bluuebunny/crossref_metadata_2025 huggingface dataset:
Deng Entropy Weighted Risk Priority Number Model for Failure Mode and Effects Analysis
Authors: Zheng Haixia , Tang Yongchuan
Published: March 2020

Failure mode and effects analysis (FMEA), as a commonly used risk management method, has been extensively applied to the engineering domain. A vital parameter in FMEA is the risk priority number (RPN), which is the product of occurrence (O), severity (S), and detection (D) of a failure mode. To deal with the uncertainty in the assessments given by domain experts, a novel Deng entropy weighted risk priority number (DEWRPN) for FMEA is proposed in the framework of Dempster–Shafer evidence theory (DST). DEWRPN takes into consideration the relative importance in both risk factors and FMEA experts. The uncertain degree of objective assessments coming from experts are measured by the Deng entropy. An expert’s weight is comprised of the three risk factors’ weights obtained independently from expert’s assessments. In DEWRPN, the strategy of assigning weight for each expert is flexible and compatible to the real decision-making situation. The entropy-based relative weight symbolizes the relative importance. In detail, the higher the uncertain degree of a risk factor from an expert is, the lower the weight of the corresponding risk factor will be and vice versa. We utilize Deng entropy to construct the exponential weight of each risk factor as well as an expert’s relative importance on an FMEA item in a state-of-the-art way. A case study is adopted to verify the practicability and effectiveness of the proposed model.
Surfing on Fitness Landscapes: A Boost on Optimization by Fourier Surrogate Modeling
Authors: Manzoni Luca , Papetti Daniele M. , Cazzaniga Paolo , Spolaor Simone , Mauri Giancarlo , Besozzi Daniela , Nobile Marco S.
Published: March 2020

Surfing in rough waters is not always as fun as wave riding the “big one”. Similarly, in optimization problems, fitness landscapes with a huge number of local optima make the search for the global optimum a hard and generally annoying game. Computational Intelligence optimization metaheuristics use a set of individuals that “surf” across the fitness landscape, sharing and exploiting pieces of information about local fitness values in a joint effort to find out the global optimum. In this context, we designed surF, a novel surrogate modeling technique that leverages the discrete Fourier transform to generate a smoother, and possibly easier to explore, fitness landscape. The rationale behind this idea is that filtering out the high frequencies of the fitness function and keeping only its partial information (i.e., the low frequencies) can actually be beneficial in the optimization process. We prove our theory by combining surF with a settings free variant of Particle Swarm Optimization (PSO) based on Fuzzy Logic, called Fuzzy Self-Tuning PSO. Specifically, we introduce a new algorithm, named F3ST-PSO, which performs a preliminary exploration on the surrogate model followed by a second optimization using the actual fitness function. We show that F3ST-PSO can lead to improved performances, notably using the same budget of fitness evaluations.
Entropy Dynamics of Phonon Quantum States Generated by Optical Excitation of a Two-Level System
Authors: Hahn Thilo , Wigger Daniel , Kuhn Tilmann
Published: March 2020

In quantum physics, two prototypical model systems stand out due to their wide range of applications. These are the two-level system (TLS) and the harmonic oscillator. The former is often an ideal model for confined charge or spin systems and the latter for lattice vibrations, i.e., phonons. Here, we couple these two systems, which leads to numerous fascinating physical phenomena. Practically, we consider different optical excitations and decay scenarios of a TLS, focusing on the generated dynamics of a single phonon mode that couples to the TLS. Special emphasis is placed on the entropy of the different parts of the system, predominantly the phonons. While, without any decay, the entire system is always in a pure state, resulting in a vanishing entropy, the complex interplay between the single parts results in non-vanishing respective entanglement entropies and non-trivial dynamics of them. Taking a decay of the TLS into account leads to a non-vanishing entropy of the full system and additional aspects in its dynamics. We demonstrate that all aspects of the entropy’s behavior can be traced back to the purity of the states and are illustrated by phonon Wigner functions in phase space.
Generalizations of Fano’s Inequality for Conditional Information Measures via Majorization Theory
Authors: Sakai Yuta
Published: March 2020

Fano’s inequality is one of the most elementary, ubiquitous, and important tools in information theory. Using majorization theory, Fano’s inequality is generalized to a broad class of information measures, which contains those of Shannon and Rényi. When specialized to these measures, it recovers and generalizes the classical inequalities. Key to the derivation is the construction of an appropriate conditional distribution inducing a desired marginal distribution on a countably infinite alphabet. The construction is based on the infinite-dimensional version of Birkhoff’s theorem proven by Révész [Acta Math. Hungar. 1962, 3, 188–198], and the constraint of maintaining a desired marginal distribution is similar to coupling in probability theory. Using our Fano-type inequalities for Shannon’s and Rényi’s information measures, we also investigate the asymptotic behavior of the sequence of Shannon’s and Rényi’s equivocations when the error probabilities vanish. This asymptotic behavior provides a novel characterization of the asymptotic equipartition property (AEP) via Fano’s inequality.
It Takes a Village: Listening to Parents
Authors: Bolaji Stephen , Jalloh Sulay , Kell Marilyn
Published: March 2020

The study was premised on the concern of the migrant African parents about their children’s lack of aspiration for higher education after completing their secondary education in the Northern Territory (NT), Australia. There appears to be little understanding of, or confusion around, the different pathways available to higher education in Australia. The reports and anecdotes around African youths in the NT demonstrating antisocial behaviors, including, but not limited to drug offences, teen pregnancies and suicides prompted this research. These troubling behaviors have culminated in the death of two young boys in the African community in Darwin 2016 and another girl in 2019 in Kathrine. The study comprises of African parents who migrated to NT in Australia from different demographics in Africa. This study used a questionnaire and semi-structured interviews to investigate African parents’ perception of their child’s post-secondary school aspiration. The outcome of this investigation revealed a lack of understanding of the NT Australian school systems and reporting strand on their children performance and the different pathways through which their children can access higher education in Australia. This study provided four recommendations to help African parents understand the NT Australian government policies and programs on education.
Optimizing Energy Consumption in the Home Energy Management System via a Bio-Inspired Dragonfly Algorithm and the Genetic Algorithm
Authors: Hussain Irshad , Ullah Majid , Ullah Ibrar , Bibi Asima , Naeem Muhammad , Singh Madhusudan , Singh Dhananjay
Published: March 2020

Due to the exponential increase in the human population of this bio-sphere, energy resources are becoming scarce. Because of the traditional methods, most of the generated energy is wasted every year in the distribution network and demand side. Therefore, researchers all over the world have taken a keen interest in this issue and finally introduced the concept of the smart grid. Smart grid is an ultimate solution to all of the energy related problems of today’s modern world. In this paper, we have proposed a meta-heuristic optimization technique called the dragonfly algorithm (DA). The proposed algorithm is to a real-world problem of single and multiple smart homes. In our system model, two classes of appliances are considered; Shiftable appliances and Non-shiftable appliances. Shiftable appliances play a significant role in demand side load management because they can be scheduled according to real time pricing (RTP) signal from utility, while non-shiftable appliances are not much important in load management, as these appliances are fixed and cannot be scheduled according to RTP. On behalf of our simulation results, it can be concluded that our proposed algorithm DA has achieved minimum electricity cost with a tolerable waiting time. There is a trade-off between electricity cost and waiting time because, with a decrease in electricity cost, waiting time increases and vice versa. This trade-off is also obtained by our proposed algorithm DA. The stability of the grid is also maintained by our proposed algorithm DA because stability of the grid depends on peak-to-average ratio (PAR), while PAR is reduced by DA in comparison with an unscheduled case.
Goal-Oriented Obstacle Avoidance with Deep Reinforcement Learning in Continuous Action Space
Authors: Cimurs Reinis , Lee Jin Han , Suh Il Hong
Published: March 2020

In this paper, we propose a goal-oriented obstacle avoidance navigation system based on deep reinforcement learning that uses depth information in scenes, as well as goal position in polar coordinates as state inputs. The control signals for robot motion are output in a continuous action space. We devise a deep deterministic policy gradient network with the inclusion of depth-wise separable convolution layers to process the large amounts of sequential depth image information. The goal-oriented obstacle avoidance navigation is performed without prior knowledge of the environment or a map. We show that through the proposed deep reinforcement learning network, a goal-oriented collision avoidance model can be trained end-to-end without manual tuning or supervision by a human operator. We train our model in a simulation, and the resulting network is directly transferred to other environments. Experiments show the capability of the trained network to navigate safely around obstacles and arrive at the designated goal positions in the simulation, as well as in the real world. The proposed method exhibits higher reliability than the compared approaches when navigating around obstacles with complex shapes. The experiments show that the approach is capable of avoiding not only static, but also dynamic obstacles.
High Precision Pseudo-Range Measurement in GNSS Anti-Jamming Antenna Array Processing
Authors: Lu Zukun , Chen Feiqiang , Xie Yuchen , Sun Yifan , Cai Hongliang
Published: March 2020

Radio frequency interference has become a rising problem to the signal of the Global Navigation Satellite System (GNSS). An effective way to achieve anti-jamming is by using an antenna array in GNSS signal processing. However, antenna array processing will cause a decline in the accuracy of pseudo-range measurements because of the channel mismatch and some other non-ideal factors. To solve this problem, space–time or space–frequency adaptive array processing is widely used for interference cancellation while constraining the delay of each antenna at the same time. In this paper, an anti-jamming algorithm with a time-delay constraint is proposed, where one antenna is chosen as the reference and data from other antennas is corrected based on the signal received from it. The deduction and simulation results show that the proposed algorithm can effectively improve the accuracy of pseudo-range measurements without degradation of anti-jamming performance.
Reputation Management Using Honeypots for Intrusion Detection in the Internet of Things
Authors: Khan Zeeshan Ali , Abbasi Ubaid
Published: March 2020

Internet of Things (IoT) networks consist of tiny devices with limited processing resources and restricted energy budget. These devices are connected to the world-wide web (www) using networking protocols. Considering their resource limitations, they are vulnerable to security attacks by numerous entities on the Internet. The classical security solutions cannot be directly implemented on top of these devices for this reason. However, an Intrusion Detection System (IDS) is a classical way to protect these devices by using low-cost solutions. IDS monitors the network by introducing various metrics, and potential intruders are identified, which are quarantined by the firewall. One such metric is reputation management, which monitors the behavior of the IoT networks. However, this technique may still result in detection error that can be optimized by combining this solution with honeypots. Therefore, our aim is to add some honeypots in the network by distributing them homogeneously as well as randomly. These honeypots will team up with possible maliciously behaving nodes and will monitor their behavior. As per the simulation results, this technique reduces the error rate within the existing IDS for the IoT; however, it costs some extra energy. This trade-off between energy consumption and detection accuracy is studied by considering standard routing and MAC protocol for the IoT network.
Identification of Warning Situations in Road Using Cloud Computing Technologies and Sensors Available in Mobile Devices: A Systematic Review
Authors: Pires Ivan Miguel , Garcia Nuno M.
Published: March 2020

The use of mobile devices connected continuously to the cloud is increasing, and the development of a cloud-based solution may power the function of these devices in mobility. Several types of sensors available in the mobile devices may allow the acquisition of different kinds of data, including inertial sensors, magnetic sensors, location sensors, acoustic sensors, and imaging sensors. The primary purpose of this study is to review the methods, features, and studies related to the identification of road conditions and warning situations. We performed systematic research to discover relevant studies written in English for the identification of different situations using the sensors available in the mobile devices, published between 2011 and 2019. After that, we analyzed the remaining studies to verify its reproducibility. The major part of the studies does not report the accuracy in the detection of warning situations. As future work, we intend to develop a system based on the Centre of Portugal for the detection of warning situations, road problems, and other issues verified during driving activities. As future work, we intend to develop a system using only a mobile device for the acquisition of sensors data in the centre of Portugal. We verified that the majority of the studies were performed in big lands, but in small areas, the number of accidents and road abnormalities is also high.
Edge Computing Robot Interface for Automatic Elderly Mental Health Care Based on Voice
Authors: Yvanoff-Frenchin Camille , Ramos Vitor , Belabed Tarek , Valderrama Carlos
Published: March 2020

We need open platforms driven by specialists, in which queries can be created and collected for long periods and the diagnosis made based on a rigorous clinical follow-up. In this work, we developed a multi-language robot interface helping to evaluate the mental health of seniors by interacting through questions. Through the voice interface, the specialist can propose questions, as well as receive users’ answers, in text form. The robot can automatically interact with the user using the appropriate language. It can process the answers and under the guidance of a specialist, questions and answers can be oriented towards the desired therapy direction. The prototype was implemented on an embedded device meant for edge computing, thus it was able to filter environmental noise and can be placed anywhere at home. The proposed platform allows the integration of well-known open source and commercial data flow processing frameworks. The experience is now available for specialists to create queries and answers through a Web-based interface.
Modelling the Publishing Process of Big Location Data Using Deep Learning Prediction Methods
Authors: Yan Yan , Wang Bingqian , Sheng Quan Z. , Mahmood Adnan , Feng Tao , Xie Pengshou
Published: March 2020

Centralized publishing of big location data can provide accurate and timely information to assist in traffic management and for facilitating people to decide travel time and route, mitigate traffic congestion, and reduce unnecessary waste. However, the spatio-temporal correlation, non-linearity, randomness, and uncertainty of big location data make it impossible to decide an optimal data publishing instance through traditional methods. This paper, accordingly, proposes a publishing interval predicting method for centralized publication of big location data based on the promising paradigm of deep learning. First, the adaptive adjusted sampling method is designed to address the challenge of finding a reasonable release time via a prediction mechanism. Second, the Maximal Overlap Discrete Wavelet Transform (MODWT) is introduced for the decomposition of time series in order to separate different features of big location data. Finally, different deep learning models are selected to construct the entire framework according to various time-domain features. Experimental analysis suggests that the proposed prediction scheme is not only feasible, but also improves the prediction accuracy in contrast to the traditional deep learning mechanisms.
Time-Domain Electromagnetic Scattering by Buried Dielectric Objects with the Cylindrical-Wave Approach for GPR Modelling
Authors: Ponti Cristina , Santarsiero Massimo , Schettini Giuseppe
Published: March 2020

Electromagnetic modelling of ground penetrating radar applications to the survey of buried targets is a fundamental step in the interpretation of measured data from experimental campaigns. When pulsed source fields are employed, such a modelling is commonly performed through time-domain numerical techniques. The cylindrical wave approach is proposed here to solve the scattering of a pulsed field by circular cross-section cylinders buried in a semi-infinite medium. The field radiated field by a transmitting antenna is modelled using a line-current source. Theoretical solution is developed on a semi-analytical basis, through a spectral approach. Time and space spectra are employed to derive the scattered fields, and the final space–time dependence is found through an inverse Fourier Transform. The proposed approach allows an accurate modelling of a wide class of ground penetrating radar problems that are commonly simulated through two-dimensional layouts.
Brain-Switches for Asynchronous Brain–Computer Interfaces: A Systematic Review
Authors: Han Chang-Hee , Müller Klaus-Robert , Hwang Han-Jeong
Published: March 2020

A brain–computer interface (BCI) has been extensively studied to develop a novel communication system for disabled people using their brain activities. An asynchronous BCI system is more realistic and practical than a synchronous BCI system, in that, BCI commands can be generated whenever the user wants. However, the relatively low performance of an asynchronous BCI system is problematic because redundant BCI commands are required to correct false-positive operations. To significantly reduce the number of false-positive operations of an asynchronous BCI system, a two-step approach has been proposed using a brain-switch that first determines whether the user wants to use an asynchronous BCI system before the operation of the asynchronous BCI system. This study presents a systematic review of the state-of-the-art brain-switch techniques and future research directions. To this end, we reviewed brain-switch research articles published from 2000 to 2019 in terms of their (a) neuroimaging modality, (b) paradigm, (c) operation algorithm, and (d) performance.
A New Method of Determining Energy Efficiency Operational Indicator for Specialized Ships
Authors: Prill Katarzyna , Behrendt Cezary , Szczepanek Marcin , Michalska-Pożoga Iwona
Published: March 2020

Limitation of CO2 emission is one of the main goals and regulations introduced by the international institutions’ rules. In the case of ships using oil-related and gas fuels this problem is dealt with by the International Maritime Organization (IMO) introducing the methodology of Energy Efficiency Operational Indicator (EEOI) determining for ships being under exploitation. The methodology allows for determining EEOI for seven types of ships, for which the value of this index depends on the amount of transported cargo or number of passengers, type of and amount of fuel used, as well as distance travelled by the ship. Such a methodology cannot be used for the specialized ships, whose exploitation tasks are different to the ships of the trade fleet that transport the cargo or the passengers. The methodology allows for determining EEOI for seven types of ships and it does not include specialized ships. The article presents a new methodology of determining EEOI for specialized ships that takes the characteristics of their exploitation into consideration. The way of its use has been presented taking into account the results of exploitation studies carried out on the chosen research and training ship. Obtained results and their analysis allowed for energy efficiency assessment of research and training ships depending on exploitation tasks, voyage time, type of fuel used, distance travelled and ship’s speed. EEOI index value determines energy efficiency of the vessel power system that is directly connected to the amount of the liquid or gas fuel used and the amount of emitted CO2. The aim should be to minimalize the value of EEOI index through planning of the exploitation tasks realization order and adjusting the speed of the ship as well as realization time of particular exploitation tasks, in the case of specialized ships. The analysis results can also be used when managing energy efficiency of these types of ships.
Epigenetic Modulation of Self-Renewal Capacity of Leukemic Stem Cells and Implications for Chemotherapy
Authors: Momparler Richard , Côté Sylvie , Momparler Louise
Published: March 2020

Most patients with acute myeloid leukemia (AML) have a poor prognosis. Curative therapy of AML requires the complete eradication of the leukemic stem cells (LSCs). One aspect of LSCs that is poorly understood is their low frequency in the total population of leukemic cells in AML patients. After each cell division of LSCs, most of the daughter cells lose their capacity for self-renewal. Investigations into the role of Isocitrate dehydrogenase (IDH) mutations in AML provide some insight on the regulation of the proliferation of LSCs. The primary role of IDH is to convert isocitrate to alpha-keto-glutarate (α-KG). When IDH is mutated, it converts α-KG to 2-hydroxyglutarate (2-HG), an inhibitor of the TET pathway and Jumonji-C histone demethylases (JHDMs). The demethylating action of these enzymes removes the epigenetic gene-silencing markers, DNA methylation, H3K27me3 and H3K9me2 and can lead to the differentiation of LSCs. This enzymatic action is blocked by 2-HG in mutated IDH (mut-IDH) AML patients, who can be induced into remission with antagonists of 2-HG. These observations suggest that there exists in cells a natural enzymatic mechanism that uses demethylation to reverse epigenetic gene-silencing, leading to a loss of the self-renewal capacity of LSCs. This mechanism limits the proliferative potential of LSCs. Epigenetic agents that inhibit DNA and histone methylation exhibit a synergistic antineoplastic action on AML cells. It is possible that the therapeutic potential of this epigenetic therapy may be enhanced by demethylation enzymes, resulting in a very effective treatment for AML.
Divergent DNA Methylation Signatures of Juvenile Seedlings, Grafts and Adult Apple Trees
Authors: Perrin Adrien , Daccord Nicolas , Roquis David , Celton Jean-Marc , Vergne Emilie , Bucher Etienne
Published: March 2020

The vast majority of previous studies on epigenetics in plants have centered on the study of inheritance of DNA methylation patterns in annual plants. In contrast, perennial plants may have the ability to accumulate changes in DNA methylation patterns over numerous years. However, currently little is known about long-lived perennial and clonally reproducing plants that may have evolved different DNA methylation inheritance mechanisms as compared to annual plants. To study the transmission of DNA methylation patterns in a perennial plant, we used apple (Malus domestica) as a model plant. First, we investigated the inheritance of DNA methylation patterns during sexual reproduction in apple by comparing DNA methylation patterns of mature trees to juvenile seedlings resulting from selfing. While we did not observe a drastic genome-wide change in DNA methylation levels, we found clear variations in DNA methylation patterns localized in regions enriched for genes involved in photosynthesis. Using transcriptomics, we also observed that genes involved in this pathway were overexpressed in seedlings. To assess how DNA methylation patterns are transmitted during clonal propagation we then compared global DNA methylation of a newly grafted tree to its mature donor tree. We identified significant, albeit weak DNA methylation changes resulting from grafting. Overall, we found that a majority of DNA methylation patterns from the mature donor tree are transmitted to newly grafted plants, however with detectable specific local differences. Both the epigenomic and transcriptomic data indicate that grafted plants are at an intermediate phase between an adult tree and seedling and inherit part of the epigenomic history of their donor tree.
Assessing the Potential of Forest Stands for Ectomycorrhizal Mushrooms as a Subsistence Ecosystem Service for Socially Disadvantaged People: A Case Study from Central Slovakia
Authors: Olah Branislav , Kunca Vladimír , Gallay Igor
Published: March 2020

Mushrooming is a widespread leisure activity for a significant part of the Slovak population. From the point of view of the ecosystem services, it combines a provisioning service (mushrooms as food or delicacies) and a cultural service (mushroom picking as physical activity in nature). For urban residents, the forest is a refuge from the daily work routine, and mushrooming contributes significantly to improving their quality of life. For mushroom pickers living in rural areas, the occurrence and availability of mushroom harvesting sites are often even more important since it contributes to their diet or even provides an occasional income. We summarised the ecological preferences of selected ectomycorrhizal mushrooms and applied them as parameters for modelling the potential of forest stands for mushroom growing in central Slovakia. In the second step, we analysed the theoretical demand for wild mushrooms as a subsistence provisioning service for the local population with a special focus on socially disadvantaged inhabitants. The results showed that there is a spatial overlap of forest stands with a high potential for mushroom growing and the districts with the highest proportion of unemployment or of inhabitants receiving social benefits, and the best mushroom forest stands are situated within walking distance from the settlements. This supports the initial assumption that wild mushrooms may contribute to a better life for disadvantaged local communities.
Economic Performance of Forest Plantations in Vietnam: Eucalyptus, Acacia mangium, and Manglietia conifera
Authors: Cuong Tran , Chinh Tran Thi Quy , Zhang Yaoqi , Xie Yi
Published: March 2020

Forest plantations have expanded rapidly in response to financial support from the state and local governments and have had significant positive impacts on rural livelihoods and development in Vietnam, since the late 1980s. This study used net present value (NPV) and internal rate of return (IRR) to examine the economic performance of plantations for three species, Acacia mangium Willd, Eucalyptus (Eucalyptus urophylla S.T. Blake × Eucalyptus camaldulensis Dehn), and Manglietia conifera Dandy, in Bac Kan province. On the basis of an annual discount rate of 6%, the results showed that rural households earned positive financial returns from forest plantations with seven-year rotations. Eucalyptus generated the highest NPV but A. mangium generated the greatest IRR. The plantations were facilitated by financial support from the state, land tenure reforms, and wood exports. The results provide valuable business information and policy implications for both local farmers and policy makers. Since the farmers consider more of the short term and economic return of the plantations, the results provide valuable information for policy makers to apply subsidies and other support to promote plantations with significant ecological and environmental benefits for sustainable development of rural economies.
Soil Microbial Community Assembly and Interactions Are Constrained by Nitrogen and Phosphorus in Broadleaf Forests of Southern China
Authors: Zhao Mengxin , Cong Jing , Cheng Jingmin , Qi Qi , Sheng Yuyu , Ning Daliang , Lu Hui , Wyckoff Kristen N. , Deng Ye , Li Diqiang , Zhou Jizhong , Zhang Yuguang
Published: March 2020

Subtropical and tropical broadleaf forests play important roles in conserving biodiversity and regulating global carbon cycle. Nonetheless, knowledge about soil microbial diversity, community composition, turnover and microbial functional structure in sub- and tropical broadleaf forests is scarce. In this study, high-throughput sequencing was used to profile soil microbial community composition, and a micro-array GeoChip 5.0 was used to profile microbial functional gene distribution in four sub- and tropical broadleaf forests (HS, MES, HP and JFL) in southern China. The results showed that soil microbial community compositions differed dramatically among all of four forests. Soil microbial diversities in JFL were the lowest (5.81–5.99) and significantly different from those in the other three forests (6.22–6.39). Furthermore, microbial functional gene interactions were the most complex and closest, likely in reflection to stress associated with the lowest nitrogen and phosphorus contents in JFL. In support of the importance of environmental selection, we found selection (78–96%) dominated microbial community assembly, which was verified by partial Mantel tests showing significant correlations between soil phosphorus and nitrogen content and microbial community composition. Taken together, these results indicate that nitrogen and phosphorus are pivotal in shaping soil microbial communities in sub- and tropical broadleaf forests in southern China. Changes in soil nitrogen and phosphorus, in response to plant growth and decomposition, will therefore have significant changes in both microbial community assembly and interaction.
Nutritional Characteristics of Prepacked Feta PDO Cheese Products in Greece: Assessment of Dietary Intakes and Nutritional Profiles
Authors: Katsouri Evangelia , Magriplis Emmanuella , Zampelas Antonios , Nychas George-John , H. Drosinos Eleftherios
Published: March 2020

Feta cheese, a protected designation of origin (PDO) food, is one of the most important Mediterranean food products. Although it is the cheese with the highest consumption in Greece, the nutritional characteristics of products available in the market, as well as their contribution to the Greek diet, have not been evaluated in detail. In the present study, the basic nutritional content of 81 prepacked feta cheese products available in the Greek market were recorded based on their labels. This was combined with consumption data to provide an overall picture of feta cheese’s contribution to the Greek diet. The nutrient contents per 100 g ranged as follows. Energy: 221–343 kcal, total fat: 20–29 g, saturated fat: 12.8–20.3 g, carbohydrates: 0–3.1 g, sugars: 0–3 g, proteins: 13.1–21.0 g and salt: 1.2–5.1 g. The median feta daily individual consumption was found to be 39 g, ranging from 20 g to 100 g (fifth and 95th percentiles, respectively). The nutritional intake analysis as a percentage of dietary reference intake (DRI) showed that saturated fat and salt are ranked on the top of the list, with intakes reaching 101.5% and 85% respectively. The products were also evaluated against five nutrient profile models and their potential use under statutory requirements and policy development are discussed.
Immunoreactivity of Lupine and Soybean Allergens in Foods as Affected by Thermal Processing
Authors: Villa Caterina , Moura Mónica B. M. V. , Costa Joana , Mafra Isabel
Published: March 2020

Lupine and soybean are important technological aids for the food industry. However, they are also capable of inducing severe allergic reactions in food-sensitized/allergic individuals. In this context, this work intended to study the combined effects of thermal processing and food matrix on the immunoreactivity of lupine and soybean proteins used as ingredients in bakery and meat products, respectively. For this purpose, the effects of baking, mild oven cooking, and autoclaving on the protein profiles were evaluated, using model mixtures simulating the production of lupine-containing breads and soybean-containing cooked hams/sausages, by native- and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and immunoblotting using specific antibodies. The results showed that lupine gamma-conglutin immunoreactivity was slightly decreased in wheat flour mixtures compared to rice, but it was more pronounced in baked products. In meat mixtures, substantial protein fragmentation was noted after autoclaving, with decreased immunoreactivity of soybean trypsin inhibitor. The analysis of 22 commercial products enabled the identification of lupine gamma-conglutin in four bakery samples and soybean trypsin-inhibitor in five sausages, and further differentiated autoclaved from other milder thermally treated products. Generally, the immunoreactivity of target proteins was reduced by all the tested thermal treatments, though at a higher extent after autoclaving, being slightly altered by the food matrix.
Development of Head Space Sorptive Extraction Method for the Determination of Volatile Compounds in Beer and Comparison with Stir Bar Sorptive Extraction
Authors: Ruvalcaba José E. , Durán-Guerrero Enrique , Barroso Carmelo G. , Castro Remedios
Published: March 2020

A headspace sorptive extraction method coupled with gas chromatography–mass spectrometry (HSSE–GC–MS) was developed for the determination of 37 volatile compounds in beer. After optimization of the extraction conditions, the best conditions for the analysis were stirring at 1000 rpm for 180 min, using an 8-mL sample with 25% NaCl. The analytical method provided excellent linearity values (R2 > 0.99) for the calibration of all the compounds studied, with the detection and quantification limits obtained being low enough for the determination of the compounds in the beers studied. When studying the repeatability of the method, it proved to be quite accurate, since RSD% values lower than 20% were obtained for all the compounds. On the other hand, the recovery study was successfully concluded, resulting in acceptable values for most of the compounds (80–120%). The optimised method was successfully applied to real beer samples of different types (ale, lager, stout and wheat). Finally, an analytical comparison of the optimised HSSE method, with a previously developed and validated stir bar sorptive extraction (SBSE) method was performed, obtaining similar concentration values by both methods for most compounds.
Influence of Adding Chinese Yam (Dioscorea opposita Thunb.) Flour on Dough Rheology, Gluten Structure, Baking Performance, and Antioxidant Properties of Bread
Authors: Li Qing-Ming , Li Yan , Zou Jin-Hao , Guo Shi-Yin , Wang Feng , Yu Peng , Su Xiao-Jun
Published: March 2020

Impacts of wheat flour substituted with various levels of Chinese yam (Dioscorea opposita Thunb.) flour (from 0% to 25%) on the dough rheological characteristics, gluten structure, baking performance, and antioxidant properties of bread were investigated. The water absorption increased significantly (p < 0.05), while development time and stability decreased remarkably (p < 0.05) as the proportion of yam flour increased. SEM results indicated that the addition of yam flour destroyed the gluten network structure in the dough. Fourier Transform Infrared Spectroscopy (FTIR) spectra showed that addition of yam flour decreased the content of α-helix and β-sheet in gluten. With the increase in the proportion of yam flour, the specific volume and overall acceptability decreased (p < 0.05) whereas the total phenolics content (TPC), polysaccharides content, total flavonoids content (TFC), allantoin content, The 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging capability, fractal dimension, and hardness increased (p < 0.05). Overall, breads made of wheat flour replacement with no more than 15% Guihuai number 2 yam flour were of a high quality and had more antioxidant properties. These showed that Guihuai number 2 had broad application prospects in baked products.
Anti-Hyperglycemic Effects of Green Crab Hydrolysates Derived by Commercially Available Enzymes
Authors: Kang Bouhee , Skonberg Denise I. , Myracle Angela D.
Published: March 2020

The predation and burrowing activity of invasive green crabs have had detrimental effects on important marine resources and habitats. Our objective is to develop bioactive hydrolysates by enzymatic proteolysis of underutilized green crab. Mechanically separated mince was hydrolyzed with Alcalase, Protamex, Flavourzyme, and Papain (1%) for 60 min. Subsequently, the hydrolysates were introduced to a simulated gastrointestinal digestion model. Selected samples were fractionated by ultrafiltration, and their anti-hyperglycemic effects including α-glucosidase, α-amylase, and dipeptidyl peptidase-IV (DPP-IV) inhibitory activities and glucagon-like 1 (GLP-1) secretory activity were evaluated. The Protamex treatment showed the highest α-glucosidase inhibitory activity (IC50 1.38 ± 0.19 mg/mL) compared to other enzyme treatments and the crab mince control, and its α-amylase inhibitory activity (IC50 11.02 ± 0.69 mg/mL) was lower than its α-glucosidase inhibitory activity. Its GLP-1 secretory activity was approximately four times higher than the positive control (10 mM glutamine). The <3 kD fraction contributed significantly to the anti-hyperglycemic activity of Protamex-derived hydrolysates, and this activity was stable after simulated digestion. Our results suggest that green crab hydrolysates obtained by Protamex treatment have the potential for type 2 diabetes management and could be incorporated in food products as a health-promoting ingredient.
The Analysis of Marketing Factors Influencing Consumers’ Preferences and Acceptance of Organic Food Products—Recommendations for the Optimization of the Offer in a Developing Market
Authors: Melovic Boban , Cirovic Dragana , Dudic Branislav , Vulic Tamara Backovic , Gregus Michal
Published: March 2020

Considering the benefits of the organic production system, it is recognized as one of the main drivers of future economic development. However, the imbalance between demand and supply at the local market level represents one of the serious obstacles that prevents its future growth. Therefore, this article examines the key factors related to the main elements of the offer that have the strongest impact on consumer preferences and acceptance of organic food products. In that sense, organic product, price, distribution channel, and promotion are considered the main elements of the offer and are analyzed in this paper from the consumer preferences perspective. Further, this article provides insight into some of the sensory properties of the offer that are important to consumers. Finally, it gives recommendations for optimization of the offer on the organic food market based on the analysis of the influence of each of those elements (product, price, distribution, and promotion) on consumer acceptance of organic products and making purchasing decisions. The data were collected using a questionnaire, and analyzed using the structural equation model (SEM). The results revealed that price and promotion have the strongest impact on consumer acceptance and buying decisions. Further analysis revealed that attitudes towards organic food products, price/quality ratio, distribution barriers, and modern media as a promotion instrument are the factors that have the most significant impact on consumer perception and attitudes towards the available market offer. These findings can help producers and other decision makers to better understand what creates added value of the organic food products in consumers’ mind and therefore make an offer that is in line with their expectations and preferences, which is recognized as one of the main prerequisites for the acceptance and purchase of organic food products.
Exploiting Milling By-Products in Bread-Making: The Case of Sprouted Wheat
Authors: Cardone Gaetano , D’Incecco Paolo , Casiraghi Maria Cristina , Marti Alessandra
Published: March 2020

This research investigated the effect of sprouting on wheat bran. Bran from un-sprouted (BUW) and sprouted (BSW) wheat were characterized in terms of chemical composition, enzymatic activities, and hydration properties. In addition, the rheological properties (using GlutoPeak, Farinograph, Extensograph, and Rheofermentometer tests) and bread-making performance (color, texture, volume of bread) of wheat doughs enriched in bran at 20% replacement level were assessed. Sprouting process caused a significant decrease in phytic acid (~20%), insoluble dietary fiber (~11%), and water holding capacity (~8%), whereas simple sugars (~133%) and enzymatic activities significantly increased after processing. As regards the gluten aggregation kinetics, the BSW-blend profile was more similar to wheat than BUW-blend, indicating changes in the fiber and gluten interactions. BSW led to a worsening of the mixing and leavening properties, instead, no significant changes in extensibility were observed. Finally, BSW improved bread volume (~10%) and crumb softness (~52%). Exploiting bran from sprouted wheat might be useful to produce bread rich in fiber with enhanced characteristics.
The In Vivo Antioxidant and Hepatoprotective Actions of Selected Chinese Teas
Authors: Cao Shi-Yu , Li Bang-Yan , Gan Ren-You , Mao Qian-Qian , Wang Yuan-Feng , Shang Ao , Meng Jin-Ming , Xu Xiao-Yu , Wei Xin-Lin , Li Hua-Bin
Published: March 2020

Tea is a popular beverage and shows very strong in vitro antioxidant activity. However, the relationship among in vitro and in vivo antioxidant activities in teas is seldom reported. In this study, in vivo antioxidant and hepatoprotective activities of 32 selected Chinese teas were evaluated on a mouse model with acute alcohol-induced liver injury. The results showed that most teas significantly reduced the levels of alanine transaminase, aspartate transaminase, alkaline phosphatase, triacylglycerol, and total bilirubin in the sera of mice at a dose of 400 mg/kg. In addition, most teas greatly decreased the malondialdehyde level and increased the levels of superoxide dismutase, glutathione peroxidase, and glutathione in the liver of mice, indicating the antioxidant and hepatoprotective activities of teas. Furthermore, the in vivo antioxidant activity of dark tea was stronger than that of green tea, opposite to the results of the in vitro study. Among these 32 teas, Black Fu Brick Tea, Pu-erh Tea, and Qing Brick Tea showed the strongest antioxidant and hepatoprotective activities. Moreover, total phenolic content as well as the contents of epicatechin, gallocatechin gallate, and chlorogenic acid were found to contribute, at least partially, to the antioxidant and hepatoprotective actions of these teas. Overall, teas are good dietary components with antioxidant and hepatoprotective actions.
Production of Milk Phospholipid-Enriched Dairy Ingredients
Authors: Huang Zhiguang , Zheng Haotian , Brennan Charles S. , Mohan Maneesha S. , Stipkovits Letitia , Li Lingyi , Kulasiri Don
Published: March 2020

Milk phospholipids (MPLs) have been used as ingredients for food fortification, such as bakery products, yogurt, and infant formula, because of their technical and nutritional functionalities. Starting from either buttermilk or beta serum as the original source, this review assessed four typical extraction processes and estimated that the life-cycle carbon footprints (CFs) of MPLs were 87.40, 170.59, 159.07, and 101.05 kg CO2/kg MPLs for membrane separation process, supercritical fluid extraction (SFE) by CO2 and dimethyl ether (DME), SFE by DME, and organic solvent extraction, respectively. Regardless of the MPL content of the final products, membrane separation remains the most efficient way to concentrate MPLs, yielding an 11.1–20.0% dry matter purity. Both SFE and solvent extraction processes are effective at purifying MPLs to relatively higher purity (76.8–88.0% w/w).
Three-Year Longitudinal Study: Prevalence of Salmonella Enterica in Chicken Meat is Higher in Supermarkets than Wet Markets from Mexico
Authors: Regalado-Pineda Iván D. , Rodarte-Medina Rene , Resendiz-Nava Carolina N. , Saenz-Garcia Cinthia E. , Castañeda-Serrano Pilar , Nava Gerardo M.
Published: March 2020

Worldwide, chicken meat is considered one of the main sources of Salmonella enterica in humans. To protect consumers from this foodborne pathogen, international health authorities recommend the establishment of continuous Salmonella surveillance programs in meat. However, these programs are scarce in many world regions; thus, the goal of the present study was to perform a longitudinal surveillance of S. enterica in chicken meat in Mexico. A total of 1160 samples were collected and analyzed monthly from 2016 to 2018 in ten chicken meat retailers (supermarkets and wet markets) located in central Mexico. The isolation and identification of S. enterica was carried out using conventional and molecular methods. Overall, S. enterica was recovered from 18.1% (210/1160) of the chicken meat samples. Remarkably, during the three years of evaluation, S. enterica was more prevalent (p < 0.0001) in supermarkets (27.2%, 158/580) than in wet markets (9.0%, 52/580). The study was 3.8 times more likely (odds ratio = 3.8, p < 0.0001) to recover S. enterica from supermarkets than wet markets. Additionally, a higher prevalence (p < 0.05) of this pathogen was observed during the spring, summer, autumn, and winter in supermarkets compared with wet markets. Moreover, the recovery rate of S. enterica from supermarkets showed a gradual increase from 20.78% to 42% (p < 0.0001) from 2016 to 2018. Interestingly, no correlation (p > 0.05) was observed between the S. enterica recovery rate in chicken meat and reported cases of Salmonella infections in humans. Higher levels of S. enterica in chicken meat retailed in supermarkets are not unusual; this phenomenon has also been reported in some European and Asian countries. Together, these results uncover an important health threat that needs to be urgently addressed by poultry meat producers and retailers.