bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Gate Driver for Suppressing Crosstalk of SiC MOSFET
Authors: Liang Mei , Chen Jiwen , Bai Jinchao , Jia Pengyu , Jiao Yuzhe
Published: October 2022

High switching-speed Silicon Carbide Metal-Oxide-Semiconductor Field-Effect Transistor (SiC MOSFET) has serious crosstalk issues. During the turn-ON transition and turn-OFF transition of the active switch in a phase-leg configuration, the voltage drops across the common-source inductor and the displacement current of the gate-drain capacitor of the OFF-state switch induce a spurious pulse on its gate-source voltage. This paper proposes a new gate driver using two Bipolar Junction Transistors (BJTs) and one diode to connect the gate terminal of SiC MOSFET and the negative driver voltage, which provides a low impedance path to bypass the displacement current of the gate-drain capacitor when crosstalk issues occur. The simulation results prove the proposed driver is valid on suppressing the crosstalk issue. The comparisons between the prior drivers and the proposed driver show the superiority of the proposed driver. Finally, the proposed gate driver is successfully implemented and experimentally verified on a 1.1 kW synchronous buck prototype.
Scalable Hardware Efficient Architecture for Parallel FIR Filters with Symmetric Coefficients
Authors: Ye Jinghao , Yanagisawa Masao , Shi Youhua
Published: October 2022

Symmetric convolutions can be utilized for potential hardware resource reduction. However, they have not been realized in state-of-the-art transposed block FIR designs. Therefore, we explore the feasibility of symmetric convolution in transposed parallel FIRs and propose a scalable hardware efficient parallel architecture. The proposed design inserts delay elements after multipliers for temporal reuse of intermediate tap products. By doing this, the number of required multipliers can be reduced by half. As a result, we can achieve up to 3.2× and 1.64× area efficiency improvements over the modern transposed block method on reconfigurable and fixed designs, respectively. These results confirm the effectiveness of the proposed STB-FIR architecture for hardware-efficient, high-speed signal processing.
Simulations of the Comparative Study of the Single-Phase Shift and the Dual-Phase Shift-Controlled Triple Active Bridge Converter
Authors: Koneh Norbert Njuanyi , Ko Jae-Sub , Kim Dae-Kyong
Published: October 2022

This paper presents a comparative study between the traditional phase shift (also referred to as the Single-Phase Shift (SPS)) and the Dual-Phase Shift (DPS) controlled Triple Active Bridge (TAB) converter. Being a multi-port DC-DC converter with flexible power flow control and characterized by high power density, the TAB converter is applicable in almost any situation where a DC-DC converter is needed. With the availability of multiple control schemes, this work highlights the advantages and disadvantages of the most employed control scheme used on the TAB converter, in comparison with the DPS control scheme that has so far been applied only on Dual-Active Bridge (DAB) converters. As an example, for a TAB converter with a 14 kW maximum power capacity, the work sees the comparison of the backflow power, the maximum possible current, the processed power at the different ports of the converter, the transformer voltage and current waveforms, and the Total Harmonic Distortion (THD). Based on the results obtained, we found that the DPS-controlled TAB converter was more efficient when applied to the TAB converter compared to the traditional phase shift control algorithm.
End-to-End Decoupled Training: A Robust Deep Learning Method for Long-Tailed Classification of Dermoscopic Images for Skin Lesion Classification
Authors: Foahom Gouabou Arthur Cartel , Iguernaissi Rabah , Damoiseaux Jean-Luc , Moudafi Abdellatif , Merad Djamal
Published: October 2022

Due to its increasing incidence, skin cancer, and especially melanoma, is considered a major public health issue. Manually detecting skin lesions (SL) from dermoscopy images is a difficult and time-consuming process. Thus, researchers designed computer-aided diagnosis (CAD) systems to assist dermatologists in the early detection of skin cancer. Moreover, SL detection naturally exhibits a long-tailed distribution due to the complex patient-level conditions and the existence of rare diseases. Very limited research for handling this issue exists on SL detection. In this paper, we propose an end-to-end decoupled training for the long-tailed skin lesion classification task. Specifically, we initialized the training of a network with a novel loss function Lf able to guide the model to a better representation of the features. Then, we fine-tuned the pretrained networks with a weighted variant of Lf helping to improve the robustness of the network to class imbalance. We evaluated our model on the ISIC 2018 public dataset against existing methods for handling class imbalance and existing approaches for SL detection. The results demonstrated the superiority of our framework, outperforming all compared methods by a minimum margin of 2% with a single model.
The Influence of a High-Voltage Discharge in a Helicoidal Twisted-Pair Structure on Enzyme Adsorption
Authors: Ivanov Yuri D. , Tatur Vadim Yu. , Shumov Ivan D. , Kozlov Andrey F. , Valueva Anastasia A. , Ivanova Irina A. , Ershova Maria O. , Ivanova Nina D. , Stepanov Igor N. , Lukyanitsa Andrei A. , Ziborov Vadim S.
Published: October 2022

The effect of a high-voltage discharge in a helicoidal structure on the adsorption properties of an enzyme on mica has been studied with the example of horseradish peroxidase (HRP). The discharge was generated at the expense of a sparkover in a 3 mm gap between two electrodes, to which a 10 kV, 50 Hz AC voltage was applied. The electrodes were connected to a twisted pair, which was wound onto a cone, forming the helicoidal structure. The incubation of the enzyme solution near the top of the helicoidal structure has been found to cause an increase in the degree of aggregation of HRP adsorbed on mica in comparison with the control HRP sample. The results obtained should be taken into account in studies of enzymes using biosensors with helicoidal structures as heating elements, as well as in refining models describing effects of low-frequency alternating current, flowing through helicoidal structures, on proteins and biological objects.
Adaptive Handover Decision Using Fuzzy Logic for 5G Ultra-Dense Networks
Authors: Hwang Wen-Shyang , Cheng Teng-Yu , Wu Yan-Jing , Cheng Ming-Hua
Published: October 2022

With the explosive increase in traffic volume in fifth-generation (5G) mobile wireless networks, an ultra-dense network (UDN) architecture, composed of highly concentrated millimeter-wave base stations within the fourth-generation (4G) system, has been developed. User equipment (UE) may encounter more frequent handover opportunities when moving in a UDN. Conventional handover schemes are too simple to adapt to the diverse handover scenarios encountered in 5G UDNs because they consider only UE signal strength. Unnecessary handovers aggravate the ping-pong effect and degrade the quality of service of cellular networks. Fuzzy logic (FL) is considered the best technique to unravel the handover problem in a high-density scenario of small cells for 4G/5G networks. In this paper, we propose an FL-based handover scheme to dynamically adjust the values of two handover parameters, namely handover margin (HOM) and time to trigger (TTT), with respect to each UE. The proposed scheme, abbreviated as FLDHDT, has dynamic adjustment of TTT in addition to HOM by using the signal to interference plus noise ratio and horizontal moving speed of the UE as inputs to the FL controller. To demonstrate the effectiveness and superiority of FLDHDT, we perform simulations using the well-known ns-3 simulator. The performance measures include the number of handovers, overall system throughput, and ping-pong ratio. The simulation results demonstrate that FLDHDT improves the handover performance of 5G UDNs in terms of the number of handovers, ping-pong ratio, and overall system throughput compared to a conventional handover scheme, namely Event A3, and an FL-based handover scheme with dynamic adjustment of only HOM.
Typhoon Tracks Prediction with ConvLSTM Fused Reanalysis Data
Authors: Lu Peng , Xu Mingyu , Sun Ao , Wang Zhenhua , Zheng Zongsheng
Published: October 2022

Typhoon occurrences pose a great threat to people’s lives and property; therefore, it is important to predict typhoon tracks accurately for disaster prevention and reduction. In recent years, research using traditional machine learning methods has struggled to include temporal and spatial features. Moreover, research that has been conducted using satellite images only does not consider the influence of physical factors on typhoon movement; therefore, this paper proposes to add a convolutional layer to the Convolutional LSTM (ConvLSTM) model to improve the ability of the model to extract images. The previous positions of the typhoon’s center are marked on subsequent reanalysis images. The subsequent coordinates of the typhoon’s center are found by fitting the predicted coordinates of each physical variable. The research method in this paper required selecting the physical variables group which was most correlated with the direction and distance of the typhoon movement from 11 physical variables; this was achieved using Canonical Correlation Analysis (CCA) and Grey Relation Analysis (GRA). Then, reanalysis data is transformed into images and a continuous series of reanalysis image sequences is inputted into the ConvLSTM model so that it can make predictions. The mean absolute error of distance used for the ERA5 dataset, using the method proposed, was 54.69 km; thus, the validity of the model was proven.
A Comprehensive Study on Air-Cathode Limitations and Its Mitigation Strategies in Microbial Desalination Cell—A Review
Authors: Juma Al Balushi Noor , Nayak Jagdeep Kumar , Rahman Sadik , Sana Ahmad , Al-Mamun Abdullah
Published: October 2022

Microbial desalination cells (MDCs) are promising bioelectrochemical systems for desalination using the bacteria-generated electricity from the biodegradation of organic wastes contained in the wastewater. Instead of being a sustainable and eco-friendly desalination technology, the large-scale application of MDC was limited due to the high installation cost of the metal-catalyst-coated cathode electrode and the poor performance of the cathode in long-term operation due to catalyst fouling. Such cathodic limitations have hindered its large-scale application. The cathodic limitation has arisen mainly because of three losses, such as (1) Ohmic loss, (2) mass transfer loss, and (3) activation loss. The catalyst-assisted cathodic reduction reaction is an electrochemical surface phenomenon; thereby, the cathode’s surface charge transfer and thermodynamic efficiency are crucial for reaction kinetics. This review article aims to provide an overview of the MDC process, performance indicators, and summarizes the limiting factors that could hinder the process performance. Then, the article represented a comprehensive summary of the air-cathodic limitations and the mechanisms applied to improve the air-cathodic limitations in MDC to enhance the cathodic reaction kinetics through cathode surface modification through catalysts. The study is significantly different from other review studies by the precise identification and illustration of the cathodic losses and their mitigation strategies through surface modification. The details about the role of photocatalysts in the minimization of the cathode losses and improvement of the performance of MDC were well presented.
Influence-Based Consequence Assessment of Subsea Pipeline Failure under Stochastic Degradation
Authors: Adumene Sidum , Islam Rabiul , Dick Ibitoru Festus , Zarei Esmaeil , Inegiyemiema Morrison , Yang Ming
Published: October 2022

The complexity of corrosion mechanisms in harsh offshore environments poses safety and integrity challenges to oil and gas operations. Exploring the unstable interactions and complex mechanisms required an advanced probabilistic model. The current study presents the development of a probabilistic approach for a consequence-based assessment of subsea pipelines exposed to complex corrosion mechanisms. The Bayesian Probabilistic Network (BPN) is applied to structurally learn the propagation and interactions among under-deposit corrosion and microbial corrosion for the failure state prediction of the asset. A two-step consequences analysis is inferred from the failure state to establish the failure impact on the environment, lives, and economic losses. The essence is to understand how the interactions between the under-deposit and microbial corrosion mechanisms’ nodes influence the likely number of spills on the environment. The associated cost of failure consequences is predicted using the expected utility decision theory. The proposed approach is tested on a corroding subsea pipeline (API X60) to predict the degree of impact of the failed state on the asset’s likely consequences. At the worst degradation state, the failure consequence expected utility gives 1.0822×108 USD. The influence-based model provides a prognostic tool for proactive integrity management planning for subsea systems exposed to stochastic degradation in harsh offshore environments.
Fractal Dimension of Digital 3D Rock Models with Different Pore Structures
Authors: Li Xiaobin , Wei Wei , Wang Lei , Cai Jianchao
Published: October 2022

The macroscopic physical properties of rocks are profoundly determined by their microstructure, and the research of accurately characterizing rock pore structure has been extensively carried out in the fields of petroleum engineering and geoscience. Fractal geometry is an effective means of quantitatively estimating the pore structure properties of porous media. In this study, the evolution law of the fractal dimension and the quantitative relationship between the fractal dimension and porosity were investigated based on the digital 3D rock models. First, three kinds of models with gradually changing pore structures, namely sedimentation, compaction, and cementation, were systematically reconstructed by the process-based approach. Then, the fractal dimensions of the skeleton, pore, and surface of the models were computed and analyzed. Finally, the relationships among the fractal dimension, porosity, and complexity were explored qualitatively. These works reveal the changing laws of three types of fractal dimensions for different pore structure models. The pore structure differences in sedimentation model can only be distinguished by the surface fractal dimension, while both pore and surface fractal dimensions are available parameters for characterizing different pore structures in compaction and cementation models. The quantitative relations between box-counting fractal dimension and porosity were established, which can be expressed by combining linear and logarithmic formulas. The comparison of fractal dimensions of compaction and cementation models proves that fractal dimensions can distinguish the subtle pore structure differences in digital 3D rock models. Understanding the evolution law between the fractal dimension and pore structure parameters provides more references for classifying and evaluating rock pore structure features using fractal dimensions.
Shape Optimization of Oscillating Buoy Wave Energy Converter Based on the Mean Annual Power Prediction Model
Authors: Liu Tiesheng , Liu Yanjun , Huang Shuting , Xue Gang
Published: October 2022

In order to improve the energy capture efficiency of an oscillating buoy wave energy converter (WEC), a buoy-shape optimization design method based on the mean annual power prediction model is proposed. According to the statistical data of long-term wave characteristics in the Chinese sea area, the optimal design space is determined. Sixty-three sample points were randomly selected in the optimized space. Based on simulation, the mean annual power corresponding to each sample point is calculated to quantitatively describe the energy capture ability. The response surface method (RSM), radial basis function neural network (RBFNN), and elliptical basis functions neural network (EBFNN) are used to establish the mean annual power prediction models, respectively. By combining the prediction model with the multi-island genetic algorithm (MIGA), the optimal solution in the design space is easily obtained. The reliability of the optimal solution is further proved by quantitative analysis about the influence of optimization parameters on the mean annual captured power. Compared with the common RSM and RBFNN methods, the prediction model established by the EBFNN method has a higher prediction accuracy. In the optimization process, the simulation calculation is replaced by a prediction model, which can effectively solve the problem of high simulation calculation cost.
Modeling of Direct-Drive Permanent Magnet Synchronous Wind Power Generation System Considering the Power System Analysis in Multi-Timescales
Authors: Ge Chenchen , Liu Muyang , Chen Junru
Published: October 2022

The dynamics of wind power generation cannot be neglected in the modern power system and could have a great impact on the system dynamics, even raising the risk of a blackout. Because of this, power system simulation has to include the model of wind power generation. However, due to the high order of the full model of the wind power generator, it is impossible to model them in detail in the use of the power system dynamic simulation considering the thousands of wind generators in the grid. In this context, a simplified model is normally used with the trade-off in lower accuracy. As a direct-drive permanent magnet synchronous wind power generation system (D-PMSG) would take up a certain occupation in the modern power system, a proper D-PMSG simplified model is needed in the power system simulation. For a different research purpose in a different timescale, a different complexity of the model can be used to maximize the accuracy, in the meantime speeding up the simulation. This paper proposes a set of simplified models of the direct-drive permanent magnet synchronous wind power generation system (D-PMSG) and classifies them according to the timescale of the dynamics and the use cases, i.e., faults (transient stability analysis), system contingencies (voltage and frequency stability analysis) and wind speed variations (energy transformation). The accuracy of the proposed simplified models is verified by comparing them with the detailed D-PMSG electromagnetic transient mode in Matlab/Simulink, and their use case of the power system simulation is validated based on the case study of the IEEE 39-bus system considering the above scenarios.
Vibration and Noise Optimization of Variable-Frequency-Driven SPMSM Used in Compressor Based on Electromagnetic Analysis and Modal Characteristics
Authors: Shou Jiabo , Ma Jien , Zhang Zhiping , Qiu Lin , Xu Bowen , Luo Chao , Li Binqi , Fang Youtong
Published: October 2022

The high-frequency electromagnetic noise caused by a frequency converter power supply has become the main composition of the vibration and noise of frequency-converter-driven PMSMs. Determining how to reduce this kind of noise is very important to improve motor performance. This paper analyzes the frequency characteristics of the high-frequency noise generated by an inverter, using the magnetic circuit analysis and Maxwell tensor methods. The switching frequency and the natural frequencies of the main modes are optimized according to the modal characteristics of the motor in order to reduce the vibration and noise of the motor. The results show that the high-frequency electromagnetic vibration and noise generated by the inverter is mainly caused by the high-frequency switching harmonic current. The frequencies of the vibration and noise are related to the switching frequency and the modulation wave frequency. At the same time, the simulation calculation of the natural frequencies of the main modes and the noise spectrum obtained from the experiment provide direction for the optimization of the vibration noise near the switching frequency. The switching frequency optimization and the natural frequency optimization based on the main modes of the motor can effectively reduce vibration and noise. This work has certain reference significance for the design of low-noise PMSMs.
A Study on the Effect of Hydrogen Gas Explosion in a Cylinder Cabinet for Semiconductors on the Protective Wall
Authors: Min Mimi , Lee Kwangho , Jung Seungho
Published: October 2022

In the semiconductor industry, hydrogen is used with many other hazardous and dangerous substances with flammable, toxic, and corrosive properties. In order to safely handle them, convenient-to-use gas cabinets are often required. As known well, hydrogen is highly flammable and explosive, and risk analysis needs to safely use the gas in the cabinets. In this study, overpressure and impact according to various gas cabinet conditions were measured when hydrogen leaks in the gas cabinet, and the effect of overpressure on the protective wall was simulated. For the research, a demonstration experiment was conducted by custom manufacturing a gas cylinder cabinet identical to the standard used in the field, and the protection performance analysis was performed by reverse-engineering it through 3D scanning. As a result of the demonstration experiment, the maximum pressure at the time of hydrogen gas explosion in the gas cylinder cabinet was measured at 0.3 bar. After calculating the detonation pressure propagation profile using the TNT equivalence method, the protective performance of the protective wall was confirmed using AUTODYN. The maximum stress of the concrete and the maximum stress of the reinforcing bar due to the explosion in the gas cylinder cabinet were calculated to be 30.211 MPa and 112.88 MPa, respectively, which do not exceed the tensile strength of concrete and the yield strength of the reinforcing bar. This result is expected to be of great help to the development of the semiconductor industry by suggesting the rationale for mitigating the firewall when changing the semiconductor layout.
Prediction of the Behavior of Sunflower Husk Ash after Its Processing by Various Torrefaction Methods
Authors: Isemin Rafail , Tabet Fouzi , Nebyvaev Artemy , Kokh-Tatarenko Vadim , Kuzmin Sergey , Milovanov Oleg , Klimov Dmitry , Mikhalev Alexander , Dobkin Semen , Zhulaev Yuri
Published: October 2022

Biomass can be considered an alternative to coal in the production of heat and electricity. Many types of biomass are waste from agriculture and the food industry. This waste is cheap, readily available, and replenished annually. However, most agricultural and food industry wastes (sugar cane pulp, olive and sunflower oil production wastes, straw, etc.) have ash with a low melting point. This leads to a rapid growth of ash deposits on the heating surfaces of boilers; as a result, the actual efficiency of boilers in which waste from agriculture and the food industry is burned is 45–50%. Known biomass pre-treatment technologies that allow for the fuel characteristics of biowaste. For example, leaching of biowaste in water at a temperature of 80–240 °C makes it possible to drastically reduce the content of alkali metal compounds in the ash, the presence of which reduces the melting point of the ash. However, this biomass pre-treatment technology is complex and requires additional costs for drying the treated biomass. We proposed to use torrefaction for pre-treatment of biomass, which makes it possible to increase the heat of combustion of biomass, increase the hydrophobicity of biomass, and reduce the cost of grinding it. However, we are not aware of studies that have studied the effect of torrefaction on the chemical composition of ash from the point of view of solving the problem of preventing the formation of agglomerates and reducing the growth rate of ash deposits on the convective heating surfaces of boilers. In this paper, the characteristics of sunflower husk subjected to torrefaction in an environment of superheated steam at a temperature of 300 °C and in an environment of gaseous products at a temperature of 250 °C are studied. All experiments were conducted using fluidized bed technology. The resulting biochar has a calorific value of 14.8–23% higher than the initial husk. To assess the behavior of sunflower husk ash, predictive coefficients were calculated. Torrefaction of sunflower husks does not exclude the possibility of slagging of the furnace but reduces the likelihood of slagging by 2.31–7.27 times. According to calculations, the torrefaction of sunflower husks reduces the likelihood of ash deposits on the convective heating surfaces of the boiler by 2.1–12.2 times. According to its fuel characteristics, the husk, after torrefaction in an environment of superheated steam, approaches wood waste, i.e., can be burned separately without additives or mixtures with other fuels with refractory ash.
Big Data Analysis for Optimising the Decision-Making Process in Sustainable Energy Action Plans: A Multi-Criteria Evaluation Approach Applied to Sicilian Regional Recovery and Resilience Plans
Authors: Di Matteo Umberto , Agostinelli Sofia
Published: October 2022

Keeping the global temperature rise below 2 degrees Celsius, as foreseen by the Paris Agreement, requires a new global roadmap for the energy transition. For this reason, the European Commission decided to directly involve local municipalities in reaching these objectives through multilevel, bottom-up actions for sustainable energy. The Covenant of Mayors is a very concrete demonstration of this trend of development and adoption of sustainable energy action plans (SEAP), rethinking the way cities operate and bringing them closer to energy self-sufficiency, with measures favouring local economic development and improving citizens’ quality of life. The numerous RES/RUE actions included in SEAPs at the regional level have led both to the request for huge funding and to increased complexity for regional managers to identify the best projects to be financed. To manage the multitude of data (emissions, energy consumption, cost, etc.) present in the SEAPs at a regional level, a web-based platform called Lex-energetica was developed. In this context, this paper aims to present a participatory supportive framework for the decision-making process involved in financing the SEAPs’ actions, considering the selection of sustainable Renewable Energy Sources (RES) and Rational Use of Energy (RUE) technologies. This study proposes a methodology based on two macro-phases: the first phase consists of a ranking evaluation of categories of areas of intervention based on the analytic hierarchy process, while the second identifies nine criteria, according to the domains corresponding to the three pillars of sustainability, to compare the most appropriate RES/RUE actions.
Selection of the Electric Drive for the Wood Waste Compacting Unit
Authors: Wilczyński Dominik , Talaśka Krzysztof , Wojtkowiak Dominik , Wałęsa Krzysztof , Wojciechowski Szymon
Published: October 2022

This work presents the study of the compaction and unloading process wood post-production waste, i.e., oak sawdust. The sawdust was compacted employing the forces F = 5000, 10,000, 20,000, 30,000, 40,000 and 50,000 N. Each compacted sample was compressed so as to determine the force value Fc required for the destruction of the sample. For each compaction force, the coefficient of the friction value µ1 was determined for the sawdust–steel material pair, which was used in the construction of the sleeve and stamp compacting system employed in the study. The determined parameters of the compressive force Fc and the coefficient of friction µ1 as a function of the compaction force F enabled to determine the optimal process parameters. A proposed construction of the compacting unit with an electrical drive is provided in the following part of the work comprising a motor, gear wheels, cam and a compacting piston. The selection of the parameters for the compaction process and the drive is of key importance from the standpoint of its energy consumption, influencing the energy balance, i.e., the ratio of input process energy and the energy obtained from the manufactured briquette. For the purpose of selecting the drive system, a mathematical model was developed utilizing earlier results of experimental studies. This model enabled to determine the maximum torque value Ms necessary to drive the proposed compacting unit. As a result of the carried-out work, it was determined that the maximum compaction force F is not ideal, considering other process parameters and their influence on its performance, allowing to lower the maximum torque and power of the proposed compacting unit.
Review on the Damage and Fault Diagnosis of Wind Turbine Blades in the Germination Stage
Authors: Song Xiaowen , Xing Zhitai , Jia Yan , Song Xiaojuan , Cai Chang , Zhang Yinan , Wang Zekun , Guo Jicai , Li Qingan
Published: October 2022

In recent years, wind turbines have shown a maximization trend. However, most of the wind turbine blades operate in areas with a relatively poor natural environment. The stability, safety, and reliability of blade operation are facing many challenges. Therefore, it is of great significance to monitor the structural health of wind turbine blades to avoid the failure of wind turbine outages and reduce maintenance costs. This paper reviews the commonly observed types of damage and damage detection methods of wind turbine blades. First of all, a comprehensive summary of the common embryonic damage, leading edge erosion, micro-cracking, fiber defects, and coating defects damage. Secondly, three fault diagnosis methods of wind turbine blades, including nondestructive testing (NDT), supervisory control and data acquisition (SCADA), and vibration signal-based fault diagnosis, are introduced. The working principles, advantages, disadvantages, and development status of nondestructive testing methods are analyzed and summarized. Finally, the future development trend of wind turbine blade detection and diagnosis technology is discussed. This paper can guide the use of technical means in the actual detection of wind turbine blades. In addition, the research prospect of fault diagnosis technology can be understood.
In Vitro Assessment of Probiotic and Technological Properties of Lactic Acid Bacteria Isolated from Indigenously Fermented Cereal-Based Food Products
Authors: Meena Kamalesh Kumar , Taneja Neetu Kumra , Jain Devendra , Ojha Ankur , Kumawat Dinesh , Mishra Vijendra
Published: October 2022

The present study concerns the isolation and characterization of potential probiotic bacteria isolated from indigenously fermented cereal-based products commonly produced by tribal people of the Aravali hills region of India and the documentation of their unexplored probiotic attributes. The isolated strains were evaluated for probiotic attributes, such as bile salt and acid tolerance, lysozyme and phenol tolerance, antagonistic and antifungal activity, cell autoaggregation, cell-surface hydrophobicity, simulated gastric and pancreatic digestion, antioxidative potential, bile salt hydrolase activity, and H2O2 production. The safety of isolates was assessed by antibiotic sensitivity, hemolytic activity, DNase activity, and biogenic amine production assays, while technological properties, such as fermenting ability, amylolytic activity, and EPS production, were also evaluated. A total of 70 LAB isolates were screened initially, and 6 strains showed good potential as probiotic candidates in in vitro assessments. The efficient strains were identified using phenotyping and biochemical characterization, which results were further confirmed and recognized at the strain level using phylogenetic analysis and 16S rDNA sequencing. The current study has shown that Lactiplantibacillus plantarum KMUDR7 isolated from “Makka ki Raab” has excellent probiotic attributes and could be a potential probiotic for product preparation. However, other strains, Lactobacillus delbrueckii subsp. bulgaricus KMUDR1 and Lacticaseibacillus rhamnosus KMUDR9, showed good properties, while KMUDR14, -17, and -20 also have comparable probiotic attributes.
Research on the Influence of Narrow and Long Obstacles with Regular Configuration on Crowd Evacuation Efficiency Based on Tri-14 Model with an Example of Supermarket
Authors: Lu Ligang , Ji Jingwei , Zhai Cheng , Wang Shengcheng , Zhang Zhen , Yang Tiantian
Published: October 2022

Regular shelves configuration forms unique characteristics of internal obstacles in a supermarket. It is crucial to study the crowd evacuation affected by obstacles during accidents or disasters in supermarkets as assembly occupancies. Based on the Tri-14 model, this paper studied the influence of safety exit designs and shelves’ configuration on the crowd evacuation efficiency with different densities in a supermarket through parameters and images. The results mainly indicate that: (1) The evacuation distance of farthest grid (Dfg) is the key factor to determine the total evacuation time of a low-density crowd. (2) For a high-density crowd, the closer the proportion ratio of the number of evacuees choosing each exit is to that of designed strand numbers of crowd flow at each exit, the higher the evacuation efficiency and average utilization efficiency of exits get; the scattered arrangement of exits will not necessarily lead to improving evacuation efficiency. Shelves’ configuration could lead to the extension of Dfg, but the change may reduce evacuation time instead, especially when forming effective advanced-gathering zones. (3) Under appropriate conditions, the impact of shelves’ configuration on evacuation efficiency can be negligible. This study has certain guiding significance for obstacle configuration and architectural design in large public gathering places.
Length–Weight Relationships, Growth Models of Two Croakers (Pennahia macrocephalus and Atrobucca nibe) off Taiwan and Growth Performance Indices of Related Species
Authors: Huang Shu-Chiang , Chang Shui-Kai , Lai Chi-Chang , Yuan Tzu-Lun , Weng Jinn-Shing , He Jia-Sin
Published: October 2022

Information on age and growth is essential to modern stock assessment and the development of management plans for fish resources. To provide quality otolith-based estimates of growth parameters, this study performed five types of analyses on the two important croakers that were under high fishing pressure in southwestern Taiwan: Pennahia macrocephalus (big-head pennah croaker) and Atrobucca nibe (blackmouth croaker): (1) Estimation of length–weight relationships (LWR) with discussion on the differences with previous studies; (2) validation of the periodicity of ring formation using edge analysis; (3) examination of three age determination methods (integral, quartile and back-calculation methods) and selection of the most appropriate one using a k-fold cross-validation simulation; (4) determination of the representative growth models from four candidate models using a multimodel inference approach; and, (5) compilation of growth parameters for all Pennahia and Atrobucca species published globally for reviewing the clusters of estimates using auximetric plots of logged growth parameters. The study observed that features of samples affected the LWR estimates. Edge analysis supported the growth rings were formed annually, and the cross-validation study supported the quartile method (age was determined as the number of opaque bands on otolith plus the quartile of the width of the marginal translucent band) provided more appropriate estimates of age. The multimodel inference approach suggested the von Bertalanffy growth model as the optimal model for P. macrocephalus and logistic growth model for A. nibe, with asymptotic lengths and relative growth rates of 18.0 cm TL and 0.789 year−1 and 55.21 cm, 0.374 year−1, respectively. Auximetric plots of global estimates showed a downward trend with clusters by species. Growth rates of the two species were higher than in previous studies using the same aging structure (otolith) and from similar locations conducted a decade ago, suggesting a possible effect of increased fishing pressure and the need to establish a management framework. This study adds updated information to the global literature and provides an overview of growth parameters for the two important croakers.
Winter Ice Dynamics in a Semi-Closed Ice-Covered Sea: Numerical Simulations and Satellite Data
Authors: Chernov Ilya , Tolstikov Alexey , Baklagin Vyacheslav , Iakovlev Nikolay
Published: October 2022

The White Sea is a small shallow sea covered by ice in winter. There are very few numerical models of this sea. For the ice-free sea, much data has been collected, but for winter only a small amount (satellite data only). We use our finite-element numerical model Jasmine and satellite data to trace the ice advection and exchange between parts of the White Sea. The aim of the investigation is to adjust the model to adequately reproduce the White Sea ice dynamics. By comparing satellite data on sea-ice concentration with the model prediction, we show that the model describes sea-ice dynamics well, and use it to estimate ice flow from bays to the middle part of the sea and ice exchange through the narrow strait. Ice exchange between neighbouring parts of the sea is shown to be intensive, with large dispersion compared to the time-mean, and bays are shown to be ice producers, while the Gorlo straight is shown to accept ice. We demonstrate that the model is a tool that can be used to better understand the winter regime of the sea.
Advancements and Opportunities in Characterizing Patient-Specific Wall Shear Stress Imposed by Coronary Artery Stenting
Authors: LaDisa John F. , Ghorbannia Arash , Marks David S. , Mason Peter , Otake Hiromasa
Published: October 2022

The success of drug-eluting stents (DES) is limited by restenosis and, to a lesser extent, late stent thrombosis. Mechanical stimuli have been implicated in these outcomes, with indices of wall shear stress (WSS) determined from computational simulations being reported most frequently. The current work summarizes state-of-the-art computational approaches applicable to patient-specific models aimed at further understanding changes in WSS indexes imposed by stent implantation. We begin with a review of best practices involved in the process and then summarize the literature related to stent-induced WSS alterations. Image-based reconstruction methods are also discussed, along with the latest generation boundary conditions that replicate cardiac physiology and downstream vasculature in the setting of coronary artery disease. The influence of existing material property data on WSS results obtained with geometries reconstructed from finite element modeling and fluid structure interaction (FSI) simulations is reviewed, along with the novel approaches being used to provide coronary artery plaque data that are currently missing from the literature. We also consider the use of machine learning tools that have the potential for impact when assessing the role of adverse stent-induced WSS in suboptimal clinical outcomes. We conclude by focusing on challenging cases that involve DES implantation, which may benefit from recent advancements in patient-specific computational modeling.
Comparative Transcriptomic and Metabolomic Analyses Reveal the Regulatory Effect and Mechanism of Tea Extracts on the Biosynthesis of Monascus Pigments
Authors: Li Wen-Long , Hong Jia-Li , Lu Jin-Qiang , Tong Shan-Gong , Ni Li , Liu Bin , Lv Xu-Cong
Published: October 2022

Monascus pigments (MPs) are natural edible pigments with high safety and strong function, which have been widely used in food and health products. In this study, different types of tea extracts (rich in polyphenols) were used to regulate the biosynthesis of MPs. The results showed that 15% ethanol extract of pu-erh tea (T11) could significantly increase MPs production in liquid fermentation of Monaco’s purpureus M3. Comparative transcriptomic and metabolomic analyses combined with reverse transcription-quantitative polymerase chain reaction (RT-qPCR) were used to further explore the regulatory mechanism of T11 on the biosynthesis of MPs. Comparative transcriptomic analysis showed that there were 1503 differentially expressed genes (DEGs) between the Con group and the T11 group, which were mainly distributed in carbohydrate metabolism, amino acid metabolism, energy metabolism, lipid metabolism, metabolism of terpenoids and polyketides, etc. A total of 115 differential metabolites (DMs) identified by metabolomics between the Con and T11 groups were mainly enriched in glutathione metabolism, starch and sucrose metabolism, alanine, aspartic acid and glutamate metabolism and glycine, serine and threonine metabolism, etc. The results of metabolomics were basically consistent with those of gene transcriptomics, indicating that the regulatory effect of T11 on the biosynthesis of MPs is mainly achieved through affecting the primary metabolic pathway, providing sufficient energy and more biosynthetic precursors for secondary metabolism. In this study, tea extracts with low economic value and easy access were used as promoters of MPs biosynthesis, which may be conducive to the application of MPs in large-scale industrial production. At the same time, a more systematic understanding of the molecular regulatory mechanism of Monascus metabolism was obtained through multi-omics analysis.
The Influence of Deep Eutectic Solvents Extract from Ginger on the Formation of Heterocyclic Amines and Advanced Glycation End Products in Roast Beef Patties
Authors: Xu Yang , Jiao Ye , Luo Jie , He Zhiyong , Zeng Maomao , Shen Qingwu , Chen Jie , Quan Wei
Published: October 2022

Heterocyclic amines (HAs) and advanced glycation end products (AGEs) are important harmful products formed simultaneously during the thermal processing of food. In order to develop a green, efficient method that can be used to control the production of two harmful products simultaneously in food processing. In the present study, deep eutectic solvents (DESs) were used to extract ginger, and this method produced significantly higher levels of total phenolic and flavonoid content as well as an antioxidant activity than ginger extracted using conventional solvents. Herein, we further investigated the inhibitory effects of DES extracts from ginger on the generation of HAs and AGEs in roast beef patties. All the nine DES extracts reduced the formation of HAs and AGEs, and the application of choline chloride–lactic-acid-based DES extract caused a signification reduction of 44.33%, 29.38%, 50.95%, 78.61%, 21.94%, and 17.52% of the PhIP, MeIQx, MeIQ, 4,8-DiMeIQx, Harmane, and Norhamane content, and those for Nε-(carboxymethyl)lysine (CML) and Nε-(carboxyethyl)lysine (CEL) were 49.08% and 58.50%, respectively. Furthermore, the proximate and texture profile changes of beef patties as well as the precursors (creatine, creatinine, and glucose) of HAs and AGEs were evaluated to determine the mechanism of ginger DES extracts on the formation of HAs and AGEs and the physical/chemical changes of ginger DES extracts on beef patties. This study develops a new method for reducing the amount of HAs and AGEs in meat, which will help food manufacturers produce healthier meat products.
The “Crosstalk” between Microbiota and Metabolomic Profile of Kefalograviera Cheese after the Innovative Feeding Strategy of Dairy Sheep by Omega-3 Fatty Acids
Authors: Tzora Athina , Nelli Aikaterini , Kritikou Anastasia S. , Katsarou Danai , Giannenas Ilias , Lagkouvardos Ilias , Thomaidis Nikolaos S. , Skoufos Ioannis
Published: October 2022

The purpose of this study was to examine the effects of two different feeding systems, a control or a flaxseed and lupin diet (experimental), for a sheep flock, on the microbiota and metabolome of Kefalograviera cheese samples produced by their milk. In particular, the microbiota present in Kefalograviera cheese samples was analyzed using 16S rRNA gene sequencing, while ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) was applied to investigate the chemical profile of the cheeses, considering the different feeding systems applied. The metagenomic profile was found to be altered by the experimental feeding system and significantly correlated to specific cheese metabolites, with Streptococcaceae and Lactobacillaceae establishing positive and negative correlations with the discriminant metabolites. Overall, more than 120 features were annotated and identified with high confidence level across the samples while most of them belonged to specific chemical classes. Characteristic analytes detected in different concentrations in the experimental cheese samples including arabinose, dulcitol, hypoxanthine, itaconic acid, L-arginine, L-glutamine and succinic acid. Therefore, taken together, our results provide an extensive foodomics approach for Kefalograviera cheese samples from different feeding regimes, investigating the metabolomic and metagenomic biomarkers that could be used to foresee, improve, and control cheese ripening outcomes, demonstrating the quality of the experimental Kefalograviera cheese.
Impact of Different Storage Temperature on the Enzymatic Activity of Apis mellifera Royal Jelly
Authors: Sagona Simona , Coppola Francesca , Giannaccini Gino , Betti Laura , Palego Lionella , Tafi Elena , Casini Lucia , Piana Lucia , Dall’Olio Raffaele , Felicioli Antonio
Published: October 2022

Royal Jelly is a nutrient secretion of nurse bees and a high interest functional food in human nutrition. Very little information is available on its chemical composition integrity and enzymatic activity during shelf life and assessment of new freshness markers are desirable for its conservation. In this study, the activity of glucose oxidase, five proteases and two antioxidant enzymes in refrigerated and frozen Royal Jelly for different storage times was preliminary investigated. Refrigeration determined a significantly reduction in glucose oxidase and carboxypeptidase A-like activity in Royal Jelly after one year of storage while no differences were recorded in the activity of these enzymes in frozen samples. After one year of storage glucose oxidase and carboxypeptidase A-like activity resulted higher in frozen samples frozen than in refrigerate ones. Results obtained suggest that the activities of these enzymes may be good markers of Royal Jelly freshness within 1 year at refrigeration condition. Freezing could be a valid alternative storage method to ensure a higher preservation of glucose oxidase and carboxypeptidase A-like activities for at least 1 year. Further investigation to determine the timing of glucose oxidase inactivation/degradation under refrigerated conditions and the enzymatic activity trend under prolonged frozen conditions are desirable.