bluuebunny/crossref_metadata_2025 huggingface dataset:
Microstructural and Energy-Dispersive X-ray Analyses on Argon Ion Implantations in Tantalum Thin Films for Microelectronic Substrates
Authors: Ramezani Amir Hoshang , Hoseinzadeh Siamak , Ebrahiminejad Zhaleh , Sangashekan Milad , Memon Saim
Published: November 2021

In the present study, the microstructural and statistical properties of unimplanted in comparison to argon ion-implanted tantalum-based thin film surface structures are investigated for potential application in microelectronic thin film substrates. In the study, the argon ions were implanted at the energy of 30 keV and the doses of 1 × 1017, 3 × 1017, and 7 × 1017 (ion/cm2) at an ambient temperature. Two primary goals have been pursued in this study. First, by using atomic force microscopy (AFM) analysis, the roughness of samples, before and after implantation, has been studied. The corrosion apparatus wear has been used to compare resistance against tantalum corrosion for all samples. The results show an increase in resistance against tantalum corrosion after the argon ion implantation process. After the corrosion test, scanning electron microscopy (SEM) analysis was applied to study the sample morphology. The elemental composition of the samples was characterized by using energy-dispersive X-ray (EDX) analysis. Second, the statisticalcharacteristics of both unimplanted and implanted samples, using the monofractal analysis with correlation function and correlation length of samples, were studied. The results show, however, that all samples are correlated and that the variation of ion doses has a negligible impact on the values of correlation lengths. Moreover, the study of height distribution and higher-order moments show the deviation from Gaussian distribution. The calculations of the roughness exponent and fractal dimension indicates that the implanted samples are the self-affine fractal surfaces.
Self-Adaptive Multi-Task Differential Evolution Optimization: With Case Studies in Weapon–Target Assignment Problem
Authors: Zheng Xiaolong , Zhou Deyun , Li Na , Wu Tao , Lei Yu , Shi Jiao
Published: November 2021

Multi-task optimization (MTO) is related to the problem of simultaneous optimization of multiple optimization problems, for the purpose of solving these problems better in terms of optimization accuracy or time cost. To handle MTO problems, there emerges many evolutionary MTO (EMTO) algorithms, which possess distinguished strategies or frameworks in the aspect of handling the knowledge transfer between different optimization problems (tasks). In this paper, we explore the possibility of developing a more efficient EMTO solver based on differential evolution by introducing the strategies of a self-adaptive multi-task particle swarm optimization (SaMTPSO) algorithm, and by developing a new knowledge incorporation strategy. Then, we try to apply the proposed algorithm to solve the weapon–target assignment problem, which has never been explored in the field of EMTO before. Experiments were conducted on a popular MTO test benchmark and a WTA-MTO test set. Experimental results show that knowledge transfer in the proposed algorithm is effective and efficient, and EMTO is promising in solving WTA problems.
An Automated Recognition of Work Activity in Industrial Manufacturing Using Convolutional Neural Networks
Authors: Patalas-Maliszewska Justyna , Halikowski Daniel , Damaševičius Robertas
Published: November 2021

The automated assessment and analysis of employee activity in a manufacturing enterprise, operating in accordance with the concept of Industry 4.0, is essential for a quick and precise diagnosis of work quality, especially in the process of training a new employee. In the case of industrial solutions, many approaches involving the recognition and detection of work activity are based on Convolutional Neural Networks (CNNs). Despite the wide use of CNNs, it is difficult to find solutions supporting the automated checking of work activities performed by trained employees. We propose a novel framework for the automatic generation of workplace instructions and real-time recognition of worker activities. The proposed method integrates CNN, CNN Support Vector Machine (SVM), CNN Region-Based CNN (Yolov3 Tiny) for recognizing and checking the completed work tasks. First, video recordings of the work process are analyzed and reference video frames corresponding to work activity stages are determined. Next, work-related features and objects are determined using CNN with SVM (achieving 94% accuracy) and Yolov3 Tiny network based on the characteristics of the reference frames. Additionally, matching matrix between the reference frames and the test frames using mean absolute error (MAE) as a measure of errors between paired observations was built. Finally, the practical usefulness of the proposed approach by applying the method for supporting the automatic training of new employees and checking the correctness of their work done on solid fuel boiler equipment in a manufacturing company was demonstrated. The developed information system can be integrated with other Industry 4.0 technologies introduced within an enterprise.
Economic Design of Hybrid Pico-Hydraulic/Photovoltaic Generation System: A Case Study in Egypt
Authors: Selim Fathalla F. , Abdelaziz Almoataz , Taha Ibrahim B. M.
Published: November 2021

Clean and renewable energy sources are the preferable power system generations for the overall world. This research aims to present a very highly integrated, economic, professional, and simple construction, clean and natural resources usage of the renewable hybrid generation system. This research performs analysis, systematic representation, evaluation, and design of the hybrid proposed system—pico-hydraulic from home usage water and photovoltaic (PV)—to generate an optimal renewable generation system using a new professional control system. Applying this proposed technique in Egypt shows that the hybrid system successfully overcame Egypt’s energy crisis. Renewable energy will rise to 8.782% by increasing 7.323% (14,408.83 GWh/Y). Besides, this system increases the power supply reliability; it gives an additional emergency supply and reduces the exhausts from other generation stations (e.g., CO2). The saving from this hybrid system is very effective for; the residential sector (subscribes), which will be ranged from 9599.298 million E£/10Ys up to 86,393.68 million E£/10Ys that equals 5399.6 million $, government to use this extra generation energy to reduce the maximum loads from various stations. A practical model has been presented with results to verify the high efficiency of the proposed system that illustrates the effective performance of the used hybrid system.
Mapping Discrete Emotions in the Dimensional Space: An Acoustic Approach
Authors: Trnka Marián , Darjaa Sakhia , Ritomský Marian , Sabo Róbert , Rusko Milan , Schaper Meilin , Stelkens-Kobsch Tim H.
Published: November 2021

A frequently used procedure to examine the relationship between categorical and dimensional descriptions of emotions is to ask subjects to place verbal expressions representing emotions in a continuous multidimensional emotional space. This work chooses a different approach. It aims at creating a system predicting the values of Activation and Valence (AV) directly from the sound of emotional speech utterances without the use of its semantic content or any other additional information. The system uses X-vectors to represent sound characteristics of the utterance and Support Vector Regressor for the estimation the AV values. The system is trained on a pool of three publicly available databases with dimensional annotation of emotions. The quality of regression is evaluated on the test sets of the same databases. Mapping of categorical emotions to the dimensional space is tested on another pool of eight categorically annotated databases. The aim of the work was to test whether in each unseen database the predicted values of Valence and Activation will place emotion-tagged utterances in the AV space in accordance with expectations based on Russell’s circumplex model of affective space. Due to the great variability of speech data, clusters of emotions create overlapping clouds. Their average location can be represented by centroids. A hypothesis on the position of these centroids is formulated and evaluated. The system’s ability to separate the emotions is evaluated by measuring the distance of the centroids. It can be concluded that the system works as expected and the positions of the clusters follow the hypothesized rules. Although the variance in individual measurements is still very high and the overlap of emotion clusters is large, it can be stated that the AV coordinates predicted by the system lead to an observable separation of the emotions in accordance with the hypothesis. Knowledge from training databases can therefore be used to predict AV coordinates of unseen data of various origins. This could be used to detect high levels of stress or depression. With the appearance of more dimensionally annotated training data, the systems predicting emotional dimensions from speech sound will become more robust and usable in practical applications in call-centers, avatars, robots, information-providing systems, security applications, and the like.
Metal Object Detection in a Wireless High-Power Transfer System Using Phase–Magnitude Variation
Authors: Kim Sunhee , Choi Woong , Lim Yongseok
Published: November 2021

Recently, wireless charging technologies for large moving objects, such as electric vehicles and robots, have been actively researched. The power transmitting and receiving coils in most large moving objects are structurally separated by a given distance, which exposes a high output power to the outside world. If a foreign metal object enters the area between these two coils during wireless power transfer, fire hazards or equipment damage may occur. Therefore, we propose a method for detecting foreign metal objects in the gap between the transmitting and receiving coils in a wireless high-power transfer system. A resonant detection coil set is used to exploit the change induced in electrical characteristics when a foreign metal object is inserted. The mutual inductance of the foreign metal object changes the impedance of the detection coil set. We developed a simple circuit to detect both the magnitude and phase change of the voltage signal according to the altered impedance. Additionally, we implemented a prototype of a wireless power transfer system with a detection system to verify that even small foreign metal objects can be detected effectively.
Model-Based Design of an Improved Electric Drive Controller for High-Precision Applications Based on Feedback Linearization Technique
Authors: Dini Pierpaolo , Saponara Sergio
Published: November 2021

This paper presents the design flow of an advanced non-linear control strategy, able to absorb the effects that the main causes of torque oscillations, concerning synchronous electrical drives, cause on the positioning of the end-effector of a manipulator robot. The control technique used requires an exhaustive modelling of the physical phenomena that cause the electromagnetic torque oscillations. In particular, the Cogging and Stribeck effects are taken into account, whose mathematical model is incorporated in the whole system of dynamic equations representing the complex mechatronic system, formed by the mechanics of the robot links and the dynamics of the actuators. Both the modelling procedure of the robot, directly incorporating the dynamics of the actuators and the electrical drive, consisting of the modulation system and inverter, and the systematic procedure necessary to obtain the equations of the components of the control vector are described in detail. Using the Processor-In-the-Loop (PIL) paradigm for a Cortex-A53 based embedded system, the beneficial effect of the proposed advanced control strategy is validated in terms of end-effector position control, in which we compare classic control system with the proposed algorithm, in order to highlight the better performance in precision and in reducing oscillations.
A Methodology to Produce Augmented-Reality Guided Tours in Museums for Mixed-Reality Headsets
Authors: Martí-Testón Ana , Muñoz Adolfo , Solanes J. Ernesto , Gracia Luis , Tornero Josep
Published: November 2021

In recent years, the use of technology in the museum context has changed radically. It has switched from the display of information to offering emotive, immersive, and rich experiences with heritage. Virtual interactive media have the potential to put museums back into a relevant place in our increasingly digital society. The emergence of augmented-reality glasses offers the possibility to test and implement new methodologies compatible with this aim. However, most of the first examples developed in recent years did not take advantage of the possibilities of this new medium. This paper presents a novel methodology for producing mixed-reality applications for museums and heritage sites, with an intuitive, immersive, and natural way of operating. An experimental prototype designed for the archaeological museum of the Almoina is shown in the paper to demonstrate the benefits of the proposed system and methodology of production. In addition, the paper shows the results of several tests.
A Survey on Techniques in the Circular Formation of Multi-Agent Systems
Authors: Litimein Hamida , Huang Zhen-You , Hamza Ameer
Published: November 2021

Distributed control solutions to the multi-agent systems in terms of coordination, formation, and consensus problems are extensively studied in the literature. The circular formation control of multi-agent systems becomes one of the most challenging and active research topics in distributed cooperative control. The research potential of circular formation control has grown especially in satellite formation and control. The circular formation control aims to drive a group of agents to move on a circular trajectory around a center with spacing adjustment to avoid the collision. This paper covers the fundamental research in consensus and formation control and the latest developments in the applications of formation control especially in circular formation control and stability analysis. Literature related to various control streams to achieve circular formation is discussed. Algebraic graph theory is used as a building block in problem definition, problem formulation, and solutions. A review of bearing, range, and received signal strength measurements with respect to circular formation control is presented. Leader following, behavior-based, artificial potential function, virtual structure, and cyclic pursuit are the methods discussed most in this context. The stabilization of the collective circular motion with the unicycles approach is also discussed. Further results on circular formation, several applications, and future research directions are presented.
A Collaborative CPU Vector Offloader: Putting Idle Vector Resources to Work on Commodity Processors
Authors: Son Youngbin , Kang Seokwon , Um Hongjun , Lee Seokho , Ham Jonghyun , Kim Donghyeon , Park Yongjun
Published: November 2021

Most modern processors contain a vector accelerator or internal vector units for the fast computation of large target workloads. However, accelerating applications using vector units is difficult because the underlying data parallelism should be uncovered explicitly using vector-specific instructions. Therefore, vector units are often underutilized or remain idle because of the challenges faced in vector code generation. To solve this underutilization problem of existing vector units, we propose the Vector Offloader for executing scalar programs, which considers the vector unit as a scalar operation unit. By using vector masking, an appropriate partition of the vector unit can be utilized to support scalar instructions. To efficiently utilize all execution units, including the vector unit, the Vector Offloader suggests running the target applications concurrently in both the central processing unit (CPU) and the decoupled vector units, by offloading some parts of the program to the vector unit. Furthermore, a profile-guided optimization technique is employed to determine the optimal offloading ratio for balancing the load between the CPU and the vector unit. We implemented the Vector Offloader on a RISC-V infrastructure with a Hwacha vector unit, and evaluated its performance using a Polybench benchmark set. Experimental results showed that the proposed technique achieved performance improvements up to 1.31× better than the simple, CPU-only execution on a field programmable gate array (FPGA)-level evaluation.
End-Effector Force and Joint Torque Estimation of a 7-DoF Robotic Manipulator Using Deep Learning
Authors: Kružić Stanko , Musić Josip , Kamnik Roman , Papić Vladan
Published: November 2021

When a mobile robotic manipulator interacts with other robots, people, or the environment in general, the end-effector forces need to be measured to assess if a task has been completed successfully. Traditionally used force or torque estimation methods are usually based on observers, which require knowledge of the robot dynamics. Contrary to this, our approach involves two methods based on deep neural networks: robot end-effector force estimation and joint torque estimation. These methods require no knowledge of robot dynamics and are computationally effective but require a force sensor under the robot base. Several different architectures were considered for the tasks, and the best ones were identified among those tested. First, the data for training the networks were obtained in simulation. The trained networks showed reasonably good performance, especially using the LSTM architecture (with a root mean squared error (RMSE) of 0.1533 N for end-effector force estimation and 0.5115 Nm for joint torque estimation). Afterward, data were collected on a real Franka Emika Panda robot and then used to train the same networks for joint torque estimation. The obtained results are slightly worse than in simulation (0.5115 Nm vs. 0.6189 Nm, according to the RMSE metric) but still reasonably good, showing the validity of the proposed approach.
Application of Differential Geometry to the Array Manifolds of Linear Arrays in Antenna Array Processing
Authors: Safi Alamgir , Khan Muhammad Asghar , Aziz Muhammad Adnan , Alsharif Mohammed H. , Cheema Tanweer Ahmad , Ullah Insaf , Jahid Abu , Alghtani Abdulaziz H , Aly Ayman A.
Published: November 2021

This article deals with the application of differential geometry to the array manifolds of non-uniform linear antenna array (NULA) when estimating the direction of arrival (DOA) of multiple sources present in an environment using far field approximation. In order to resolve this issue, we utilized a doublet linear antenna array (DLA) comprising two individual NULAs, along with a proposed algorithm that chooses correct directions of the impinging sources with the help of the prior knowledge of the ambiguous directions calculated with the application of differential geometry to the manifold curves of each NULA. The algorithm checks the correlation of the estimated direction of arrival (DOAs) by both the individual NULA with its corresponding ambiguous set of directions and chooses the output of the NULA, which has a minimum correlation between their estimated DOAs and corresponding ambiguous DOAs. DLA is designed such that the intersection of all the ambiguous set of DOAs among the individual NULAs are null sets. DOA of sources, which imping signals from different directions on the DLA, are estimated using three direction finding (DF) techniques, such as, genetic algorithm (GA), pattern search (PS), and a hybrid technique that utilizes both GA and PS at the same time. As compared to the existing techniques of ambiguity resolution, the proposed algorithm improves the estimation accuracy. Simulation results for all the three DF techniques utilizing the DLA along with the proposed algorithm are presented using MATLAB. As compared to the genetic algorithm and pattern search, the intelligent hybrid technique, such that, GA–PS, had better estimation accuracy in choosing corrected DOAs, despite the fact that the impinging DOAs were from ambiguous directions.
Occurrence of P. aeruginosa in Water Intended for Human Consumption and in Swimming Pool Water
Authors: Vukić Lušić Darija , Maestro Nerma , Cenov Arijana , Lušić Dražen , Smolčić Katarina , Tolić Sonja , Maestro Daniel , Kapetanović Damir , Marinac-Pupavac Sandra , Tomić Linšak Dijana , Linšak Željko , Glad Marin
Published: November 2021

Considering the fact that water is a basic need of every living being, it is important to ensure its safety. In this work, the data on the presence of the opportunistic pathogen P. aeruginosa in drinking water (n = 4171) as well as in pool water (n = 5059) in Primorje-Gorski Kotar County in Croatia in the five-year period (2016–2020) were analysed. In addition, the national criteria were compared with those of neighboring countries and worldwide. The proportion of P. aeruginosa-positive samples was similar for drinking water (3.9%) and pool water (4.6%). The prevalence of this bacterium was most pronounced in the warmer season. P. aeruginosa-positive drinking water samples were mostly collected during building commissioning, while pool samples were from entertainment and spa/hydromassage pools. Outdoor pools showed a higher percentage of positive samples than indoor pools, as well as the pools filled with freshwater rather than seawater. The highest P. aeruginosa load was found in rehabilitation pools. Croatia, Serbia and Montenegro are countries that have included P. aeruginosa in their national regulations as an indicator of the safety of water for human consumption as well as for bottled water, while Slovenia and Bosnia and Herzegovina have limited this requirement to bottled water only. In the case of swimming pool water, this parameter is mandatory in all countries considered in this study.
Delivery of Ecosystem Services by Community Woodland Groups and Their Networks
Authors: Dunn Mike , Ambrose-Oji Bianca , O’Brien Liz
Published: November 2021

The Millennium Ecosystem Assessment stresses that it is possible to manage ecosystems so as to strengthen their capacity to provide a range of goods and services. In reality, the delivery of ecosystem services reflects policy and delivery mechanisms, the environment, and the objectives of landowners and managers. Amid gradual changes to forest policy and more recent periods of austerity, the management of treescapes by locally led groups, such as Community Woodland Groups (CWGs), has become increasingly common. Through document analysis and interviews we explore the objectives and activities of British-based CWGs, and the implications these have for the delivery of ecosystem services. Additionally, we explore CWGs involvement with three types of networks and the ways in which each facilitate CWGs’ establishment, operations and ecosystem service provision. We conclude that, while CWGs are capable of delivering a range of ecosystem services, their focus is typically on: (i) cultural services for the benefit of the local community, and (ii) biodiversity. Since these foci parallel the goods and services emphasised in contemporary forest policy agendas, it is apparent that CWGs represent a promising model for woodland management. However, to realise their potential and confront management challenges, CWGs often rely on access to advice, labour, equipment and funding from across multiple networks.
Birds and the Fire Cycle in a Resilient Mediterranean Forest: Is There Any Baseline?
Authors: Prodon Roger
Published: November 2021

This study investigates the effects of recurrent wildfires on the resilience of a typical Mediterranean ecosystem. It is based on uninterrupted monitoring over 42 years of the avifauna in a cork oak forest that burned three times during this time interval. The monitoring involved two line-transect counts in spring accompanied by the simultaneous and independent estimation of the vegetation cover profile. One of the two transects was initially designed to serve as an unburned control before it also burned during the second fire. Many forest bird species were already present from the first spring postfire due to the rapid regeneration of the canopy. Some open-habitat bird species colonized the burned area during the first 2–4 years after the fire, resulting in an initial phase of high diversity. The postfire bird succession was mainly driven by sedentary species that recolonized the burned area after the first winter, whereas most migratory species present before the fire resettled as early as the first postfire spring, probably because of site tenacity. It was found that the impact of the second fire on avifauna was lower than that of the first or third fire. The return to an avifauna and forest structure successionally equivalent to the prefire control was achieved in about 15 years, which can be considered as the recovery time. Afterwards, both vegetation and avifauna in the burned areas tended to take on more forest characteristics than in the prefire control. These findings suggest that: (i) the recurrence of fire does not necessarily result in the cumulative degradation of the ecosystem at each repetition; (ii) the asymptotic resilience model is not adapted to the case of disturbances in non-mature environments; (iii) the notion of returning to an original undisturbed baseline is illusive in an area that has been under continuous human influence since ancient times.
The Contribution of Trees Outside of Forests to Landscape Carbon and Climate Change Mitigation in West Africa
Authors: Skole David L. , Samek Jay H. , Dieng Moussa , Mbow Cheikh
Published: November 2021

While closed canopy forests have been an important focal point for land cover change monitoring and climate change mitigation, less consideration has been given to methods for large scale measurements of trees outside of forests. Trees outside of forests are an important but often overlooked natural resource throughout sub-Saharan Africa, providing benefits for livelihoods as well as climate change mitigation and adaptation. In this study, the development of an individual tree cover map using very high-resolution remote sensing and a comparison with a new automated machine learning mapping product revealed an important contribution of trees outside of forests to landscape tree cover and carbon stocks in a region where trees outside of forests are important components of livelihood systems. Here, we test and demonstrate the use of allometric scaling from remote sensing crown area to provide estimates of landscape-scale carbon stocks. Prominent biomass and carbon maps from global-scale remote sensing greatly underestimate the “invisible” carbon in these sparse tree-based systems. The measurement of tree cover and carbon in these landscapes has important application in climate change mitigation and adaptation policies.
Handheld Devices for Food Authentication and Their Applications: A Review
Authors: Müller-Maatsch Judith , van Ruth Saskia M.
Published: November 2021

This review summarises miniaturised technologies, commercially available devices, and device applications for food authentication or measurement of features that could potentially be used for authentication. We first focus on the handheld technologies and their generic characteristics: (1) technology types available, (2) their design and mode of operation, and (3) data handling and output systems. Subsequently, applications are reviewed according to commodity type for products of animal and plant origin. The 150 applications of commercial, handheld devices involve a large variety of technologies, such as various types of spectroscopy, imaging, and sensor arrays. The majority of applications, ~60%, aim at food products of plant origin. The technologies are not specifically aimed at certain commodities or product features, and no single technology can be applied for authentication of all commodities. Nevertheless, many useful applications have been developed for many food commodities. However, the use of these applications in practice is still in its infancy. This is largely because for each single application, new spectral databases need to be built and maintained. Therefore, apart from developing applications, a focus on sharing and re-use of data and calibration transfers is pivotal to remove this bottleneck and to increase the implementation of these technologies in practice.
Who Are the Superfoodies? New Healthy Luxury Food Products and Social Media Marketing Potential in Germany
Authors: Wiedenroth Christoph Frank , Otter Verena
Published: November 2021

Superfoods, former traditional foods that in some cases are now regarded as new healthy luxury food products (NHLFP), have been growing in popularity in high- and middle-income societies. Despite a growing interest in superfoods, a precise definition of NHLFP, which appears to mark a subcategory of superfoods, together with a comprehensive analysis of NHLFP consumer segments does not yet exist. This is of particular relevance to managers as profound knowledge of different consumer groups is a prerequisite for the use of marketing approaches such as social media marketing. Therefore, this research proposes and validates an NHLFP definition and investigates whether promising NHLFP consumer groups can be identified based on selected psychographic and sociodemographic consumer characteristics and whether these groups are also accessible through social media marketing. A data set of 697 fruit consumers in Germany was retrieved in the time period of May to June 2020 and analyzed through exploratory factor analysis and hierarchical cluster analysis. Eleven factors and four consumer groups were identified, two of which represented favorable superfood consumer groups—one group consumed for intrinsic, health-related reasons rather than for luxury-driven motives, while the other showed tendencies to purchase superfoods for luxury reasons, thus emerging as a promising NHLFP target group. This group is relatively younger, well-educated, and highly receptive of online marketing.
Low Acrylamide Flatbreads Prepared from Colored Rice Flours and Relationship to Asparagine and Proximate Content of Flours and Flatbreads
Authors: Li Xueqi , Kahlon Talwinder , Wang Selina C. , Friedman Mendel
Published: November 2021

Acrylamide is a potentially toxic compound present in many plant-based foods, such as coffee, breads, and potato fries, which is reported to have carcinogenic, neurotoxic, and antifertility properties in vivo, suggesting the need to keep the acrylamide content of widely consumed food as low as possible. As pigmented rice contains bioactive phenolic and flavonoid compounds, the objective of this study was to potentially enhance the beneficial properties of flatbreads by evaluating the acrylamide content and proximate composition of 12 novel flatbreads prepared from the following commercial pigmented rice seeds: Black Japonica, Chinese Black, French Camargue, Himalayan Red, Long Grain Brown, Purple Sticky, Short Grain Brown, Wehani, Wild, Indian Brown Basmati, Organic Brown Jasmine, and Organic Jade Pearl. Although acrylamide levels ranged from 4.9 µg/kg in Long Grain Brown to 50.8 µg/kg in Chinese Black, the absolute values were all low (though statistically significantly differences existed among varieties). Acrylamide content did not correlate with its precursor asparagine. The variations in protein, carbohydrate, fat, ash, dry matter, and water content determined by proximate analysis, and the reported health benefits of colored rice cultivars used to prepare the flatbreads, might also be useful for relating composition to nutritional qualities and health properties, facilitating their use as nutritional and health-promoting functional foods.
Heavy Metals, Proximate Analysis and Brine Shrimp Lethality of Vernonia amygdalina and Ocimum gratissimum Growing in Crude Oil-Rich Delta State, Nigeria
Authors: Diyaolu Oluwatofunmilayo Arike , Attah Alfred F. , Oluwabusola Emmanuel T. , Moody Jones Olanrewaju , Jaspars Marcel , Ebel Rainer
Published: November 2021

Vernonia amygdalina (VA) and Ocimum gratissimum (OG) are among the most frequently consumed vegetables in Kokori and Abraka communities of Delta State, Nigeria. However, the continuous crude oil exploration and spillages in Kokori may threaten their safety for use as food and medicine. Twelve samples of VA and OG obtained from crude oil-rich and crude oil-free communities were comparatively analysed for proximate composition, heavy metals, and cytotoxicity. Data obtained were subjected to various multivariate statistical techniques, including principal component analysis (PCA), biplot, and analysis of variance (ANOVA), to investigate the correlations between the vegetables from the different communities and the effect of crude oil exploration and spill on plant biomass. Results obtained indicate a significant difference (p < 0.05) in the proximate composition of VA and OG and higher heavy metal content for VA from the crude oil-spill Kokori. Two VA collections from Kokori were exceptionally toxic to cellular crustaceans.
3D Characterization of Sponge Cake as Affected by Freezing Conditions Using Synchrotron X-ray Microtomography at Negative Temperature
Authors: Zennoune Amira , Latil Pierre , Ndoye Fatou-Toutie , Flin Frederic , Perrin Jonathan , Geindreau Christian , Benkhelifa Hayat
Published: November 2021

In this study, the microstructural evolution of a non-reactive porous model food (sponge cake) during freezing was investigated. Sponge cake samples were frozen at two different rates: slow freezing (0.3 °C min−1) and fast freezing (17.2 °C min−1). Synchrotron X-ray microtomography (µ-CT) and cryo-scanning electron microscopy (Cryo-SEM) were used to visualize and analyze the microstructure features. The samples were scanned before and after freezing using a specific thermostated cell (CellStat) combined with the synchrotron beamline. Cryo-SEM and 3D µ-CT image visualization allowed a qualitative analysis of the ice formation and location in the porous structure. An image analysis method based on grey level was used to segment the three phases of the frozen samples: air, ice and starch. Volume fractions of each phase, ice local thickness and shape characterization were determined and discussed according to the freezing rates.
Selection of Autochthonous LAB Strains of Unripe Green Tomato towards the Production of Highly Nutritious Lacto-Fermented Ingredients
Authors: Pereira Nelson , Alegria Carla , Aleixo Cristina , Martins Paula , Gonçalves Elsa M. , Abreu Marta
Published: November 2021

Lactic fermentation of unripe green tomatoes as a tool to produce food ingredients is a viable alternative for adding value to industrial tomatoes unsuitable for processing and left in large quantities in the fields. Fermentation using starter cultures isolated from the fruit (plant-matrix adapted) can have advantages over allochthonous strains in obtaining fermented products with sensory acceptability and potentially probiotic characteristics. This paper details the characterisation of the unripe green tomato lactic microbiota to screen LAB strains for use as starter cultures in fermentation processes, along with LAB strains available from INIAV’s collection. Morphological, biochemical (API system), and genomic (16S rDNA gene sequencing) identification showed that the dominant LAB genera in unripe green tomato are Lactiplantibacillus, Leuconostoc, and Weissella. Among nine tested strains, autochthonous Lactiplantibacillus plantarum and allochthonous Weissella paramesenteroides showed tolerance to added solanine (200 ppm) and the best in vitro probiotic potential. The results indicate that the two LAB strains are promising candidates for manufacturing probiotic fermented foods from unripe green tomatoes.
Changes of Volatile Flavor Compounds in Large Yellow Croaker (Larimichthys crocea) during Storage, as Evaluated by Headspace Gas Chromatography–Ion Mobility Spectrometry and Principal Component Analysis
Authors: Zhao Tengfei , Benjakul Soottawat , Sanmartin Chiara , Ying Xiaoguo , Ma Lukai , Xiao Gengsheng , Yu Jin , Liu Guoqin , Deng Shanggui
Published: November 2021

The large yellow croaker is one of the most economically important fish in Zhoushan, Zhejiang Province, and is well known for its high protein and fat contents, fresh and tender meat, and soft taste. However, the mechanisms involved in its flavor changes during storage have yet to be revealed, although lipid oxidation has been considered to be one important process in determining such changes. Thus, to explore the changes in the flavor of large yellow croaker fish meat during different storage periods, the main physical and chemical characteristics of the fish meat, including the acid value, peroxide value, p-anisidine value, conjugated diene value, and identities of the various flavor substances, were investigated and analyzed by multivariable methods, including headspace gas chromatography–ion mobility spectrometry (GC-IMS) and principal component analysis (PCA). It was found that after 60 d storage, the types and contents of the aldehyde and ketone aroma components increased significantly, while after 120 d, the contents of ketones (2-butanone), alcohols (1-propanethiol), and aldehydes (n-nonanal) decreased significantly. More specifically, aldehyde components dominated over ketones and lipids, while the n-nonanal content showed a downward trend during storage, and the 3-methylbutanol (trimer), 3-methylbutanol (dimer, D), 3-pentanone (D), and 3-pentanone (monomer) contents increased, whereas these compounds were identified as the key components affecting the fish meat flavor. Furthermore, after 120 d storage, the number of different flavor components reached its highest value, thereby confirming that the storage time influences the flavor of large yellow croaker fish. In this context, it should be noted that many of these compounds form through the Maillard reaction to accelerate the deterioration of fish meat. It was also found that after storage for 120 d, the physical indices of large yellow croaker meat showed significant changes, and its physicochemical properties varied. These results therefore demonstrate that a combination of GC-IMS and PCA can be used to identify the differences in flavor components present in fish meat during storage. Our study provides useful knowledge for understanding the different flavors associated with fish meat products during and following storage.
Cultured Meat Prospects for a Billion!
Authors: Kamalapuram Sishir K , Handral Harish , Choudhury Deepak
Published: November 2021

The dietary protein requirements of almost 9.8 billion people need to be fulfilled in a healthy and sustainable manner by 2050. Meat consumption contributes to 35% of the total protein requirement of the Indian population. Meat intake needs to be sustainable and economical without causing food security and production issues. Consumption of meat in India is projected to rise with an increase in consumer incomes. Hence, novel alternative proteins, including cultured meat (CM) and plant-based meat (PBM), are being developed to satisfy the demand for meat-derived proteins in the diet. This involves the creation of novel PBM/CM products with a similar taste and texture as conventional animal meat with tailor-made nutritional attributes. In this article, we provide critical insights into the technical and business aspects of relevance to production and sustainability encountered by the Indian CM industry at a series of stages that can be termed the CM value chain comprising upstream and downstream processes. We shed light on the need for regulatory authorities and a framework. Consumer concerns towards CM products can be alleviated through effective scientific communication strategies, including prior familiarity, narrative building and transparency, and labelling aspects of CM products.
Development of Antioxidant and Nutritious Lentil (Lens culinaris) Flour Using Controlled Optimized Germination as a Bioprocess
Authors: Rico Daniel , Peñas Elena , del Carmen García María , Rai Dilip K. , Martínez-Villaluenga Cristina , Frias Juana , Martín-Diana Ana B.
Published: November 2021

Germination is an efficient and natural strategy that allows the modification of the nutritional value and the nutraceutical properties of seeds, enabling one to tailor the process according to its final use. This study aimed at optimization of germination conditions to produce novel lentil flours with improved nutritional and functional features. Response Surface Methodology (RSM) was applied to model the effect of temperature (15–27 °C) and time (1–5 days) on different nutritional and quality parameters of lentil flours including proximate composition, content and profile of fatty acids, content of phytic acid, ascorbic acid and γ-aminobutyric acid (GABA), content and profile of phenolic compounds, antioxidant activity, expected glycemic index (GI) and color during germination. As shown by RSM polynomial models, sprouting promoted the reduction of phytic acid content and enhanced the levels of ascorbic acid, GABA, insoluble phenolic compounds, antioxidant activity and expected GI, and modified the color of the resultant lentil flours. RSM optimization of germination temperature and time using desirability function revealed that the optimal process conditions to maximize the nutritional, bioactive and quality properties of sprouted lentil flours were 21 °C for 3.5 days.
Authenticity of Hay Milk vs. Milk from Maize or Grass Silage by Lipid Analysis
Authors: Imperiale Sebastian , Kaneppele Elke , Morozova Ksenia , Fava Federico , Martini-Lösch Demian , Robatscher Peter , Peratoner Giovanni , Venir Elena , Eisenstecken Daniela , Scampicchio Matteo
Published: November 2021

Hay milk is a traditional dairy product recently launched on the market. It is protected as “traditional specialty guaranteed” (TSG) and subjected to strict regulations. One of the most important restrictions is that the cow’s feed ration must be free from silage. There is the need for analytical methods that can discriminate milk obtained from a feeding regime including silage. This study proposes two analytical approaches to assess the authenticity of hay milk. Hay milk and milk from cows fed either with maize or grass silage were analyzed by targeted GC-MS for cyclopropane fatty acid (dihydrosterculic acid, DHSA) detection, since this fatty acid is strictly related to the bacterial strains found in silage, and by HPLC-HRMS. The presence of DHSA was correlated to the presence of maize silage in the feed, whereas it was ambiguous with grass silage. HPLC-HRMS analysis resulted in the identification of 14 triacylglycerol biomarkers in milk. With the use of these biomarkers and multivariate statistical analysis, we were able to predict the use of maize and grass silage in the cow’s diet with 100% recognition. Our findings suggest that the use of analytical approaches based on HRMS is a viable authentication method for hay milk.
Epilobiumpyrricholophum Extract Suppresses Porcine Pancreatic Elastase and Cigarette Smoke Extract-Induced Inflammatory response in a Chronic Obstructive Pulmonary Disease Model
Authors: Jung Sun Young , Kim Gun-Dong , Choi Dae Woon , Shin Dong-Uk , Eom Ji-Eun , Kim Seung Yong , Chai Ok Hee , Kim Hyun-Jin , Lee So-Young , Shin Hee Soon
Published: November 2021

Chronic airway exposure to harmful substances, such as deleterious gases, cigarette smoke (CS), and particulate matter, triggers chronic obstructive pulmonary disease (COPD), characterized by impaired lung function and unbridled immune responses. Emerging epigenomic and genomic evidence suggests that excessive recruitment of alveolar macrophages and neutrophils contributes to COPD pathogenesis by producing various inflammatory mediators, such as reactive oxygen species (ROS), neutrophil elastase, interleukin (IL) 6, and IL8. Recent studies showed that Epilobium species attenuated ROS, myeloperoxidase, and inflammatory cytokine production in murine and human innate immune cells. Although the Epilobium genus exerts anti-inflammatory, antioxidant, and antimicrobial effects, the question of whether the Epilobium species regulate lung inflammation and innate immune response in COPD has not been investigated. In this study, Epilobium pyrricholophum extract (EPE) suppressed inflammatory cell recruitment and clinical symptoms in porcine pancreatic elastase and CS extract-induced COPD mice. In addition, EPE attenuated inflammatory gene expression by suppressing MAPKs and NFκB activity. Furthermore, UPLC-Q-TOF MS analyses revealed the anti-inflammatory effects of the identified phytochemical constituents of EPE. Collectively, our studies revealed that EPE represses the innate immune response and inflammatory gene expression in COPD pathogenesis in mice. These findings provide insights into new therapeutic approaches for treating COPD.
Structural and Physicochemical Characteristics of Oil Bodies from Hemp Seeds (Cannabis sativa L.)
Authors: Garcia Francesca Louise , Ma Sihan , Dave Anant , Acevedo-Fani Alejandra
Published: November 2021

The structural and physicochemical characteristics of oil bodies from hemp seeds were explored in this study. Oil bodies from several plant-based sources have been previously studied; however, this is the first time a characterisation of oil bodies from the seeds of industrial hemp is provided. The morphology of oil bodies in hemp seeds and after extraction was investigated using cryo-scanning electron microscopy (cryo-SEM), and the interfacial characteristics of isolated oil bodies were studied by confocal laser scanning microscopy (CLSM). Proteins associated with oil bodies were characterised using sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). The effect of pH and ionic strength on colloidal properties of the oil bodies was investigated. Oil bodies in hemp seeds appeared spherical and sporadically distributed in the cell, with diameters of 3 to 5 μm. CLSM images of isolated oil bodies revealed the uniform distribution of phospholipids and proteins at their interface. Polyunsaturated fatty acids were predominant in the lipid fraction and linoleic acid accounted for ≈61% of the total fatty acids. The SDS-PAGE analysis of washed and purified oil bodies revealed major bands at 15 kDa and 50–25 kDa, which could be linked to membrane-specific proteins of oil bodies or extraneous proteins. The colloidal stability of oil bodies in different pH environments indicated that the isoelectric point was between pH 4 and 4.5, where oil bodies experienced maximum aggregation. Changes in the ionic strength decreased the interfacial charge density of oil bodies (ζ-potential), but it did not affect their mean particle size. This suggested that the steric hindrance provided by membrane-specific proteins at the interface of the oil bodies could have prevented them from flocculation at low interfacial charge density. The results of this study provide new tertiary knowledge on the structure, composition, and colloidal properties of oil bodies extracted from hemp seeds, which could be used as natural emulsions or lipid-based delivery systems for food products.