, respondents were more tolerant if the water was used for uses that have limited human contact and less tolerant for uses that have close human contact. Therefore, any future decision to connect recycled stormwater into houses would require careful consideration and investigation as it depends on a range of issues including the proximity to human contact and the quality attributes of the water. Gender was a weak predictor in moderating respondents' attitudes towards using recycled stormwater, which adds to the inconsistent literature.

Data-driven modeling of consumer product satisfaction using an orthogonal arrangement of sound attributes

Sound quality attributes have been proven to be important predictors of customer satisfaction with consumer appliances. The results of several studies indicate that level-based, tonal, and temporal aspects of sound influence the perceived quality of consumer products. The current state-of-the-art of inferring consumer satisfaction with sound attributes is based on the jury test methodology. However, listening-based jury studies fail to capture interaction effects nor study sound samples based on an orthogonal arrangement of sound quality attributes. Therefore, this study aims to develop data-driven models to mathematically relate sound attributes to consumer satisfaction. A baseline sound obtained from the operational noise generated by a fan-powered home appliance was used as a reference sound for researching the importance of sound quality attributes. An orthogonal-designed experiment was conducted to prepare sound samples based on selected sound attributes, including loudness, sharpness, roughness, and prominence ratio. Consumer studies were conducted to measure the product satisfaction of the various sound samples, which were used to train the data-driven model. The data-driven model was shown to accurately predict consumer satisfaction metrics based on sound quality attributes. Therefore, the proposed methods are valuable for evaluating new products within the model inference space without conducting further listening-based jury studies.

Score Disclosure

Abstract We study verifiable disclosure by a seller when the product has multiple quality attributes. We identify an equilibrium in which, for some qualities, the seller discloses its score—the average of the qualities—and does not reveal anything else. This occurs when its score is sufficiently high or when the qualities are sufficiently similar and the score is not too low. Otherwise, the seller fully discloses. While full unraveling is still an equilibrium, it is dominated by this partial score disclosure equilibrium in terms of ex ante as well as ex post profits.

Contributions to a Theoretical Framework for Evaluating the Supply–Demand Matching of Medical Care Facilities in Mega-Cities: Incorporating Location, Scale, and Quality Factors

The rapid urbanization and population growth in mega-cities have led to a significant increase in the demand for medical services, highlighting the critical need for a more efficient alignment between the supply and demand of medical resources. Previous research often focuses on singular factors, such as accessibility or quantity, as the primary criteria for matching medical services, without comprehensively considering the location, scale, and quality factors of medical facilities. Addressing this gap, this study develops a theoretical framework that integrates these three critical factors to assess the supply–demand matching (SDM) of medical care facilities (MCFs) with population needs. This assessment is conducted using geospatial analysis techniques with ArcGIS and Python. The study includes an empirical analysis of 134 streets within the Chongqing municipality. The empirical results reveal significant disparities in the performance of integrated medical care facilities (MCFs), as well as variations across the dimensions of location, scale, and quality. Central districts like Yuzhong demonstrate high levels of accessibility, appropriate scale matching, and satisfactory service quality, whereas rapidly urbanizing peripheral districts such as Yubei suffer from significant mismatches in resource availability and service quality. The theoretical framework contributes to the field of medical care research, and the corresponding empirical findings provide valuable insights for urban planners and policymakers to optimize the allocation of medical resources, improve healthcare accessibility, and enhance service quality across different urban areas.

Quality by Design Approach for the Development of Cariprazine Hydrochloride Loaded Lipid-Based Formulation for Brain Delivery via Intranasal Route.

Cariprazine (CPZ) is a third-generation antipsychotic medication that has been approved for treating schizophrenia. This study aimed to develop a cariprazine-loaded nanostructured lipid carrier (CPZ-NLCs) to prevent first-pass metabolism and improve bioavailability and site-specific delivery from the nose to the brain. The CPZ-NLCs were prepared using melt emulsification. The formulation was optimized using the Box-Behnken design (BBD); where the influence of independent variables on critical quality attributes, such as particle size and entrapment efficiency, was studied. The optimized batch (F6) had a particle size of 173.3 ± 0.6 nm and an entrapment efficiency of 96.1 ± 0.57%, respectively. The in vitro release showed >96% release of CPZ from NLC within 30 min. The optimized formulation's ex vivo studies revealed significantly increased CPZ permeability (>75%) in sheep nasal mucosa compared to the CPZ suspension (~26%). The ciliotoxicity study of the nasal mucosa revealed that the CPZ-NLC formulation did not affect the nasal epithelium. The intranasal administration of the formulation achieved 76.14±6.23 μg/ml concentration in the brain which was significantly higher than the oral CPZ suspension administration (30.46±7.24 μg/ml). The developed formulation was stable for 3 months. The study concluded that the developed CPZ-NLC could significantly improve the bioavailability with quick delivery to the brain.

Smart dimensional quality assessment of embedded steel plates based on images and laser data fusion

Abstract Accurate and efficient positioning is critical to ensuring the dimensional quality assessment of embedded steel plates. However, traditional manual measurement methods struggle to efficiently measure and evaluate these plates. Vision-based measurement methods offer advantages such as high resolution, fast data acquisition, and processing speed, allowing accurate measurement of 2D coordinates. LiDAR can capture highly accurate point clouds, due to the unordered nature of point clouds, processing and analysis require significant computational resources. This paper proposes a method for smart 3D localization of embedded steel plates using image and laser data. (1) We introduce an improved Rectangular Diagonal Constraint Harris (RDC-Harris) corner detection method and achieve subpixel 2D corner detection of embedded plates based on deep learning；(2) Given a calibrated camera-LiDAR, we develop a smart detection algorithm guided by 2D image bounding boxes, achieving 3D corner localization. In indoor testing and engineering applications, this method effectively ensures the dimensional quality of embedded steel plates. Compared to traditional manual inspection, the measurement efficiency reaches 10 minutes per station, with an accuracy of 2.12 mm.

Full-scale application of dimensional quality assessment on precast slabs: A scan planning approach

Ensuring precise dimensional quality of individual precast concrete (PC) slabs is crucial to guarantee smooth assembly at construction sites. Although many studies have been conducted to increase the accuracy of dimensional quality assessment (DQA), there has been few studies that systematically determine best locations where accuracy is maximized and scanning time is minimized. To tackle this issue, this study presents a scan planning technique for rapid and accurate DQA of PC slabs. A two-scan strategy along the longitudinal direction is proposed as PC slabs are lengthy to avoid the effect of large incident angle. A series of experimental tests are conducted and the results show a DQA accuracy of 3.1 mm within 582 s for a full-scale slab with 12-m long, outperforming the previous study by 4.6 %. The findings of this study are expected to be useful for accurate and rapid DQA of PC slabs.

The Potential of Using Generative AI/NLP to Identify and Analyse Critical Incidents in a Critical Incident Reporting System (CIRS): A Feasibility Case-Control Study.

To enhance patient safety in healthcare, it is crucial to address the underreporting of issues in Critical Incident Reporting Systems (CIRSs). This study aims to evaluate the effectiveness of generative Artificial Intelligence and Natural Language Processing (AI/NLP) in reviewing CIRS cases by comparing its performance with human reviewers and categorising these cases into relevant topics. A case-control feasibility study was conducted using CIRS cases from the German CIRS-Anaesthesiology subsystem. Each case was reviewed by a human expert and by an AI/NLP model (ChatGPT-3.5). Two CIRS experts blindly assessed these reviews, rating them on linguistic quality, recognisable expertise, logical derivability, and overall quality using six-point Likert scales. On average, the CIRS experts correctly classified 80% of human CIRS reviews as created by a human and misclassified 45.8% of AI reviews as written by a human. Ratings on a scale of 1 (very good) to 6 (failed) revealed a comparable performance between human- and AI-generated reviews across the dimensions of linguistic expression (p = 0.39), recognisable expertise (p = 0.89), logical derivability (p = 0.84), and overall quality (p = 0.87). The AI model was able to categorise the cases into relevant topics independently. This feasibility study demonstrates the potential of generative AI/NLP in analysing and categorising cases from the CIRS. This could have implications for improving incident reporting in healthcare. Therefore, additional research is required to verify and expand upon these discoveries.

Continuous Process Verification 4.0 application in upstream: adaptiveness implementation managed by AI in the hypoxic bioprocess of the Pichia pastoris cell factory.

The experimental approach developed in this research demonstrated how the cloud, the Internet of Things (IoT), edge computing, and Artificial Intelligence (AI), considered key technologies in Industry 4.0, provide the expected horizon for adaptive vision in Continued Process Verification (CPV), the final stage of Process Validation (PV). Pichia pastoris producing Candida rugosa lipase 1 under the regulation of the constitutive GAP promoter was selected as an experimental bioprocess. The bioprocess worked under hypoxic conditions in carbon-limited fed-batch cultures through a physiological control based on the respiratory quotient (RQ). In this novel bioprocess, a digital twin (DT) was built and successfully tested. The implementation of online sensors worked as a bridge between the microorganism and AI models, to provide predictions from the edge and the cloud. AI models emulated the metabolism of Pichia based on critical process parameters and actionable factors to achieve the expected quality attributes. This innovative AI-aided Adaptive-Proportional Control strategy (AI-APC) improved the reproducibility comparing to a Manual-Heuristic Control strategy (MHC), showing better performance than the Boolean-Logic-Controller (BLC) tested. The accuracy, indicated by the Mean Relative Error (MRE), was for the AI-APC lower than 4%, better than the obtained for MHC (10%) and BLC (5%). Moreover, in terms of precision, the same trend was observed when comparing the Root Mean Square Deviation (RMSD) values, becoming lower as the complexity of the controller increases. The successful automatic real time control of the bioprocess orchestrated by AI models proved the 4.0 capabilities brought by the adaptive concept and its validity in biopharmaceutical upstream operations.