bluuebunny/crossref_metadata_2025 huggingface dataset:
Anatomical Landmark Detection Using a Feature-Sharing Knowledge Distillation-Based Neural Network
Authors: Huang Di , Wang Yuzhao , Wang Yu , Gu Guishan , Bai Tian
Published: July 2022

Existing anatomical landmark detection methods consider the performance gains under heavyweight network architectures, which lead to models tending to have poor scalability and cost-effectiveness. To solve this problem, state-of-the-art knowledge distillation (KD) methods are proposed. However, they only require the teacher model to guide the output of the final layer of the student model. In this way, the semantic information learned by the student model is very limited. Different from previous works, we propose a novel KD-based model-training strategy, named feature-sharing fast landmark detection (FSF-LD), which focuses on intermediate features and effectively transfers richer spatial information from the teacher model to the student model. Moreover, to generate richer and more reliable knowledge, we propose a multi-task learning structure to pretrain the teacher model before FSF-LD. Finally, a tiny and effective anatomical landmark detection model is obtained. We evaluate our proposed FSF-LD on a public 2D hand radiograph dataset, a public 2D cephalometric radiograph dataset and a private 2D hip radiograph dataset. On the 2D hand dataset, our FSF-LD has 11.7%, 12.1%, 12.0,% and 11.4% improvement on SDR (r = 2 mm, r = 2.5 mm, r = 3 mm, r = 4 mm) compared with other KD methods. The results suggest the superiority of FSF-LD in terms of model performance and cost-effectiveness. However, it is a challenge to further improve the detection accuracy of anatomical landmarks and realize the clinical application of the research results, which is also our next plan.
Dubins Path-Oriented Rapidly Exploring Random Tree* for Three-Dimensional Path Planning of Unmanned Aerial Vehicles
Authors: Yang Youyoung , Leeghim Henzeh , Kim Donghoon
Published: July 2022

Unmanned aerial vehicles (UAVs) do not collide with obstacles, generate a path in real-time, and must fly to the target point. The sampling-based rapidly exploring random tree (RRT) algorithm has the advantages of fast computation and low computational complexity. It is suitable for real-time path generation, but the optimal path cannot be guaranteed. Further, the direction of the flight and the minimum radius of rotation have not been taken into account for the characteristics of the UAVs. This work proposes a Dubins path-oriented RRT* algorithm, which applies the Dubins path to the RRT algorithm to consider the direction of flight and the minimum radius of rotation and improves optimality and convergence. The proposed algorithm sets the sample node as the target point, orients toward the Dubins path, and then generates a tree. To verify the performance of the proposed algorithm, it is compared with existing RRT algorithms. As a result of performance analysis, the proposed algorithm improved the path length by 14.87% and the calculation time by 82.36%. Finally, the algorithm’s performance is verified by applying the proposed algorithm to a fixed-wing UAV and performing a numerical analysis of the generated path.
A Study on Particle Swarm Algorithm Based on Restart Strategy and Adaptive Dynamic Mechanism
Authors: Liu Lisang , Xu Hui , Wang Bin , Zhang Rongsheng , Chen Jionghui
Published: July 2022

Aiming at the problems of low path success rate, easy precocious maturity, and easily falling into local extremums in the complex environment of path planning of mobile robots, this paper proposes a new particle swarm algorithm (RDS-PSO) based on restart strategy and adaptive dynamic adjustment mechanism. When the population falls into local optimal or premature convergence, the restart strategy is activated to expand the search range by re-randomly initializing the group particles. An inverted S-type decreasing inertia weight and adaptive dynamic adjustment learning factor are proposed to balance the ability of local search and global search. Finally, the new RDS-PSO algorithm is combined with cubic spline interpolation to apply to the path planning and smoothing processing of mobile robots, and the coding mode based on the path node as a particle individual is constructed, and the penalty function is selected as the fitness function to solve the shortest collision-free path. The comparative results of simulation experiments show that the RDS-PSO algorithm proposed in this paper solves the problem of falling into local extremums and precocious puberty, significantly improves the optimization, speed, and effectiveness of the path, and the simulation experiments in different environments also show that the algorithm has good robustness and generalization.
Distribution Network Regionalized Fault Location Based on an Improved Manta Ray Foraging Optimization Algorithm
Authors: Zhang Rongsheng , Liu Lisang
Published: July 2022

To address the problem that the accuracy of traditional intelligent algorithms in distribution network fault location decreases with the expansion of distribution network scale, a regionalized fault location method for distribution networks containing distributed power sources based on the improved manta ray foraging optimization (IMRFO) algorithm is proposed. First, the global convergence property of the basic manta ray foraging optimization (MRFO) algorithm is improved by fusing the restart strategy and the opposition-based learning strategy. Then, based on the two-port equivalence principle, a topological model for regionalized fault hierarchical localization in distribution networks is constructed. Finally, the algorithm is improved by binary discretization using the Sigmoid function to output the fault vector and complete the fault location of the distribution network. Simulation experiments are conducted using MATLAB for IEEE-33 node distribution networks and the simulation results show that the IMRFO algorithm combined with the regionalization of complex distribution networks has a better effect of dimensionality reduction. Compared with the traditional distribution network simulation model, the fault location fault tolerance is greatly improved and its accuracy rate is increased by 1.8% and the location speed is improved by 15.537 ms.
Application of Improved YOLOv5 in Aerial Photographing Infrared Vehicle Detection
Authors: Fan Youchen , Qiu Qianlong , Hou Shunhu , Li Yuhai , Xie Jiaxuan , Qin Mingyu , Chu Feihuang
Published: July 2022

Aiming to solve the problems of false detection, missed detection, and insufficient detection ability of infrared vehicle images, an infrared vehicle target detection algorithm based on the improved YOLOv5 is proposed. The article analyzes the image characteristics of infrared vehicle detection, and then discusses the improved YOLOv5 algorithm in detail. The algorithm uses the DenseBlock module to increase the ability of shallow feature extraction. The Ghost convolution layer is used to replace the ordinary convolution layer, which increases the redundant feature graph based on linear calculation, improves the network feature extraction ability, and increases the amount of information from the original image. The detection accuracy of the whole network is enhanced by adding a channel attention mechanism and modifying loss function. Finally, the improved performance and comprehensive improved performance of each module are compared with common algorithms. Experimental results show that the detection accuracy of the DenseBlock and EIOU module added alone are improved by 2.5% and 3% compared with the original YOLOv5 algorithm, respectively, and the addition of the Ghost convolution module and SE module alone does not increase significantly. By using the EIOU module as the loss function, the three modules of DenseBlock, Ghost convolution and SE Layer are added to the YOLOv5 algorithm for comparative analysis, of which the combination of DenseBlock and Ghost convolution has the best effect. When adding three modules at the same time, the mAP fluctuation is smaller, which can reach 73.1%, which is 4.6% higher than the original YOLOv5 algorithm.
Online Trajectory Planning with Reinforcement Learning for Pedestrian Avoidance
Authors: Fehér Árpád , Aradi Szilárd , Bécsi Tamás
Published: July 2022

Planning the optimal trajectory of emergency avoidance maneuvers for highly automated vehicles is a complex task with many challenges. The algorithm needs to decrease accident risk by reducing the severity and keeping the car in a controllable state. Optimal trajectory generation considering all aspects of vehicle and environment dynamics is numerically complex, especially if the object to be avoided is moving. This paper presents a hierarchical method for the avoidance of moving objects in an autonomous vehicle, where a reinforcement learning agent is responsible for local planning, while longitudinal and lateral control is performed by the low-level model-predictive controller and Stanley controllers. In the developed architecture, the agent is responsible for the optimization. It is trained in various scenarios to provide the necessary parameters for a polynomial-based path and a velocity profile in a neural network output. The vehicle performs only the first step of the trajectory, which is redesigned repeatedly by the planner based on the new state. In the training phase, the vehicle executes the entire trajectory via low-level controllers to determine the reward value, which realizes a prediction for the future. The agent receives feedback and can further improve its performance. Finally, the proposed framework was tested in a simulation environment and was also compared to human drivers’ abilities.
Real-Time ISR-YOLOv4 Based Small Object Detection for Safe Shop Floor in Smart Factories
Authors: Ku Byungjin , Kim Kangsan , Jeong Jongpil
Published: July 2022

Wearing a hard hat can effectively improve the safety of workers on a construction site. However, workers often take off their helmets because they have a weak sense of safety and are uncomfortable, and this action poses a large danger. Workers not wearing hard hats are more likely to be injured in accidents such as human falls and vertical falls. Therefore, the detection of wearing a helmet is an important step in the safety management of a construction site, and it is urgent to detect helmets quickly and accurately. However, the existing manual monitor is labor intensive, and it is difficult to popularize the method of mounting the sensor on the helmet. Thus, in this paper, we propose an AI method to detect the wearing of a helmet with satisfactory accuracy with a high detection rate. Our method selects based on YOLOv4 and adds an image super resolution (ISR) module at the end of the input. Afterward, the image resolution is increased, and the noise in the image is removed. Then, dense blocks are used to replace residual blocks in the backbone network using the CSPDarknet53 framework to reduce unnecessary computation and reduce the number of network structure parameters. The neck then uses a combination of SPPnet and PANnet to take full advantage of the small target’s capabilities in the image. We add foreground and background balance loss functions to the YOLOv4 loss function part to solve the image background and foreground imbalance problem. Experiments performed using self-constructed datasets show that the proposed method has more efficacy than the currently available small target detection methods. Finally, our model achieves an average precision of 93.3%, a 7.8% increase over the original algorithm, and it takes only 3.0 ms to detect an image at 416 × 416.
Soiling Spectral and Module Temperature Effects: Comparisons of Competing Operating Parameters for Four Commercial PV Module Technologies
Authors: Diniz Antonia Sônia A. C. , Duarte Tulio P. , Costa Suellen A. C. , Braga Daniel Sena , Santana Vinicius Camatta , Kazmerski Lawrence L.
Published: July 2022

The choice of a particular PV technology for best performance is sometimes based upon a single factor or single operating condition. However, many parameters have functionalities that oppose each under actual operating conditions. In this paper, the comparisons of different PV module technologies under moderate environmental conditions (Tropical Climate Zone, Belo Horizonte, Brazil) are explored based upon the two competing parameters of soiling-layer spectral effects and panel operating temperature. Specifically, low-bandgap PV technologies (e.g., Si or Cu(In,Ga)(SSe)2) are reported to have performances less affected by the absorption of incoming sunlight than higher-bandgap absorbers (e.g., a-Si:H or CdTe). However, the opposite is true for operating temperatures, with higher bandgaps having advantages under higher-temperature operating conditions. We present a simple comparative soiling-temperature model with experimental collaborative data to address the following question: What is the controlling parameter of the combination of soiling spectral effects and temperature on lower- and higher-bandgap module technologies? Temperature coefficients are measured for groups of modules for the four technologies having bandgaps ranging from 1.1 to 1.7 eV. Additional optical absorption for the soiling layers in the range of 300 nm to ~600 nm is confirmed by transmission measurements. The data from our soiling monitoring stations indicate that these potential spectral effects are based on consistent differences in soiling ratios and soiling rates. Some differences between the model predications and experimental observations are discussed. This paper reports temperature and soiling regions of “best-of-class” performances for these four commercial PV technologies in this climate region based upon the two competing parameters.
Energy Diversification: A Friend or Foe to Economic Growth in Nordic Countries? A Novel Energy Diversification Approach
Authors: Ahmed Nihal , Sheikh Adnan Ahmed , Mahboob Farhan , Ali Muhammad Sibt e , Jasińska Elżbieta , Jasiński Michał , Leonowicz Zbigniew , Burgio Alessandro
Published: July 2022

Energy is essential to achieving economic growth, yet the production of energy results in the emission of carbon dioxide, the primary factor in the deterioration of the environment and the acceleration of climate change. In this sense, the diversity of energy sources can contribute to achieving both environmentally sustainable development. This study investigates the relationship between energy diversification and economic growth in Nordic nations by employing a unique measure of energy diversity. The Nonlinear Panel Autoregressive Distributed Lag (NPARDL) approach is utilized in the research, and it looks at data from 1998 through 2018. According to our results, these nations experience favorable economic growth when there is an increase in the long-term diversity of their energy sources. However, in the near term, they have seen negative economic development due to the diversification of their energy sources. According to these findings, energy diversification benefits Nordic economic growth; however, further research is required for developing economies. As a result, further preventative actions must be implemented while simultaneously diversifying energy sources.
Robust Exploration and Production Sharing Agreements Using the Taguchi Method
Authors: Balhasan Saad , Alnahhal Mohammed , Towler Brian , Salah Bashir , Ruzayqat Mohammed , Tabash Mosab I.
Published: July 2022

The short- and long-term volatility of oil and gas prices has a wide-ranging impact on both parties of petroleum contractual agreements, thus affecting the profitability of the project at any stage. Therefore, the government (first party) and the international oil company (second party) set the parameters of their contracts in a way that reduces the uncertainty. The effect of price fluctuations on economic indicators is investigated in this paper. The Taguchi method is used for the first time to find the best-agreement parameters, which are the “A” and “B” factors, in the standard Libyan agreement. There are four “A” components from “A1” to “A4”, and four “B” components from “B1” to “B4”. The purpose is to reduce the variability in the response variables, which are the company take (the percent of net cash flow for the international company) and average value of the second-party percent share of production (ASPS). The noise factors considered in this paper are oil, liquefied hydrocarbon byproduct (LHP), and gas prices. The method was applied to a case study of oil field development in Libya. The results showed that “A3” and “A4” were the most important control factors that affect the ASPS, while “B2” and “B3” are the most important factors affecting the company take. To obtain robust results, the most important factors to reduce variability were also determined. The effect of control parameters on the average NPV may be worth more than USD 22 MM in the 1-billion-barrel oilfield case study. The results showed that, for a given combination of “A” and “B” factors with a certain company take, the mean absolute deviation (MAD) of the NPV of the second party was reduced by 18% if the optimal combinations of the levels were used.
Numerical Investigation of Interaction Mechanism between Hydraulic Fracture and Natural Karst Cave Based on Seepage-Stress-Damage Coupled Model
Authors: Li Yue , Mou Jianye , Zhang Shicheng , Ma Xinfang , Xiao Cong , Fang Haoqing
Published: July 2022

Oil/gas is mainly distributed in caves for fractured-vuggy carbonate reservoirs, it is therefore of significance to effectively connect caves for successful carbonate reservoir development. However, the mechanism and controlling factors that influence the connection between fractures and caves still remain unknown. To investigate how hydraulic fracture interacts with natural karst cave, a coupled seepage-stress-damage model for a vuggy carbonate reservoir is established based on statistical damage mechanics theory and finite element method. The accuracy of the proposed model is validated in comparison with experimental results. Some influencing factors, including fluid pressure in the cave, formation parameters, and construction parameters, are fully taken into account. The study results show that, when the fracture deflection degree is small, a hydraulic fracture can indirectly connect with the cave through high permeable damage units. The matrix heterogeneity that influences hydraulic fracture morphology almost does not affect the interactions between fracture and cave. The higher permeability can lead to insufficient net pressure in the fracture, which is detrimental to the connection between fracture and cave. The ability of the cave to repel fracture is proportional to the in-situ stress magnitude. The higher in-situ stress difference can cause hydraulic fracture extends along with its original path, hindering hydraulic fracture deflection. The compressive stress concentration effect around the cave weakens as the fluid pressure in the cave rises, causing the cave wall to gradually transform from a compressed to a tensioned state. The hydraulic fracture can propagate along its initial trajectory because of the high injection rate’s ability to lessen the impact of the cave. These findings achieve deep insights into interaction patterns between fracture and cave, as well as provide useful guidance for hydraulic fracturing treatment design in fractured-vuggy carbonate reservoirs.
Modeling and Analysis of Load Growth Expected for Electric Vehicles in Pakistan (2021–2030)
Authors: Unar Naveed Ahmed , Mirjat Nayyar Hussain , Aslam Bilal , Qasmi Muneer Ahmed , Ansari Maha , Lohana Kush
Published: July 2022

The world is facing severe environmental challenges as it heavily relies on a USD 100 trillion fossil-fuel-based economy. Its transition from a fuel-intensive to a material-intensive economy is not well understood. The conventional energy resources are responsible for the excessive generation of Green House Gas (GHG) emissions resulting in increased environmental degradation owing to climate change. The human impact has been cited as highly indisputable in this respect. Pakistan is one of the most climate-vulnerable countries highly suffering from such increased impact of climate change and, thus, has been warned against the excessive use of conventional resources. As such, in the premises of Pakistan, conventional products are being excessively utilized in both power generation and transport sectors. Apart from the electrical power sector, the transport sector is also one of the main contributors to GHG emissions. In this context, the automobile industry has emerged as an environmentally friendly solution, which presents Electric Vehicles (EVs) as an efficient and feasible alternative to mitigate the GHG footprint. The transition from fossil-fuel-based vehicles (FFVs) to EVs is, therefore, considered as a potential way to decarbonize the transport sector, where the socio-economic conditions may be improved to a significant extent. A major prerequisite under planning and implementation in Pakistan is forecasting of load growth of EVs in Pakistan. Therefore, this paper proposes a load growth model (load forecast), used to forecast the load growth expected for electric vehicles in Pakistan from 2021 to 2030. This paper discusses in detail the original and revised models. According to the revised model, total EV energy demand stood at 24.61 GWh in 2020 and increased up to 2862.54 GWh in 2030.
Dynamic Characteristics and Successive Start-Up Control Strategy Optimization of Pumped Storage Units under Low-Head Extreme Conditions
Authors: Li Yonggang , Hou Jinjiao , Gu Juan , Li Chaoshun , Xu Yanhe
Published: July 2022

With inherent ‘S’ characteristics and the one-tunnel-with-two-units arrangement of the pump-turbine, hydraulic transient changes in the successive start-up process are complex, and the optimal control is difficult. This paper aims to study the dynamic characteristics and successive start-up control strategy optimization of two hydraulic couplings pumped storage units (PSUs) under low-head extreme conditions. Firstly, an accurate model of two hydraulic coupling PSUs’ successive start-up is established. Based on this model, the influence of the interval time of successive start-up on the dynamic characteristics of PSUs is carried out. It is shown that the change of the interval time of the successive start-up (ΔT) of the two PSUs has a significant impact on the dynamic response stability of the low-head start-up. If ΔT is more than 40 s, the hydraulic oscillation and speed fluctuation of the PSUs deteriorate. Secondly, with the different controller parameters for the two PSUs, a novel multi-objective optimization scheme with fractional order PID controller (FOPID) is proposed to figure out the best control scheme for the successive start-up. Furthermore, selecting the sum of the rise time (Tr) of the rotating speed of two PSUs and the sum of the integral time absolute error (ITAE) of two PSUs is the objective. Meanwhile, the optimization scheme of PID with different parameters (PIDDP) is used to compare and verify the optimization method proposed in this paper. The results for this extreme condition indicate that FOPID has more significant advantages in optimizing the instability of the successive start-up process, with the better Pareto front, and the optimized scheme has a more stable dynamic transition process of flow, water hammer pressure, and rotational speed.
Improved Control Strategy for Zero-Crossing Distortion Elimination in Totem-Pole PFC Converter with Coupled Inductor
Authors: Fu Han , Duan Shanxu , Li Yong , Li Qiqi
Published: July 2022

Coupled inductors can effectively optimize the THD, loss, current ripple, and power density of multiphase interleaved totem-pole PFC converters. However, a coupled inductor will also worsen the zero-crossing distortion process. This paper first introduces the working principle of the interleaved totem-pole PFC converter with a coupled inductor based on a detailed analysis of modes, and then analyzes the influence on the zero-crossing process caused by the coupled inductor. To eliminate the zero-crossing distortion caused by the coupled inductor, an improved control strategy and its digital realization method of the totem-pole PFC converter is presented through the system model. Finally, the validity and correctness of the proposed circuit and control are verified in the 7.7 kW interleaved totem-pole PFC converter.
A Perspective on Decarbonizing Mobility: An All-Electrification vs. an All-Hydrogenization Venue
Authors: Manakhov Anton , Orlov Maxim , Babiker Mustafa , Al-Qasim Abdulaziz S.
Published: July 2022

The growing demand for low-carbon fuel is predicted by ultimate goals to fit the carbon neutrality by 2050 in many countries and regions including the European Union. According to the International Energy Agency, the CO2 emissions related to transportation stand for around 30% of total annual emissions, and so, the decarbonization of the mobility sector has the highest priority. In this work, we attempt to evaluate the expected demand for low-carbon fuels, including blue and green hydrogen, and low-carbon electricity in order to compare the available and required capacities of low-carbon fuels and electricity. According to our calculations based on the figures from 2020, the transition toward H2 mobility would require an amount of hydrogen equal to 366 million tons/annum, and by 2035, this requirement will increase up to 422 million tons/annum, which is several times larger than the existing H2 production capacities. We have estimated the volume of the carbon capture and storage facilities required for full decarbonization of the mobility sector globally, and in the case of hydrogen mobility driven by blue hydrogen, it exceeds 4.0 billions tons of CO2 per annum, while the decarbonization of coal-fired plants will require more than 10.0 billions tons of CO2 per annum. In addition to the calculation of required resources, we have estimated the cost of the fuel and required capital investments and have compared different possible solutions from different points of view: economic viability, technical readiness, and social perception. Finally, it can be concluded that the decarbonization of the mobility sector would require a complex solution involving both low-carbon hydrogen and electrification, and the capacities of low-carbon fuel must be significantly increased in the following decade to fulfill the climate goals.
Financial Situation of Local Government Units as a Determinant of the Standards of Living for the Polish Population
Authors: Malinowski Mariusz
Published: July 2022

In this paper, the author intends to show the interaction between the living standards of the population and the financial situation of Polish local government units at the commune level. The first (theoretical) part of the paper provides a synthetic description of topics related to defining the economic terms and to the local government’s ability to impact the standards of living of the local population. In view of the multifaceted nature of terms covered by this analysis, the second part uses a canonical analysis (which means multiple linear regressions are generalized for two sets of variables) in order to identify the relationships between them. The analysis resulted in identifying a number of indicators, including canonical correlations, total redundancy and variances extracted, as well as six statistically significant canonical variates, which enabled the identification of multidimensional relationships between the categories considered. The greatest and the most statistically significant canonical correlation coefficient was over 0.93; for the last statistically significant canonical variate, it was over 0.57. The analysis provides grounds for concluding that when the values of variables representing the financial capacity of Polish rural communes are known, they can be used to explain over 32% of the variance in the set of variables relating to the population’s standards of living. The statistical data originated from the author’s own surveys carried out with presidents and vice-presidents of commune councils.
Accounting for Fixed Effects in Re-Fracturing Using Dynamic Multivariate Regression
Authors: Kroschel Josh , Rabiei Minou , Rasouli Vamegh
Published: July 2022

The oil and gas (O&G) industry is now as focused on minimizing costs and maximizing efficiency just as much as maximizing production. Operators are looking for new and cost-effective ways to add profitable assets to their portfolio. One such way is to re-fracture existing wells. There is evidence that these wells can be very productive in the Bakken. However, because of factors such as depletion and aging wellbore material, re-fracturing wells can be a difficult process to implement successfully and often have binding constraints on surface treating pressure (STP). This study attempts to quantify the effects that completion parameters have on re-fracturing treatment implementation by constructing dynamic fixed effects (FE) multivariate regression models. These models are not generally used in O&G and are more commonly used in economics and policy analysis. However, given that both economics and O&G deal with large amounts of uncertainty for each individual person and well, respectively, these models provide a much simpler approach to handle the uncertainty. These models also attempt to account for stress shadow effects from subsequent stages on treatment. The FE model has the advantage of treating a compilation of well treatment data as panel data and differencing out any unobservable fixed parameters. To the authors’ knowledge, this is the first study using dynamic FE models to estimate temporal stress shadow effects from one stage to the next. These models may then be thought of as estimating the boundary effects from stress shadows, which will affect treatment implementation. The novelty lies in estimating these effects, while accounting for fixed within-well variation, using simpler models than those usually found in industry. We stress that the simplicity of these models is a feature, not a bug. This study found that previous stage average STP, acid volume pumped, and perforation standoff were all statistically significant predictors of average STP with a strong temporal dependence of average STP on subsequent stages after accounting for fixed wellbore and geologic parameters. The models in this study also predict a positive marginal effect from acid volume average STP, which may seem counterintuitive, but is also backed by a previous study.
Energy Loss Reduction for Distribution Networks with Energy Storage Systems via Loss Sensitive Factor Method
Authors: Wu Xiangming , Yang Chenguang , Han Guang , Ye Zisong , Hu Yinlong
Published: July 2022

The loss of distribution networks caused by various electrical motors including transformers and generators can significantly affect the efficiency and economical operation of the power grid, especially for new power systems with high penetration of renewable energies. In this paper, the potential of using an energy storage system (ESS) for loss reduction is investigated, where a novel two-stage method for key-bus selection and ESS scheduling is proposed. At the first stage, the most sensitive key buses to the variation of load are selected by using the loss sensitive factors (LSF) method. At the second stage, ESS scheduling is conducted by solving an optimization problem with uncertainties caused by high penetration of renewable energies, where the uncertainties are characterized by confidence levels. The optimal scheduling of ESS including locations, capacities, and working modes are obtained at the second stage. The effectiveness of the proposed method is demonstrated via numerical simulations. The influences of capacities of ESS and confidence levels with respect to uncertainties are also analyzed. It is demonstrated that the loss-reduction performances can be improved if the ESSs are deployed on the buses selected by the LSF method and operated under the developed optimal scheduling method.
Experimental Determination, Modeling, and Simulation of Nonlinear Thermal Effects in Bipolar Transistors under Static Conditions: A Critical Review and Update
Authors: d’Alessandro Vincenzo , Catalano Antonio Pio , Scognamillo Ciro , Müller Markus , Schröter Michael , Zampardi Peter J. , Codecasa Lorenzo
Published: July 2022

This paper presents a comprehensive overview of nonlinear thermal effects in bipolar transistors under static conditions. The influence of these effects on the thermal resistance is theoretically explained and analytically modeled using the single-semiconductor assumption. A detailed review of experimental techniques to extract the thermal resistance as a function of backside temperature and/or dissipated power from DC measurements is provided; advantages, underlying approximations, and limitations of all methods are clarified, and guidelines for their correct application are given. Accurate FEM thermal simulations of an InGaP/GaAs and a Si/SiGe HBT are performed to verify the accuracy of the single-semiconductor theory. The thermal resistance formulations employed in the most popular compact bipolar transistor models for circuit simulators are investigated, and it is found that they do not properly describe nonlinear thermal effects. Alternative implementations of the more accurate single-semiconductor theory are then proposed for the future versions of the compact models.
Generalists and Specialists Determine the Trend and Rate of Soil Fungal Distance Decay of Similarity in a 20-ha Subtropical Forest
Authors: Chaithaisong Pachchara , Alcantara Mark Jun M. , Song Liang , Hu Yue-Hua
Published: July 2022

Fungi are an important component of microbial communities that serve a variety of important roles in nutrient cycling and are essential for plant nutrient uptake in forest soils. Distance decay of similarity (DDS) is one of the few ubiquitous phenomena in community ecology. However, the contribution of specialist and generalist fungal species in shaping DDS remains poorly investigated. Through removing operational taxonomic units (OTU) with low or high frequencies, we rigorously quantified the impact of specialists or generalists on the change in slope, initial similarity, and halving distance of DDS of undefined saprotroph, plant mutualist, and plant putative pathogen communities in a 20-ha subtropical evergreen forest plot in Yunnan Province, Southwest China. We hypothesized that (1) the soil fungal co-occurrence networks are different between the three fungal guilds; (2) specialists and generalists contribute to the spatial turnover and nestedness of beta diversity, respectively; and (3) the removal of specialists or generalists will have opposite effects on the change of slope, initial similarity, and halving distance of DDS. Co-occurrence network analysis showed that the undefined saprotroph network had a much more complicated structure than mutualist and pathogen networks. Ascomycota and Basidiomycota were the two most abundant phyla in soil fungal communities. We found that partly in line with our expectations, the change in initial similarity increased and decreased when removing specialists and generalists, respectively, but there was always one exception guild of out of the three communities for the change in slope and halving distance. We identified that such change was mainly due to the change in turnover and nestedness of beta diversity. Furthermore, the results show that species turnover rather than species nestedness drove fungal beta diversity across functional guilds for both specialists and generalists.
Do Emotional Perceptions of Visible Greeneries Rely on the Largeness of Green Space? A Verification in Nanchang, China
Authors: Huang Siying , Zhu Jinjin , Zhai Kunbei , Wang Yang , Wei Hongxu , Xu Zhihui , Gu Xinren
Published: July 2022

Experiencing nature can induce the perception of happiness because of mental stress alleviation and well-being restoration. The largeness of green space may not always mean the frequency of experiencing greenery. It is arguing about the probability of positive sentiments in response to an experience of interacting with green nature. In this study, 38 green spaces were investigated in Nanchang City, China, where the green space area was evaluated by the largeness of the landscape metrics of the Normalized Vegetation Index (NDVI), and Green View Index (GVI) data were further obtained using Open Street Maps (OSM). The semantic segmentation method was used by machine learning to analyze a total of 1549 panoramic photos taken in field surveys to assess the Panoramic Green View Index (PGVI) proportion. The photos of 2400 people’s facial expressions were obtained from social networks at their check-in visits in green spaces and rated for happy and sad scores using FireFACE software. Split-plot analysis of variance suggested that different categories of NDVI largeness had a significant positive effect on posted positive sentiments. Multivariate linear regression indicated that PGVI was estimated to have a significant contribution to facial expression. Increasing the amount of PGVI promoted happy and PRI scores, while at the same time, neutral sentiments decreased with increasing PGVI. Overall, increasing the PGVI in green spaces, especially in parks with smaller green spaces, can be effective in promoting positive emotions in the visitor experience.
Proteolytic Development and Volatile Compounds Profile of Domiati Cheese under Modified Atmosphere Packaging
Authors: Atallah Atallah A. , Ismail Elsayed A. , Yehia Hany M. , Elkhadragy Manal F. , Khater El-Sayed G.
Published: July 2022

This study explored the impacts of modified atmosphere packaging (MAP) treatment on the proteolytic development and volatile compounds of Domiati cheese during storage. Domiati cheese samples were kept for 75 days at refrigerator temperature, under aerobic packaging (C1) or vacuum (C2). In parallel, other Domiati cheese samples were kept under MAP, at different levels of CO2 and N2, as follows: 10% CO2/90% N2 (D1), 15% CO2/85% N2 (D2), 25% CO2/75% N2 (D3), 100% CO2 (D4), and 100% N2 (D5). The normal control (C1) treatment showed the highest reduction in pH from 6.64 at zero time to 6.23 and 6.01 after 40 and 75 days of storage, respectively. On the other hand, the under-vacuum samples (C2) showed the lowest reduction in pH, from 6.64 at zero time to 6.49 and 6.28 after 40 and 75 days of storage, respectively. Proteolysis during cheese storage was lower in MAP of cheeses than in the C1 treatment. Total free amino acids (FAAs) were higher in C1 treatment than other cheeses during the whole storage period. The lowest level of total FAA was detected in D4 treatment after 75 days of storage. Volatile acids, aldehydes, ketones, and esters compounds were detected in all treatments during storage, but particularly higher in aerobic packaging than the other treatments after 75 days. The level of each acid compound increased with storage period, and the increases were particularly clear in pentanoic acid, hexanoic acid, heptanoic acid, benzoic acid, and n-decanoic acid. The normal control (C1) showed high contents of the different volatile ketone compounds. However, the samples packaged under 100% N2 (D5) showed the significantly highest levels of all the volatile ketones after 75 days of storage, particularly 2-pentanone, acetoin, methyl isobutyl ketone, 2-heptanone, 2-nonanone, and 2-undecanone. Some important compounds contributing to the good flavor of the cheese are acetic acid, butanoic acid, pentanal, benzaldehyde, acetoin, and 2,3-butanedione. The CO2 and N2 treatments exerted significant changes in all groups during the storage of cheese. All cheese samples showed gradual increases in CO2 co-occurring with parallel decreases in N2 during refrigerated storage periods, except for D4 treatment (100% CO2), which showed a decrease. A significant decrease in O2 level occurred in C1 treatment during cold storage.
A Framework for Resource Allocation in Fire Departments: A Structured Literature Review
Authors: Eslamzadeh Milad K. , Grilo António , Espadinha-Cruz Pedro
Published: July 2022

A significant amount of research has been conducted on the resource allocation in fire departments (RAFD) and literature reviews about the fire protection service (FPS), but to the best of our knowledge, no literature reviews have been conducted about the RAFD. Therefore, the purpose of this research is to review literature about allocating resources to urban fire departments (FDs) to gain state-of-the-art knowledge of RAFD and identify the most frequent methodologies and measures in the studies. A five-stage structured literature review (SLR) is undertaken to analyze the RAFD-related studies; subsequently, statistical analysis is used to disclose additional information from the retrieved data and develop a general framework for RAFD. According to the structured literature review, which yielded 417 independent variables for RAFD, integer programming (IP) and data envelopment analysis (DEA) are the most common approaches for RAFD among the mathematical and statistical models in the evaluated articles. Based on the findings, a general conceptual framework for RAFD is suggested. The findings of this study can help public and private FDs and FPS managers, decision-makers, resource allocation (RA) researchers, and academicians gain state-of-the-art knowledge of RAFD. The proposed RAFD framework can provide the FPS decision-makers with the appropriate method and variables for allocating their limited resources in a more efficient way within their FDs.
Exogenous Melatonin Treatment Induces Disease Resistance against Botrytis cinerea on Post-Harvest Grapes by Activating Defence Responses
Authors: Li Zezhen , Zhang Shujuan , Xue Jianxin , Mu Bingyu , Song Hong , Liu Yanping
Published: July 2022

Botrytis cinerea seriously affects the value of post-harvest grapes. Melatonin can act as an exogenous regulator in the resistance of exogenous pathogens due to its antioxidant activity. An artificial inoculation trial was conducted to research the induced resistance mechanism of melatonin treatment using the table grape “Muscat Hamburg” (Vitis vinifera L. cv). Grapes were immersed with 0.02, 0.2, and 2 mmol/L melatonin, followed by B. cinerea suspension injections after 48 h. The results showed that the mycelial growth and spore germination of B. cinerea was not significantly inhibited by melatonin at different concentrations (0.02–2 mmol/L). However, post-harvest melatonin treatment inhibited the increase of disease incidence and severity of grey mould, induced the synthesis and accumulation of total phenols and flavonoids, reduced malondialdehyde generation, and inhibited an increase in cell membrane permeability. Meanwhile, defensive enzyme activities, including superoxide dismutase (SOD), peroxidize (POD), catalase (CAT), phenylalanine ammonia-lyase (PAL), polyphenol oxidase (PPO), chitinase (CHI), and β-1,3-glucanase, were significantly increased in fruits treated with exogenous melatonin. These results suggested that exogenous melatonin treatment could activate defence responses to combat the infection of B. cinerea in post-harvest grapes.
Effect of Refining Degree on the Quality Changes and Lipid Oxidation of Camellia (Camellia oleifera) Oil during Heating
Authors: Wang Mei , Wan Yin , Liu Ting , Zeng Xiuying , Liang Xinmei , Wu Xiaojiang , Fu Guiming
Published: July 2022

Refining degree has an important influence on the quality of camellia (Camellia oleifera) oil. The deterioration behaviors and lipid oxidation of three kinds of camellia oils, including camellia crude oil (CO), moderate refined oil (MRO), and refined oil (RO), during heating were investigated in this study. The results of deterioration behavior analysis showed that the oxidation degree was RO > CO > MRO. Tocopherol and polyphenolic substances in the oil might help delay oil oxidation. The lipid oxidation results indicated that the heating process had greater effects on CO and MRO than RO; it upregulated neutral lipid content and downregulated phospholipid content in terms of lipid changes and the multiplicity of differences. Glycerophospholipid metabolism was the most remarkable pathway and was important to study the heating process of refined oil. Moderate refining is good for retaining the beneficial lipids in camellia oil. The results of this study would provide a theoretical basis for camellia oil processing.
Effects of Cinnamon Essential Oil on Oxidative Damage and Outer Membrane Protein Genes of Salmonella enteritidis Cells
Authors: Zhang Zhen , Zhao Yuanyuan , Chen Xueqin , Li Wei , Li Wen , Du Jianming , Wang Li
Published: July 2022

Salmonella is an important pathogen causing food poisoning. Food safety and health are the themes of today′s society. As a class of food-borne pathogens, Salmonella enteritidis had become one of the common zoonotic pathogens. Cinnamon essential oil (CEO) had been reported as an antibacterial agent, but there are few studies on its antibacterial mechanism. This study investigated the effects of CEO on oxidative damage and outer membrane protein genes of Salmonella enteritidis cells. First, the reactive oxygen species content in bacteria treated with different concentrations of cinnamon essential oil was determined by fluorescence spectrophotometry, and the effects of superoxide dismutase (SOD), catalase (CAT) and superoxide dismutase (SOD), and catalase (CAT) and peroxidase (POD) were determined by the kit method. The activity of POD and the content of malondialdehyde (MDA) were investigated to investigate the oxidative damage of CEO to Salmonella enteritidis cells. By analyzing the effect of CEO on the Salmonella enteritidis cell membrane’s outer membrane protein gene expression, the mechanism of CEO′s action on the Salmonella enteritidis cell membrane was preliminarily discussed. The results showed that CEO treatment had an obvious oxidative damaging effect on Salmonella enteritidis. Compared with the control group, the increase in CEO concentration caused a significant increase in the bacteria ROS content. The observation technique experiment found that with the increase in CEO concentration, the number of stained cells increased, which indicated that CEO treatment would increase the ROS level in the cells, and it would also increase with the increase in CEO concentration, thus causing the oxidation of cells and damage. In addition, CEO treatment also caused the disruption of the balance of the cellular antioxidant enzymes (SOD, CAT, POD) system, resulting in an increase in the content of MDA, a membrane lipid metabolite, and increased protein carbonylation, which ultimately inhibited the growth of Salmonella enteritidis. The measurement results of cell membrane protein gene expression levels showed that the Omp genes to be detected in Salmonella enteritidis were all positive, which indicated that Salmonella enteritidis carried these four genes. Compared with the control group, the relative expressions of OmpF, OmpA and OmpX in the CEO treatment group were significantly increased (p < 0.05), which proved that the cell function was disturbed. Therefore, the toxicity of CEO to Salmonella enteritidis could be attributed to the damage of the cell membrane and the induction of oxidative stress at the same time. It was speculated that the antibacterial mechanism of CEO was the result of multiple effects. This work was expected to provide a theoretical basis for the development of new natural food preservatives and the prevention and control of Salmonella enteritidis.