bluuebunny/crossref_metadata_2025 huggingface dataset:
Antiamoebic Activity of Imidazothiazole Derivatives against Opportunistic Pathogen Acanthamoeba castellanii
Authors: Akbar Noor , El-Gamal Mohammed I. , Saeed Balsam Qubais , Oh Chang-Hyun , Abdel-Maksoud Mohammed S. , Khan Naveed Ahmed , Alharbi Ahmad M. , Alfahemi Hasan , Siddiqui Ruqaiyyah
Published: September 2022

We examined the antiamoebic effect of several imidazothiazole derivatives on Acanthamoeba castellanii of the T4 genotype. Trypan blue exclusion assays and haemocytometer counting were used to determine the reduction in A. castellanii trophozoite proliferation, in response to treatment with these compounds. To determine the effects of these compounds on host cells, lactate dehydrogenase assay was performed using HeLa cell lines. Amoebicidal assays revealed that the tested compounds at concentrations of 50 µM significantly inhibited amoebae trophozoites compared to controls. Compounds 1m and 1zb showed the highest amoebicidal effects eradicating 70% and 67% of A. castellanii, respectively. The compounds blocked both the encystation and excystation process in A. castellanii. Compounds 1m and 1zb blocked 61% and 55%, respectively, of amoeba binding to human cells. Moreover, the compounds showed minimal cytotoxic effects against host cells and considerably reduced amoeba-mediated host cell death. Overall, our study revealed that compounds 1m and 1zb have excellent antiamoebic potential, and should be considered in the development of curative antiamoebic medications in future studies. Further work is critical to determine the translational value of these findings.
Intelligent Deep-Q-Network-Based Energy Management for an Isolated Microgrid
Authors: Phan Bao Chau , Lee Meng-Tse , Lai Ying-Chih
Published: September 2022

The development of hybrid renewable energy systems (HRESs) can be the most feasible solution for a stable, environment-friendly, and cost-effective power generation, especially in rural and island territories. In this studied HRES, solar and wind energy are used as the major resources. Moreover, the electrolyzed hydrogen is utilized to store energy for the operation of a fuel cell. In case of insufficiency, battery and fuel cell are storage systems that supply energy, while a diesel generator adds a backup system to meet the load demand under bad weather conditions. An isolated HRES energy management system (EMS) based on a Deep Q Network (DQN) is introduced to ensure the reliable and efficient operation of the system. A DQN can deal with the problem of continuous state spaces and manage the dynamic behavior of hybrid systems without exact mathematical models. Following the power consumption data from Basco island of the Philippines, HOMER software is used to calculate the capacity of each component in the proposed power plant. In MATLAB/Simulink, the plant and its DQN-based EMS are simulated. Under different load profile scenarios, the proposed method is compared to the convectional dispatch (CD) control for a validation. Based on the outstanding performances with fewer fuel consumption, DQN is a very powerful and potential method for energy management.
Investigation of Behavior of Masonry Walls Constructed with Autoclaved Aerated Concrete Blocks under Blast Loading
Authors: Mollaei Somayeh , Babaei Ghazijahani Reza , Noroozinejad Farsangi Ehsan , Jahani Davoud
Published: September 2022

Autoclaved aerated concrete (AAC) blocks have widespread popularity in the construction industry. In addition to lightness, these materials have other advantages, including fire resistance, low acoustic and thermal conductivity, ease of cutting and grooving, and simple transportation. Since the behavior of AAC under severe dynamic loading conditions such as blast loads has not been adequately studied in the literature, in the current paper, the behavior of masonry walls constructed with AAC blocks was evaluated under blast loading. In this study, after performing experimental testing on materials and obtaining their compressive, tensile, and shear strength values, the finite element (FE) models of AAC-based masonry walls were created in the ABAQUS/Explicit nonlinear platform. Three different wall thicknesses of 15, 20, and 25 cm were simulated, and the models were analyzed under a lateral explosion caused by 5 and 7 kg of TNT at the stand-off distances of 2, 5, and 10 m from the wall face. The stress distributions, displacement responses, adsorbed energy, and crack propagation pattern were investigated in each case. The results showed the inappropriate behavior of these materials against explosion loads, especially at shorter distances and on walls with less thickness. The outcome gives valuable information to prioritize these walls for possible blast strengthening.
Probiotics and Microbiota-Derived Molecules for Inflammation, Neuroinflammation and Mood Disorders
Authors: Traina Giovanna
Published: September 2022

The gut microbiota plays an important role in inflammation, neuroinflammation and the function of neuronal cells [...]
Artificial Intelligence-Based Technological-Oriented Knowledge Management, Innovation, and E-Service Delivery in Smart Cities: Moderating Role of E-Governance
Authors: Bokhari Syed Asad Abbas , Myeong Seunghwan
Published: September 2022

The fundamental goal of this research is to investigate the quantitative relationship between technology-oriented knowledge management, innovation, e-governance, and smart city performance using knowledge management-based service science theory and diffusion of innovation theory. Previous research has found a connection between knowledge management, innovation, e-governance, and e-service delivery. We believe these are not only direct connections but also contextual and interactive relationships, so we explored the significance of innovation as a mediator between knowledge management and e-service delivery. Furthermore, we investigated the moderating impact of e-governance on the relationship between innovation and e-service delivery. A survey questionnaire was administered to the population of public officers, entrepreneurs, and citizens, from metropolitan cities for data sampling, and SPSS was applied to analyze data of 569 participants collected from South Korea, Pakistan, Japan, and Bangladesh. We discovered from the analysis that the direct relationships are contextual because innovation mediates the relationship between knowledge management and e-service delivery, and e-governance plays a moderating role in the relationship between innovation and e-service delivery. Based on the outcomes from quantitative analysis, all our proposed hypotheses in this study were supported significantly.
MAToC: A Novel Match-Action Table Architecture on Corundum for 8 × 25G Networking
Authors: Lin Jiawei , Guo Zhichuan , Chen Xiao
Published: September 2022

Packet processing offloads are increasingly needed by high-speed networks. This paper proposes a high throughput, low latency, scalable and reconfigurable Match-Action Table (MAT) architecture based on the open source FPGA-based NIC Corundum. The flexibility and capability of this scheme is demonstrated by an example implementation of IP layer forwarding offload. It makes the NIC work as a router that can forward packets for different subnet and virtual local area networks (VLAN). Experiments are performed on a Zynq MPSoC device with two QSFPs and the results show that it can work at line rate of 8 × 25 Gbps (200 Gbps), within a maximum latency of 76 nanoseconds. In addition, a high-performance MAT pipeline with full-featured, resource-efficient TCAM and a compact frame merging deparser are presented.
Skeletal Muscle Symptoms in Students of Health Majors with Dependence on Mobile Devices: An Observational Descriptive Study
Authors: Giraldo-Jiménez Claudia F. , Jembuel-Giraldo Ana M. , Galeano-Zapata Juan C. , Quintana-Caro Arleidis M. , Botero-Carvajal Alejandro , Valderrama-Aguirre Augusto , Millán-Estupiñan Juan C.
Published: September 2022

In the world, there are more mobile phone lines than people. These numbers have been increasing, especially in university students, due to the academic and social demands of a globalized and interconnected world in social networks, raising concerns about the health effects of mobile device overuse. The goal of this study was to establish the relationship between musculoskeletal symptoms in students at the health department of an institution of higher education and their dependence on mobile devices. An observational, descriptive study in which 334 interviews were presented, of which 244 were selected, corresponding to students with dependence on mobile devices. We find most symptoms in the neck (56.3%), followed by the dorsal region with (49.4%), wrist (42.6%), shoulder (33.9%), and elbow (9.6%). Study correlations were low for the back (Rho: 0.274) and wrist (Rho: 0.200) and very low for the neck (Rho: 0.171) and shoulder (Rho: 0.142). The presence of musculoskeletal symptoms, mainly in the neck, back, and wrist in university students with dependence on mobile devices belonging to the health department associated with academic programs in phonoaudiology, physiotherapy, and medicine, is common; however, the correlation was found to be low between dependency level and pain in the back and wrist and very low between dependency level and pain in the neck. Our results suggest that university wellness programs should focus on the neck, dorsal region of the back, wrist, and shoulder and that contrary to what was previously thought, there is a low correlation between dependence on cell phone use and musculoskeletal symptoms.
Special Issue on New Challenges in the Civil Structures for Fire Responses
Authors: Laím Luís , Santiago Aldina , Tondini Nicola
Published: September 2022

Civil structures may be subjected to serious hazards during their lifespans, including natural hazards (i [...]
Experimental Study on Small-Strain Shear Modulus of Unsaturated Silty-Fine Sand
Authors: Yan Kai , Wang Yong , Yang Zhiyong , Lai Xianghua , Chen Cheng
Published: September 2022

The small-strain stiffness of soil is significant in the accurate prediction of the deformation caused by interactions between foundation soil and structures. Considering the whole range of small strain (10−6~10−3), a bending element-resonant column (BE-RC) combined test system was developed to conduct continuous tests on the shear modulus of unsaturated soil. Under the dehydration path, it was used to investigate the small-strain shear modulus of unsaturated silty-fine sand in Hangzhou Bay, China. The results show that the shear modulus under different net stresses and matrix suctions appeared to non-linearly decay with the increase in strain until stable values were reached at a large strain. At the beginning from the saturated state, the Gmax value increased slowly with decreasing saturation and reached its maximum value at the optimum saturation (Sr)opt; then, it rapidly decayed to the level in the saturated, once the saturation degree decreased to a level lower than (Sr)opt. Additionally, an improved prediction model was proposed for the Gmax of unsaturated sand, considering different saturations. Based on the mesoscopic evolution of internal pore water morphology and the variation in intergranular stress caused by capillary action, the variation in the Gmax could be divided into three segments of saturation: the boundary effect stage, the transition stage and the unsaturated residual stage.
Stochastic Modeling of the Al Hoceima (Morocco) Aftershock Sequences of 1994, 2004 and 2016
Authors: Hamdache Mohamed , Peláez José A. , Gospodinov Dragomir , Henares Jesús , Galindo-Zaldívar Jesús , Sanz de Galdeano Carlos , Ranguelov Boyko
Published: September 2022

The three aftershock sequences that occurred in Al Hoceima, Morocco, in May 1994 (Mw 6.0), February 2004 (Mw 6.4) and January 2016 (Mw 6.3) were stochastically modeled to investigate their temporal and energetic behavior. A form of the restricted trigger model known as the restricted epidemic type aftershock sequence (RETAS) was used for the temporal analysis of the selected series. The best-determined fit models for each sequence differ based on the Akaike information criteria. The revealed discrepancies suggest that, although the activated fault systems are close (within 10 to 20 km), their stress regimes change and shift across each series. In addition, a stochastic model was presented to study the strain release following a specific strong earthquake. This model was constructed using a compound Poisson process and depicted the progression of the strain release during the aftershock sequence. The proposed model was then applied to the data. After the RETAS model was used to evaluate the behavior of the aftershock decay rate, the best-fit model was obtained and integrated into the strain-release stochastic analysis. By detecting the potential disparities between the observed data and model, the applied stochastic model of strain release allows for a more comprehensive examination. Furthermore, comparing the observed and expected cumulative energy release numbers revealed some variations at the start of all three sequences. This demonstrates that significant aftershock clusters occur more frequently shortly after the mainshock at the start of the sequence rather than if they are assumed to occur randomly.
Special Issue on Enhancement of Titanium Dental Implant/Abutment Surfaces
Authors: Pesce Paolo , Pera Francesco , Menini Maria
Published: September 2022

In the last decades, there has been an increasing effort in enhancing the surface of dental implants and abutments, as a challenge to improve the osseointegration process and implant rehabilitation success [...]
Four-Qubit Cluster States Generation through Multi-Coin Quantum Walk
Authors: Wang Tianyi , Chen Xiaoguang , Liang Jianxiong
Published: September 2022

Quantum computing requires large numbers of resources of entangled qubits, which cannot be satisfied using traditional methods of entanglement generation, such as optical systems. Therefore, we need more efficient ways of entanglement generation. It has been proved that multi-coin quantum walks can be used to replace direct Bell state measurements during the process of entanglement generation in order to avoid the difficulty of Bell state measurement. In this paper, we take one step further and generate 4-qubit cluster states using multi-coin quantum walks, which simplifies the generation of 4-qubit cluster states by using only Bell states and local measurements. We also propose a method for preparing 4-qubit cluster states with quantum circuits to facilitate their use in quantum computing.
Towards the Feasibility of Long Range Wireless Power Transfer over an Ocean Surface
Authors: Liu Louis W. Y. , Thành Sơn Nguyễn
Published: September 2022

In this work, we have realized Zenneck’s style of wireless power transfer over a seawater surface. Method: The problem can be thought of as a surface electromagnetic wave propagating along an interface between a low-loss non-polar medium and seawater. A 10 m long water-filled plastic duct was connected to two separated water tanks, with one tank identified as the transmitting end and the other the receiving end. At the transmitting end, the water tank was excited with a 100 kV plasma from a spark gap transmitter at 44 MHz. At the receiving end, surface power was harvested in an open-circuit manner with the help of a suspended monopole antenna. Results: Without any antenna, no power was received at the receiving end. However, when two monopole antennas were individually connected to the transmitter and the receiver, a power was noticeably detected and successfully delivered to multiple loads even if the water’s conductivity was low. As the salinity level increased from 0 to 5 g/L, the transmission efficiency was increased from 10% to 99%. Consistent with Marconi’s law of transmission, the transmission distance leading to the first maximum efficiency was found to be approximately proportional to square of the antenna heights. Conclusion: A vertically mounted monopole antenna enables power to be wirelessly transmitted along the interface between a low-loss dielectric medium and seawater.
The Holistic Perspective of the INCISIVE Project—Artificial Intelligence in Screening Mammography
Authors: Lazic Ivan , Agullo Ferran , Ausso Susanna , Alves Bruno , Barelle Caroline , Berral Josep Ll. , Bizopoulos Paschalis , Bunduc Oana , Chouvarda Ioanna , Dominguez Didier , Filos Dimitrios , Gutierrez-Torre Alberto , Hesso Iman , Jakovljević Nikša , Kayyali Reem , Kogut-Czarkowska Magdalena , Kosvyra Alexandra , Lalas Antonios , Lavdaniti Maria , Loncar-Turukalo Tatjana , Martinez-Alabart Sara , Michas Nassos , Nabhani-Gebara Shereen , Raptopoulos Andreas , Roussakis Yiannis , Stalika Evangelia , Symvoulidis Chrysostomos , Tsave Olga , Votis Konstantinos , Charalambous Andreas
Published: September 2022

Finding new ways to cost-effectively facilitate population screening and improve cancer diagnoses at an early stage supported by data-driven AI models provides unprecedented opportunities to reduce cancer related mortality. This work presents the INCISIVE project initiative towards enhancing AI solutions for health imaging by unifying, harmonizing, and securely sharing scattered cancer-related data to ensure large datasets which are critically needed to develop and evaluate trustworthy AI models. The adopted solutions of the INCISIVE project have been outlined in terms of data collection, harmonization, data sharing, and federated data storage in compliance with legal, ethical, and FAIR principles. Experiences and examples feature breast cancer data integration and mammography collection, indicating the current progress, challenges, and future directions.
Robust Optimization of Natural Laminar Flow Airfoil Based on Random Surface Contamination
Authors: Wang Shunshun , Guo Zheng
Published: September 2022

Natural laminar-flow (NLF) airfoils are one of the most promising technologies for extending the range and endurance of aircrafts. However, there is a lack of methods for the optimization of airfoils based on the surface contamination that destroys the laminar flow. In order to solve this problem, a robust optimization process is proposed using the Non-dominated Sorting genetic algorithm- II (NSGA-II) evolutionary algorithm, and Monte Carlo simulation combined with an aerodynamic calculation software Xfoil. Firstly, the airfoil is optimized normally and the aerodynamic performance of optimized airfoil under surface contamination is analyzed. Then, the original airfoil is robustly optimized under random surface contamination based on the assumption that its locations follow triangular and uniform probability distributions. Finally, all the optimized results and original airfoil are compared. It is found that robust optimization reduces the sensitivity of the airfoil to random surface contamination, hence, improving the robustness of the airfoil. The proposed methods make it possible to improve the aerodynamic performance of NLF airfoils considering surface contamination.
A Forwarding Latency Optimization Method for Software Data Plane Based on Spin-Polling
Authors: Tang Xinxin , Zeng Xuewen , Song Lei
Published: September 2022

Modern software data planes use spin-polling and batch processing mechanisms to significantly improve maximum throughput and forwarding latency. The user-level IO queue-based spin polling mechanism has a higher response speed than the traditional interrupt mechanism. The batch mechanism enables the software data plane to achieve higher throughput by amortizing the IO overhead over multiple packets. However, the software data plane under the spin-polling mechanism keeps running at full speed regardless of the input traffic rate, resulting in significant performance waste. At the same time, we find that the batch processing mechanism does not cope well with different input traffic, mainly reflected in the forwarding latency. The purpose of this paper is to optimize the forwarding latency by leveraging the wasted performance. We propose a forwarding latency optimization scheme for the software data plane based on the spin polling mechanism in this paper. First, we calculate the CPU utilization of the software data plane according to the number of cycles the CPU spends on the valuable task. Then, our scheme controls the Tx queues and dynamically adjusts the output batch size based on the CPU utilization to optimize the forwarding latency of the software data plane. Compared with the original software data plane, the evaluation result shows that the forwarding latency can be reduced by 3.56% to 45% (in a single queue evaluation) and 4.35% to 55.54% (in a multiple queue evaluation).
Linear and Nonlinear Reduced Order Models for Sloshing for Aeroelastic Stability and Response Predictions
Authors: Pizzoli Marco , Saltari Francesco , Mastroddi Franco
Published: September 2022

This paper makes use of sloshing reduced-order models to investigate the effects of sloshing dynamics on aeroelastic stability and response of flying wing structure. More specifically, a linear frequency-domain operator derived by an equivalent mechanical model is used to model lateral (linear) sloshing dynamics whereas data-driven neural-networks are used to model the vertical (nonlinear) sloshing dynamics. These models are integrated into a formulation that accounts for both the rigid and flexible behavior of aircraft. A time domain representation of the unsteady aerodynamics is achieved by rational function approximation of the fully unsteady aerodynamics obtained via the doublet lattice method. The case study consists of the so called Body Freedom Flutter research model in two different configurations with one or two tanks partially filled with liquid with a mass comprising 25% of the aircraft structure. The results show that linear sloshing dynamics are able to change the stability margin of the aircraft in addition to having non-negligible effects on rigid body dynamics. On the other hand, vertical sloshing acts as a nonlinear damper and eventually provides limit cycle oscillations after flutter onset.
A Multispectral and Panchromatic Images Fusion Method Based on Weighted Mean Curvature Filter Decomposition
Authors: Pan Yuetao , Liu Danfeng , Wang Liguo , Xing Shishuai , Benediktsson Jón Atli
Published: September 2022

Since the hardware limitations of satellite sensors, the spatial resolution of multispectral (MS) images is still not consistent with the panchromatic (PAN) images. It is especially important to obtain the MS images with high spatial resolution in the field of remote sensing image fusion. In order to obtain the MS images with high spatial and spectral resolutions, a novel MS and PAN images fusion method based on weighted mean curvature filter (WMCF) decomposition is proposed in this paper. Firstly, a weighted local spatial frequency-based (WLSF) fusion method is utilized to fuse all the bands of a MS image to generate an intensity component IC. In accordance with an image matting model, IC is taken as the original α channel for spectral estimation to obtain a foreground and background images. Secondly, a PAN image is decomposed into a small-scale (SS), large-scale (LS) and basic images by weighted mean curvature filter (WMCF) and Gaussian filter (GF). The multi-scale morphological detail measure (MSMDM) value is used as the inputs of the Parameters Automatic Calculation Pulse Coupled Neural Network (PAC-PCNN) model. With the MSMDM-guided PAC-PCNN model, the basic image and IC are effectively fused. The fused image as well as the LS and SS images are linearly combined together to construct the last α channel. Finally, in accordance with an image matting model, a foreground image, a background image and the last α channel are reconstructed to acquire the final fused image. The experimental results on four image pairs show that the proposed method achieves superior results in terms of subjective and objective evaluations. In particular, the proposed method can fuse MS and PAN images with different spatial and spectral resolutions in a higher operational efficiency, which is an effective means to obtain higher spatial and spectral resolution images.
Machine Learning and Deep Learning Models Applied to Photovoltaic Production Forecasting
Authors: Cordeiro-Costas Moisés , Villanueva Daniel , Eguía-Oller Pablo , Granada-Álvarez Enrique
Published: September 2022

The increasing trend in energy demand is higher than the one from renewable generation, in the coming years. One of the greatest sources of consumption are buildings. The energy management of a building by means of the production of photovoltaic energy in situ is a common alternative to improve sustainability in this sector. An efficient trade-off of the photovoltaic source in the fields of Zero Energy Buildings (ZEB), nearly Zero Energy Buildings (nZEB) or MicroGrids (MG) requires an accurate forecast of photovoltaic production. These systems constantly generate data that are not used. Artificial Intelligence methods can take advantage of this missing information and provide accurate forecasts in real time. Thus, in this manuscript a comparative analysis is carried out to determine the most appropriate Artificial Intelligence methods to forecast photovoltaic production in buildings. On the one hand, the Machine Learning methods considered are Random Forest (RF), Extreme Gradient Boost (XGBoost), and Support Vector Regressor (SVR). On the other hand, Deep Learning techniques used are Standard Neural Network (SNN), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN). The models are checked with data from a real building. The models are validated using normalized Mean Bias Error (nMBE), normalized Root Mean Squared Error (nRMSE), and the coefficient of variation (R2). Standard deviation is also used in conjunction with these metrics. The results show that the models forecast the test set with errors of less than 2.00% (nMBE) and 7.50% (nRMSE) in the case of considering nights, and 4.00% (nMBE) and 11.50% (nRMSE) if nights are not considered. In both situations, the R2 is greater than 0.85 in all models.
Research on the Visual Guidance System of Zoning Casting Grinding Based on Feature Points
Authors: Zhu Minjian , Shang Tao , Jin Zelin , Liu Chunshan , Deng Wenbin , Chen Yanli
Published: September 2022

Compared to traditional rough casting grinding (RCG), the individualization of castings is very different, which makes it difficult to realize the automation of casting grinding. At this stage, the primary method is manual grinding. In this study, the regional casting grinding system based on feature points is adopted to achieve the personalized grinding of castings and improve the grinding efficiency and the automation level of the manufacturing process. After preprocessing the point cloud, the fast point feature histogram (FPFH) descriptor is used to describe the features of each region and construct the local template. The position of the local region is obtained by template matching. The random sample consensus (RANSAC) algorithm is used to calculate the plane and fit the point cloud to obtain the contact point trajectory of the grinding head. Then, according to different polishing methods, different polishing poses are generated. The simulation experimental results show that the system has good adaptability, and the consistency of finished products is good.
Measuring the Positions of the Solder Pins of Electrical Connectors from the Side
Authors: Lee Wei-chen , Huang Kuan-Chuan
Published: September 2022

In the electronics industry, it is common to measure the positions of the solder pins of electrical connectors from the bottom using the automated optical inspection (AOI) technique. However, the pins’ surfaces facing the camera of the AOI system may generate image noises, leading to inaccurate measurement results. The objective of the paper is to develop a machine vision system with an algorithm to measure the pin position from the side. Two images must be captured in different view directions so that the algorithm can use the information on the images to calculate the positions of the pins. Comparing the results obtained using the proposed method and those obtained using a 2D vision measuring machine to measure the positions from the bottom, we found that the maximum difference in the results was 0.03 mm. The technique presented in the paper can provide an alternative solution for measuring the positions of the solder pins of electrical connectors or similar components if measurement from the bottom is not feasible.
Decoding Structure–Odor Relationship Based on Hypergraph Neural Network and Deep Attentional Factorization Machine
Authors: Wang Yu , Zhao Qilong , Ma Mingyuan , Xu Jin
Published: September 2022

Understanding the relationship between the chemical structure and physicochemical properties of odor molecules and olfactory perception, i.e., the structure–odor relationship, remains a decades-old, challenging task. However, the differences among the molecular structure graphs of different molecules are subtle and complex, and the molecular feature descriptors are numerous, with complex interactions that cause multiple odor perceptions. In this paper, we propose to decompose the features of the molecular structure graph into feature vectors corresponding to each odor perception descriptor to effectively explore higher-order semantic interactions between odor molecules and odor perception descriptors. We propose an olfactory perception prediction model noted as HGAFMN, which utilizes a hypergraph neural network with the olfactory lateral inhibition-inspired attention mechanism to learn the molecular structure feature from the odor molecular structure graph. Furthermore, existing methods cannot effectively extract interactive features in the large number of molecular feature descriptors, which have complex relations. To solve this problem, we add an attentional factorization mechanism to the deep neural network module and obtain a molecular descriptive feature through the deep feature combination based on the attention mechanism. Our proposed HGAFMN has achieved good results in extensive experiments and will help product design and quality assessment in the food, beverage, and fragrance industries.
Economic Optimal Scheduling of Wind–Photovoltaic-Storage with Electric Vehicle Microgrid Based on Quantum Mayfly Algorithm
Authors: Liu Ximu , Zhao Mi , Wei Zihan , Lu Min
Published: September 2022

The effectiveness of energy management systems is a great concern for wind–photovoltaic-storage electric vehicle systems, which coordinate operation optimization and flexible scheduling with the power grid. In order to save system operation cost and reduce the energy waste caused by wind and light abandonment, a time-sharing scheduling strategy based on the state of charge (SOC) and flexible equipment is proposed, and a quantum mayfly algorithm (QMA) is innovatively designed to implement the strategy. Firstly, a scheduling strategy is produced according to the SOC of the battery and electric vehicle (EV), as well as the output power of wind–photovoltaic generation. In addition, the minimum objective function of the comprehensive operation cost is established by considering the cost of each unit’s operation and electricity market sale price. Secondly, QMA is creatively developed, including its optimization rule, whose performance evaluation is further carried out by comparisons with other typical bionics algorithms. The advantages of QMA in solving the low-power multivariable functions established in this paper are verified in the optimization results. Finally, using the empirical value of the power generation and loads collected in enterprise as the initial data, the mayfly algorithm (MA) and QMA are executed in MATLAB to solve the objective function. The scheduling results show that the time-sharing scheduling strategy can reduce the system’s cost by 60%, and the method decreases energy waste compared with ordinary scheduling methods, especially when using QMA to solve the function.
Activation Energy and Inclination Magnetic Dipole Influences on Carreau Nanofluid Flowing via Cylindrical Channel with an Infinite Shearing Rate
Authors: Ayub Assad , Sajid Tanveer , Jamshed Wasim , Zamora William , More Leandro , Talledo Luz , Rodríguez Ortega de Peña Nélida , Hussain Syed , Hafeez Muhammad , Krawczuk Marek
Published: September 2022

Background: The infinite shear viscosity model of Carreau fluid characterizes the attitude of fluid flow at a very high/very low shear rate. This model has the capacity for interpretation of fluid at both extreme levels, and an inclined magnetic dipole in fluid mechanics has its valuable applications such as magnetic drug engineering, cold treatments to destroy tumors, drug targeting, bio preservation, cryosurgery, astrophysics, reaction kinetics, geophysics, machinery efficiency, sensors, material selection and cosmology. Novelty: This study investigates and interprets the infinite shear rate of Carreau nanofluid over the geometry of a cylindrical channel. The velocity is assumed to be investigated through imposing an inclined magnetic field onto cylindrical geometry. Activation energy is utilized because it helps with chemical reactions and mass transport. Furthermore, the effects of thermophoresis, the binary chemical process and the Brownian movement of nanoparticles are included in this attempt. Formulation: The mathematics of the assumed Carreau model is derived from Cauchy stress tensor, and partial differential equations (PDEs) are obtained. Similarity transformation variables converted these PDEs into a system of ordinary differential equations (ODEs). Passing this system under the bvp4c scheme, we reached at numerical results of this research attempt. Findings: Graphical debate and statistical analysis are launched on the basis of the obtained computed numerical results. The infinite shear rate aspect of Carreau nanofluid gives a lower velocity. The inclined magnetic dipole effect shows a lower velocity but high energy. A positive variation in activation energy amplifies the concentration field.
Implementation of Petrographical and Aeromagnetic Data to Determine Depth and Structural Trend of Homrit Waggat Area, Central Eastern Desert, Egypt
Authors: Lasheen El Saeed R. , Mohamed Waheed H. , Ene Antoaneta , Awad Hamdy A. , Azer Mokhles K.
Published: September 2022

In the current study, we conducted petrographic investigation combined with aeromagnetic data in order to classify variable granitic rocks, delineate structural trends and deduce depth of the basement rocks cropping out in Homrit Waggat area, Central Eastern Desert, Egypt. Field and petrographic investigations revealed that the granitic Homrit Waggat rocks include two groups. The first group includes the older granitic rocks, comprising tonalites and granodiorites. In contrast, the second one includes younger granitic rocks, involving alkali-feldspar granites, syenogranites and albitized granites. Depth as well as subsurface structures can be identified using magnetic method. Two tectonic maps representing the deep-seated and the shallow-seated structural features were constructed to show the structural history of the study area. The major tectonic trends indicate that the regional structures are controlled by deeper structures which have NW–SE, NNE–SSW—NE–SW and N–S directions. On the other hand, we find that the local structure trends are controlled by the local shallow structures that have NNE–SSW, NNW–SSE, ESE–WNW and N–S directions. Depth levels of the economic rare metal-bearing rocks range from 0 km to 1.2 km (Euler deconvolution technique) and from 0 km to 2.3 km (the analytical signal profiles) by using the aeromagnetic data, reflecting large resources of rare metal-bearing rocks.
Cumulative Energy Demand and Carbon Footprint of the Greenhouse Cultivation System
Authors: Grabarczyk Robert , Grabarczyk Sławomir
Published: September 2022

The paper describes the influence of horticultural production in greenhouses under Polish climate conditions on energy consumption, contributing to greenhouse gas emissions and global warming. Four scenarios were studied, two of which were non-renewable fuels: coal and natural gas, while the other two were renewable energy sources: wood pellets and wood chips, to identify opportunities for reducing energy costs and greenhouse gas emissions. Cumulative energy demand was defined to assess these four scenarios. The environmental impact was determined using the carbon footprint of the principal greenhouse gases emitted and using CO2 as the reference gas (CO2-equivalents). Renewable energy sources in greenhouse production can reduce the cumulative energy demand by 83.3% and greenhouse gas emissions by 95% compared to the coal-burning scenario. The presented research results relate to a greenhouse intended for growing flowers in pots, which has not been conducted so far. The article also updates the data on the environmental impact of crops grown in greenhouses located in Poland. The study provides important information for horticultural producers, mainly due to increasing competition and consumer awareness of the origin of products. Renewable energy sources in horticulture reveal a great potential in the reduction in greenhouse gases, and thus may become an inspiration to look for new solutions in this area.
Co-Inoculation with Phosphate-Solubilizing Microorganisms of Rock Phosphate and Phosphogypsum and Their Effect on Growth Promotion and Nutrient Uptake by Ryegrass
Authors: Amri Marwa , Mateus Dina , Gatrouni Marwa , Rjeibi Mohamed Ridha , Asses Nedra , Abbes Chaabane
Published: September 2022

In the previous half-century, natural rock phosphates (PN) have been a valuable alternative for phosphorus (P) fertilizer for sustainable agriculture; furthermore, phosphogypsum (PG) has been widely used as a soil amendment fertilizer since it improves some soil properties, increases crop yields, and represents an environmental concern that can make a good economic profit; this research aimed to study the effects of microbial consortia of phosphate-solubilizing microorganisms (PSM) on the solubilization of PN and PG in the soil, and their effects on promoting plant growth and nutrient assimilation using ryegrass as a plant model. Local supply of PG with Pseudomonas fluorescens (MW165744) significantly increases root proliferation and plant biomass dry weight compared to other isolates, as well as improves total P uptake, with a maximum value of 62.31 mg/pot. The opposite occurred in mixing inoculation with Pseudomonas fluorescens, Pantoea agglomerans (MW165752) and Stenotrophomonas maltophilia (MW221274), with a negligible total P assimilation of 5.39 mg/pot. Whereas the addition of Pseudomonas agglomerans with PG gave outstanding total P absorption of 57.05 mg/pot when compared with PN input of 38.06 mg/pot. Finally, the results prove that the co-inoculation of Pseudomonas fluorescens with PG could be a promising and alternative option to use it as a source of P fertilizer for plants and to maintain a high level of nutrients in the soil.
Elucidating the Chemical Compositions and Source Apportionment of Multi-Size Atmospheric Particulate (PM10, PM2.5 and PM1) in 2019–2020 Winter in Xinxiang, North China
Authors: Liu Huanjia , Jia Mengke , You Ke , Wang Jingjing , Tao Jie , Liu Hengzhi , Zhang Ruiqin , Li Lanqing , Xu Mengyuan , Ren Yan , Zhao Yijie , Liu Yongli , Cheng Ke , Fan Yujuan , Li Juexiu
Published: September 2022

The pollution characteristics of multi-size atmospheric particulates in Xinxiang, which was one of the most polluted cities across China, are still unclear even through air quality in Xinxiang has been improved in recent years. PM10, PM2.5, and PM1 samples were synchronously collected from 21 December 2019 to 17 January 2020 to explore pollution levels and reveal sources of PM in Xinxiang. The average mass concentrations of PM10, PM2.5, and PM1 were as high as 155.53 μg m−3, 120.07 μg m−3, and 85.64 μg m−3 during the observation period, respectively. Almost all of the chemical compositions in PM10, PM2.5 and PM1 increased continuously and obviously with the aggravation of the pollution level. Compared with the clean period, the enhancement of sulfate (23–27%) in PM was obvious higher than nitrate (19–22%) during the pollution period, which demonstrated that sulfate was the main contributor to the high concentration of PM in this study. Similar source distributions for PM10, PM2.5, and PM1 were also found, including traffic source, combustion source, secondary aerosols, industrial source, and fugitive dust, by using the positive matrix factorization (PMF) model. Furthermore, the contributions of the combustion source and secondary aerosol were found to be higher in smaller particles (PM2.5 and PM1), while the contribution of fugitive dust was higher in PM10. Moreover, dust and sand were entrained by air masses from the northwest that increased the contribution of dust in PM at the observation site. The potential source contribution function (PSCF) analysis illustrated that regional emission sources in northern and eastern Xinxiang might be important potential contributors to PM pollution in Xinxiang.
US Clean Energy Futures—Air Quality Benefits of Zero Carbon Energy Policies
Authors: Vasilakos Petros N. , Shen Huizhong , Mehdi Qasim , Wilcoxen Peter , Driscoll Charles , Fallon Kathy , Burtraw Dallas , Domeshek Maya , Russell Armistead G.
Published: September 2022

In this work, we compare the air quality benefits of a variety of future policy scenarios geared towards controlling EGU (electricity generating units) emissions between the present-day conditions and 2050. While these policies are motivated by reducing CO2 emissions, they also yield significant co-benefits for criteria pollutants, such as ozone and PM2.5. An integrated set of clean energy policies were examined to assess the time-varying costs and benefits of a range of decarbonization strategies, including business as usual and the Affordable Clean Energy plan, with a primary focus on others that look to achieve very low, if not zero, CO2 emissions from the EGU sector by 2050. Benefits assessed include mitigation of greenhouse gas emissions as well as air quality co-benefits. In this introductory work, we describe the potential air quality changes from various clean air policies, to set the stage for upcoming work looking at health and monetized benefits. Emission changes for key pollutants are forecast using the Integrated Planning Model (IPM), which are then transformed into emission inputs for the Community Multiscale Air Quality Model (CMAQ). For all primary scenarios considered that achieve large greenhouse gas decreases, significant reductions in ozone and PM are realized, mainly in the eastern US, and all policies produce air quality benefits.
Influence of Atmospheric 10–20 Day Low Frequency Oscillation on Regional Strong Cooling Events in the Winter of Northern China over the Past 40 Years
Authors: Zhang Wei , Li Liping , Ren Jinghua
Published: September 2022

Using daily minimum temperature data at 2481 stations provided by the National Meteorological Information Center (China) and the daily reanalysis data from NCEP/NCAR during the period from 1980 to 2019, the effects of atmospheric low frequency oscillations (LFOs) on the regional strong cooling events (RSCEs) in the winter of northern China are investigated, and the extended range forecast signals of the RSCEs are extracted. The results show that: (1) The frequency of RSCEs is higher before the year 2000 and then decreases, but its interannual variability increases. There are 10–20, 20–30 and 30–60 d significant low frequency periods in the regional average minimum temperature in northern China, and the low frequency oscillation with a period of 10–20 d is the most significant. (2) The low frequency key systems affecting RSCEs in the west, middle, and east of northern China are the Ural blocking high and the trough of Lake Balkhash-Baikal (Lake Ba-Bei), the blocking high in the northwest and the low trough in the southeast of Lake Ba-Bei, the Lake Ba-Bei blocking high and the East Asian trough, respectively, and the Siberian High (SH) that expands and moves with the blocking high all the time. The low frequency jets at the upper level are weaker in the north and stronger in the south. (3) The low frequency high potential vorticity (PV) center in the lower stratosphere moves eastward and southward along the 315 K isentropic surface via the north of Lake Ba-Bei, southern Lake Baikal and Northeast China to the Sea of Japan, causing the 2 PVU line to move southward and then the above-mentioned high PV center in the mid-high troposphere to extend vertically. Meanwhile, under the influence of gradually increasing upper level jets and vertical meridional circulation, the high PV column continues to propagate downward to the mid-low troposphere at lower latitudes along the 300–315 K isentropic surfaces, which enhances the low frequency positive vorticity and deepens the key trough. In addition, the convergence in the upper troposphere, the divergence in the lower layer, and the development of descending motion behind the trough lead to the development and southward movement of the SH. (4) At −10 d, the positive and negative low frequency anomalies at 500 hPa geopotential height appearing in the East European Plain and Western Siberian Plain are the extended range forecast signals for RSCEs in the winter of northern China, respectively.
A 3D Monte Carlo Simulation for Aerosol Deposition onto Horizontal Surfaces by Combined Mechanisms of Brownian Diffusion and Gravity Sedimentation
Authors: Wu Shixian , Zhu Hui , Chen Yongping , Qi Can , Li Gang
Published: September 2022

A three-dimensional Monte Carlo model was developed to simulate the deposition of aerosol particles onto horizontal solid surfaces. The random walk method was employed to solve the particle transport equation, which allowed obtaining the trajectory of particle motion by a combined mechanism of Brownian diffusion and gravity sedimentation. The particle transport mechanism was described in terms of a Peclet number (Pe). The local structures of the dust layer, the relationship between the structure of the dust layer and particle transport mechanisms, and the number of the particles attached to the solid surface were investigated. The results showed that for a small Pe, when Brownian diffusion was a controlling mechanism for aerosol transport, the dust layer might exhibit a more open and looser structure, while for a large Pe, the dust layer was dense and tight. The differences of deposition morphologies under different transport mechanisms were caused by the different random intensities of particle motion. There was an upper limit of the maximum number of particles attached to the surface, and it strongly depended on particle transport mechanisms and size distributions. Additionally, the deposit morphologies obtained with the 3D Monte Carlo model were in good agreement with the experimental results found in the literature.