bluuebunny/crossref_metadata_2025 huggingface dataset:
An Explainable Classification Method of SPECT Myocardial Perfusion Images in Nuclear Cardiology Using Deep Learning and Grad-CAM
Authors: Papandrianos Nikolaos I. , Feleki Anna , Moustakidis Serafeim , Papageorgiou Elpiniki I. , Apostolopoulos Ioannis D. , Apostolopoulos Dimitris J.
Published: July 2022

Background: This study targets the development of an explainable deep learning methodology for the automatic classification of coronary artery disease, utilizing SPECT MPI images. Deep learning is currently judged as non-transparent due to the model’s complex non-linear structure, and thus, it is considered a «black box», making it hard to gain a comprehensive understanding of its internal processes and explain its behavior. Existing explainable artificial intelligence tools can provide insights into the internal functionality of deep learning and especially of convolutional neural networks, allowing transparency and interpretation. Methods: This study seeks to address the identification of patients’ CAD status (infarction, ischemia or normal) by developing an explainable deep learning pipeline in the form of a handcrafted convolutional neural network. The proposed RGB-CNN model utilizes various pre- and post-processing tools and deploys a state-of-the-art explainability tool to produce more interpretable predictions in decision making. The dataset includes cases from 625 patients as stress and rest representations, comprising 127 infarction, 241 ischemic, and 257 normal cases previously classified by a doctor. The imaging dataset was split into 20% for testing and 80% for training, of which 15% was further used for validation purposes. Data augmentation was employed to increase generalization. The efficacy of the well-known Grad-CAM-based color visualization approach was also evaluated in this research to provide predictions with interpretability in the detection of infarction and ischemia in SPECT MPI images, counterbalancing any lack of rationale in the results extracted by the CNNs. Results: The proposed model achieved 93.3% accuracy and 94.58% AUC, demonstrating efficient performance and stability. Grad-CAM has shown to be a valuable tool for explaining CNN-based judgments in SPECT MPI images, allowing nuclear physicians to make fast and confident judgments by using the visual explanations offered. Conclusions: Prediction results indicate a robust and efficient model based on the deep learning methodology which is proposed for CAD diagnosis in nuclear medicine.
A New Road Damage Detection Baseline with Attention Learning
Authors: Zhang Hongwei , Wu Zhaohui , Qiu Yuxuan , Zhai Xiangcheng , Wang Zichen , Xu Peng , Liu Zhenzheng , Li Xiantong , Jiang Na
Published: July 2022

Automated detection of road damage (ADRD) is a challenging topic in road maintenance. It focuses on automatically detecting road damage and assessing severity by deep learning. Because of the sparse distribution of characteristic pixels, it is more challenging than object detection. Although some public datasets provide a database for the development of ADRD, their amounts of data and the standard of classification cannot meet network training and feature learning. With the aim of solving this problem, this work publishes a new road damage dataset named CNRDD, which is labeled according to the latest evaluation standard for highway technical conditions in China (JTG5210-2018). The dataset is collected by professional onboard cameras and is manually labeled in eight categories with three different degrees (mild, moderate and severe), which can effectively help promote research of automated detection of road damage. At the same time, a novel baseline with attention fusion and normalization is proposed to evaluate and analyze the published dataset. It explicitly leverages edge detection cues to guide attention for salient regions and suppresses the weights of non-salient features by attention normalization, which can alleviate the interference of sparse pixel distribution on damage detection. Experimental results demonstrate that the proposed baseline significantly outperforms most existing methods on the existing RDD2020 dataset and the newly released CNRDD dataset. Further, the CNRDD dataset is proved more robust, as its high damage density and professional classification are more conducive to promote the development of ADRD.
Artificial Intelligence (AI) Applied in Civil Engineering
Authors: Lagaros Nikos D. , Plevris Vagelis
Published: July 2022

In recent years, artificial intelligence (AI) has drawn significant attention with respect to its applications in several scientific fields, varying from big data handling to medical diagnosis [...]
Infrared Spectroscopy–Quo Vadis?
Authors: Hlavatsch Michael , Haas Julian , Stach Robert , Kokoric Vjekoslav , Teuber Andrea , Dinc Mehmet , Mizaikoff Boris
Published: July 2022

Given the exquisite capability of direct, non-destructive label-free sensing of molecular transitions, IR spectroscopy has become a ubiquitous and versatile analytical tool. IR application scenarios range from industrial manufacturing processes, surveillance tasks and environmental monitoring to elaborate evaluation of (bio)medical samples. Given recent developments in associated fields, IR spectroscopic devices increasingly evolve into reliable and robust tools for quality control purposes, for rapid analysis within at-line, in-line or on-line processes, and even for bed-side monitoring of patient health indicators. With the opportunity to guide light at or within dedicated optical structures, remote sensing as well as high-throughput sensing scenarios are being addressed by appropriate IR methodologies. In the present focused article, selected perspectives on future directions for IR spectroscopic tools and their applications are discussed. These visions are accompanied by a short introduction to the historic development, current trends, and emerging technological opportunities guiding the future path IR spectroscopy may take. Highlighted state-of-the art implementations along with novel concepts enhancing the performance of IR sensors are presented together with cutting-edge developments in related fields that drive IR spectroscopy forward in its role as a versatile analytical technology with a bright past and an even brighter future.
Converging Telco-Grade Solutions 5G and beyond to Support Production in Industry 4.0
Authors: Varga Pal , Bácsi Sándor , Sharma Ravi , Fayad Abdulhalim , Mandeel Ali Raheem , Soos Gabor , Franko Attila , Fegyo Tibor , Ficzere Dániel
Published: July 2022

The Industry 4.0 initiative has been showing the way for industrial production to optimize operations based on collecting, processing, and sharing data. There are new requirements on the production floor: flexible but ultra-reliable, low latency wireless communications through interoperable systems can share data. Further challenges of data sharing and storage arise when diverse systems come into play at the Manufacturing Operations Management and Business Planning & Logistics levels. The emerging complex cyber-physical systems of systems need to be engineered with care. Regarding industrial requirements, the telecommunication industry has many similarities to production—including ultra-reliability, high complexity, and having humans “in-the-loop”. The current paper aims to provide an overview of converging telco-grade solutions that can be successfully applied in the wide sense of industrial production. These toolsets range from model-driven engineering through system interoperability frameworks, 5G- and 6G-supported manufacturing, and the telco-cloud to speech recognition in noisy environments.
Using a Combination of Activated Carbon and Graphene Nanoparticles in a Consolidated Form for Adsorption Ice Maker: A System-Level Modeling
Authors: Elsheniti Mahmoud Badawy , Eissa Mohamed Shaaban , Al-Ansary Hany , Orfi Jamel , El-Leathy Abdelrahman , Elsamni Osama
Published: July 2022

Adsorption refrigeration systems are one of the emerging decarbonization technologies that can use eco-friendly heating sources and working fluids. However, the highly porous adsorbent materials used in these systems have a low thermal conductivity that hinders their system performance enhancement. Graphene nanoplatelets are proposed in the literature to improve the conductive heat transfer through the adsorbent field and the resulting composite adsorbents were favorably testified at the material level. In this study, the impact of employing a composite adsorbent that comprises of 50% activated carbon type Maxsorb III, 40% graphene nanoplatelets, and 10% binder was numerically investigated at a system level. The contradictory effects of heat and mass transfer mechanisms within the composite adsorbent on the performance of an adsorption ice production system were explored for three cases of composite layer thicknesses at different cycle times. The results showed that the maximum specific daily ice production and coefficient of performance of 33.27 kgice·kgads−1·day−1 and 0.3046 were attained at composite thicknesses of 2 and 5 mm and cycle times of 430 and 1230 s, respectively. The higher composite thickness of 10 mm increased the mass transfer resistances, which overlooked the enhancement in the heat transfer and reduced the overall performance.
Accelerating FVM-Based Parallel Fluid Simulations with Better Grid Renumbering Methods
Authors: Zhang Huajian , Guo Xiao-Wei , Li Chao , Liu Qiao , Xu Hanwen , Liu Jie
Published: July 2022

Grid renumbering techniques have been shown to be effective in improving the efficiency of computational fluid dynamics (CFD) numerical simulations based on the finite volume method (FVM). However, with the increasing complexity of real-world engineering scenarios, there is still a huge challenge to choose better sequencing techniques to improve parallel simulation performance. This paper designed an improved metric (MDMP) to evaluate the structure of sparse matrices. The metric takes the aggregation of non-zero elements inside the sparse matrix as an evaluation criterion. Meanwhile, combined with the features of the cell-centered finite volume method supporting unstructured grids, we proposed the cell quotient (CQ) renumbering algorithm to further reduce the maximum bandwidth and contours of large sparse matrices with finite volume discretization. Finally, with real-world engineering cases, we quantitatively analyzed the evaluation effect of MDMP and the optimization effect of different renumbering algorithms. The results showed that the classical greedy algorithm reduces the maximum bandwidth of the sparse matrix by at most 60.34% and the profile by 95.38%. Correspondingly, the CQ algorithm reduced them by at most 92.94% and 98.70%. However, in terms of MDMP, the CQ algorithm was 83.43% less optimized than the Greedy algorithm. In terms of overall computational speed, the Greedy algorithm was optimized by a maximum of 38.19%, and the CQ algorithm was optimized by a maximum of 27.31%. The above is in accordance with the evaluation results of the MDMP metric. Thus, our new metric can more accurately evaluate the renumbering method for numerical fluid simulations, which is of great value in selecting a better mesh renumbering method in engineering applications of CFD.
An NUTSF at Sub-Region for Suppression of Torque Ripple in Switched Reluctance Motors
Authors: Huang Chaozhi , Cao Wensheng , Xu Junxin
Published: July 2022

The conventional torque sharing function (TSF) control strategy in a switched reluctance motor (SRM) has higher torque ripple due to the weak torque tracking ability with an increase in speed. A non-unity torque sharing function (NUTSF) is proposed in order to minimize the torque ripple. Firstly, the working principle of the conventional TSF is introduced, and the causes of higher torque ripple are analyzed. Secondly, the NUTSF control strategy at each sub-region, where the two-phase exchange region is further divided into region 1 and region 2 based on the inductance characteristics, is proposed, and an optimization algorithm at each sub-region is applied so that the TSF is more suitable for the inductance and torque characteristics of the motor. Finally, a three-phase 6/20 SRM is taken as an example for simulation analysis and a prototype experiment. The results show that the proposed control strategy can effectively reduce the torque ripple of an SRM at a wide speed range.
Analysis and Application of Lining Resistance to Water Pressure in Tunnel through Karst Cave
Authors: Huang Mingli , Li Jiacheng , Yang Ze , Zhang Zhien , Song Yuan
Published: July 2022

Using RFPA software, the hydraulic pressure resistance and damage process of the grouted stone body of a tunnel in the high-pressure karst zone were analyzed, and the hydraulic pressure resistance of the composite surrounding rock and composite structure when the tunnel was expanded through the cavern under the effect of hydraulic coupling was investigated. Then, a new parallel heading expansion scheme for the New Yuanliang Mountain Tunnel was innovatively discussed, and the reliability of the results of the calculation model was verified by a field test. Lastly, the model calculation results guided the project to adopt a 5 m grouting range and advanced secondary lining to ensure that the composite structure’s water pressure resistance could reach 3 MPa; by adopting the improved technology of parallel heading expansion based on the CRD method, the safety of tunnel expansion through the cavity was effectively ensured, which can provide a reference for similar projects in the future.
Study on Reducing Towing Drag by Varying the Shape and Arrangement of Floats and Gears
Authors: Jung Jung-Mo , Matsushita Yoshiki , Kim Seonghun
Published: July 2022

Many studies have been conducted with the aim of reducing fuel consumption by the fishing industry. We examined whether drag can be reduced by changing the arrangement of gears without requiring the development of new parts for the conventional float and ground gear. Ten differently shaped floats and ground gears were measured in a water flume tank. The float and ground gear were fixed to a steel rod to measure fluid drag according to attack angle, using a multi-component load cell. To estimate the frictional drag of ground gear on the seabed, five types of large ground gear were towed on flat land while changing attack angle using the load cell to measure tension. The fluid drag of the float and ground gear was highest at an attack angle of 60°, regardless of shape, size, and flow velocity. The resistance coefficients of the float and ground gear varied depending on the attack angle and tended to be lower at small attack angles. The frictional drag of the ground gear was greater when the axis of rotation had a small attack angle in the towing direction compared to other attack angles. We then investigated a method for designing bottom-towed gear that reduces drag while maintaining the size, buoyancy, and sinking force of conventional fishing gear parts. This gear design showed 1.2% drag reduction and an estimated 0.8% improvement in fuel efficiency per haul.
Detecting Dynamic Communities in Vehicle Movements Using Ant Colony Optimization
Authors: Liu Qiliang , Zhu Sancheng , Chen Meihua , Liu Wenkai
Published: July 2022

Detecting dynamic community structure in vehicle movements is helpful for revealing urban structures and human mobility patterns. Despite the fruitful research outcomes of community detection, the discovery of irregular-shaped and statistically significant dynamic communities in vehicle movements is still challenging. To overcome this challenge, we developed an evolutionary ant colony optimization (EACO) method for detecting dynamic communities in vehicle movements. Firstly, a weighted, spatially embedded graph was constructed at each time snapshot. Then, an ant-colony-optimization-based spatial scan statistic was upgraded to identify statistically significant communities at each snapshot by considering the effects of the communities discovered at the previous snapshot. Finally, different rules defined based on the Jaccard coefficient were used to identify the evolution of the communities. Experimental results on both simulated and real-world vehicle movement datasets showed that EACO performs better than three representative dynamic community detection methods: FacetNet (a framework for analyzing communities and evolutions in dynamic networks), DYNMOGA (dynamic multi-objective genetic algorithm), and RWLA (random-walk-based Leiden algorithm). The dynamic communities identified by EACO may be useful for understanding the dynamic organization of urban structures.
Evaluation of Selected Heavy Metals Contaminants in the Fruits and Leaves of Organic, Conventional and Wild Raspberry (Rubus idaeus L.)
Authors: Kotuła Marta , Kapusta-Duch Joanna , Smoleń Sylwester
Published: July 2022

Chemical pollutants contaminate the air, soil and then plants, which are the main source of xenobiotics for humans. Many consumers perceive that organically grown foods are of better quality, healthier and more nutritious than conventionally grown foods. The aim of the study was to analyse raspberry fruits and leaves from organic, conventional and wild crops in Poland for two years, independently of climatic and agrotechnical conditions. The metal contents (Al, B, Cu, Mn and Zn) were determined using the validated Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and by Inductively Coupled Plasma Mass Spectrometry (ICP-MS/MS) (As, Cd, Pb, Cr, Co, Mo, V, Sr, Sb, Ti and Tl). The raspberry fruits from organic farming contained more (p ≤ 0.05) Cd, Zn, Mn and V compared to those from conventional cultivation. Fruits of wild-growing raspberry had more Cd, Zn, Co and Mn compared to other crops. Wild-growing raspberry leaves had more Cd, Pb, Zn, Mn and Tl than the other leaves. The raspberry leaves from organic cultivation had more Cr, Cd and Pb compared to leaves from conventional cultivation. The leaves and fruits of wild-growing raspberry are characterized by a significantly higher content of heavy metals.
Split-Spectrum Processing with Raised Cosine Filters of Constant Frequency-to-Bandwidth Ratio for L(0,2) Ultrasonic Guided Wave Testing in a Pipeline
Authors: Tang Binghui , Wang Yuemin , Chen Ang , Zhao Yunwei , Xu Jianjian
Published: July 2022

Ultrasonic guided wave (UGW) nondestructive testing suffers from poor signal interpretation accuracy caused by the coherent noise that is related to dispersion, multi-mode and mode conversion. In order to split the L(0,2) UGW from the coherent noise, split-spectrum processing with raised cosine filters of constant frequency-to-bandwidth ratio (FBR-RC-SSP) is proposed. With the advantages of time domain resolution and frequency domain split, FBR-RC-SSP is studied based on time-frequency analysis using the chirplet transform, and the effects of filter parameters on signal-to-noise ratio gain (SNRG) and defect-to-coherent noise gain (DCRG) are explained. The excellent effects of eliminating the coherent noise and improving the signal resolution in FBR-RC-SSP are reported by the validation of synthesized, simulated and experimental UGW signals, of which the average SNRG and DCRG are 22.92% and 23.71% higher than those of traditional SSP using Gaussian filters, and it has the potential to locate and characterize defects in further UGW testing research.
Distribution of Magnetic Flux Density under Stress and Its Application in Nondestructive Testing
Authors: Berkache Azouaou , Lee Jinyi , Wang Dabin , Sim Sunbo
Published: July 2022

Carbon steels are commonly used in railroad, shipment, building, and bridge construction. They provide excellent ductility and toughness when exposed to external stresses. They are able to resist stresses and strains effectively, and guarantee safe operation of the devices through nondestructive testing (NDT). The magnetic metal memory (MMM) can be used as an NDT method to measure the residual stress. The ability of carbon steel to produce a magnetic memory effect under stress is explored here, and enables the magnetic flux density to be analyzed. The relationship between stress and magnetic flux density has not been fully presented until now. The purpose of this paper is to assess the relationship between stress distribution and the magnetic flux density measured by the experiment. For this, an experimental method for examining a carbon steel plate (SA 106), based on the four-point loading test, was used. The effect of stresses resulting from the applied loads on the response of the experimented SA 106 specimen was examined. A three directional tunnel magnetoresistance (TMR) measurement system was used to collect the triaxial magnetic flux density distribution in the SA 106 specimen. In addition, finite element method (FEM) analyses were performed, and provided information on the direction and distribution of the stress over the studied SA 106 specimen. Indeed, a correlation was derived by comparing the stress analysis by FEM and the measured triaxial magnetic flux density.
A Simulation-Based Framework for Manufacturing Design and Resilience Assessment: A Case Study in the Wood Sector
Authors: Longo Francesco , Mirabelli Giovanni , Solina Vittorio , Alberto Umberto , De Paola Giuseppe , Giordano Luigi , Ziparo Marco
Published: July 2022

The advent of modern digital technologies offers new opportunities to improve the performance of manufacturing systems from design to monitoring and control during operation. At the same time, the recent COVID-19 pandemic has highlighted the fragility of all global supply chains and manufacturing systems. In this paper, a simulation-based framework, exploiting the benefits of the digital model concept, is proposed. It aims at: (1) supporting manufacturing design to effectively start a new business, (2) assessing the resilience of a manufacturing system in the face of disruptions, (3) evaluating the goodness of possible strategies to deal with COVID-like crises. The validity of the proposed framework is successfully demonstrated through a real-life case study, referring to the wood sector. The results show that a lack of system preparedness can lead to productivity reductions of up to 31.8%. At the same time, having the ability to react to unexpected events can limit damage and increase productivity by 26% compared to not reacting.
Percolation Threshold of Red-Bed Soft Rock during Damage and Destruction
Authors: Yu Lei , Lai Haoqiang , Zhou Cuiying , Liu Zhen , Zhang Lihai
Published: July 2022

The critical damage point of the red-bed soft rock percolation phenomenon can be described as the percolation threshold. At present, there are insufficient theoretical and experimental studies on the percolation phenomenon and threshold of red-bed soft rock. In combination with theoretical analysis, compression experiment and numerical simulation, the percolation threshold and destruction of red-bed soft rock are studied in this paper. The theoretical percolation threshold of red-bed soft rock was obtained by constructing a renormalization group model of soft rock. Based on damage mechanics theory, rock damage characterization and strain equivalent hypothesis, a constitutive model of red-bed soft rock percolation damage was obtained. The percolation threshold of red-bed soft rock was determined by compression test and a damage constitutive model, which verified the rationality of the theoretical percolation threshold, and we numerically simulated the percolation of red-bed soft rock under triaxial compression. The results showed that the percolation threshold increases as the confining pressure rises, but decreases significantly with the action of water. In this study, the critical failure conditions and percolation characteristics of red-bed soft rock under different conditions were obtained. The relationship between percolation and soft rock failure was revealed, providing a new direction for studying the unstable failure of red-bed soft rock.
A Modified Hyrax-Type Expander Is Effective for Distal Bodily Movement of the Maxillary First Molar
Authors: Takahashi Mifumi , Tabuchi Masako , Sato Takuma , Hoshino Rina , Miyazawa Ken , Goto Shigemi
Published: July 2022

Impaction and eruption disturbance of permanent teeth are frequently encountered in orthodontic practice. The canine teeth play an important role both functionally and esthetically. Eruption disturbance of a maxillary canine, if left untreated, can cause not only disturbed jaw movement and esthetic problems, but also root resorption of adjacent permanent teeth, and thus should be diagnosed and treated appropriately. In this report, we present a case of a patient with eruption disturbance of the maxillary left canine in which the maxillary left second molar was extracted and the maxillary left first molar was distally moved with a Hyrax-type expander (Veltri Monolateral Screw®; Leone, Firenze, Italy) designed to enable the distal movement of a unilateral first molar in order to create eruption space for the maxillary left canine, resulting in smooth distal molar movement and alignment of the left maxillary canine in the dental arch. Furthermore, the maxillary third molar was also aligned to achieve a good occlusal relationship without reducing the number of teeth.
A Progressively Expanded Database for Automated Lung Sound Analysis: An Update
Authors: Hsu Fu-Shun , Huang Shang-Ran , Huang Chien-Wen , Cheng Yuan-Ren , Chen Chun-Chieh , Hsiao Jack , Chen Chung-Wei , Lai Feipei
Published: July 2022

We previously established an open-access lung sound database, HF_Lung_V1, and developed deep learning models for inhalation, exhalation, continuous adventitious sound (CAS), and discontinuous adventitious sound (DAS) detection. The amount of data used for training contributes to model accuracy. In this study, we collected larger quantities of data to further improve model performance and explored issues of noisy labels and overlapping sounds. HF_Lung_V1 was expanded to HF_Lung_V2 with a 1.43× increase in the number of audio files. Convolutional neural network–bidirectional gated recurrent unit network models were trained separately using the HF_Lung_V1 (V1_Train) and HF_Lung_V2 (V2_Train) training sets. These were tested using the HF_Lung_V1 (V1_Test) and HF_Lung_V2 (V2_Test) test sets, respectively. Segment and event detection performance was evaluated. Label quality was assessed. Overlap ratios were computed between inhalation, exhalation, CAS, and DAS labels. The model trained using V2_Train exhibited improved performance in inhalation, exhalation, CAS, and DAS detection on both V1_Test and V2_Test. Poor CAS detection was attributed to the quality of CAS labels. DAS detection was strongly influenced by the overlapping of DAS with inhalation and exhalation. In conclusion, collecting greater quantities of lung sound data is vital for developing more accurate lung sound analysis models.
A Data-Driven Model for Aerodynamic Loads on Road Vehicles Exposed to Gusty Bora-Like Winds
Authors: Kozmar Hrvoje , Jokić Marko , Butler Kyle , Stegić Milenko , Kareem Ahsan
Published: July 2022

Strong cross-wind gusts can cause the vehicle to overturn or slide off the road. This problem is particularly experienced on bridges, as vehicles are extremely sensitive to complex wind-bridge–vehicle interactions. While quasi-steady atmospheric winds create serious difficulties for vehicles, this fact is exacerbated by gusts of wind, as is the case with bora, where gusts of wind can reach velocities five times the average wind velocity. In the present study, experiments concerning aerodynamic loads experienced by vehicles exposed to gusty, bora-like winds are carried out. It is noted that the wind gusting and vortex shedding determine unsteady wind loads on vehicles. The experimental results are used as a basis for developing a simple data-driven modeling approach capable of predicting the time history of aerodynamic loads on vehicles exposed to cross-wind gusts. The modeling results indicate that a model using more than two-state variables is needed to capture the unsteady aerodynamic loads.
A QoS-Guaranteed and Congestion-Controlled SDN Routing Strategy for Smart Grid
Authors: Su Yueyuan , Jiang Ping , Chen Huan , Deng Xiaoheng
Published: July 2022

The smart grid (SG) is an integration of a traditional power grid with advanced information and communication infrastructure for a large number of electrical applications. Despite all these advantages that the SG will bring, certain issues arise when designing a high-quality SG communication network. One of the critical challenges is that the existing routing strategies in smart power grids are incapable of guaranteeing differentiated QoS requirements considering the network dynamics. To address this limitation, we propose an SDN routing algorithm called the QoS-guaranteed and congestion-controlled OpenFlow routing strategy (QCORS) to satisfy the various communication demands by utilizing the flexibility of SDN. Gaining from its open and programmable idea in SDN, the proposed strategy is expected to divide the link into different congestion levels based on predicting the future congestion status from transmission links. Then packets are expected to be transmitted to routers through links under lower load conditions. The simulation results have demonstrated that the proposed method can reduce the average peer-to-peer delay of all the vocational flow and guarantee the reliability of the network.
Characterization of Sorghum Processed through Dry Heat Treatment and Milling
Authors: Batariuc Ana , Ungureanu-Iuga Mădălina , Mironeasa Silvia
Published: July 2022

Sorghum grain nutritional quality can be enhanced by applying dry heat treatments. The purpose of this study was to investigate the effects of dry heat treatment at two temperatures (121 and 140 °C) with three fractionation factors (S fraction < 200 μm, M fraction 200–250 μm and, L fraction > 300 μm) on sorghum flour chemical and functional properties, to optimize processes by means of a desirability function, and to characterize the optimal products. Treatment temperature negatively affected oil- and water-absorption capacity, protein and moisture contents, while the opposite trend was obtained for hydration capacity, swelling power, emulsifying properties, fat, ash, and carbohydrate content. Sorghum flour fractions positively influenced the hydration and water-retention capacities, emulsifying properties, and protein and carbohydrate content, while oil absorption, swelling power, fat, ash, and moisture were negatively affected. The optimal processing determined for each fraction was heat treatment at 121.00 °C for S fraction, 132.11 °C for M, and 139.47 °C for L. Optimal product characterization revealed that the color, bioactive properties, and protein and starch structures of the optimal samples had changed after heat treatment, depending on the fraction. These findings could be helpful for the cereal industry, since sorghum flour could be an alternative for conventional crops for the development of new products, such as snacks, baked goods, and pasta.
Attenuation of Lightning-Induced Effects on Overhead Distribution Systems in Urban Areas
Authors: Mestriner Daniele , Marchesoni Flavia , Procopio Renato , Brignone Massimo
Published: July 2022

Overhead distribution systems can be strongly affected and damaged by indirect lightning. The induced voltages are usually computed neglecting the surrounding geometry and the presence of buildings in urban areas. Buildings can strongly change the behavior of the measured lighting-induced electromagnetic (EM) fields in the proximity of the point of impact. As a consequence, induced voltages can deviate from what would be measured in the absence of buildings. This work proposes an analysis of the main variables, which affect the deviation of the EM fields and of the consequent induced voltages along an overhead distribution line due to the presence of a building. Different distances between the line and the building and different building heights are considered.
An Adaptive Dempster-Shafer Theory of Evidence Based Trust Model in Multiagent Systems
Authors: Wang Ningkui , Wei Daijun
Published: July 2022

Multiagent systems (MASs) have a wide range of industrial applications due to agents’ advantages. However, because of the agents’ dynamic behaviors, it is a challenge to ensure the quality of service they present. In this paper, to address this problem, we propose an adaptive agent trust estimation model where agents may decide to go from genuine to malicious or the other way around. In the proposed trust model, both direct trust and indirect reputation are used. However, the indirect reputation derived from the direct experience of third-party agents must have reasonable confidence to be useful. The proposed model introduces a near-perfect measure that utilizes consistency, credibility, and certainty to capture confidence. Moreover, agents are incentivized to contribute correct information (to be honest) through a credit mechanism in the proposed model. Simulation experiments are conducted to evaluate the proposed model’s performance against some of the previous trust models reported in the literature.
Experimental Study on Dynamic Mechanical Properties of Sandstone Corroded by Strong Alkali
Authors: Ping Qi , Wang Chen , Gao Qi , Shen Kaifan , Wu Yulin , Wang Shuo , Sun Shijia
Published: July 2022

In order to analyze the effect of different corrosion times on the dynamic compression mechanical properties of sandstone, the coal mine sandstone specimens are subjected to corrosion in NaOH solution with pH 11 for 0 d, 1 d, 3 d, 7 d, 14 d, and 28 d, and then, the impact compression tests and Brazilian splitting test are conducted using a split Hopkinson pressure bar apparatus. The study results show that sandstone specimen mass and the average density growth rate increases, with the corrosion time first rapidly increasing and then tending to level off the trend. The impact of the compression specimens on the dynamic stress–strain curve change law is basically the same, but the time gradient curve shape is different, and the line elastic deformation stage and plastic deformation stage curve difference gradually decreases. The specimen dynamic compressive strength and the dynamic elastic modulus with corrosion time are quadratic, and the exponential function declines the relationship. After corrosion of 28 d sandstone specimens, the dynamic compressive strength and dynamic elastic modulus are much lower than the uncorroded specimens. The average strain rate and the dynamic peak strain with the corrosion time extension are a quadratic function of the increasing relationship after the corrosion effect of the sandstone dynamic peak strain, and the average strain rate is significantly greater than the uncorroded specimens. With the corrosion time extension of sandstone specimens by the impact of damage degree being increased, the 14 d and 28 d specimen ruptures’ degree is much greater than other time gradients. The dynamic tensile strength of the split specimens decreases with increasing corrosion time; the dynamic peak strain increases quadratically; and the transmitted energy also decreases with increasing corrosion time.
An Intelligent DOA Estimation Error Calibration Method Based on Transfer Learning
Authors: Zhang Min , Wang Chenyang , Zhu Wenli , Shen Yi
Published: July 2022

Affected by various error factors in the actual environment, the accuracy of the direction of arrival (DOA) estimation algorithm will greatly decrease during an application. To address this issue, in this paper, we propose an intelligent DOA estimation error calibration method based on transfer learning, which learns error knowledge from a small number of actual signal samples and improves the DOA estimation accuracy in the real application. We constructed a deep convolutional neural network (CNN)-based intelligent DOA estimation model to learn the mapping between the input signals and their azimuths. We generated a large number of ideal simulation signal samples to train the CNN model and used it as the pretrained model. Then, we fine-tuned the CNN model with a small number of actual signal samples collected in the actual environment. We demonstrate the effectiveness of the proposed method through simulation experiments. The experimental results indicate that the proposed method can effectively improve the accuracy of DOA estimation in the actual environment.
Intelligent Volume-Assured Pressure Support vs. Spontaneous/Timed Mode as a Weaning Strategy in COPD—Evaluation of a New Ventilation Strategy
Authors: Bhakta Pradipta , Mandal Mohanchandra , Mukherjee Prosenjit , O’Brien Brian , Esquinas Antonio M.
Published: July 2022

We thank Salama S et al [...]
Spatial Effects of Urban Transport on Air Pollution in Metropolitan Municipalities of Mexico
Authors: Avilés-Polanco Gerzaín , Almendarez-Hernández Marco Antonio , Beltrán-Morales Luis Felipe , Ortega-Rubio Alfredo
Published: July 2022

The objective of this work was to estimate the local effects and spatial spillover effects of the number of vehicles, use of urban public transport, and population density on nitrogen oxide emissions for 405 metropolitan municipalities in Mexico in 2016. To this end, a Spatial Durbin Model was estimated. We found positive direct effects of the number of vehicles and population density and negative direct effects of the use of urban public transport. The number of vehicles in circulation had negative spillover effects on the nitrogen oxide emissions of neighboring municipalities. These results indicate that the design of public policy programs aimed at reducing air pollution in Mexico should be based on coordination across metropolitan municipalities.
A GDM-GTWR-Coupled Model for Spatiotemporal Heterogeneity Quantification of CO2 Emissions: A Case of the Yangtze River Delta Urban Agglomeration from 2000 to 2017
Authors: Zhu Zhen , Yu Junyan , Luo Jinhui , Zhang Huiyuan , Wu Qilong , Chen Yuhua
Published: July 2022

CO2 emissions from fossil energy have caused global climate problems and threatened human survival. However, there are few studies on the spatiotemporal distribution and driving factors of carbon emissions. This paper takes the Yangtze River Delta (YRD) urban agglomeration as the research object and analyzes the spatiotemporal heterogeneity of carbon dioxide emissions and their driving factors from 2000 to 2017. First, a series of preprocessing, such as resample, interpolation, and image clipping, are conducted on the CO2 emission data and nighttime light remote sensing images. Second, the dynamic time wrapping (DTW) and hierarchical clustering algorithms were involved in manipulating the CO2 emission data. Consequently, the cities’ and CO2 emissions’ time series were classified into four categories and three stages separately. Finally, the geographical detector model (GDM) and geographical and temporal weighted regression (GTWR) are coupled to evaluate the spatiotemporal heterogeneity and quantify the driving factors. The results show the following: (1) The spatiotemporal distribution of CO2 emissions has spatial consistency from 2000 to 2017. High-emission areas are concentrated in economically developed areas such as Shanghai, Suzhou, and Wuxi. The results are consistent with previous research. (2) Regional aggregation is a revealed new trend. CO2 emissions in the target urban areas are gradually converging into economic center cities and diverse class cities, e.g., Shanghai and Ningbo. (3) In cities of different economic development levels, the driving factors of CO2 emissions are different. The secondary sector and urban infrastructure dominate in the early stages of developed cities. On top of that, the influence of the tertiary industry is more significant in the later development stages. According to the results, in the urban development process, humans should not only pursue the increase in speed but also pay attention to the negative impact of the economic development process on the ecological environment. Besides, since the spatiotemporal characteristics and dominant factors of urban carbon emissions are different in each stage of development, the formulation of carbon reduction policies should be associated with urban features.
Enumeration of the Additive Degree–Kirchhoff Index in the Random Polygonal Chains
Authors: Geng Xianya , Zhu Wanlin
Published: July 2022

The additive degree–Kirchhoff index is an important topological index. This paper we devote to establishing the explicit analytical expression for the simple formulae of the expected value of the additive degree–Kirchhoff index in a random polygon. Based on the result above, the additive degree–Kirchhoff indexes of all polygonal chains with extremal values and average values are obtained.
Nanomechanical, Structural and Electrochemical Investigation of Amorphous and Crystalline MoO3 Thin-Film Cathodes in Rechargeable Li-Ion Batteries
Authors: Methani Wissem , Pál Edit , Lipcsei Sándor , Ugi Dávid , Pászti Zoltán , Groma István , Jenei Péter , Dankházi Zoltán , Kun Robert
Published: July 2022

In this work, a comprehensive investigation of amorphous and crystalline modification of identical electrode active material as a thin-film electrode for a future all-solid-state Li-ion battery application is presented and discussed. Using the proposed micro-battery system, we aim to unravel the effect of the crystallinity of the positive electrode material on the intrinsic durability of all-solid-state thin-film Li-ion batteries during prolonged electrochemical cycling. We demonstrate the preparation, structural-, nanomechanical and electrochemical characteristics of molybdenum (VI) oxide (MoO3) thin-film cathodes based on their different crystallinity. The nanomechanical properties of the electrode layers were determined using nanoindentation along with acoustic emission studies. Based on the electrochemical test results, as-prepared thin films that did not go under any heat treatment showed the best performance and stability throughout cycling around 50 μAh initial capacity when cycled at C/2. This suits well their nanomechanical properties, which showed the highest hardness but also the highest flexibility in comparison with the heat-treated layers with lower hardness, high brittleness, and numerous cracks upon mechanical loads. According to our results, we state that amorphous-type electrode materials are more durable against electro-chemo-mechanical-aging related battery performance loss in all-solid-state Li-ion batteries compared to their crystalline counterparts.
Production of Fungal Quinones: Problems and Prospects
Authors: Christiansen Johan Vormsborg , Larsen Thomas Ostenfeld , Frisvad Jens Christian
Published: July 2022

Fungal quinones can be used for a variety of applications, such as pharmaceuticals, food colorants, textile dyes, and battery electrolytes. However, when producing quinones by fungal cultivation, many considerations arise regarding the feasibility of a production system, such as the quinone yield, purity, ease of extraction, and the co-production of mycotoxins. In this work, we display the initial screening of filamentous fungi for quinone production and evaluate their potential for future optimization. We investigated toluquinone (TQ) potentially produced by Penicillium cf. griseofulvum, terreic acid (TA) produced by Aspergillus parvulus and A. christenseniae, and anthraquinone (AQ) monomers and dimers produced by Talaromyces islandicus. The strains grew on various agar and/or liquid media and were analyzed by ultra-high-performance liquid chromatography–diode array detection–quadrupole time-of-flight mass spectrometry (UHPLC-DAD-QTOF MS). In the case of AQs, feature-based molecular networking (FBMN) was used for the identification of AQ analogs. TQ was not observed in the production strains. TA constituted one of the major chromatogram peaks and was secreted into the growth medium by A. parvulus. The AQs constituted many major chromatogram peaks in the mycelium extracts and endocrocin and citreorosein were observed extracellularly in small amounts.
Multifaceted Roles of the N6-Methyladenosine RNA Methyltransferase METTL3 in Cancer and Immune Microenvironment
Authors: Hu Chenxi , Liu Jiacheng , Li Yue , Jiang Wei , Ji Ding , Liu Wei , Ma Teng
Published: July 2022

As the most abundant internal mRNA modification in eukaryotic cells, N6-methyladenosine (m6A) has emerged as an important regulator of gene expression and has a profound impact on cancer initiation and progression. mRNA m6A modification is regulated by m6A methyltransferases, demethylases and reader proteins to fine tune gene expression at the post-transcriptional level. The most well-studied m6A methyltransferase, METTL3, plays critical roles in regulating gene expression and affecting the outcome of various cancers. In this review, we discuss the multifaceted roles of METTL3 in regulating specific molecular signaling pathways in different types of cancers and the recent progress on how METTL3 impacts the tumor immune microenvironment. Finally, we discuss future directions and the potential for therapeutic targeting of METTL3 in cancer treatment.
PGRMC1 Regulates Cellular Senescence via Modulating FOXO1 Expression in Decidualizing Endometrial Stromal Cells
Authors: Tsuru Atsuya , Yoshie Mikihiro , Kojima Junya , Yonekawa Ryo , Azumi Mana , Kusama Kazuya , Nishi Hirotaka , Tamura Kazuhiro
Published: July 2022

The appropriate differentiation of endometrial stromal cells (ESCs) into decidual cells is required for embryo implantation and subsequent placentation into humans. Decidualization is accompanied by the appearance of senescent-like cells. We recently reported the secretory phase-specific downregulation of endometrial progesterone receptor membrane component 1 (PGRMC1) and enhanced decidualization upon PGRMC1 knockdown and inhibition in cultured ESCs. However, it remains unknown whether PGRMC1 is involved in cellular senescence during decidualization. Here, we showed that the small interfering RNA (siRNA)-mediated knockdown of PGRMC1 and the inhibition of PGRMC1 by AG-205 increased the expression of the transcription factor forkhead box protein O1 (FOXO1) and the senescence-associated β-galactosidase activity in cAMP analog- and progesterone-treated ESCs. Furthermore, the knockdown of FOXO1 repressed the decidual senescence induced by siRNA-based PGRMC1 knockdown or AG-205 treatment. Taken together, the decreased PGRMC1 expression in ESCs may accelerate decidualization and cellular senescence via the upregulation of FOXO1 expression for appropriate endometrial remodeling and embryo implantation during the secretory phase.