bluuebunny/crossref_metadata_2025 huggingface dataset:
Factory Extraction from Satellite Images: Benchmark and Baseline
Authors: Deng Yifei , Li Chenglong , Lu Andong , Li Wenjie , Luo Bin
Published: November 2022

Factory extraction from satellite images is a key step in urban factory planning, and plays a crucial role in ecological protection and land-use optimization. However, factory extraction is greatly underexplored in the existing literature due to the lack of large-scale benchmarks. In this paper, we contribute a challenging benchmark dataset named SFE4395, which consists of 4395 satellite images acquired from Google Earth. The features of SFE4395 include rich multiscale factory instances and a wide variety of factory types, with diverse challenges. To provide a strong baseline for this task, we propose a novel bidirectional feature aggregation and compensation network called BACNet. In particular, we design a bidirectional feature aggregation module to sufficiently integrate multiscale features in a bidirectional manner, which can improve the extraction ability for targets of different sizes. To recover the detailed information lost due to multiple instances of downsampling, we design a feature compensation module. The module adds the detailed information of low-level features to high-level features in a guidance of attention manner. In additional, a point-rendering module is introduced in BACNet to refine results. Experiments using SFE4395 and public datasets demonstrate the effectiveness of the proposed BACNet against state-of-the-art methods.
Ionospheric Phase Scintillation Correction Based on Multi-Aperture Faraday Rotation Estimation in Spaceborne P-Band Full-Polarimetric SAR Data
Authors: Tang Feixiang , Ji Yifei , Zhang Yongsheng , Dong Zhen , Yao Baidong
Published: November 2022

The spaceborne P-band fully polarimetric synthetic aperture radar (SAR) working system is highly susceptible to the scintillation effects induced by ionospheric irregularities due to its low carrier frequency. The scintillation phase error (SPE) is a dominant factor that leads to azimuth decorrelation. The aperture-dependent and spatial-varying characteristics of the SPE promote the complexity of the SPE estimation and compensation. In this paper, a methodology is described that compensates the SPE by estimating the Faraday rotation (FR) angle from fully polarimetric SAR data. The multi-aperture scheme is adopted, including the sub-aperture FR estimation, multi-aperture splicing, and overall compensation, to take the complicated characteristics of the aperture-dependent and spatial-varying SPE into account. The methodology is finally validated on simulated data derived from the airborne P-band SAR real data, and compared with an existing method. The new method does not need prior knowledge of the ionospheric height. Furthermore, its performance is investigated in relation to several key factors in different simulation conditions.
Robust Visual Odometry Leveraging Mixture of Manhattan Frames in Indoor Environments
Authors: Yuan Huayu , Wu Chengfeng , Deng Zhongliang , Yin Jiahui
Published: November 2022

We propose a robust RGB-Depth (RGB-D) Visual Odometry (VO) system to improve the localization performance of indoor scenes by using geometric features, including point and line features. Previous VO/Simultaneous Localization and Mapping (SLAM) algorithms estimate the low-drift camera poses with the Manhattan World (MW)/Atlanta World (AW) assumption, which limits the applications of such systems. In this paper, we divide the indoor environments into two different scenes: MW and non-MW scenes. The Manhattan scenes are modeled as a Mixture of Manhattan Frames, in which each Manhattan Frame in itself defines a Manhattan World of a specific orientation. Moreover, we provide a method to detect Manhattan Frames (MFs) using the dominant directions extracted from the parallel lines. Our approach is designed with lower computational complexity than existing techniques using planes to detect Manhattan Frame (MF). For MW scenes, we separately estimate rotational and translational motion. A novel method is proposed to estimate the drift-free rotation using MF observations, unit direction vectors of lines, and surface normal vectors. Then, the translation part is recovered from point-line tracking. In non-MW scenes, the tracked and matched dominant directions are combined with the point and line features to estimate the full 6 degree of freedom (DoF) camera poses. Additionally, we exploit the rotation constraints generated from the multi-view dominant directions observations. The constraints are combined with the reprojection errors of points and lines to refine the camera pose through local map bundle adjustment. Evaluations on both synthesized and real-world datasets demonstrate that our approach outperforms state-of-the-art methods. On synthesized datasets, average localization accuracy is 1.5 cm, which is equivalent to state-of-the-art methods. On real-world datasets, the average localization accuracy is 1.7 cm, which outperforms the state-of-the-art methods by 43%. Our time consumption is reduced by 36%.
Early Detection of Fusarium oxysporum Infection in Processing Tomatoes (Solanum lycopersicum) and Pathogen–Soil Interactions Using a Low-Cost Portable Electronic Nose and Machine Learning Modeling
Authors: Feng Hanyue , Gonzalez Viejo Claudia , Vaghefi Niloofar , Taylor Paul W. J. , Tongson Eden , Fuentes Sigfredo
Published: November 2022

The early detection of pathogen infections in plants has become an important aspect of integrated disease management. Although previous research demonstrated the idea of applying digital technologies to monitor and predict plant health status, there is no effective system for detecting pathogen infection before symptomatology appears. This paper presents the use of a low-cost and portable electronic nose coupled with machine learning (ML) models for early disease detection. Several artificial neural network models were developed to predict plant physiological data and classify processing tomato plants and soil samples according to different levels of pathogen inoculum by using e-nose outputs as inputs, plant physiological data, and the level of infection as targets. Results showed that the pattern recognition models based on different infection levels had an overall accuracy of 94.4–96.8% for tomato plants and between 94.81% and 96.22% for soil samples. For the prediction of plant physiological parameters (photosynthesis, stomatal conductance, and transpiration) using regression models or tomato plants, the overall correlation coefficient was 0.97–0.99, with very significant slope values in the range 0.97–1. The performance of all models shows no signs of under or overfitting. It is hence proven accurate and valid to use the electronic nose coupled with ML modeling for effective early disease detection of processing tomatoes and could also be further implemented to monitor other abiotic and biotic stressors.
A Novel Fuzzy Controller for Visible-Light Camera Using RBF-ANN: Enhanced Positioning and Autofocusing
Authors: Zhou Junpeng , Xue Letang , Li Yan , Cao Lihua , Chen Changqing
Published: November 2022

To obtain high-precision for focal length fitting and improve the visible-light camera autofocusing speed, simultaneously, the backlash caused by gear gaps is eliminated. We propose an improved RBF (Radical Basis Function) adaptive neural network (ANN) FUZZY PID (Proportional Integral Derivative) position closed-loop control algorithm to achieve the precise positioning of zoom and focus lens groups. Thus, the Levenberg–Marquardt iterative algorithm is used to fit the focal length, and the improved area search algorithm is applied to achieve autofocusing and eliminate backlash. In this paper, we initially adopt an improved RBF ANN fuzzy PID control algorithm in the position closed-loop in the visible-light camera position and velocity double closed-loop control system. Second, a similar triangle method is used to calibrate the focal length of the visible-light camera system, and the Levenberg–Marquardt iterative algorithm is used to fit the relation of the zoom potentiometer code values and the focal length to achieve the zoom position closed-loop control. Finally, the improved area search algorithm is used to achieve fast autofocusing and acquire clear images. The experimental results show that the ITAE (integrated time and absolute error) performance index of the improved RBF ANN fuzzy PID control algorithm is improved by more than two orders of magnitude as compared with the traditional fuzzy PID control algorithm, and the settling time is 6.4 s faster than that of the traditional fuzzy PID control. Then, the Levenberg–Marquardt iterative algorithm has a fast convergence speed, and the fitting precision is high. The quintic polynomial fitting results are basically consistent with the sixth-degree polynomial. The fitting accuracy is much better than that of the quadratic polynomial and exponential. Autofocusing requires less than 2 s and is improved by more than double that of the traditional method. The improved area search algorithm can quickly obtain clear images and solve the backlash problem.
Seamless Power Management for a Distributed DC Microgrid with Minimum Communication Links under Transmission Time Delays
Authors: Tran Dat Thanh , Habibullah Al Faris , Kim Kyeong-Hwa
Published: November 2022

To maintain voltage stabilization under transmission time delays, this paper proposes a seamless power management scheme for a distributed DC microgrid (DCMG) with minimum digital communication links (DCLs). First, a DCL topology with minimum communication data is presented for the construction of distributed DCMG system not only to mitigate the communication burden but also to enhance the system’s flexibility and reliability. In addition, based on information gathered from nearby agents and local measurements, the operating modes of local agents in a DCMG system are determined properly to ensure a proper power balance under various conditions. During normal operation, the proposed scheme works as a distributed control scheme either in the grid-connected or islanded mode to take advantage of the distributed control method. To maintain seamless power management even under transmission time delays such as grid fault detection delays and grid recovery detection delays, the operating modes of each agent in a DCMG system are switched to a decentralized scheme based on the droop control method. When the utility grid information is properly identified by all power agents after a transmission time delay, the DCMG system returns to the distributed control scheme based on DC-link voltage (DCV) control to guarantee voltage stabilization. Furthermore, the scalability issue of a distributed DCMG system is also considered in this paper when an additional energy storage system (AESS) agent is involved in the DCMG system. For this purpose, a DCL topology with minimum communication data is designed for the AESS, which enables power units to participate in or to leave the distributed DCMG system easily. Simulation and experimental results under various conditions demonstrate the effectiveness and reliability of the proposed seamless power management strategy.
The Effects of the Type and Quantity of Recycled Materials on Physical and Mechanical Properties of Concrete and Mortar: A Review
Authors: Brahami Yassine , Saeidi Ali , Fiset Mathieu , Ba Kadiata
Published: November 2022

The reuse of industrial wastes to produce concrete and mortar is an environmental solution for their disposal as well as for the development of ecological and sustainable concrete. A large number of previous studies summarized in this review paper focused on adding different types of waste in the concrete and mortar mix in the form of fine aggregates, coarse aggregates or cement additives, and investigated the physical and mechanical properties of the enhanced material. Reusing waste in concrete and mortar mix design significantly affects the material’s fresh and hardened properties. This literature review offers a general insight to the civil and industrial engineering community on ecological waste-based concrete and mortar that can serve as a basis for construction and future work in this field.
Challenges in Implementing Competency-Based Management in the Brazilian Public Sector: An Integrated Model
Authors: de Araújo Mariana Lopes , Menezes Pedro Paulo Murce , Demo Gisela
Published: November 2022

Studies have identified the interference of contextual factors that inhibit the effective implementation of Competency-based Management (CM) under the National Personnel Development Policy (NPDP) in the Brazilian public sector, though organizations have overcome these factors through various initiatives. This article proposes an integrated model that relates the factors that interfere with CM implementation with the initiatives adopted by public organizations to circumvent and overcome them. This qualitative study through documental research and interviews with those responsible for implementing CM in six organizations within the Brazilian public sector. Pre and post-categorical analysis have enabled the establishment of a relationship between the 20 categories identified and divided into four kinds of interfering factors and the 20 adopted initiatives identified in seven categories. It was identified that the organizational and departmental factors are the ones that most interfere with the implementation of CM in the public sector. The strategic role of the HR unit, capable of carrying out structural changes, was identified as the most important initiative to induce the implementation of CM. This study provides a model that integrates strategic, political, and instrumental thematics, showing how these aspects impact the effective implementation of CM, which helps HR managers to recognize the factors that are under their control and how to face them.
Microplastics’ and Nanoplastics’ Interactions with Microorganisms: A Bibliometric Study
Authors: Grande-Tovar Carlos David , Carrascal-Hernández Domingo Cesar , Trilleras Jorge , Mora Katelediana , Arana Victoria A.
Published: November 2022

Microplastics (MPs) and nanoplastics (NPs) are plastic particles of concern worldwide as they negatively affect the environment and human health. The interactions of microorganisms with microplastics and nanoplastics are different. On one hand, microorganisms might biodegrade MPs/NPs through enzymes, but on the other hand, they serve as vehicles to spread diseases or negatively affect their viability. As a result, several studies have reported disturbances in soil balance and negative impacts on geochemical cycles. With an increasing number of investigations into microorganisms and their interactions with MPs and NPs, this study demonstrates a growing interest in biodegradable alternatives. A bibliometric analysis of 719 documents published from 2010 to December 2021 presents the research landscape on the interaction of microplastics and nanoplastics with microorganisms. The study shows that China, the United States, the United Kingdom, and Germany lead the scientific production on this topic. However, in situ studies of large-scale pilot applications in the environment are scarce. More research funding from governments in the form of national action that stimulates national and international cooperation through universities, institutes, and industries is required. There is an urgent need for studies focusing on the degradation mechanisms of various microorganisms through the characterization of enzymes involved in the chemical modification of these emerging contaminants (MPs/NPs) with transparent standard methodologies. Moreover, there is no standardization for MP/NP extraction or characterization methodologies for different environments, especially in atmosphere. The patent need for alternative pathways for MP/NP degradation is evident, using microorganisms such as bacteria, fungi, microalgae, and a consortium (peripheral biofilms) to mitigate the negative impact of the constantly increasing anthropogenic MP/NP pollutants in the world.
Strength Estimation of Damaged Rock Considering Initial Damage Based on P-Wave Velocity Using Regression Analysis
Authors: Xu Xiao , Xu Chuanhua , Hu Jianhua , Ma Shaowei , Li Yue , Wen Lei , Wen Guanping
Published: November 2022

High dispersion of rock mass strength causes significant difficulties in strength prediction. This study aims to investigate experimentally the strength prediction model for brittle damaged rock with multiscale initial damage based on P-wave velocity using regression analysis. Intact dolomitic limestone was collected from a deep metal mine in Southern China. Rock specimens with different initial damage degrees were prepared through the application of uniaxial compressive stress. Both intact rock and damaged rock specimens were tested for P-wave velocity and uniaxial compressive strength (UCS). The test results indicate that the method of prefabricating initial damage to the rock mass through uniaxial compressive stress is feasible. The UCS values of the damaged rock specimens were correlated with the square of the P-wave velocity (linearly positive) and the initial damage (linearly negative). The parameters of the new strength prediction model have a physical significance, and its results are within the upper and lower limits of the 95% confidence interval of the UCS. The strength prediction model considering multiscale initial damage based on P-wave velocity could reasonably predict the strengths of brittle rock masses.
Atmospheric Anomalies Associated with the 2021 Mw 7.2 Haiti Earthquake Using Machine Learning from Multiple Satellites
Authors: Khan Muhammad Muzamil , Ghaffar Bushra , Shahzad Rasim , Khan M. Riaz , Shah Munawar , Amin Ali H. , Eldin Sayed M. , Naqvi Najam Abbas , Ali Rashid
Published: November 2022

The remote sensing-based Earth satellites has become a beneficial instrument for the monitoring of natural hazards. This study includes a multi-sensors analysis to estimate the spatial-temporal variations of atmospheric parameters as precursory signals to the Mw 7.2 Haiti Earthquake (EQ). We studied EQ anomalies in Land Surface Temperature (LST), Air Temperature (AT), Relative Humidity (RH), Air Pressure (AP), and Outgoing Longwave Radiation (OLR). Moreover, we found EQ-associated atmospheric abnormalities in a time window of 3–10 days before the main shock by different methods (e.g., statistical, wavelet transformation, deep learning, and Machine Learning (ML)-based neural networks). We observed a sharp decrease in the RH and AP before the main shock, followed by an immense enhancement in AT. Similarly, we also observed enhancement in LST and OLR around the seismic preparation region within 3–10 days before the EQ, which validates the precursory behavior of all the atmospheric parameters. These multiple-parameter irregularities can contribute with the physical understanding of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) in the future in order to forecast EQs.
The COVID-19 Restrictions and Biological Invasion: A Global Terrestrial Ecosystem Perspective on Propagule Pressure and Invasion Trajectory
Authors: Adomako Michael Opoku , Roiloa Sergio , Yu Fei-Hai
Published: November 2022

Biological invasions driven by climate change, transportation, and intercontinental trade, as well as land-use change and tourism, pose severe threats to biodiversity and ecosystem services worldwide. However, the COVID-19-induced shutdowns and cross-border restrictions could have significantly impacted some of these drivers. Thus, COVID-19-induced restrictions may potentially alter the invasion trajectories and propagule pressure of invasive alien species, yet very few studies have examined this possibility. Here, we provide a unique conceptual framework to examine how COVID-19-induced restrictions may influence the rate, magnitude, and trajectories of biological invasions. We also discuss the similarities between the high-hit regions of COVID-19 and the global hotspot of biological invasions. Additionally, we assessed whether previous predictions of biological invasions still hold despite the strong impact of COVID-19 on the drivers of invasions. Finally, we emphasize the possibility of harnessing such restrictive measures to manage invasive species, nature reserves, and national parks. The present study is a significant addition to the current understanding of the interplay between pandemic outbreaks and biological invasions in the context of both direct and indirect effects of global ecosystem change.
Exploring the Choice of Bicycling and Walking in Rajshahi, Bangladesh: An Application of Integrated Choice and Latent Variable (ICLV) Models
Authors: Mohiuddin Hossain , Rahman Bhuiya Md Musfiqur , Jamal Shaila , Chen Zhi
Published: November 2022

Bangladesh has emphasized active transportation in its transportation policies and has encouraged its population, especially the youth and students, towards bicycling. However, there is a scarcity of studies that have examined the factors important to the choice of active transportation that can be referenced to support the initiative. To address this research gap, in this study, we explore the influence of sociodemographics and latent perceptions of a built environment on the choice to walk and bicycle among students and nonstudents in Rajshahi, Bangladesh. In Rajshahi, we conducted a household survey between July and August, 2017. We used a modeling framework that integrated choice and latent variable (ICLV) models to effectively incorporate the latent perception variables in the choice model, addressing measurement error and endogeneity bias. Our models show that students are influenced by perceptions of safety from crime, while nonstudents are influenced by their perceptions of the walkability of a built environment when choosing a bicycle for commuting trips. For recreational bicycle trips, students are more concerned about the perceptions of road safety, whereas nonstudents are concerned about safety from crime. We find that road safety perception significantly and positively influences walking behavior among nonstudents. Structural equation models of the latent perception variables show that females are more likely to provide lower perceptions of neighborhood walkability, road safety, and safety from crime. Regarding active transportation decisions, overall, we find there is a difference between student and nonstudent groups and also within these groups. The findings of this study can assist in developing a sustainable active transportation system by addressing the needs of different segments of the population. In this study, we also provide recommendations regarding promoting active transportation in Rajshahi.
From Decarbonization to Depopulation: An Emerging Challenge for the Carbon-Intensive Regions under the Energy Transition in Spain
Authors: Garha Nachatter Singh
Published: November 2022

Since 1990, Spain has undergone a rapid decarbonization process focused on closing carbon-intensive facilities such as coal mines and coal-fired power plants and promoting renewable energy sources. These facilities have been the main source of income and employment in the regions where they were located, in addition to being a major source of carbon emissions. Their closure can have a huge impact on the socioeconomic and demographic composition of these carbon-intensive regions, damaging the social fabric and accelerating the process of depopulation. Based on a detailed analysis of policy documents and demographic data (from municipal registers and the 1991–2011 census), this article aims to: first identify and delineate the main carbon-intensive regions in Spain that are vulnerable to the negative impacts of the ongoing decarbonization process; second, examine the different policy responses and phases of the decarbonization process in Spain; and finally, examine the impact of the decarbonization process on the demographic (size, structure, and composition of the population) and socioeconomic configuration of the different carbon-intensive regions in Spain.
Body Condition and Allometry of Free-Ranging Short-Finned Pilot Whales in the North Atlantic
Authors: Arranz Patricia , Christiansen Fredrik , Glarou Maria , Gero Shane , Visser Fleur , Oudejans Machiel G. , Aguilar de Soto Natacha , Sprogis Kate
Published: November 2022

To understand the effects of anthropogenic disturbance on the nutritional health of animals, it is important to measure and understand the morphometrics, allometrics, and body condition of the species. We examined the body shape, allometric relationships, and body condition of short-finned pilot whales (Globicephala macrorhynchus) in three locations across the North Atlantic. Using unmanned aerial vehicles, the body length (BL) and width (along the body axis) were measured from photographs of the dorsal side, while body height (dorso-ventral distance) was measured on the lateral side. Seventy-seven pilot whales were measured (mean ± SD), including 9 calves (BL 2.37 m ± 0.118), 31 juveniles (2.90 m ± 0.183), and 37 adults (3.72 m ± 0.440). The body shape was similar among reproductive classes, with the widest point being anterior of the dorsal fin (at 30–35% BL from the rostrum). The cross-sectional body shape of the whales was flattened in the lateral plane, which increased towards the peduncle and fluke. The rostrum-blowhole distance and fluke width increased linearly with BL. The estimated volumes of pilot whales ranged between 0.15 and 0.32 m3 for calves, 0.25 and 0.64 m3 for juveniles, and 0.46 and 1.13 m3 for adults. The body condition (residual of log-volume vs. log-length) ranged from −34.8 to +52.4%. There was no difference in body condition among reproductive classes or locations.
Exploring the Cloud Computing Implementation Drivers for Sustainable Construction Projects—A Structural Equation Modeling Approach
Authors: Kineber Ahmed , Oke Ayodeji , Alyanbaawi Ashraf , Abubakar Abdurrahman , Hamed Mohammed
Published: November 2022

Sustainability aspects should be adopted during all the decision-making stages of executing construction projects to gain maximum benefits without compromising the objective of such projects. Cloud computing has been a valuable tool for sustainable construction success in several countries over the last two decades. Cloud computing and its drivers have undoubtedly improved the sustainable success target of cost, quality, and time. However, cloud computing implementation in Nigeria’s construction industry is minimal. Consequently, the study aims to generate a decision support model to support a cloud computing implementation by looking into the relationship between cloud computing drivers and construction activities in Nigeria. This study’s data was obtained from previous literature and quantitatively augmented with a questionnaire survey. The data was obtained from questionnaires administered to one hundred and four construction practitioners in Lagos State. Thus, exploratory factor analysis (EFA) was used to validate the questionnaire survey results. However, to assess and validate the factors (drivers) constructed and analyze the relationships between cloud computing drivers and construction activities, partial least square structural equation modelling (PLS-SEM) method was used. An analysis of construction project activities was carried out through EFA, and it generated five main components: pre-contract stage, management, design and storage, estimation and communications, and finally, back-office activities. The study indicated that the implementation of cloud computing drivers had a significant impact on construction activities. The findings also revealed a weak relationship between cloud computing implementation and construction activities, with a 0.087 percent impact. Furthermore, the findings indicate that human satisfaction is the primary factor influencing cloud computing deployment, followed by organization, client acceptance, and industry-based factors. The significance of the findings can be used as a reference or standard for decision-makers to base their decisions on the cost efficiency of cloud computing and its capability to boost efficiency in the construction sector. This research contributes to current construction engineering management by enhancing knowledge of cloud computing implementation drivers and their implications on construction activities.
Maintenance Prioritisation of Irrigation Infrastructure Using a Multi-Criteria Decision-Making Methodology under a Fuzzy Environment
Authors: Mahmoodian Mojtaba , Shahrivar Farham , Li Chunqing
Published: November 2022

The aging infrastructure and rising demand in the irrigation industry as a result of population growth have increased maintenance works in recent years. The most efficient asset maintenance practice is proactive. However, while a limited budget and an increase in aging infrastructure has made proactive asset maintenance challenging, customers still expect quality service, and contemporary challenges such as climate change and the competitive market further add to the existing pressure on asset owners. In this context, the present work has the primary objective of developing a novel, accurate, efficient and straightforward methodology for measuring assessment criteria weights and using them to prioritise assets for maintenance. For this aim, fuzzy multi-criteria decision-making (MCDM) methods are developed for the optimisation of asset maintenance prioritisation. Using objective and subjective data, the proposed method will be utilised to prioritise six irrigation channels in Northern Victoria, Australia, for maintenance. To verify the efficiency and accuracy of the developed MCDM method, the prioritised channels are validated by comparing against their existing physical condition. Results prove the ability of the proposed method in distinguishing and taking into account the differences between the channels (in terms of their size, physical condition, financial impacts, etc.) in prioritisation for maintenance. This study will also provide suggestions to improve the existing asset maintenance prioritisation methods in practice
Research on Current Distribution Strategy Based on Interleaved Double Boost Converter
Authors: Wang Pengcheng , Li Chengchen , Liu Junqi , Cao Xingchen , Cui Haoran , Zhang Yi , Wang Rui
Published: November 2022

In the new energy DC microgrid system, most of the new energy outputs DC power with a low voltage level and a large fluctuation range, which cannot be directly connected to the network. It needs to be boosted by a DC–DC converter, then connected to the power grid or supplied with a DC load. On the premise that the traditional DC–DC converter cannot meet the requirements of high-power applications, the interleaved dual boost converter (IDBC) has been widely used because of its low input current ripple, low device stress and high-power density. It is necessary to maintain the current balance of each phase of the converter during a heavy load and to improve the efficiency during a light load. This paper analyzes the working principle of the six-phase IDBC and reduces the high order model to the low order model according to the symmetry. Due to the current imbalance caused by the mismatch of the parasitic parameters of each phase, two current distribution strategies are designed for different operating. To balance the current of each phase when the converter is overloaded, the relationship between the phase current, parasitic parameters and duty cycle is analyzed based on the state space average method. The estimated parasitic parameters are used to obtain the duty cycle compensation of each phase to eliminate the current imbalance. In addition, to improve the overall efficiency of the converter when the converter connects with a light load, the optimal power distribution coefficient is obtained according to the parasitic parameters to achieve the optimization of the input power, so as to improve the efficiency of the converter. Finally, the simulation results verify the feasibility and effectiveness of the proposed control strategy.
Agency Theory’s “Truth Regime”: Reading Danish Pension Funds’ Decisions Regarding Shell from the Perspective of Agency Theory
Authors: Lundberg Johannes
Published: November 2022

With the progression of both the climate crisis and financial capitalism, institutional investors play an increasingly central role in fossil fuel companies’ business decisions. Against this backdrop, this article investigates the underlying rationales of Danish pension funds’ climate-related investment decisions analyzed from the perspective of one of the dominant finance theories today on the governance relationship between investors and corporations: agency theory. Hitherto, investors’ climate-related investment decisions have not yet been studied from the perspective of how investors’ actions align with the assumptions of agency theory. Thus, this study explores the degree to which select Danish pension funds’ climate-related investment decisions regarding Royal Dutch Shell can be verified according to agency theory. First, deploying Foucault’s notion of a “truth regime”, the article analyzes how a certain action can be defined as true, read from the perspective of investment assumptions derived from agency theory, a truth regime of agency theory. Second, the paper explores the degree to which this truth regime can be identified in the climate-related investment decisions of the three Danish pension funds, PFA, PKA, and AkademikerPension, regarding Shell’s general assembly, 2021. The investigation concludes that the assumptions of the agency theory truth regime constitute a part of the central reasonings in financial capitalism and that, insofar as investors significantly align with the prescriptions of agency theory, it substantially reduces their possibilities to take Paris-aligned investment decisions.
Evaluation and Temporal-Spatial Evolution of Regional New and Old Driving Force Conversion in Shandong Province
Authors: Wu Xiuguo , Wang Sipeng
Published: November 2022

New and old driving force conversion is regarded as the principal strategy to realize economic development from high speed to high quality currently in China. Exploring the temporal-spatial evolution of the new and old driving force conversion can help decision-makers formulate relevant policies and regulations, thereby promoting industrial restructuring and sustainable development of the economy. From the view of regional evolution, this study first presents the methods of measuring conversion speed and direction of the new and old driving force, including the Moore index and the advanced industrial structure coefficient. Then, the conversion development of new and old driving force is evaluated using an improved entropy method and a novel evaluation index system with eight first-level and twenty-two second-level indicators. After that, the spatial correlation of new and old driving force conversion is further analyzed using the global and local Moran’s I, respectively. Finally, the proposed approach is applied to regional cities’ temporal-spatial evolution analysis in Shandong province in China. The results show that: (1) each cities’ conversion development of new and old driving force in the studied province has been steadily improved in recent years, and their conversion developments show noticeable agglomeration effects from a spatial view; (2) however, the conversion of the new and old driving force in the studied province is still at a low level with unbalanced and insufficient development, which prompts the urgent need to accelerate inter-regional collaboration according to their local conditions in the future.
Rural Revitalization and Land Institution Reform: Achievement, Conflict and Potential Risk
Authors: Xu Zhihan , Xu Jianchun , Chai Xiaofang , Zhang Ning , Ye Rong , Xu Fei
Published: November 2022

Rural depression is a global issue in the process of worldwide urbanization. Compared with rural economic institution reform, rural land institution reform is more thorough in realizing rural revitalization. In this paper, polycentric governance theory is used to introduce marketization reform of collective profit-oriented land (MRCPL). MRCPL aims to allow rural collective profit-oriented construction land to be sold and leased with the same rights and at the same price as state-owned construction land. In the process of MRCPL, we suppose that the key subject is the central government, and the multiple auxiliary subjects include local governments, markets, villagers, and village collectives. Herein, Deqing County was selected as the research area and its achievements, conflicts, and potential risks in the process of MRCPL were studied. This study found that in Deqing County, a unified urban–rural construction land market has been preliminarily established, the rural revenue allocation mechanism has been updated, and the rural land finance mechanism has been developed. However, MRCPL may have conflicts with existing land requisition institutions and land banking institutions, and may also have conflicts within different subjects (farmers, village collective, local government, and central government). These conflicts may lead to potential risks, such as rent-seeking risk, land-financing risk, and real-estate-bubble risk. In general, the MRCPL aims to allow rural collective profit-oriented construction land to be sold and leased with the same rights and at the same prices as state-owned construction land. This reform can protect farmers’ land rights and promote the construction of urban and rural integration.
Bipolar Spherical Fuzzy Soft Topology with Applications to Multi-Criteria Group Decision-Making in Buildings Risk Assessment
Authors: Yolcu Adem
Published: November 2022

A generalized soft set model that is more accurate, useful, and realistic is the bipolar spherical fuzzy soft set (BSFSs). It is a more developed variant of current fuzzy soft set models that may be applied to characterize erroneous data in practical applications. Bipolar spherical fuzzy soft sets and bipolar spherical fuzzy soft topology are novel ideas that are intended to be introduced in this work. Bipolar spherical fuzzy soft intersection, bipolar spherical fuzzy soft null set, spherical fuzzy soft absolute set, and other operations on bipolar spherical fuzzy soft sets are some of the fundamental ideas defined in this work. The bipolar spherical fuzzy soft open set, the bipolar spherical fuzzy soft close set, the bipolar spherical fuzzy soft closure, and the spherical fuzzy soft interior are also defined. Additionally, the characteristics of this specified set are covered and described using pertinent instances. The innovative notion of BSFSs makes it easier to describe the symmetry of two or more objects. Moreover, a group decision-making algorithm based on the TOPSIS (Technique of Order Preference by Similarity to an Ideal Solution) approach to problem-solving is described. We analyze the symmetry of the optimal decision and ranking of feasible alternatives. A numerical example is used to show how the suggested approach may be used. The extensive benefits of the proposed work over the existing techniques have been listed.
A New Symbolic Time Series Analysis Method Based on Time-to-Space Mapping, through a Symmetric Magnetic Field, Quantized by Prime Numbers
Authors: Contoyiannis Yiannis , Papadopoulos Pericles , Matiadou Niki-Lina , Potirakis Stelios M.
Published: November 2022

This work presents a new analysis method for two-symbol symbolic time series based on the time-to-space mapping achieved through a device of current carrying circular rings. An algorithm based on the theory of prime numbers is proposed for the approximate estimation of the stratified magnetic field produced by the aforementioned device. The main property of the specific algorithm is that it quantizes the stratified magnetic field. If a two-symbol symbolic time series is used to determine the flow directions of the rings’ currents, a time-to-space mapping of the dynamics of the system producing the time series is observed. A unique “fingerprint” of the symbolic dynamics is shaped by the spatial allocation of the values of the six-valued symmetric quantized magnetic field produced by the device. This allows for the quantitative evaluation of the original system’s dynamics by analyzing the resultant quantized magnetic field values space allocation, in a spectrum ranging from the lack of dynamics (randomness) to the presence of dynamics at all scales (criticality). Two examples of application–corresponding to the extremes of the dynamics spectrum, specifically, for symbolic time series resulting from (a) a random numbers generator and (b) the spin alternation of 2D-Ising in its critical state, verify the reliable time-to-space mapping of the involved symbolic dynamics. Moreover, an application to the symbolic sequence produced by the DNA of the GAPDH (Glyceraldehyde-3-Phosphate Dehydrogenase) human gene is presented as a real-world, intermediate dynamics case. The proposed symbolic time series analysis method presents the advantage that can take into account information related to both symbols, which is particularly useful in analyzing two-symbol time series of relatively short length where the probabilities of occurrence of the two symbols are not equal. By inferring the universality class of an artificial-neural-network-based hybrid spin model through the value of the critical exponent δ, it is shown that for such time series, the proposed method provides a unique way to expose the real dynamics of the underlying complex system, in contrast to the analysis of waiting times in the time domain that leads to an ambiguous quantitative result.
Symmetry, Special Functions and Number Theory
Authors: Planat Michel
Published: November 2022

This editorial is a short review of papers accepted in Symmetry in 2020–2022 about the topic of Number Theory [...]
Effect of Intratrigonal Botulinum Toxin in Patients with Bladder Pain Syndrome/Interstitial Cystitis: A Long-Term, Single-Center Study in Real-Life Conditions
Authors: Abreu-Mendes Pedro , Ferrão-Mendes António , Botelho Francisco , Cruz Francisco , Pinto Rui
Published: November 2022

The high percentage of treatment failures seen in patients with bladder pain syndrome/interstitial cystitis (BPS/IC) managed conservatively frequently demands invasive treatment options. We aimed to evaluate the long-term efficacy and adverse events of intratrigonal botulinum toxin injection in such circumstances, as well as to determine possible predictors of response to toxin treatment. A retrospective cohort study included 47 female BPS/IC patients treated with onabotulinum toxin A (OnabotA) in a tertiary hospital between the years 2009 and 2022. All patients received 100 U of OnabotA in ten injections limited to the trigonal area. Patients were divided into three groups based on their treatment response as responders, non-responders and lost to follow-up due to non-medical reasons. The clinical and surgical records of the individuals were retrieved, including the 10-point visual analogue scale (VAS), the number of treatments, the time between injections, and the age at the first injection. A total of 25 patients (>50% of the cohort) were long-term responders, but none of the evaluated parameters was a predictor for this circumstance: age, pain intensity, or duration of improvement following the injection. The time between injections was stable (around 1 year). No severe adverse events were registered. The intratrigonal injection of botulinum toxin in patients with BPS/IC was an effective and safe long-term treatment for patients’ refractory to conservative forms of treatment. Age, basal pain intensity, and time to injection request did not predict long-term response to OnaBotA.
Degradation of Emerging Pollutants by Photocatalysis: Radiation Modeling and Kinetics in Packed-Bed Reactors
Authors: Manassero Agustina , Alfano Orlando Mario , Satuf María Lucila
Published: November 2022

Radiation modeling and kinetics in two different packed-bed reactors filled with TiO2-coated glass rings are presented. The first reactor was cylindrical, irradiated from one end by a 150 W mercury lamp. It was employed to obtain the values of the intrinsic kinetic parameters of the degradation of the emerging contaminant clofibric acid (CA). The expression to represent the kinetics of the pollutant was derived from a proposed reaction scheme, and it includes explicitly the effect of photon absorption rate on the reaction rate. The second reactor was annular, irradiated internally and externally by 40 UV-LED lamps. The kinetic parameters calculated in the first reactor were directly employed to simulate the performance of the second one, without using any adjustable parameter. The Monte Carlo method was applied to solve the radiation models in both reactors. Good agreement was obtained between simulation results and experimental data under different operating conditions, with a percentage root-mean-square error of 4.6%. The kinetic parameters proved to be independent of the irradiation source, reactor geometry, and catalyst film thickness, and can be readily applied to design real scale devices.
Hydrologic Performance of Low Impact Developments in a Cold Climate
Authors: Xiao Shunlin , Feng Youcan , Xue Lijun , Ma Zhenjie , Tian Lin , Sun Hongliang
Published: November 2022

The application of the low impact development (LID) in a cold climate such as northeastern China is constrained by two unresolved research questions with regards to its infiltration potential through the winter and its varied runoff regimes between winters and summers. This study picked a typical residential district under construction in Changchun, China, and modeled the storm drainage system with and without LID facilities based on the Storm Water Management Model. The hydrological performance of LID was evaluated through various design storms and historic rain events in dry, average, and wet years. The influence of the Horton and the Green–Ampt infiltration methods on the seasonal water budgets was particularly compared since the former is universally adopted in China while the latter is more widely used in the U.S. and other countries. The results indicate that the Horton method tended to generate a higher infiltration volume than the Green–Ampt method. Consequently, when driven by the 100-year design storm, the Horton method led to a 17.4% higher outflow than the Green–Ampt method; when driven by the measured 3-year precipitation in the study area, the yearly runoff coefficients, with regards to the Horton method, were at least 1.3 times higher than those modeled by the Green–Ampt method. This finding challenged the interchangeable use of the Horton and Green–Ampt methods without tests. Furthermore, the formation of snow covers in winter also reduced the permeability of LID and its capacity of managing runoff compared to summer. However, LID still exhibited a decent potential of regulating the winter runoff in the cold region compared to the baseline, possibly owing to the presence of frequent freezing-thawing cycles.
Hydraulic Transients in Water Distribution Systems
Authors: Fuertes-Miquel Vicente S.
Published: November 2022

Hydraulic transients in water distribution systems (WDS) is a field of research that has advanced greatly in the last few decades [...]
Improving the Survival Rate of Common Carp (Cyprinus carpio) Fry Using Malathion and Prophylactic Measures
Authors: KUMAR D.
Published: November 2022

A field experiment involving sixteen 600-m2 nursery ponds was conducted. to test (1) the efficacy of malathion for selectively killing the copepod predators of larvae of common carp (Cyprinus carpio); (2) prophylactic drug treatment of the carp to avoid bacterial and other infections; and (3) a combination of both treatments. Significant differences were found between the treatment groups (P < 0.01) while differences among the replicates were not significant (P > 0.05). The mean survival of fry was 2.8, 1. 7, and 3.4 times higher using malathion, prophylactic drugs and both combined, respectively, than in the control.