bluuebunny/crossref_metadata_2025 huggingface dataset:
Accelerating Transition to a Low-Carbon Economy: A Coupling Analysis of Agricultural Products and Resource Environment
Authors: Liang Xueqiu , Xu Jingbo
Published: July 2024

This study examines the low-carbon economy, agricultural products, and the resource environment as three interconnected subsystems, establishing an evaluation framework for their coordinated growth across eight regions of China. The results highlight significant regional imbalances, particularly in North China, Northwest China, and Northeast China. Principal component analysis (PCA) shows that the agricultural product system captures 99.502% of its information, while the resource-environment system accounts for 84.823%, demonstrating robust explanatory power. The national Economic–Agricultural–Resource–Environment (EARE) system progressed from sub-coordinated growth (2010–2014) to coordinated growth (2019–2020), moving from mild imbalance to high-quality growth. Initially, resource growth lagged behind economic development (2010–2015), which then shifted to economic growth lagging behind resource and environmental growth (2015–2020). This study underscores the need for targeted policies to enhance regional sustainability and balanced development.
Correction: Yun et al. A Novel Extended Higher-Order Moment Multi-Factor Framework for Forecasting the Carbon Price: Testing on the Multilayer Long Short-Term Memory Network. Sustainability 2020, 12, 1869
Authors: Yun Po , Zhang Chen , Wu Yaqi , Yang Xianzi , Wagan Zulfiqar Ali
Published: July 2024

(1)The authors wish to delete the expression of “where ⊗ means the Kronecker product and ⊕ means the XOR logic operation” throughout the entire paper [...]
Metro Stations as Catalysts for Land Use Patterns: Evidence from Wuhan Line 11
Authors: Yang Yaoning , Zeng Juncheng , Yin Junfeng , Wu Pengrui , Xu Genyu , Jing Chuanbao , Zhou Jie , Wen Xun , Reinders Johannes , Amatyakul Wasita , Orozco Munoz Sebastian , Chen Tao
Published: July 2024

Urban rail transit systems significantly influence land use patterns in newly developed areas, yet their impact on spatial organization and functional characteristics remains understudied. This research examines Wuhan Metro Line 11, analyzing land use within an 800 m radius of stations using Point of Interest data, ArcGIS spatial analysis, and locational entropy methods. The study reveals three station types, i.e., single-function, mixed-function, and underdeveloped, each exhibiting distinct spatial differentiation patterns. On this basis, a novel “core-diffusion” model emerges, with the highest density of functional elements observed at approximately 600 m from station centers, challenging conventional proximity assumptions. Three spatial organization modes are identified: single-core independent in two-level axis, single-core continuous in single-level axis, and double-core continuous in two-level axis. These findings contribute to the Transit-Oriented Development literature, offering sustainable insights into optimizing land use around metro stations in rapidly urbanizing contexts. This study also provides a methodological framework applicable to similar urban environments, enhancing the understanding of the complex relationships between metro development and surrounding land use patterns. These results have significant implications for urban planning and policy-making, particularly in emerging economies seeking to balance transit efficiency with sustainable urban growth.
Hydrogel Applications in Nitrogen and Phosphorus Compounds Recovery from Water and Wastewater: An Overview
Authors: Szopa Daniel , Wróbel Paulina , Anwajler Beata , Witek-Krowiak Anna
Published: July 2024

This article provides an overview of the diverse applications of hydrogels in nutrient recovery from water and wastewater. Due to their unique properties, such as high water-retention capacity, nutrient rerelease, and tunable porosity, hydrogels have emerged as promising materials for efficient nutrient capture and recycling. It has been suggested that hydrogels, depending on their composition, can be reused in agriculture, especially in drought-prone areas. Further research paths have been identified that could expand their application in these regions. However, the main focus of the article is to highlight the current gaps in understanding how hydrogels bind nitrogen and phosphorus compounds. The study underscores the need for research that specifically examines how different components of hydrogel matrices interact with each other and with recovered nutrients. Furthermore, it is essential to assess how various nutrient-recovery parameters, such as temperature, pH, and heavy metal content, interact with each other and with specific matrix compositions. This type of research is crucial for enhancing both the recovery efficiency and selectivity of these hydrogels, which are critical for advancing nutrient-recovery technologies and agricultural applications. A comprehensive research approach involves using structured research methodologies and optimization techniques to streamline studies and identify crucial relationships.
Who Needs Academic Campuses? Are There Advantages to Studying on an Academic Campus Considering the Experience of Online Teaching Five Years after COVID-19?
Authors: Davidovitch Nitza , Eckhaus Eyal
Published: July 2024

This study explores students’ perceptions of the advantages of academic campuses as the location of studies that involve social interaction, with a focus on the role of social interaction in the learning experience. The study examines students’ perspectives approximately five years after the time of COVID-19, when online studies have become more prevalent. Participants were 1048 students from several departments at two academic institutions, a university and a college, of whom 39.1% (407) were male and 60.9% (633) female. The age of the respondents ranged from 18–23 (30.4%), 24–30 (60.3%), and 31–63 (9.3%). Among all respondents, 64.2% were studying social sciences and 35.8% engineering. A mixed methods research design was employed, combining qualitative and quantitative analysis. Structural equation modeling (SEM) was utilized to test the goodness-of-fit of the presented model. The research findings showed that measures of comprehensibility, concentration, and contact with the lecturer enhance learning in a physical classroom more than learning via online teaching. However, interaction with peers does not improve one’s studies at all and is not a sufficient reason to attend classes. These findings are based on analysis of survey responses, after applying SEM to test the goodness-of-fit of the presented model. The final model showed a good fit: CMIN/DF = 1.26, CFI = 0.999, NFI = 0.996, TLI = 0.994, RMSEA = 0.02. The findings of this study may hold importance for leaders of higher education when endeavoring to plan teaching, learning, and evaluation at academic institutions and for shaping the academic campus as a significant educational space in the future. Moreover, the findings may have important implications for education management strategies towards sustainable development. Higher education institutions need to re-evaluate the role of the physical campus and social interaction within it in the era of remote learning.
Comparison of Urban Climate Change Adaptation Plans in Selected European Cities from a Legal and Spatial Perspective
Authors: Nowak Maciej J. , Bera Milena , Lazoglou Miltiades , Olcina-Cantos Jorge , Vagiona Dimitra G. , Monteiro Renato , Mitrea Andrei
Published: July 2024

The aim of this paper is to identify and compare the key institutional features of urban climate change adaptation plans in three geographically, systemically, and climatically distinct European countries (Greece, Spain, and Poland). The paper concentrates on the tool indicated and confirms the circumstances and potential outcomes of its usage in the selected countries. A case study of a particular city was chosen in each country and the applicability of the climate change adaptation plan there was confirmed. Analysis was also performed on the plans’ legal aspect, connection to national-level strategic planning, and spatial planning. The research questions formulated and addressed are as follows: how do urban climate change adaptation plans in the selected countries define key climate challenges? Is the content of the municipal climate change adaptation plans consistent with the content of the diagnosis of climate challenges at the supra-local level and in the scientific discussion? How are climate change adaptation plans translated into the implementation sphere? Τhe example of Spain and Greece confirms that plans can combine general climate change adaptation objectives with specific (evasive) guidelines for urban policies, while the example of Poland shows that the content of climate change adaptation plans can often be too vague and difficult to further integrate into urban policies. The research results obtained are relevant from the perspective of comparing institutional responses to climate challenges. The research proposes possible methods for making such comparisons.
The Role of Websites in Promoting Wine Tourism: An Evaluation of Romanian Wineries
Authors: Vîlcea Cristiana , Licurici Mihaela , Popescu Liliana
Published: July 2024

While aspiring to become internationally valued producers of high-quality wines, certain Romanian wineries recently turned towards wine tourism. Given the increasing role of smart devices and online-based information in holiday selection and planning, the main objective of the paper is to evaluate the online presence, informational content and effectiveness of Romanian wineries’ websites for the promotion of wine tourism. This evaluation comprised 53 features tested in previous research and organized into four categories: main website characteristics, wine tourism, marketing, and education. Based on content analysis conducted on 154 websites of wineries identified in all Romanian regions, scores were computed and, subsequently, wineries were classified, mapped, and evaluated. The findings show that certain basic features are overall available, while exclusive features that could positively influence tourist preferences and experiences are insufficient in terms of design, education, and marketing characteristics. Less than 50% of the analysed websites inform about wine tasting activities, less than 35% specify visiting hours, and less than 20% mention tourist amenities. The websites that indicate other local wineries, allied industries or tourist attractions represent exceptions. This study underlines the importance of leveraging digital tools within the marketing strategy of wineries and the need to enhance networking among regional stakeholders as prerequisite for sustainable development.
Biosorption of Cd(II), Co(II), and Cu(II) onto Microalgae under Acidic and Neutral Conditions
Authors: Phiri Jesse T. , Oh Sanghwa
Published: July 2024

The biosorption of Cd, Co, and Cu onto three microalgae species (Chlorella vulgaris, Scenedesmus sp., and Spirulina platensis) was compared to determine the microalgae’s capability for heavy metal adsorption in acidic and neutral environments. The Langmuir, Freundlich, and Dubinin–Radushkevich isotherm models were used to characterize the adsorption of the heavy metals onto microalgae. The maximum adsorption capacity (qmax) determined using the Langmuir and D-R model showed results in the order of Cu > Co > Cd in both acidic and neutral conditions. A shift from acidic to neutral conditions increased the microalgae’s adsorption affinity for heavy metals, as determined using the Freundlich parameter (KF). The adsorption affinity of the biomass for Cd and Co was in the order S. platensis > C. vulgaris > Scenedesmus sp. while that of Cu was in the order C. vulgaris > Scenedesmus sp. > S. platensis. In addition, it was found that the adsorption of Cd and Co enhanced the production of Dissolved Organic Content (DOC) as a byproduct of biosorption, whereas the adsorption of Cu appeared to suppress the generation of DOC. The mean adsorption energy (E) values computed by the D-R model were less than 8 (kJ/mol), indicating that physisorption was the primary force of sorption in both acidic and neutral settings. The findings of this study suggest that microalgae may be used as a low-cost adsorbent for metal removal from industrial effluent.
The Impacts of Centralized Control on Mixed Traffic Network Performance: A Strategic Games Analysis
Authors: Kotsi Areti , Politis Ioannis , Mitsakis Evangelos
Published: July 2024

Cooperative Intelligent Transport Systems (C-ITS) address contemporary transportation challenges, as Connected Vehicles (CVs) can play a pivotal role in enhancing efficiency and safety. The role of central governing authorities in shaping traffic management policies for CVs influences decision-making processes and system performance. In this work, the role of central governing authorities in the traffic management of a mixed traffic network is examined, integrating System Optimum principles with game theory. More specifically, we introduce and develop a framework that models and analyses the strategic interactions between different stakeholders in a mixed traffic environment, considering central governing authorities with varying levels of control. The results indicate how the various levels of control of a central governing authority may have an impact on the network in terms of traffic measures. Through a strategic games analysis, the trade-offs associated with centralized control mechanisms are demonstrated and recommendations are offered for policymakers and practitioners to optimize traffic management strategies.
Survival Probability of Tourist Accommodation Establishments in Romania in Relation to the Action of Some Relevant Factors
Authors: Rujescu Ciprian Ioan , Sicoe-Murg Oana Maria , Milin Ioana Anda , Ciolac Ramona
Published: July 2024

The units with tourist functions in Romania have a variable duration of activity resulting from the actions of different factors, but which can be analysed mathematically through survival analysis models. The number of establishments offering accommodation for tourism purposes in Romania exceeds 22,000, and the data indicated by the Ministry of Economy, Entrepreneurship and Tourism on the companies that manage them are the inputs of the study. These allowed for the creation of a statistical database showing the total operating time from establishment to the present or to the cessation of activity. Grouping was carried out according to the type of establishment, the location of the companies in rural or urban areas, their belonging to a geographical region of Romania and classification according to the comfort category. The drawing up of evolution curves describing the probability of survival of the establishments, distinctly for the groups mentioned, and the statistical analysis to establish the significance of the differences between the groups provide information that allows for determining and understanding how certain factors influence the chances of survival of the tourist establishment. The type of accommodation unit, the region of development in which the unit is located and the category of comfort are the factors that have a statistically significant influence on the probability of survival of these units. The location of tourism units in rural or urban areas is not a relevant factor. Knowledge of the actions of these factors allows for optimising the measures taken at the start of an activity in the tourism industry. These can result in improving the survivability of tourism. Sustainable tourism involves developing and supporting different forms of tourism by implementing activity management at both the accommodation unit level and at the locality, regional or whole tourist area level. The survival and continuity of the tourism business on the market and, at the same time, respect for the natural, social and economic integrity of the environment can ensure the rational exploitation of natural and cultural resources for future generations.
Dematerialization of Concrete: Meta-Analysis of Lightweight Expanded Clay Concrete for Compressive Strength
Authors: Uslu İlbüke , Uysal Orkun , Aktaş Can B. , Chang Byungik , Yaman İsmail Özgür
Published: July 2024

The construction industry is responsible for a significant share of global material consumption, including natural resources. Therefore, the United Nations Sustainable Development Goal 12.2 on sustainable management and efficient use of natural resources cannot be achieved without significant advances and contributions from the construction sector. Furthermore, various materials used by the construction industry contribute to the development and expansion of the LEED (Leadership in Energy and Environmental Design) system. LECA (Light Expanded Clay Aggregate) is one such material that enhances LEED performance through its key benefits, including lightness, thermal insulation, sound insulation, and fire resistance. One of the most effective methods for reducing the weight of concrete is the incorporation of lightweight aggregates, and the advantages of LECA include lessening loads and enabling reduced cross-sections, directly improving the sustainability of the built environment via reduced materials consumption. This study aims to develop a prediction model for the compressive strength of LECA-incorporated concrete through a meta-analysis. More than 140 data points were compiled through literature via 15 separate studies, and results were analyzed to conduct the meta-analysis. Moreover, an experimental program was carried out to verify the model and evaluate its accuracy in predicting compressive strength. Results from the developed model and the experimental program were in accordance with concrete having lower compressive strengths compared to those at high strength values. Likewise, more accurate results were obtained for concrete mixes that have w/b ratios of 0.5 or higher. Concrete mixes that have higher amounts of LECA by volume of concrete yielded more accurate results when using the prediction model. A sensitivity analysis was carried out to quantify the impact of several parameters on the compressive strength of LECA concrete.
Improving Influenza Epidemiological Models under Caputo Fractional-Order Calculus
Authors: E. Alsubaie Nahaa , EL Guma Fathelrhman , Boulehmi Kaouther , Al-kuleab Naseam , A. Abdoon Mohamed
Published: July 2024

The Caputo fractional-order differential operator is used in epidemiological models, but its accuracy benefits are typically ignored. We validated the suggested fractional epidemiological seasonal influenza model of the SVEIHR type to demonstrate the Caputo operator’s relevance. We analysed the model using fractional calculus, revealing its basic properties and enhancing our understanding of disease progression. Furthermore, the positivity, bounds, and symmetry of the numerical scheme were examined. Adjusting the Caputo fractional-order parameter α = 0.99 provided the best fit for epidemiological data on infection rates. We compared the suggested model with the Caputo fractional-order system and the integer-order equivalent model. The fractional-order model had lower absolute mean errors, suggesting that it could better represent sickness transmission and development. The results underline the relevance of using the Caputo fractional-order operator to improve epidemiological models’ precision and forecasting. Integrating fractional calculus within the framework of symmetry helps us build more reliable models that improve public health interventions and policies.
Discrete Space Deep Reinforcement Learning Algorithm Based on Support Vector Machine Recursive Feature Elimination
Authors: Kim Chayoung
Published: July 2024

Algorithms for training agents with experience replay have advanced in several domains, primarily because prioritized experience replay (PER) developed from the double deep Q-network (DDQN) in deep reinforcement learning (DRL) has become a standard. PER-based algorithms have achieved significant success in the image and video domains. However, the exceptional results observed in images and videos are not as effective in many domains with simple action spaces and relatively small states, particularly in discrete action spaces with sparse rewards. Moreover, most advanced techniques may improve sampling efficiency using deep learning algorithms rather than reinforcement learning. However, there is growing evidence that deep learning algorithms cannot generalize during training. Therefore, this study proposes an algorithm suitable for discrete action space environments that uses the sample efficiency of PER based on DDQN but incorporates support vector machine recursive feature elimination (SVM-RFE) without enhancing the sampling efficiency through deep learning algorithms. The proposed algorithm exhibited considerable performance improvements in classical OpenAI Gym environments that did not use images or videos as inputs. In particular, simple discrete space environments with reflection symmetry, such as Cart–Pole, exhibited a faster and more stable learning process. These results suggest that the application of SVM-RFE, which leverages the orthogonality of support vector machines (SVMs) across learning patterns, can be appropriate when the data in the reinforcement learning environment demonstrate symmetry.
Functional Bethe Ansatz for a sinh-Gordon Model with Real q
Authors: Sergeev Sergey
Published: July 2024

Recently, Bazhanov and Sergeev have described an Ising-type integrable model which can be identified as a sinh-Gordon-type model with an infinite number of states but with a real parameter q. This model is the subject of Sklyanin’s Functional Bethe Ansatz. We develop in this paper the whole technique of the FBA which includes: (1) Construction of eigenstates of an off-diagonal element of a monodromy matrix. The most important ingredients of these eigenstates are the Clebsh-Gordan coefficients of the corresponding representation. (2) Separately, we discuss the Clebsh-Gordan coefficients, as well as the Wigner’s 6j symbols, in details. The later are rather well known in the theory of 3D indices. Thus, the Sklyanin basis of the quantum separation of variables is constructed. The matrix elements of an eigenstate of the auxiliary transfer matrix in this basis are products of functions satisfying the Baxter equation. Such functions are called usually the Q-operators. We investigate the Baxter equation and Q-operators from two points of view. (3) In the model considered the most convenient Bethe-type variables are the zeros of a Wronskian of two well defined particular solutions of the Baxter equation. This approach works perfectly in the thermodynamic limit. We calculate the distribution of these roots in the thermodynamic limit, and so we reproduce in this way the partition function of the model. (4) The real parameter q, which is the standard quantum group parameter, plays the role of the absolute temperature in the model considered. Expansion with respect to q (tropical expansion) gives an alternative way to establish the structure of the eigenstates. In this way we classify the elementary excitations over the ground state.
CP Violation in the Quark Sector: Mixing Matrix Unitarity
Authors: Martinelli Maurizio
Published: July 2024

Since its discovery in the 1960s, the violation of CP symmetry has intrigued scientists and stimulated the advancement of knowledge in particle physics. Numerous experiments were designed and built to study it in increasingly deeper detail. Nowadays, the phenomenon is well framed within the Standard Model of Particle Physics. Nevertheless, new results are being produced by modern experiments at colliders that challenge the current understanding of the model. In this article, the current status of CP violation studies and the role of CP violation in the search for effects beyond the Standard Model are described together with the prospects for ongoing and future experiments.
Using Spatial Analysis to Design a Solid Waste Collection System
Authors: Araiza-Aguilar Juan Antonio , Rojas-Valencia María Neftalí , Nájera-Aguilar Hugo Alejandro , Gutiérrez-Hernández Rubén Fernando , García-Lara Carlos Manuel
Published: July 2024

In this paper, a proposal was presented to improve the MSW collection service in the municipality of Reforma, in Chiapas, Mexico. Specific field work was developed and various spatial analysis techniques were applied in the GIS environment. The application of a multivariate analysis technique (Grouping Analysis) allowed the study area to be clustered into three waste collection sectors with common characteristics, which were the basis for generating three collection route scenarios. Scenario 1 corresponds to the current situation, where 478 waste collection points are served, with an average travel distance of 60.30 km and a collection time of 8.00 h. Scenario 2 was generated through the “maximize coverage” algorithm and vehicle route modeling in ArcGis 10.8. In this scenario, 1220 waste collection points are served, with an average travel distance of 143.21 km and an average collection time of 12.38 h. Scenario 3 was created using the “minimize facilities” algorithm, as well as collection modeling in ArcGis 10.8. Using this algorithm, impedances (distances) were automatically minimized so that 697 waste collection points could be served, with an average travel distance of 100.00 km and an average collection time of 9.66 h. In terms of improvement, scenario 3 gives the best results, because it minimizes distances and average travel times.
Neurological Complications of COVID-19: Unraveling the Pathophysiological Underpinnings and Therapeutic Implications
Authors: Vashisht Ashutosh , Vashisht Vishakha , Singh Harmanpreet , Ahluwalia Pankaj , Mondal Ashis K. , Williams Colin , Farmaha Jaspreet , Woodall Jana , Kolhe Ravindra
Published: July 2024

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease (COVID-19), induced a global pandemic with a diverse array of clinical manifestations. While the acute phase of the pandemic may be waning, the intricacies of COVID-19′s impact on neurological health remain a crucial area of investigation. Early recognition of the spectrum of COVID-19 symptoms, ranging from mild fever and cough to life-threatening respiratory distress and multi-organ failure, underscored the significance of neurological complications, including anosmia, seizures, stroke, disorientation, encephalopathy, and paralysis. Notably, patients requiring intensive care unit (ICU) admission due to neurological challenges or due to them exhibiting neurological abnormalities in the ICU have shown increased mortality rates. COVID-19 can lead to a range of neurological complications such as anosmia, stroke, paralysis, cranial nerve deficits, encephalopathy, delirium, meningitis, seizures, etc., in affected patients. This review elucidates the burgeoning landscape of neurological sequelae associated with SARS-CoV-2 infection and explores the underlying neurobiological mechanisms driving these diverse manifestations. A meticulous examination of potential neuroinvasion routes by SARS-CoV-2 underscores the intricate interplay between the virus and the nervous system. Moreover, we dissect the diverse neurological manifestations emphasizing the necessity of a multifaceted approach to understanding the disease’s neurological footprint. In addition to elucidating the pathophysiological underpinnings, this review surveys current therapeutic modalities and delineates prospective avenues for neuro-COVID research. By integrating epidemiological, clinical, and diagnostic parameters, we endeavor to foster a comprehensive analysis of the nexus between COVID-19 and neurological health, thereby laying the groundwork for targeted therapeutic interventions and long-term management strategies.
Genetic Characterization of African Swine Fever Italian Clusters in the 2022–2023 Epidemic Wave by a Multi-Gene Approach
Authors: Giammarioli Monica , Torresi Claudia , Biccheri Roberta , Cammà Cesare , Marcacci Maurilia , Dondo Alessandro , Razzuoli Elisabetta , Fusco Giovanna , Casalinuovo Francesco , Scicluna Maria Teresa , Dei Giudici Silvia , Martin Ana Maria Moreno , Rossi Elisabetta , Casciari Cristina , Pela Michela , Iscaro Carmen , Gallardo Carmina , Marocco Gaia , Orrico Mario , Feliziani Francesco
Published: July 2024

The first report of African swine fever virus (ASFV) genotype II in Italy in 2022 marked the beginning of a significant invasion in at least eight Italian regions with different infection clusters. In this study, we used the multi-gene approach to investigate the epidemiological associations between ASFV strains causing cases and outbreaks in wild boar and pigs in Italy from January 2022 to the end of 2023. Our results confirm that all the tested ASFV-positive Italian samples belonged to genotype II and show high homology with genotype II ASFV sequences previously collected in Eurasian countries. Molecular characterization revealed the presence of four genetic groups in Italy. The majority of African swine fever (ASF) samples analyzed in the current study (72%) belonged to genetic group 3, which was the most representative in Europe. The results also provide evidence of the prevalence of genetic group 19 (15.9%). In addition, we identified new putative genetic groups, genetic group 25 (9.1%) and genetic group 26 (3.0%), which have never been described before. This is the first detailed report on the molecular characterization of more than 130 ASFV strains circulating in Italy.
An Overview of the Characteristics, Pathogenesis, Epidemiology, and Detection of Human Enterovirus in the Arabian Gulf Region
Authors: Ayyub Mohammed , Thomas Joshua George , Hodeify Rawad
Published: July 2024

Enteroviruses are RNA viruses that initiate infections through the gastrointestinal (GI) tract and are associated with enteric illness in individuals of all ages. Most serious infections of enteroviruses are in infants and young children where it is the common cause of aseptic meningitis and other systemic diseases, leading to a high mortality rate. Enteroviruses belong to the small non-enveloped family of the Picornaviridae family. The virus can spread mainly through fecal–oral and respiratory routes. In the Arabian Gulf countries, the incidence of enteroviral infections is only restricted to a few reports, and thus, knowledge of the epidemiology, characteristics, and pathogenesis of the virus in the gulf countries remains scarce. In this minireview, we sought to provide an overview of the characteristics of enterovirus and its pathogenesis, in addition to gathering the reports of enterovirus infection prevalence in Gulf Cooperation Council (GCC) countries. We also present a summary of the common methods used in its detection.
Spatio-Temporal Variability of Water Quality in the Middle Danube—The Influence of Air Temperature and Discharge
Authors: Grzywna Antoni , Grabić Jasna , Różańska-Boczula Monika , Vranešević Milica
Published: July 2024

Large watercourses are characterised by significant spatial and temporal changes in water quality due to both natural and anthropogenic impacts. The paper analyses changes in the Danube’s spatial and seasonal water quality in its middle part at five monitoring stations for the period 2018–2022. Examined water quality parameters include oxygen saturation (Os), ammonium (N-NH4), pH, 5-day biochemical oxygen demand (BOD), nitrate nitrogen (N-NO3), orthophosphates (P-PO4), suspended solids (SS), electrical conductivity (EC), and water temperature (WT). Furthermore, the analysis took into account the influence of two additional factors: air temperature (AT) and discharge (D). Throughout the entire period under study, all parameters were characterised by low concentration values, which met the environmental objective of good ecological status. The use of multivariate statistical methods allowed for the identification of EC, N-NH4, WT, Os, SS, and N-NO3 as determining the greatest spatio-seasonal variability of water quality in a selected section of the Danube. Regression models determined WT, EC and nitrogen nitrate changes as depending on AT, flow, and exposure time. Knowing models not only gives a better understanding of the dynamics of changes in water quality in the stretch of the Danube under study but potentially allows the prediction of these parameters based on easily measurable environmental variables.
Timescales of Ecological Processes, Settling, and Estuarine Transport to Create Estuarine Turbidity Maxima: An Application of the Peter–Parker Model
Authors: Engel Lilian , Stacey Mark
Published: July 2024

The estuarine exchange flow increases the longitudinal dispersion of passive tracers and trap sinking particles, potentially creating an estuarine turbidity maximum (ETM): a localized maximum of suspended particulate matter concentration in an estuary. The ETM can have many implications: dead zones due to increased turbidity or hypoxia from organic matter decomposition, naval navigation challenges, and other water quality problems. Using timescales, we investigate how the interaction between exchange flow and particle sinking leads to ETMs by modeling a sinking tracer in an idealized box model of the Total Exchange Flow (TEF) first developed by Parker MacCready. Results indicate that the balance of particle sinking and vertical mixing is critical to determining ETM size and location. We then focus on the role of ecology in ETM formation through the use of the Peter–Parker Model, a new biophysical model which combines the TEF box model with a Nutrient–Phytoplankton–Zooplankton–Detritus (NPZD) model, the likes of which were first developed by Peter J.S. Franks. Detritus sinking rates similarly influence detritus peak concentration and location (an ETM), but detritus ETMs occur in a different location than the sinking tracer due to the influence of biological factors, which create a time lag of about 1 day. Lastly, we characterize the flow of the models with a dimensionless parameter that compares timescales and summarizes the dynamics of the sinking tracer in ETM formation and that can be used across systems.
Spatial Analysis of Aquatic Ecological Health under Future Climate Change Using Extreme Gradient Boosting Tree (XGBoost) and SWAT
Authors: Woo Soyoung , Kim Wonjin , Jung Chunggil , Lee Jiwan , Kim Yongwon , Kim Seongjoon
Published: July 2024

Climate change not only affects the water resource system but also has a great impact on the aquatic ecosystem, which is complexly linked to various organic and inorganic matter. It is difficult to simulate the current aquatic ecosystem and predict the future system due to the immensity and complexity of aquatic ecosystems; however, a spatial analysis of future aquatic ecological health is necessary if we are to adapt and take action against future climate change. In this study, we evaluated the aquatic ecological health of the Han River basin under the future climate change RCP4.5 and RCP8.5 scenarios using three indices: fish assessment index (FAI), trophic diatom index (TDI), and benthic macroinvertebrate index (BMI). For this, we developed the SWAT-XGBoost linkage algorithm, and the algorithm accuracy for the FAI, TDI, and BMI was 89.3~95.2%. In the case of the FAI and BMI assessment of aquatic ecological health, the upstream Han River was classified as a hot spot. In the case of the TDI, the downstream area of the Han River was classified as a cold spot. However, as the current TDI downstream was classified as grades D and E, continuous management is needed.
Microbial Selection for the Densification of Activated Sludge Treating Variable and High-Strength Industrial Wastewater
Authors: Ahmed Mukhtiar , Goettert Dorothee , Vanherck Catharina , Goossens Koen , Dries Jan
Published: July 2024

This study investigates the densification/granulation of activated sludge with poor settleability, treating real industrial wastewater from a tank truck cleaning company. The wastewater is low in nutrients, acidic in nature, and high and variable in chemical oxygen demand (COD, ranging from 2770 mg·L−1 to 14,050 mg·L−1). A microbial selection strategy was applied to promote slow-growing glycogen-accumulating microorganisms (GAO) by the implementation of an anaerobic feast/aerobic famine strategy in a sequencing batch reactor (SBR). After 60 to 70 days, the uptake of carbon during the anaerobic phase exceeded 80%, the sludge morphology improved, and the sludge volume index (SVI) dropped below 50 mL·g−1. 16S rRNA gene sequencing showed the enrichment of the GAOs Defluviicoccus and Candidatus Competibacter. Stable sludge densification was maintained when using a constant organic loading rate (OLR) of 0.85 ± 0.05 gCOD·(L·d)−1, but the sludge quality deteriorated when switching to a variable OLR. In view of the integration of densified/granular sludge in a membrane bioreactor configuration, the filtration properties of the densified SBR sludge were compared to the seed sludge from the full-scale plant. The densified sludge showed a significantly lower resistance due to pore blockage and a significantly higher sustainable flux (45 vs. 15 L·(m2·h)−1).
Urban Stormwater Management: A Sustainable Approach
Authors: Karamoutsou Lina , Veliou Elisavet , Kvernberg Eivind Bigum , Psilovikos Aris
Published: July 2024

Climate change is impacting urban areas, especially through extreme rainfall that stresses conventional water management systems. Rainwater resulting from impervious runoffs, stormwater leads to an increase in the amount of wastewater that requires treatment and an overflow of the combined sewer system. Therefore, untreated wastewater is released into the surroundings or, in some cases, causes damage to urban systems. Nevertheless, many cities in the world are in the process of establishing a sustainable approach to urban water management. Sustainable stormwater management practices are essential for overcoming various environmental challenges and promoting community sustainability and resilience. The purpose of this paper is to communicate Oslo’s success in implementing sustainable stormwater management in urban areas. By analyzing successful cases, researchers may be able to record patterns that offer potential answers to the stormwater management challenge. The present case study presents an approach that can enlighten urban planners and policymakers about the potential outcomes of sustainable stormwater management under the conditions presented.
The Technology Innovation of Hybrid Electric Vehicles: A Patent-Based Study
Authors: Zhu Yan , Wu Jie , Gaidai Oleg
Published: July 2024

A hybrid electric vehicle (HEV) is a relatively practical technology that has emerged as electric vehicle technology has gradually matured. The analysis of the HEV patent lifecycle is crucial for understanding its impact on the development of this technology. This lifecycle tracks the progress of HEV technologies from their inception and patenting, through their market adoption, and to the expiration of their patent protection. In this study, we aimed to evaluate the technology lifecycle of the HEV industry using the growth S-curve method. The purpose of this study is to describe the technological lifecycle trajectory and current stage of the HEV industry, as well as the technical stages of each sub-technology, to facilitate better decision making. As part of this study, we used patent family data collected from the Derwent Innovation Index database from 1975 to 2022 and established an S-curve model for HEVs and their sub-technologies using logistic regression. In 2022, the technological maturity of HEVs reached 44%. The sub-technologies with the most substantial diffusion capabilities are energy management, propulsion systems, and cooling circuits. According to predictions, the saturation period for the patent family quantity related to HEVs is estimated to be around 53 years.
Optimal Fast-Charging Strategy for Cylindrical Li-Ion Cells at Different Temperatures
Authors: Jaguemont Joris , Darwiche Ali , Bardé Fanny
Published: July 2024

Ensuring efficiency and safety is critical when developing charging strategies for lithium-ion batteries. This paper introduces a novel method to optimize fast charging for cylindrical Li-ion NMC 3Ah cells, enhancing both their charging efficiency and thermal safety. Using Model Predictive Control (MPC), this study presents a cost function that estimates the thermal safety boundary of Li-ion batteries, emphasizing the relationship between the temperature gradient and the state of charge (SoC) at different temperatures. The charging control framework combines an equivalent circuit model (ECM) with minimal electro-thermal equations to estimate battery state and temperature. Optimization results indicate that at ambient temperatures, the optimal charging allows the cell’s temperature to self-regulate within a safe operating range, requiring only one additional minute to reach 80% SoC compared to a typical fast-charging protocol (high current profile). Validation through numerical simulations and real experimental data from an NMC 3Ah cylindrical cell demonstrates that the simple approach adheres to the battery’s electrical and thermal limitations during the charging process.
Стан нормативного та методичного забезпечення вимірювань
Authors: Чижик І. В. , Солоненко І. М.
Published: July 2024

Розглядаються проблемні питання, пов'язані з недостатнім забезпеченням підприємств нормативними документами, що регламентують методики вимірювань.
Розглядаються рекомендації Національного органу стандартизації стосовно застосування скасованих міждержавних стандартів, які не замінені національними стандартами України, надаються коментарі.
Зазначаються проблеми використання існуючої нормативної бази для вимірювальних підрозділів, викликані несумісністю з діючими нормативно-правовими актами та нормативними документами.
Пропонуються шляхи вирішення наведених проблем для підприємств, що виконують вимірювання та претендують на певне визнання вимірювальних можливостей.
A Chitchat on Using ChatGPT for Cheating
Authors: Tirumala Sreenivas Sremath , Mayhew Chris
Published: July 2024

With the rapid increase in the usage of artificial intelligence, there has been considerable impact on how AI tools are utilised for academic misconduct. Catching this behaviour has been a big challenge, as learners have developed approaches to remove traces and footprints that indicate possible usage of AI tools. Tools such as Turnitin can check for originality or plagiarism, but provide very little assistance in differentiating AI- and non-AI-generated works. Generative tools such as ChatGPT, Bard and Copilot are posing challenges to academic staff in identifying misconduct. This research aims to emphasise the importance of investigating various approaches to tackle academic misconduct, particularly in computer science courses that involve a considerable amount of coding. This research looks at various resources that learners may use and go undetected, particularly in coding and presentations.
Can hDAS Produce Tailored Instructional Design Methods, for the Design of Technology-Based VET Interventions?
Authors: Cochrane Todd
Published: July 2024

Hybrid educational design-based agile software development (hDAS) for producing tailored instructional design has been applied in the development of multi-user virtual environments. hDAS is being developed and applied in three contexts that provide new feed into the design and implementation of hDAS processes. The first two contexts are the design and implementation of a short course that introduces AI using a pretrained AI model to implement gesture-based game control, and vine-pruning worker training for the Regional Skills Employer programme. The third context applies hDAS in the design of computationally theoretic graphs to model learning systems. Undertaking research on hDAS systems on relatively different projects triangulates the application of the designed systems and enhances hDAS. This paper presents a summary of those projects and presents a brief reflection on the ongoing development of hDAS.
ANALISIS PENGENDALIAN KUALITAS UNTUK MENGURANGI DEFECT PADA GLASS BOTTLE DENGAN MENGGUNAKAN METODE QUALITY CONTROL CIRCLE PT MULIAGLASS CONTAINER DIVISION CIKARANG JAWA BARAT
Authors: Dadang Surya Kencana  , Elis Chalisyah  , Yollanda Riswana Azhari
Published: July 2024

PT Muliaglass Container Division is a subsidiary of PT Mulia Industrindo, Tbk which is engaged in the glass industry by producing flat glass, glass block, glass packaging, and automotive safety glass as a result of its production. PT Muliaglass Container Division was founded in 1989. The quality control carried out by PT Muliaglass Container Division experienced problems in the Quality Control section or checking checkers, resulting in the defect pass rate so far exceeding the tolerance limits set by the company. There are several types of product defects in glass bottle packaging at PT Muliaglass Container Division, namely Check Ring, Check Under Ring, Leaner, Hot Mold Check, and others. To overcome the problems encountered, research is needed using the Quality Control Circle Method and Statistical Quality Control which are used to calculate how big the reasonable limit is in the product pass rate. After processing Statistical Quality Control data and knowing the number of acceptable quality labels for passing controlled defects or not, proceed with the Quality Control Circle Method, to find out what causes product defects to pass.
Moving Beyond Medical Statistics: A Systematic Review on Missing Data Handling in Electronic Health Records
Authors: Ren Wenhui , Liu Zheng , Wu Yanqiu , Zhang Zhilong , Hong Shenda , Liu Huixin ,   on behalf of the Missing Data in  Electronic health Records (MINDER) Group
Published: July 2024

Background:
Missing data in electronic health records (EHRs) presents significant challenges in medical studies. Many methods have been proposed, but uncertainty exists regarding the current state of missing data addressing methods applied for EHR and which strategy performs better within specific contexts.
Methods:
All studies referencing EHR and missing data methods published from their inception until 2024 March 30 were searched via the MEDLINE, EMBASE, and Digital Bibliography and Library Project databases. The characteristics of the included studies were extracted. We also compared the performance of various methods under different missingness scenarios.
Results:
After screening, 46 studies published between 2010 and 2024 were included. Three missingness mechanisms were simulated when evaluating the missing data methods: missing completely at random (29/46), missing at random (20/46), and missing not at random (21/46). Multiple imputation by chained equations (MICE) was the most popular statistical method, whereas generative adversarial network-based methods and the k nearest neighbor (KNN) classification were the common deep-learning-based or traditional machine-learning-based methods, respectively. Among the 26 articles comparing the performance among medical statistical and machine learning approaches, traditional machine learning or deep learning methods generally outperformed statistical methods. Med.KNN and context-aware time-series imputation performed better for longitudinal datasets, whereas probabilistic principal component analysis and MICE-based methods were optimal for cross-sectional datasets.
Conclusions:
Machine learning methods show significant promise for addressing missing data in EHRs. However, no single approach provides a universally generalizable solution. Standardized benchmarking analyses are essential to evaluate these methods across different missingness scenarios.