bluuebunny/crossref_metadata_2025 huggingface dataset:
Intuitionistic SIR Technique with Double Parameters to Detect the Operative Vaccine of COVID-19
Authors: Devi S. Aicevarya , Augustin Felix
Published: June 2023

Since 2019, COVID disease threats the world. It originated in China, and due to its easy spread characteristics, it spreads quickly among all the countries. As the world faced a new kind of virus, the government could not control its spread, and the fatality rate had also hugely increased. In 2021, the vaccine for the virus was introduced by various countries, which aids in controlling the spread and mortality rate. The mutant form of this virus exhibits high efficiency. So, this study analyzes the effective of COVID vaccines released after 2020 against all COVID variants through the fuzzy superiority and inferiority ranking (SIR) decision-making method. The vaccines and variants are analyzed by the [Formula: see text] matrix pattern under the fuzzy SIR-integrated weight method. The disease variants are taken as criteria and that are assigned integrated weight based on subjective, objective weight approaches. The intuitionistic fuzzy set-double parameter (IFS-DP) handles the vagueness by strictly including only membership and non-membership functions with the condition [Formula: see text]. As a result, the vaccines Moderna and Covishield are attained top rank and have a high likelihood to combat all the COVID variants compared to other vaccines. The reached outcomes are corroborated through sensitivity and comparative analysis. The sensitivity and comparative studies are measured by increasing the order of IFS-DP and extant fuzzy MCDM methods, respectively. The comparison of these results with those obtained from the proposed method is similar to the sensitivity study, along with minor variations observed in the comparative study. Therefore, the proposed method generates an efficient outcome. Moreover, the testing hypothesis technique is applied to check the efficiency of proposed method.
Estimation of Missing Entries in Preference Pairwise Matrices Through Nuclear Norm Minimization
Authors: Scioni Manuela , Fabbris Luigi
Published: June 2023

This paper aims to evaluate the possibility of applying the nuclear norm minimization technique to the problem of incompleteness of an additive preference pairwise matrix. The proposed technique applies to the case of missing values in any position within a matrix of any order, provided that all the alternatives are connected, or equivalently that there is a preference path between each pair of alternatives. The unknown entries are estimated by finding a matrix that best matches the given entries, assuming that the reconstructed matrix can be well approximated by a lower-rank matrix and that the entries are missing completely at random. A series of applications with simulated data were used to evaluate the validity of the proposed technique, particularly in comparison to another popular technique of missing value estimation based on the minimization of an index measuring matrix inconsistency. The simulation results suggest the effectiveness of nuclear norm minimization as a completion technique in some of the considered setting, in particular if violations of strong transitivity property are considered.
Fermions tunneling of Kerr–Newman–de Sitter black hole in Lorentz violation theory
Authors: Media Ningthoujam , Laxmi Y. Onika , Singh T. Ibungochouba
Published: June 2023

In this paper, the tunneling of fermions near the event horizon of Kerr–Newman–de Sitter (KNdS) black hole is investigated in frame dragging coordinate systems, Eddington coordinate system and Painleve coordinate system by using Dirac equation with Lorentz violation theory, Feynman prescription and WKB approximation. The Hawking temperature, heat capacity and change in black hole entropy of the black hole are modified due to the presence of Lorentz violation theory. The modified Hawking temperatures, heat capacities and change in black hole entropies at the event horizon of KNdS black hole would increase or decrease depending upon the choices of ether like vectors [Formula: see text]. In the absence of Lorentz violation theory, the original Hawking temperature, entropy and heat capacity are recovered.
Exploring the bouncing cosmological models in symmetric teleparallel gravity
Authors: Shaikh Alfred Y.
Published: June 2023

In this study, the bouncing cosmological models have been presented in the non-metricity-based gravitational theory, the [Formula: see text] gravity, where [Formula: see text] be the non-metricity scalar. The two bouncing cosmological models, one in which the Lagrangian [Formula: see text] is assumed to have a linear dependence on [Formula: see text] and the other in which it has a polynomial functional form have been shown. It has been obtained that the parameters of the models largely depend on the behavior of the models. The equation of state (EoS) parameter shows the bouncing behavior of the Universe. It should be highlighted that the built-in cosmological models go against the energy requirements. The kinematical and physical characteristics of the models are also analyzed.
Electronic properties and redox chemistry ofN-confused metalloporphyrins
Authors: Martins Frederico F. , Swart Marcel
Published: June 2023

Here we study the effect of metals on the characteristic Soret band of N-confused porphyrins. We used DFT calculations to study how this low-lying region of the spectrum of the NCP-2H isomer is affected by the introduction of transition metals with various ([Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] d-electron configurations. The spin ground state of these complexes is mostly dependent on the number of unpaired electrons, both with and without the presence of an axial ligand. The analysis of the electronic distribution and spin density showed that these unpaired electrons are often harbored by the N-confused porphyrin ring instead of on the metal. Time-dependent DFT results indicated that the aromatic system of porphyrin is disrupted in the N-confused isomer: instead of the typical large Soret band, this now gives rise to two peaks of much lower intensity. Most metallo-porphyrins exhibited similar optical properties, with the HOMO/LUMO orbitals showing a mixed metal/porphyrin character. The only exception was the Rh metalloporphyrin that exhibited a ligand-to-metal charge transfer band with increasing intensity as function of the ligand field. This suggests Rh is the only metal whose orbitals are higher in energy than the ligand’s, indicating that it is the only system where the redox processes occur on the metal.
Quantitative Detection of Ortho-Aminophenol by Using Modified Reduced Graphene Oxide/Indium Tin Oxide Glass Electrode
Authors: Boruah Sontara Konwar , Das Hirendra , Boruah Prabin Kumar
Published: June 2023

In this research work the electrochemical oxidation of ortho-aminophenol (oAP) is studied using modified reduced graphene oxide/indium tin oxide (rGO/ITO) glass electrode in acetonitrile medium, tetrabutyl ammonium perchlorate (TBAP) supporting electrolyte. Cyclic voltammetry (CV) and linear-sweep voltammetry (LSV) techniques were used to study the redox behavior of oAP. The graphene oxide-initiated auto-oxidized 2-aminophenoxazine-3-one is irreversibly reduced by modified rGO/ITO glass electrode at −0.048[Formula: see text]V (versus Ag–AgCl electrode). LSV response shows that the cathodic peak current increases notably compared to that of bare rGO/ITO glass electrode and with the increasing concentration of oAP. The oxidized product of oAP was characterized by UV–Visible and FT-IR spectroscopy. The redox behavior of oAP of modified rGO/ITO glass electrode was compared with the electrochemical behavior of oAP at bare glassy carbon electrode.
IS SOLAR AND BIOGAS A BETTER CHOICE THAN ELECTRICITY AND DIESEL?
Authors: AKMAL NADEEM , QASIM MUHAMMAD , SHAH HASSNAIN , ZAMAN SUMIA BINT , FAROOQ WAQAS , AHMAD NAJID
Published: June 2023

This study measures the cost-effectiveness of alternate energy sources for irrigation in Pakistan. Primary data has been collected from eight districts of three provinces of Pakistan. Overall, 223 farmers were personally interviewed out of which, 58 farmers were using electric tube-well, 95 diesel tube-well, and 35 each for solar and biogas-operated tube-wells. The cost of extracting one cubic meter of water through electricity, diesel, subsidized electricity, biogas, and solar was $0.180, $0.013, $0.011, $0.010, and $0.005, respectively. The paper concludes that water pumping using alternative energy sources is cost-effective. Major constraints to adopting solar-powered water pumping systems were the high upfront cost, the lack of awareness, and the lack of available spare parts. The constraints to adopting biogas were difficulty operating and managing through winter.
An Energy and Quality Efficient MTJ/FinFET Approximate 5:2 Compressor for Image Processing Applications
Authors: Siahkal-Mahalle Behrang Hadian , Mazloum Jalil
Published: June 2023

Shrinking the transistor dimensions in complementary metal-oxide-semiconductor (CMOS) technology has led to many huge problems, like high power density. Various methods at different design levels of abstraction, such as approximate computing and spintronic devices based on magnetic tunnel junction (MTJ), have been studied to solve these problems. In this paper, we propose a novel hybrid MTJ/FinFET-based approximate 5:2 compressor. The proposed design employs the spin-transfer torque (STT) method assisted by the spin-Hall effect (SHE) to store inputs in MTJs. Due to the SHE assistance, the energy efficiency of the MTJ switching is improved considerably over the conventional STT method. Our design significantly improves the energy consumption compared to the previous compressors, thanks to the decrease in MTJ and transistor counts. The proposed circuit and previous designs are simulated using HSPICE with 7-nm FinFET and SHE perpendicular-anisotropy MTJ model. From the simulation results, we can see that the proposed design improves power consumption, write energy, read energy, number of transistors and MTJ count on average by 49%, 50%, 63%, 20% and 50%, respectively, in comparison with the existing counterparts. Furthermore, the accuracy of the approximate designs is evaluated through comprehensive MATLAB simulations. The results indicate that the proposed circuit outperforms the best previous energy-efficient designs in terms of accuracy despite having better hardware characteristic parameters.
Modeling of Conjugated Core-Based Non-Fullerene Acceptor Materials for Organic Photovoltaic Applications
Authors: Adnan Muhammad , Faisal Muhammad , Hussain Riaz , Usman Khan Muhammad , Yaqoob Junaid , Hussain Fakhar , Siddique Sabir Ali , Farooq Umar , Cho Churl-Hee , Lim Jongchul
Published: June 2023

Non-Fullerene acceptors (NFAs) are attracting much attention from scientists worldwide for their potential use in organic solar cells (OSC). Herein, we developed C-shaped NFAs acceptors (FA1–FA10) by performing end-capped alteration on GL1. The structural-property relation and optoelectronic characteristics were examined theoretically. Furthermore, the impact of structural changes on the optoelectronic characteristics of FA1–FA10 molecules was investigated by using density functional theory (DFT), and time-dependent DFT. The photo-physical and optoelectronic features such as frontier molecular orbitals, electron–hole overlapping, excitation and binding energy, molecular electrostatic potential, the density of states, transition density matrix, open circuit voltage, and reorganization energies of hole and electron, of the designed materials have been simulated. Compared to GL1 (R), the developed materials displayed a red-shifted absorption (ranges 769.84–856.36[Formula: see text]nm), better electric-charge movement, lower binding (0.30[Formula: see text]eV), and excitation energies (1.28[Formula: see text]eV), and narrower bandgaps (ranges 1.59–1.79[Formula: see text]eV), respectively. Therefore, we suggest these to synthetic researchers for the future development of efficient OSCs.
Basin-scale 3D modelling of the northern Upper Rhine Graben: insights into basement fault-related geothermal flow pathways
Authors: Lemgruber-Traby Adriana , Bossennec Claire , Béthune Gillian , Souque Christine , Divies Renaud , van der Vaart Jeroen , Bär Kristian , Sass Ingo
Published: June 2023

A regional assessment of the potential for geothermal heat production, power generation and also heat storage requires an evaluation of the heat in place and its recharge. Both are controlled by the flow properties and natural fluid flow through the reservoir at the present day, which must be thoroughly analysed based on the understanding and modelling of the architecture of deep reservoirs. In the Upper Rhine Graben, well known for its vast geothermal potential, a characterization of the structural organization at the basin scale and an understanding of mass and heat transfer are, therefore, useful for correctly estimating the technical and economic potential for geothermal energy. The distribution of the resources can be quantified based on the basin analysis approach. This is classically used for hydrocarbon resources and is applied in this study to predict the geothermal fluid-flow paths. The role of faults and their hydraulic regime on temperature field heterogeneities is investigated. Several scenarios with or without rift basin internal faults and various transmissivity ranges along these faults are analysed and compared. The measured temperature field is used for the calibration of the different model scenarios results. The scenario with the most significant role for internal faults as fluid-flow pathways in the western Upper Rhine Graben is the one that provides the most accurate reproduction of the temperature field. Such output highlights the importance of quantifying the hydraulic behaviour of faults and associated fracture networks in space and time.

Supplementary material:
dataset containing geometry, facies distribution and main results of scenario 4 is available at
https://doi.org/10.6084/m9.figshare.c.6628506
Silurian to Early Devonian tectonic evolution of the southeastern Qilian Orogen inferred from zircon U–Pb dating and geochemistry of intrusive rocks
Authors: Li Xi-Yao , Li Sanzhong , Yu Sheng-Yao , Liu Yongjiang , Qin Zhengwei , Huang Zeng-Bao , Lu Qing
Published: June 2023

Early to mid-Paleozoic tectonothermal events in the Qilian Orogen developed during the closure of the Proto-Tethys Ocean and the convergence of microcontinents in the periphery of East Gondwana. In this paper, we present geochronological, geochemical and Sr–Nd-Hf isotopic data for the granitoid rocks and mafic dykes in southeastern Qilian Orogen. The Liwan (440 Ma), Shixia (434 Ma) and Huchuan (429 Ma) granitoid rocks have metaluminous to weakly peraluminous features, with whole-rock

ε

Nd
(
t
) values of 1.1 to 1.6, −4.2 to −4.4 and −2.6 to 1.1, and zircon

ε

Hf
(
t
) values of 0 to 8.9, −6.6 to 1.6 and −4.6 to 2.2, respectively. Geochemical data suggest that the Liwan, Shixia and Huchuan granitoids are derived from partial melting of the Proterozoic basement with addition of juvenile material, felsic crustal basement and mafic crustal material, respectively. The Zhangjiayuan mafic dykes (403 Ma) are high-K to shoshonitic with whole-rock

ε

Nd
(
t
) (−1.1 to −0.9) and zircon

ε

Hf
(
t
) values (−0.9 to 13.3), derived from an enriched lithospheric mantle. We suggest that these Silurian–Early Devonian intrusive rocks were formed via complex events involving arc-related subduction followed by slab-tearing to post-collisional processes during the Silurian and subsequent lithospheric extension in the Early Devonian.

Supplementary material:
Tables giving zircon U–Pb isotopic data, whole-rock major and trace element results, whole-rock Sr–Nd isotopic data and zircon
in situ
Lu–Hf isotopic data are available at
https://doi.org/10.6084/m9.figshare.c.6693575
3D Seismic reflection evidence for lower crustal intrusions beneath the Faroe–Shetland Basin, NE Atlantic Margin
Authors: Layfield Lucinda K. , Schofield Nick , Watson Douglas , Holford Simon P. , Jolley David W. , Kilhams Ben A. , Muirhead David K. , Roberts Alan M. , Alvey Andrew D. , Ellwood Alex , Widdowson Mike
Published: June 2023

Lower crustal intrusion is considered to be a common process along volcanic or magma-rich passive margins, including the NE Atlantic Margin, where it is thought to have occurred during phases of Paleogene magmatism, both prior to and during continental break-up between NW Europe and Greenland. Evidence of Paleogene magmatism is prevalent throughout the sub-basins of the Faroe–Shetland Basin as extensive lava flows and pervasive suites of igneous intrusions. However, in contrast with other areas located along the NE Atlantic Margin, no lower crustal reflectivity indicative of lower crustal intrusion has been documented beneath the Faroe–Shetland Basin. The nearest documentation of lower crustal reflectivity and interpretation of lower crustal intrusion to the Faroe–Shetland Basin is NW of the Fugloy Ridge, beneath the Norwegian Basin of the Faroese sector. Despite this, the addition of magma within the lower crust and/or at the Mohorovičić discontinuity is thought to have played a part in Paleogene uplift and the subsequent deposition of Paleocene–Eocene sequences. Advances in sub-basalt seismic acquisition and processing have made significant improvements in facilitating the imaging of deep crustal structures along the NE Atlantic Margin. This study used broadband 3D seismic reflection data to map a series of deep (
c.
14–20 km depth) high-amplitude reflections that may represent igneous intrusions within the lower crust beneath the central-northern Corona Ridge. We estimate that the cumulative thicknesses of the reflections may be >5 km in places, which is consistent with published values of magmatic underplating within the region based on geochemical and petrological data. We also estimate that the total volume of lower crustal high-amplitude reflections within the 3D dataset may be >2000 km
3
. 2D gravity modelling of a seismic line located along the central-northern Corona Ridge supports the interpretation of lower crustal intrusions beneath this area. This study provides evidence of a potential mechanism for Paleogene uplift within the region. If uplift occurred as a result of lower crustal intrusions emplaced within the crust during the Paleogene, then we estimate that
c.
300 m of uplift may have been generated within the Corona Ridge area.
Zircon U–Pb geochronology, Nd isotopes and geochemistry of mafic granulites from the Central Indian Tectonic Zone: isotopic constraints on Proterozoic crustal evolution
Authors: Alam Meraj , Kaulina Tatiana V. , Varma Rakhi R. , Ahmad Talat
Published: June 2023

The Central Indian Tectonic Zone (CITZ) comprises northern and southern Indian cratonic blocks and is a tectonic window that is suitable for investigating the Proterozoic crustal evolution because of the presence of a wide variety of lithologies. Geochemical and geochronological data on mafic granulites by previous workers do not ascertain the possibility of mafic protoliths and their coeval link to other CITZ units. Thus, determining the precise timing of the formation of mafic granulites may indicate a connection between metamorphism and fragmentation of the Columbian supercontinent. This study presents zircon U–Pb ages, Nd isotopes and the geochemistry of mafic granulites to evaluate their genesis and timing of metamorphism. The results show the tholeiitic affinity and primary magmatic differentiation of the parental melt. Depletion of Nb, P, Zr and Ti and positive enrichment of Ba, U and Pb indicate the derivation of mafic granulites from a variably enriched subcontinental lithospheric mantle (SCLM) source. The zircon U–Pb ages (1564 ± 8 to 1598 ± 9 Ma) are interpreted as a period of granulite-facies metamorphism. The
T
DM
(depleted-mantle) model ages (2.9–3.4 Ga) of mafic granulites indicate the timing of mafic protolith extraction. The mineral isochron age
c.
1.0 Ga indicates that these rocks underwent some events during an early Neoproterozoic period. Protolith of mafic granulites could be related to the evolution of melts derived from metasomatized SCLM through fractional crystallization processes.
The Cambrian Atlas – Ossa–Morena – North Armorican Rift, West Gondwana: along- and off-axis stratigraphic and volcano-tectonic patterns
Authors: Álvaro J. Javier , Sánchez-García Teresa , Casas Josep Maria
Published: June 2023

The Cambrian Atlas – Ossa–Morena – North Armorican Rift extended along West Gondwana from the end of the Pan-African and Cadomian orogenies until the diachronous beginning of drift conditions related to the opening of the Rheic Ocean. The along-axis rift cross-cut the western parts of the Anti-Atlas, High Atlas and Coastal Meseta, which were linked to the Ossa–Morena Zone and the North Armorican Domain, whereas several joint tectonic branches connected with off-axis rift transects of the Central Iberian, West Asturian–Leonese and Cantabrian zones (Iberian Massif), the Central and South Armorican domains, the Occitan Domain, the Pyrenees, and southern Sardinia. The pre-rift unconformity, post-dating the orogenic collapse, is characterized by initial (half-)graben development and subsequent infill, with slope-related breccias and conglomerates controlled by the denudation of surrounding uplands. Synrift pulses show regional extension and are distinctly identifiable on the top of rift shoulders, recording episodes of carbonate production due to their association with karst and hydrothermal processes. The break-up unconformity ranges from volcanic-free angular discordances and paraconformities to generalized uplift and denudation of subaerially exposed areas, associated with the onset of granite-dominant large igneous provinces (LIPs). The Furongian–Tremadocian (Toledanian) and Ordovician (Sardic) phases have been interpreted as due to: (i) Andean-type subduction magmatism reaching the crust in an arc–back-arc setting; (ii) post-collisional decompression melting without significant mantle involvement; and (iii) partial melting of the lower continental crust affected by the underplating of hot mafic magmas linked to superplumes.
Interactive System Modelling for the Internet of Things
Authors: Bowen Judy , Turner Jessica
Published: June 2023

The rapid growth in the number of Internet of Things (IoT) systems and their increasing use in safety-critical domains has led to the need for an evolution of development methods. Model-Driven Development (MDD) approaches have been used in software engineering to reduce development time and minimise errors in implemented systems. This paper introduces a novel Model-Driven Development (MDD) approach for Internet of Things (IoT) systems which considers interactivity from the perspective of both users and IoT components. A real-world example is presented to explain the motivation for the work and demonstrate the benefits and use of lightweight interactive system models adapted for the design and development of IoT systems.
Using RFID in the Engineering of Interactive Software Systems: A Systematic Mapping
Authors: Maia Vitor Carneiro , de Oliveira Kathia Marçal , Kolski Christophe , Travassos Guilherme Horta
Published: June 2023

IoT, Industry 4.0, and ubiquitous applications demand an intense exchange of information between actors (humans, animals, plants, or other objects) and things. Different interaction technologies, techniques, and methods can support it, including RFID, a well-known technology capable of identifying and locating actors. However, the variety of application domains and interaction possibilities jeopardize the use of RFID without a clear understanding of its usage issues. Therefore, we have performed a systematic mapping to characterize the adoption of RFID technology in this kind of interactive software system by intercepting human-computer interaction and software engineering issues. Our goal is to reveal (i) which application domains address RFID; (ii) why RFID is used instead of other technologies; (iii) who interacts through RFID and how the interaction is; (iv) what are the requirements and limitations associated with it; and (v) what are the common quality characteristics and measures which should be considered for their evaluation. The results showed that (i) RFID is specially used for implementing implicit interactions in healthcare, embedded systems, and manufacturing applications. (ii) Passive UHF RFID is usually adopted due to being contactless, low-cost, and well-performing indoors. (iii) It interacts with humans and things in the same proportion, most frequently to collect locations of sensor data constantly. (iv) RFID presents limitations, such as causing electromagnetic interference and not working well near metallic walls. However, tags work under high temperatures and can be well hidden in cement or clothes. (v) Interactive system designers usually create applications with invisible infrastructures, which tend to keep users' focus on the real world.?
Developing a Multimodal Classroom Engagement Analysis Dashboard for Higher-Education
Authors: Sabuncuoglu Alpay , Sezgin T. Metin
Published: June 2023

Developing learning analytics dashboards (LADs) is a growing research interest as online learning tools have become more accessible in K-12 and higher education settings. This paper reports our multimodal classroom engagement data analysis and dashboard design process and the resulting engagement dashboard. Our work stems from the importance of monitoring classroom engagement, which refers to students' active physical and cognitive involvement in learning that influences their motivation and success in a given course. To monitor this vital facade of learning, we developed an engagement dashboard using an iterative and user-centered process. We first created a multimodal machine learning model that utilizes face and pose features obtained from recent deep learning models. Then, we created a dashboard where users can view their engagement over time and discover their learning/teaching patterns. Finally, we conducted user studies with undergraduate and graduate-level participants to obtain feedback on our dashboard design. Our paper makes three contributions by (1) presenting a student-centric, open-source dashboard, (2) demonstrating a baseline architecture for engagement analysis using our open-access data, and (3) presenting user insights and design takeaways to inspire future LADs. We expect our research to guide the development of tools for novice teacher education, student self-evaluation, and engagement evaluation in crowded classrooms.
Sequential and Graphical Cross-Domain Recommendations with a Multi-View Hierarchical Transfer Gate
Authors: Li Huiyuan , Yu Li , Niu Xi , Leng Youfang , Du Qihan
Published: June 2023

Cross-domain recommender systems could potentially improve the recommendation performance by means of transferring abundant knowledge from the auxiliary domain to the target domain. They could help address some key challenges in recommender systems, such as data sparsity and cold start. However, most existing cross-domain recommendation approaches represent the user preferences based on a single kind of user’s feature or behavior and fail to explore the hidden interaction effects of different kinds of features or behaviors. In this article, we propose the
S
equential and
G
raphical
Cross
-Domain Recommendations with a Multi-View Hierarchical Transfer Gate (SGCross) to transfer user representations from multiple perspectives. The SGCross model constructs a user profile by learning the personal preference from a personal view, the dynamic preference from a temporal view, as well as the collaborative preference from a collaborative view. Specifically, a Multi-view Hierarchical Gate (MHG) is designed to transfer the informative representations of user knowledge on different views from the auxiliary domain separately, aiming to enhance the user representations. Furthermore, a two-stage attentive fusion module is designed to integrate transferred information at two levels: the domain level and the view level. Extensive experiments on the Amazon dataset and the Douban dataset have demonstrated that SGCross effectively improves the accuracy of cross-domain recommendations and outperforms the state-of-the-art baseline models.
CoupledGT: Coupled Geospatial-temporal Data Modeling for Air Quality Prediction
Authors: Ren Siyuan , Guo Bin , Li Ke , Wang Qianru , Wang Qinfen , Yu Zhiwen
Published: June 2023

Air pollution seriously affects public health, while effective air quality prediction remains a challenging problem since the complex spatial-temporal couplings exist in multi-area monitoring data of the city. Current approaches rarely consider relative geographical locations when capturing spatial-temporal relations, instead the latent inter-dependencies (i.e., implicit spatial relations) of data as a replacement. However, such relations cannot necessarily reflect the diffusion of air pollutants in the real world, and genuine location-related information could be lost during the implicit relation learning process. In this article, we introduce a new concept, geospatial-temporal data, and propose a novel deep neural network architecture, CoupledGT, to learn the geospatial-temporal couplings within data for air quality prediction. Specifically, the asymmetric diffusion relation of air quality data between two areas is first explicitly represented by the newly developed planar Gaussian diffusion (PGD) equation. And then, a geospatial couplings diffuser (GCD) is designed to parameterize the PGD equation and learn multi-areas diffusion mutually affected geospatial couplings. Besides, the RNN is employed to capture temporal couplings of each area, and incorporated with GCD to learn both shared and unique characteristics of the geospatial-temporal data simultaneously, which empowers the generalization and efficiency of the model. Extensive experiments on two real-world datasets demonstrate our method is robust and outperforms existing baseline methods in air quality prediction tasks.
Federated Clique Percolation for Privacy-preserving Overlapping Community Detection
Authors: Guo Kun , Guo Wenzhong , Ye Enjie , Fang Yutong , Zheng Jiachen , Liu Ximeng , Chen Kai
Published: June 2023

Community structure is a typical characteristic of complex networks. Finding communities in complex networks has many important applications, such as the advertisement and recommendation based on social networks and the discovery of new protein molecules in biological networks, which make it a hot topic in the field of complex network analysis. With the increasing concerns about the leakage of personal privacy, discovering communities spread across the local networks owned by multiple participants accurately while preserving each participant’s privacy has become an emerging challenge in distributed community detection. In this article, we propose a general federated graph learning model for privacy-preserving distributed graph learning and develop two federated clique percolation algorithms (CPAs) based on it to discover overlapping communities distributed across multiple participants’ local networks without disclosing any participant’s network privacy. Homomorphic encryption and hash operation are used in combination to protect the privacy of the vertices and edges of each local network. Furthermore, vertex attributes are involved in the calculation of clique similarity and clique percolation when dealing with attributed networks. The experimental results on real-world and artificial datasets demonstrate that the proposed algorithms achieve identical results to those of their stand-alone counterparts and more than 200% higher accuracy than the simple distributed CPAs without federating learning.
Server-Client Collaborative Distillation for Federated Reinforcement Learning
Authors: Mai Weiming , Yao Jiangchao , Chen Gong , Zhang Ya , Cheung Yiu-Ming , Han Bo
Published: June 2023

Federated Learning (FL) learns a global model in a distributional manner, which does not require local clients to share private data. Such merit has drawn lots of attention in the interaction scenarios, where Federated Reinforcement Learning (FRL) emerges as a cross-field research direction focusing on the robust training of agents. Different from FL, the heterogeneity problem in FRL is more challenging because the data depends on the policy of agents and the environment dynamics. FRL learns to interact under the non-stationary environment feedback, while the typical FL methods aim at handling the constant data heterogeneity. In this article, we are among the first attempts to analyze the heterogeneity problem in FRL and propose an off-policy FRL framework. Specifically, a student–teacher–student model learning and fusion method, termed asServer-Client Collaborative Distillation(SCCD), is introduced. Unlike the traditional FL, we distill all local models on the server side for model fusion. To reduce the variance of the training, a local distillation is also conducted every time the agent receives the global model. Experimentally, we compare SCCD with a range of straightforward combinations between FL methods and RL. The results demonstrate that SCCD has a superior performance in four classical continuous control tasks with non-IID environments.
REPAIRS: Gaussian Mixture Model-based Completion and Optimization of Partially Specified Systems
Authors: Terway Prerit , Jha Niraj K.
Published: June 2023

Most system optimization techniques focus on finding the values of the system components to achieve the best performance. Searching over all component values gives the search methodology the freedom to explore the entire design space to determine the best system configuration. However, real-world systems often require searching in a restricted space over only a subset of component values while freezing some of the components to fixed values. Rather than optimizing from scratch to search over the subset of components, incorporating the past simulation logs (search performed when all components were allowed to vary) enables the optimization mechanism to utilize knowledge from past system behavior. In addition, when the system gives the same response over different combinations of input values, the designer may prefer one combination over another. Furthermore, real-world data often contain errors. To avoid catastrophic consequences of making decisions based on incorrect data points, we need a mechanism to identify and correct the resulting error. We propose REPAIRS, a methodology to complete/optimize partially specified systems. It also performs data integrity checks and identifies/corrects errors after detecting an anomaly in the data. We use a Gaussian mixture model to learn the joint distribution of the system inputs and the corresponding output response (objectives/constraints). We use the learned model to complete a partially specified system where only a subset of the component values and/or the system response is specified. When the system response exhibits multiple modes (e.g., same response for different combinations of input values), REPAIRS determines the combinations of input values that correspond to the several modes. Using past simulation logs, it searches over various subsets of system inputs to improve the performance of the reference solution. We also present a framework for verifying the integrity of a given data instance. When the integrity check fails, we provide a mechanism to identify the error location and correct the error. REPAIRS provides an explanation for the decision it makes for the different use cases described in this article. We provide results of REPAIRS in the context of completion, partial optimization, and data integrity check of real-world systems. REPAIRS achieves a hypervolume that is better than that obtained using a baseline method by up to 50%. It successfully identifies the error location and predicts the correct value of the erroneous feature with an error less than 0.2%. It detects error locations with a mean accuracy of up to 95% even when three feature values have an error.
An Improved Compression Factor Particle Swarm Optimization-Unscented Particle Filter Algorithm for Accurate Lithium-Ion Battery State of Energy Estimation
Authors: Hao Xueyi , Wang Shunli , Fan Yongcun , Liang Yawen , Wang Yangtao , Fernandez Carlos
Published: June 2023

Accurate prediction of the remaining range remains a challenge for electric vehicles. The state of energy (SOE) is a state parameter representing the remaining mileage and remaining charge of a lithium-ion battery, which is related to the prediction of the remaining range of electric vehicles. To obtain the mathematical description and SOE parameters of lithium-ion batteries with high accuracy, a parameter identification method using an improved particle swarm optimization algorithm with compression factor is proposed. For the estimation of energy state, a particle filter (PF) is constructed in this paper, and the unscented particle filtering (UPF) algorithm with particle swarm optimization (PSO) is used to achieve the estimation of energy state, which can solve the problems of particle degradation and insufficient particle diversity of particle filtering. The experimental results show that the SOE estimation error is within 0.97% at 25 degrees for all three operating conditions and within 1.29% at 5 degrees for all three operating conditions. Therefore, the proposed algorithm has high accuracy and strong robustness at different temperatures and different working conditions, and the estimation results prove the validity of energy state estimation.
Overtaking Assistance System based on Signal Strength to Prevent Accidents in V2V Communication Environment
Authors: Rai Laxmisha , Rodrigo Amila , Samadhi Chamathka , Abeysekara Dasun Madhawa
Published: June 2023

The directional antennas with received signal strength indicator (RSSI) output from 0.52 V to 1.34 V are designed as a receiving component. These antennas have the ability to rotate up to 180° to find the maximum signal strength angle. RSSI signal strength is converted as customized measurement unit as Analog Reading Units (ARU) which varies from 0ARU to 400ARU and signal receiver has −90 dBm receiving sensitivity. The experimental results demonstrate that, the variance of RSSI with speed of a vehicle shows a clear relationship at the position of signal receiving point. Two regions are defined as effective region and non-effective region to show the capability of the proposed model. Effective region is of 60 m range from one vehicle to the other vehicle which plays a role in the overtaking process. When a vehicle is detected within the range, the RSSI value is greater than 150ARU. When the distance is less than 160 m, the RSSI value will be greater than 200ARU. Results prove that the overtaking status of a vehicle is clearly identified as zones and sectors ranging from 1 m to 160 m.
Stimulated myotube contractions regulate membrane-bound and soluble TLR4 to prevent LPS-induced signaling and myotube atrophy in skeletal muscle cells
Authors: Ducharme Jeremy B. , Fennel Zachary J. , McKenna Zachary J. , Nava Roberto C. , Deyhle Michael R.
Published: June 2023

Excessive Toll-like receptor 4 (TLR4) activation causes muscle atrophy. Muscle contractions can limit TLR4 activation on immune cells, but its impact on TLR4 expressed on skeletal muscle cells remains unclear. Here, we demonstrate in C2C12 myotubes for the first time that stimulated myotube contractions reduce membrane-bound TLR4 and increase soluble TLR4, preventing TLR4-mediated signaling and myotube atrophy. Further analyses revealed soluble TLR4 independently prevents myotube atrophy, supporting a potential therapeutic role in combating TLR4-mediated atrophy.
Extracellular matrix composition alters endothelial force transmission
Authors: Subramanian Balachandar Vignesh Aravind , Steward Robert L.
Published: June 2023

The endothelium constitutes the innermost layer of all blood vessels and plays an important role in vascular physiology and pathology. During certain vascular diseases, the extracellular matrix has been suggested to transition from a collagen-rich matrix to a fibronectin-rich matrix. In this study, we demonstrate the impact various collagen and fibronectin ratios have on endothelial biomechanical and morphological response.
Chronic repetitive cooling and caffeine-induced intracellular Ca2+ elevation differentially impact adaptations in slow- and fast-twitch rat skeletal muscles
Authors: Takagi Ryo , Tabuchi Ayaka , Hayakawa Kosei , Osana Shion , Yabuta Hiroya , Hoshino Daisuke , Poole David C. , Kano Yutaka
Published: June 2023

Intracellular Ca2+ concentration ([Ca2+]i) is considered important in the regulation of skeletal muscle mass. This study tested the hypothesis that chronic repeated cooling and/or caffeine ingestion would acutely increase [Ca2+]i and hypertrophy muscles potentially in a fiber-type-dependent manner. Control rats and those fed caffeine were subjected to repeated bidiurnal treatments of percutaneous icing, under anesthesia, to reduce the muscle temperature below ∼5°C. The predominantly fast-twitch tibialis anterior (TA) and slow-twitch soleus (SOL) muscles were evaluated after 28 days of intervention. The [Ca2+]i elevating response to icing was enhanced by caffeine loading only in the SOL muscle, with the response present across a significantly higher temperature range than in the TA muscle under caffeine-loading conditions. In both the TA and SOL muscles, myofiber cross-sectional area (CSA) was decreased by chronic caffeine treatment (mean reductions of 10.5% and 20.4%, respectively). However, in the TA, but not the SOL, CSA was restored by icing (+15.4 ± 4.3% vs. noniced, P < 0.01). In the SOL, but not TA, icing + caffeine increased myofiber number (20.5 ± 6.7%, P < 0.05) and satellite cell density (2.5 ± 0.3-fold) in cross sections. These contrasting muscle responses to cooling and caffeine may reflect fiber-type-specific [Ca2+]i responses and/or differential responses to elevated [Ca2+]i.
Cardiovascular manifestations of inflammatory bowel diseases and the underlying pathogenic mechanisms
Authors: Xiao Ying , Powell Don W. , Liu Xiaowei , Li Qingjie
Published: June 2023

Inflammatory bowel disease (IBD), consisting of ulcerative colitis and Crohn’s disease, mainly affects the gastrointestinal tract but is also known to have extraintestinal manifestations because of long-standing systemic inflammation. Several national cohort studies have found that IBD is an independent risk factor for the development of cardiovascular disorders. However, the molecular mechanisms by which IBD impairs the cardiovascular system are not fully understood. Although the gut-heart axis is attracting more attention in recent years, our knowledge of the organ-to-organ communication between the gut and the heart remains limited. In patients with IBD, upregulated inflammatory factors, altered microRNAs and lipid profiles, as well as dysbiotic gut microbiota, may induce adverse cardiac remodeling. In addition, patients with IBD have a three- to four times higher risk of developing thrombosis than people without IBD, and it is believed that the increased risk of thrombosis is largely due to increased procoagulant factors, platelet count/activity, and fibrinogen concentration, in addition to decreased anticoagulant factors. The predisposing factors for atherosclerosis are present in IBD and the possible mechanisms may involve oxidative stress system, overexpression of matrix metalloproteinases, and changes in vascular smooth muscle phenotype. This review focuses mainly on 1) the prevalence of cardiovascular diseases associated with IBD, 2) the potential pathogenic mechanisms of cardiovascular diseases in patients with IBD, and 3) adverse effects of IBD drugs on the cardiovascular system. Also, we introduce here a new paradigm for the gut-heart axis that includes exosomal microRNA and the gut microbiota as a cause for cardiac remodeling and fibrosis.
Methods for Predicting the Minimum Temperature of the Outage Loop and the Maximum Power Caused by the Low-Temperature Coolant
Authors: Liu Xinxin , Yu Lei , Hao Jianli , Wang Xiaolong
Published: June 2023

When the feedwater valve at the outage loop of the floating nuclear power plant leaks, thermal stratification occurs in the steam generator. It causes lower water temperature in the outage loop. The extent of hazard of this phenomenon cannot be directly determined by the existing measurement parameters, which poses a threat to the operational safety of the reactor. Therefore, this study adopts two routes: data-driven combined with safety analysis system (DSAS) and mechanism model-driven combined with safety analysis system (MSAS), to propose the prediction methods for the minimum temperature of the outage loop and the maximum power caused by the low-temperature coolant. Then, the actual data are used to verify these methods and the prediction results under different initial conditions are analyzed. The results show that both the DSAS method and the MSAS method can predict the minimum temperature of the steam generator in the outage loop and the maximum power when the outage loop is put into operation, but the DSAS method has better performance under certain conditions. These methods can provide guidance to the operators to avoid reactivity insertion accident.
Influence of Different Altitudes on the Solid Rocket Contrail Formation in the Near Field
Authors: Zeng Peigao , Jiang Yi , Yang Lina , Yang Ying , Yan Song
Published: June 2023

Detecting the infrared characteristics of the contrails is a reasonable approach to tracing the rocket, and the particle properties of the contrails are the basis of the infrared analysis. The conventional numerical approach to obtaining the particle properties is a Euler/Lagrange method or a simple Euler/Euler method, difficultly obtaining more accurate results because it ignores the particle size distribution in parcels or cells. A modified Euler/Euler method is applied to simulate the contrail formation in the near field of a solid rocket motor at different altitudes, which considers the size distribution by adding the first- to second-order particle radius moments based on the simple Euler/Euler method. The simulation results show that the crystals are generated at altitudes from 10 km to 20 km and that the contrails are visible at altitudes from 10 km to 15 km, where the radii of the crystals are from 0.1 μm to 0.3 μm. The visible contrails indicate that aviation vehicles are cruising at altitudes from 10 km to 15 km, and the smaller crystals indicate that the contrails are generated by rockets, not aircraft. Our work can provide important insight for the follow-up infrared analysis of the contrails based on the obtained particle radii.