bluuebunny/crossref_metadata_2025 huggingface dataset:
Contactless Fingerprint Recognition Using Deep Learning—A Systematic Review
Authors: Chowdhury A M Mahmud , Imtiaz Masudul Haider
Published: September 2022

Contactless fingerprint identification systems have been introduced to address the deficiencies of contact-based fingerprint systems. A number of studies have been reported regarding contactless fingerprint processing, including classical image processing, the machine-learning pipeline, and a number of deep-learning-based algorithms. The deep-learning-based methods were reported to have higher accuracies than their counterparts. This study was thus motivated to present a systematic review of these successes and the reported limitations. Three methods were researched for this review: (i) the finger photo capture method and corresponding image sensors, (ii) the classical preprocessing method to prepare a finger image for a recognition task, and (iii) the deep-learning approach for contactless fingerprint recognition. Eight scientific articles were identified that matched all inclusion and exclusion criteria. Based on inferences from this review, we have discussed how deep learning methods could benefit the field of biometrics and the potential gaps that deep-learning approaches need to address for real-world biometric applications.
Study on the Surface Interactions of Co(II) with Phospholipids from the Marine Environment
Authors: Bačinić Anđela , Vukosav Petra , Kero Ivana , Mlakar Marina
Published: September 2022

Natural phospholipid (PL)n extract from cultured green algae Dunaliela tertiolecta was used as the main component of cell membranes for studies on the interaction with trace metal Co(II). The phospholipids of the membranes were extracted from other biological components using TiO2-µSPE cartridges selective for the phosphate group according to a completely new protocol. The interaction of Co(II) with natural and standard phospholipids, phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidylglycerol (PG) are registered only in the presence of the additional chelating ligand 1,10-Phenathroline (Phen). 1,10-Phenathroline, as a model of humic substances in the marine environment, formed a neutral complex with Co(II) by the substitution of water molecules of central metal ions. The interaction of hydrophobic mixed-ligand complexes with phospholipids was enabled by the substitution of the remaining water molecules in the coordination shell of Co(II), which was registered by voltammetric measurements. The Co(II)-Phen-PL complex is reduced from the adsorbed state at −1.65 V by the transfer of two electrons, followed by its irreversible dissociation and desorption, indicating an EC mechanism. The interaction between the mixed-ligand complexes Co(II)-Phen-lipids was confirmed by atomic force microscopy (AFM). AFM images of PL, PL with Phen mixture and PL, Phen with Co(II) showed different 3D structures on the mica surface, indicating changes caused by the interaction between cobalt(II), 1,10-Phenanthroline and phospholipids.
A Cooperative Hunting Method for Multi-AUV Swarm in Underwater Weak Information Environment with Obstacles
Authors: Zhao Zhenyi , Hu Qiao , Feng Haobo , Feng Xinglong , Su Wenbin
Published: September 2022

Cooperative hunting is a typical task that reflects the intelligence level of a swarm. For the complex underwater weak information environment with obstacles, a problem description of the multi-autonomous underwater vehicle (AUV) cooperative hunting task is given, considering the influencing factors, including underwater obstacles, AUV sensing interaction range, and target escape strategy. A hybrid adaptive preference method based on improved artificial potential fields (HAP-IAPF) is proposed. Then the strategies of obstacle avoidance and hunting are designed separately according to the task requirements. The adaptive weight control unit is used to adjust the preference strategy. The multi-AUV cooperative hunting in dynamic obstacle underwater environments under weakly connected conditions are achieved. In order to prove the effectiveness of the proposed algorithm, simulation results compared with the traditional artificial potential field method and the optimized artificial potential field method are given in this paper. The results show that the proposed method is robust and effective in different environments.
Spot Charter Rate Forecast for Liquefied Natural Gas Carriers
Authors: Lyridis Dimitrios V.
Published: September 2022

Recent maritime legislation demands the transformation of the transportation sector to greener and more energy efficient. Liquified natural gas (LNG) seems a promising alternative fuel solution that could replace the conventional fuel sources. Various studies have focused on the prediction of the LNG price; however, no previous work has been carried out on the forecast of the spot charter rate of LNG carrier ships, an important factor for the maritime industries and companies when it comes to decision-making. Therefore, this study is focused on the development of a machine learning pipeline to address the aforementioned problem by: (i) forming a dataset with variables relevant to LNG; (ii) identifying the variables that impact the freight price of LNG carrier; (iii) developing and evaluating regression models for short and mid-term forecast. The results showed that the general regression neural network presented a stable overall performance for forecasting periods of 2, 4 and 6 months ahead.
The C2H2 Zinc Finger Protein MaNCP1 Contributes to Conidiation through Governing the Nitrate Assimilation Pathway in the Entomopathogenic Fungus Metarhizium acridum
Authors: Li Chaochuang , Xia Yuxian , Jin Kai
Published: September 2022

Zinc finger proteins are an important class of multifunctional regulators. Here, the roles of a C2H2 zinc finger protein MaNCP1 (Metarhizium acridum nitrate-related conidiation pattern shift regulatory factor 1) in nitrogen utilization and conidiation were explored in the entomopathogenic fungus M. acridum. The results showed that MaNCP1-disruption mutant (ΔMaNCP1) impaired the ability to utilize nitrate, ammonium and glutamine and reduced the expression of nitrate assimilation-related genes, suggesting that MaNCP1 was involved in governing nitrogen utilization. In addition, the conidial yield of the ΔMaNCP1 strain, cultured on the microcycle conidiation medium (SYA), was significantly decreased, which could be restored or even enhanced than that of the WT strain through increasing the nitrate content in SYA medium. Further study showed that MaAreA, a core regulator in the nitrogen catabolism repression (NCR) pathway, was a downstream target gene of MaNCP1. Screening the differential expression genes between WT and ΔMaNCP1 strains revealed that the conidial yield of M. acridum regulated by nitrate might be related to NCR pathway on SYA medium. It could be concluded that MaNCP1 contributes to the nitrate assimilation and conidiation, which will provide further insights into the relationship between the nitrogen utilization and conidiation in fungi.
Effectiveness of Artificial Intelligence Methods in Personalized Aggression Risk Prediction within Inpatient Psychiatric Treatment Settings—A Systematic Review
Authors: Tay Jing Ling , Li Ziqiang , Sim Kang
Published: September 2022

Aggression risk assessments are vital to prevent injuries and morbidities amongst patients and staff in psychiatric settings. More recent studies have harnessed artificial intelligence (AI) methods such as machine learning algorithms to determine factors associated with aggression in psychiatric treatment settings. In this review, using Cooper’s five-stage review framework, we aimed to evaluate the: (1) predictive accuracy, and (2) clinical variables associated with AI-based aggression risk prediction amongst psychiatric inpatients. Databases including PubMed, Cochrane, Scopus, PsycINFO, CINAHL were searched for relevant articles until April 2022. The eight included studies were independently evaluated using critical appraisal tools for systematic review developed by Joanna Briggs Institute. Most of the studies (87.5%) examined health records in predicting aggression and reported acceptable to excellent accuracy with specific machine learning algorithms employed (area under curve range 0.75–0.87). No particular machine learning algorithm outperformed the others consistently across studies (area under curve range 0.61–0.87). Relevant factors identified with aggression related to demographic and social profile, past aggression, forensic history, other psychiatric history, psychopathology, challenging behaviors and management domains. The limited extant studies have highlighted a potential role for the use of AI methods to clarify factors associated with aggression in psychiatric inpatient treatment settings.
Deep Learning on Basal Cell Carcinoma In Vivo Reflectance Confocal Microscopy Data
Authors: Shavlokhova Veronika , Vollmer Michael , Gholam Patrick , Saravi Babak , Vollmer Andreas , Hoffmann Jürgen , Engel Michael , Freudlsperger Christian
Published: September 2022

Background: Extended skin malignancies of the head and neck region are among the most common cancer types and are associated with numerous diagnostic and therapeutical problems. The radical resection of skin cancer in the facial area often leads to severe functional and aesthetic impairment, and precise margin assessments can avoid the extensive safety margins. On the other hand, the complete removal of the cancer is essential to minimize the risk of recurrence. Reliable intraoperative assessments of the wound margins could overcome this discrepancy between minimal invasiveness and safety distance in the head and neck region. With the help of reflectance confocal laser microscopy (RCM), cells can be visualized in high resolution intraoperatively. The combination with deep learning and automated algorithms allows an investigator independent and objective interpretation of specific confocal imaging data. Therefore, we aimed to apply a deep learning algorithm to detect malignant areas in images obtained via in vivo confocal microscopy. We investigated basal cell carcinoma (BCC), as one of the most common entities with well-described in vivo RCM diagnostic criteria, within a preliminary feasibility study. Patients and Methods: We included 62 patients with histologically confirmed BCC in the head and neck region. All patients underwent in vivo confocal laser microscope scanning. Approximately 382 images with BCC structures could be obtained, annotated, and proceeded for further deep learning model training. Results: A sensitivity of 46% and a specificity of 85% in detecting BCC regions could be achieved using a convolutional neural network model (“MobileNet”). Conclusion: The preliminary results reveal the potential and limitations of the automated detection of BCC with in vivo RCM. Further studies with a larger number of cases are required to obtain better predictability.
Correction: Pérez-Calderon et al. Tourism Business in Spanish National Parks: A Multidimensional Perspective of Sustainable Tourism. Land 2022, 11, 190
Authors: Pérez-Calderón Esteban , Miguel-Barrado Vanessa , Sánchez-Cubo Francisco
Published: September 2022

In the original publication [...]
An Evaluation of the National Program of Systematic Land Registration in Romania Using the Fit for Purpose Spatial Framework Principles
Authors: Păunescu Vlad , Kohli Divyani , Iliescu Alexandru-Iulian , Nap Mircea-Emil , Șuba Elemer-Emanuel , Sălăgean Tudor
Published: September 2022

The National Program of Systematic Land Registration aims to register all land property in Romania by 2023. The goal has proven difficult to achieve, as by June 2022 only 4% of the localities in the country were completed. The aim of this research is to find the similarities and differences between the fit for purpose principles of land administration for the spatial framework and the practices in The Romanian National Program of Systematic Land Registration. This is the first study that analyzes the Romanian land registration program through the lens of the fit for purpose concept. The research shows that there are similarities with the fit for purpose spatial framework principles for the use of aerial images and the participatory nature of the process. However, The National Program of Systematic Land Registration uses almost exclusively fixed boundaries and does not have different standards of accuracy and procedures for incremental improvement. Registering the parcels earlier in the process, flexibility for accuracy, and technical standards and regulations for incremental improvement of the system can speed up the registration in a fit for purpose manner.
Response of Permafrost Thermal State to Global Climatic Change in Urbanised Landscapes, Yakutsk, Russia
Authors: Kunitsky Viktor V. , Syromyatnikov Igor I. , Litovko Andrey V.
Published: September 2022

A study was undertaken to investigate the structure and condition of urban permafrost in the city of Yakutsk. The response of permafrost to recent climate change was assessed for a Shergin Shaft site in a cryogenic landscape. The results indicate that the thickness of the active layer which consists of anthropogenic soils experienced no change during the second half of the 20th century and the early 21st century. However, the thermal state of the underlying alluvial sediments has changed significantly in response to the warming of the climate. The permafrost temperatures at a depth of 10 m increased by about 3 °C between 1934 and 2015.
Malachite Green Dye Decoloration over Au/TiO2-Nanotubes Photocatalyst under Simulate Visible-Light Irradiation
Authors: Hernández-Cruz María Guadalupe , Solís-Casados Dora Alicia , Toledo-Antonio José Antonio , Vargas-García Jorge Roberto , Estrada-Flores Miriam , Ángeles-Chávez Carlos , Cortés-Jácome María Antonia , Encarnación-Gómez Cecilia
Published: September 2022

Au nanoparticles were supported on TiO2 nanotubes by a novel vapor phase impregnation approach (VPI) using gold dimethyl-acetylacetonate as a precursor. This study aimed to evaluate the capacity of these materials in the photodecoloration of malachite green dye, with the vision to correlate the chemical, structural, morphological, and optical properties with its photocatalytic performance. The photocatalysts were characterized by X-ray diffraction, Raman spectroscopy, X-ray photoelectronic spectroscopy (XPS), electronic microscopy (HAADF-STEM and HRTEM), and UV–vis spectroscopy. The techniques mentioned above made it possible to detect the presence of small gold nanoparticles (around 3.1 nm), with a high apparent dispersion even at high metal loading for all analyzed systems. According to the XPS results, the Au nanoparticles remain reduced (Au°), and they have a high electronic interaction with TiO2, which eventually originates an electronic exchange between them and consequently a decrease in the band gap energy. In addition, the surface plasmonic resonance observed through UV–vis spectroscopy of the Au nanoparticles are factors that can be related to the high decoloration observed in these photocatalysts, specifically in the 15 wt% Au material, which achieves maximum photodecoloration of malachite green dye at 93%.
Seismic Performance of Reinforced Concrete Columns Retrofitted with Hybrid Concrete Jackets Subjected to Combined Loadings
Authors: Kim Min Sook , Lee Young Hak
Published: September 2022

In the existing reinforced concrete columns where they are insufficient seismic details, critical failure mode such as shear failure can be observed under seismic loads. One strategy for the retrofitting of existing concrete columns is to use concrete jacketing. Concrete jacketing consists of a new concrete layer with longitudinal and transverse reinforcements, and can improve seismic resistance capacity. In this paper, a detail of concrete jacket that can be expected for easy construction and improved adhesion performance of longitudinal and transverse reinforcement was proposed. Additionally, a combined cyclic loading test was conducted to consider the seismic load with multiaxial characteristics. The concrete jacket details utilize three components: Steel Grid Reinforcement (SGR), Steel Wire Mesh (SWM), and Steel Fiber Non-Shrinkage Mortar (SFNM). One RC column with non-seismic details and two jacketed RC columns were fabricated to demonstrate the construction efficiencies and structural capacities of the jacketed columns. Two details of jacketed section were considered as variables. It was observed that the specimens retrofitted with concrete jacket resisted torsional load more than the un-retrofitted specimen in terms of crack and failure mode. The experimental results showed that the maximum load of retrofitted specimens was increased by more than 8 times compared to the un-retrofitted specimen, regardless of the jacket details. Newly designed concrete jacket effectively increased the strength. Compared with the un-retrofitted column, the columns retrofitted with the proposed details achieved significant increase in initial stiffness and energy dissipation.
The Influence of Freeze–Thaw Cycles and Corrosion on Reinforced Concrete and the Relationship between the Evolutions of the Microstructure and Mechanical Properties
Authors: Zhang Shuhua , Tian Bin , Chen Bofu , Lu Xiaochun , Xiong Bobo , Shuang Ning
Published: September 2022

Freeze–thaw cycles (FTCs) and steel bar corrosion (SBC) are the most common service conditions of hydraulic concrete and have significant impacts on its durability. Using pullout and microscopic tests of different FTC and SBC rates, we selected the mass loss rate, ultrasonic velocity, bond strength and bond slip in order to describe the changes in the macro-properties, and also selected the porosity and pore size distribution as micro-parameters in order to explore the influence of FTCs and SBC on the mechanical properties of hydraulic concrete. The results showed that the bond strength decreased as the FTCs increased due to the microstructure damage caused by FTC and SBC, which affects the mechanical properties. A corrosion rate of ≤3% offset the damage caused by 50 FTCs. FTCs and SBC resulted in superimposed damage effects on the concrete. In addition, we established a bond strength damage model based on the joint FTCs and SBC and quantitatively described the degradation law of the macro-mechanical properties. The analysis shows that the influence of FTCs on the bond strength was greater than that of the SBC. These research results can provide a reference and experimental support for the frost-resistant design and durability prediction of hydraulic concrete structures in cold environments.
Reaction Model and Mechanism of Preparing (Al2O3 + C) Precursor for Carbothermal Synthesis of AlN by a Modified Low Temperature Combustion Synthesis Method
Authors: Chu Aimin , Zhang Longqing , Ud-din Rafi , Zhao Yuping
Published: September 2022

The preparation of a homogeneous mixture of (Al2O3 + C) precursor is the key step for the successful synthesis of AlN powders by the carbothermal reduction and nitridation method. In the present work, the homogeneous (Al2O3 + C) precursor prepared by a modified low temperature combustion synthesis (MLCS) method by using aluminum nitrate, glucose, and urea as materials exhibited high reaction activity. Furthermore, in order to absolutely control the MLCS process and continuously improve the properties of (Al2O3 + C) precursor, the reaction model of preparing precursors from various molar ratios of urea to aluminum nitrate (U/Al) was investigated by carrying out thermodynamic calculation and by performing experiments in the present work. The whole process was found to involve various phenomena. First, the type and amount of various generated nitrogen-containing gases (N2, NO, N2O, N2O3, N2O4, and NO2) vary with the change of U/Al during combustion process. Second, under the present experimental condition of ignition temperature, the decomposition reaction of aluminum nitrate is more prone to occur than the combustion reaction of urea. Third, the real reaction system with U/Al = 2.5 reaches the highest combustion temperature which is well consistent with the propellant chemical theory. The occurrence of above phenomena was discussed in detail. Moreover, the reaction mechanism of synthesizing precursor from U/Al = 1 with high reaction activity was investigated by using various techniques such as FTIR, XRD, and DTA.
Optimization Based on Toughness and Splitting Tensile Strength of Steel-Fiber-Reinforced Concrete Incorporating Silica Fume Using Response Surface Method
Authors: Köksal Fuat , Beycioğlu Ahmet , Dobiszewska Magdalena
Published: September 2022

The greatest weakness of concrete as a construction material is its brittleness and low fracture energy absorption capacity until failure occurs. In order to improve concrete strength and durability, silica fume SF is introduced into the mixture, which at the same time leads to an increase in the brittleness of concrete. To improve the ductility and toughness of concrete, short steel fibers have been incorporated into concrete. Steel fibers and silica fume are jointly preferred for concrete design in order to obtain concrete with high strength and ductility. It is well-known that silica fume content and fiber properties, such as aspect ratio and volume ratio, directly affect the properties of SFRCs. The mixture design of steel-fiber-reinforced concrete (SFRC) with SF addition is a very important issue in terms of economy and performance. In this study, an experimental design was used to study the toughness and splitting tensile strength of SFRC with the response surface method (RSM). The models established by the RSM were used to optimize the design of SFRC in terms of the usage of optimal silica fume content, and optimal steel fiber volume and aspect ratio. Optimum silica fume content and fiber volume ratio values were determined using the D-optimal design method so that the steel fiber volume ratio was at the minimum and the bending toughness and splitting tensile strength were at the maximum. The amount of silica fume used as a cement replacement, aspect ratio, and volume fraction of steel fiber were chosen as independent variables in the experiment. Experimentally obtained mechanical properties of SFRC such as compression, bending, splitting, modulus of elasticity, toughness, and the toughness index were the dependent variables. A good correlation was observed between the dependent and independent variables included in the model. As a result of the optimization, optimum steel fiber volume was determined as 0.70% and silica fume content was determined as 15% for both aspect ratios.
Femtosecond Laser Modification of Silica Optical Waveguides for Potential Bragg Gratings Sensing
Authors: Chen Jian , Feng Ji-Jun , Liu Hai-Peng , Chen Wen-Bin , Guo Jia-Hao , Liao Yang , Shen Jie , Li Xue-Feng , Huang Hui-Liang , Zhang Da-Wei
Published: September 2022

The optimum femtosecond laser direct writing of Bragg gratings on silica optical waveguides has been investigated. The silica waveguide has a 6.5 × 6.5 µm2 cross-sectional profile with a 20-µm-thick silicon dioxide cladding layer. Compared with conventional grating inscribed on fiber platforms, the silica planar waveguide circuit can realize a stable performance as well as a high-efficiency coupling with the fiber. A thin waveguide cladding layer also facilitates laser focusing with an improved spherical aberration. Different from the circular fiber core matching with the Gaussian beam profile, a 1030-nm, 400-fs, and 190-nJ laser is optimized to focus on the top surface of the square silica waveguide, and the 3rd-order Bragg gratings are inscribed successfully. A 1.5-mm long uniform Bragg gratings structure with a reflectivity of 90% at a 1548.36-nm wavelength can be obtained. Cascaded Bragg gratings with different periods are also inscribed in the planar waveguide. Different reflection wavelengths can be realized, which shows great potential for wavelength multiplexing-related applications such as optical communications or sensing.
Concrete Containing Waste Glass as an Environmentally Friendly Aggregate: A Review on Fresh and Mechanical Characteristics
Authors: Qaidi Shaker , Najm Hadee Mohammed , Abed Suhad M. , Özkılıç Yasin Onuralp , Al Dughaishi Husam , Alosta Moad , Sabri Mohanad Muayad Sabri , Alkhatib Fadi , Milad Abdalrhman
Published: September 2022

The safe disposal of an enormous amount of waste glass (WG) in several countries has become a severe environmental issue. In contrast, concrete production consumes a large amount of natural resources and contributes to environmental greenhouse gas emissions. It is widely known that many kinds of waste may be utilized rather than raw materials in the field of construction materials. However, for the wide use of waste in building construction, it is necessary to ensure that the characteristics of the resulting building materials are appropriate. Recycled glass waste is one of the most attractive waste materials that can be used to create sustainable concrete compounds. Therefore, researchers focus on the production of concrete and cement mortar by utilizing waste glass as an aggregate or as a pozzolanic material. In this article, the literature discussing the use of recycled glass waste in concrete as a partial or complete replacement for aggregates has been reviewed by focusing on the effect of recycled glass waste on the fresh and mechanical properties of concrete.
Graphene: A Path-Breaking Discovery for Energy Storage and Sustainability
Authors: Goyal Deepam , Dang Rajeev Kumar , Goyal Tarun , Saxena Kuldeep K. , Mohammed Kahtan A. , Dixit Saurav
Published: September 2022

The global energy situation requires the efficient use of resources and the development of new materials and processes for meeting current energy demand. Traditional materials have been explored to large extent for use in energy saving and storage devices. Graphene, being a path-breaking discovery of the present era, has become one of the most-researched materials due to its fascinating properties, such as high tensile strength, half-integer quantum Hall effect and excellent electrical/thermal conductivity. This paper presents an in-depth review on the exploration of deploying diverse derivatives and morphologies of graphene in various energy-saving and environmentally friendly applications. Use of graphene in lubricants has resulted in improvements to anti-wear characteristics and reduced frictional losses. This comprehensive survey facilitates the researchers in selecting the appropriate graphene derivative(s) and their compatibility with various materials to fabricate high-performance composites for usage in solar cells, fuel cells, supercapacitor applications, rechargeable batteries and automotive sectors.
Optimisation of Solidification Structure and Properties of Hypoeutectic Chromium Cast Iron
Authors: Siekaniec Dorota , Kopyciński Dariusz , Tyrała Edward , Guzik Edward , Szczęsny Andrzej
Published: September 2022

This paper presents a comprehensive approach to optimising the structure and properties of chromium cast iron that is intended for use in the production of castings that operate under abrasive-wear conditions. In the study, chromium cast iron was inoculated to reduce the grain size in the solidification structure. The finer-grained structure of the casting has a positive effect on its mechanical properties. A number of inoculants have been used that allow the elimination of many types of casting defects: hot cracks and porosities that often occur during the production of chromium cast iron castings. Another advantage of the developed inoculation procedure is the resulting increase in the toughness of chromium cast iron. It should be emphasised that this cast iron does not have a high impact strength in its as-cast condition due to the formation of chromium carbides in the structure. This work also proposes a specially designed heat treatment for inoculated cast iron. The parameters of the applied heat treatment were determined on the basis of dilatometric tests. The visible deviation on a dilatogram at a temperature of about 600 °C is the result of a partial martensitic transformation in the area of grain boundaries. Therefore, the increase in abrasion resistance chromium cast iron is mainly due to the appearance of martensite. The microstructure of the investigated cast iron is particularly desirable in the case of alloys that work with lubrication. The microcavities that are formed by the abrasion of the softer phase constitute natural grease, which reduces abrasive wear. Under the influence of heat treatment, only a part of austenite located near the carbides is destabilized and transformed into martensite. Therefore, this phase of composition formation provided much greater resistance to abrasive wear and hardness.
NiCrBSi Coatings Fabricated on 45 Steel Using Large Spot Laser Cladding
Authors: Zhao Longjie , Yu Huijun , Wang Yanxiang , Zhao Zhihuan , Song Weihai , Chen Chuanzhong
Published: September 2022

Ni35 coatings were fabricated on 45 steel using a CO2 laser at various parameters. A relatively large spot (10 mm diameter) was adopted, which was beneficial to the coating quality and the cladding efficiency. The cross-sectional geometry, phase constituent, and microstructure of the coatings were investigated. With a lower specific energy, coating height increased, while coating width, melted depth, dilution rate, width to height ratio and contact angle decreased. Ni35 coating primarily consisted of γ-Ni, FeNi3, Ni3B, Cr23C6, and Cr5B3. Dendrites with flower-like, fishbone-like, pearl-like, and column-like morphologies were observed. The fraction of flower-like dendrites increased gradually with the decrease in scanning velocity due to the dendrite growth direction evolution. With the decrease in scanning velocity, the microstructure of the heat-affected zone transformed from martensite to martensite + sorbite and finally sorbite. The maximum microhardness of the Ni35 coating reached 451.8 HV0.2, which was about double that of the substrate (220 HV0.2).
The Microstructure Transformations and Wear Properties of Nanostructured Bainite Steel with Different Si Content
Authors: Fu Lihua , Zhou Meng , Wang Yanlin , Gao Yuanan , Zhang Yongzhen , Du Sanming , Zhang Yi , Mao Yanshan
Published: September 2022

Nanostructured bainite (NB) bearing steel has excellent strength and ductility combinations, which can improve the fatigue life and wear resistance of bearing steel in harsh conditions. However, the phase transformations and the correlation between the microstructure and wear properties of NB bearing steel are still unclear. In this study, bearing steels with different Si contents (GCr15SiMo and GCr15Si1Mo) were prepared to have nano-bainitic structures, and their microstructure transformations and wear mechanisms were investigated. The results show that the Si element can inhibit the precipitation of carbides and can then promote the block-like retained austenite formation and refine the bainitic ferrite lamellar structure. The impact energy of GCr15Si1Mo is larger than that of GCr15SiMo because the nanostructured bainite and retained austenite are the main toughness phase in these steels. The wear results indicate that the steels which possess appropriate strength and toughness are helpful for improving wear resistance properties. Finally, the wear resistance performance of the GCr15Si1Mo austempered at 210 °C and GCr15SiMo austempered at 230 °C was good in this work.
Analysis and Mitigation of AC Losses in High Performance Propulsion Motors
Authors: Hebala Ahmed , Nuzzo Stefano , Connor Peter H. , Volpe Giuseppe , Gerada Chris , Galea Michael
Published: September 2022

In this paper, the AC copper losses in classical random windings are investigated and mitigated using several techniques across a range of permanent magnet synchronous motor designs. At high operating frequencies, AC copper losses can represent a substantial share of the total loss in electrical machines, thus, reducing the machine’s overall performance, and increasing the thermal loading. Recently, different approaches for modelling AC copper losses have been proposed. This paper utilises simulation software to quantify the expected AC losses in six different propulsion motor designs. The motor designs are then modified to reduce the AC winding losses through the implementation of five different methods. Using two-dimensional finite element analysis, the magnetisation direction, magnet to airgap ratio, copper stranding, magnetic wedges and the motor slot openings are modified to reduce AC losses. The paper considers distributed, fractional, slot and concentrated windings, and the results show promising reductions across these different winding configurations.
Squeeze Film Damper Modeling: A Comprehensive Approach
Authors: Gheller Edoardo , Chatterton Steven , Vania Andrea , Pennacchi Paolo
Published: September 2022

Squeeze film dampers (SFDs) are components used in many industrial applications, ranging from turbochargers to jet engines. SFDs are applied when the vibration levels or some instability threatens the safe operation of the machine. However, modeling these components is difficult and somewhat counterintuitive due to the multiple complex phenomena involved. After a thorough investigation of the state of the art, the most relevant phenomena for the characterization of the SFDs are highlighted. Among them, oil film cavitation, air ingestion, and inertia are investigated and modeled. The paper then introduces a numerical model based on the Reynolds equation, discretized with the finite difference method. Different boundary conditions for oil feeding and discharging are implemented and investigated. The model is validated by means of experimental results available in the literature, whereas different designs and configurations of the feeding and sealing system are considered. Eventually, an example of the application of a SFD to a compressor rotor for the reduction of vibration and correction of the instability is proposed. The paper provides an insight regarding the critical aspects of modeling SFDs, underscoring the limits of the numerical model, and suggesting where to further develop and improve the modeling.
Adaptive Neural-PID Visual Servoing Tracking Control via Extreme Learning Machine
Authors: Luo Junqi , Zhu Liucun , Wu Ning , Chen Mingyou , Liu Daopeng , Zhang Zhenyu , Liu Jiyuan
Published: September 2022

The vision-guided robot is intensively embedded in modern industry, but it is still a challenge to track moving objects in real time accurately. In this paper, a hybrid adaptive control scheme combined with an Extreme Learning Machine (ELM) and proportional–integral–derivative (PID) is proposed for dynamic visual tracking of the manipulator. The scheme extracts line features on the image plane based on a laser-camera system and determines an optimal control input to guide the robot, so that the image features are aligned with their desired positions. The observation and state–space equations are first determined by analyzing the motion features of the camera and the object. The system is then represented as an autoregressive moving average with extra input (ARMAX) and a valid estimation model. The adaptive predictor estimates online the relevant 3D parameters between the camera and the object, which are subsequently used to calculate the system sensitivity of the neural network. The ELM–PID controller is designed for adaptive adjustment of control parameters, and the scheme was validated on a physical robot platform. The experimental results showed that the proposed method’s vision-tracking control displayed superior performance to pure P and PID controllers.
Geometric Studies on Mittag-Leffler Type Function Involving a New Integrodifferential Operator
Authors: Ghanim F. , Al-Janaby Hiba F. , Al-Momani Marwan , Batiha Belal
Published: September 2022

The generalized exponential function in a complex domain is called the Mittag-Leffler function (MLF). The implementations of MLF are significant in diverse areas of science. Over the past few decades, MLF and its analysis with generalizations have become an increasingly rich research area in mathematics and its allied fields. In the geometric theory of meromorphic functions, the main contribution to this discipline of study is to enrich areas of operator theory on complex punctured domains and differential complex inequalities, namely, subordination theory. This effort presents integrodifferential operator of meromorphic functions in the punctured unit disk. It is formulated by combining the differential operator and the integral operator correlating with the extended generalized Mittag-Leffler function. Furthermore, some interesting geometric features in terms of the subordination principle are investigated.
Path-Wise Attention Memory Network for Visual Question Answering
Authors: Xiang Yingxin , Zhang Chengyuan , Han Zhichao , Yu Hao , Li Jiaye , Zhu Lei
Published: September 2022

Visual question answering (VQA) is regarded as a multi-modal fine-grained feature fusion task, which requires the construction of multi-level and omnidirectional relations between nodes. One main solution is the composite attention model which is composed of co-attention (CA) and self-attention(SA). However, the existing composite models only consider the stack of single attention blocks, lack of path-wise historical memory, and overall adjustments. We propose a path attention memory network (PAM) to construct a more robust composite attention model. After each single-hop attention block (SA or CA), the importance of the cumulative nodes is used to calibrate the signal strength of nodes’ features. Four memoried single-hop attention matrices are used to obtain the path-wise co-attention matrix of path-wise attention (PA); therefore, the PA block is capable of synthesizing and strengthening the learning effect on the whole path. Moreover, we use guard gates of the target modal to check the source modal values in CA and conditioning gates of another modal to guide the query and key of the current modal in SA. The proposed PAM is beneficial to construct a robust multi-hop neighborhood relationship between visual and language and achieves excellent performance on both VQA2.0 and VQA-CP V2 datasets.
Solving Hydrodynamic Problems Based on a Modified Upwind Leapfrog Scheme in Areas with Complex Geometry
Authors: Sukhinov Alexander , Chistyakov Alexander , Kuznetsova Inna , Belova Yulia , Rahimbaeva Elena
Published: September 2022

In recent years, the number of adverse and dangerous natural and anthropogenic phenomena has increased in coastal zones around the world. The development of mathematical modeling methods allows us to increase the accuracy of the study of hydrodynamic processes and the prediction of extreme events. This article discusses the application of the modified Upwind Leapfrog scheme to the numerical solution of hydrodynamics and convection–diffusion problems. To improve the accuracy of solving the tasks in the field of complex shapes, the method of filling cells is used. Numerical experiments have been carried out to simulate the flow of a viscous liquid and the transfer of substances using a linear combination of Upwind and Standard Leapfrog difference schemes. It is shown that the application of the methods proposed in the article allows us to reduce the approximation error in comparison with standard schemes in the case of large grid numbers of Péclet and to increase the smoothness of the solution accuracy at the boundary. The soil dumping and suspended matter propagation problems are solved using the developed schemes.
The Discrete Carnivorous Plant Algorithm with Similarity Elimination Applied to the Traveling Salesman Problem
Authors: Zhang Pan-Li , Sun Xiao-Bo , Wang Ji-Quan , Song Hao-Hao , Bei Jin-Ling , Zhang Hong-Yu
Published: September 2022

The traveling salesman problem (TSP) widely exists in real-life practical applications; it is a topic that is under investigation and presents unsolved challenges. The existing solutions still have some challenges in convergence speed, iteration time, and avoiding local optimization. In this work, a new method is introduced, called the discrete carnivorous plant algorithm (DCPA) with similarity elimination to tackle the TSP. In this approach, we use a combination of six steps: first, the algorithm redefines subtraction, multiplication, and addition operations, which aims to ensure that it can switch from continuous space to discrete space without losing information; second, a simple sorting grouping method is proposed to reduce the chance of being trapped in a local optimum; third, the similarity-eliminating operation is added, which helps to maintain population diversity; fourth, an adaptive attraction probability is proposed to balance exploration and the exploitation ability; fifth, an iterative local search (ILS) strategy is employed, which is beneficial to increase the searching precision; finally, to evaluate its performance, DCPA is compared with nine algorithms. The results demonstrate that DCPA is significantly better in terms of accuracy, average optimal solution error, and iteration time.
New Hermite–Hadamard Inequalities for Convex Fuzzy-Number-Valued Mappings via Fuzzy Riemann Integrals
Authors: Khan Muhammad , Santos-García Gustavo , Noor Muhammad , Soliman Mohamed
Published: September 2022

This study uses fuzzy order relations to examine Hermite–Hadamard inequalities (
Regression Analysis of Multivariate Interval-Censored Failure Time Data under Transformation Model with Informative Censoring
Authors: Yu Mengzhu , Du Mingyue
Published: September 2022

We consider a regression analysis of multivariate interval-censored failure time data where the censoring may be informative. To address this, an approximated maximum likelihood estimation approach is proposed under a general class of semiparametric transformation models, and in the method, the frailty approach is employed to characterize the informative interval censoring. For the implementation of the proposed method, we develop a novel EM algorithm and show that the resulting estimators of the regression parameters are consistent and asymptotically normal. To evaluate the empirical performance of the proposed estimation procedure, we conduct a simulation study, and the results indicate that it performs well for the situations considered. In addition, we apply the proposed approach to a set of real data arising from an AIDS study.
Characterization of Blast Wave Parameters in the Detonation Locus and Near Field for Shaped Charges
Authors: Mejía Nestor , Mejía Rodrigo , Toulkeridis Theofilos
Published: September 2022

Understanding physical phenomena such as blast shock waves produced by controlled explosions are relevant for issues appearing in the fields of military and civilian activities. The current study analyzes detonations of cylindrical and 3D cone-shaped charges through experimental trials and numerical simulations. In order to accomplish such goals, the work is divided into three sections, which include (a) numerical studies on spherical charges to define an accurate model; (b) numerical and experimental studies to assess the influence of cylindrical and 3D cone-shaped charges on incident peak pressure and the shape of shock wave propagation; and (c) numerical studies to define the magnitude of incident peak pressure as a function of orientation, L/D aspect ratio and scaled distance. Validation studies proved that the applied model was reasonably accurate. Furthermore, relevant findings included the observation that when the L/D aspect ratio decreases, more release energy is concentrated in the axial direction for a 3D cone-shaped charge, while as the aspect ratio increases, more release energy is concentrated in the radial direction for a cylindrical-shaped charge. Additionally, the blast shock wave produced a great quantity of energy for the explosive charge with the largest surface. Finally, the orientation has less influence than the L/D aspect ratio on the incident pressure contours. Therefore, cylindrical charges have the potential of inflicting great damage when used as confined charges, and 3D charges are able to cut solid materials in case of a direct contact.
Hybrid Fake Information Containing Strategy Exploiting Multi-Dimensions Data in Online Community
Authors: Cao Huiru , Li Xiaomin , Lin Yanfeng , Lian Songyao
Published: September 2022

It is well-established that, in the past few years, internet users have rapidly increased. Meanwhile, various types of fake information (such as fake news or rumors) have been flooding social media platforms or online communities. The effective containing or controlling of fake news or rumor has drawn wide attention from areas such as academia to social media platforms. For that reason, numerous studies have focused on this subject from different perspectives, such as employing complex networks and spreading models. However, in the real online community, misinformation usually spreads quickly to thousands of users within minutes. Conventional studies are too theoretical or complicated to be applied to practical applications, and show a lack of fast responsiveness and poor containing effects. Therefore, in this work, a hybrid strategy exploiting the multi-dimensional data of users and content was proposed for the fast containing of fake information in the online community. The strategy is mainly composed of three steps: the fast detection of fake information by continuously updating the content comparison dataset according to the specific hot topic and the fake contents; creating spreading force models and user divisions via historical data, and limiting the propagation of fake information based on the content and user division. Finally, an experiment was set up online with BBS (Bulletin Board System), and the acquired results were analyzed by comparison with other methods in different metrics. From the extracted results, it has been demonstrated that the proposed solution clearly outperforms traditional methods.
Efficiency-Enhancing Horizontal Mergers in Spatial Competition with Network Externalities
Authors: Bao Lei , Yu Wenshi
Published: September 2022

We study horizontal mergers in a network products market with a three-firm model of spatial competition, where two merged firms become compatible at the expense of product differentiation. We consider two different approaches to modeling rational expectations: responsive and passive. The results show that the merger may reduce industry competition, since the merger-related compatibility enlarges the network scales for insiders and amplifies product differentiation between the insiders and the outsider; therefore, the proposed merger may benefit all firms, raise consumer surplus, and enhance social welfare, i.e., the merger is Pareto-improving.