Improved Nursing Workload by Introducing a Traceability System to Manage Medical Materials.

This paper reports a case study in which an improvement in nursing work was achieved through the introduction of a traceability system compatible with radio-frequency identification (RFID) and bar codes for the management of medical materials. In verifying the RFID-based system in an operating room, the work time was reduced to approximately one-tenth of that of barcode reading. In the catheterization laboratory, a system consisting of a cartel management system utilizing bar codes and an RFID-compatible inventory management cabinet was introduced. The system eliminates the need to cut and paste packages onto vouchers after the cases are completed and digitizes the data sent to the medical affairs department for secure billing. We are implementing this system at many facilities, and, in addition to improving the work of nurses, we are taking new steps to improve hospital management through data linkage.

Blockchain-enabled architecture for lead acid battery circularity.

Widespread use of lead acid batteries (LABs) is resulting in the generation of million tons of battery waste, globally. LAB waste contains critical and hazardous materials, which have detrimental effects on the environment and human health. In recent times, recycling of the LABs has become efficient but the collection of batteries in developing countries is not efficient, which led to the non-professional treatment and recycling of these batteries in the informal sector. This paper proposes a blockchain-enabled architecture for LAB circularity, which ensures authentic, traceable and transparent system for collection and treatment of batteries. The stakeholders-battery manufacturers, distributors, retailers, users, and validators (governments, domain experts, third party experts, etc.)-are integrated in the circular loop through a blockchain network. A mobile application user interface is provided to all the stakeholders for the ease of adoption. The batteries manufactured and supplied in a geographical region as well as the recycled materials at the battery end-of-life are traced authentically. This architecture is expected to be useful for the battery manufacturers to improve their extended producer responsibility and support responsible consumption and production.

Comparative evaluating laser ionization and iKnife coupled with rapid evaporative ionization mass spectrometry and machine learning for geographical authentication of Larimichthys crocea.

Larimichthys crocea (LYC) holds significant economic value as a marine fish species. However, inaccuracies in labeling its origin can adversely affect consumer interests. Herein, a laser assisted rapid evaporative ionization mass spectrometry (LA-REIMS) and machine learning (ML) was developed for geographical authentication. When compared to iKnife, the LA demonstrated to be superior owing to reduced thermal damage to sample tissue, enhanced automation, and ease of use. Analysis of LYC from six distinct geographical origins across China revealed a total of 798 ions, which were then subjected to six classifiers to establish ML models. Following hyperparameter optimization and feature engineering, the Chi2(15%)-KNN model exhibited the highest training and testing accuracy, achieving 98.4 ± 0.9% and 98.5 ± 1.4%, respectively. This LA-REIMS/ML methodology offers a rapid, accurate, and intelligent solution for tracing the origin of LYC, thereby providing valuable technical support for the establishment of traceability systems in the aquatic product industry.

Mass spectrometry in measurement of thyroid biomarkers.

In 2022, the number of patients with thyroid disease in China exceeded 200 million (10 million with hyperthyroidism, 90 million with hypothyroidism, and 100 million with other thyroid disease such as goiter, thyroid nodules, and thyroid cancer). Well-established markers include FT3, FT4, TT3, TT4, and TSH tested by a number of immunoassay methods. This approach is based on the primary binding of antigen with antibody and a subsequent secondary chemical reaction that provides an indirect measure. The use of traceable standards for quantitation remains an important factor to ensure inter-assay reliability and precision. Recently, mass spectrometry (MS) has received considerable attention as an analytic tool due to high resolution and quantitative accuracy. In addition, MS allows for sensitive determination of low-abundance markers making it ideal for development of traceable standards. Furthermore, this technology will allow for the development of highly accurate thyroid biomarker assays to facilitate diagnosis, enable early treatment and improve outcomes. Herein, we provide a systematic review and summary of MS in enhancing the analysis of thyroid biomarkers.

What the fish? Tracing the geographical origin of fish using NIR spectroscopy.

Food authentication is a growing concern with rising complexities of the food supply network, with fish being an easy target of food fraud. In this regard, NIR spectroscopy has been used as an efficient tool for food authentication. This article reviews the latest research advances on NIR based fish authentication. The process from sampling/sample preparation to data analysis has been covered. Special attention was given to NIR spectra pre-processing and its unsupervised and supervised analysis. Sampling is an important aspect of traceability study and samples chosen ought to be a true representative of the population. NIR spectra acquired is often laden with overlapping bands, scattering and highly multicollinear. It needs adequate pre-processing to remove all undesirable features. The pre-processing technique can make or break a model and thus need a trial-and-error approach to find the best fit. As for spectral analysis and modelling, multicollinear nature of NIR spectra demands unsupervised analysis (PCA) to compact the features before application of supervised multivariate techniques such as LDA, PLS-DA, QDA etc. Machine learning approach of modelling has shown promising result in food authentication modelling and negates the need for unsupervised analysis before modelling.

A high security coding and anti-counterfeiting method based on the nonlinear magnetization response of superparamagnetic nanomaterials.

Traditional coding methods based on graphics and digital or magnetic labels have gradually decreased their anti-counterfeiting because of market popularity. This paper presents a new magnetic anti-counterfeiting coding method. This method uses a high-performance coding material, which, along with small changes to the material itself and the particle size of the superparamagnetic nanomaterials, results in a large difference in the nonlinear magnetization response. This method, which adopts 12-site coding and establishes a screening model by measuring the voltage amplitude of 12-site variables, can code different kinds of products, establishing long-term stable coding and decoding means. Through the anti-counterfeiting experiment of wine, the experiment results show that the authenticity of the coded products can be verified using the self-developed magnetic encoding and decoding system. The new coding technology can verify the anti-counterfeiting of 9000 products, with a single detection accuracy of 97% and a detection time of less than one minute. Moreover, this coding method completely depends on the production batch of the superparamagnetic nanomaterials, which is difficult to imitate, and it provides a new coding anti-counterfeiting technology for related industries with a wide range of potential applications.

Polygonati Rhizoma varieties and origins traceability based on multivariate data fusion combined with an artificial intelligence classification algorithm.

This study collected multidimensional feature data such as spectra, texture, and component contents of Polygonati Rhizoma from different origins and varieties (Polygonatum kingianum Coll. et Hemsl from Yunnan and Guizhou; Polygonatum cyrtonema Hua from Anhui and Jiangxi; Polygonatum sibiricum Red from Hunan). Multivariate statistical analysis was used to select 39 characteristic factors for distinguishing PR origins and 14 characteristic factors for discriminating PR varieties (VIP > 1 and P < 0.05). In addition, by combining multivariate statistical analysis with a deep belief network (DBN) classification algorithm, a novel artificial intelligence algorithm was developed and optimized. Compared to traditional discriminant analysis methods, the accuracy of this new approach was significantly improved, achieving a 100% discrimination rate for PR varieties and a 100% accuracy rate for tracing the origin of PR. This research provides a reference and data support for constructing intelligent algorithms based on multidimensional data fusion, to achieve food variety discrimination and origin tracing.

Definition, detection, and tracking of nanowaste in foods: Challenges and perspectives.

Commercial applications of nanotechnology in the food industry are rapidly increasing. Accordingly, there is a simultaneous increase in the amount and diversity of nanowaste, which arise as byproducts in the production, use, disposal, or recycling processes of nanomaterials utilized in the food industry. The potential risks of this nanowaste to human health and the environment are alarming. It is of crucial significance to establish analytical methods and monitoring systems for nanowaste to ensure food safety. This review provides comprehensive information on nanowaste in foods as well as comparative material on existing and new analytical methods for the detection of nanowaste. The article is specifically focused on nanowaste in food systems. Moreover, the current techniques, challenges as well as potential use of new and progressive methods are underlined, further highlighting advances in technology, collaborative efforts, as well as future perspectives for effective nanowaste detection and tracking. Such detection and tracking of nanowaste are required in order to effectively manage this type ofwasted in foods. Although there are devices that utilize spectroscopy, spectrometry, microscopy/imaging, chromatography, separation/fractionation, light scattering, diffraction, optical, adsorption, diffusion, and centrifugation methods for this purpose, there are challenges to be overcome in relation to nanowaste as well as food matrix and method characteristics. New technologies such as radio-frequency identification, Internet of things, blockchain, data analytics, and machine learning are promising. However, the cooperation of international organizations, food sector, research, and political organizations is needed for effectively managing nanowaste. Future research efforts should be focused on addressing knowledge gaps and potential strategies for optimizing nanowaste detection and tracking processes.

Changes in source composition of wet nitrate deposition after air pollution control in a typical area of Southeast China.

In recent years, China has adopted numerous policies and regulations to control NOx emissions to further alleviate the adverse impacts of NO3--N deposition. However, the variation in wet NO3--N deposition under such policies is not clear. In this study, the southeastern area, with highly developed industries and traditional agriculture, was selected to explore the variation in NO3--N deposition and its sources changes after such air pollution control through field observation and isotope tracing. Results showed that the annual mean concentrations of NO3--N in precipitation were 0.67 mg L-1 and 0.54 mg L-1 in 2014-2015 and 2021-2022, respectively. The average wet NO3--N depositions in 2014-2015 and 2021-2022 was 7.76 kg N ha-1 yr-1 and 5.03 kg N ha-1 yr-1, respectively, indicating a 35% decrease. The δ15N-NO3- and δ18O-NO3- values were lower in warm seasons and higher in cold seasons, and both showed a lower trend in 2021-2022 compared with 2014-2015. The Bayesian model results showed that the NOx emitted from coal-powered plants contributed 53.6% to wet NO3--N deposition, followed by vehicle exhaust (22.9%), other sources (17.1%), and soil emissions (6.4%) during 2014-2015. However, the contribution of vehicle exhaust (33.3%) overpassed the coal combustion (32.3%) and followed by other sources (25.4%) and soil emissions (9.0%) in 2021-2022. Apart from the control of air pollution, meteorological factors such as temperature, precipitation, and solar radiation are closely related to the changes in atmospheric N transformation and deposition. The results suggest phased achievements in air pollution control and that more attention should be paid to the control of motor vehicle exhaust pollution in the future, at the same time maintaining current actions and supervision of coal-powered plants.

A synergistic solution for fighting fraudulent practices in squid using light stable isotope ratios and lanthanide tracers.

To identify a novel optimized strategy for preventing fraudulent substitutions of squid species and origins, forty European squids (Loligo vulgaris) and forty flying squids (Todarodes sagittatus) from the Mediterranean Sea and Atlantic Ocean were analyzed for δ13C, δ15N, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Yb, and Lu using isotope ratio mass spectrometry and inductively coupled plasma-mass spectrometry. While δ13C and δ15N variations were mainly species-related, they alone could not reliably distinguish samples. To address this issue, decision rules were developed using Classification and Regression Tree analysis. Threshold values for δ13C (-19.91‰), δ15N (14.87‰), and Pr (0.49 µg kg-1) enabled successful discrimination among Mediterranean European squids, Atlantic European squids, Mediterranean flying squids, and Atlantic flying squids, achieving over 90% accuracy, 81% precision, 80% sensitivity, and 93% specificity. This method holds promise for enhancing traceability and safety in the seafood industry, ensuring product integrity and consumer trust.

Improving Accuracy and Reliability of Hearing Tests: Measurement Standards for Audiometric Devices.

Pure-tone audiometry, using an audiometer, is the fundamental hearing test for diagnosing hearing loss. The requirements of the devices and the detailed process for calibrating the related equipment are described in international standards. However, traceable calibration and uncertainty evaluation processes are not widely accepted or applied to the qualification and maintenance of audiometric equipment. Here, we briefly review standard measurement systems for audiometric devices and introduce their calibration procedures. The uncertainty of each calibration process was investigated, and its impact on hearing test results was considered. Our findings show that the traceability of each procedure can be secured, satisfying the uncertainty requirement and being sufficiently smaller than the permissible deviation from the audiometer requirement. To guarantee the objectivity and reliability of hearing tests and maintain low uncertainty, close cooperation and mutual understanding between the metrology field and the medical community are necessary.

Molecular Traceability Approach to Assess the Geographical Origin of Commercial Extra Virgin Olive Oil.

Extra virgin olive oil (EVOO) is a precious and healthy ingredient of Mediterranean cuisine. Due to its high nutritional value, the interest of consumers in the composition of EVOO is constantly increasing, making it a product particularly exposed to fraud. Therefore, there is a need to properly valorize high-quality EVOO and protect it from fraudulent manipulations to safeguard consumer choices. In our study, we used a straightforward and easy method to assess the molecular traceability of 28 commercial EVOO samples based on the use of SSR molecular markers. A lack of correspondence between the declared origin of the samples and the actual origin of the detected varieties was observed, suggesting possible adulteration. This result was supported by the identification of private alleles based on a large collection of national and international olive varieties and the search for them in the molecular profile of the analyzed samples. We demonstrated that the proposed method is a rapid and straightforward approach for identifying the composition of an oil sample and verifying the correspondence between the origin of olives declared on the label and that of the actual detected varieties, allowing the detection of possible adulterations.

Geotraceability of Falanghina del Sannio (South Italy): Preliminary mineralogical and isotopic data.

The present study gathers mineralogical and isotopic geochemical data of 45 soil samples collected from the La Guardiense and Cantina di Solopaca wineries (Southern Italy) in order to provide useful information for the geotraceability of Falanghina white wine terroir. Mineralogical analyses show the ubiquitous presence of quartz, frequent and moderate contents of feldspars and phyllosilicates (i.e., illite/mica, kaolinite, and smectite). Rhizosphere soils from La Guardiense vineyards show a strontium isotope signature (87Sr/86Sr) ranging from 0.708604 to 0.711234 (average 0.710334; 1σ = 0.000943; n = 7) for the total fraction and a narrower range (from 0.706907 to 0.708807; average 0.708120; 1σ = 0.000641; n = 7) for the bioavailable one. For the rhizosphere soils collected from the vineyards of Cantina di Solopaca winery, 87Sr/86Sr ratios range from 0.708268 to 0.712413 (average 0.710145; 1σ = 0.001622; n = 8) and from 0.707968 to 0.709157 (average 0.708384; 1σ = 0.000409; n = 8) for the total and the bioavailable fraction, respectively. Actually, the bioavailable Sr fraction shows a narrower range of 87Sr/86Sr ratios compared to that of the total fraction, making the former more suitable for any study of wine traceability.

Metrological realization of the radon activity concentration in air.

In the framework of the EMPIR research project Metrology for Radon, a facility was devised that provides stable and traceable atmospheres for the realization of radon activity concentration at a high metrological level. The facility is used to calibrate and test devices for measuring radon in the air. It enables precise long-term exposures in the range between 100 Bq/m3 and 1000 Bq/m3. The radon activity concentrations are realized with uncertainties of about 1.0 % (k = 1).

CO2 Laser-labeling on Fresh Produce: Evaluating Postharvest Quality, Microbial Safety, and Economic Analysis.

Fresh produce is traditionally labeled with plastic price lookup (PLU) stickers that are attached to the produce surface using edible glue. However, both the stickers and glue are environmental contaminants, and the stickers can still easily detach from the produce surface during handling and disrupt traceability. An alternative method of labeling, the CO2 laser-labeling technology (LLT), has been gaining attention in recent years. However, engraving Quick Response (QR) code using LLT is unique, and the performance of this technology varies from produce item to produce item, and information on its effects on postharvest quality, microbial safety, and economic feasibility has not been reported. The objectives of this study were to investigate the effect of laser-labeling technology on (1) postharvest quality, (2) microbial safety, and (3) economic analysis of this technology. Three horticultural crops, 'Red Delicious' apple (Malus pumila), green bell pepper (Capsicum annuum), and cucumber (Cucumis sativus) were procured from a local grocery store. Each produce was engraved with a Quick Response (QR) code or 6-digit alphanumerical (text) code using the commercially available Trotec Speedy 300 CO2 laser engraver, followed by the application of edible wax. Fresh weight loss for laser-printed produce was higher compared to controls, but no difference in visual quality ratings was observed. The laser-labeled produce was assessed for microbial contamination by artificially inoculating rifampicin-resistant Escherichia coli (E. coli) log10 6 CFU/mL to the labeled fruit. The results showed that the population of rifampicin-resistant E. coli was statistically higher in all three products labeled with text code compared to the nontreated controls. The QR-coded treatments were similar to the controls. The wax application did not affect the microbial attachment on the laser-labeled produce. The CO2 laser labeling technology has the potential for industrial application.

Secure traceability mechanism of green electricity based on smart contracts and provenance model.

Green and low-carbon development is an important part of global sustainable development. Green power trading provides strong support and assurance for promoting green and low-carbon development. Due to the long cycle of green power data chains and their susceptibility to malicious tampering, the integrity and traceability of data are difficult to guarantee. Therefore, this paper first proposes a security provenance model with enhanced relations based on the core structure of PROV and blockchain technology, which can securely capture provenance records, use the transfer time and number of transactions between various links in the traceability network as reasoning clues, realize the correlation tracing of the green electricity transfer process. Under the model, a traceability mechanism of green electricity is designed based on smart contracts. Trustworthy green electricity data collection is achieved through data filling and data verification techniques. Traceability query technique is adopted to achieve trustworthy traceability of green electricity. And the effectiveness of the proposed solution is demonstrated through simulation experiments.

An integrative review of analytical techniques used in food authentication: A detailed description for milk and dairy products.

The use of suitable analytical techniques for the detection of adulteration, falsification, deliberate substitution, and mislabeling of foods has great importance in the industrial, scientific, legislative, and public health contexts. This way, this work reports an integrative review with a current analytical approach for food authentication, indicating the main analytical techniques to identify adulteration and perform the traceability of chemical components in processed and non-processed foods, evaluating the authenticity and geographic origin. This work presents results from a systematic search in Science Direct® and Scopus® databases using the keywords "authentication" AND "food", "authentication," AND "beverage", from published papers from 2013 to, 2024. All research and reviews published were employed in the bibliometric analysis, evaluating the advantages and disadvantages of analytical techniques, indicating the perspectives for direct, quick, and simple analysis, guaranteeing the application of quality standards, and ensuring food safety for consumers. Furthermore, this work reports the analysis of natural foods to evaluate the origin (traceability), and industrialized foods to detect adulterations and fraud. A focus on research to detect adulteration in milk and dairy products is presented due to the importance of these products in the nutrition of the world population. All analytical tools discussed have advantages and drawbacks, including sample preparation steps, the need for reference materials, and mathematical treatments. So, the main advances in modern analytical techniques for the identification and quantification of food adulterations, mainly milk and dairy products, were discussed, indicating trends and perspectives on food authentication.

Stepping-up accurate quantification of chlorinated paraffins: Successful certification of the first matrix reference material.

BACKGROUND: Chlorinated paraffins (CPs) are industrial chemicals categorised as persistent organic pollutants because of their toxicity, persistency and tendency to long-range transport, bioaccumulation and biomagnification. Despite having been the subject of environmental attention for decades, analytical methods for CPs still struggle reaching a sufficient degree of accuracy. Among the issues negatively impacting the quantification of CPs, the unavailability of well-characterised standards, both as pure substances and as matrix (certified) reference materials (CRMs), has played a major role. The focus of this study was to provide a matrix CRM as quality control tool to improve the comparability of CPs measurement results. RESULTS: We present the process of certification of ERM®-CE100, the first fish reference material assigned with certified values for the mass fraction of short-chain and medium-chain chlorinated paraffins (SCCPs and MCCPs, respectively). The certification was performed in accordance with ISO 17034:2016 and ISO Guide 35:2017, with the value assignment step carried out via an intercomparison of laboratories of demonstrated competence in CPs analysis and applying procedures based on different analytical principles. After confirmation of the homogeneity and stability of the CRM, two certified values were assigned for SCCPs, depending on the calibrants used: 31 ± 9 µg kg-1 and 23 ± 7 µg kg-1. The MCCPs certified value was established as 44 ± 17 µg kg-1. All assigned values are relative to wet weight in the CRM that was produced as a fish paste to enhance similarity to routine biota samples. SIGNIFICANCE AND NOVELTY: The fish tissue ERM-CE100 is the first matrix CRM commercially available for the analysis of CPs, enabling analytical laboratories to improve the accuracy and the metrological traceability of their measurements. The certified CPs values are based on results obtained by both gas and liquid chromatography coupled with various mass spectrometric techniques, offering thus a broad validity to laboratories employing different analytical methods and equipment.

Research of 2D-COS with metabolomics modifications through deep learning for traceability of wine.

To tackle the difficulty of extracting features from one-dimensional spectral signals using traditional spectral analysis, a metabolomics analysis method is proposed to locate two-dimensional correlated spectral feature bands and combine it with deep learning classification for wine origin traceability. Metabolomics analysis was performed on 180 wine samples from 6 different wine regions using UPLC-Q-TOF-MS. Indole, Sulfacetamide, and caffeine were selected as the main differential components. By analyzing the molecular structure of these components and referring to the main functional groups on the infrared spectrum, characteristic band regions with wavelengths in the range of 1000-1400 nm and 1500-1800 nm were selected. Draw two-dimensional correlation spectra (2D-COS) separately, generate synchronous correlation spectra and asynchronous correlation spectra, establish convolutional neural network (CNN) classification models, and achieve the purpose of wine origin traceability. The experimental results demonstrate that combining two segments of two-dimensional characteristic spectra determined by metabolomics screening with convolutional neural networks yields optimal classification results. This validates the effectiveness of using metabolomics screening to determine spectral feature regions in tracing wine origin. This approach effectively removes irrelevant variables while retaining crucial chemical information, enhancing spectral resolution. This integrated approach strengthens the classification model's understanding of samples, significantly increasing accuracy.

Traceability of gushing water in the MiddleRoute of the South-to-North Water Diversion (Beijing section) through the river area.

To trace the origin of the gushing water in the riverine area of the Beijing section of The Middle Route of South-to-North Water Diversion Project, a dataset was established comprising water chemistry, three-dimensional fluorescence spectra, and stable isotopes for different water bodies. Results indicated significant differences in Electrical Conductivity (EC), Total Dissolved Solids (TDS), and Ca2+ concentration among the gushing water, river water, and the water from the Middle Route of South-to-North Water Diversion Project (MRSD). Analysis using parallel factor analysis (PARAFAC) and fluorescence index revealed that dissolved organic matter (DOM) in the MRSD mainly originated from endogenous sources, while the river water and gushing water showed influences from both endogenous and exogenous sources. Nitrate sources varied among the water bodies, with distinct contributions from domestic sewage and fertilizer sources. The evaporation lines of river water and gushing water exhibited similar intercepts and slopes, but their intercepts and slopes are much smaller than those of the MRSD, suggesting stronger kinetic evaporative fractionation. In conclusion, the gushing water in the riverine area of the MRSD was determined to originate from the river, providing a fast and efficient method for gushing water source identification.