Machine Learning Models and Applications for Early Detection.

From the various perspectives of machine learning (ML) and the multiple models used in this discipline, there is an approach aimed at training models for the early detection (ED) of anomalies. The early detection of anomalies is crucial in multiple areas of knowledge since identifying and classifying them allows for early decision making and provides a better response to mitigate the negative effects caused by late detection in any system. This article presents a literature review to examine which machine learning models (MLMs) operate with a focus on ED in a multidisciplinary manner and, specifically, how these models work in the field of fraud detection. A variety of models were found, including Logistic Regression (LR), Support Vector Machines (SVMs), decision trees (DTs), Random Forests (RFs), naive Bayesian classifier (NB), K-Nearest Neighbors (KNNs), artificial neural networks (ANNs), and Extreme Gradient Boosting (XGB), among others. It was identified that MLMs operate as isolated models, categorized in this article as Single Base Models (SBMs) and Stacking Ensemble Models (SEMs). It was identified that MLMs for ED in multiple areas under SBMs' and SEMs' implementation achieved accuracies greater than 80% and 90%, respectively. In fraud detection, accuracies greater than 90% were reported by the authors. The article concludes that MLMs for ED in multiple applications, including fraud, offer a viable way to identify and classify anomalies robustly, with a high degree of accuracy and precision. MLMs for ED in fraud are useful as they can quickly process large amounts of data to detect and classify suspicious transactions or activities, helping to prevent financial losses.

Improving fraud detection with semi-supervised topic modeling and keyword integration.

Fraud detection through auditors' manual review of accounting and financial records has traditionally relied on human experience and intuition. However, replicating this task using technological tools has represented a challenge for information security researchers. Natural language processing techniques, such as topic modeling, have been explored to extract information and categorize large sets of documents. Topic modeling, such as latent Dirichlet allocation (LDA) or non-negative matrix factorization (NMF), has recently gained popularity for discovering thematic structures in text collections. However, unsupervised topic modeling may not always produce the best results for specific tasks, such as fraud detection. Therefore, in the present work, we propose to use semi-supervised topic modeling, which allows the incorporation of specific knowledge of the study domain through the use of keywords to learn latent topics related to fraud. By leveraging relevant keywords, our proposed approach aims to identify patterns related to the vertices of the fraud triangle theory, providing more consistent and interpretable results for fraud detection. The model's performance was evaluated by training with several datasets and testing it with another one that did not intervene in its training. The results showed efficient performance averages with a 7% increase in performance compared to a previous job. Overall, the study emphasizes the importance of deepening the analysis of fraud behaviors and proposing strategies to identify them proactively.

Exploring Strategies to Mitigate the Lightness Effect on the Prediction of Soybean Oil Content in Blends of Olive and Avocado Oil Using Smartphone Digital Image Colorimetry.

Extra virgin olive oil (EVOO) and avocado oil (AVO) are recognized for their unique sensory characteristics and bioactive compounds. Declared blends with other vegetable oils are legal, but undeclared mixing is a common type of fraud that can affect product quality and commercialization. In this sense, this study explored strategies to mitigate the influence of lighting in order to make digital image colorimetry (DIC) using a smartphone more robust and reliable for predicting the soybean oil content in EVOO and AVO blends. Calibration models were obtained by multiple linear regression using the images' RGB values. Corrections based on illuminance and white reference were evaluated to mitigate the lightness effect and improve the method's robustness and generalization capability. Lastly, the prediction of the built model from data obtained using a distinct smartphone was assessed. The results showed models with good predictive capacities, R2 > 0.9. Generally, models solely based on GB values showed better predictive performances. The illuminance corrections and blank subtraction improved the predictions of EVOO and AVO samples, respectively, for image acquisition from distinct smartphones and lighting conditions as evaluated by external validation. It was concluded that adequate data preprocessing enables DIC using a smartphone to be a reliable method for analyzing oil blends, minimizing the effects of variability in lighting and imaging conditions and making it a potential technique for oil quality assurance.

The Pandora's box of transparency opened by direct-to-consumer genetic testing.

With the increasing use of direct-to-consumer (DTC) genetic testing, several cases of fertility fraud have been uncovered throughout the world. A review of newspaper articles and specialized literature was made to analyze the issue of fertility fraud. The most famous cases, some of which are narrated in this article, became a scandal because they were committed by the doctors who treated the patients in question as a routine procedure in their medical practice. Some have been widely exposed in documentaries on streaming platforms, thereby raising awareness about a grave problem. The discussion focuses on the ambiguous regulation on the anonymity of donors, which has been one of the elements of the deception committed against the families using these services. Anonymity nowadays collides with the fascinating Pandora's box of transparency in genetic information that has been opened by DTC genetic testing.

Una Revisión de los tipos de Fraude Científico más Frecuentes / A Review of the most frequent types of Scientific Fraud

La presión que existe hoy por publicar ha llevado a que muchos investigadores cometan malas conductas científicas, siendo el fraude la más grave de todas. Este ocurre en forma de fabricación, falsificación, plagio, problemas de autoría, manipulación de imágenes y publicaciones redundantes. El fraude científico se define como una tergiversación deliberada por parte de alguien que conoce la verdad. En la historia de la humanidad se han conocido importantes casos de fraude científico, dentro de ellos se pueden destacar: el hombre de Piltdown, caso Shinichi Fujimura, el escándalo de las vacunas, caso Pearce, el caso Yoshitaka Fujii, entre otros. Con el objetivo de neutralizar el fraude, se han desarrollado diferentes estrategias dirigidas a detectarlo, dentro de ellas encontramos: evaluación mediante pares evaluadores, programas de Conducta de Investigación Responsable (RCR), regulaciones que la misma comunidad científica realiza, donde encontramos la fundación PubPeer y el blog For Better Science. Del mismo modo, se han impuesto diferentes medidas para contrarrestar el fraude, tales como: transparencia de las presiones y oportunidades, disponibilidad pública de los datos que sustentan la hipótesis y denuncia pública de los fraudes científicos. El impacto de un fraude trae consecuencias importantes para la ciencia, estudiar a partir de información falsa o errónea conlleva a un gran retroceso en los avances científicos del mundo actual. Es responsabilidad de cada uno ser consciente de lo que se escribe y lo que se lee, ya que como se sabe, esa es la única manera de combatirlo. Como investigadores somos responsables de actuar éticamente en nuestras investigaciones y tener conocimiento de las medidas que existen hoy para detectar y combatir el fraude científico.

The pressure to publish today has led many researchers to commit scientific misconduct, fraud being the most serious of all. This occurs in the form of fabrication, falsification, plagiarism, authorship problems, image manipulation, and redundant posting. Scientific fraud is defined as deliberate misrepresentation by someone who knows the truth. In the history of humanity, important cases of scientific fraud have been known, among them the following can be highlighted: the Piltdown man, the Shinichi Fujimura case, the vaccine scandal, the Pearce case, the Yoshitaka Fujii case, among others. In order to neutralize fraud, different strategies have been developed to detect it, among them we find: evaluation by peer reviewers, Responsible Research Conduct (RCR) programs, regulations that the scientific community itself carries out, where we find the PubPeer Foundation and the For Better Science blog. Similarly, different measures have been imposed to counteract fraud, such as: transparency of pressures and opportunities, public availability of the data that support the hypothesis, and public denunciation of scientific fraud. The impact of a fraud has important consequences for science, studying from false or wrong information leads to a great setback in scientific advances in the world today. It is the responsibility of each one to be aware of what is written and what is read, since as is known, that is the only way to combat it. As researchers we are responsible for acting ethically in our research and being aware of the measures that exist today to detect and combat scientific fraud.

Fraude alimentario: Pasado, presente y futuro

La adulteración y el fraude de productos alimenticios son tan antiguos como los sistemas de procesamiento y producción de alimentos, sin embargo, en la actualidad son cada vez más frecuentes. Con la globalización y los sistemas de producción y distribución de alimentos cada día más complejos, la adulteración puede ocurrir en distintos puntos de la cadena alimentaria y tener un impacto de gran alcance, e incluso, consecuencias adversas para la salud de las personas. Los enfoques regulatorios de la comunidad internacional para enfrentar y resolver el fraude alimentario están dispersos y en constantes ajustes. Se necesita un enfoque colectivo y coordinado para identificar a todos los interesados en la cadena de suministro de alimentos, calificarlos y certificarlos, excluir a aquellos que no cumplan con los estándares adecuados y rastrear los alimentos en tiempo real. Este artículo de actualización revisará conceptos claves asociados a la integridad alimentaria, historia del fraude alimentario y episodios de fraude alimentario de connotación pública en el mundo y en Chile, herramientas analíticas y alimentos más vulnerables al fraude, reglamentos y nuevas acciones en el mundo y en Chile para enfrentar la inocuidad y el riesgo de fraude alimentario.

Food adulteration and food fraud is as old as food production and processing however, it is increasingly prevalent today. With globalization and increasingly complex food production and distribution systems, adulteration can occur at different points in the food chain and may have far-reaching impacts and even adverse consequences for human health. The international community's regulatory approaches to confronting and resolving food fraud are scattered and in constant adjustment. A collective and coordinated approach is needed to identify all stakeholders in the food supply chain, certify and qualify them, exclude those who do not meet applicable standards, and trace food in real time. This update provides definitions and background on key concepts associated with food integrity, episodes of food fraud in Chile and the world, main foods vulnerable to food fraud, common fraud practices and analytical techniques, regulations and new actions in Chile and the world to face food safety and the risk of food fraud.

Rapid and non-destructive cinnamon authentication by NIR-hyperspectral imaging and classification chemometrics tools.

Cinnamon is a valuable aromatic spice widely used in pharmaceutical and food industry. Commonly, two-cinnamon species are available in the market, Cinnamomum verum (true cinnamon), cropped only in Sri Lanka, and Cinnamomum cassia (false cinnamon), cropped in different geographical origins. Thus, this work aimed to develop classification models based on NIR-hyperspectral imaging (NIR-HSI) coupled to chemometrics to classify C. verum and C. cassia sticks. First, principal component analysis (PCA) was applied to explore hyperspectral images. Scores surface displayed the high similarity between species supported by comparable macronutrient concentration. PC3 allowed better class differentiation compared to PC1 and PC2, with loadings exhibiting peaks related to phenolics/aromatics compounds, such as coumarin (C. cassia) or catechin (C. verum). Partial least square discriminant analysis (PLS-DA) and Support vector machine (SVM) reached similar performance to classify samples according to origin, with error = 3.3 % and accuracy = 96.7 %. A permutation test with p < 0.05 validated PLS-DA predictions have real spectral data dependency, and they are not result of chance. Pixel-wise (approach A) and sample-wise (approach B, C and D) classification maps reached a correct classification rate (CCR) of 98.3 % for C. verum and 100 % for C. cassia. NIR-HSI supported by classification chemometrics tools can be used as reliable analytical method for cinnamon authentication.

Cenário da falsificação de medicamentos no Brasil entre os anos de 2015 e 2022 / Scenario of drug counterfeiting in Brazil between 2015 and 2022

A falsificação de medicamentos é uma prática criminosa frequente em situações de alta demanda, carência de produtos e preços elevados no mercado, gerando muitos riscos à saúde da população. Objetivo: Estabelecer o panorama da falsificação de medicamentos no Brasil entre os anos de 2015 e 2022. Método: Trata-se de um estudo descritivo e retrospectivo dos registros de apreensão de medicamentos com indícios de falsificação, disponibilizados pela Agência Nacional de Vigilância Sanitária. Resultados: 30 fármacos diferentes foram mencionados nos registros de falsificação do período estudado, com predomínio de medicamentos biológicos e controlados e das formas farmacêuticas de via parenteral. Os fármacos que apresentaram mais registros de falsificação foram somatropina, imunoglobulina, sofosbuvir/ledispavir, eculizumabe e defibrotida. Conclusão: Por muitos anos, a falsificação de medicamentos no Brasil foi caracterizada principalmente por estimulantes sexuais masculinos, anabolizantes e anorexígenos. Entretanto, nos últimos anos, os medicamentos de alto custo destinados ao tratamento de doenças crônicas e raras se sobressaíram. Este cenário pode estar relacionado a diversos fatores, como gravidade das doenças, avanços das terapias medicamentosas, elevada lucratividade, falta de acesso aos medicamentos e dificuldades sociais e econômicas associadas à pandemia da doença por coronavírus 2019 (COVID-19)

Drug counterfeiting is a common criminal practice in situations of high demand, lack of products and high market prices, which generates risks to the health of the population. Objective: To establish an overview of drug counterfeiting in Brazil between 2015 and 2022. Method: This is a descriptive and retrospective study of data on drugs arrest with evidence of counterfeiting made available by the Brazilian Health Surveillance Agency. Results: 30 different drugs were mentioned in counterfeiting records for the period studied with a predominance of biopharmaceuticals and controlled substances, and parenteral pharmaceutical forms. The drugs with the most falsification records were somatropin, immunoglobulin, sofosbuvir/ledispavir, eculizumab and defibrotide. Conclusion: For many years, drug counterfeiting in Brazil was mainly characterized by male sexual stimulants, anabolic steroids, and anorectic. However, high-cost drugs for treating chronic and rare diseases have recently gained prominence. This scenario may be related to several factors, such as the severity of the diseases, advances in drug therapies, high profitability, lack of access to drugs, and social and economic difficulties associated with the coronavirus disease 2019 (COVID-19) pandemic

The forensics of fraud: Evidence from the 2018 Brazilian presidential election.

Objective: This paper studies the integrity of the vote counting system in Brazil. Method: We analyze data from the Superior Electoral Court (TSE) for the 2018 Brazilian presidential election to assess suspicious vote count patterns deploying five techniques commonly used to detect fraud: a) the second-digit Benford's law test; b) the last digit mean; c) frequency analysis of last digits 0 and 5; d) correlation between the percentage of votes and the turnout rate; and e) resampled Kernel density of the proportion of votes. Results: The results show that the second-digit distributions for the three most voted candidates - Jair Messias Bolsonaro (PSL), Fernando Haddad (PT), and Ciro Gomes (PDT) - conform to Benford's law. We also find that last digit means and last digit frequency are within normal parameters, indicating no irregularities. Similarly, the fingerprint plot indicates a correlation coefficient that is consistent with the theoretical expectation of a fair election. The resampled Kernel density suggests that the vote count was performed without statistically significant distortions. These results are robust at different levels of data aggregation (polling station and municipality). Conclusion: The joint application of digit-focused tests, regression-based techniques, and patterns in the distribution of vote-shares provide a more reliable method for detecting anomalous cases. Relying on this unified framework, we find no evidence of electoral fraud in the 2018 Brazilian presidential election. These results advance our current understanding of statistical forensics tools and may be easily replicated to examine electoral integrity in other countries.

Cheating Motivation Scale: evidence of validity and reliability / Escala de Motivação para Trapacear: evidências de validade e confiabilidade / Escala de Motivación para Engañar: evidencias de validez y fiabilidad

This study aimed to adapt the Motivation to Cheat Scale (MCS) to the Brazilian student context, gathering evidence of validity based on its internal structure. Two studies were carried out. In Study 1, the 20 items of the MCS were translated into Portuguese and evaluated semantically by ten students, who consider them sufficiently understandable. Subsequently, seeking to know the internal structure of the measure, there was the participation of 212 high school students (M = 16.10 years; SD = 1.02). An exploratory factor analysis indicated the existence of two factors (search for success and moral initiation), which were saturated 18 items. O Study 2 aimed to verify this factorial structure. Logo, the 18 items answered by 229 high school students (M = 16.20 years; SD = 1.23). A confirmatory factorial analysis confirmed bifactorial adjustment. MCS has evidence of validity based on internal structure, which can be used in research outside of Brazil. (AU)

Objetivou-se adaptar a Escala de Motivação para Trapacear (EMT) para o contexto estudantil brasileiro, reunindo evidências de validade baseadas em sua estrutura interna. Realizaram-se dois estudos. No Estudo 1, os 20 itens da EMT foram traduzidos para o português e submetidos à avaliação semântica de dez estudantes, que os consideraram suficientemente compreensíveis. Posteriormente, buscando-se conhecer a estrutura interna da medida, contou-se com a participação de 212 estudantes do Ensino Médio (M = 16,10 anos; DP = 1,02). Uma análise fatorial exploratória indicou a existência de dois fatores (busca de realização e inibição moral), nos quais saturaram 18 itens. O Estudo 2 visou comprovar essa estrutura fatorial. Logo, os 18 itens foram respondidos por 229 estudantes do Ensino Médio (M = 16,20 anos; DP = 1,23). Uma análise fatorial confirmatória comprovou o ajuste bifatorial. A EMT apresentou evidências de validade baseadas na estrutura interna, podendo ser utilizada em pesquisas no Brasil. (AU)

Este estudio tuvo como objetivo adecuar la Escala de Motivación para Engañar (EME) al contexto estudiantil brasileño, recogiendo evidencias de validez a partir de su estructura interna. Se realizaron dos estudios. En el Estudio 1, los 20 ítems de la EME fueron traducidos al portugués y sometidos a la evaluación semántica por parte de diez estudiantes, quienes los consideraron suficientemente comprensibles. Posteriormente, buscando comprender la estructura interna de la medida, participaron 212 estudiantes de la Educación Secundaria (M = 16,10 años; DS = 1,02). Un análisis factorial exploratorio indicó la existencia de dos factores (búsqueda de realización e inhibición moral), en los que se saturaron 18 ítems. El Estudio 2 tuvo como objetivo verificar esta estructura factorial. Por lo que, los 18 ítems fueron respondidos por 229 estudiantes de Secundaria (M = 16,20 años; DS = 1,23). Un análisis factorial confirmatorio demostró la adecuación bifactorial. La EME ha revelado evidencias de validez basadas en la estructura interna, pudiendo ser utilizada en investigaciones brasileñas. (AU)

Authenticity under threat: grated Parmesan cheese sold in Brazil.

This research communication depicts the quality and authenticity of grated Parmesan cheese sold in Brazil, with novel emphasis on ripening time. The sampling included all brands manufactured and packed at Brazilian dairy plants under federal inspection and sold in Londrina between June and September 2017. A total of 24 samples were analyzed (3 batches of 8 brands) for microbiological and compositional characteristics, including urea-PAGE electrophoresis for the quantitative determination of the milk proteins. About 80% of the samples were insufficiently ripened and 32% with low-fat content. Faced with these economically motivated food frauds, the authenticity of grated Parmesan in Brazil may be under threat. It is high recommended that future surveys and regulatory agencies go further than microbiological assessment, including and emphasizing the ripening time as the main parameter of grated Parmesan cheese.

Variable selection in the chemometric treatment of food data: A tutorial review.

Food analysis covers aspects of quality and detection of possible frauds to ensure the integrity of the food. The arsenal of analytical instruments available for food analysis is broad and allows the generation of a large volume of information per sample. But this instrumental information may not yet give the desired answer; it must be processed to provide a final answer for decision making. The possibility of discarding non-informative and/or redundant signals can lead to models of better accuracy, robustness, and chemical interpretability, in line with the principle of parsimony. Thus, in this tutorial review, we cover aspects of variable selection in food analysis, including definitions, theoretical aspects of variable selection, and case studies showing the advantages of variable selection-based models concerning the use of a wide range of non-informative and redundant instrumental information in the analysis of food matrices.

Artificial neural networks in the prediction of fraud in integral milk powder by adding whey powder / Redes neurais artificiais na predição de fraude em leite em pó integral pela adição de soro lácteo em pó

This research was performed to ascertain the most suitable Artificial Neural Network (ANN) model to quantify the degree of fraud in powdered milk through the addition of powdered whey via regular standard physicochemical analyses. In this study, an evaluation was done on 103 samples with different quantities of added whey powder to whole milk powder. Using Fourier Transform Infrared Spectroscopy the fat, cryoscopy, total solids, defatted dry extract, lactose, protein and casein were analyzed. The hyperbolic tangent transformation function was used with 45 topologies, and the Holdback and K-fold validation methods were tested. In the Holdback method, 75% of the database was employed for training, while 25% was used for validation. In the K-fold method, the database was categorized into five equal sized subsets, which alternated between training and validation. Of the two methods, the K-fold method was proven to have superior efficiency. Next, analysis was done on three models of multilayer perceptron networks with feedforward architecture. In Model 1, the input layer contained all the physicochemical analyses conducted, in model 2 the casein analysis was excluded, and in model 3 the routine analyses performed for dairy products was done (fat, defatted dry extract, cryoscopy and total solids). From Model 3 an ANN was derived which could satisfactorily predict fraud calculated from using the routine and standard analyses for dairy products, containing 64 nodes in the hidden layer, with R² of 0.9935 and RMSE of 0.5779 for training, and R² of 0.9964 and RMSE of 0.4358 for validation.

O objetivo do trabalho foi determinar o melhor modelo de rede neural artificial (RNA) para quantificar fraude em leite em pó, pela adição de soro em pó, por meio de analises físico-químicas de rotina. Foram avaliados 103 níveis de adição de soro lácteo em pó em leite em pó integral. As análises de gordura, crioscopia, sólidos totais, extrato seco desengordurado, lactose, proteína e caseína foram realizadas por espectroscopia no infravermelho com transformada de Fourier. A função de transformação utilizada foi a tangente hiperbólica, em que testou-se 45 topologias e dois métodos de validação: holdback e k-fold. Para o método holdback, 75% do banco de dados foi utilizado para o treinamento e 25% para a validação. Para o método k-fold, o banco de dados foi dividido em cinco subconjuntos de mesmo tamanho que se alternavam entre treinamento e validação. O método k-fold se mostrou mais eficiente. Três modelos de redes perceptron de múltiplas camadas com arquitetura feedforward foram analisados. No modelo 1 a camada de entrada constituía todas as análises físico-químicas realizadas, no modelo 2 excluiu-se a análise de caseína e no modelo 3 utilizou-se as análises de rotina em laticínios (gordura, extrato seco desengordurado, crioscopia e sólidos totais). O modelo 3 obteve uma RNA capaz de predizer satisfatoriamente a fraude avaliada a partir de análises consideradas de rotina em laticínios com uma RNA contendo 64 nodos na camada oculta, R² de 0,9935 e RMSE de 0,5779 para treinamento, R² de 0,9964 e RMSE de 0,4358 para validação.

Three centuries on the science of coffee authenticity control.

Food authenticity relies on genuineness and reliability according to the information displayed on the package. Since the 18th century, when coffee became popularized in the West, adulteration began. Several methods have been developed to detect different kinds of frauds and they have evolved as demands increased and new technologies were introduced. The evolution of the science of coffee authenticity control in the past three centuries is reviewed, focusing on the discrimination between coffee and other foods or between coffee and its by-products. The earliest chemical and physical methods are presented followed by methods developed in the 20th and 21st centuries using microscopy, chromatography and spectroscopy associated with advanced statistical tools, and DNA-based methods. In addition to non-food material, before the 20th century, chicory was the most studied food-adulterant. From the 20th century on, corn, coffee by-products, and barley were the most studied, followed by chicory, rice and other food items. Matrix effects seem to be among the most challenging problems in these approaches, associated with variations in roast degree, particle size (particularly in spectroscopy-based methods), and lack of control over reference samples regarding species and purity. Limits of detection vary considerably within each category, with most limits being too high for commercial use. DNA-based methods appear to be promising to assess coffee authenticity, given that the limits of detection and quantification are low, and specificity is higher than in other methods. Nevertheless, as roast intensity increases, the sensitivity of the method decreases. So far, most reported methods have not been validated and only a few have been tested on commercial brands, except for those involving microscopy which has been highly used for monitoring coffee authenticity although not always efficiently enough.

Fourteen years of manifestations and factors of health insurance fraud, 2006-2020: a scoping review.

BACKGROUND: Healthcare fraud entails great financial and human losses; however, there is no consensus regarding its definition, nor is there an inventory of its manifestations and factors. The objective is to identify the definition, manifestations and factors that influence health insurance fraud (HIF). METHODS: A scoping review on health insurance fraud published between 2006 and 2020 was conducted in ACM, EconPapers, PubMed, ScienceDirect, Scopus, Springer and WoS. RESULTS: Sixty-seven studies were included, from which we identified 6 definitions, 22 manifestations (13 by the medical provider, 7 by the beneficiary and, 2 by the insurance company) and 47 factors (6 macroenvironmental, 15 mesoenvironmental, 20 microenvironmental, and 6 combined) associated with health insurance fraud. We recognized the elements of fraud and its dependence on the legal framework and health coverage. From this analysis, we propose the following definition: "Health insurance fraud is an act of deception or intentional misrepresentation to obtain illegal benefits concerning the coverage provided by a health insurance company". Among the most relevant manifestations perpetuated by the provider are phantom billing, falsification of documents, and overutilization of services; the subscribers are identity fraud, misrepresentation of coverage and alteration of documents; and those perpetrated by the insurance company are false declarations of benefits and falsification of reimbursements. Of the 47 factors, 25 showed an experimental influence, including three in the macroenvironment: culture, regulations, and geography; five in the mesoenvironment: characteristics of provider, management policy, reputation, professional role and auditing; 12 in the microenvironment: sex, race, condition of insurance, language, treatments, chronic disease, future risk of disease, medications, morale, inequity, coinsurance, and the decisions of the claims-adjusters; and five combined factors: the relationships between beneficiary-provider, provider-insurance company, beneficiary-insurance company, managers and guanxi. CONCLUSIONS: The multifactorial nature of HIF and the characteristics of its manifestations depend on its definition; Identifying the influence of the factors will support subsequent attempts to combat HIF.

Dripping test to assessment the water content in frozen chicken carcases commercialized in Ji-Paraná, Rondônia, Brazil / Dripping test para avaliação do teor de água em carcaças de frango congeladas comercializadas em Ji-Paraná, Rondônia, Brasil

The growth in demand for chicken meat is due to the increase in demand for white meat, as they are considered tasty and at an attractive price. Therefore, the search for quality is essential. In Brazil, the water loss due to the melting of the carcasses is controlled by companies and by the Ministry of Agriculture, Livestock and Supply (MAPA) and, frequently, they analyze water loss from the carcasses above the limits required by the legislation. Given the assumption, the aimed of this study was to evaluate the water losses due to thawing in frozen chicken carcasses marketed in the municipality of Ji-Paraná, Rondônia, Brazil. There 25 carcasses of whole frozen chickens were evaluated, from six brands, lots and different establishments, submitted to standardized conditions for the performance of the Dripping test, in order to verify the percentage of water absorbed by the carcasses. It was found that 48% of the samples showed water loss beyond that allowed by the current legislation, which is 6%. When observing that almost half of the evaluated carcasses showed irregularities in relation to the legislation, it is understood that the companies that supply these products should be better inspected, carrying out Dripping test analyzes periodically to reduce or eliminate this type of crime.

O crescimento da demanda de carne de frango se deve ao aumento da procura de carnes brancas, por serem con-sideradas saborosas e com preço atrativo. Por isso, a busca pela qualidade é imprescindível. No Brasil, a perda de água pelo degelo das carcaças é controlada pelas empresas e pelo Ministério da Agricultura Pecuária e Abastecimento (MAPA) e, fre-quentemente, analisam perda de água das carcaças acima dos limites exigidos pela legislação. Diante do pressuposto, o obje-tivo desse estudo foi avaliar as perdas de água por degelo em carcaças de frango congeladas comercializadas no município de Ji-Paraná, Rondônia. Foram avaliadas 25 carcaças de frangos congelados inteiros, de seis marcas, lotes e estabelecimentos dis-tintos, submetidos a condições padronizadas para a realização do Dripping test, com a finalidade de verificar o percentual de água absorvida pelas carcaças. Constatou-se que 48% das amostras apresentaram perda de água além do permitido pela legis-lação vigente, que é de 6%. Ao observar que quase a metade das carcaças avaliadas apresentaram irregularidades frente à legis-lação, entende-se que as empresas fornecedoras desses produtos devem ser melhor fiscalizadas, realizando análises de Dripping test periodicamente para reduzir ou eliminar esse tipo de delito.

Dripping test to assessment the water content in frozen chicken carcases commercialized in Ji-Paraná, Rondônia, Brazil / Dripping test para avaliação do teor de água em carcaças de frango congeladas comercializadas em Ji-Paraná, Rondônia, Brasil

The growth in demand for chicken meat is due to the increase in demand for white meat, as they are considered tasty and at an attractive price. Therefore, the search for quality is essential. In Brazil, the water loss due to the melting of the carcasses is controlled by companies and by the Ministry of Agriculture, Livestock and Supply (MAPA) and, frequently, they analyze water loss from the carcasses above the limits required by the legislation. Given the assumption, the aimed of this study was to evaluate the water losses due to thawing in frozen chicken carcasses marketed in the municipality of Ji-Paraná, Rondônia, Brazil. There 25 carcasses of whole frozen chickens were evaluated, from six brands, lots and different establishments, submitted to standardized conditions for the performance of the Dripping test, in order to verify the percentage of water absorbed by the carcasses. It was found that 48% of the samples showed water loss beyond that allowed by the current legislation, which is 6%. When observing that almost half of the evaluated carcasses showed irregularities in relation to the legislation, it is understood that the companies that supply these products should be better inspected, carrying out Dripping test analyzes periodically to reduce or eliminate this type of crime.(AU)

O crescimento da demanda de carne de frango se deve ao aumento da procura de carnes brancas, por serem con-sideradas saborosas e com preço atrativo. Por isso, a busca pela qualidade é imprescindível. No Brasil, a perda de água pelo degelo das carcaças é controlada pelas empresas e pelo Ministério da Agricultura Pecuária e Abastecimento (MAPA) e, fre-quentemente, analisam perda de água das carcaças acima dos limites exigidos pela legislação. Diante do pressuposto, o obje-tivo desse estudo foi avaliar as perdas de água por degelo em carcaças de frango congeladas comercializadas no município de Ji-Paraná, Rondônia. Foram avaliadas 25 carcaças de frangos congelados inteiros, de seis marcas, lotes e estabelecimentos dis-tintos, submetidos a condições padronizadas para a realização do Dripping test, com a finalidade de verificar o percentual de água absorvida pelas carcaças. Constatou-se que 48% das amostras apresentaram perda de água além do permitido pela legis-lação vigente, que é de 6%. Ao observar que quase a metade das carcaças avaliadas apresentaram irregularidades frente à legis-lação, entende-se que as empresas fornecedoras desses produtos devem ser melhor fiscalizadas, realizando análises de Dripping test periodicamente para reduzir ou eliminar esse tipo de delito.(AU)

Validation of a method employing liquid chromatography to identify and quantify glycomacropeptide of casein in raw milk / Validación de un método mediante cromatografía líquida para identificar y cuantificar glicomacropéptido de caseína en la leche cruda

Background: The information on official testing methods, or regulatory methods in Colombia to test whey in milk is limited; this restriction of information goes against the possibility of mitigating the risk of food fraud. Objectives: The validation of an HPLC method to determine casein glycomacropeptide (c-GMP), a protein that countries such as Brazil, Spain, and Ecuador have used as an indicator of raw milk adulteration with whey, was carried out. Methods: A 10mL sample of raw milk is precipitated with 24% TCA using ultrasound, a process followed by filtration. The collected fraction ensured the separation of c-GMP and then injected into the liquid chromatography. Results: A 30 minutes analysis allowed the determination of c-GMP with a retention time of 12.9 ± 0.5 minutes. The performance characteristics method in the validation exercise were: recovery percentage 99.97%, linearity R2> 0.95; % RSD accuracy <5.3%. Conclusion, the method exhibits desirable attributes for the intended purpose

Antecedentes: En Colombia la información de dominio público en metodologías de análisis de lactosuero en leche es limitada, restringiendo la posibilidad de acceder a ellas para mitigar el riesgo de fraude alimentario. Objetivos: Se realizó validación de un método por HPLC para determinar en leche cruda c-GMP, proteína usada como indicador de adulteración en países como Brasil y Ecuador. Metodos: Una muestra de 10mL de leche cruda es precipitada con TCA al 24% empleando ultrasonido, proceso seguido por filtración. La fracción recolectada aseguró la separación del c-GMP para luego inyectar al cromatógrafo líquido. Resultados: La determinación de c-GMP permitió el análisis en 30 minutos con tiempo de retención de 12,9 ± 0,5 minutos. Las características de desempeño del método en el ejercicio de validación fueron: porcentaje de recuperación 99,97%, linealidad R2>0,95; precisión %RSD< 5,3%. Conclusión: el método al final del ejercicio exhibe atributos para el fin previsto

Standardization of a rapid quadruplex PCR method for the simultaneous detection of bovine, buffalo, Salmonella spp, and Listeria monocytogenes DNA in milk / [Padronização de um método rápido de PCR quadriplex para a detecção simultânea de DNA de bovino, bubalino, Salmonella spp. e Listeria monocytogenes em leite]

The objective of the present study was to Standardize a Polymerase Chain Reaction (PCR) protocol for the authentication of bovine and buffalo milk, and to detect the presence of Salmonella spp. and Listeria monocytogenes. For this, the target DNA was extracted, mixed, and subjected to a PCR assay. Milk samples were defrauded and experimentally contaminated with microorganisms to assess the detection of target DNA at different times of cultivation, bacterial titers, and concentration of genetic material. In addition, the protocol was tested with DNA extracted directly from food, without a pre-enrichment step. The proposed quadruplex PCR showed good accuracy in identifying target DNA sequences. It was possible to simultaneously identify all DNA sequences at the time of inoculation (0h), when the samples were contaminated with 2 CFU/250mL and with 6h of culture when the initial inoculum was 1 CFU/250mL. It was also possible to directly detect DNA sequences from the food when it was inoculated with 3 CFU/mL bacteria. Thus, the proposed methodology showed satisfactory performance, optimization of the analysis time, and a potential for the detection of microorganisms at low titers, which can be used for the detection of fraud and contamination.

O objetivo do presente estudo foi padronizar um protocolo de reação em cadeia da polimerase (PCR) para a autenticação de leite bovino e bubalino e a detecção da presença de Salmonella spp. e Listeria monocytogenes. Para isso, o DNA-alvo foi extraído, misturado e submetido ao ensaio de PCR. Amostras de leite foram fraudadas e contaminadas experimentalmente com os micro-organismos, para se avaliar a detecção do DNA-alvo em diferentes tempos de cultivo, os títulos bacterianos e a concentração de material genético. Além disso, o protocolo foi testado com DNA extraído diretamente do alimento, sem a etapa de pré-enriquecimento. A PCR quadriplex proposta mostrou boa precisão na identificação de sequências de DNA-alvo. Foi possível identificar simultaneamente todas as sequências de DNA no momento da inoculação (0h), quando as amostras estavam contaminadas com 2 UFC/250mL, e com seis horas de cultura, quando o inóculo inicial foi de 1 UFC/250mL. Também foi possível detectar diretamente as sequências de DNA do alimento quando este foi inoculado com 3 UFC/mL de bactérias. Dessa forma, a metodologia proposta apresentou desempenho satisfatório, otimização do tempo de análise e potencial para detecção de micro-organismos em baixos títulos, podendo ser utilizada para detecção de fraude e contaminação.

Honey authentication in terms of its adulteration with sugar syrups using UV-Vis spectroscopy and one-class classifiers.

This work proposes the use of UV-Vis spectroscopy and one-class classifiers to authenticate honey in terms of their individual and simultaneous adulterations with corn syrup, agave syrup, and sugarcane molasses. Then, spectra of aqueous authentic (n = 73) and adulterated (n = 162) honey samples were recorded. Before the construction of OC-PLS and DD-SIMCA models, different pre-processing techniques were used to removed baseline shifts. The best result obtained by DD-SIMCA using offset correction, correctly classifying all the samples in the test set. Therefore, the proposed methodology can be used as a promising tool to authenticate honey and prevent fraudulent labeling, affording security to consumers and providing an alternative to regulatory agencies. Moreover, it avoids laborious sample preparation and additional operational costs, since the analytical information is acquired using a routine instrumental technique, without the need for any sample preparation step, other than dilution of the samples in water alone.