bluuebunny/crossref_metadata_2025 huggingface dataset:
Electrical Impedance Tomography of Industrial Two-Phase Flow Based on Radial Basis Function Neural Network Optimized by the Artificial Bee Colony Algorithm
Authors: Zhu Zhiheng , Li Gang , Luo Mingzhang , Zhang Peng , Gao Zhengyang
Published: September 2023

In electrical impedance tomography (EIT) detection of industrial two-phase flows, the Gauss-Newton algorithm is often used for imaging. In complex cases with multiple bubbles, this method has poor imaging accuracy. To address this issue, a new algorithm called the artificial bee colony–optimized radial basis function neural network (ABC-RBFNN) is applied to industrial two-phase flow EIT for the first time. This algorithm aims to enhance the accuracy of image reconstruction in electrical impedance tomography (EIT) technology. The EIDORS-v3.10 software platform is utilized to generate electrode data for a 16-electrode EIT system with varying numbers of bubbles. This generated data is then employed as training data to effectively train the ABC-RBFNN model. The reconstructed electrical impedance image produced from this process is evaluated using the image correlation coefficient (ICC) and root mean square error (RMSE) criteria. Tests conducted on both noisy and noiseless test set data demonstrate that the ABC-RBFNN algorithm achieves a higher ICC value and a lower RMSE value compared to the Gauss–Newton algorithm and the radial basis function neural network (RBFNN) algorithm. These results validate that the ABC-RBFNN algorithm exhibits superior noise immunity. Tests conducted on bubble models of various sizes and quantities, as well as circular bubble models, demonstrate the ABC-RBFNN algorithm’s capability to accurately determine the size and shape of bubbles. This outcome confirms the algorithm’s generalization ability. Moreover, when experimental data collected from a 16-electrode EIT experimental device is employed as test data, the ABC-RBFNN algorithm consistently and accurately identifies the size and position of the target. This achievement establishes a solid foundation for the practical application of the algorithm.
Overview of Space-Capable Global Navigation Satellite Systems Receivers: Heritage, Status and the Trend towards Miniaturization
Authors: Gill Eberhard , Morton Jade , Axelrad Penina , Akos Dennis M. , Centrella Marianna , Speretta Stefano
Published: September 2023

Spaceborne Global Navigation Satellite Systems (GNSS) receivers have become ubiquitous sensors for spacecraft navigation, especially in Low Earth Orbits (LEOs), often also supporting science endeavors or as acting dedicated science payloads. Due to the large number of space-capable GNSS receiver models available, spacecraft designers, as well as scientists, may find it difficult to have or gain an overview of suitable state-of-the-art models for their purposes and constraints. Based on a literature review that included more than 90 different receiver models, this paper aims to provide an overview of space-capable GNSS receivers that have a heritage in space missions. It analyses trends from the collected data and provides an outlook on miniaturized GNSS receiver models, which have a high potential of being used in future space missions.
A Robot-Assisted Framework for Rehabilitation Practices: Implementation and Experimental Results
Authors: Chiriatti Giorgia , Carbonari Luca , Ceravolo Maria Gabriella , Andrenelli Elisa , Millevolte Marzia , Palmieri Giacomo
Published: September 2023

One of the most interesting characteristics of collaborative robots is their ability to be used in close cooperation scenarios. In industry, this facilitates the implementation of human-in-loop workflows. However, this feature can also be exploited in different fields, such as healthcare. In this paper, a rehabilitation framework for the upper limbs of neurological patients is presented, consisting of a collaborative robot that helps users perform three-dimensional trajectories. Such a practice is aimed at improving the coordination of patients by guiding their motions in a preferred direction. We present the mechatronic setup, along with a preliminary experimental set of results from 19 volunteers (patients and control subjects) who provided positive feedback on the training experience (52% of the subjects would return and 44% enjoyed performing the exercise). Patients were able to execute the exercise, with a maximum deviation from the trajectory of 16 mm. The muscular effort required was limited, with average maximum forces recorded at around 50 N.
A Topic Modeling Approach to Discover the Global and Local Subjects in Membrane Distillation Separation Process
Authors: Aytaç Ersin , Khayet Mohamed
Published: September 2023

Membrane distillation (MD) is proposed as an environmentally friendly technology of emerging interest able to aid in the resolution of the worldwide water issue and brine processing by producing distilled water and treating high-saline solutions up to their saturation with a view toward reaching zero liquid discharge (ZLD) at relatively low temperature requirements and a low operating hydrostatic pressure. Topic modeling (TM), which is a Machine Learning (ML) method combined with Natural Language Processing (NLP), is a customizable approach that is ideal for researching massive datasets with unknown themes. In this study, we used BERTopic, a new cutting-edge Python library for topic modeling, to explore the global and local themes in the MD separation literature. By using the BERTopic model, the words describing the collected dataset were detected together with over- and underexplored research topics to guide MD researchers in planning their future works. The results indicated that two global themes are widely discussed and are relevant to MD scientists abroad. In brief, these topics are permeate flux, heat-energy recovery, surface modification, and polyvinylidene fluoride hydrophobic membranes. BERTopic discovered 62 local concepts. The most researched local topics were solar applications, membrane scaling, and electrospun membranes, while the least investigated were boron removal, dairy effluent applications, and nickel wastewater treatment. In addition, the topics were illustrated in a 2D plane to better understand the obtained results.
Sequential Separation of Essential Oil Components during Hydrodistillation of Azorean Cryptomeria japonica Foliage: Effects on Yield, Physical Properties, and Chemical Composition
Authors: Arruda Filipe , Lima Ana , Wortham Tanner , Janeiro Alexandre , Rodrigues Tânia , Baptista José , Rosa José S. , Lima Elisabete
Published: September 2023

The hydrodistillation (HD) process is used to obtain and fractionate essential oils (EOs). In this study, we aimed to evaluate, for the first time, the effects of six different HD timeframes (HDTs: 0–2, 2–10, 10–30, 30–60, 60–120, and 120–240 min) on the yield, physical properties, and chemical profile of Azorean Cryptomeria japonica foliage (Az–CJF) EO. An Az–CJF EO obtained by a typical HD over 4 h was used as a control sample, yielding 0.82%, w/fresh weight (f.w.), and containing eighty-nine components, as determined by GC–MS. The EO fraction yield revealed a narrow range (0.06–0.18%, w/f.w.), with ca. 50% obtained within the first hour. Monoterpene hydrocarbons dominated in Fr1 and Fr2 (92 and 45%, respectively, mainly α-pinene) while oxygen-containing sesquiterpenes prevailed in Frs. 3–6 (42–62%, mainly elemol and eudesmol isomers). Furthermore, Fr2 and Fr3 were the richest in oxygen-containing monoterpenes (9 and 7%, respectively, mainly bornyl acetate) and in sesquiterpene hydrocarbons (6 and 5%, respectively, mainly δ-cadinene), while Fr4 and Fr5 had higher amounts of diterpene hydrocarbons (ca. 22% both, mainly phyllocladene) and Fr6 exhibited the highest oxygen-containing diterpenes content (4%, mainly nezukol). In addition, regression models were established to predict EO yield, HD rate, and composition (major components) for a given HDT. As a result of this study, specific EO fractions can now be targeted in Az–CJF EO by adjusting the HDT. Hence, these findings can help reduce distillation time and, thus, operating costs associated with the HD process. It can also meet specific market demands due to the differential composition of the obtained EO fractions. In turn, this contributes to increasing the commercial potential of C. japonica EO.
Experimental Study on Mechanical Properties and Acoustic Emission Characteristics of Dry and Water-Saturated Soft Rocks under Different Dynamic Loadings
Authors: Chen Lugen , Wang Dong , Jiang Yujing , Luan Hengjie , Zhang Guangchao , Liang Bin
Published: September 2023

Studying how soft rocks behave dynamically in water-rich settings is vital for ensuring sustainable coal extraction from deep water-saturated soft rock mines. A dynamic disturbance loading system utilizing creep-impact dynamics was employed to analyze the mechanical traits and acoustic emission behaviors of both dry and fully saturated soft rock. Expanding on uniaxial compression tests as a foundational framework, additional experiments involving dynamic disturbances and acoustic emission observations were carried out on the aforementioned soft rock samples. These experiments encompassed a spectrum of cyclic disturbance amplitudes ranging from 2 kN to 10 kN. Experimental results indicated the following: (1) during dynamic disturbance, the hysteresis loop exhibits a “sparse to dense” variation. When subjected to the same number of disturbances, the hysteresis loop takes on a pointed leaf-like shape, which increases with the amplitude of the disturbances. (2) The pinnacle of intensity and the elastic modulus of the samples, when exposed to diverse amplitudes of disturbances, can be categorized into a strengthening phase and weakening phase. The reinforcement effect is highest for both samples under the effect of a perturbation of 4 amplitudes. (3) Under the action of disturbances at various amplitudes, the acoustic emission signals from the samples can be classified into four stages. In all stages, the maximum acoustic emission signals exhibited by the desiccated samples surpass those emanated from the saturated samples. In the fluctuation period (II), dry and saturated samples exhibit a cyclic strengthening effect, which becomes more pronounced as the amplitude increases. The study results offer theoretical support for understanding deformation and instability mechanisms in roadways of deep water-saturated soft rock mines, which is essential for ensuring sustainable coal resource development.
Human Energy Management in Industry: A Systematic Review of Organizational Strategies to Reinforce Workforce Energy
Authors: Onyemelukwe Ifeoma Chukwunonso , Ferreira José Antonio Vasconcelos , Ramos Ana Luísa
Published: September 2023

Recent global events, including the pandemic, social unrest, geopolitical instabilities, automation risk, and socio-economic upheavals, have amplified challenges and stressors that deplete human energy. Coupled with work-related stress, these factors substantially strain the invaluable human capital that fuels organizational productivity. Many scholars acknowledge the existence of a global human energy crisis. While industry may not be in a position to control these stressors, leaders and managers can positively influence employee experience by optimizing workforce energy. Via a systematic literature review adhering to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines, this study aims to explore (1) the concept of human energy and its importance in a human-centered industry, (2) promoting a culture of human energy management within an organizational context, and (3) the existing approaches and strategies that manage human energy. The search in two databases, Scopus and Web of Science, found 1084 papers. After identification and screening, 86 documents remained, and 32 papers was retained after title, keyword, and abstract assessment. Subsequently, a full-text analysis yielded 18 papers included in the review. This study emphasizes industry’s potential to address a societal challenge, “the human energy crisis”, aligning with the European Union’s vision of a sustainable and resilient society.
A Novel Procedure for Comprehensive Recovery of Zinc Fluoride, Manganese Fluorides, Manganese Dioxide, and Carbon Powder from the Electrode Powder of Spent Alkaline Batteries
Authors: Wang Li-Pang , Hsu Wei-Tai , Chen Yan-Jhang , Chen Yan-Fu , Lin I-Chun , Zhou Heng , Kou Mingyin , Sreearunothaia Paiboon
Published: September 2023

In this paper, a novel procedure is proposed for comprehensively recovering zinc fluoride (ZnF2), manganese fluorides [MnFx(x = 2, 3)], manganese dioxide (MnO2), and carbon powder from the electrode powder of spent alkaline batteries. Firstly, hydrofluoric acid (HF) leaching is conducted on the electrode powder of spent alkaline batteries. Secondly, potassium permanganate (KMnO4) is introduced into the leachate to selectively precipitate manganese (Mn) ions to recover MnO2. Subsequently, the water content in the leachate is evaporated to recover ZnF2. Finally, the leaching residue is leached again by using HF, after which the water content in the leachate is evaporated to recover MnFx. The results indicated that under optimal conditions of a HF concentration of 4 M, a leaching time of 15 min, and a liquid–solid ratio of 5 mL/g, the optimal leaching selectivity for Zn and Mn was achieved and the leaching efficiencies of Zn and Mn were 97.83% and 39.94%, respectively. When KMnO4 with a dosage (KMnO4/Mn ion molar ratio) of 0.5:1 was added to the leachate, MnO2 with a grade of 91.68% and a Mn recovery of 39.07% was obtained. In addition, ZnF2 with a grade of 97.98% and a Zn recovery of 96.15% was also obtained after removing the water content from the leachate via evaporation. Under the optimal conditions of a HF concentration of 2 M, a leaching time of 15 min, and a liquid–solid ratio of 10 mL/g for the leaching residue, followed by removing the water content in the leachate via evaporation, MnFx with a grade of 94.20% and a Mn recovery of 59.46%, was obtained. The residue of the releaching process was carbon powder. The effectiveness of the proposed recovery procedure was confirmed.
Factors Affecting Accountants’ Adoption of Remote Working: Evidence from Jordanian Governmental Organizations
Authors: Odat Qutaiba Adeeb , Alshurafat Hashem , Al Shbail Mohannad Obeid , Ananzeh Husam , Al Amosh Hamzeh
Published: September 2023

This study aims to examine the factors that impact accountants’ adoption of remote working within Jordanian governmental organizations. Several models have proven to explain the acceptance and usefulness of technology. Therefore, this study provides an integrated model from a set of theories, including the Technology Acceptance Model (TAM), Technology–Organization–Environment (TOE), Social Capital Theory (SCT), and Theory of Reasoned Action (TRA). The data were gathered from 155 accountants working in Jordanian governmental organizations. PLS-SEM was performed on the data using the Smart-PLS 3 software. The study found a positive relationship between organizational culture, management support, policies, perceived ease of use, and subjective norms with perceived usefulness. In addition, the study found a positive supported relationship between perceived ease of use, perceived usefulness, and subjective norms and attitude toward use. Lastly, this study found a positive supported relationship between attitude toward use and behavioural intention and actual use. This study recommends that future research expand the model by adopting the technological context. In addition, further research could implement the study over a new geographical context in developed and developing countries and compare outcomes.
Factor Structure of Student Science-Learning Motivation: Evidence from TIMSS U.S. Data
Authors: Zhang Fa , Bae Christine L. , Broda Michael D. , Koenka Alison C.
Published: September 2023

We investigated the structure of science motivation among a nationally representative sample of grade 8 students in the United States from the TIMSS dataset. Drawing on an integrative conceptual model of motivation, the following constructs from situative expectancy-value theory (SEVT) and self-determination theory (SDT) were examined through confirmatory factor analyses, including self-concept, task value (intrinsic and utility value), and sense of relatedness, to test the underlying factor structure of motivation. Internal validity evidence was established, which showed that a four-factor model fits the data significantly better than a three-factor model and one-factor model. This study contributes to the current literature by providing evidence of the four dimensions of motivation in a manner that is theoretically aligned with SEVT and SDT, and validated using the TIMSS dataset. The student’s sense of relatedness as a key interpersonal facet of learning motivation is highlighted in this study.
Antecedent Configurations of ESG Disclosure: Evidence from the Banking Sector in China
Authors: Wu Jialing , Wang Daojuan , Fu Xiaoxia , Meng Weina
Published: September 2023

This study examines the complex joint effect of firm and board characteristics on environmental, social, and governance (ESG) disclosure by Chinese listed banks, viewed from a configurational perspective. By utilizing fuzzy-set qualitative comparative analysis (fsQCA) on a sample of 33 Chinese listed banks from 2020, we obtained results that explain some of the inconsistent findings in the current literature and suggest that four specific configurations of firm and board characteristics are equally conducive to high levels of ESG disclosure. Specifically, bank attributes (i.e., size, state ownership, and cross-listing) are the most salient aspects of promoting ESG disclosure, but the final effect relies on a combination of these attributes and other board characteristics (i.e., board size, independence, gender diversity, and a corporate social responsibility committee). We demonstrate the significance of employing configurational thinking to evaluate corporate governance in relation to ESG disclosure. Our findings indicate that the connection between board characteristics and high levels of ESG disclosure varies according to bank attributes.
Participation of Bulgarian Furniture Manufacturing in Global and Local Value Chains as a Factor Supporting Their Innovation Activities
Authors: Georgieva Daniela Ventsislavova , Neykov Nikolay , Barčić Andreja Pirc , Ćurić Petar , Klarić Kristina
Published: September 2023

Innovations can offer key advantages to companies, but in some EU regions, the design and development of innovation measures are still relatively novel concepts. The aim of this study was to analyze the collaborations of innovative Bulgarian furniture manufacturers with external stakeholders and the used information channels as factors for the development and implementation of innovation and participation in global value chains over their innovation activities. Out of 3890 Bulgarian companies, the number of companies included in the target group was further reduced to 85 firms due to missing information on some variables. The data for the present study were collected using a large-scale questionnaire distributed on the spot during the months of March and April 2022. Logistic regression was used to reveal the real contribution of the collaborations and the information sources to the ability of companies to innovate. The research results indicated that in Bulgaria, the furniture sector is not considered very innovative, and Bulgarian furniture manufacturing companies do not rely on collaboration with the IT and mechatronics sectors. These companies do not want to participate in GVCs, as they refer to them in relation to supply chains. Therefore, they are less dependent on chain shocks. Companies prefer to hide their innovations for further protection, which might be the reason for the lack of cooperation between the furniture manufacturing companies and academia, NGOs, and other relevant institutions. The findings of the study contribute to new insights into the literature on the participation in GVCs as a factor for collaboration with different stakeholders and hence for product and process innovation development within the furniture industry companies.
The Study of Carbon Neutralization Effects with Green Credit: Evidence from a Panel Data Analysis for Interprovinces in China
Authors: Jiao Jie , Zhang Jiyuan , Yang Jie , Zhang Wenwen , Guang Fengtao , Liu Liying
Published: September 2023

Giving full play to carbon emission reduction of green credits is essential to achieve carbon neutrality. According to low-carbon pilot policies and the condition of industrial transfer, this paper first sorts those provinces into different research zones. The zones are as follows: (Ⅰ) the first and second batch of low-carbon municipalities and the first batch of pilot provinces (L1) and other provinces (L2) and (Ⅱ) strong industry transfer-out zone (STR), weak industry transfer-out zone (WTR), and industrial transfer-in area (TIR). Then, we employ a dynamic panel data model and systematic GMM (SYS-GMM) approach to empirically test the impact of green credit and nongreen credit on carbon emissions. Further, this paper analyzes how to coordinate two types of credits to achieve carbon neutrality. The results show that, first, at the national level, the nexus of green credit and carbon emissions with an inverted U-shaped curve and the current impact of green credit is still in the first half of the inverted U-shaped stage. The achievement of carbon neutrality is associated with the ratio structure of green credit to nongreen credit and the scale of green credit. Second, the achievement of carbon neutrality is with regional heterogeneity. The achievement of carbon neutrality is associated with the scale of green credit in L2 and TIR, but also with the ratio structure of nongreen credit to green credit in L2 and STR. However, the carbon neutralization effects with green credit are insignificant in L1 WTR. Finally, based on those conclusions, this paper puts forwards some suggestions to provide references for the policy formulation of green credits and carbon neutrality.
Factors Influencing Ground Settlement during Tunnel Proximity Construction
Authors: Yuan Xun , Wang Hongchao , Kang Shun , Liu Changwu , Chen Yulin , Zhou Xianliang , Wu Chengzhe , Zhu Haowei , Yang Changyu , Zhu Yong , Wu Hua
Published: September 2023

Adjacent tunnel excavation has an adverse impact on existing structures. Based on the engineering project of the Donghuashan Tunnel under-crossing an existing tunnel, this paper designed 25 sets of orthogonal numerical simulation tests to investigate the influential mechanisms of five parameters on ground displacement and deformation. The influential factors are skew angle (α), proximity distance (l), buried depth (h), clearance (D), and ratio of tunnel clearances (ν). The orthogonal test results revealed that (1) the new tunnel clearance is the main impact factor of both ground settlement and curvature deformation, (2) ground horizontal movement is most significantly influenced by the skew angle between the existing tunnel and the new tunnel, and (3) the new tunnel buried depth is the key influential parameter for ground tilt deformation as well as horizontal deformation. The conclusions of this research suggest that during the period of railway planning, it is very important to plan the buried depths and spans of new tunnels rationally to minimize disturbance to existing tunnels.
Research on Community Fitness Spaces under the Guidance of the National Fitness Program
Authors: Liu Keyi , Zhang Xia , Xu Danning
Published: September 2023

In the context of sub-health caused by the sedentary lifestyle, sports for health, as an effective way to promote sustainable urban development, has attracted the attention of the government and residents. The proposal of policies represented by the National Fitness Program has facilitated the rapid development of community fitness spaces, which constitute an indispensable part of the Chinese outdoor fitness system. Despite this, many of these spaces still remain unused in reality due to unscientific planning, design, and management. To address this issue, we conducted a study in Liaocheng, Shandong Province, focusing on communities with fitness spaces. Through PSPL, questionnaire surveys and data analysis using software such as Urban Quadrant and SPSS 26, five factors impacting the utilization rates and satisfaction levels of these spaces were identified. And based on MLR, the number of rest facilities was verified as the most important factor and should be considered carefully. By providing insight into the utilization of community fitness spaces, our study can serve as a valuable reference for future planning or renovation of these spaces.
Plane Cascade Aerodynamic Performance Prediction Based on Metric Learning for Multi-Output Gaussian Process Regression
Authors: Liu Lin , Yang Chunming , Xiang Honghui , Lin Jiazhe
Published: September 2023

Multi-output Gaussian process regression measures the similarity between samples based on Euclidean distance and assigns the same weight to each feature. However, there are significant differences in the aerodynamic performance of plane cascades composed of symmetric and asymmetric blade shapes, and there are also significant differences between the geometry of the plane cascades formed by different blade shapes and the experimental working conditions. There are large differences in geometric and working condition parameters in the features, which makes it difficult to accurately measure the similarity between different samples when there are fewer samples. For this problem, a metric learning for the multi-output Gaussian process regression method (ML_MOGPR) for aerodynamic performance prediction of the plane cascade is proposed. It shares parameters between multiple output Gaussian distributions during training and measures the similarity between input samples in a new embedding space to reduce bias and improve overall prediction accuracy. For the analysis of ML_MOGPR prediction results, the overall prediction accuracy is significantly improved compared with multi-output Gaussian process regression (MOGPR), backpropagation neural network (BPNN), and multi-task learning neural network (MTLNN). The experimental results show that ML_MOGPR is effective in predicting the performance of the plane cascade, and it can quickly and accurately make a preliminary estimate of the aerodynamic performance and meet the performance parameter estimation accuracy requirements in the early stage.
On a Fifth-Order Method for Multiple Roots of Nonlinear Equations
Authors: Neta Beny
Published: September 2023

There are several measures for comparing methods for solving a single nonlinear equation. The first is the order of convergence, then the cost to achieve such rate. This cost is measured by counting the number of functions (and derivatives) evaluated at each step. After that, efficiency is defined as a function of the order of convergence and cost. Lately, the idea of basin of attraction is used. This shows how far one can start and still converge to the root. It also shows the symmetry/asymmetry of the method. It was shown that even methods that show symmetry when solving polynomial equations are not so when solving nonpolynomial ones. We will see here that the Euler–Cauchy method (a member of the Laguerre family of methods for multiple roots) is best in the sense that the boundaries of the basins have no lobes. The symmetry in solving a polynomial equation having two roots at ±1 with any multiplicity is obvious. In fact, the Euler–Cauchy method converges very fast in this case. We compare one member of a family of fifth-order methods for multiple roots with several well-known lower-order and efficient methods. We will show using a basin of attraction that the fifth-order method cannot compete with most of those lower-order methods.
The Onset of Darcy–Brinkman Convection in a Porous Layer with Mutual Impact of Thermal Non-Equilibrium and Non-Uniform Temperature Gradients
Authors: Shyabal Suma , Hanumagowda B. N. , Ravisha M. , Mamatha A. L. , Shivaraju N. , D. O. Soumya , Alkarni Shalan , Shah Nehad Ali
Published: September 2023

The two-field thermal conditions of local thermal nonequilibrium (LTNE) were used to investigate linear stability of thermal convection in a liquid-saturated, porous layer via the extended Brinkman–Darcy model for different non-uniform basic thermal gradients. The critical values were numerically computed by the Galerkin method for rigid isothermal boundaries. The impact of LTNE and different forms of non-uniform basic temperature gradients on the onset of porous convection was examined. The porosity modified conductivity ratio has no influence on system stability at a small inter-phase heat transport coefficient limit. However, for higher values of the inter-phase heat transport coefficient, an increase in the porosity modified conductivity ratio hastens the onset of convection. An increase in the Darcy number delays the convective motions. The results for different basic temperature profiles are symmetric qualitatively. In addition, the possibility of control of convection by a basic temperature profile was studied in detail.
A Multi-Strategy Differential Evolution Algorithm with Adaptive Similarity Selection Rule
Authors: Zheng Liming , Wen Yinan
Published: September 2023

The differential evolution (DE) algorithm is a simple and efficient population-based evolutionary algorithm. In DE, the mutation strategy and the control parameter play important roles in performance enhancement. However, single strategy and fixed parameter are not universally applicable to problems and evolution stages with diverse characteristics; besides, the weakness of the advanced DE optimization framework, called selective-candidate framework with similarity selection rule (SCSS), is found by focusing on its single strategy and fixed parameter greedy degree (GD) setting. To address these problems, we mainly combine the multiple candidates generation with multi-strategy (MCG-MS) and the adaptive similarity selection (ASS) rule. On the one hand, in MCG-MS, two symmetrical mutation strategies, “DE/current-to-pbest-w/1” and designed “DE/current-to-cbest-w/1”, are utilized to build the multi-strategy to produce two candidate individuals, which prevents the over-approximation of the candidate in SCSS. On the other hand, the ASS rule provides the individual selection mechanism for multi-strategy to determine the offspring from two candidates, where parameter GD is designed to increase linearly with evolution to maintain diversity at the early evolution stage and accelerate convergence at the later evolution stage. Based on the advanced algorithm jSO, replacing its offspring generation strategy with the combination of MCG-MS and ASS rule, this paper proposes multi-strategy differential evolution algorithm with adaptive similarity selection rule (MSDE-ASS). It combines the advantages of two symmetric strategies and has an efficient individual selection mechanism without parameter adjustment. MSDE-ASS is verified under the Congress on Evolutionary Computation (CEC) 2017 competition test suite on real-parameter single-objective numerical optimization, and the results indicate that, of the 174 cases in total, it wins in 81 cases and loses in 30 cases, and it has the smallest performance ranking value, of 3.05. Therefore, MSDE-ASS stands out compared to the other state-of-the-art DEs.
BiGTA-Net: A Hybrid Deep Learning-Based Electrical Energy Forecasting Model for Building Energy Management Systems
Authors: So Dayeong , Oh Jinyeong , Jeon Insu , Moon Jihoon , Lee Miyoung , Rho Seungmin
Published: September 2023

The growth of urban areas and the management of energy resources highlight the need for precise short-term load forecasting (STLF) in energy management systems to improve economic gains and reduce peak energy usage. Traditional deep learning models for STLF present challenges in addressing these demands efficiently due to their limitations in modeling complex temporal dependencies and processing large amounts of data. This study presents a groundbreaking hybrid deep learning model, BiGTA-net, which integrates a bi-directional gated recurrent unit (Bi-GRU), a temporal convolutional network (TCN), and an attention mechanism. Designed explicitly for day-ahead 24-point multistep-ahead building electricity consumption forecasting, BiGTA-net undergoes rigorous testing against diverse neural networks and activation functions. Its performance is marked by the lowest mean absolute percentage error (MAPE) of 5.37 and a root mean squared error (RMSE) of 171.3 on an educational building dataset. Furthermore, it exhibits flexibility and competitive accuracy on the Appliances Energy Prediction (AEP) dataset. Compared to traditional deep learning models, BiGTA-net reports a remarkable average improvement of approximately 36.9% in MAPE. This advancement emphasizes the model’s significant contribution to energy management and load forecasting, accentuating the efficacy of the proposed hybrid approach in power system optimizations and smart city energy enhancements.
Evaluation of the Removal and Effects of Cylindrospermopsin on Ripened Slow Sand Filters
Authors: Valencia-Cárdenas Daniel , Tavares Thatiane Souza , Silveira Rafaella , Brandão Cristina Celia Silveira , Soares Raquel Moraes , Ginoris Yovanka Pérez
Published: September 2023

The occurrence of toxic blooms of cyanobacteria has been a matter of public health interest due to the cyanotoxins produced by these microorganisms. Cylindrospermopsin (CYN) is a cyanotoxin of particular concern due to its toxic effects on humans. This study investigated the removal and effects of CYN in ripened slow sand filters (SSFs) treating water from Paranoá Lake, Brasilia, Brazil. Four pilot-scale SSFs were ripened and operated for 74 days. Two contamination peaks with CYN were applied along the filtration run. The improvement of any of the evaluated water quality parameters was not affected by the presence of CYN in the raw water. The SSFs efficiently removed CYN, presenting concentrations lower than 0.8 µg/L in the filtered water. The microbiota of the SSFs were dominated by protozoa of the genus Euglypha and amoebas of the genera Arcella, Centropyxis, and Amoeba, together with some groups of rotifers. These microorganisms played a crucial role in removing total coliforms and E. coli. In addition, CYN was not identified as a determining factor in the microbiota composition.
Biotics (Pre-, Pro-, Post-) and Uremic Toxicity: Implications, Mechanisms, and Possible Therapies
Authors: Mitrea Laura , Medeleanu Mădălina , Pop Carmen-Rodica , Rotar Ancuța-Mihaela , Vodnar Dan-Cristian
Published: September 2023

In recent years, more scientific data have pointed out the close connection between intestinal microbial community, nutritional habits, lifestyle, and the appearance of various affections located at certain anatomical systems. Gut dysbiosis enhances the formation and accumulation of specific metabolites with toxic potential that induce the appearance of kidney-associated illnesses. Intestinal microbes are involved in the degradation of food, drugs, or other ingested products that lead to the formation of various metabolites that end up in renal tissue. Over the last few years, the possibilities of modulating the gut microbiota for the biosynthesis of targeted compounds with bioactive properties for reducing the risk of chronic illness development were investigated. In this regard, the present narrative review provides an overview of the scientific literature across the last decade considering the relationship between bioactive compounds, pre-, pro-, and post-biotics, uremic toxicity, and kidney-associated affections, and the possibility of alleviating the accumulation and the negative effects of uremic toxins into the renal system.
Disentangling the Relationship between Urban Form and Urban Resilience: A Systematic Literature Review
Authors: Eldesoky Ahmed Hazem , Abdeldayem Walid Samir
Published: September 2023

The concept of resilience was only recently introduced into urban studies to address the complexity and future uncertainty in cities. In particular, the interest in better understanding how it can be integrated into studying urban form—as the raw material of urban planning/design and key for the sustainability of cities—has been growing. However, resilience is a polysemic concept with different meanings/interpretations, which creates ambiguity and challenges in its operationalization. This paper resolves this issue through a systematic review of 106 peer-reviewed publications guided by recurring questions in the literature (e.g., resilience of/through what? To what? For whom? How? When? Where?). The results showed that the urban form–resilience relationship is complex, where many urban form elements can influence resilience to a great many disturbances (general/specified). In facing these disturbances, urban form exhibits different performances (i.e., persistence, adaptability and transformability) and where it can be either persistent/adaptable/transformable itself or can enhance people’s persistence/adaptation capacities. The review also showed that there are many actors for urban form resilience and potential trade-offs. Finally, an overview of existing definitions of urban form resilience is provided to improve clarity in the field, and examples of general urban planning/design recommendations were formulated to enhance the resilience of different urban form elements.
Correction: Kosoltanapiwat et al. A Novel Simian Adenovirus Associating with Human Adenovirus Species G Isolated from Long-Tailed Macaque Feces. Viruses 2023, 15, 1371
Authors: Kosoltanapiwat Nathamon , van der Hoek Lia , Kinsella Cormac M. , Tongshoob Jarinee , Prasittichai Luxsana , Klein Michelle , Jebbink Maarten F. , Deijs Martin , Reamtong Onrapak , Boonnak Kobporn , Khongsiri Wathusiri , Phadungsombat Juthamas , Tongthainan Daraka , Tulayakul Phitsanu , Yindee Marnoch
Published: September 2023

After publication of the article, the authors received comments from a member of the Viruses editorial board who is an expert in the field of adenovirus concerning figures and references that should be included in the paper [...]
Characteristics of Hydrological and Meteorological Drought Based on Intensity-Duration-Frequency (IDF) Curves
Authors: Abu Arra Ahmad , Şişman Eyüp
Published: September 2023

As a catastrophic phenomenon, drought has destructive impacts on water resources, the environment, and the ecosystem. Consequently, drought plays a vital role in risk assessment, water resources management, and drought mitigation plans. The main aim of this research is to obtain critical intensity-duration-frequency (IDF) drought curves and to provide a comprehensive understanding of the drought characteristics by considering the meteorological Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological Standardized Streamflow Index (SSI). Critical IDF curves for the drought index and return period selection are identified. Also, new terms are defined as the specific drought duration, the maximum drought duration, and the critical intensity based on drought IDF curves. The results show that the SPI3 based on run theory for 500 years return period has higher drought intensity compared with other drought indices. In some IDF curves, the 2-year return period of a 12-month duration timescale is not provided. Regarding the maximum drought duration, the SPEI12 gave a longer duration. With the new concepts in this research, the presented IDF drought methodology has a novel additional practice to identify the critical intensity and maximum drought duration. Using this methodology for any drought index will contribute to converting data with mathematical calculations into IDF curves for design and risk assessment purposes.
(Re-)Envisioning Natural Resource Management Involving First Nations: Toward an Effective Co-Management Policy
Authors: McKibbin Corey
Published: September 2023

In this paper, I posit a relationship between what I consider to be two distinct views of natural resource management: the reductionist and holistic views. The purpose of this comparison is to highlight the dangers of reducing environmental management to its ability to bolster a nation’s economic status. Part of the problem with this view is that it cannot take seriously the needs and desires of Indigenous persons. As such, I compare the reductionist view with the holistic view. The holistic view does not only consider the economics of natural resources; unlike the reductionist view, it aims to take seriously the needs and desires of Indigenous communities that have used natural resources in their territories since time immemorial. To illustrate the differences between the reductionist and holistic views, I examine at length the case of the James Bay Hydro Development in Quebec, Canada. I then apply these insights to an international context by utilizing the literature from Australia. The literature from both Canada and Australia implies that natural resource management involving First Nations needs to take a holistic approach to water management and policy such that the hopes, needs, and desires of Indigenous communities are not merely placated, but fulfilled.
Water Heating Systems Performance in Multi-Family Residential Buildings in Brazil
Authors: Sangoi Juliana May , Scolaro Taylana Piccinini , Ghisi Enedir
Published: September 2023

The performance of water heating systems must be evaluated considering energy consumption and efficiency in storing and distributing hot water, together with building and climate characteristics. This work aims to analyse the performance of different water heating systems compared to electric showers, which are widely used in Brazil. Systems with individual gas heaters and solar heaters with electric backup and gas backup were analysed in multi-family buildings. In addition, the influence of thermal insulation of hot water pipes was verified. The analyses were conducted using the EnergyPlus programme, considering three Brazilian cities with different climates: Curitiba, Brasília, and Belém. The results showed that solar heaters are a low primary energy consumption alternative, especially if combined with gas heaters. However, electric showers are the most efficient option for larger buildings and cold-climate cities, where thermal losses in distribution are more significant. Monthly, an electric shower can save up to 1.82 kWh/m2 of electricity compared to a solar heating system with an electric backup. The insulation has a limited influence on the performance of short-length pipes (temperature difference less than 0.3 °C in the instantaneous gas system). For longer pipes, the absence of insulation significantly reduces the shower temperature (up to 2.47 °C in solar heating systems), mainly in cold-climate locations. It is concluded that the most suitable water heating system should be determined according to the climate and characteristics of the buildings, such as the size and length of the pipe.
Effects of Chemical Activation Conditions on Hierarchical Porous Carbon via Oxytetracycline Adsorption
Authors: Hayrera Fernando Oscar , Kim Do-Gun , Ko Seok-Oh
Published: September 2023

This study investigated the characteristics and oxytetracycline (OTC) adsorption of hierarchical porous carbons (HPCs) synthesized under different activation conditions using biomass wheat flour (WF) and NaHCO3 as an activator. It was found that the characteristics of the HPCs, such as specific surface area, total and mesopore volume, defects, and crystallinity, were highly dependent on the activation temperature, the dose of the activator, and activation time. In particular, the adsorption mechanisms and adsorption capacity were dominantly governed by the degree of defects in graphitic structures and mesoporosity, which are largely determined by the dose of the activator and the activation temperature. The best OTC adsorption was achieved with the HPC of the most abundant mesopores, which was prepared at 900 °C, a WF:NaHCO3 mass ratio of 1:1, and a duration of 2 h (HPC900_R1.0_2H). Based on the results of the experiments concerning adsorption kinetics, equilibrium adsorption, and the effects of pH, OTC adsorption onto HPC900_R1.0_2H was monolayer in type, homogeneous, governed by the combination of diffusion and chemisorption, and largely attributed to π–π electron–donor–acceptor interactions and electrostatic interactions. The thermodynamic parameters suggest that it is spontaneous and endothermic. These findings provide valuable information about the design and synthesis of HPCs from biomass, which exhibit optimized properties for the adsorption of refractory organic pollutants.
Can Selenium Be Removed in a Pilot Plant for Biological Iron and Manganese Removal?
Authors: Steuer Andrea , Dippon-Deißler Urs , Mahringer Daniel , Ruhl Aki S.
Published: September 2023

Selenium (Se) is essential to human health, yet harmful in high doses. Of the water-soluble Se redox species, Se(IV) readily adsorbs onto iron and aluminium oxides. Se(VI), the dominant form in oxygenated waters, is more mobile and less readily adsorbed. In this study, the removal of Se(VI) by reduction with Fe(II) to Se(IV) and subsequent adsorption onto iron hydroxides is investigated in a pilot plant for biological iron and manganese removal from groundwater to investigate an economical approach for Se removal during drinking water production. While Se(IV) is removed by up to 90%, Se(VI) shows no removal over 48 h. In batch-shaking tests, the adsorption of Se(IV) and Se(VI) onto iron hydroxides with and without addition of Fe(II) or dithionite as reducing agents was studied. Se(IV) was removed to a greater extent by adsorption than Se(VI) (7% and 2.6%, respectively, at a starting concentration of 0.1 mg/L) and the addition of reducing agents resulted in no significantly higher removal of Se(VI). Reducing Se(VI) with Fe(II) or dithionite and consequent adsorption onto iron hydroxides can therefore be excluded as viable removal mechanism for Se(VI).
Invasive and Rare Aquatic Invertebrates of Taiwan with a Focus on Their Dormancy
Authors: Alekseev Victor , Dahms Hans-Uwe , Hwang Jiang-Shiou , Sukhikh Natalia
Published: September 2023

Invertebrates in tropical ecosystems are generally considered to have little or no need for a dormant phase due to the stability of the habitat. However, resting stages of aquatic organisms are occasionally found here as well. This fact increases the possibility of transport of tropical organisms by ships’ ballast water, which is the main vector for the spread of alien aquatic organisms between continents. During a study of resting stages in the bottom sediments of the island of Taiwan in 2006–2007, nine species of invertebrates were found, invasive or new to the fauna of the island, with some of them forming large banks of resting stages in sediments.