bluuebunny/crossref_metadata_2025 huggingface dataset:
AI4PD—Towards a Standardized Interconnection of Artificial Intelligence Methods with Product Development Processes
Authors: Gerschütz Benjamin , Goetz Stefan , Wartzack Sandro
Published: February 2023

The transformation of virtual product development to Digital Engineering (DE) requires the successful integration of Digital Engineering or data-driven methods into existing product development processes. Those methods allow for the analysis and usage of existing data. However, missing knowledge about these methods, as well as their performance or limitations, is a major burden for their application, especially in small and medium-sized enterprises. In order to close this gap, this paper proposes the AI4PD ontology, linking product development processes (PD) and Digital Engineering methods (AI). This knowledge representation gives companies an overview of the available methods to support them in selecting a suitable solution for their problems. The representation of AI4PD is performed in Protégé using the W3C standard OWL syntax. The opportunities of AI4PD are shown by a use case of identifying a DE-Method for predicting manufacturing possibilities based on test data and CAD files. Furthermore, after possible problems in existing product development processes are identified, AI4PD covers the necessary knowledge for a successful method of identification and integration to transform virtual product development to Digital Engineering.
Are Green Buildings an Indicator of Sustainable Development?
Authors: Marotta Antonio , Porras-Amores César , Rodríguez Sánchez Antonio
Published: February 2023

The world’s population keeps growing together with the construction rate of buildings that need to reduce their environmental footprint in order to mitigate global warming. This paper analyses if the spread of green buildings can be used as an indicator of broader sustainable development. The study is carried out with data taken from Eurostat Database and green buildings directories for 27 EU countries in the 10-year period spanning from 2010 to 2019. The relationship between the indicators is examined through simple linear regressions, and the results confirm the Environmental Kuznets Curve hypothesis: in developed countries, a growing economy (more GDP) is related to an environmental improvement (fewer GHG emissions). In addition, this study proves that the variance of green buildings expresses with a consistent probability the variance of GDP per capita (p-value = 0.0004 and R2 = 0.8475) and the variance of GHG emissions (p-value = 0.0002 and R2 = 0.8825), meaning that green buildings are indeed an indicator of sustainable development. This is due to the upfront cost required to implement advanced construction technologies that ultimately cut GHG emissions during the building lifecycle. This also points out that policy makers should encourage green building implementation through tax relieves and grants.
An Efficient Computational Approach for Inverse Kinematics Analysis of the UR10 Robot with SQP and BP-SQP Algorithms
Authors: Huang Yizhe , Liu Jiaen , Zhang Xuwei , Wang Jun , Li Xiao , Tu Xikai , Chen Shuisheng , Wang Chenlin , Huang Qibai
Published: February 2023

Two algorithms that are distinct from the closed algorithm are proposed to create the inverse kinematics model of the UR10 robot: the Sequential Quadratic Programming (SQP) algorithm and the Back Propagation-Sequential Quadratic Programming (BP-SQP) algorithm. The SQP algorithm is an iterative algorithm in which the fundamental tenet is that the joint’s total rotation radian should be at a minimum when the industrial robot reaches the target attitude. With this tenet, the SQP algorithm establishes the inverse kinematics model of the robot. Since the SQP algorithm is overly reliant on the initial values, deviations occur easily and the solution speed, and the accuracy of the algorithm is undermined. To assuage this disadvantage of the SQP algorithm, a BP-SQP algorithm incorporating a neural network is introduced to optimize the initial values. The results show that the SQP algorithm is an iterative algorithm that relies excessively on the initial values and has a narrow range of applications. The BP-SQP algorithm eliminates the limitations of the SQP algorithm, and the time complexity of the BP-SQP algorithm is greatly reduced. Subsequently, the effectiveness of the SQP algorithm and the BP-SQP algorithm is verified. The results show that the SQP and BP-SQP algorithms can significantly reduce the operation time compared with the closed algorithm, and the BP-SQP algorithm is faster but requires a certain number of samples as a prerequisite.
Detection of Inappropriate Tweets Linked to Fake Accounts on Twitter
Authors: Alsubaei Faisal S.
Published: February 2023

It is obvious that one of the most significant challenges posed by Twitter is the proliferation of fraudulent and fake accounts, as well as the challenge of identifying these accounts. As a result, the primary focus of this paper is on the identification of fraudulent accounts, fake information, and fake accounts on Twitter, in addition to the flow of content that these accounts post. The research utilized a design science methodological approach and developed a bot account referred to as “Fake Account Detector” that assists with the detection of inappropriate posts that are associated with fake accounts. To develop this detector, previously published tweets serve as the datasets for the training session. This data comes from Twitter and are obtained through the REST API. The technique of machine learning with random forest (RF) is then used to train the data. The high levels of accuracy (99.4%) obtained from the RF detection results served as the foundation for the development of the bot account. This detector tool, developed using this model, can be utilized by individuals, businesses, and government agencies to assist in the detection and prevention of Twitter problems related to fake news and fake accounts.
Aspects of Cyber Security in Autonomous and Connected Vehicles
Authors: Mudhivarthi Bhavesh Raju , Thakur Prabhat , Singh Ghanshyam
Published: February 2023

An automobile is a computer on wheels after the integration of electronics. This handshake of electronics and mechanical systems makes a vehicle smart, and comfortable; driver assistance for achieving this involves data exchange and surroundings sensing. Devices such as sensors, telematics, protocols, etc., are responsible for data exchange and data sensing. This process contains some loopholes that are the preliminary sources for the attacker to attack the vulnerable devices to control the vehicle. This article provides a review of possible attacks and defenses on autonomous and connected vehicles. The attacker’s area of autonomous and connected vehicles is classified into three categories that are safety system attacks, connectivity attacks, and diagnostics attacks, and provided all possible defenses for those attacks. In addition, we provided an analysis of the domain to understand the scenarios in this domain, recommendations, and future scope in this area for further work.
Ceramic Matrix Composites for Aero Engine Applications—A Review
Authors: Karadimas George , Salonitis Konstantinos
Published: February 2023

Ceramic matrix materials have attracted great attention from researchers and industry due to their material properties. When used in engineering systems, and especially in aero-engine applications, they can result in reduced weight, higher temperature capability, and/or reduced cooling needs, each of which increases efficiency. This is where high-temperature ceramics have made considerable progress, and ceramic matrix composites (CMCs) are in the foreground. CMCs are classified into non-oxide and oxide-based ones. Both families have material types that have a high potential for use in high-temperature propulsion applications. The oxide materials discussed will focus on alumina and aluminosilicate/mullite base material families, whereas for non-oxides, carbon, silicon carbide, titanium carbide, and tungsten carbide CMC material families will be discussed and analyzed. Typical oxide-based ones are composed of an oxide fiber and oxide matrix (Ox-Ox). Some of the most common oxide subcategories are alumina, beryllia, ceria, and zirconia ceramics. On the other hand, the largest number of non-oxides are technical ceramics that are classified as inorganic, non-metallic materials. The most well-known non-oxide subcategories are carbides, borides, nitrides, and silicides. These matrix composites are used, for example, in combustion liners of gas turbine engines and exhaust nozzles. Until now, a thorough study on the available oxide and non-oxide-based CMCs for such applications has not been presented. This paper will focus on assessing a literature survey of the available oxide and non-oxide ceramic matrix composite materials in terms of mechanical and thermal properties, as well as the classification and fabrication methods of those CMCs. The available manufacturing and fabrication processes are reviewed and compared. Finally, the paper presents a research and development roadmap for increasing the maturity of these materials allowing for the wider adoption of aero-engine applications.
Geothermal Anomalies and Coupling with the Ionosphere before the 2020 Jiashi Ms6.4 Earthquake
Authors: Jia Donghui , Yu Huaizhong , Zhao Binbin , Ma Yuchuan
Published: February 2023

Rock temperature reflects the adjustment in crustal stress, and the fluctuation of ionospheric electron concentration is closely related to short-term disturbances of the stress field. Their coupling may reveal short-term effects before strong earthquakes. This study explores the rock temperature changes and mechanical-electrical coupling in the lithosphere–ionosphere before the Jiashi Ms6.4 earthquake on 19 January 2020. The observed data were detrended by general polynomial piecewise fitting; three observation points within 150 km of the epicenter were found to show significant temperature fluctuations in the 15 days before the earthquake. The peak occurred synchronously five days before the earthquake, and the variation range was approximately 10−3 orders of magnitude. Five days before the earthquake, the electromagnetic satellite Zhangheng-1 synchronously observed an anomalous electron concentration in orbit near the epicenter, with a maximum value of 2.01 × 1010 m−3. The loading/unloading response ratio (LURR) was calculated using small earthquakes within 100 km of the epicenter; it showed that the large changes in rock temperature and the ionosphere occurred at high LURR, indicating high-stress accumulation in the region. Various anomalies appeared simultaneously and may indicate fault rupture, which may be caused by an acoustic-gravity wave, indicating a synchronous coupling between the lithosphere atmosphere and the ionosphere.
Dynamic Characteristics of Urban Rail Train in Multivehicle Marshaling under Traction Conditions
Authors: Zhang Yichao , Yang Jianwei , Wang Jinhai , Zhao Yue
Published: February 2023

In recent years, urban rail transportation has rapidly developed in China and become one of the most important modes of travel. Most existing studies on the dynamic characteristics of urban rail trains have been based on single-section trains, and there have been fewer studies on marshaling urban rail trains that incorporate traction transmission systems. The dynamic performance of each carriage directly affects the operational reliability and even the running safety of urban rail trains. For this reason, in this paper, a marshaling urban rail train model with a traction transmission system was established and its accuracy was validated by field tests. This dynamics model enables the consideration of the coupling interactions between the gear transmission motion, the vertical, the lateral and the longitudinal motions of the vehicle. First, the model accuracy was validated by field tests. Then, the relationship between the motor torque and the running time of the urban rail train under traction conditions was calculated. Finally, the dynamic performance of each car of the marshaling train was studied. The research results show that there is a clear difference between the dynamics of the motor car and the trailer, and that the motor car is significantly inferior to the trailer. Among the four motor cars, the dynamic performances of the first and last moving cars were worse than those of the other motor cars. Among the two trailers, the trailer at the back was worse than the trailer at the front. The traction transmission system has a greater impact on the vertical and lateral vibration of the train bogie frame and wheelset, but the impact on the vibration of the car body is negligible. This paper provides theoretical support for the research one train dynamic performance optimization and operation safety.
The Application of Transition Metal Sulfide Nanomaterials and Their Composite Nanomaterials in the Electrocatalytic Reduction of CO2: A Review
Authors: Parsons Jason , Alotaibi Mataz
Published: February 2023

Electrocatalysis has become an important topic in various areas of research, including chemical catalysis, environmental research, and chemical engineering. There have been a multitude of different catalysts used in the electrocatalytic reduction of CO2, which include large classes of materials such as transition metal oxide nanoparticles (TMO), transition metal nanoparticles (TMNp), carbon-based nanomaterials, and transition metal sulfides (TMS), as well as porphyrins and phthalocyanine molecules. This review is focused on the CO2 reduction reaction (CO2RR) and the main products produced using TMS nanomaterials. The main reaction products of the CO2RR include carbon monoxide (CO), formate/formic acid (HCOO−/HCOOH), methanol (CH3OH), ethanol (CH3CH2OH), methane (CH4), and ethene (C2H4). The products of the CO2RR have been linked to the type of transition metal–sulfide catalyst used in the reaction. The TMS has been shown to control the intermediate products and thus the reaction pathway. Both experimental and computational methods have been utilized to determine the CO2 binding and chemically reduced intermediates, which drive the reaction pathways for the CO2RR and are discussed in this review.
Intelligent Recognition of Key Earthquake Emergency Chinese Information Based on the Optimized BERT-BiLSTM-CRF Algorithm
Authors: Wang Zhonghao , Huang Meng , Li Chenxi , Feng Jilin , Liu Shuai , Yang Guang
Published: February 2023

To address the problems of the text of earthquake emergency information keeps changing incrementally with the time of an earthquake’s occurrence and there being more and more information categories, thus making it difficult to identify earthquake emergency key information, this paper proposes an intelligent recognition algorithm of earthquake emergency information based on the optimized BERT-BiLSTM-CRF algorithm. Based on the historical seismic emergency information dataset of the past 10 years, first, the BIO sequence labeling method is used to classify the seismic entities, and the BERT pretraining model is constructed to represent the seismic emergency text with sentence-level feature vectors. The BiLSTM algorithm is used to obtain the contextual information of the bidirectional seismic emergency text, and we introduce the attention mechanism to enhance the recognition effect of the seismic emergency key information in the statements. Finally, we use conditional randomization to enhance the recognition of earthquake emergency key information in the utterance. The conditional randomization algorithm is applied to extract the dependency relationship between adjacent vectors and improve the accuracy identification to realize the intelligent recognition of earthquake emergency information. The experimental results show that our model can extract earthquake emergency information from online media efficiently and accurately, with better performance than other baseline models.
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
Authors: Ali Tariq Emad , Chong Yung-Wey , Manickam Selvakumar
Published: February 2023

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an SVM-based DDoS detection model shows superior performance. This comparative analysis offers a valuable insight into the development of efficient and accurate techniques for detecting DDoS attacks in SDN environments with less complexity and time.
Graph-Augmentation-Free Self-Supervised Learning for Social Recommendation
Authors: Xiang Nan , Ma Xiaoxia , Liu Huiling , Tang Xiao , Wang Lu
Published: February 2023

Social recommendation systems can improve recommendation quality in cases of sparse user–item interaction data, which has attracted the industry’s attention. In reality, social recommendation systems mostly mine real user preferences from social networks. However, trust relationships in social networks are complex and it is difficult to extract valuable user preference information, which worsens recommendation performance. To address this problem, this paper proposes a social recommendation algorithm based on multi-graph contrastive learning. To ensure the reliability of user preferences, the algorithm builds multiple enhanced user relationship views of the user’s social network and encodes multi-view high-order relationship learning node representations using graph and hypergraph convolutional networks. Considering the effect of the long-tail phenomenon, graph-augmentation-free self-supervised learning is used as an auxiliary task to contrastively enhance node representations by adding uniform noise to each layer of encoder embeddings. Three open datasets were used to evaluate the algorithm, and it was compared to well-known recommendation systems. The experimental studies demonstrated the superiority of the algorithm.
An Artificial Network-Based Prediction of Key Reference Zones on Axial Stress–Strain Curves of FRP-Confined Concrete
Authors: Fallah Pour Ali , Gholampour Aliakbar
Published: February 2023

The accurate prediction of reference points on the axial stress–axial strain relationship of fiber-reinforced polymer (FRP)-confined concrete is vital to pre-design structures made with this system. This study uses an artificial neural network (ANN) for predicting hoop rupture strain (εh,rup) and transition zone, namely transition strain (εc1) and stress (f’c1), on axial stress–strain curves of FRP-confined concrete. These are key parameters for estimating a transition zone of stress–strain curves. In this study, accompanied with these parameters, ultimate condition parameters, including compressive strength and ultimate axial strain, were predicted using a comprehensive database. Various combinations of input data and ANN parameters were used to increase the accuracy of the predictions. A sensitivity analysis and a model validation assessment were performed to evaluate the predictability of the developed models. At the end, a comparison between the proposed models in this study and existing ANN and design-oriented models was presented. It is shown that the accuracy of the developed ANN models in this study is higher or comparable to that of existing ANN models. Additionally, the developed models in this study to predict f’c1 and εc1 exhibit a higher accuracy compared to existing design-oriented models. These results indicate that the proposed ANN models capture the lateral confinement effect on ultimate and transition zones of FRP-confined concrete with a more robust performance compared to existing models.
History Haunting the Present: Re-Interpreting the Truth in Contemporary Art of Iran
Authors: Keshmirshekan Hamid
Published: February 2023

This article examines the notions of history and memory with references to the works of contemporary artists from Iran. It interrogates the theme of challenging the present through the re-interpretation of history and investigates how artists respond to social, cultural and political conditions by creating a multi-faceted aesthetics of resistance. While looking at the broader subject of history and memory in contemporary Iran, the article scrutinises the works of artists who have been involved in themes such as the embodiment of cultural memory, concern for truth, historical record and intellectual reference to history to reflect the present. I adopt a hauntological interpretation when reading works of artists as it corresponds to their recurring references to the past to invoke an unsettling view of an imagined future.
Statistical Seismo-Ionospheric Influence with the Focal Mechanism under Consideration
Authors: Li Mei , Yang Zhigao , Song Jin , Zhang Yongxian , Jiang Xianghua , Shen Xuhui
Published: February 2023

This research aims to statistically investigate seismo-ionospheric influence related to strong earthquakes with different focal mechanisms. The nighttime O+ density and electron density, measured by the CSES satellite for about 3 years and by the DEMETER satellite for 6 years, were utilized to globally search for ionospheric perturbations with different datasets. Data on strong M ≥ 6.0 earthquakes with focal mechanism information within a ±45° geographic latitude were collected during the periods considered. A comparison was automatically performed using software to correlate these ionospheric variations and earthquakes under the condition that a perturbation occurred at a horizontal distance less than 1500 km from the epicenter and up to 15 days before the earthquake. The Kp index was maintained as less than 3 in this timeframe to reduce the effects of geomagnetic activities. Combined with statistical results provided by four groups of rupture and strike-slip earthquakes corresponding to both satellites, it was shown that the averaged ionospheric number of rupture earthquakes is slightly higher than that obtained from strike-slip events, on which basis it seems that, averagely, rupture earthquakes tend to give rise to a heavier influence on the ionosphere than strike-slip ones. Furthermore, this conclusion was comparatively confirmed by commonly detected earthquakes and random events completely for the CSES satellite and partly for the DEMETER satellite. At the same time, we did not gain a firm conclusion regarding the detection rates corresponding to these two types of earthquakes. Thus, further investigations will be necessary as more data are collected.
Meteorological Influences on Short-Term Carbon-Water Relationships in Two Forests in Subtropical China
Authors: Pan Jihua , Liu Jane , Yang Mengmiao , Wang Rong
Published: February 2023

Carbon and water fluxes in ecosystems are tightly coupled by gas diffusion through stomata. However, carbon–water (C–W) relationships vary largely across time scales, vegetation types, and regions. Subtropical forests in China play an important role in the global carbon and water cycles, yet studies of C–W relationships in this region remain limited. Here, we investigated summer-time C–W relationships in this region at two subtropical sites: the evergreen broadleaved forest at Dinghushan (23.17° N, 112.53° E, 300 m) and the evergreen coniferous forest at Qianyanzhou (26.74° N, 115.06° W, 106 m), using the flux tower data from the FLUXNET2015. The C–W relationship was examined using two measures. The first was daily water use efficiency (WUE), which is the ratio of daily gross primary productivity (GPP) to evapotranspiration (ET). The second was the correlation coefficient (r) of hourly GPP and ET. Our analysis showed that the daily WUE in the two forests ranged over 4–14 mg CO2 per g H2O, higher in the coniferous forest than in the broadleaved forest. The mean values of r for hourly C–W coupling were similar at the two forests, being 0.5–0.6, which suggests asynchronous diurnal variations in GPP and ET. Both daily WUE and r were modulated by meteorological conditions. In general, high radiation, air temperature, and humidity can reduce WUE at both sites. For the broadleaved forest, the most influential factor on WUE was VPD, followed by radiation, while in the coniferous forest, VPD, air temperature, and radiation were almost equally important. For hourly C–W coupling, VPD plays a significant role. The drier the air is, the weaker the coupling in the two forests. The daily WUE and hourly C–W coupling reflect the C–W relationship from different perspectives. Both showed the strongest response to VPD but with different sensitivity.
Impact of Building Energy Mitigation Measures on Future Climate
Authors: Pokhrel Rabindra , Gonzalez Jorge E. , Ramamurthy Prathap , Comarazamy Daniel
Published: February 2023

As cities are increasing technological efficacy on greenhouse gas (GH) emission reduction efforts, the surrounding urban ecosystems and natural resources may be affected by these measures. In this research, climate indicators such as heat index, extreme heat events, intensified urban heat islands (UHIs), and sea breeze are projected for the middle and end of the 21st century to understand the climate change signal on these variables with and without building energy mitigation measures. Cities amplify extreme heat and UHI impacts by concentrating large populations and critical infrastructure in relatively small areas. Here, we evaluate the combined climate and building energy mitigation impacts on localized climate metrics throughout the 21st century across extreme emission scenarios (RCP8.5) for the tropical coastal city of San Juan. The analysis of statistically downscaled global circulation model outputs shows underestimation for uncorrected summer daily maximum temperatures, leading to lower extreme heat intensity and duration projections from the present time which are corrected using bias-corrected techniques. High-resolution dynamic downscaling simulations reveal a strong dependency of changes in extreme heat events in urban settings, however, the intensities shift to lower-level grasslands and croplands with energy mitigation measures (combination of white roof, tilted photovoltaic roof, and efficient heating ventilation and air conditioning systems). The building energy mitigation measures have the potential of reducing the UHI intensities to 1 °C and 0.5 °C for the 2050 and 2100 climate periods, respectively.
Impacts of Tibetan Plateau Spring Snowmelt on Spring and Summer Precipitation in Northwest China
Authors: Wang Zhilan , Yang Kai , Zhang Feimin , Zhang Jinyu , Sun Xuying
Published: February 2023

Snow on the Tibetan Plateau (TP) is an important signal for the prediction of East Asian climate. In this study, the relationship between the TP spring snowmelt and spring and summer precipitation in Northwest China (NWC) was investigated, along with the possible mechanisms linked to the impacts of snowmelt on precipitation. The results showed that the TP spring snowmelt had significant impacts on spring and summer precipitation in NWC. For example, when there was a large spring snowmelt in the central- eastern TP, the spring and summer precipitation in the Hexi Corridor and southeast NWC was excessive, especially in summer; when there was a large spring snowmelt in the northern TP, the spring and summer precipitation was deficient across the whole of NWC, while a large spring snowmelt in the western TP led to deficient spring and summer precipitation in eastern NWC but excessive precipitation in western NWC. The possible mechanisms for this included the fact that more spring snowmelt over the TP led to higher soil moisture contents, which further resulted in weakened subtropical westerly and enhanced ridge over Xinjiang. By changing the TP thermal forcing, these anomalous atmospheric circulation conditions transported water vapor into NWC, thus creating excessive summer precipitation in that region.
Sensitivity Analysis of Pipe–Soil Interaction Influencing Factors under Frost Heaving
Authors: Huang Long , Sheng Yu , Chen Liping , Peng Erxing , Huang Xubin , Zhang Xiyan
Published: February 2023

The mechanism of pipe–soil interaction under frost heaving is complicated due to many factors affecting the pipe–soil system. In order to analyze the sensitivity of various pipe–soil interaction influencing factors and highlight the relationship between the factors and the pipe’s mechanical characteristics during frost heaving, a pipe–soil interaction model based on a semi-infinite elastic frozen soil foundation is developed. Besides, the mechanical indices characterizing the influence factors and their change law are emphatically explored. The results show that the pipe stress changes most obviously at the transition region between the frost-heaving and non-frost-heaving regions. The equivalent stress increases nonlinearly with the increase of foundation coefficient, linearly with the increase of frost heave and elastic modulus of pipe, and decreases nonlinearly with the increase of transition length and pipe wall thickness. The peak stress of the pipe increases linearly with the increase of temperature difference. Moreover, the maximum allowable frost heave deformation decreases nonlinearly with the increase of oil pressure. This study helps provide theoretical reference for the adjustment, control, and prediction of stress and deformation in the design of buried pipelines under frost heaving.
Coinciding Mean of the Two Symmetries on the Set of Mean Functions
Authors: Mihoković Lenka
Published: February 2023

On the set M of mean functions, the symmetric mean of M with respect to mean M0 can be defined in several ways. The first one is related to the group structure on M, and the second one is defined trough Gauss’ functional equation. In this paper, we provide an answer to the open question formulated by B. Farhi about the matching of these two different mappings called symmetries on the set of mean functions. Using techniques of asymptotic expansions developed by T. Burić, N. Elezović, and L. Mihoković (Vukšić), we discuss some properties of such symmetries trough connection with asymptotic expansions of means involved. As a result of coefficient comparison, a new class of means was discovered, which interpolates between harmonic, geometric, and arithmetic mean.
Topologies on Smashed Twisted Wreath Products of Metagroups
Authors: Ludkowski Sergey Victor
Published: February 2023

In this article, topologies on metagroups and quasigroups are studied. Topologies on smashed twisted wreath products of metagroups are scrutinized, which are making them topological metagroups. For this purpose, transversal sets are studied. As a tool for this, semi-direct products of topological metagroups are also investigated. They have specific features in comparison with topological groups because of the nonassociativity, in general, of metagroups. A related structure of topological metagroups is investigated. Particularly, their compact subloops and submetagroups are studied. Isomorphisms of topological unital quasigroups (i.e., loops) obtained by the smashed twisted wreath products are investigated. Examples are provided.
Multifunctional Multilayer Nanospheres for Ion Regulation in Lithium Metal Batteries
Authors: Li Yan , Xiao Manjie , Shen Chunli , Ma Haoqing , Cui Lianmeng , Yang Wei , Zhao Tianhao , Zhao Yan , Xu Xu
Published: February 2023

Lithium metal anodes have the potential to break through the theoretical energy density bottleneck of commercial lithium ion batteries. However, the solid-electrolyte interphase (SEI) layer generated from the decomposition of traditional lithium metal electrolytes is destroyed during the lithium metal expansion process, resulting in the growth of lithium dendrites and the formation of dead lithium. In this work, multilayer Fe3O4@Al(OH)3@ZnO (FAZ) nanospheres are prepared using a hydrothermal method to modify lithium metal anodes. An SEI layer rich in LiF can be formed in fluorine-poor electrolytes. The battery assembled using FAZ nanospheres remains stable for 100 cycles with Coulombic efficiency up to 98.6%. A battery paired with a LiFePO4 cathode (18.3 mg/cm2) can perform 100 cycles with a capacity retention rate of 87%. This work provides a simple and practical solution for low-fluoride lithium metal battery technology.
Visual Blood, a 3D Animated Computer Model to Optimize the Interpretation of Blood Gas Analysis
Authors: Schweiger Giovanna , Malorgio Amos , Henckert David , Braun Julia , Meybohm Patrick , Hottenrott Sebastian , Froehlich Corinna , Zacharowski Kai , Raimann Florian J. , Piekarski Florian , Noethiger Christoph B. , Spahn Donat R. , Tscholl David W. , Roche Tadzio R.
Published: February 2023

Acid–base homeostasis is crucial for all physiological processes in the body and is evaluated using arterial blood gas (ABG) analysis. Screens or printouts of ABG results require the interpretation of many textual elements and numbers, which may delay intuitive comprehension. To optimise the presentation of the results for the specific strengths of human perception, we developed Visual Blood, an animated virtual model of ABG results. In this study, we compared its performance with a conventional result printout. Seventy physicians from three European university hospitals participated in a computer-based simulation study. Initially, after an educational video, we tested the participants’ ability to assign individual Visual Blood visualisations to their corresponding ABG parameters. As the primary outcome, we tested caregivers’ ability to correctly diagnose simulated clinical ABG scenarios with Visual Blood or conventional ABG printouts. For user feedback, participants rated their agreement with statements at the end of the study. Physicians correctly assigned 90% of the individual Visual Blood visualisations. Regarding the primary outcome, the participants made the correct diagnosis 86% of the time when using Visual Blood, compared to 68% when using the conventional ABG printout. A mixed logistic regression model showed an odds ratio for correct diagnosis of 3.4 (95%CI 2.00–5.79, p < 0.001) and an odds ratio for perceived diagnostic confidence of 1.88 (95%CI 1.67–2.11, p < 0.001) in favour of Visual Blood. A linear mixed model showed a coefficient for perceived workload of −3.2 (95%CI −3.77 to −2.64) in favour of Visual Blood. Fifty-one of seventy (73%) participants agreed or strongly agreed that Visual Blood was easy to use, and fifty-five of seventy (79%) agreed that it was fun to use. In conclusion, Visual Blood improved physicians’ ability to diagnose ABG results. It also increased perceived diagnostic confidence and reduced perceived workload. This study adds to the growing body of research showing that decision-support tools developed around human cognitive abilities can streamline caregivers’ decision-making and may improve patient care.
Editorial to the Special Issue “Information Processing in Neuronal Circuits and Systems”
Authors: Valizadeh Alireza , Mirasso Claudio
Published: February 2023

The nervous system processes sensory information through a hierarchical structure with multiple processing stages [...]
Identifying Whitemouth Croaker (Micropogonias furnieri) Populations along the Rio de Janeiro Coast, Brazil, through Microsatellite and Otolith Analyses
Authors: Franco Taynara Pontes , Vilasboa Anderson , Araújo Francisco Gerson , de Moura Gama Joana , Correia Alberto Teodorico
Published: February 2023

The inshore area of the Southwestern Atlantic between 22 °S and 29 °S (South Brazilian Bight) is a transitional climatic zone, where the tropical and warm temperate provinces mix. In its northern part, i.e., in the coastal waters of Rio de Janeiro, Brazil, local oceanographic conditions, such as upwelling in the north, and great bays with different degrees of anthropogenic influences in the center and south can determine the population structure of several fish stocks. The Whitemouth croaker (Micropogonias furnieri) is one the most heavily exploited fishing resources in this area, but there are still some doubts about its population structure. In this study, through combined analyses using nuclear genetic markers and morphological and geochemical signatures of otoliths, a divergence of individuals between two populations was identified using microsatellites, while a finer spatial structure with three populations (north, center and south, respectively) was found based on otolith shapes and elemental signatures. This regional population structure may have direct implications for rational fisheries management and conservation of the species.
Thermal Profiles of Chainsaw Hollows and Natural Hollows during Extreme Heat Events
Authors: Callan Michael N. , Krix Dan , McLean Christopher M. , Murray Brad R. , Webb Jonathan K.
Published: February 2023

Loss of hollow-bearing trees threatens many hollow-dependent wildlife. To mitigate this process, artificial chainsaw-carved hollows (CHs) are often created in dead trees, yet little is known about their thermal profiles. We measured temperatures inside 13 natural hollows (8 live and 5 dead trees) and 45 CHs (5 live and 40 dead trees) in the central west of NSW, Australia, over the course of 2 summers. Maximum temperatures and daily temperature ranges within natural hollows and artificial hollows were similar in 2017–2018. Hollow temperatures were lower in thicker-walled hollows than in thinner-walled hollows. During the January 2019 heatwave, temperatures inside CHs in dead trees exceeded 4–35 °C higher than the upper limit of the thermal neutral zone of sugar gliders—for 6.2 consecutive days (range 0–9 days). CHs in dead trees provided little buffering from thermal extremes; when air temperatures peaked at 44.6 °C, CHs in dead trees were on average 2.4 °C cooler than ambient (range: 5.5 °C cooler to 1.0 °C hotter than ambient). These results show that CHs created in dead trees may not provide suitable thermal conditions for hollow-dependent marsupials during summer heatwaves. Retention of large live trees, coupled with revegetation, is crucial for conserving hollow-dependent fauna in agricultural landscapes.
Prediction of Potential Suitable Distribution Areas of Quasipaa spinosa in China Based on MaxEnt Optimization Model
Authors: Hou Jinliang , Xiang Jianguo , Li Deliang , Liu Xinhua
Published: February 2023

Quasipaa spinosa is a large cold-water frog unique to China, with great ecological and economic value. In recent years, due to the impact of human activities on the climate, its habitat has been destroyed, resulting in a sharp decline in natural population resources. Based on the existing distribution records of Q. spinosa, this study uses the optimized MaxEnt model and ArcGis 10.2 software to screen out 10 factors such as climate and altitude to predict its future potential distribution area because of climate change. The results show that when the parameters are FC = LQHP and RM = 3, the MaxEnt model is optimal and AUC values are greater than 0.95. The precipitation of the driest month (bio14), temperature seasonality (bio4), elevation (ele), isothermality (bio3), and the minimum temperature of coldest month (bio6) were the main environmental factors affecting the potential range of the Q. spinosa. At present, high-suitability areas are mainly in the Hunan, Fujian, Jiangxi, Chongqing, Guizhou, Anhui, and Sichuan provinces of China. In the future, the potential distribution area of Q. spinosa may gradually extend to the northwest and north. The low-concentration emissions scenario in the future can increase the area of suitable habitat for Q. spinosa and slow down the reduction in the amount of high-suitability areas to a certain extent. In conclusion, the habitat of Q. spinosa is mainly distributed in southern China. Because of global climate change, the high-altitude mountainous areas in southern China with abundant water resources may be the main potential habitat area of Q. spinosa. Predicting the changes in the distribution patterns of Q. spinosa can better help us understand the biogeography of Q. spinosa and develop conservation strategies to minimize the impacts of climate change.
Connections between Diabetes Mellitus and Metabolic Syndrome and the Outcome of Cardiac Dysfunctions Diagnosed during the Recovery from COVID-19 in Patients without a Previous History of Cardiovascular Diseases
Authors: Tudoran Cristina , Bende Renata , Bende Felix , Giurgi-Oncu Catalina , Enache Alexandra , Dumache Raluca , Tudoran Mariana
Published: February 2023

(1) Background: Throughout the COVID-19 pandemic, it became obvious that individuals suffering with obesity, diabetes mellitus (T2DM), and metabolic syndrome (MS) frequently developed persisting cardiovascular complications, which were partially able to explain the onset of the long-COVID-19 syndrome. (2) Methods: Our aim was to document, by transthoracic echocardiography (TTE), the presence of cardiac alterations in 112 patients suffering from post-acute COVID-19 syndrome and T2DM, MS, and/or obesity, in comparison to 91 individuals without metabolic dysfunctions (MD); (3) Results: in patients with MD, TTE borderline/abnormal left (LVF) and/or right ventricular function (RVF), alongside diastolic dysfunction (DD), were more frequently evidenced, when compared to controls (p ˂ 0.001). Statistically significant associations between TTE parameters and the number of factors defining MS, the triglyceride-glucose (TyG) index, the severity of the SARS-CoV-2 infection, and the number of persisting symptoms (p ˂ 0.001) were noted. Significant predictive values for the initial C-reactive protein and TyG index levels, both for the initial and the 6-month follow-up levels of these TTE abnormalities (p ˂ 0.001), were highlighted by means of a multivariate regression analysis. (4) Conclusions: in diabetic patients with MS and/or obesity with comorbid post-acute COVID-19 syndrome, a comprehensive TTE delineates various cardiovascular alterations, when compared with controls. After 6 months, LVF and RVF appeared to normalize, however, the DD—although somewhat improved—did persist in approximately a quarter of patients with MD, possibly due to chronic myocardial changes.
Neuromodulation of Neural Oscillations in Health and Disease
Authors: Weiss Evan , Kann Michael , Wang Qi
Published: February 2023

Using EEG and local field potentials (LFPs) as an index of large-scale neural activities, research has been able to associate neural oscillations in different frequency bands with markers of cognitive functions, goal-directed behavior, and various neurological disorders. While this gives us a glimpse into how neurons communicate throughout the brain, the causality of these synchronized network activities remains poorly understood. Moreover, the effect of the major neuromodulatory systems (e.g., noradrenergic, cholinergic, and dopaminergic) on brain oscillations has drawn much attention. More recent studies have suggested that cross-frequency coupling (CFC) is heavily responsible for mediating network-wide communication across subcortical and cortical brain structures, implicating the importance of neurotransmitters in shaping coordinated actions. By bringing to light the role each neuromodulatory system plays in regulating brain-wide neural oscillations, we hope to paint a clearer picture of the pivotal role neural oscillations play in a variety of cognitive functions and neurological disorders, and how neuromodulation techniques can be optimized as a means of controlling neural network dynamics. The aim of this review is to showcase the important role that neuromodulatory systems play in large-scale neural network dynamics, informing future studies to pay close attention to their involvement in specific features of neural oscillations and associated behaviors.
Effects of Different Fasting Interventions on Cardiac Autonomic Modulation in Healthy Individuals: A Secondary Outcome Analysis of the EDIF Trial
Authors: Zimmermann Paul , Herz Daniel , Karl Sebastian , Weiß Johannes W. , Lackner Helmut K. , Erlmann Maximilian P. , Sourij Harald , Schierbauer Janis , Haupt Sandra , Aberer Felix , Wachsmuth Nadine B. , Moser Othmar
Published: February 2023

The impact of a fasting intervention on electrocardiographic (ECG) time intervals and heart rate variability (HRV) is a focus that is scarcely analyzed. The main focus of these secondary outcome data was to describe the impact of a different fasting intervention on ECG and HRV analyses. Twenty-seven healthy individuals participated in this study (11 females, aged 26.3 ± 3.8 years, BMI 24.7 ± 3.4 kg/m2), including a pre-intervention controlled run-in period. Participants were randomized to one of the three fasting cohorts: (I) alternate day fasting (ADF, n = 8), (II) 16/8 fasting (16/8 h of fasting/feasting, n = 11) and (III) 20/4 fasting (20/4 h of fasting/feasting, n = 8). An analysis of baseline ECG parameters and HRV parameters following different fasting interventions demonstrated the safety of these interventions without impacting on heart rate variability parameters during Schellong-1 testing, and revealed comparable preserved autonomic cardiac modulation (ACM) independently of the fasting intervention. In conclusion, different short-term fasting interventions demonstrated no safety ECG-based concerns and showed comparable ACM based on ECG and HRV assessments. Finally, our research topic might strengthen the scientific knowledge of intermittent fasting strategies and indicate potential clinically preventive approaches with respect to occurring metabolic disease and obesity in healthy young subjects.
PIP2-Effector Protein MPRIP Regulates RNA Polymerase II Condensation and Transcription
Authors: Balaban Can , Sztacho Martin , Antiga Ludovica , Miladinović Ana , Harata Masahiko , Hozák Pavel
Published: February 2023

The specific post-translational modifications of the C-terminal domain (CTD) of the Rpb1 subunit of RNA polymerase II (RNAPII) correlate with different stages of transcription. The phosphorylation of the Ser5 residues of this domain associates with the initiation condensates, which are formed through liquid-liquid phase separation (LLPS). The subsequent Tyr1 phosphorylation of the CTD peaks at the promoter-proximal region and is involved in the pause-release of RNAPII. By implementing super-resolution microscopy techniques, we previously reported that the nuclear Phosphatidylinositol 4,5-bisphosphate (PIP2) associates with the Ser5-phosphorylated-RNAPII complex and facilitates the RNAPII transcription. In this study, we identified Myosin Phosphatase Rho-Interacting Protein (MPRIP) as a novel regulator of the RNAPII transcription that recruits Tyr1-phosphorylated CTD (Tyr1P-CTD) to nuclear PIP2-containing structures. The depletion of MPRIP increases the number of the initiation condensates, indicating a defect in the transcription. We hypothesize that MPRIP regulates the condensation and transcription through affecting the association of the RNAPII complex with nuclear PIP2-rich structures. The identification of Tyr1P-CTD as an interactor of PIP2 and MPRIP further points to a regulatory role in RNAPII pause-release, where the susceptibility of the transcriptional complex to leave the initiation condensate depends on its association with nuclear PIP2-rich structures. Moreover, the N-terminal domain of MPRIP, which is responsible for the interaction with the Tyr1P-CTD, contains an F-actin binding region that offers an explanation of how nuclear F-actin formations can affect the RNAPII transcription and condensation. Overall, our findings shed light on the role of PIP2 in RNAPII transcription through identifying the F-actin binding protein MPRIP as a transcription regulator and a determinant of the condensation of RNAPII.