bluuebunny/crossref_metadata_2025 huggingface dataset:
Human Activity Recognition Using an Ensemble Learning Algorithm with Smartphone Sensor Data
Authors: Tan Tan-Hsu , Wu Jie-Ying , Liu Shing-Hong , Gochoo Munkhjargal
Published: January 2022

Human activity recognition (HAR) can monitor persons at risk of COVID-19 virus infection to manage their activity status. Currently, many people are isolated at home or quarantined in some specified places due to the spread of COVID-19 virus all over the world. This situation raises the requirement of using the HAR to observe physical activity levels to assess physical and mental health. This study proposes an ensemble learning algorithm (ELA) to perform activity recognition using the signals recorded by smartphone sensors. The proposed ELA combines a gated recurrent unit (GRU), a convolutional neural network (CNN) stacked on the GRU and a deep neural network (DNN). The input samples of DNN were an extra feature vector consisting of 561 time-domain and frequency-domain parameters. The full connected DNN was used to fuse three models for the activity classification. The experimental results show that the precision, recall, F1-score and accuracy achieved by the ELA are 96.8%, 96.8%, 96.8%, and 96.7%, respectively, which are superior to the existing schemes.
Klystron-like Cyclotron Amplification of a Transversely Propagating Wave by a Spatially Developed Electron Beam
Authors: Novak Ekaterina , Samsonov Sergey , Savilov Andrei
Published: January 2022

A klystron-like gyro-amplifier based on the excitation of a wave propagating across a spatially developed (in the transverse direction) electron beam is described within the simplest 2-D model. Such a configuration is attractive as a way of implementation of a short-wavelength source with a relatively high level of output power and with the possibility of quasicontinuous frequency tuning. We study the peculiarities of the 2-D process (developing in both the axial and transverse directions) of electron bunching and “free” wave emission from the electron beam in the open drift space, as well as the excitation of the output cavity used to provide formation of a compact and powerful output wave signal. The main problem of this 2-D process is that different fractions of the electron beam (located at different points of its cross-section) move in different wave fields. In addition, excitation of the parasitic wave propagating in the opposite direction relative to the operating wave is possible. However, we show that it is possible to organize effective electron–wave energy exchange for almost all fractions of the electron beam.
Cavity Backed Slot Antenna Fed by a Stripline with SIW Structure and Vertical Coaxial Transition for Microwave Solid-State Heating Applications
Authors: Santón Pablo , De los Reyes Ruth , Balbastre Juan Vicente
Published: January 2022

This paper presents a new approach to feed multimode cavities used as microwave applicators for industrial and domestic microwave ovens using solid-state sources operating in the 2.45 GHz ISM (Industrial, Scientific and Medical) band (commonly used for industrial microwave applications). The feeding structure consists of a slot on the top side of the applicator cavity. The slot is fed by a shielded asymmetric stripline with a Substrate Integrated Waveguide structure (to preserve the stripline Transversal Electro-Magnetic (TEM) operation within the shield) and is N-connectorized. A first design of the antenna was obtained using state-of-the-art antenna theory assuming free-space radiation. Then, it was refined using a commercial simulation tool based on the Finite Element Method in the frequency domain to achieve VSWR values lower than 1.5 in the source bandwidth (from 2.42 to 2.48 GHz) when the antenna radiates into the applicator cavity. The design parameters of all the components making up this feeding structure are discussed throughout the paper. A prototype was built and measured in the laboratory. The experimental results are presented at the end of the paper along with the simulated ones, showing a very good agreement.
Wound Detection by Simple Feedforward Neural Network
Authors: Marijanović Domagoj , Nyarko Emmanuel Karlo , Filko Damir
Published: January 2022

Chronic wounds are a heavy burden on medical facilities, so any help in treating them is most welcome. Current research focuses on wound analysis, especially wound tissue classification, wound measurement, and wound healing prediction to assist medical personnel in wound treatment, with the main goal of reducing wound healing time. The first phase of wound analysis is wound segmentation, where the task is to extract wounds from the healthy tissue and image background. In this work, a standard feedforward neural network was developed for the purpose of wound segmentation using data from the MICCAI 2021 Foot Ulcer Segmentation (FUSeg) Challenge. It proved to be a simple yet efficient method for extracting wounds from images. The proposed algorithm is part of a compact system that analyzes chronic wounds using a robotic manipulator, RGB-D camera and 3D scanner. The feedforward neural network consists of only five fully connected layers, the first four with Rectified Linear Unit (ReLU) activation functions and the last with sigmoid activation functions. Three separate models were trained and tested using images provided as part of the challenge. The predicted images were post-processed and merged to improve the final segmentation performance.The accuracy metrics observed during model training and selection were Precision, Recall and F1 score. The experimental results of the proposed network provided a recall value of 0.77, precision value of 0.72, and an F1 score (Dice score) of 0.74.
Performance Analysis of Multi-User MIMO Schemes under Realistic 3GPP 3-D Channel Model for 5G mmWave Cellular Networks
Authors: Riviello Daniel Gaetano , Di Stasio Francesco , Tuninato Riccardo
Published: January 2022

Novel techniques such as mmWave transmission and massive MIMO have proven to present many attractive features able to support high data demand for 5G NR technologies. Towards the standardization of 5G networks, channel modeling has become an important step in order to test the reliability of theoretical studies. In this paper, we study the performance of a 5G network at mmWave range for the downlink. We consider a single trisectorized base station equipped with planar arrays, and we model users as a spatial Poisson process in a hexagonal grid. We adopt the latest 3GPP channel model described in TR 38.901 and we provide a thorough description and step-by-step tutorial of it along with our customizations and MATLAB scripts for channel generation in the presented scenario. Moreover, we evaluate the performance of Multi-User Multi-Layer MIMO techniques, such as Signal-to-Leakage-plus-Noise Ratio (SLNR) precoding and MMSE combined with different system configurations by means of achievable per-user rate.
Monitoring and Analysis of Geotemperature during the Tunnel Construction
Authors: Wen Tao , Hu Zheng , Wang Yankun , Zhang Zihan , Sun Jinshan
Published: January 2022

High geotemperatures are encountered during tunnel construction in areas with complex geological structures, which can seriously affect personnel and equipment in the process of tunnel construction and operation. The Nige tunnel, a deep-buried extra-long tunnel, was selected to monitor the geotemperature during construction. The air, rock, and water temperatures during the tunnel construction were measured at the tunnel face, and the actual temperatures of the rock or water body at the tunnel face were measured by advanced drilling. The variation trends of the water temperature, air temperature, and flow of water with the tunnel mileage were analyzed. The differences in three measured rock temperatures in three advanced drillings were revealed. The results showed that the Nige tunnel had a maximum water temperature of 63.4 °C, maximum rock temperature (Rock T) of 88.8 °C, and maximum air temperature (Air T) of 56.4 °C. Increasing trends of the air, rock, and water temperatures with the tunnel’s horizontal distance and the buried depth (vertical depth) were obvious, and the geotemperature gradient was approximately 7.6 °C per 100 m. Additionally, the variation laws of the construction ambient temperature with time in a complete construction cycle showed four stage characteristics, and each stage presented different mathematical relationships. These findings will provide guidance for the construction of high geotemperature tunnels in future.
Optimized EMS and a Comparative Study of Hybrid Hydrogen Fuel Cell/Battery Vehicles
Authors: Kamal Elkhatib , Adouane Lounis
Published: January 2022

This paper presents a new Fuel Cell Fuel Consumption Minimization Strategy (FCFCMS) for Hybrid Electric Vehicles (HEVs) powered by a fuel cell and an energy storage system, in order to minimize as much as possible the consumption of hydrogen while maintaining the State Of Charge (SOC) of the battery. Compared to existing Energy Management Strategies (EMSs) (such as the well-known State Machine Strategy (SMC), Fuzzy Logic Control (FLC), Frequency Decoupling and FLC (FDFLC), and the Equivalent Consumption Minimization Strategy (ECMS)), the proposed strategy increases the overall vehicle energy efficiency and, therefore, minimizes the total hydrogen consumption while respecting the constraints of each energy and power element. A model of a hybrid vehicle has been built using the TruckMaker/MATLAB software. Using the Urban Dynamometer Driving Schedule (UDDS), which includes several stops and accelerations, the performance of the proposed strategy has been compared with these different approaches (SMC, FLC, FDFLC, and ECMS) through several simulations.
Optimization of Active Power Losses in Smart Grids Using Photovoltaic Power Plants
Authors: Pál Daniel , Beňa Ľubomír , Kolcun Michal , Čonka Zsolt
Published: January 2022

This article addresses the reduction of power losses in smart grids. Two optimization algorithms are used in this article. The first method is the enumerative method. The second method of the optimization calculation is based on the self-organizing migrating algorithm. In the first step, the network parameters are calculated based on the input data, and then the target function is determined. In this article, the target function is used to reduce the active power losses that occur during the operation of an electric network. More specifically, we attempt to determine the reactive power with the enumerative and SOMA algorithms to reduce the value of the active power losses. This article intends to illustrate the differences between the selected optimization algorithms. As observed, the optimization algorithm determines the computation time.
Investigation of Biomass Integrated Air Gasification Regenerative Gas Turbine Power Plants
Authors: Abdalla Momin Elhadi , Abdalla Salah Ahmed , Taqvi Syed Ali Ammar , Naqvi Salman Raza , Chen Wei-Hsin
Published: January 2022

The results show that Wood Chips of Acacia Nilotica trees available in Sudan lands can be successfully used in the gasification process and, on the same basis, as a bio-renewable energy resource. Simulation models were used to characterize the air gasification process integrated with a Regenerative Gas Turbine Unit. The results revealed that at a moisture content of 12%, gasification temperature of 1500 K, pressure of 20 bar, and air-like gasification medium, the biomass gasifier’s flow rate is higher at higher syngas rates. The results verified that there is an optimum ER for each syngas rate, in which the slow growth of the ER revealed the maximum gasifier biomass flow rate. For ER growth at lower levels, the specific fuel consumption (SFC) of the RGT Unit declines sharply from the maximum value reached at 0.27 kg/kW·h at an ER of 5% to the minimum value reached at 0.80 kg/kW·h at an ER of 25% for the lowest gasification temperature of 1000 K. Moreover, ER growths at low levels have a significant effect on the RGT plant’s performance, leading to increased RGT thermal efficiency. The increase in the biomass moisture content led to a sharp decrease in the RGT thermal efficiency. The RGT thermal efficiency remains high at higher gasification pressure. The results revealed that the syngas lower heating value remains high at lower produced syngas rates. At the optimum ER, the H2 mole fraction depicted a value of 1.25%, 0.85% of CO, and 10.50% of CH4 for a lower heating value of 38 MJ/kg syngas. It is shown that the gasification air entered into the gasifier decreases amid the increase in the biomass moisture content. At different syngas rates (3–10 kg/s) and optimum ER, the results predicted that the Wood Chip biomass flow rates decrease when the gasifier efficiency increases. The simulation model revealed that ER growths at lower levels have a significant effect on increasing the power of the RGT plant.
Vibration Enhancement or Weakening Effect Caused by Permanent Magnet Synchronous Motor Radial and Tangential Force Formed by Tooth Harmonics
Authors: Liu Mingchuan , Zou Jibin , Xu Yongxiang , Lan Hua , Yu Guodong
Published: January 2022

This paper investigates the vibration enhancement or weakening effect caused by permanent magnet synchronous motor radial and tangential force formed by tooth harmonics. First, the analytical expressions of an air gap magnetic field are deduced based on a permanent magnet synchronous motor model. Then, the Maxwell stress tensor method is employed to calculate the radial and tangential force density produced by permanent magnet magnetomotive force harmonics and tooth harmonics. Moreover, the spatial phase difference between the minimum non-zero spatial order radial and tangential force waves under loading operation are also obtained. It is followed by stator vibration deformation induced by radial and tangential force waves, and the vibration enhancement or weakening effect is discussed. This study shows that the tangential force wave has a significant influence on the vibration performance similar to the radial force wave. At specific frequencies, superposition of the radial and tangential force waves can intensify the vibration while weakening each other to reduce the vibration at other specific frequencies. Numerical simulation and a vibration measurement experiment of the prototype motor were carried out to confirm the proposed theory, which can guide motor designers in selecting an appropriate pole and slot combination to apply the weakening effect between radial and tangential force waves and improve PMSM vibration performance.
The Value of Sector Coupling for the Development of Offshore Power Grids
Authors: Gea-Bermúdez Juan , Kitzing Lena , Koivisto Matti , Das Kaushik , Murcia León Juan Pablo , Sørensen Poul
Published: January 2022

Offshore grids can play key roles in the transition of energy systems toward sustainability. Although they require extensive infrastructure investments, they allow for the exploitation of additional resources and may be important in providing for part of the increasing electricity demands driven by sector coupling. This paper quantifies the socioeconomic value of offshore grids and identifies their major drivers, performing energy system optimization in a model application of the northern–central European energy system and the North Sea offshore grid towards 2050. The increasing wake loss with the sizes of hub-connected wind farms is integrated in the modeling. We find that without sector coupling no offshore grid may develop, and that the higher the level of sector coupling, the higher the value of offshore grids. Therefore, it can be strongly stated that offshore grid infrastructure development should not be discussed as a separate political topic, but seen in connection to sector coupling.
Thermo-Chemical Conversion of Microwave Selectively Pre-Treated Biomass Blends
Authors: Goldšteins Linards , Dzenis Māris Gunārs , Valdmanis Raimonds , Zaķe Maija , Arshanitsa Alexandr
Published: January 2022

Possibilities of more efficient use of regional lignocellulosic resources (wood, wheat straw, peat) of different origin for an environmentally friendly energy production using selectively MW pre-treated blends of commercial wood or wheat straw pellets with raw peat pellets are studied. A hypothesis is proposed and tested that selective MW pre-treatment of wood or wheat straw pellets at the frequency 2.45 GHz and blending of MW pre-treated pellets with raw peat pellets can be used to enhance and control the thermo-chemical conversion of biomass blends. To test this hypothesis, a combined experimental study and mathematical modelling of the processes were performed. The thermo-chemical conversion of selectively activated blends was experimentally studied using a batch-size pilot device, which consists of a biomass gasifier and a combustor. To evaluate the effect of selective MW pre-treatment of biomass pellets on the thermo-chemical conversion of pre-treated blends, measurements of the kinetics of weight loss, yield of combustible volatiles, flame temperature, heat output of the device, and composition of emissions were made at different MW pre-treatment regimes of wheat straw and wood pellets and different mass fractions of pre-treated pellets in biomass blends. The developed novel 2D numerical model of thermo-chemical conversion of MW pre-treated straw confirmed that the pre-treatment of wheat straw pellets increases the generated heat and significantly affects the temperature distribution in the flame/bed zones. It was confirmed that MW pre-treatment leads to a faster thermal decomposition of biomass pellets, synergistically activating the non-treated parts of blends. The overall improved yield of combustible volatiles and their complete combustion provide a surplus of heat production by limiting the formation of GHG emissions, which allows promoting MW pre-treated biomass of different origin as efficient regional bioenergy resources for energy production.
Fault Diagnosis of Submersible Motor on Offshore Platform Based on Multi-Signal Fusion
Authors: Zhang Yahui , Yang Kai
Published: January 2022

As an important production equipment of the offshore platform, the operation reliability of submersible motors is critical to oil and gas production, natural gas energy supplies, and social and economic benefits, etc. In order to realize the health management and fault diagnosis of submersible motors, a motor fault-monitoring method based on multi-signal fusion is proposed. The current signals and vibration signals were selected as characteristic signals. Through fusion correlation analysis, the correlation between different signals was established to enhance the amplitude at the same frequency, so as to highlight the motor fault characteristic frequency components, reduce the difficulty of fault identification, and provide sample data for motor fault pattern identification. Furthermore, the wavelet packet node energy analysis and back propagation neural network were combined to identify the motor faults and realize the real-time monitoring of the operating status of the submersible motor. The genetic algorithm was used to optimize the parameters of the neural network model to improve the accuracy of motor fault pattern recognition. The results show that the combination of multi-signal fusion monitoring and an artificial intelligence algorithm can diagnose motor fault types with high confidence. This research originally proposed the fusion correlation spectrum technology, which solved the shortcomings of the small amplitude and complex composition of the single signal spectrum components in the fault diagnosis and improved the reliability of the fault diagnosis. It further combined the neural network to realize the automatic monitoring and intelligent diagnosis of submersible motors, which has certain application value and inspiration in the field of electrical equipment intelligent monitoring.
Possibility to Use Professional Bicycle Computers for the Scientific Evaluation of Electric Bikes: Trajectory, Distance, and Slope Data
Authors: Matyja Tomasz , Kubik Andrzej , Stanik Zbigniew
Published: January 2022

This work presents an analysis of data recorded by a bicycle computer paired with typical measurement sensors in order to determine whether the data can be useful for a scientific evaluation of the cyclist–electric bicycle anthropotechnical system. There are no studies on this subject in the available literature. An attempt was made to estimate the quality of data and define the most effective methods of processing and filtering. The imperfections of the measurement system and the potential directions of the development of bicycle computers are indicated. Particular attention has been given to the data needed to compare the energy efficiency of assisted electric bicycles. However, the results of the analyses can also be used in cyclist endurance tests and to simulate routes in various types of bicycle trainers. The article focuses on the data obtained from the GPS module and the barometric altimeter, which make it possible to estimate the trajectory of movement, the distance traveled, and the height of the route above sea level as well as its slope. In order to assess the accuracy, the data from the bicycle computer was compared with the geodetic data. Methods for averaging GPS routes were also proposed. In this way, it was possible to identify the parameters of the selected path for testing bicycles quite accurately. The research presented in this paper is an introduction to the development of methods for assessing the energy efficiency of electric bicycles. Analyses of other data measured by the cycling computer, such as speed, cadence, and power, will be carried out in the second planned part of the article.
Multi-Criteria Decision Support System for Smart and Sustainable Machining Process
Authors: Celent Luka , Mladineo Marko , Gjeldum Nikola , Crnjac Zizic Marina
Published: January 2022

Sustainatableble development assumes the meeting of humanity’s everyday needs and development goals while sustaining the ability of nature to provide the resources and ecosystem on which the economy and society depend. It means that an increase of economic benefit cannot be a single optimization problem anymore, instead, the multi-criteria approach is used with the accent on ecology and social welfare. However, it is not easy to harmonize these aims with machining, which is a well known industrial pollutant. On the other hand, new industrial paradigms such as Industry 4.0/5.0, are driving toward the smart concept that collects data from the manufacturing process and optimizes it in accordance with productivity and/or ecologic aims. In this research, the smart concept is used through the development of the multi-criteria decision support system for the selection of the optimal machining process in terms of sustainability. In the case of milling process selection, it has been demonstrated that green machining, without a multi-criteria approach, will always remain an interesting research option, but not a replacement for conventional machining. However, when applying realistic ecological and social criteria, green machining becomes a first choice imperative. The multi-criteria decision-making PROMETHEE method is used for the comparison and ranking, and validation of results is made through criteria weights sensitivity analysis. The contribution of this concept is that it could also be applied to other manufacturing processes.
Environmental and Economic Impacts of Mismanaged Plastics and Measures for Mitigation
Authors: Diggle Avalon , Walker Tony R.
Published: January 2022

The mismanagement of plastic materials has grown to become a mounting global pollution concern that is closely implicated in unsustainable production and consumption paradigms. The ecological, social, and economic impacts of plastic waste mismanagement are currently transboundary in nature and have necessitated numerous methods of government intervention in order to address and mitigate the globalized and multifaceted dilemmas posed by high rates and volumes of plastic waste generation. This review examines the current landscape of a plastics economy which has operated with a linear momentum, employing large quantities of primary resources and disincentivizing the functioning of a robust recycling market for collecting plastic waste and reintegrating it into the consumer market. This contextualizes an increasing plastic pollution crisis that has required global efforts to address and mitigate the ecological risks and socio-economic challenges of mismanaged plastic waste. A timeline of government interventions regarding plastic pollution is described, including numerous international, regional, and local actions to combat plastic waste, and this is followed by an examination of the relevance of the extended producer responsibility principle to improve plastic waste management and obligate industry to assume responsibility in waste collection and recycling.
Comparison of Data Grouping Strategies on Prediction Accuracy of Tree-Stem Taper for Six Common Species in the Southeastern US
Authors: Yang Sheng-I , Green P. Corey
Published: January 2022

Clustering data into similar characteristic groups is a commonly-used strategy in model development. However, the impact of data grouping strategies on modeling stem taper has not been well quantified. The objective of this study was to compare the prediction accuracy of different data grouping strategies. Specifically, a population-level model was compared to the models fitted with grouped data based on taxonomic rank, tree form and size. A total of 3678 trees were used in the analyses, which included six common species in upland hardwood forests of the southeastern U.S. Results showed that overall predictions are more accurate when building stem taper models at the species, species group or division level rather than at the population level. The prediction accuracy was not considerably improved between species-specific functions and models fitted with species-related groups for the four hardwood species examined. Grouping data by taxonomic rank provided more reliable predictions than height-to-diameter ratio (H–D ratio) or diameter at breast height (DBH). The form/size-related grouping methods (i.e., data grouped by H–D ratio or DBH) generally did not improve the prediction precision compared to a population-level model. In this study, the effect of sample size in model fitting showed a minimal impact on prediction accuracy. The methodology presented in this study provides a modeling strategy for mixed-species data, which will be of practical importance when data grouping is needed for developing stem taper models.
Remedial Action of Yoghurt Enriched with Watermelon Seed Milk on Renal Injured Hyperuricemic Rats
Authors: Shahein Magdy Ramadan , Atwaa El Sayed Hassan , El-Zahar Khaled Magawry , Elmaadawy Ahdab Abdo , Hijazy Hayfa Hussin Ali , Sitohy Mahmoud Zaky , Albrakati Ashraf , Elmahallawy Ehab Kotb
Published: January 2022

The consumption of plant-based dairy alternatives has increased rapidly around the world as a result of numerous positive health effects. Little information is available about the potential use of watermelon seed milk in the manufacture of yoghurt. The present study was undertaken to investigate the remedial action of yoghurt enriched with watermelon seed milk in renal injured hyperuricemic rats. A new yoghurt, substituting cow’s milk with different proportions of watermelon seed milk was prepared, followed by evaluation of its acceptability and functionality. Four different types of yoghurt were prepared from cow’s milk containing 3% fat, with different proportions of blended watermelon seed milk (0.0, 25, 50 and 75%). Sensorial traits, i.e., appearance, flavor, body and texture, and overall acceptability demonstrated that the blended treatment (50% cow’s milk and 50% watermelon seed milk.) was the most acceptable. This blend was then tested as an anti-hyperuricemia agent in rats. In this respect, twenty-four male albino rats were assigned into four groups (n = 6). The first group was solely administered a standard diet, and served as the negative control. The other rats (n = 18) received a basal diet including 20 g/kg dietary potassium oxonate in order to induce hyperuricemia. The hyperuricemic rats were then divided into three groups; the first group did not receive any treatment and served as the positive control, while the second and third groups were administered 10% cow’s milk yoghurt and 10% watermelon seed milk yoghurt, respectively. Interestingly, the results showed that the hyperuricemic group receiving a diet supplemented with 10% watermelon seed milk yoghurt was not significantly different from the negative control in the measured biological parameters, and saw a significant improvement in renal function compared to the positive control. The biologically favorable action of watermelon seed milk yoghurt could be attributed to its potential promotion of antioxidant status via enhancement of the activities of superoxide dismutase, catalase, and glutathione transferase. Collectively, this study concluded that watermelon seed milk can be used in yoghurt manufacturing in proportions of up to 50%, and may improve kidney function as an anti-hyperuricemic agent.
New Avoparcin-like Molecules from the Avoparcin Producer Amycolatopsis coloradensis ATCC 53629
Authors: Ramoni Gina , Capozzoli Carmine , Bava Adriana , Foschi Francesca , Broggini Gianluigi , Beltrametti Fabrizio
Published: January 2022

Amycolatopsis coloradensis ATCC 53629 is the producer of the glycopeptide antibiotic avoparcin. While setting up the production of the avoparcin complex, in view of its use as analytical standard, we uncovered the production of a to-date not described ristosamynil-avoparcin. Ristosamynil-avoparcin is produced together with α- and β-avoparcin (overall indicated as the avoparcin complex). Selection of one high producer morphological variant within the A. coloradensis population, together with the use of a new fermentation medium, allowed to increase productivity of the avoparcin complex up to 9 g/L in flask fermentations. The selected high producer displayed a non-spore forming phenotype. All the selected phenotypes, as well as the original unselected population, displayed invariably the ability to produce a complex rich in ristosamynil-avoparcin. This suggested that the original strain deposited was not conforming to the description or that long term storage of the lyovials has selected mutants from the original population.
Simulating Forest Fire Spread with Cellular Automation Driven by a LSTM Based Speed Model
Authors: Li Xingdong , Zhang Mingxian , Zhang Shiyu , Liu Jiuqing , Sun Shufa , Hu Tongxin , Sun Long
Published: January 2022

The simulation of forest fire spread is a key problem for the management of fire, and Cellular Automata (CA) has been used to simulate the complex mechanism of the fire spread for a long time. The simulation of CA is driven by the rate of fire spread (ROS), which is hard to estimate, because some input parameters of the current ROS model cannot be provided with a high precision, so the CA approach has not been well applied yet in the forest fire management system to date. The forest fire spread simulation model LSTM-CA using CA with LSTM is proposed in this paper. Based on the interaction between wind and fire, S-LSTM is proposed, which takes full advantage of the time dependency of the ROS. The ROS estimated by the S-LSTM is satisfactory, even though the input parameters are not perfect. Fifteen kinds of ROS models with the same structure are trained for different cases of slope direction and wind direction, and the model with the closest case is selected to drive the transmission between the adjacent cells. In order to simulate the actual spread of forest fire, the LSTM-based models are trained based on the data captured, and three correction rules are added to the CA model. Finally, the prediction accuracy of forest fire spread is verified though the KAPPA coefficient, Hausdorff distance, and horizontal comparison experiments based on remote sensing images of wildfires. The LSTM-CA model has good practicality in simulating the spread of forest fires.
Use of Focus Group as Selection Method of Descriptors for Check-All-That-Apply (CATA) for Sensory Characteristics of Hot Dogs
Authors: Rodrigues Isabela , Magalhaes Danielle Rodrigues , Trindade Marco Antonio
Published: January 2022

Check-all-that-apply (CATA) is a methodology for sensory product characterization that can be used by consumers. These characteristics, on the other hand, are determined by a trained panel, and consumers are not asked how they perceive these attributes; as a result, some of the characteristics raised by the trained panel may not be relevant to consumers. In this study, the CATA test was applied to characterize three types of hot dogs, those with or without irradiation and salt reduction, and the focus group (FG) technique was employed to determine the CATA descriptors. Each participant in the FG provided five words (attributes) that, in their opinion, best defined each sample. Then, to understand the meaning and to assemble each of the different terms, a discussion of the defined attributes was conducted. The list of CATA descriptors was compiled using the most often cited attributes. The findings indicate that the major difference in hot dogs was between the formulations with and without sodium reduction. The consumers only noticed minor effects resulting from the irradiation process. The use of focus group as the method to select the CATA descriptors related to hot dogs was proven to be valid since the words that were listed for these samples were attributes that typically characterize hot dog sausages.
Italian Tomato Cultivars under Drought Stress Show Different Content of Bioactives in Pulp and Peel of Fruits
Authors: Conti Veronica , Romi Marco , Guarnieri Massimo , Cantini Claudio , Cai Giampiero
Published: January 2022

Background: This study aims to evaluate the performance, in terms of accumulation of antioxidant compounds in fruits, of nine local and three commercial Italian tomato cultivars subjected to drought stress. The same local cultivars had been previously studied at morpho-physiological level. Methods: The present manuscript analyzes drought stress as a tool to increase the amount of secondary metabolites that can enhance fruit quality. Nutraceutical characterization of the fruits was performed by analyzing the content of antioxidants, phenols, flavonoids, lycopene, ascorbic acid (vitamin C), rutin, caffeic acid, and naringenin. At the same time, plant sensitivity to stress during the reproductive phase was monitored in terms of flower abscission, fruit drop, and seed germination. Results: Perina turns out to be the tomato cultivar with the best nutraceutical properties in the absence of stress while the Quarantino cultivar is so for flavonoid content (control plants) and lycopene and vitamin C content (stressed plants). Perina and Quarantino are the cultivars with the best response to drought and Perina has the highest concentrations of bioactives. Quarantino responds most effectively to stress in the reproductive phase. Conclusions: data confirm that drought stress increases bioactive production in some local cultivars of tomato, which produce higher quality fruits.
Stable Isotope and Element Profiling for Determining the Agroclimatic Origin of Cow Milk within a Tropical Country
Authors: Kalpage Maheshika , Dissanayake Champa , Diyabalanage Saranga , Chandrajith Rohana , Frew Russell , Fernando Ruchika
Published: January 2022

Information on the geographic origin of milk is important in determining quality attributes and for economic gain through building brand value associated with origin. Stable isotope signatures and trace element concentrations have been increasingly used in authentication of milk, though information on the power of such technology in verifying agroclimatic origin in small continents with diverse climatic, environmental conditions, and animal management practice is scarce. Therefore, the main objective of this study was to investigate the possibility of using a stable isotope composition of C, N, O, and H and element fingerprints to determine the agroclimatic origin of milk produced in different agroclimatic zones of Sri Lanka. Stable isotopes ratios of C, N, H, and O, and elemental fingerprints of milk samples were determined by IRMS and ICP-MS, respectively. Significant variations were observed in stable isotope ratios, especially δ18O and the mean content of Li, Al, Cr, Mn, and Sr in the bulk milk samples obtained from different agroclimatic zones. A linear discriminant analysis differentiated cow milk produced from four agroclimatic zones based on stable isotope ratios, and the inclusion of elemental ratios enhanced the discriminating ability.
Effects of the Incorporation of Calcium Chloride on the Physical and Oxidative Stability of Filled Hydrogel Particles
Authors: Li Xin , Cao Chuanai , Yuan Dongxue , Liu Qian , Zhao Jinhai
Published: January 2022

In this study, the effects of calcium chloride (CaCl2) addition on the physical and oxidative stabilities of filled hydrogel were investigated. The results revealed that CaCl2 significantly enhanced the particle size, interfacial layer thickness, apparent viscosity, and viscoelastic behavior of filled hydrogels and decreased their light and whiteness values (p < 0.05). This phenomenon was mainly attributed to the strong binding ability between Ca2+ and protein/pectin mixtures, which were present in the interfacial area or aqueous phase, as verified by cryo-scanning electron microscopy results. Moreover, lower levels of CaCl2 (2 or 4 mM) significantly enhanced the oxidative stability of filled hydrogels (p < 0.05), particularly at a concentration of 4 mM. However, a higher level of CaCl2 (6 or 8 mM) resulted in an electrostatic shielding effect, which resulted in the aggregation of multiple droplets and the flocculation of the filled hydrogels, which negatively affected the oxidative stability of filled hydrogels. The findings of this study indicated that appropriate Ca2+ levels (4 mM) improved the physical and oxidative stability of filled hydrogel, and this finding may provide useful insights for the development of effective delivery systems for specific applications.
Preparation of Water-in-Oil Nanoemulsions Loaded with Phenolic-Rich Olive Cake Extract Using Response Surface Methodology Approach
Authors: Niknam Seyed Mehdi , Kashaninejad Mansoore , Escudero Isabel , Sanz María Teresa , Beltrán Sagrario , Benito José M.
Published: January 2022

In this study, we aimed to prepare stable water-in-oil (W/O) nanoemulsions loaded with a phenolic-rich aqueous phase from olive cake extract by applying the response surface methodology and using two methods: rotor-stator mixing and ultrasonic homogenization. The optimal nanoemulsion formulation was 7.4% (w/w) of olive cake extract as the dispersed phase, and 11.2% (w/w) of a surfactant mixture of polyglycerol polyricinoleate (97%) and Tween 80 (3%) in Miglyol oil as the continuous phase. Optimum results were obtained by ultrasonication for 15 min at 20% amplitude, yielding W/O nanoemulsion droplets of 104.9 ± 6.7 nm in diameter and with a polydispersity index (PDI) of 0.156 ± 0.085. Furthermore, an optimal nanoemulsion with a droplet size of 105.8 ± 10.3 nm and a PDI of 0.255 ± 0.045 was prepared using a rotor-stator mixer for 10.1 min at 20,000 rpm. High levels of retention of antioxidant activity (90.2%) and phenolics (83.1–87.2%) were reached after 30 days of storage at room temperature. Both W/O nanoemulsions showed good physical stability during this storage period.
Role of Flaxseed Gum and Whey Protein Microparticles in Formulating Low-Fat Model Mayonnaises
Authors: Yang Keying , Xu Ruoting , Xu Xiyu , Guo Qing
Published: January 2022

Flaxseed gum (FG) and whey protein microparticles (WPMs) were used to substitute fats in model mayonnaises. WPMs were prepared by grinding the heat-set whey protein gel containing 10 mM CaCl2 into small particles (10–20 µm). Then, 3 × 4 low-fat model mayonnaises were prepared by varying FG (0.3, 0.6, 0.9 wt%) and WPM (0, 8, 16, 24 wt%) concentrations. The effect of the addition of FG and WPMs on rheology, instrumental texture and sensory texture and their correlations were investigated. The results showed that all samples exhibited shear thinning behavior and ‘weak gel’ properties. Although both FG and WPMs enhanced rheological (e.g., viscosity and storage modulus) and textural properties (e.g., hardness, consistency, adhesiveness, cohesiveness) and kinetic stability, this enhancement was dominated by FG. FG and WPMs affected bulk properties through different mechanisms, (i.e., active filler and entangled polysaccharide networks). Panellists evaluated sensory texture in three stages: extra-oral, intra-oral and after-feel. Likewise, FG dominated sensory texture of model mayonnaises. With increasing FG concentration, sensory scores for creaminess and mouth-coating increased, whereas those of firmness, fluidity and spreadability decreased. Creaminess had a linear negative correlation with firmness, fluidity and spreadability (R2 > 0.985), while it had a linear positive correlation with mouth-coating (R2 > 0.97). A linear positive correlation (R2 > 0.975) was established between creaminess and viscosity at different shear rates/instrumental texture parameters. This study highlights the synergistic role of FG and WPMs in developing low-fat mayonnaises.
Application of Aqueous Saline Process to Extract Silkworm Pupae Oil (Bombyx mori): Process Optimization and Composition Analysis
Authors: Tangsanthatkun Janjira , Peanparkdee Methavee , Katekhong Wattinee , Harnsilawat Thepkunya , Tan Chin Ping , Klinkesorn Utai
Published: January 2022

Silkworm pupae, a waste product from the silk production industry, can be an alternative source of edible oil, thus reducing the industry’s waste. In the present work, frozen silkworm pupae were used as raw material to extract oil via an aqueous saline process. The Box–Behnken design (BBD) and response surface methodology (RSM) were used to optimize the extraction process. The extraction conditions with the highest oil yield and a low peroxide value were obtained when using a saline solution concentration of 1.7% w/v, a ratio of aqueous liquid to silkworm pupae of 3.3 mL/g, and a 119 min stirring time at the stirring speed of 100 rpm. Under these conditions, silkworm oil with a yield of 3.32%, peroxide values of approximately 1.55 mM, and an acid value of 0.67 mg KOH/g oil was obtained. The extracted oil contained omega-3 acids (α-linolenic acid), which constituted around 25% of the total fatty acids, with approximate cholesterol levels of 109 mg/100 g oil. The amounts of β-carotene and α-tocopherol were approximately 785 and 9434 μg/100 g oil, respectively. Overall, the results demonstrated that oil extracted from silkworm pupae has good quality parameters and thus can be used as a new valuable source of edible lipids.
Application of 3D Gel Dosimetry as a Quality Assurance Tool in Functional Leksell Gamma Knife Radiosurgery
Authors: Kudrevicius Linas , Jaselske Evelina , Adliene Diana , Rudzianskas Viktoras , Radziunas Andrius , Tamasauskas Arimantas
Published: January 2022

Highly precise dose delivery to the target (tumor or cancerous tissue) is a key point when brain diseases are treated applying recent stereotactic techniques: intensity-modulated, image-guided radiotherapy, volumetric modulated arc therapy, Gamma knife radiosurgery. The doses in one single shot may vary between tens and hundreds of Gy and cause significant cell/tissue/organ damages. This indicates the need for implementation of quality assurance (QA) measures which are realized performing treatment dose verification with more than one calibrated quality assurance method or tool, especially when functional radiosurgery with a high dose (up to 40 Gy in our case) shall be delivered to the target using small 4 mm collimator. Application of two dosimetry methods: radiochromic film dosimetry using RTQA2 and EBT3 films and dose gel dosimetry using modified nPAG polymer gels for quality assurance purposes in stereotactic radiosurgery treatments using Leksell Gamma Knife© Icon™ facility is discussed in this paper. It is shown that due to their polymerization ability upon irradiation nPAG gels might be potentially used as a quality assurance tool in Gamma knife radiosurgery: they indicate well pronounced linear dose response in hypo-fractionated (up to 10 Gy) dose range and are sensitive enough to irradiation dose changes with a high (at least 0.2 mm) spatial resolution. Dose assessment sensitivity of gels depends on parameters of a dose evaluation method (optical or magnetic resonance imaging), however, is similar to this estimated using film dosimetry, which is set as a standard dosimetry method for dose verification in radiotherapy.
Inherent and Composite Hydrogels as Promising Materials to Limit Antimicrobial Resistance
Authors: Carpa Rahela , Remizovschi Alexei , Culda Carla Andreea , Butiuc-Keul Anca Livia
Published: January 2022

Antibiotic resistance has increased significantly in the recent years, and has become a global problem for human health and the environment. As a result, several technologies for the controlling of health-care associated infections have been developed over the years. Thus, the most recent findings in hydrogel fabrication, particularly antimicrobial hydrogels, could offer valuable solutions for these biomedical challenges. In this review, we discuss the most promising strategies in the development of antimicrobial hydrogels and the application of hydrogels in the treatment of microbial infections. The latest advances in the development of inherently and composite antimicrobial hydrogels will be discussed, as well as hydrogels as carriers of antimicrobials, with a focus on antibiotics, metal nanoparticles, antimicrobial peptides, and biological extracts. The emergence of CRISR-Cas9 technology for removing the antimicrobial resistance has led the necessity of new and performant carriers for delivery of the CRISPR-Cas9 system. Different delivery systems, such as composite hydrogels and many types of nanoparticles, attracted a great deal of attention and will be also discussed in this review.
Genome-Wide Association Study of Root System Architecture in Maize
Authors: Wu Bin , Ren Wei , Zhao Longfei , Li Qiang , Sun Jiazheng , Chen Fanjun , Pan Qingchun
Published: January 2022

Roots are important plant organs for the absorption of water and nutrients. To date, there have been few genome-wide association studies of maize root system architecture (RSA) in the field. The genetic basis of maize RSA is poorly understood, and the maize RSA-related genes that have been cloned are very limited. Here, 421 maize inbred lines of an association panel were planted to measure the root systems at the maturity stage, and a genome-wide association study was performed. There was a strong correlation among eight RSA traits, and the RSA traits were highly correlated with the aboveground plant architecture traits (e.g., plant height and ear leaf length, r = 0.13–0.25, p < 0.05). The RSA traits of the stiff stalk subgroup (SS) showed lower values than those of the non-stiff stalk subgroup (NSS) and tropical/subtropical subgroup (TST). Using the RSA traits, the genome-wide association study identified 63 SNPs and 189 candidate genes. Among them, nine candidate genes co-localized between RSA and aboveground architecture traits. A further co-expression analysis identified 88 candidate genes having high confidence levels. Furthermore, we identified four highly reliable RSA candidate genes, GRMZM2G099797, GRMZM2G354338, GRMZM2G085042, and GRMZM5G812926. This research provides theoretical support for the genetic improvement of maize root systems, and it identified candidate genes that may act as genetic resources for breeding.