Search results for: artificial food

Authors: A. Rezazadeh, B Damari, S. Riazi-Esfahani, M. Hajian

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The consumption of junk food in Iran is alarmingly increasing. This study aimed to investigate the influencing factors of junk food consumption and amendable interventions that are criticized and approved by stakeholders, in order to presented to health policy makers. The articles and documents related to the content of study were collected by using the appropriate key words such as junk food, carbonated beverage, chocolate, candy, sweets, industrial fruit juices, potato chips, French fries, puffed corn, cakes, biscuits, sandwiches, prepared foods and popsicles, ice cream, bar, chewing gum, pastilles and snack, in scholar.google.com, pubmed.com, eric.ed.gov, cochrane.org, magiran.com, medlib.ir, irandoc.ac.ir, who.int, iranmedex.com, sid.ir, pubmed.org and sciencedirect.com databases. The main key points were extracted and included in a checklist and qualitatively analyzed. Then a summarized abstract was prepared in a format of a questionnaire to be presented to stakeholders. The design of this was qualitative (Delphi). According to this method, a questionnaire was prepared based on reviewing the articles and documents and it was emailed to stakeholders, who were asked to prioritize and choose the main problems and effective interventions. After three rounds, consensus was obtained.            Studies revealed high consumption of junk foods in the Iranian population, especially in children and adolescents. The most important affecting factors include availability, low price, media advertisements, preference of fast foods taste, the variety of the packages and their attractiveness, low awareness and changing in lifestyle. Main interventions recommended by stakeholders include developing a protective environment, educational interventions, increasing healthy food access and controlling media advertisements and putting pressure from the Industry and Mining Ministry on producers to produce healthy snacks. According to the findings, the results of this study may be proposed to public health policymakers as an advocacy paper and to be integrated in the interventional programs of Health and Education ministries and the media. Also, implementation of supportive meetings with the producers of alternative healthy products is suggested.

Keywords: junk foods, situation, qualitative study, Iran

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Authors: Praveen Chandramenon, Andrew Gascoyne, Fideline Tchuenbou-Magaia

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Aquaponics offers a simple conclusive solution to the food and environmental crisis of the world. This approach combines the idea of Aquaculture (growing fish) to Hydroponics (growing vegetables and plants in a soilless method). Smart Aquaponics explores the use of smart technology including artificial intelligence and IoT, to assist farmers with better decision making and online monitoring and control of the system. Identification of different growth stages of Swiss Chard plants and predicting its harvest time is found to be important in Aquaponic yield management. This paper brings out the comparative analysis of a standard Aquaponics with a Vermiponics (Aquaponics with worms), which was grown in the controlled environment, by implementing IoT and deep learning-based growth stage segregation and harvest time prediction of Swiss Chards before and after applying an optimal freshwater replenishment. Data collection, Growth stage classification and Harvest Time prediction has been performed with and without water replenishment. The paper discusses the experimental design, IoT and sensor communication with architecture, data collection process, image segmentation, various regression and classification models and error estimation used in the project. The paper concludes with the results comparison, including best models that performs growth stage segregation and harvest time prediction of the Aquaponic and Vermiponic testbed with and without freshwater replenishment.

Keywords: aquaponics, deep learning, internet of things, vermiponics

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Authors: Elisa Esposito, Johannes C. Jansen, Loredana Dellamuzia, Ugo Moretti, Lidietta Giorno

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The reduction of CO₂ emission into the atmosphere as a result of human activity is one of the most important environmental challenges to face in the next decennia. Emission of CO₂, related to the use of fossil fuels, is believed to be one of the main causes of global warming and climate change. In this scenario, the production of biomethane from organic waste, as a renewable energy source, is one of the most promising strategies to reduce fossil fuel consumption and greenhouse gas emission. Unfortunately, biogas upgrading still produces the greenhouse gas CO₂ as a waste product. Therefore, this work presents a case study on biogas upgrading, aimed at the simultaneous purification of methane and CO₂ via different steps, including CO₂/methane separation by polymeric membranes. The original objective of the project was the biogas upgrading to distribution grid quality methane, but the innovative aspect of this case study is the further purification of the captured CO₂, transforming it from a useless by-product to a pure gas with food-grade quality, suitable for commercial application in the food and beverage industry. The study was performed on a pilot plant constructed by Tecno Project Industriale Srl (TPI) Italy. This is a model of one of the largest biogas production and purification plants. The full-scale anaerobic digestion plant (Montello Spa, North Italy), has a digestive capacity of 400.000 ton of biomass/year and can treat 6.250 m3/hour of biogas from FORSU (organic fraction of solid urban waste). The entire upgrading process consists of a number of purifications steps: 1. Dehydration of the raw biogas by condensation. 2. Removal of trace impurities such as H₂S via absorption. 3.Separation of CO₂ and methane via a membrane separation process. 4. Removal of trace impurities from CO₂. The gas separation with polymeric membranes guarantees complete simultaneous removal of microorganisms. The chemical purity of the different process streams was analysed by a certified laboratory and was compared with the guidelines of the European Industrial Gases Association and the International Society of Beverage Technologists (EIGA/ISBT) for CO₂ used in the food industry. The microbiological purity was compared with the limit values defined in the European Collaborative Action. With a purity of 96-99 vol%, the purified methane respects the legal requirements for the household network. At the same time, the CO₂ reaches a purity of > 98.1% before, and 99.9% after the final distillation process. According to the EIGA/ISBT guidelines, the CO₂ proves to be chemically and microbiologically sufficiently pure to be suitable for food-grade applications.

Keywords: biogas, CO₂ separation, CO2 utilization, CO₂ food grade

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Authors: Chuanxiang Cheng, Tiantian Min, Jin Yue

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Antimicrobial active packaging enables extensive biological effects to improve food safety. However, the efficacy of antimicrobial packaging hinges on factors including the diffusion rate of the active agent toward the food surface, the initial content in the antimicrobial agent, and the targeted food shelf life. Among the possibilities of antimicrobial packaging design, an interesting approach involves the incorporation of volatile antimicrobial agents into the packaging material. In this case, the necessity for direct contact between the active packaging material and the food surface is mitigated, as the antimicrobial agent exerts its action through the packaging headspace atmosphere towards the food surface. However, it still remains difficult to achieve controlled and precise release of bioactive compounds to the specific target location with required quantity in food packaging applications. Remarkably, the development of stimuli-responsive materials for electrospinning has introduced the possibility of achieving controlled release of active agents under specific conditions, thereby yielding enduring biological effects. Relative humidity (RH) for the storage of food categories such as meat and aquatic products typically exceeds 90%. Consequently, high RH can be used as an abiotic trigger for the release of active agents to prevent microbial growth. Hence, a novel RH - responsive polyvinyl alcohol/chitosan (PVA/CS) composite nanofibrous film incorporated with 4-terpineol/β-cyclodextrin inclusion complexes (4-TA@β-CD ICs) was engineered by electrospinning that can be deposited as a functional packaging materials. The characterization results showed the thermal stability of the films was enhanced after the incorporation due to the hydrogen bonds between ICs and polymers. Remarkably, the 4 wt% 4-TA@β-CD ICs/PVA/CS film exhibited enhanced crystallinity, moderate hydrophilic (Water contact angle of 81.53°), light barrier property (Transparency of 1.96%) and water resistance (Water vapor permeability of 3.17 g mm/m2 h kPa). Moreover, this film also showed optimized mechanical performance with a Young’s modulus of 11.33 MPa, a tensile strength of 19.99 MPa and an elongation at break of 4.44 %. Notably, the antioxidant and antibacterial properties of this packaging material were significantly improved. The film demonstrated the half-inhibitory concentrations (IC50) values of 87.74% and 85.11% for scavenging 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2, 2′-azinobis (3-ethylbenzothiazoline-6-sulfonic) (ABTS) free radicals, respectively, in addition to an inhibition efficiency of 65% against Shewanella putrefaciens, the characteristic bacteria in aquatic products. Most importantly, the film achieved controlled release of 4-TA under high 98% RH by inducing the plasticization of polymers caused by water molecules, swelling of polymer chains, and destruction of hydrogen bonds within the cyclodextrin inclusion complex. Consequently, low relative humidity is suitable for the preservation of nanofibrous film, while high humidity conditions typical in fresh food packaging environments effectively stimulated the release of active compounds in the film. This film with a long-term antimicrobial effect successfully extended the shelf life of Litopenaeus vannamei shrimp to 7 days at 4 °C. This attractive design could pave the way for the development of new food packaging materials.

Keywords: controlled release, electrospinning, nanofibrous film, relative humidity–responsive, shrimp preservation

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

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The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter

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Authors: Soheila Sadeghi

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— The growing integration of Artificial Intelligence (AI) into Human Resources (HR) processes has transformed the way organizations manage recruitment, performance evaluation, and employee engagement. While AI offers numerous advantages—such as improved efficiency, reduced bias, and hyper-personalization—it raises significant concerns about employee well-being, job security, fairness, and transparency. The study examines how AI shapes employee perceptions, job satisfaction, mental health, and retention. Key findings reveal that: (a) while AI can enhance efficiency and reduce bias, it also raises concerns about job security, fairness, and privacy; (b) transparency in AI systems emerges as a critical factor in fostering trust and positive employee attitudes; and (c) AI systems can both support and undermine employee well-being, depending on how they are implemented and perceived. The research introduces an AI-employee well-being Interaction Framework, illustrating how AI influences employee perceptions, behaviors, and outcomes. Organizational strategies, such as (a) clear communication, (b) upskilling programs, and (c) employee involvement in AI implementation, are identified as crucial for mitigating negative impacts and enhancing positive outcomes. The study concludes that the successful integration of AI in HR requires a balanced approach that (a) prioritizes employee well-being, (b) facilitates human-AI collaboration, and (c) ensures ethical and transparent AI practices alongside technological advancement.

Keywords: artificial intelligence, human resources, employee well-being, job satisfaction, organizational support, transparency in AI

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Authors: Saksit Saengboon

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The study of English in Thailand receives comparatively little attention in the world of Englishes scholarship despite a complex and dynamic linguistic landscape. Like many countries in the region, English is used in predictable contexts, such as schools and at work. However, English is being increasingly used as a contact language among Thais and non-Thais, requiring much needed empirical attention. This study aims to address this neglected issue by examining how Thais perceive and use English in contemporary Thai society. This study explored the ways in which English has been used in public signage, mass media, especially about Thai food, and perceptions of Thais (N = 80) regarding English. Findings indicate that English in Thailand is used in a complicated manner portraying both standard and non-standard English. Thais still hold a static or traditional view of English, making it impractical, if not impossible, to have Thai English as an established variety.

Keywords: Thai english, thainess in english, public signage, mass media, thai food, thai linguistic landscape

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Authors: D. M. Bassuney, W. A. Ibrahim, Medhat A. E. Moustafa

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Appropriate start-up of an anaerobic baffled reactor (ABR) is considered to be the most delicate and important issue in the anaerobic process, and depends on several factors such as wastewater composition, reactor configuration, inoculum and operating conditions. In this work, the start-up performance of an ABR with working volume of 30 liters, fed continuously with synthetic food industrial wastewater along with semi-batch study to measure the methangenic activity by specific methanogenic activity (SMA) test were carried out at various organic loading rates (OLRs) to determine the best OLR used to start up the reactor. The comparison was based on COD removal efficiencies, start-up time, pH stability and methane production. An OLR of 1.8 Kg COD/m3d (5400 gCOD/m3 and 3 days HRT) showed best overall performance with COD removal efficiency of 94.44% after four days from the feeding and methane production of 3802 ml/L with an overall SMA of 0.36 gCH4-COD/gVS.d

Keywords: anaerobic baffled reactor, anaerobic reactor start-up, food industrial wastewater, specific methanogenic activity

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Authors: Juzhong Tan, William Kerr

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Roasting is one critical procedure in chocolate processing, where special favors are developed, moisture content is decreased, and better processing properties are developed. Therefore, determination of roasting degree of cocoa bean is important for chocolate manufacturers to ensure the quality of chocolate products, and it also decides the commercial value of cocoa beans collected from cocoa farmers. The roasting degree of cocoa beans currently relies on human specialists, who sometimes are biased, and chemical analysis, which take long time and are inaccessible to many manufacturers and farmers. In this study, a self-made electronic nose system consists of gas sensors (TGS 800 and 2000 series) was used to detecting the gas generated by cocoa beans with a different roasting degree (0min, 20min, 30min, and 40min) and the signals collected by gas sensors were used to train a three-layers ANN. Chemical analysis of the graded beans was operated by traditional GC-MS system and the contents of volatile chemical compounds were used to train another ANN as a reference to electronic nosed signals trained ANN. Both trained ANN were used to predict cocoa beans with a different roasting degree for validation. The best accuracy of grading achieved by electronic nose signals trained ANN (using signals from TGS 813 826 820 880 830 2620 2602 2610) turned out to be 96.7%, however, the GC trained ANN got the accuracy of 83.8%.

Keywords: artificial neutron network, cocoa bean, electronic nose, roasting

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Authors: Abdullah Ali Salamai

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Risk management in the construction supply chain (CSC) is vital in construction project risks. CSC has various risks affecting product quality and project timeline, such as operational, social, financial, technical, design, and safety risks. These risks should be mitigated in project construction. So, this paper proposed a set of technologies to overcome risks in CSC, like artificial intelligence (AI), blockchain, data analytics, and IoT, to select the best one. So, the multi-criteria decision-making (MCDM) methodology is used to deal with various risks. The Multi-Attribute Utility Theory (MAUT) method is used to rank technologies. The weights of risks are obtained by the average method by using the decision matrix. The MCDM methodology is integrated with a fuzzy set to overcome uncertainty data. Experts used triangular fuzzy numbers to express their opinions instead of exact numbers. These allow the model to overcome inconsistent and vague data. The MCDM methodology was applied to 18 risks and 5 technologies. The results show that social risks have the highest weight. AI is the best technology for overcoming risks in CSC. AI can integrate with CSC from raw data to final products to deliver to the user.

Keywords: risk management, construction supply chain, fuzzy sets, multi-criteria decision making, supply chain management, artificial intelligence, blockchain

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Authors: Nayab Kanwal, Noor Us Saher

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The management and utilization of food resources is becoming a big issue due to rapid urbanization, wastage and non-sustainable use of food, especially in developing countries. Therefore, the use of seafood as alternative sources is strongly promoted worldwide. Marine pollution strongly affects marine organisms, which ultimately decreases their export quality. The monitoring of contamination in marine organisms is a good indicator of the environmental quality as well as seafood quality. Monitoring the accumulation of chemical elements within various tissues of organisms has become a useful tool to survey current or chronic levels of heavy metal exposure within an environment. In this perspective, this study was carried out to compare the previous and current levels (Year 2012 and 2014) of heavy metals (Cd, Pb, Cr, Cu and Zn) in crabs marketed in Karachi and to estimate the toxicological risk associated with their intake. The accumulation of metals in marine organisms, both essential (Cu and Zn) and toxic (Pb, Cd and Cr), natural and anthropogenic, is an actual food safety issue. Significant (p>0.05) variations in metal concentrations were found in all crab species between the two years, with most of the metals showing high accumulation in 2012. For toxicological risk assessment, EWI (Estimated weekly intake), Target Hazard quotient (THQ) and cancer risk (CR) were also assessed and high EWI, Non- cancer risk (THQ < 1) showed that there is no serious threat associated with the consumption of shellfish species on Karachi coast. The Cancer risk showed the highest risk from Cd and Pb pollution if consumed in excess. We summarize key environmental health research on health effects associated with exposure to contaminated seafood. It could be concluded that considering the Pakistan coast, these edible species may be sensitive and vulnerable to the adverse effects of environmental contaminants; more attention should be paid to the Pb and Cd metal bioaccumulation and to toxicological risks to seafood and consumers.

Keywords: cancer risk, edible crabs, heavy metals pollution, risk assessment

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Authors: John K. Mensah, Mary A. Sword Sayer, Ryan L. Nadel, George Matusick, Zhaofei Fan, Lori G. Eckhardt

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Leptographium terebrantis is an opportunistic root pathogen commonly associated with loblolly pine (Pinus taeda L.) stands that are undergoing a loss of vigor in the southeastern US. In order to understand the relationship between L. terebrantis inoculum density and host physiology, an artificial inoculation study was conducted in a five-year-old naturally regenerated loblolly pine stand over a 24 week period in a completely randomized design. L. terebrantis caused sapwood occlusions that increased in severity as inoculum density increased. The occlusions significantly reduced water transport through the stem but did not interfere with fascicle-level stomatal conductance or induce moisture stress in the saplings. The resilience of stomatal conductance among pathogen-infested saplings is attributed to the growth and hydraulic function of new sapwood that developed after artificial inoculation. Results demonstrate that faster-growing families of loblolly pine may be capable of tolerating the vascular root disease when the formation of new sapwood is supported by sustained crown health.

Keywords: hydraulic conductance, inoculum density, Leptographium terebrantis, Pinus taeda, sapwood occlusion

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Authors: Gabriela Borilova, Monika Petrakova, Petr Kralik

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Nowadays, European producers are increasingly interested in the production of halal meat products. Halal meat has been increasingly appearing in the EU's market network and meat products from European producers are being exported to Islamic countries. Halal criteria are mainly related to the origin of muscle used in production, and also to the way products are obtained and processed. Although the EU has legislatively addressed the question of food authenticity, the circumstances of previous years when products with undeclared horse or poultry meat content appeared on EU markets raised the question of the effectiveness of control mechanisms. Replacement of expensive or not-available types of meat for low-priced meat has been on a global scale for a long time. Likewise, halal products may be contaminated (falsified) by pork or food components obtained from pigs. These components include collagen, offal, pork fat, mechanically separated pork, emulsifier, blood, dried blood, dried blood plasma, gelatin, and others. These substances can influence sensory properties of the meat products - color, aroma, flavor, consistency and texture or they are added for preservation and stabilization. Food manufacturers sometimes access these substances mainly due to their dense availability and low prices. However, the use of these substances is not always declared on the product packaging. Verification of the presence of declared ingredients, including the detection of undeclared ingredients, are among the basic control procedures for determining the authenticity of food. Molecular biology methods, based on DNA analysis, offer rapid and sensitive testing. The PCR method and its modification can be successfully used to identify animal species in single- and multi-ingredient raw and processed foods and qPCR is the first choice for food analysis. Like all PCR-based methods, it is simple to implement and its greatest advantage is the absence of post-PCR visualization by electrophoresis. qPCR allows detection of trace amounts of nucleic acids, and by comparing an unknown sample with a calibration curve, it can also provide information on the absolute quantity of individual components in the sample. Our study addresses a problem that is related to the fact that the molecular biological approach of most of the work associated with the identification and quantification of animal species is based on the construction of specific primers amplifying the selected section of the mitochondrial genome. In addition, the sections amplified in conventional PCR are relatively long (hundreds of bp) and unsuitable for use in qPCR, because in DNA fragmentation, amplification of long target sequences is quite limited. Our study focuses on finding a suitable genomic DNA target and optimizing qPCR to reduce variability and distortion of results, which is necessary for the correct interpretation of quantification results. In halal products, the impact of falsification of meat products by the addition of components derived from pigs is all the greater that it is not just about the economic aspect but above all about the religious and social aspect. This work was supported by the Ministry of Agriculture of the Czech Republic (QJ1530107).

Keywords: food fraud, halal food, pork, qPCR

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Authors: J. M. Kim, Y. W. Jung, E. Lee, Y. K. Kwack, , S. K. Sim*

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Cyanobacterial blooms in lakes, reservoirs, and rivers have been environmental and social issues due to its toxicity, odor, etc. Among the cyanotoxins, microcystins exist mostly within the cyanobacterial cells, and they are released from the cells. Therefore, an innovative technology is needed to detoxify the harvested microalgae for environment-friendly utilization of the harvested microalgae. This study develops detoxification method of microcystins in the harvested microalgae and recycling harvested microalgae with food waste using salt-tolerant mushroom strains and natural ecosystem decomposer. During this eco-friendly organic waste recycling process, diverse bacteria or various enzymes of the salt-tolerant mushroom strains decompose the microystins and cyclic peptides. Using PHLC/Mass analysis, it was verified that 99.8% of the microcystins of the harvested microalgae was detoxified in the harvested mushroom as well as in the recycled organic biomass. Further study is planned to verify the decomposition mechanisms of the microcystins by the bacteria or enzymes. In this study, the harvested microalgae is mixed with the food waste, and then the mixed toxic organic waste is used as mushroom compost by adjusting the water content of about 70% using cellulose such as sawdust cocopeats and cottonseeds. The mushroom compost is bottled, sterilized, and salt-tolerant mushroom spawn is inoculated. The mushroom is then cultured and growing in the temperature, humidity, and CO2 controlled environment. During the cultivation and growing process of the mushroom, microcystins are decomposed into non-toxic organic or inorganic compounds by diverse bacteria or various enzymes of the mushroom strains. Various enzymes of the mushroom strains decompose organics of the mixed organic waste and produce nutritious and antibiotic mushrooms. Cultured biomass compost after mushroom harvest can be used for organic fertilizer, functional bio-feed, and RE-100 biomass renewable energy source. In this eco-friendly organic waste recycling process, no toxic material, wastewater, nor sludge is generated; thus, sustainable with the circular economy.

Keywords: microalgae, microcystin, food waste, salt-tolerant mushroom strains, sustainability, circular economy

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Authors: É. Kónya, E. Szabó, I. Bata-Vidács, T. Deák, M. Ottucsák, N. Adányi, A. Székács

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Spice paprika is a major spice commodity in the European Union (EU), produced locally and imported from non-EU countries, reported not only for chemical and microbiological contamination, but also for fraud. The effective interaction between producers’ quality management practices and government and EU activities is described on the example of spice paprika production and control in Hungary, a country of leading spice paprika producer and per capita consumer in Europe. To demonstrate the importance of various contamination factors in the Hungarian production and EU trade of spice paprika, several aspects concerning food safety of this commodity are presented. Alerts in the Rapid Alert System for Food and Feed (RASFF) of the EU between 2005 and 2013, as well as Hungarian state inspection results on spice paprika in 2004 are discussed, and quality non-compliance claims regarding spice paprika among EU member states are summarized in by means of network analysis. Quality assurance measures established along the spice paprika production technology chain at the leading Hungarian spice paprika manufacturer, Kalocsai Fűszerpaprika Zrt. are surveyed with main critical control points identified. The structure and operation of the Hungarian state food safety inspection system is described. Concerted performance of the latter two quality management systems illustrates the effective interaction between internal (manufacturer) and external (state) quality control measures.

Keywords: spice paprika, quality control, reporting mechanisms, RASFF, vulnerable points, HACCP

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Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

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This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: product recommender system, ensemble technique, association rules, decision tree, artificial neural networks

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Authors: V. Shapaval, N. K. Afseth, D. Tzimorotas, A. Kohler

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Globally there is a dramatic increase in the demand for food, energy, materials and clean water since natural resources are limited. As a result, industries are looking for ways to reduce rest materials and to improve resource efficiency. Microorganisms have a high potential to be used as bio factories for the production of primary and secondary metabolites that represent high-value bio-products (enzymes, polyunsaturated fatty acids, bio-plastics, glucans, etc.). In order to find good microbial producers, to design suitable substrates from food rest materials and to optimize fermentation conditions, rapid analytical techniques for quantifying target bio products in microbial cells are needed. In the EU project FUST (R4SME, Fp7), we have developed a fully automated high-throughput FUST system based on micro-cultivation and FTIR spectroscopy that facilitates the screening of microorganisms, substrates and fermentation conditions for the optimization of the production of different high-value metabolites (single cell oils, bio plastics). The automated system allows the preparation of 100 samples per hour. Currently, The FUST system is in use for screening of filamentous fungi in order to find oleaginous strains with the ability to produce polyunsaturated fatty acids, and the optimization of cheap substrates, derived from food rest materials, and the optimization of fermentation conditions for the high yield of single cell oil.

Keywords: FTIR spectroscopy, FUST system, screening, biotechnology

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Authors: Natela Gerliani, Mohammed Aider

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Nowadays, the interest of using sustainable technologies for protein extraction from underutilized oilseeds is growing. Currently, a major disposal problem for the oil industry is by-products of plant food processing such as soybean meal. That is why valorization of soybean meal is important for the oil industry since it contains high-quality proteins and other valuable components. Generally, soybean meal is used in livestock and poultry feed but is rarely used in human feed. Though chemical composition of this meal compensate nutritional deficiency and can be used to balance protein in human food. Regarding the efficiency of soybean meal valorization, extraction is a key process for obtaining enriched protein ingredient, which can be incorporated into the food matrix. However, most of the food components such as proteins extracted from oilseeds by-products imply the utilization of organic and inorganic chemicals (e.g. acids, bases, TCA-acetone) having a significant environmental impact. In a context of sustainable production, the use of an electro-activation technology seems to be a good alternative. Indeed, the electro-activation technology requires only water, food grade salt and electricity as main materials. Moreover, this innovative technology helps to avoid special equipment and trainings for workers safety as well as transport and storage of hazardous materials. Electro-activation is a technology based on applied electrochemistry for the generation of acidic and alkaline solutions on the basis of the oxidation-reduction reactions that occur at the vicinity electrode/solution interfaces. It is an eco-friendly process that can be used to replace the conventional acidic and alkaline extraction. In this research, the electro-activation technology for protein extraction from soybean meal was carried out in the electro-activation reactor. This reactor consists of three compartments separated by cation and anion exchange membranes that allow creating non-contacting acidic and basic solutions. Different current intensities (150 mA, 300 mA and 450 mA) and treatment durations (10 min, 30 min and 50 min) were tested. The results showed that the extracts obtained by the electro-activation method have good quality in comparison to conventional extracts. For instance, extractability obtained with electro-activation method was 55% whereas with the conventional method it was only 36%. Moreover, a maximum protein quantity of 48 % in the extract was obtained with the electro-activation technology comparing to the maximum amount of protein obtained by conventional extraction of 41 %. Hence, the environmentally sustainable electro-activation technology seems to be a promising type of protein extraction that can replace conventional extraction technology.

Keywords: by-products, eco-friendly technology, electro-activation, soybean meal

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Authors: Mandeep Saini

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The rapid advancement of Artificial Intelligence (AI) is transforming various fields, including intellectual property law. This paper explores the emerging role of AI in interpreting patent claims, a critical and highly specialized area within intellectual property rights. Patent claims define the scope of legal protection granted to an invention, and their precise interpretation is crucial in determining the boundaries of the patent holder's rights. Traditionally, this interpretation has relied heavily on the expertise of patent examiners, legal professionals, and judges. However, the increasing complexity of modern inventions, especially in fields like biotechnology, software, and electronics, poses significant challenges to human interpretation. Introducing AI into patent claim interpretation raises several legal and ethical concerns. This paper addresses critical issues such as the reliability of AI-driven interpretations, the potential for algorithmic bias, and the lack of transparency in AI decision-making processes. It considers the legal implications of relying on AI, particularly regarding accountability for errors and the potential challenges to AI interpretations in court. The paper includes a comparative study of AI-driven patent claim interpretations versus human interpretations across different jurisdictions to provide a comprehensive analysis. This comparison highlights the variations in legal standards and practices, offering insights into how AI could impact the harmonization of international patent laws. The paper proposes policy recommendations for the responsible use of AI in patent law. It suggests legal frameworks that ensure AI tools complement, rather than replace, human expertise in patent claim interpretation. These recommendations aim to balance the benefits of AI with the need for maintaining trust, transparency, and fairness in the legal process. By addressing these critical issues, this research contributes to the ongoing discourse on integrating AI into the legal field, specifically within intellectual property rights. It provides a forward-looking perspective on how AI could reshape patent law, offering both opportunities for innovation and challenges that must be carefully managed to protect the integrity of the legal system.

Keywords: artificial intelligence (ai), patent claim interpretation, intellectual property rights, algorithmic bias, natural language processing, patent law harmonization, legal ethics

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Authors: Yazdan Moradi

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Spirulina platensis is a blue-green microalga with unique nutrient content and has many nutritional and therapeutic effects that are used to enrich various foods. The purpose of this research was to investigate the effect of Spirulina platensis microalgae on the nutritional value and sensory and physical properties of four different cereal-based products. For this purpose, spirulina microalgae dry powder with amounts of 0.25, 0.5, 0.75, and 1 is added to the formula of pasta, bulk bread, layered sweets, and cupcakes. A sample without microalgae powder of each product is also considered as a control. The results showed that adding Spirulina powder to the formulation of selected foods significantly changed the nutrition value and sensory and physical characteristics. Comparison to control protein increased in the samples containing spirulina powder. The increase in protein was about 1, 0.6, 1.2 and 1.1 percent in bread, cake, layered sweets and Pasta, respectively. The iron content of samples, including Spirulina, also increased. The increase was 0.6, 2, 5 and 18 percent in bread, cake, layered sweets and Pasta respectively. Sensory evaluation analysis showed that all products had an acceptable acceptance score. The instrumental analysis of L*, a*, and b* color indices showed that the increase of spirulina caused green color in the treatments, and this color change is more significant in the bread and pasta samples. The results of texture analysis showed that adding spirulina to selected food products reduces the hardness of the samples. No significant differences were observed in fat content in samples, including spirulina samples and control. However, fatty acid content and a trace amount of EPA found in samples included 1% spirulina. Added spirulina powder to food ingredients also changed the amino acid profile, especially essential amino acids. An increase of histidine, isoleucine, leucine, tryptophan, and valine in samples, including Spirulina was observed.

Keywords: spirulina, nutrition, Alge, iron, food

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Authors: Osagbai Joshua Eriki, Ngozi Agunwamba, Alice Hill, Lorna Almond, Maniya Duffy, Devashini Naidoo, David Ho, Raman Deo

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Aims: To evaluate the baseline eating pattern in a psychiatric hospital through quantifying purchases of food and drink items at the hospital shop and to implement a traffic light healthy eating labeling system. Method: A electronic till with reporting capabilities was purchased. A two-week period of baseline data collection was conducted. Thereafter, a system for labeling items based on the nutritional value of the food items at the hospital shop was implemented. Green labeling represented the items with the lowest calories and red the most. Further data was collated on the number and types of items purchased by patients according to the category, and the initial effectiveness of the system was evaluated. Result: Despite the implementation of the traffic light system, the red category had the highest number of items purchased by patients, highlighting the importance of promoting healthy eating choices. However, the study also showed that the system was effective in promoting healthy options, as the number of items purchased from the green category increased during the study period. Conclusion: The implementation of a traffic light labeling system for items sold at the hospital shop offers a promising approach to promoting healthy eating habits and choices. This is likely to contribute to a toolkit of measures when considering the multifactorial challenges that obesity and weight issues pose for long-stay psychiatric inpatients

Keywords: mental health, nutrition, food, healthy

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Authors: James V. Luisi

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Understanding consciousness requires a synthesis of ideas from multiple disciplines, including obvious ones like psychology, biology, evolution, neurology, and neuroscience, as well as less obvious ones like protozoology, botany, entomology, carcinology, herpetology, mammalogy, and computer sciences. Furthermore, to incorporate the necessary backdrop, it is best presented in a theme of Eastern philosophy, specifically leveraging the teachings of Buddhism for its relevance to early thought on consciousness. These ideas are presented as a multi-level framework that illustrates the various aspects of consciousness within a tapestry of foundational and dependent building blocks as to how living organisms evolved to understand elements of their reality sufficiently to survive, and in the case of Homo sapiens, eventually move beyond meeting the basic needs of survival, but to also achieve survival of the species beyond the eventual fate of our planet. This is not a complete system of thought, but just a framework of consciousness gathering some of the key elements regarding the evolution of consciousness and the advent of free will, and presenting them in a unique way that encourages readers to continue the dialog and thought process as an experience to enjoy long after reading the last page. Readers are encouraged to think for themselves about the issues raised herein and to question every facet presented, as much further exploration is needed. Needless to say, this subject will remain a rapidly evolving one for quite some time to come, and it is probably in the interests of everyone to at least consider attaining both an ability and willingness to participate in the dialog.

Keywords: consciousness, sentience, intelligence, artificial intelligence, Buddhism

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Authors: M. T. Artese, G. Ciocca, I. Gagliardi

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Food is a social and cultural aspect of every individual. Food products, processing, and traditions have been identified as cultural objects carrying history and identity of social groups. Traditional recipes are passed down from one generation to the other, often to strengthen the link with the territory. The paper presents CookIT, a web portal developed to collect Italian traditional recipes related to regional cuisine, with the purpose to disseminate the knowledge of typical Italian recipes and the Mediterranean diet which is a significant part of Italian cuisine. The system designed is completed with multimodal means of browsing and data retrieval. Stored recipes can be retrieved integrating and combining a number of different methods and keys, while the results are displayed using classical styles, such as list and mosaic, and also using maps and graphs, with which users can play using available keys for interaction.

Keywords: collaborative portal, Italian cuisine, intangible cultural heritage, traditional recipes, searching and browsing

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Authors: Damien P. Fevre, Peter K. Dearden

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Honeybee population sustainability is a critical concern for environmental stability and human food security. The success of a colony relies heavily on the egg-laying capacity of the queen, as it determines the production of thousands of worker bees who, in turn, perform essential functions in foraging and transforming food to make it digestible for the colony. The main sources of nutrition for honeybees are nectar, providing carbohydrates, and pollen, providing protein. This study delves into the impact of the proportion of these macronutrients on the food consumption patterns of nurse bees responsible for feeding the queen and how it affects the characteristics of the eggs produced. Using nutritional geometry, qRT-PCR, and RNA-seq analysis, this study sheds light on the pivotal role of nutrition in influencing gene expression in nurse bees, honeybee queen egg-laying capacity and embryonic development. Interestingly, while nutrition is crucial, the queen's genotype plays an even more significant role in this complex relationship, highlighting the importance of genotype-by-environment interactions. Understanding the interplay between genotype and nutrition is key to optimizing beekeeping management and strategic queen breeding practices. The findings from this study have significant implications for beekeeping practices, emphasizing the need for an appropriate nutrition to support the social nutrition of Apis mellifera. Implementing these insights can lead to improved colony health, increased productivity, and sustainable honeybee conservation efforts.

Keywords: honeybee, egg-laying, nutrition, transcriptomics

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Sonia Anand Knowlton

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As the use of Artificial Intelligence is becoming increasingly integrated in virtually every area of life, the need and interest to logically formalize the law and judicial reasoning is growing tremendously. The study of argumentation frameworks (AFs) provides promise in this respect. AF’s provide a way of structuring human reasoning using a formal system of non-monotonic logic. P.M. Dung first introduced this framework and demonstrated that certain arguments must prevail and certain arguments must perish based on whether they are logically “attacked” by other arguments. Dung labelled the set of prevailing arguments as the “preferred extension” of the given argumentation framework. Trevor Bench-Capon’s Value-based Argumentation Frameworks extended Dung’s AF system by allowing arguments to derive their force from the promotion of “preferred” values. In VAF systems, the success of an attack from argument A to argument B (i.e., the triumph of argument A) requires that argument B does not promote a value that is preferred to argument A. There has been thorough discussion of the application of VAFs to the law within the computer science literature, mainly demonstrating that legal cases can be effectively mapped out using VAFs. This article analyses VAFs from a jurisprudential standpoint to provide a philosophical and theoretical analysis of what VAFs tell the legal community about the judicial reasoning, specifically distinguishing between legal and moral reasoning. It highlights the limitations of using VAFs to account for judicial moral reasoning in theory and in practice.

Keywords: nonmonotonic logic, legal formalization, computer science, artificial intelligence, morality

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Authors: S. Rustagi, N. S. Sodhi, B. Dhillon, T. Kaur

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The objective of this study was to check whether there is any relationship between electromyographic (EMG) and textural parameters during food texture evaluation. In this study, a total of eighteen mastication variables were measured for entire mastication, per chew mastication and three different stages of mastication (viz. early, middle and late) by EMG for five different foods using eight human subjects. Cluster analysis was used to reduce the number of mastication variables from 18 to 5, so that principal component analysis (PCA) could be applied on them. The PCA further resulted in two meaningful principal components. The principal component scores for each food were measured and correlated with five textural parameters (viz. hardness, cohesiveness, chewiness, gumminess and adhesiveness). Correlation coefficients were found to be statistically significant (p < 0.10) for cohesiveness and adhesiveness while if we reduce the significance level (p < 0.20) then chewiness also showed correlation with mastication parameters.

Keywords: electromyography, mastication, sensory, texture

Procedia PDF Downloads 337

Authors: McKenna Halverson, Allison Karpyn

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Introduction: The COVID-19 pandemic posed unprecedented challenges for families with young children in the United States. The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), a federal nutrition assistance program that provides low-income mothers and young children with access to healthy foods (e.g., infant formula, milk, and peanut butter), mitigated some financial challenges for families. However, the U.S. experienced a national infant formula shortage and rising inflation rates during the pandemic, which likely impacted WIC participants’ shopping experiences and well-being. As such, this study aimed to characterize how the COVID-19 pandemic and related events impacted Delaware WIC participants’ in-store benefit redemption experiences and overall well-being. Method: The authors conducted semi-structured interviews with 51 WIC participants in Wilmington, Delaware. Survey measures included demographic questions and open-ended questions regarding participants’ experiences with WIC benefit redemption during the COVID-19 pandemic. Data were analyzed using a hybrid inductive and deductive coding approach. Findings: The COVID-19 pandemic significantly impacted WIC participants’ shopping experiences and well-being. Specifically, participants were forced to alter their shopping behaviors to account for rising food prices (e.g., used coupons, bought less food, used food banks). Additionally, WIC participants experienced significant distress during the national infant formula shortage resulting from difficulty finding formula to feed their children. Participants also struggled with in-store benefit redemption due to inconsistencies in shelf labelling, the WIC app, and low stock of WIC foods. These findings highlight the need to reexamine WIC operations and emergency food response policy in the United States during times of crisis to optimize public health and ensure federal nutrition assistance programs meeting the needs of low-income families with young children.

Keywords: benefit redemption, COVID-19 pandemic, infant formula shortage, inflation, shopping, WIC

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Authors: Dong Hwi Kim, Dharaneedharan Subramanian, So Hyun Park, Ha-Ri Choi, Ji-Hyung Kim, Dong-Hoon Lee, Moon Soo Heo

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The present study was performed to evaluate the use of Bacillus amyloliquefaciens JFP-2 isolated from a traditional fermented sea food, as probiotic bacteria in the diets for Rock-bream, Oplegnathus faciatus. A total of 180 fish (187.4 ± 2.7 g) were divided into two groups, control (C) and probiotic (P) group (90 fish per group) in triplicate. C group was fed with basal diet without probiotic, while P group was fed with B. amyloliquefaciens spores at concentration of 1.4 x 106 colony forming units per gram (CFU/g) of feed. After two months of feeding experiments, P group fish showed significant improvements in body weight (BW), weight gain (WG), specific growth rate (SGR) and food conversion ratio (FCR) compared with C group. Also, bi-weekly assessment of serum protein, glucose, fatty acid profile showed a significant increase in probiotic fed fish than that of control fish group. Similar increase in serum antioxidant and lysozyme activity was found in probiotic fed fish group. Twenty days challenge experiment shows decrease mortality in probiotic fed fish group when compared with that of control group. Hence, these results indicate that the use of B. amyloliquefaciens JFP-2 as a feed supplement, is beneficial to improve the health status of Oplegnathus fasciatus challenged with Vibrio anguillarum.

Keywords: Bacillus amyloliquefaciens, Oplegnathus fasciatus, probiotic feed, rock bream

Procedia PDF Downloads 255

Authors: Waleed Afandi

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Artificial intelligence (AI) has rapidly transformed various sectors, including education. This paper explores the integration of AI in education, emphasizing its potential to revolutionize learning processes, enhance teaching methodologies, and personalize education. We examine the historical context of AI in education, current applications, and the potential challenges and ethical considerations associated with its implementation. By reviewing a wide range of literature, this study aims to provide a comprehensive understanding of how AI can be leveraged to improve educational outcomes and the future directions of AI-driven educational innovations. Additionally, the paper discusses the impact of AI on student engagement, teacher support, and administrative efficiency. Case studies highlighting successful AI applications in diverse educational settings are presented, showcasing the practical benefits and real-world implications. The analysis also addresses potential disparities in access to AI technologies and suggests strategies to ensure equitable implementation. Through a balanced examination of the promises and pitfalls of AI in education, this study seeks to inform educators, policymakers, and technologists about the optimal pathways for integrating AI to foster an inclusive, effective, and innovative educational environment.

Keywords: artificial intelligence, education, personalized learning, teaching methodologies, educational outcomes, AI applications, student engagement, teacher support, administrative efficiency, equity in education

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