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One of the significant challenges in scaling agile software development is organizing software development teams to ensure effective communication among members while equipping them with the capabilities to deliver business value independently. A formal approach to address this challenge involves modeling it as an optimization problem: given a professional staff, how can they be organized to optimize the number of communication channels, considering both intra-team and inter-team channels? In this article, we propose applying a set of bio-inspired algorithms to solve this problem. We introduce an enhancement that incorporates ensemble learning into the resolution process to achieve nearly optimal results. Ensemble learning integrates multiple machine-learning strategies with diverse characteristics to boost optimizer performance. Furthermore, the studied metaheuristics offer an excellent opportunity to explore their linear convergence, contingent on the exploration and exploitation phases. The results produce more precise definitions for team sizes, aligning with industry standards. Our approach demonstrates superior performance compared to the traditional versions of these algorithms.

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Arabinoxylans (AXs) are compounds with high nutritional value and applicability, including prebiotics or supplementary ingredients, in food manufacturing industries. Unfortunately, the recovery of AXs may require advanced separation and integrated strategies. Here, an analysis of the emerging techniques to extract AXs from cereals and their by-products is discussed. This review covers distinct methods implemented over the last 2-3 years, identifying that the type of method, extraction source, AX physicochemical properties and pre-treatment conditions are the main factors influencing the recovery yield. Alkaline extraction is among the most used methods nowadays, mostly due to its simplicity and high recovery yield. Concurrently, recovered AXs applied in food applications is timely reviewed, such as potential bread ingredient, prebiotic and as a wall material for probiotic encapsulation, in beer and non-alcoholic beverage manufacturing, complementary ingredient in bakery products and cookies, improvers in Chinese noodles, 3D food printing and designing of nanostructures for delivery platforms.

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As a current trend of fabricating healthier products, food manufacturing companies seek for natural-based food colorant aiming to replace the synthetic ones, which apart from meeting sensorial and organoleptic aspects, they can also act as health promoters offering additional added value. Carminic acid is a natural based food colorant typically found in several insect taxa. However, there are current approaches which pursue the production of this natural pigment via biotechnological synthesis. To date, this colorant has been intensively applied in the manufacture of several food items. Unfortunately, one of the main limitations deals with the establishment of the right protocol of extraction and purification of this component since there is no report analyzing the main extraction techniques for obtaining carminic acid. Therefore, this review, for the first time, comprehensively analyzes the ongoing strategies and protocols proposed by scientists towards either extraction or purification of carminic acid from its origin source, and from biotechnological systems. Emphasis has been focused on the main findings dealing with extraction techniques and the relevant insights in the field. A detailed discussion is provided on the advantages and drawbacks of the reported extraction and purification methods, main solvents used and their key interactions with target molecules.

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Diabetes mellitus type 2 (DM2) is the most common chronic disease worldwide, characterized mainly by increased glucose concentration in the blood and affecting several organs' functionality. The daily consumption of probiotic bacteria can help control diabetes and reduce the damage caused. Cell immobilization techniques are a powerful tool that provides physical cell protection to such probiotic bacteria against gastrointestinal conditions. We suggest that cell immobilization could be a significant vector for delivering a high quantity of viable probiotics to the gut, helping attenuate hyperglycemia in diabetic rats. Seventy male Wistar rats were used in this work. Nicotinamide was administrated via intraperitoneal injection 15 minutes before inducing type 2 diabetes (DM2), followed by a second intraperitoneal injection of streptozotocin to induce DM2. Rats were divided into seven groups. For 45 days, a specific treatment was applied to each group. The group of rats, supplied with immobilized Lactobacillus casei, showed a serum glucose concentration of 137 mg/dL, which was close to the one observed in the groups of healthy rats (117 mg/dL) and rats treated with metformin (155 mg/dL). The diabetic rats without treatment presented a higher serum glucose concentration (461 mg/dL). In the rats treated with immobilized L. casei, there was no biochemical parameter alteration, and the cell morphology of the analyzed tissues was similar to those of the healthy group. The consumption of immobilized L. casei could allow a high quantity of viable probiotics to be delivered to the gut, reducing serum glucose concentration by up to 70% compared to diabetic rats and reducing organ damage caused by diabetes.

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In recent decades, traditional food processing processes, such as homogenization, pasteurization, canning, drying, and smoking, among others, have been successfully applied to obtain, to some extent, acceptable food items [...].

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Melissa officinalis L. is a medicinal plant used worldwide for ethno-medical purposes. Today, it is grown everywhere; while it is known to originate from Southern Europe, it is now found around the world, from North America to New Zealand. The biological properties of this medicinal plant are mainly related to its high content of phytochemical (bioactive) compounds, such as flavonoids, polyphenolic compounds, aldehydes, glycosides and terpenes, among many other groups of substances. Among the main biological activities associated with this plant are antimicrobial activity (against fungi and bacteria), and antispasmodic, antioxidant and insomnia properties. Today, this plant is still used by society (as a natural medicine) to alleviate many other illnesses and symptoms. Therefore, in this perspective, we provide an update on the phytochemical profiling analysis of this plant, as well as the relationships of specific biological and pharmacological effects of specific phytochemicals. Currently, among the organic solvents, ethanol reveals the highest effectiveness for the solvent extraction of precious components (mainly rosmarinic acid). Additionally, our attention is devoted to current developments in the extraction and fractionation of the phytochemicals of M. officinalis, highlighting the ongoing progress of the main strategies that the research community has employed. Finally, after analyzing the literature, we suggest potential perspectives in the field of sustainable extraction and purification of the phytochemical present in the plant. For instance, some research gaps concern the application of cavitation-assisted extraction processes, which can effectively enhance mass transfer while reducing the particle size of the extracted material in situ. Meanwhile, membrane-assisted processes could be useful in the fractionation and purification of obtained extracts. On the other hand, further studies should include the application of ionic liquids and deep eutectic solvents (DES), including DESs of natural origin (NADES) and hydrophobic DESs (hDES), as extraction or fractionating solvents, along with new possibilities for effective extraction related to DESs formed in situ, assisted by mechanical mixing (mechanochemistry-based approach).

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Currently, ginger is one the most consumed plants when dealing with the treatments of various illnesses. So far, it is known that various biologically active molecules, such as gingerols, shogaols and zingerone, among others, are the main responsible for specific biological activities, opening a new window for its utilization as a nutraceutical in foods. In pioneering extraction processes, solvent extraction has been initially used for these applications; however, the drawbacks of this typical extraction method compared with other emergent separation techniques make it possible for the exploration of new extraction pathways, including microwave, ultrasound, supercritical, subcritical and pressurized-assisted extraction, along with three phase partitioning, high-speed counter current chromatography and magnetic solid phase extraction. To the best of our knowledge, there is no report documenting the recent studies and cases of study in this field. Therefore, we comprehensively review the progress and the latest findings (over the last five years) on research developments, including patents and emerging extraction methods, aiming at the purification of biologically active molecules (gingerols, shogaols and zingerone) contained in ginger. Over the course of this review, particular emphasis is devoted to breakthrough strategies and meaningful outcomes in ginger components extraction. Finally, dosage and safety concerns related to ginger extracts are also documented.

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The immunohistochemical (IHC) evaluation of epidermal growth factor 2 (HER2) for the diagnosis of breast cancer is still qualitative with a high degree of inter-observer variability, and thus requires the incorporation of complementary techniques such as fluorescent in situ hybridization (FISH) to resolve the diagnosis. Implementing automatic algorithms to classify IHC biomarkers is crucial for typifying the tumor and deciding on therapy for each patient with better performance. The present study aims to demonstrate that, using an explainable Machine Learning (ML) model for the classification of HER2 photomicrographs, it is possible to determine criteria to improve the value of IHC analysis. We trained a logistic regression-based supervised ML model with 393 IHC microscopy images from 131 patients, to discriminate between upregulated and normal expression of the HER2 protein. Pathologists' diagnoses (IHC only) vs. the final diagnosis complemented with FISH (IHC + FISH) were used as training outputs. Basic performance metrics and receiver operating characteristic curve analysis were used together with an explainability algorithm based on Shapley Additive exPlanations (SHAP) values to understand training differences. The model could discriminate amplified IHC from normal expression with better performance when the training output was the IHC + FISH final diagnosis (IHC vs. IHC + FISH: area under the curve, 0.94 vs. 0.81). This may be explained by the increased analytical impact of the membrane distribution criteria over the global intensity of the signal, according to SHAP value interpretation. The classification model improved its performance when the training input was the final diagnosis, downplaying the weighting of the intensity of the IHC signal, suggesting that to improve pathological diagnosis before FISH consultation, it is necessary to emphasize subcellular patterns of staining.

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The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which is related to new coronavirus disease (COVID-19) has mobilized several scientifics to explore clinical data using soft-computing approaches. In the context of machine learning, previous studies have explored supervised algorithms to predict and support diagnosis based on several clinical parameters from patients diagnosed with and without COVID-19. However, in most of them the decision is based on a "black-box" method, making it impossible to discover the variable relevance in decision making. Hence, in this study, we introduce a non-supervised clustering analysis with neural network self-organizing maps (SOM) as a strategy of decision-making. We propose to identify potential variables in routine blood tests that can support clinician decision-making during COVID-19 diagnosis at hospital admission, facilitating rapid medical intervention. Based on SOM features (visual relationships between clusters and identification of patterns and behaviors), and using linear discriminant analysis , it was possible to detect a group of units of the map with a discrimination power around 83% to SARS-CoV-2-positive patients. In addition, we identified some variables in admission blood tests (Leukocytes, Basophils, Eosinophils, and Red cell Distribution Width) that, in combination had strong influence in the clustering performance, which could assist a possible clinical decision. Thus, although with limitations, we believe that SOM can be used as a soft-computing approach to support clinician decision-making in the context of COVID-19.

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Nature-inspired computing is a promising field of artificial intelligence. This area is mainly devoted to designing computational models based on natural phenomena to address complex problems. Nature provides a rich source of inspiration for designing smart procedures capable of becoming powerful algorithms. Many of these procedures have been successfully developed to treat optimization problems, with impressive results. Nonetheless, for these algorithms to reach their maximum performance, a proper balance between the intensification and the diversification phases is required. The intensification generates a local solution around the best solution by exploiting a promising region. Diversification is responsible for finding new solutions when the main procedure is trapped in a local region. This procedure is usually carryout by non-deterministic fundamentals that do not necessarily provide the expected results. Here, we encounter the stagnation problem, which describes a scenario where the search for the optimum solution stalls before discovering a globally optimal solution. In this work, we propose an efficient technique for detecting and leaving local optimum regions based on Shannon entropy. This component can measure the uncertainty level of the observations taken from random variables. We employ this principle on three well-known population-based bio-inspired optimization algorithms: particle swarm optimization, bat optimization, and black hole algorithm. The proposal's performance is evidenced by solving twenty of the most challenging instances of the multidimensional knapsack problem. Computational results show that the proposed exploration approach is a legitimate alternative to manage the diversification of solutions since the improved techniques can generate a better distribution of the optimal values found. The best results are with the bat method, where in all instances, the enhanced solver with the Shannon exploration strategy works better than its native version. For the other two bio-inspired algorithms, the proposal operates significantly better in over 70% of instances.

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Since it is known that hyaluronic acid contributes to soft tissue growth, elasticity, and scar reduction, different strategies of producing HA have been explored in order to satisfy the current demand of HA in pharmaceutical products and formulations. The current interest deals with production via bacterial and yeast fermentation and extraction from animal sources; however, the main challenge is the right extraction technique and strategy since the original sources (e.g., fermentation broth) represent a complex system containing a number of components and solutes, which complicates the achievement of high extraction rates and purity. This review sheds light on the main pathways for the production of HA, advantages, and disadvantages, along with the current efforts in extracting and purifying this high-added-value molecule from different sources. Particular emphasis has been placed on specific case studies attempting production and successful recovery. For such works, full details are given together with their relevant outcomes.

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Nejayote is recognized as the main by-product resulting from the nixtamalization process of maize kernels, which is categorized as an alkaline residue with a chemical composition based on carbohydrates (37.8-55.7%), fiber (22.8-25.5%), protein (4.9-7.4%), and lipids (0.4-1.5%). In addition, Nejayote has an extensive content of simple (e.g., phenolic acids) and complex phenolic compounds (e.g., anthocyanins), which are responsible for the pigmentation and antioxidant activity of maize; therefore, there is a need of their identification depending on the type of maize. The current research has focused on the efficient extraction and identification of the phenolic acids contained in Nejayote after the processing of different types of maize. The target of this work was to fractionate Nejayote from white (NWM), red (NRM), and purple maize (NPM), using three different membranes, such as microfiltration (MF with a pore size of 1 µm) and ultrafiltration (UF100 and UF1 with a molecular weight cut-off of 100 kDa and 1 kDa, respectively), which were strategically applied to extract phenolic acids while retaining other molecules. Such a membrane system exhibited a retention in the first stage of almost all carbohydrates (MF-Retentate: ca. 12-19 g GE/L), while second stage (UF100-Permeate) a concentration of phenolic components was recovered ranging from 768 to 800 mg GAE/L. Finally, in the third stage (UF1-Permeate), 14 phenolic acids were identified, including ferulic and p-coumaric acids, derived from caffeic and ferulic acids, along with other molecules (e.g., glucose and fructose).

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Industries in the agro-food sector are the largest generators of waste in the world. Agro-food wastes and by products originate from the natural process of senescence, pretreatment, handling, and manufacturing processes of food and beverage products. Notably, most of the wastes are produced with the transformation of raw materials (such as fruits, vegetables, plants, tubers, cereals, and dairy products) into different processed foods (e.g., jams, sauces, and canned fruits/vegetables), dairy derivatives (e.g., cheese and yogurt), and alcoholic (e.g., wine and beer) and nonalcoholic beverages (e.g., juices and soft drinks). Current research is committed not only to the usage of agro-food wastes and by products as a potential source of high-value bioactive compounds (e.g., phenolic compounds, anthocyanins, and organic acids) but also to the implementation of emerging and innovative technologies that can compete with conventional extraction methods for the efficient extraction of such biomolecules from the residues. Herein, specific valorization technologies, such as membrane-based processes, microwave, ultrasound, pulsed electric-assisted extraction, supercritical/subcritical fluids, and pressurized liquids, have emerged as advanced techniques in extracting various added-value biomolecules, showing multiple advantages (improved extraction yields, reduced process time, and protection to the bioactive properties of the compounds). Hence, this comprehensive review aims to analyze the ongoing research on applying such techniques in valorization protocols. A last-five-year review, together with a featured analysis of the relevant findings in the field, is provided.

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Phenolic compounds have long been of great importance in the pharmaceutical, food, and cosmetic industries. Unfortunately, conventional extraction procedures have a high cost and are time consuming, and the solvents used can represent a safety risk for operators, consumers, and the environment. Deep eutectic solvents (DESs) are green alternatives for extraction processes, given their low or non-toxicity, biodegradability, and reusability. This review discusses the latest research (in the last two years) employing DESs for phenolic extraction, solvent components, extraction yields, extraction method characteristics, and reviewing the phenolic sources (natural products, by-products, wastes, etc.). This work also analyzes and discusses the most relevant DES-based studies for phenolic extraction from natural sources, their extraction strategies using DESs, their molecular mechanisms, and potential applications.

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The interest in microalgae production deals with its role as the third generation of feedstock to recover renewable energy. Today, there is a need to analyze the ultimate research and advances in recovering the microalgae biomass from the culture medium. Therefore, this review brings the current research developments (over the last three years) in the field of harvesting microalgae using membrane-based technologies (including microfiltration, ultrafiltration and forward osmosis). Initially, the principles of membrane technologies are given to outline the main parameters influencing their operation. The main strategies adopted by the research community for the harvesting of microalgae using membranes are subsequently addressed, paying particular attention to the novel achievements made for improving filtration performance and alleviating fouling. Moreover, this contribution also gives an overview of the advantages of applying membrane technologies for the efficient extraction of the high added-value compounds in microalgae cells, such as lipids, proteins and carbohydrates, which together with the production of renewable biofuels could boost the development of more sustainable and cost-effective microalgae biorefineries.

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Some of the current challenges faced by the food industry deal with the natural ripening process and the short shelf-life of fresh and minimally processed products. The loss of vitamins and minerals, lipid oxidation, enzymatic browning, and growth of microorganisms have been the main issues for many years within the innovation and improvement of food packaging, which seeks to preserve and protect the product until its consumption. Most of the conventional packaging are petroleum-derived plastics, which after product consumption becomes a major concern due to environmental damage provoked by their difficult degradation. In this sense, many researchers have shown interest in edible films and coatings, which represent an environmentally friendly alternative for food packaging. To date, chitosan (CS) is among the most common materials in the formulation of these biodegradable packaging together with polysaccharides, proteins, and lipids. The good film-forming and biological properties (i.e., antimicrobial, antifungal, and antiviral) of CS have fostered its usage in food packaging. Therefore, the goal of this paper is to collect and discuss the latest development works (over the last five years) aimed at using CS in the manufacture of edible films and coatings for food preservation. Particular attention has been devoted to relevant findings in the field, together with the novel preparation protocols of such biodegradable packaging. Finally, recent trends in new concepts of composite films and coatings are also addressed.

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Communicating in social and public environments are considered professional skills that can strongly influence career development. Therefore, it is important to proper train and evaluate students in this kind of abilities so that they can better interact in their professional relationships, during the resolution of problems, negotiations and conflict management. This is a complex problem as it involves corporal analysis and the assessment of aspects that until recently were almost impossible to quantitatively measure. Nowadays, a number of new technologies and sensors have being developed for the capture of different kinds of contextual and personal information, but these technologies were not yet fully integrated inside learning settings. In this context, this paper presents a framework to facilitate the analysis and detection of patterns of students in oral presentations. Four steps are proposed for the given framework: Data collection, Statistical Analysis, Clustering, and Sequential Pattern Mining. Data Collection step is responsible for the collection of students interactions during presentations and the arrangement of data for further analysis. Statistical Analysis provides a general understanding of the data collected by showing the differences and similarities of the presentations along the semester. The Clustering stage segments students into groups according to well-defined attributes helping to observe different corporal patterns of the students. Finally, Sequential Pattern Mining step complements the previous stages allowing the identification of sequential patterns of postures in the different groups. The framework was tested in a case study with data collected from 222 freshman students of Computer Engineering (CE) course at three different times during two different years. The analysis made it possible to segment the presenters into three distinct groups according to their corporal postures. The statistical analysis helped to assess how the postures of the students evolved throughout each year. The sequential pattern mining provided a complementary perspective for data evaluation and helped to observe the most frequent postural sequences of the students. Results show the framework could be used as a guidance to provide students automated feedback throughout their presentations and can serve as background information for future comparisons of students presentations from different undergraduate courses.

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Food preservation technologies are currently facing important challenges at extending the shelf-life of perishable food products (e.g., meat, fish, milk, eggs, and many raw fruits and vegetables) that help to meet the daily nutrient requirement demand. In addition, food preservation has gone beyond only preservation; the current techniques are focused on the fulfillment of two additional objectives, the suitability of the used processes and generation of environmentally friendly products with non-presence of any side effect on health. Moreover, they are also looking for additional nutritional properties. One of these preservation protocols deals with the use of edible films and coatings. Therefore, this review shows an overview of synthetic materials (e.g., glass, aluminum, plastic, and paperboard), as well as the regulations that limit their application in food packaging. Further, this review releases the current-state-of-the-art of the use of films and edible coatings as an alternative to conventional packaging, providing the main features that these biodegradable packaging should meet towards specific uses for the conservation and improvement of various food products. Herein, particular attention has been paid to the main used components (e.g., biopolymers, additives, bioactive, and probiotic components), manufacturing methods (for edible films or coatings) and their application to specific products. In addition, an outlook of the application of edible films and coatings as quality indicators of perishable products is shown.

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The production of worldwide nixtamalized products has increased in Latin American countries over the last years. For a better maize handling and exploitation of its nutritional elements, maize is subjected to a nixtamalization pretreatment protocol, which produces meaningful chemical, nutritional and quality changes in maize and its derived products, but large amounts of its primary by-product, well-known as 'nejayote', are also produced. Importantly, nejayote is usually discarded into the urbanized sewage with minimal treatment. Today, according to the recent research reports, new emerging techniques and protocols have been implemented to improve the nixtamalization products and by-products processing. New valorization approaches and biotechnological developments (including biotransformations) toward the reuse of nejayote have been developed according to its considerable content of biomolecules. Therefore, the goal of this paper is to provide a comprehensive review of the main development works at assisting nixtamalization products and by-products processing. Herein, particular attention is paid to experimental insights dealing with the valorization of nejayote.

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Steviol glycosides (SGs), as natural sweeteners from Stevia rebaudiana, are currently employed for replacing sugar and its derivatives in several food products and formulations. Such compounds play an essential role in human health. Their usage provides a positive effect on preventing diseases related to sugar consumption, including diabetes mellitus, cancer, and lipid metabolism disorders. The traditional extraction of SGs is performed by means of solvent extraction, which limits their application since the removal of residual solvents is a challenging task requiring further downstream purification steps. In addition, the presence of residual solvents negatively affects the quality of such compounds. Today, food technicians are looking for innovative and improved techniques for the extraction, recovery and purification of SGs. Membrane-based technologies, including microfiltration, ultrafiltration, and nanofiltration, have long been proven to be a valid alternative for efficient extraction and purification of several high added-value molecules from natural sources. Such processes and their possible coupling in integrated membrane systems have been successfully involved in recovery protocols of several compounds, such as metabolites, polyphenols, anthocyanins, natural pigments, proteins, from different sources (e.g., agro-food wastes, plant extracts, fruits, fermentation broths, among others). Herein, we aim to review the current progresses and developments about the extraction of SGs with membrane operations. Our attention has been paid to the latest insights in the field. Furthermore, key process parameters influencing the extraction and purification of SGs are also discussed in detail.

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