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This study investigated the bioaccessibility of folate in wheat bread baked with different ingredients and processing methods. Next, different matrices were spiked with 5-methyltetrahydrofolate, gallic acid (GA), or both to investigate the stability of 5-methyltetrahydrofolate during in vitro digestion. The folate bioaccessibility in bread varied from 44 to 96%. The inclusion of whole-grain or faba bean flour significantly improved both folate content and bioaccessibility. Baking with yeast increased the folate content by 145% in bread but decreased folate bioaccessibility compared to the bread without added yeast because of the instability of 5-methyltetrahydrofolate. Spiking experiments confirmed oxidation as a critical reason for 5-methyltetrahydrofolate loss during digestion. However, GA protected this vitamer from degradation. Additionally, 5-methyltetrahydrofolate was less stable in whole-grain wheat matrices than other matrices. This study demonstrated that the stability of 5-methyltetrahydrofolate is crucial for folate bioaccessibility in bread, and methods for stabilizing this vitamer should be further studied.

Demand for plant-based meat alternatives has increased in recent years due to concerns about health, ethics, the environment, and animal welfare. Nevertheless, the market share of plant-based meat alternatives must increase significantly if they are to support sustainable food production and consumption. Flavor is an important limiting factor of the acceptability and marketability of plant-based meat alternatives. Undesirable chemosensory perceptions, such as a beany flavor, bitter taste, and astringency, are often associated with plant proteins and products that use them. This study reviewed 276 articles to answer the following five research questions: (1) What are the volatile and nonvolatile compounds responsible for off-flavors? (2) What are the mechanisms by which these flavor compounds are generated? (3) What is the influence of thermal extrusion cooking (the primary structuring technique to transform plant proteins into fibrous products that resemble meat in texture) on the flavor characteristics of plant proteins? (4) What techniques are used in measuring the flavor properties of plant-based proteins and products? (5) What strategies can be used to reduce off-flavors and improve the sensory appeal of plant-based meat alternatives? This article comprehensively discusses, for the first time, the flavor issues of plant-based meat alternatives and the technologies available to improve flavor and, ultimately, acceptability.

Both the liberation and stability of endogenous folate are relevant to the bioaccessibility of folate. Since folates are unstable, in addition to studying the natural folate content in foods, bioaccessibility should be considered. To understand folate changes during digestion, a mixture of standard folate compounds was subjected to a static in vitro gastrointestinal digestion assay. Next, different types of bread were analysed to study how food matrices influence folate bioaccessibility. Folates were identified and quantitated by a UHPLC-PDA/FL method. Folic acid and 10-formylfolic acid were stable throughout the digestion, and the conversions among formyl folates and 5,10-methenyltetrahydrofolate were triggered at the gastric phase. Tetrahydrofolate began to degrade during the oral phase and was lost completely during the gastric phase. During the intestinal phase, 5-methyltetrahydrofolate began to degrade and suffered a 60% loss. With bread matrices, folate conversions and the decrease of reduced folates were also common, but the extent of changes varied. Generally, rye breads had the highest (80–120%) bioaccessibility of folate, while oat breads had the lowest (31–102%). The high proportion of 5-methyltetrahydrofolate could result in low bioaccessibility because of its relatively low stability during digestion in bread matrices. An increase in 10-formylfolic acid content was observed for all the breads, but 10-formyldihydrofolate seemed to be more stable in rye breads than in oat and wheat breads. The results showed that folates undergo significant changes during digestion and that food matrices could be modified to affect these changes towards better folate bioaccessibility.

Demand for plant-based meat alternatives has increased in recent years due to concerns about health, ethics, the environment, and animal welfare. Nevertheless, the market share of plant-based meat alternatives must increase significantly if they are to support sustainable food production and consumption. Flavor is an important limiting factor of the acceptability and marketability of plant-based meat alternatives. Undesirable chemosensory perceptions, such as a beany flavor, bitter taste, and astringency, are often associated with plant proteins and products that use them. This study reviewed 276 articles to answer the following five research questions: (1) What are the volatile and nonvolatile compounds responsible for off-flavors? (2) What are the mechanisms by which these flavor compounds are generated? (3) What is the influence of thermal extrusion cooking (the primary structuring technique to transform plant proteins into fibrous products that resemble meat in texture) on the flavor characteristics of plant proteins? (4) What techniques are used in measuring the flavor properties of plant-based proteins and products? (5) What strategies can be used to reduce off-flavors and improve the sensory appeal of plant-based meat alternatives? This article comprehensively discusses, for the first time, the flavor issues of plant-based meat alternatives and the technologies available to improve flavor and, ultimately, acceptability.

The aim of our long-term research program is to improve the quality and quantity of amaranth production through mutation breeding using γ-radiation. In this paper, we present the characterization of the new variety ‘Zobor’ of A. hypochondriacus × A. hybridus developed by radiation-induced mutagenesis of hybrid K-433. Multiyear phenotypic characterization of an important yield parameter (1000-seed weight) showed that the studied mutant variety ‘Zobor’ has an advantage in seed weight over the nonirradiated control seeds of K-433 with predictable performance of this yield trait. ‘Zobor’ exhibited changes in seed morphometric parameters, starch particle size, and pasting properties with no change in amylose content and swelling power. Moreover, the seeds of ‘Zobor’ showed the significantly highest folate content among selected amaranth varieties. The mutant variety could, therefore, be interesting for the development of functional foods and as a low-management crop, attractive for cultivation in Europe.

Due to COVID-19, companies were forced to adopt new work processes, and reduce modern work environments such as collaboration spaces. Professionals from many fields were forced to work remotely, almost overnight. Little is known about the impact of such non-volunteer remote work on productivity, stress, and other key aspects of work performance. To further our understanding of the impacts of this situation and remote work in general, we conducted an exploratory study by studying 28 knowledge work professionals (researchers, software developers, interior designers, service designers, and development consultants) from the viewpoint of perceived productivity and aspects affecting it in this unusual setting. Early results showed the positive influence of self-efficacy and teamwork on productivity during remote work, while no moderating effect of measured physical stress on productivity either through the intrinsic or social factor was present. peerReviewed

Machine Learning (ML) has been taking significant evolutionary steps and provided sophisticated means in developing novel and smart, up-to-date applications. However, the development has also brought new types of hazards into the daylight that can have even destructive consequences required to be addressed. Evasion attacks are among the most utilized attacks that can be generated in adversarial settings during the system operation. In assumption, ML environment is benign, but in reality, perpetrators may exploit vulnerabilities to conduct these gradient-free or gradient-based malicious adversarial inference attacks towards cyber-physical systems (CPS), such as smart buildings. Evasion attacks provide a utility for perpetrators to modify, for example, a testing dataset of a victim ML-model. In this article, we conduct a literature review concerning evasion attacks and countermeasures and discuss how these attacks can be utilized in order to deceive the, i.e., CPS smart lock system’s ML-classifier to gain access to the smart building. peerReviewed

Cereals and legumes are rich in folate. However, due to the instability of folate, processing and digestion can induce significant folate loss. In this paper, folate bioaccessibility of faba bean, oat, rye and wheat flours and pastes was studied using a static in vitro digestion model. Folate bioaccessibility depended on food matrices, varying from 42% to 67% in flours and from 40% to 123% in pastes. Digestion was associated with the inter conversion of formyl folates, as well as the increase of oxidised vitamers and decrease of reduced vitamers. Especially in faba bean, 5-methyltetrahydrofolate showed surprisingly good stability both in digestion and heat treatment, resulting in high bioaccessibility. The physiological concentration of ascorbic acid did not stabilise folate in digestion; however, a higher level helped to maintain reduced vitamers. Heat treatment (10-min paste making) could improve folate bioaccessibility by liberating folate from the food matrices and by altering folate vitamer distribution.

Cereal-based fermented foods (CBFF) are frequently consumed by young children in West-Africa. Seven CBFF types (gelatinized doughs, porridges, dumplings, and fritters, made from corn, sorghum or pearl millet) were produced according to the commonly used methods in traditional production units in Burkina Faso. Their total folate content, analyzed using a microbiological method, was between 1.8 and 31.3 mu g/100 g fresh weight. Folate degradation occurred at several steps during the cereal grain processing into CBFF, for instance during debranning (-51%), soaking (-20% to -49%) and wet-milling (-39% to -59%). Conversely, fermentation increased the folate content of some CBFF (+ 9 to + 27%). Folate bioaccessibility, assessed using a static in vitro digestion model, ranged from 23% to 81%. The bioaccessible folate content was influenced by the total folate content, the food matrix structure, and folate stability. CBFF contribution to the reference folate intake for young children was at most 23%. This work generated new information on the influence of traditional processing on the vitamin B9 content of CBFF, and the first data on folate bioaccessibility in West African CBFF.

Deficiency of correctly implemented and robust defence leaves Internet of Things devices vulnerable to cyber threats, such as adversarial attacks. A perpetrator can utilize adversarial examples when attacking Machine Learning models used in a cloud data platform service. Adversarial examples are malicious inputs to ML-models that provide erroneous model outputs while appearing to be unmodified. This kind of attack can fool the classifier and can prevent ML-models from generalizing well and from learning high-level representation; instead, the ML-model learns superficial dataset regularity. This study focuses on investigating, detecting, and preventing adversarial attacks towards a cloud data platform in the cyber-physical context. peerReviewed

IoT sensors and sensor networks are widely employed in businesses. The common problem is a remarkable number of IoT device transactions are unencrypted. Lack of correctly implemented and robust defense leaves the organization's IoT devices vulnerable to numerous cyber threats, such as adversarial and man-in-the-middle attacks or malware infections. A perpetrator can utilize adversarial examples when attacking machine learning (ML) models, such as convolutional neural networks (CNN) or deep neural networks (DNN) used, e.g., in DaaS cloud data platform service of smart buildings. DaaS cloud data platform's function in this study is to connect data from multiple IoT sensors, databases, private on-premises cloud services, public or hybrid cloud services into a metadata database. This study focuses on reviewing adversarial attack threats towards artificial intelligence systems in the smart building's context where the DaaS cloud data platform services under various information propagation chain structures utilizing ML models and reviews. Adversarial examples can be malicious inputs to ML models providing erroneous model outputs while appearing to be unmodified in human eyes. This kind of attack can knock out the classifier, prevent ML model from generalizing well, and from learning high-level representation, but instead to learn superficial dataset regularity. The purpose of this study is to investigate, detect, and prevent cyber-attack vectors, such as adversarial attacks towards DaaS cloud data platform. peerReviewed

Gathering and utilizing stored data is gaining popularity and has become a crucial component of smart building infrastructure. The data collected can be stored, for example, into private, public, or hybrid cloud service infrastructure or distributed service by utilizing data platforms. The stored data can be used when implementing services, such as building automation (BAS). Cloud services, IoT sensors, and data platforms can face several kinds of cybersecurity attack vectors such as adversarial, AI-based, DoS/DDoS, insider attacks. If a perpetrator can penetrate the defenses of a data platform, she can cause significant harm to the system. For example, the perpetrator can disrupt a building’s automatic heating system or break the heating equipment by using a suitable attack vector for a data platform. This chapter focuses on examining possibilities to protect cloud storage or data platforms from incoming cyberattacks by using, for instance, artificial-intelligence-based tools or trained neural networks that can detect and prevent typical attack vectors. peerReviewed