bluuebunny/crossref_metadata_2025 huggingface dataset:
Student and Supervisor Perspective on Undergraduate Research in a Teaching-Intensive Setting in Oman
Authors: Al Ajmi Zainab , Al Na’abi Aaya , Alrawahi Abdul-Hakeem , Al Saadoon Muna , Al Balushi Huriya Darwish , Alhabsi Fatema , Babiker Hamza A.
Published: March 2023

Undergraduate research (UGR) is a valuable experience that can potentially enhance the quality of graduates, and raise awareness of the importance of research and its impact on career development. These outcomes, however, depend on the environment under which students conduct research. The present study assessed the staff and students’ perspective of UGR in an intensive teaching setting at the college of Medicine and Health Sciences (COMHS), Sultan Qaboos University (SQU), Oman. We assessed the perception of supervisors (n = 90) and students (n = 314) of UGR and factors that hinder the research experience. Satisfaction towards UGR among supervisors and students was good (mean = 72.4 ± 13.0) and moderate (mean = 57.8 ±14.2), respectively. The students reported a good satisfaction towards the relevance of UGR (mean = 71.34 ± 20.0), the research skills acquired (63.43 ± 18.9), and interaction with research supervisors (68.47 ± 23.5). Female students were more positive towards UGR than males. The students’ grade in the UGR module was the only independent factor influencing their satisfaction. Similar to the students, supervisors were highly satisfied with the relevance of UGR (mean = 84.4% ± 20.7), the module structure (mean = 73.3 ± 14.6), workload (mean = 73.3 ± 14.6) and the students’ performance (71.8% ± 18). However, supervisors were less positive about the students’ acquired skills (mean = 69.0% ±12.8) and available logistics to support UGR (mean = 67.8% ± 16.3). In summary, supervisors and students in COMHS, Oman, (SQU) regard UGR as valuable and recognize its relevance. Supervisors were more likely than students to report a lack of resources to run UGR. Thus, resources should be maintained to inspire supervisors and sustain an active research environment to inspire students.
Building Equitable Education Datasets for Developing Nations: Equity-Minded Data Collection and Disaggregation to Improve Schools, Districts, and Communities
Authors: Taylor Z. W. , Kugiya Jase , Charran Chelseaia , Childs Joshua
Published: March 2023

Many studies of education engage with large datasets to attempt to solve educational problems. However, no studies have provided a systematic overview of how large datasets could be compiled with an eye toward solving educational problems related to equity, especially as it relates to racial, gender, and socioeconomic equity. This study provides a synthesis of literature and recommendations for how developing nations can learn from peers and collect, disaggregate, and analyze data in ways that promote equity, thus improving schools, school districts, and communities.
Predicting Parent Trust Based on Professionals’ Communication Skills
Authors: Hamm James Edward , Mousseau Angela DeSilva
Published: March 2023

Trust is critical to the establishment and maintenance of working relationships between the parents of children with disabilities and their child’s professional. Knowledge of the specific communication skills needed to secure trust is unclear. The current study investigated the relationship between parent evaluation of professionals’ communication skills and parent trust of professionals. A total of 165 parents responded to an online survey during the COVID-19 pandemic. The results indicated that professionals’ communication skills had a significant and moderately positive relationship with the parent trust of professionals. Hierarchical multiple regression analyses indicated that parents’ ratings of professionals’ communication competence, and professionals’ use of in-person communication were the only predictors of parent trust of special education professionals, even when other factors were considered. This study’s findings draw attention to the importance communication skills may have in establishing and maintaining trusting relationships with parents.
Numerical Calculation for the Line-of-Sight Attitudes of Multi-Address Transceivers without 2:1 Transmissions for Space Laser Communication Networking
Authors: Wang Lihui , Zhang Lizhong , Meng Lixin , Bai Yangyang
Published: March 2023

In order to optimize space laser communication networking, the 2:1 transmissions for all reflectors on a multi-address transceiver can be removed. However, without the 2:1 transmissions, the reflectors exhibit doubled optical coupling effect in rotation, which reduces the numerical calculation precision of the attitudes of the reflectors’ lines-of-sight (LOS). In the present study, using Snell’s law of reflection and Euler’s theorem, a mathematical model for the attitudes of the LOS of multiple reflectors without 2:1 transmissions was established, and a method was proposed for an indirect numerical calculation of the attitudes of the LOS by creating a Snell transformation matrix. This method eliminates the influence of the doubled optical coupling effect on the numerical solution of the line-of-sight attitudes of multi-reflectors. Compared to the direct numerical calculation method using the angular velocity, the calculation precisions achieved using the proposed method exhibited improvements of 3, 5, and 3 orders of magnitude in the three conical motions, respectively. The indirect calculation method and the numerical calculation model proposed in the present study, therefore, provide a theoretical basis for applying reflectors without 2:1 transmissions to multi-address transceivers.
Leading Role of E-Learning and Blockchain towards Privacy and Security Management: A Study of Electronics Manufacturing Firms
Authors: Nassani Abdelmohsen A. , Grigorescu Adriana , Yousaf Zahid , Trandafir Raluca Andreea , Javed Asad , Haffar Mohamed
Published: March 2023

The success of businesses is now mostly dependent on e-learning methods as these methods are a rapidly growing innovative technology. Blockchain technology has also been considered to have the ability to change businesses. Therefore, this research aims to explore the direct influence of e-learning on the effectiveness of privacy and security in electronics manufacturing. This study also examines the considerable mediating role of the adoption of blockchain technology between e-learning and privacy and security. Furthermore, the current research investigates how digital orientation moderates the association between e-learning and privacy and security. For the collection of data, the cross-sectional research design and random sampling technique were used, and data were gathered from employees of electronics manufacturing firms in Pakistan through questionnaires. The working response rate of the study was 70%. The findings proved that e-learning plays a considerable role in boosting the privacy and security of electronics manufacturers. The results also demonstrate that the adoption of blockchain technology mediates and digital orientation moderates the link between e-learning and privacy and security. This study adds to the better understanding of management by presenting the significant role of e-learning and blockchain technology in improving the efficiency of privacy and security for electronics manufacturing firms.
Towards Convergence in Federated Learning via Non-IID Analysis in a Distributed Solar Energy Grid
Authors: Lee Hyeongok
Published: March 2023

Federated Learning (FL) is an effective framework for a distributed system that constructs a powerful global deep learning model, which diminishes the local bias and accommodates the successful aggregation of locally trained models with heterogeneous datasets. However, when local datasets have the non-IID attribute, the optimization metric tends to diverge or show unstable convergence in the trajectory space. This paper delves into building a global model for the distributed Smart Grid environment, with regionally cumulated three solar energy datasets from January 2017 to August 2021 in a decentralized power grid in South Korea via FL. This distributed energy network involves local properties and physical distance between the regions, which raises a fundamental question of “Will time-serially curated non-IID local features be effective in constructing a global regression model?”. This paper probes this question by leveraging FL and conducts the theoretically viable non-IID case-by-case convergence analysis, providing the interpretation of the embedded temporal non-IID features and application on real-world data. Moreover, most of the FL studies predetermine the global update period, which lacks applicability when adapting FL in actual practice. As FL is a cumulative-basis structure, the update term is a crucial factor that needs to be carefully selected. This paper articulates this problem and explores the effective update period via multiple experiments on the 4.5 years of solar energy dataset, and to the best of my knowledge, this is the first literature that presents the optimal update period in the FL regression in an energy domain.
Self-Supervised Skill Learning for Semi-Supervised Long-Horizon Instruction Following
Authors: Zhuang Benhui , Zhang Chunhong , Hu Zheng
Published: March 2023

Language as an abstraction for hierarchical agents is promising to solve compositional long-time horizon decision-making tasks. The learning of the agent poses significant challenges, as it typically requires plenty of trajectories annotated with languages. This paper addresses the challenge of learning such an agent under the scarcity of language annotations. One approach for leveraging unannotated data is to generate pseudo-labels for unannotated trajectories using sparse seed annotations. However, as the scenes of the environment and tasks assigned to the agent are diverse, the inference of language instructions is sometimes incorrect, causing the policy to learn to ground incorrect instructions to actions. In this work, we propose a self-supervised language-conditioned hierarchical skill policy (SLHSP) which utilizes unannotated data to learn reusable and general task-related skills to facilitate learning from sparse annotations. We demonstrate that the SLHSP that learned with less than 10% of annotated trajectories has a comparable performance to one that learned with 100% of annotated data. Our approach to the challenging ALFRED benchmark leads to a notable improvement in the success rate over a strong baseline also optimized for sparsely annotated data.
Thermophysical Parameters and Hygrothermal Simulation of Aerogel-Based Fibre-Enhanced Thermal Insulating Renders Applied on Exterior Walls
Authors: Pedroso Marco , Gomes Maria da Glória , Silvestre José Dinis , Hawreen Ahmed , Flores-Colen Inês
Published: March 2023

Aerogel-based renders have been the subject of research in the last few years due to their high thermal insulation characteristics and the need for buildings to become more energy-efficient. This study compares the hygrothermal behaviour of an aerogel-based render (reference) with the same base formulation, replacing the powder with three different fibres (aramid 0.5%, sisal 0.1%, and biomass 0.1%, by total volume) that can be used in buildings’ envelopes. The experimental programme allowed us to characterise and compare the thermophysical properties of the different formulations and then simulate the hygrothermal performance of these solutions when applied to walls for different climatic conditions, considering additional parameters such as total water content, drying potential, water content levels, and thermal insulating performance. These thermophysical parameters were then included in hygrothermal numerical simulations. The results allowed us to verify that the incorporation of fibres improved the hygrothermal properties due to lower capillary absorption and higher water vapour permeability. These renderings showed a high potential for application to building envelopes in different climatic conditions, improving their energy efficiency by up to 20% when compared to other conventional solutions.
Thermal Stability of NASICON-Type Na3V2(PO4)3 and Na4VMn(PO4)3 as Cathode Materials for Sodium-ion Batteries
Authors: Samigullin Ruslan , Zakharkin Maxim , Drozhzhin Oleg , Antipov Evgeny
Published: March 2023

The thermal stability of NASICON-type cathode materials for sodium-ion batteries was studied using differential scanning calorimetry (DSC) and in situ high-temperature powder X-ray diffraction (HTPXRD) applied to the electrodes in a pristine or charged state. Na3V2(PO4)3 and Na4VMn(PO4)3 were analyzed for their peak temperatures and the exothermic effect values of their decomposition processes, as well as the phase transformations that took place upon heating. The obtained results indicate that Mn-substituted cathode material demonstrates much poorer thermal stability in the charged state, although pristine samples of both materials exhibit similar thermal behavior without any DSC peaks or temperature-induced phase transitions in the studied temperature range. The in situ HTPXRD revealed the amorphization of desodiated Na4VMn(PO4)3-based electrodes occurring at 150~250 °C.
A Numerical Investigation of PVT System Performance with Various Cooling Configurations
Authors: Soliman Ahmed Mohamed
Published: March 2023

A numerical analysis of a photovoltaic-thermal (PVT) hybrid system with different cooling configurations is developed. The PVT system consists mainly of a photovoltaic panel and cooling fluid channels. The developed model is used to simulate the system PVT and to study the influence of different cooling patterns, operating and weather conditions on the system performance and to evaluate its energy and exergy efficiency. Five cooling patterns were tested: the first is cooled by air above the panel and water below the panel; the second is air cooling from above and below; the third is cooled by air above the panel only; the fourth is cooled by air below the panel only; and the fifth is cooled by water below the panel only. It was shown that the results of the developed model are consistent with the results of other published works. The performance of the PVT system was analyzed under the weather conditions of Sakaka Al-Jouf, KSA, in summer and winter. It was found that the best cooling pattern is the fifth and the worst is the second. The average panel temperature of (pattern 5) is 21 °C lower than the average panel temperature of pattern 2. The highest efficiency of total energy is 90% when water is used as coolant at the bottom of the panel and air at the top (pattern 1). The lowest efficiency of the total energy of the panel is 34% when the coolant is air at the bottom of the panel (pattern 4). The electrical energy efficiency, total energy efficiency, and total exergy efficiency are strongly influenced by the water flow rate and ambient temperature, while the effect of solar intensity is insignificant.
A Robust Participation in the Load Following Ancillary Service and Energy Markets for a Virtual Power Plant in Western Australia
Authors: Behi Behnaz , Jennings Philip , Arefi Ali , Azizivahed Ali , Pivrikas Almantas , Muyeen S. M. , Gorjy Arian
Published: March 2023

Virtual power plants (VPPs) are an effective platform for attracting private investment and customer engagement to speed up the integration of green renewable resources. In this paper, a robust bidding strategy to participate in both energy and ancillary service markets in the wholesale electricity market is proposed for a realistic VPP in Western Australia. The strategy is accurate and fast, so the VPP can bid in a very short time period. To engage customers in the demand management schemes of the VPP, the gamified approach is utilized to make the exercise enjoyable while not compromising their comfort levels. The modelling of revenue, expenses, and profit for the load-following ancillary service (LFAS) is provided, and the effective bidding strategy is developed. The simulation results show a significant improvement in the financial indicators of the VPP when participating in both the LFAS and energy markets. The payback period can be improved by 3 years to the payback period of 6 years and the internal rate of return (IRR) by 7.5% to the IRR of 18% by participating in both markets. The accuracy and speed of the proposed bidding strategy method is evident when compared with a mathematical method.
Sequence Control Strategy for Grid-Forming Voltage Source Converters Based on the Virtual-Flux Orientation under Balanced and Unbalanced Faults
Authors: Dolado Fernández Juan , Eloy-Garcia Joaquín , Arnaltes Santiago , Rodríguez-Amenedo Jose Luis
Published: March 2023

Renewable power generation has increased in recent years, which has led to a decrease in the use of synchronous generators (SGs). These power plants are mainly connected to the power system through electronic converters. One of the main differences between electronic converters connected to power systems and SGs connected to the grid is the current contribution during faults, which can have an impact on protection systems. New grid codes set requirements for fast current injection, but the converters’ maximum current limitation during faults make it challenging to develop control strategies for such current contribution. This paper presents a positive and negative sequence current injection strategy according to the new Spanish grid code requirements for the novel grid-forming converter control algorithm based on virtual-flux orientation. The behavior of the proposed strategy is tested in a hardware in the loop (HiL) experimental set-up under balanced faults, meaning that the fault is symmetrically distributed among the three phases, and unbalanced faults, where the fault current is distributed asymmetrically between the phases.
Design and Implementation of a Low-Voltage Photovoltaic System Integrated with Battery Energy Storage
Authors: He Xiao , Hashimoto Seiji , Jiang Wei , Liu Jicheng , Kawaguchi Takahiro
Published: March 2023

In this paper, the simulation and design of a power converter suitable for a low-voltage photovoltaic (PV) battery energy storage converter was investigated. The converter was suitable for sources and loads with near voltage levels and were aimed at efficiency improvement. The converter was called a series partial power converter (SPPC). A continuous current and a boost SPPC topology based on an isolated Cûk converter was constructed. The operation modes of the converter were analyzed. The efficiency verification test of the SPPC in a laboratory environment was completed using an outdoor start-up test, a photovoltaic full cover test and a steady-state operation test under different power levels. The results show that the SPPC can achieve 95–98% converter efficiency within the 87 W–242 W power range. The incremental conductance method based on the SPPC can realize the dynamic MPPT under constant illumination and changing meteorological conditions.
Electrification of Oil and Gas Platforms by Wind Energy
Authors: Saadallah Nejm , Heggelund Yngve
Published: March 2023

In this paper, we address the problem of high greenhouse gas emissions from oil and gas platforms in Norway. We look at the potential of integrating an energy system composed of wind turbines and battery systems to unload the electrical power generated by gas turbines being the main source of emissions today. We propose a simulation model of the energy system, the power demand, the available wind speed, and different control strategies. By putting the models together, we evaluate the performance of various compositions of the system and determine their impact on emissions and battery lifetime. The numerical results show that changing today’s practices has great potential to reduce greenhouse gases, with amounts varying between 30% and 80% compared with today’s level.
Production of Biogas from Distillation Residue as a Waste Material from the Distillery Industry in Poland
Authors: Roubinek Otton K. , Wilinska-Lisowska Anna , Jasinska Magdalena , Chmielewski Andrzej G. , Czerwionka Krzysztof
Published: March 2023

In this paper, the possibility to obtain an alternative source of energy from methane fermentation, catalysed by biomass, has been discussed in detail. As a main substrate, the distillation residue from the distillery industry was taken in the case of mono-fermentation and its co-fermentation with sewage sludge. The results showed that higher biogas and methane production can be obtained in a mono-fermentation process. Fermentation lasted for 23 days, and during this time, 333.14 and 249.64 L/kg VS of the total biogas for mono- and co-fermentation was subsequently obtained, which gives around 63% and 50% of methane in both types of the process, respectively. Additionally, to interpret the experimental data obtained and to predict the trend of the accumulation curves, a simple Gompertz model has been applied. The application of the Gompertz model has enabled us to estimate some important parameters with a strict physical meaning, namely, the maximum production value of the biogas and its components, the production rate of a given gas, as well as the incubation phase time. Finally, an approximate analysis of the potential volume of biogas production was also carried out, based on the mass of distillation residue produced annually in Poland.
Trends and Characterization of Primary Energy Sources by Energy and Food Prices
Authors: Igbeghe Christian Barika , Mizik Tamás , Gabnai Zoltán , Bai Attila
Published: March 2023

This study introduces the most important energy trends and global food systems, as well as the relationship between the human development index (HDI) and energy supply and the relationship between energy prices and food prices. Based on seven important indicators as variables in 18 relevant countries worldwide, before and after the pandemic, with the help of cluster analysis and comparative analysis, five different primary energy clusters were created and analyzed. Our results prove the high volatility of the composition of these clusters within a short period. Another important finding is that renewable energy sources (RES) are probably not viable options for the largest (developed and developing) countries in the short term. The human development index and food production per capita are the lowest in the renewable energy cluster and the highest in countries dominated by nuclear energy and oil with typically the highest GDP, since they are able to finance the price hike in both food and energy markets. Generally, it can be stated that although there is a relationship between the measured indicators, it is not constant in all cases. Our results and methodology may be a good basis for further research to examine the relationship between the most important relevant indicators in different countries, as well as the effect of a global crisis on strengthening food and energy security.
Simulation of Boosting Efficiency of GaAs Absorption Layers with KNbO3 Scatterers for Solar Cells
Authors: Zhou Lin , Wu Yihua , Liu Xiaoning , Quan Jiajia , Bi Zhijie , Yuan Feng , Wan Yong
Published: March 2023

In this work, gallium arsenide (GaAs), which has an adjustable band gap and low cost, was adopted as an absorption layer in which KNbO3, having good dielectric, photoelectric, and piezoelectric properties, served as a scattering element for the improvement in absorption efficiency of solar cells. Benefited by the high absorption efficiency of KNbO3, the utilization of the ultraviolet and infrared bands for solar cells can be strengthened. In addition, the ferroelectric and photovoltaic characteristics of KNbO3 enable the realization of decreased thickness of solar cells. Based on the simulation of the shape, width, and period of the scattering element, the effect of the thickness of the scattering element on the absorption efficiency, quantum efficiency, and total efficiency of absorption efficiency was comprehensively simulated. The results show that the absorption layer delivers the optimal performance when using a hexagonal KNbO3 scattering element. The absorption efficiency of the GaAs absorption layer with KNbO3 as the scattering element is increased by 28.42% compared with that of a GaAs absorption layer with empty holes. In addition, the quantum efficiency is maintained above 98% and the total efficiency is 91.59%. At the same time, the efficiency of such an absorption layer is still above 90% when the angle ranges from 0 to 70°. This work provides theoretical guidance for the rational design of solar cells based on photonic crystal structures.
A Review on Leading-Edge Erosion Morphology and Performance Degradation of Aero-Engine Fan and Compressor Blades
Authors: Shi Lei , Guo Shuhan , Yu Peng , Zhang Xueyang , Xiong Jie
Published: March 2023

The leading edges of aero-engine fan and compressor blades suffer from severe erosion due to the inhalation of suspended particulates in the low-altitude atmosphere during long-term transport. A small deformation of the leading edge can significantly change the aerodynamic performance under a strong non-linear effect, leading to increased operation and maintenance costs for engines. This review first focuses on leading-edge erosion morphology during service, and models of these damages. Secondly, the performance degradation caused by eroded leading edges on different classes of engine components, including airfoils, blades, compression systems, and the whole engine, are reviewed. Finally, optimization methods for eroded blade leading edges and their effects on performance recovery are summarized. This paper contributes to an in-depth understanding of the erosion mechanism of blade leading edges in terms of status and its effect, and is a good reference for establishing erosion leading edge repair methods and improving the level of automated repair.
Enhancing the Performance of AnMBR Treating Municipal Wastewater at a High Organic Loading Rate with Iron Addition
Authors: Plevri Argyro , Barka Evridiki , Noutsopoulos Constantinos , Mamais Daniel
Published: March 2023

The performance of a laboratory-scale 40 L anaerobic membrane bioreactor (AnMBR) treating municipal wastewater with and without iron supplementation was evaluated at ambient temperatures at a hydraulic retention time (HRT) of 6 h and sludge retention time (SRT) of 50 days. The system exhibited satisfactory performance during the summer and winter periods with average COD removal efficiencies of 73 ± 4% and 60 ± 4%, respectively. Moreover, two different FeCl3 dosages were studied for optimizing operation in terms of organic load removal, phosphorus removal, biogas production, membrane fouling, and emerging contaminant removal. The addition of 25 mg FeCl3 L−1 improved the performance of the AnMBR. More specifically, average effluent COD concentrations without FeCl3 addition were 177 ± 21 mg/L, while after the addition of 25 mg FeCl3 L−1 and 30 mg FeCl3 L−1, COD decreased to 147 ± 8 mg/L and 149 ± 11 mg/L, respectively. Moreover, effluent TP decreased by 75% with the dosage of 25 mg FeCl3 L−1 and was almost completely removed with 30 mg FeCl3 L−1. The membrane performance was slightly improved by FeCl3 dosing while biogas production was not affected by iron addition. AnMBR appeared inadequate for the removal of almost all the selected micropollutants, and the effect of iron addition on micropollutant removal was very limited.
The Influence of the Reaction Parameters on the Synthesis of Fatty Acid Octyl Esters and Investigation of Applications Properties of Its Blends with Mineral Diesel
Authors: Gotovuša Mia , Racar Marko , Konjević Lucija , Parlov Vuković Jelena , Faraguna Fabio
Published: March 2023

The first aim of this paper is to study the influence of four parameters of the transesterification reaction—reaction temperature (40–80 °C), time (1–3 h), the molar ratio of 1-octanol to sunflower oil (4:1–10:1) and mass fraction of the catalyst (1–3 wt%)—on the conversion of oil to biodiesel (octyl esters of fatty acids), with potassium hydroxide as a catalyst. The highest conversion, of 99.2%, was obtained at 60 °C, a molar ratio of 1-octanol to sunflower oil of 10:1, and with 2 wt% of the catalyst after an hour. The optimal conditions determined with response surface methodology (RSM) when aiming for the lowest possible parameter values and a conversion of 95% or higher were a temperature of 40 °C, time of 1 h, 1-octanol to oil molar ratio at 8.11:1 and mass fraction of catalyst of 2.01%. Furthermore, post-synthesis and purification (>99%), the application properties of pure fatty acid octyl esters (FAOCE) and their blends with mineral diesel and 1-octanol were evaluated. Standardized tests were conducted to measure the fuel’s density, viscosity, cold filter plugging point (CFPP), and lubricity. The addition of FAOCE in mineral diesel increases its density, viscosity, and lubricity. When added up to 20 vol%, FAOCE did not have an influence on the blend’s CFPP value. Still, all the blend property values fell within the limits required by standard EN 590.
Application of Seismic Waveform Indicator Inversion in the Depth Domain: A Case Study of Pre-Salt Thin Carbonate Reservoir Prediction
Authors: Hao Jinjin , Wu Shiguo , Yang Jinxiu , Zhang Yajun , Sha Xuemei
Published: March 2023

Prestack depth-migrated seismic data, having more accurate imaging position and amplitude fidelity than prestack time-migrated seismic data, are supposed to produce a higher quality reservoir prediction result by using depth-domain inversion. Some researchers have developed different methods of depth-domain seismic inversion. However, it has not been widely used in the industry probably because of two reasons: (1) it is a complex process to conduct depth-domain seismic inversion due to the nonstationary depth-domain seismic wavelet; and (2) time-domain seismic inversion is considered capable of solving the problem with less cost, both in regard to time and the economy. In this paper, we try to use the seismic waveform indicator inversion method in the depth domain. First, a forward model was built to demonstrate that seismic waveforms both in the time domain and the depth domain are highly correlated with lithologic associations. Second, a quantitative evaluation method of seismic data for reservoir prediction was proposed, which can help geophysicists estimate time-domain and depth-domain inversion effects before inversion. Finally, the seismic waveform indicator inversion method was implemented for presalt thin carbonate reservoir prediction in the Central Block at the eastern margin of the Pre-Caspian Basin. The depth-domain inversion result shows a relatively true structure and higher resolution validated by wells.
Vegetation Extraction from Airborne Laser Scanning Data of Urban Plots Based on Point Cloud Neighborhood Features
Authors: Zhang Jianpeng , Wang Jinliang , Ma Weifeng , Deng Yuncheng , Pan Jiya , Li Jie
Published: March 2023

This study proposes an accurate vegetation extraction method used for airborne laser scanning data of an urban plot based on point cloud neighborhood features to overcome the deficiencies in the current research on the precise extraction of vegetation in urban plots. First, the plane features in the R-neighborhood are combined with Euclidean distance clustering to extract the building point cloud accurately, and the rough vegetation point cloud is extracted using the discrete features in the R-neighborhood. Then, under the building point cloud constraints, combined with the Euclidean distance clustering method, the remaining building boundary points in the rough vegetation point cloud are removed. Finally, based on the vegetation point cloud after removing the building boundary point cloud, points within a specific radius r are extracted from the vegetation point cloud in the original data, and a complete urban plot vegetation extraction result is obtained. Two urban plots of airborne laser scanning data are selected to calculate the point cloud plane features and discrete features with R = 0.6 m and accurately extract the vegetation point cloud from the urban point cloud data. The visual effect and accuracy analysis results of vegetation extraction are compared under four different radius ranges of r = 0.5 m, r = 1 m, r = 1.5 m and r = 2 m. The best vegetation extraction results of the two plots are obtained for r = 1 m. The recall and precision are obtained as 92.19% and 98.74% for plot 1 and 94.30% and 98.73% for plot 2, respectively.
The Effect of Human Trampling Activity on a Soil Microbial Community at the Urban Forest Park
Authors: Liu Qianqian , Li Wensui , Nie Hui , Sun Xiaorui , Dong Lina , Xiang Liu , Zhang Jinchi , Liu Xin
Published: March 2023

Soil degradation resulting from human trampling in urban forest parks can negatively impact the taxonomic diversity and function of soil microbial communities. In this study, we established long-term, fixed large plots in Zijin Mountain Urban Forest Park in Nanjing, China, to assess the level of trampling pressure. Soil samples were collected from depths of 0–10 cm, 10–20 cm, and 20–30 cm for light trampling (LD), moderate trampling (MD), severe trampling (SD), extreme trampling (ED), and a no-trampling control (CK). The effects of different trampling pressures on soil were studied, including soil nutrient indices, microbial biomass, and the taxonomic diversity of fungi and bacteria. ANOVA and structural equation modeling (SEM) were employed to investigate the impacts of human trampling on the microbial community structure and function. The results indicated that soil organic carbon, ammonium, and acid phosphatase activity were the primary driving factors of microbial community change. Soil microbial diversity initially increased and then decreased with increasing trampling intensity. The changes in soil microbial function and classification were found to be associated with the intensity of trampling. Moderate trampling could enhance the diversity of the soil microbial community. The succession pattern of the fungi and bacteria communities was distinct, and the composition of the bacteria community remained relatively stable. Trampling impacts vegetation and soil structure, which then affects the structure and function of the microbial community. This study provides an essential foundation for the restoration of compacted soil in urban forest parks through targeted monitoring and management efforts.
Elucidating SNP-Based Population Structure and Genetic Diversity of Bruguiera gymnorhiza (L.) Savigny in Thailand
Authors: Ruang-areerate Panthita , Sonthirod Chutima , Sangsrakru Duangjai , Waiyamitra Pitchaporn , Maknual Chatree , Wanthongchai Poonsri , Chomriang Pranom , Pootakham Wirulda , Tangphatsornruang Sithichoke
Published: March 2023

Bruguiera gymnorhiza (L.) Savigny is one of the most important and widespread mangrove species in the Indo-West Pacific region. Here, the population structure and genetic diversity of B. gymnorhiza along the coastlines of Thailand were examined. A total of 73 B. gymnorhiza accessions in 15 provinces were sequenced using RAD-seq to generate their SNPs. Based on the high-quality SNPs, the topology of the maximum likelihood phylogenetic tree clearly presented two genetically distinct groups corresponding to two geographic regions, the Gulf of Thailand and the Andaman Sea coasts. The results for the population structure provided by STRUCTURE and PCA also showed two main genetic clusters and their genetic admixture. A moderate genetic diversity was observed among the accessions, with average observed and expected heterozygosity values of 0.397 and 0.317, respectively. A high genetic differentiation (FST = 0.16, p < 0.001) between the two subpopulations was significantly found. An analysis of molecular variance revealed 83.95% of the genetic variation within populations and 16.05% of the genetic variation among populations. A high genetic variation within the populations and admixture may facilitate adaptation to local environments and climate changes. These results provide important information on the population genetic structure and genetic diversity of B. gymnorhiza in Thailand for further mangrove management.
Banging Interaction: A Ubimus-Design Strategy for the Musical Internet
Authors: Keller Damián , Yaseen Azeema , Timoney Joseph , Chakraborty Sutirtha , Lazzarini Victor
Published: March 2023

We introduce a new perspective for musical interaction tailored to a specific class of sonic resources: impact sounds. Our work is informed by the field of ubiquitous music (ubimus) and engages with the demands of artistic practices. Through a series of deployments of a low-cost and highly flexible network-based prototype, the Dynamic Drum Collective, we exemplify the limitations and specific contributions of banging interaction. Three components of this new design strategy—adaptive interaction, mid-air techniques and timbre-led design—target the development of creative-action metaphors that make use of resources available in everyday settings. The techniques involving the use of sonic gridworks yielded positive outcomes. The subjects tended to choose sonic materials that—when combined with their actions on the prototype—approached a full rendition of the proposed soundtrack. The results of the study highlighted the subjects’ reliance on visual feedback as a non-exclusive strategy to handle both temporal organization and collaboration. The results show a methodological shift from device-centric and instrumental-centric methods to designs that target the dynamic relational properties of ubimus ecosystems.
A Highly Interactive Honeypot-Based Approach to Network Threat Management
Authors: Yang Xingyuan , Yuan Jie , Yang Hao , Kong Ya , Zhang Hao , Zhao Jinyu
Published: March 2023

In this paper, considering the problem that the common defensive means in the current cyber confrontation often fall into disadvantage, honeypot technology is adopted to turn reactive into proactive to deal with the increasingly serious cyberspace security problem. We address the issue of common defensive measures in current cyber confrontations that frequently lead to disadvantages. To tackle the progressively severe cyberspace security problem, we propose the adoption of honeypot technology to shift from a reactive to a proactive approach. This system uses honeypot technology for active defense, tempting attackers into a predetermined sandbox to observe the attacker’s behavior and attack methods to better protect equipment and information security. During the research, it was found that due to the singularity of traditional honeypots and the limitations of low-interactivity honeypots, the application of honeypot technology has difficulty in achieving the desired protective effect. Therefore, the system adopts a highly interactive honeypot and a modular design idea to distinguish the honeypot environment from the central node of data processing, so that the honeypot can obtain more sufficient information and the honeypot technology can be used more easily. By managing honeypots at the central node, i.e., adding, deleting, and modifying honeypots and other operations, it is easy to maintain and upgrade the system, while reducing the difficulty of using honeypots. The high-interactivity honeypot technology not only attracts attackers into pre-set sandboxes to observe their behavior and attack methods, but also performs a variety of advanced functions, such as network threat analysis, virtualization, vulnerability perception, tracing reinforcement, and camouflage detection. We have conducted a large number of experimental comparisons and proven that our method has significant advantages compared to traditional honeypot technology and provides detailed data support. Our research provides new ideas and effective methods for network security protection.
A Network Intrusion Detection Method Incorporating Bayesian Attack Graph and Incremental Learning Part
Authors: Wu Kongpei , Qu Huiqin , Huang Conggui
Published: March 2023

For the current stage of complex and changing network environments and correlated and synchronized vulnerability attacks, this study first fuses attack graph technology and Bayesian networks and constructs Bayesian attack graphs toportray the correlation relationships between vulnerabilities and discovering attackers’ intentions. Meanwhile, improving the Bayesian attack graph is difficult because it is difficult to achieve active updates and adapt to the changing network environment and other problems. The study proposed a detection method that integrated the Bayesian attack graph and the XGBoost incremental learning (IL) approach. Experiments showed that the IL model had an accuracy of 0.951, an accuracy of 0.999, a recall of 0.815, an F1 value of 0.898, and an Area Under Curve (AUC) value of 0.907. The prediction ability of this method was better than that of the base model. Bayesian attack graphs fused with IL can detect attacks in the network more efficiently and accurately, so the probability of each node in the network system being attacked can be updated in real time.
Extended Stability and Control Strategies for Impulsive and Fractional Neural Networks: A Review of the Recent Results
Authors: Stamov Gani , Stamova Ivanka
Published: March 2023

In recent years, cellular neural networks (CNNs) have become a popular apparatus for simulations in neuroscience, biology, medicine, computer sciences and engineering. In order to create more adequate models, researchers have considered memory effects, reaction–diffusion structures, impulsive perturbations, uncertain terms and fractional-order dynamics. The design, cellular aspects, functioning and behavioral aspects of such CNN models depend on efficient stability and control strategies. In many practical cases, the classical stability approaches are useless. Recently, in a series of papers, we have proposed several extended stability and control concepts that are more appropriate from the applied point of view. This paper is an overview of our main results and focuses on extended stability and control notions including practical stability, stability with respect to sets and manifolds and Lipschitz stability. We outline the recent progress in the stability and control methods and provide diverse mechanisms that can be used by the researchers in the field. The proposed stability techniques are presented through several types of impulsive and fractional-order CNN models. Examples are elaborated to demonstrate the feasibility of different technologies.
Value of Some Scoring Systems for the Prognosis of Rebleeding and In-Hospital Mortality in Liver Cirrhosis with Acute Variceal Bleeding
Authors: Huy Duong Quang , Chung Nguyen Van , Dong Dinh Tien
Published: March 2023

Background: Upper gastrointestinal (GI) hemorrhage, caused by acute esophageal variceal bleeding, is a common complication and a leading cause of death in patients with cirrhosis. Therefore, predicting the risk in order to employ an active management to prevent rebleeding and death is crucial. Currently, there are many prognostic scoring systems that have been proposed, but research is needed to find a valid score which can be applied in clinical practice in each country and population. Aims: To compare the value of ALBI (Albumin-Bilirubin), PALBI (Platelet Albumin-Bilirubin), AIMS65, model for end-stage liver disease (MELD), and Child–Pugh scores (CPS) approaches in predicting early rebleeding and in-hospital mortality of acute variceal bleeding in patients with cirrhosis. Subjects and methods: We performed a cross-sectional descriptive study on cirrhotic patients with acute variceal bleeding who were being treated at the Department of Gastroenterology, Intensive care unit—Military Hospital 103 and the Institute for Treatment of Digestive Diseases—108 Military Central Hospital from September 2020 to May 2022. We calculated ALBI, PALBI, AIMS65, MELD, Child–Pugh values and compared them with the rates of early rebleeding and in-hospital mortality. Then, determined and compared the prognostic value through an analysis of the area under the curve (AUC). Results: 222 patients with acute esophageal variceal bleeding were eligible for inclusion in the study. The rates of rebleeding and in-hospital mortality were 9.0% and 6.8%, respectively. Regarding the prognosis of early rebleeding, the ALBI and PALBI scores have good prognostic value (AUROC 0.74; 95% CI: 0.63–0.85 and AUROC 0.7; 95% CI: 0.59–0.81; p = 0.004, respectively), while the Child–Pugh, MELD, AIMS65 scores have little prognostic value, with AUROC < 0.70. Regarding prognosis of in-hospital mortality: the ALBI, PALBI, MELD and AIMS65 all have good value in predicting in-hospital mortality, with AUROC of 0.81 (95% CI: 0.68–0.93, respectively; p < 0.001); 0.8 (95% CI: 0.69–0.91; p <0.001); 0.83 (95% CI: 0.72–0.93; p < 0.001); and 0.82 (95% CI: 0.76–0.87, p < 0.001), respectively. While Child–Pugh score only has medium prognostic value, with AUROC 0.79 (95% CI: 0.66–0.92; p < 0.05). However, there was no significant difference between these prognostic scoring systems. Conclusion: the ALBI, PALBI, MELD and AIMS65 scores all had similar good value in predicting in-hospital mortality, but with early rebleeding prognosis, only ALBI and PALBI had good value. CPS does not show prognostic value like other scores, both in predicting early rebleeding and in-hospital mortality.
Recent Development of Functional Chitosan-Based Hydrogels for Pharmaceutical and Biomedical Applications
Authors: Taokaew Siriporn , Kaewkong Worasak , Kriangkrai Worawut
Published: March 2023

Chitosan is a promising naturally derived polysaccharide to be used in hydrogel forms for pharmaceutical and biomedical applications. The multifunctional chitosan-based hydrogels have attractive properties such as the ability to encapsulate, carry, and release the drug, biocompatibility, biodegradability, and non-immunogenicity. In this review, the advanced functions of the chitosan-based hydrogels are summarized, with emphasis on fabrications and resultant properties reported in literature from the recent decade. The recent progress in the applications of drug delivery, tissue engineering, disease treatments, and biosensors are reviewed. Current challenges and future development direction of the chitosan-based hydrogels for pharmaceutical and biomedical applications are prospected.
Genome–Transcriptome Transition Approaches to Characterize Anthocyanin Biosynthesis Pathway Genes in Blue, Black and Purple Wheat
Authors: Kapoor Payal , Sharma Saloni , Tiwari Apoorv , Kaur Satveer , Kumari Anita , Sonah Humira , Goyal Ajay , Krishania Meena , Garg Monika
Published: March 2023

Colored wheat has gained enormous attention from the scientific community, but the information available on the anthocyanin biosynthetic genes is very minimal. The study involved their genome-wide identification, in silico characterization and differential expression analysis among purple, blue, black and white wheat lines. The recently released wheat genome mining putatively identified eight structural genes in the anthocyanin biosynthesis pathway with a total of 1194 isoforms. Genes showed distinct exon architecture, domain profile, regulatory elements, chromosome emplacement, tissue localization, phylogeny and synteny, indicative of their unique function. RNA sequencing of developing seeds from colored (black, blue and purple) and white wheats identified differential expressions in 97 isoforms. The F3H on group two chromosomes and F3′5′H on 1D chromosomes could be significant influencers in purple and blue color development, respectively. Apart from a role in anthocyanin biosynthesis, these putative structural genes also played an important role in light, drought, low temperature and other defense responses. The information can assist in targeted anthocyanin production in the wheat seed endosperm.