bluuebunny/crossref_metadata_2025 huggingface dataset:
A-D hypersurface of su(n) 𝒩=2 supersymmetric gauge theory with Nf=2n−2 flavors
Authors: Itoyama H. , Oota T. , Yoshioka R.
Published: February 2023

In the previous paper, arXiv:2210.16738[hep-th], we found a set of flavor mass relations as constraints such that the [Formula: see text]-deformed [Formula: see text] quiver matrix model restores the maximal symmetry in the massive scaling limit and reported the existence of Argyres–Douglas critical hypersurface. In this paper, we derive the concrete conditions on moduli parameters which maximally degenerates the Seiberg–Witten curve while maintaining the flavor mass relations. These conditions define the A-D hypersurface.
High-order semi-rational solutions of the coupled nonlinear Schrödinger equations with variable coefficients
Authors: Cui Haoguang , Shan Wenrui , Li Qianqian , Cui Wangxi
Published: February 2023

In this paper, we consider coupled variable coefficients nonlinear Schrödinger equations (VCNLS), which can be used to describe the interaction among the modes in nonlinear optics and Bose–Einstein condensation. With the help of a gauge transformation of the spectral problem, the generalized Darboux transformation (DT) for the VCNLS is constructed. As an application of the generalized DT, we first derive the second-order and third-order semi-rational solutions of the VCNLS. In addition, we investigate the dynamics of the second-order and third-order semi-rational solutions with different coefficients. Finally we find that the coefficients [Formula: see text] and [Formula: see text] mainly affect the shape of the above solutions, while the amplification or absorption coefficient [Formula: see text] will change the amplitude. The obtained results will enrich the study of theory of the nonlinear localized waves.
Convergence of sewing conformal blocks
Authors: Gui Bin
Published: February 2023

In a recent work [On factorization and vector bundles of conformal blocks from vertex algebras, preprint (2019), arXiv:1909.04683], Damiolini et al. showed that for a [Formula: see text]-cofinite rational vertex operator algebra [Formula: see text], sheaves of conformal blocks are locally free and satisfy the factorization property. In this paper, we prove that if [Formula: see text] is [Formula: see text]-cofinite, the sewing of conformal blocks is convergent. This proves a conjecture proposed by Zhu [Global vertex operators on Riemann surfaces, Commun. Math. Phys. 165(3) (1994) 485–531] and Huang [Some open problems in mathematical two-dimensional conformal field theory, preprint (2016), arXiv:1606.04493], generalizing previous results on the convergence of products, iterates, and traces (but not pseudo-traces) of vertex operators and intertwining operators in [Y. Zhu, Modular invariance of characters of vertex operator algebras, J. Amer. Math. Soc. 9(1) (1996) 237–302; Y. Z. Huang, A theory of tensor products for module categories for a vertex operator algebra, IV, J. Pure Appl. Algebra 100(1–3) (1995) 173–216; Y. Z. Huang, Differential equations, duality and modular invariance, Commun. Contemp. Math. 7(05) (2005) 649–706; Y. Z. Huang, J. Lepowsky and L. Zhang, Logarithmic tensor category theory, VII: Convergence and extension properties and applications to expansion for intertwining maps, preprint (2011), arXiv:1110.1929] and on the convergence of projective factors related to the central charge of the Virasoro algebra in [Y. Z. Huang, Two-Dimensional Conformal Geometry and Vertex Operator Algebras, Vol. 148 (Springer Science & Business Media, 1997)].
Crow Sun Flower Optimization-Based Handover Modules in 5G Networks
Authors: Kulkarni Sanjay Sudhir , Bavarva Arjav A.
Published: February 2023

Handover modifies the user equipment using mobility in which base station provides the best one. The repeated handovers may corrupt mobility reliability due to high signaling load and therefore, network capability enhancement is affected. Here, a network management system in a network is difficult one owing to the rising number of complexity issues and base stations. In this paper, Crow Sun Flower Optimization (CSFO)-based handover method is developed for enabling efficient handover in Fifth Generation (5G) network. This handover method mainly consists of four parts, such as User Preference (UP) section, Network Quality of Service (NQ) module, power section, and Decision System (DS) module. The Quality of service (QoS) is controlled by UP section and NQ module, whereas the power module is concentrated on power. Thus, the handover is decided based on three segments and DS module is used to enable the network. The DS module is effectively decided whether to offer handover in 5G network or not. Moreover, the decision is optimally selected based on an optimization technique, named as CSFO algorithm. The developed CSFO technique is newly designed by integrating Crow Search Algorithm (CSA) and Sun Flower Optimization (SFO) technique. Additionally, three performance indicators, including received power, throughput, and user-served ratio, are used to assess how well the created CSFO-based handover model performs. High received power, throughput, and user served ratio of [Formula: see text][Formula: see text]dBm, [Formula: see text][Formula: see text]kbps and 0.071, respectively, are achieved by the developed handover strategy.
Hyper Star Fault Tolerance of Hierarchical Star Networks
Authors: Yang Lulu , Hua Xiaohui
Published: February 2023

Let H and M be two connected subgraphs of an interconnection network G. If the removal of any minimum H-structure-cut (respectively, minimum H-substructure-cut) splits G into exactly two components, one of which is isomorphic to M, then G is said to be hyper[Formula: see text]-connected (respectively, hyper sub-[Formula: see text]-connected). The hierarchical star network [Formula: see text] is one of alternative interconnection networks for multiprocessor systems. Let [Formula: see text], [Formula: see text] and [Formula: see text]. In this paper, we prove that (i) both the [Formula: see text]-structure connectivity and the sub-[Formula: see text]-structure connectivity of [Formula: see text] are n; and (ii) both the [Formula: see text]-structure connectivity and the sub-[Formula: see text]-structure connectivity of [Formula: see text] are [Formula: see text]; and (iii) [Formula: see text] is hyper [Formula: see text]-connected and hyper sub-[Formula: see text]-connected, where [Formula: see text] is the complete graph with one vertex and [Formula: see text] is a star with [Formula: see text] vertices.
Dynamic Analysis of a Coupled System of High-Speed Maglev Train and a Flexible Long-Span Continuous Rigid Frame Bridge
Authors: Li Yongle , Tian Xiangfu , Xiang Huoyue , Zhu Jin
Published: February 2023

The dynamic characteristics, deformation and installation accuracy of the bridge structure will have a greater impact on the response of maglev system. This study performs the dynamic analysis of a flexible long-span continuous rigid frame bridge induced by high-speed maglev train. To achieve this, the spatial coupling analysis model is first established. Then, the influence of track irregularities and speed on the maglev system is analyzed. In addition, the mechanism of vertical resonance of the bridge and vehicle under the action of harmonic loads at low speed is also studied by a semi-analytical approach. The results show that the influence of the long-span bridge deformation on car-body vertical acceleration is greater than that of track irregularity. The resonance exists between train and the long-span bridge at low speed. When the frequency of the harmonic loads is consistent with the basic frequency of the bridge, it will cause the bridge resonance. The resonant speed range of the rigid car-body is 20–40[Formula: see text]km/h. During bridge design, it shall be avoided that the basic frequency of the bridge is consistent with that of the vehicle.
Ergodicity of exclusion semigroups constructed from quantum Bernoulli noises
Authors: Chen Jinshu , Hai Shexiang
Published: February 2023

Quantum Bernoulli noises (QBN) are the family of annihilation and creation operators acting on Bernoulli functionals, which satisfy the canonical anti-commutation relation (CAR) in equal time. This paper aimed to discuss the classical reduction and ergodicity of quantum exclusion semigroups constructed by QBN. We first study the classical reduction of the quantum semigroups to an Abelian algebra of diagonal elements and the space of off-diagonal elements. We then provide an explicit representation formula by separating the action on off-diagonal and diagonal operators, on which they are reduced to the semigroups of classical Markov chains. Finally, we prove that the asymptotic behavior of the quantum semigroups is equivalent to one of its associated Markov chains, and that the semigroups restricted to the off diagonal space of operators have a zero limit.
Intellectual Core in Supply Chain Analytics: Bibliometric Analysis and Research Agenda
Authors: Singh Nitin , Lai Kee-Hung , Zhang Justin Zuopeng
Published: February 2023

Supply chain management has evolved from local and regional purchasing and supply activities prior to the industrial revolution to the current form of technology-led, data-driven, collaborative, and global supply network. Data-driven technologies and applications in supply chain management enable supply chain planning, performance, coordination, and decision-making. Although the literature on procurement, production, logistics, distribution, and other areas within the supply chain is rich in their respective areas, systematic analyses of supply chain analytics are relatively few. Our objective is to examine supply chain analytics research to discover its intellectual core through a detailed bibliometric analysis. Specifically, we adopt citation, cocitation, co-occurrence, and centrality analysis using data obtained from the Web of Science to identify key research themes constituting the intellectual core of supply chain analytics. We find that there has been increasing attention in research circles relating to the relevance of analytics in supply chain management and implementation. We attempt to discover the themes and sub-themes in this research area. We find that the intellectual core of SCA can be classified into three main themes: (i) introduction of big data in the supply chain, (ii) adoption of analytics in different functions of operations management like logistics, pricing and location, and (iii) application of analytics for improving performance and business value. The limitations of this study and related future research directions are also presented.
Applications of Mobile Payment Services in Financial Strategies: State-of-the-Art, Taxonomy and Upcoming Directions with a Focus on Pandemic Crisis
Authors: Liu Yijie , Li Jialing , Latifian Ahmad , Rivai Faradillah Amalia
Published: February 2023

Amid the pandemic infection, people are bound to use contactless mobile payment (M-Payment) services. M-Payment is a payment method using an application in a mobile device, such as a mobile phone, and gadget. Owing to the convenience, reliability and contact-free feature of M-Payment, it has been diffusely adopted to reduce the direct and indirect contacts in transactions, allowing social distancing to be maintained and facilitating the stabilization of the social economy. Consequently, it has become one of the day’s most important topics. Therefore, the purpose of this study is to provide a systematic literature review (SLR) on the applications of M-payment services in financial strategies, focusing on the pandemic crisis. 19 papers were collected and divided into three groups for further analysis. The results showed that M-Payments applications in financial strategies during the pandemic crisis could help reduce the spread of infection risks by hastening the transition to touchless habits.
Site Selection of Car Parking with the GIS-Based Fuzzy Multi-Criteria Decision Making
Authors: Dehghani Alireza , Soltani Ali
Published: February 2023

Rapid motorization and uncertainty in urban growth patterns make parking space management a serious task, especially in middle-income developing countries, and this has severe social, economic, and environmental repercussions including increased congestion, crash frequency, fuel and time consumption, and air pollution. Due to the complexity of the urban transportation issue and the wide variety of variables involved, a multicriteria assessment is essential. This study used fuzzy logic and geographical information systems (GIS) to develop a multi-criteria decision making (MCDM) model for managing parking in Shiraz’s central business district (CBD). The literature was mined for information on the variables that affect parking site placement, and a poll of experts ([Formula: see text]) was used to determine their relative importance. The distance to travel attraction centers, distance to roads, land price, population density, and available land for multi-storey parking were among the factors considered. Meanwhile, the parking space shortage for each TAZ is calculated by subtracting the estimated parking space supply from the estimated parking space demand. An overlay of these two layers distinguishes locations that are in parking shortage zones and also meet multiple criteria. The results may aid policymakers in controlling parking demand by pinpointing the most promising places for investment.
Scalable and Data-Independent Multi-Agent Recommender System Using Social Networks Analysis
Authors: Nazari Amin , Kordabadi Mojtaba , Mansoorizadeh Muharram
Published: February 2023

Nowadays, many online users find the selection of information and required products challenging due to the growing volume of data on the web. Recommender systems are introduced to deal with information overload. Cold start and data sparsity are the two primary issues in these systems, which lead to a decrease in the efficiency of recommender systems. To solve the problems, this paper proposes a novel method based on social network analysis. Our method leverages a multi-agent system for clustering users and items and predicting relationships between them simultaneously. The information on users and items is extracted from the user-item matrix as distinct graphs. Each of the graphs is then treated as a social network, which is further processed and analyzed by community detection and link prediction procedures. The users are grouped into several clusters by the community detection agent, which results in each cluster as a community. Then link prediction agent identifies the latent relationships between users and items. Simulation results show that the proposed method has significantly improved performance metrics as compared to recent techniques.
Coherence distillation through one-way LICC
Authors: Karmakar Sumana , Sen Ajoy , Paul Biswajit , Mukherjee Kaushiki , Chattopadhyay Indrani , Bhar Amit
Published: February 2023

Understanding the resource consumption in distributed scenario is one of the main goals in resource theory. Entanglement swapping is an important example in such scenario. It involves at least three parties. Initially two pairs are entangled and other is separable. Performing Bell measurement on common party, resource is swapped in the separable pair. In resource theory of coherence, the initial separable pair may be in free state or in resource state. This feature leads to development of the idea of coherence swapping and coherence concentration. The latter one is the generalization of the first one. Both the protocols have important role in enhancement of coherence as well as coherence fraction and in reveling resource from a noisy state.
Abstract model of continuous-time quantum walk based on Bernoulli functionals and perfect state transfer
Authors: Wang Ce
Published: February 2023

In this paper, we present an abstract model of continuous-time quantum walk (CTQW) based on Bernoulli functionals and show that the model has perfect state transfer (PST), among others. Let [Formula: see text] be the space of square integrable complex-valued Bernoulli functionals, which is infinitely dimensional. First, we construct on a given subspace [Formula: see text] a self-adjoint operator [Formula: see text] via the canonical unitary involutions on [Formula: see text], and by analyzing its spectral structure we find out all its eigenvalues. Then, we introduce an abstract model of CTQW with [Formula: see text] as its state space, which is governed by the Schrödinger equation with [Formula: see text] as the Hamiltonian. We define the time-average probability distribution of the model, obtain an explicit expression of the distribution, and, especially, we find the distribution admits a symmetry property. We also justify the model by offering a graph-theoretic interpretation to the operator [Formula: see text] as well as to the model itself. Finally, we prove that the model has PST at time [Formula: see text]. Some other interesting results about the model are also proved.
Thermodynamics, phase structure of Bardeen massive black hole in Gauss-Bonnet gravity
Authors: Singh Bhupendra , Singh Benoy Kumar , Singh Dharm Veer
Published: February 2023

This work provides the exact solution of the Bardeen black hole in association with [Formula: see text] Gauss–Bonnet massive gravity in Anti-de-Sitter [Formula: see text] space–time. It is a modification of the Gauss–Bonnet when gravity couples with nonlinear matter fields which is the function of the electromagnetic field. The obtained solution gives rise to [Formula: see text] EGB Bardeen black holes when the massive gravity parameter is set to zero and it yields a [Formula: see text] Gauss–Bonnet black hole in the absence of magnetic monopole charge. Further, we analyze and adopt the thermodynamic quantities like mass ([Formula: see text]), temperature [Formula: see text] and heat capacity [Formula: see text] in the presence of massive gravity and nonlinear electrodynamics. In addition, we extend our results by considering the cosmological constant [Formula: see text] as a thermodynamical variable [Formula: see text] and obtain the critical values of pressure, temperature, horizon radius and analyze the behavior of the global parameter [Formula: see text]. The effect of a massive parameter ([Formula: see text]) of the critical exponent is opposite to the magnetic monopole charge ([Formula: see text]) and Gauss–Bonnet parameter ([Formula: see text]). According to our analysis the phase transition between a small and large black hole and van der Waals phase transition are analogous to each other.
A Flexible Triboelectric Nanogenerator Based on MXene for Jumping Motion Monitoring
Authors: Yang Renwei , Zheng Zheng
Published: February 2023

Recently, owing to the development of artificial intelligence technology, human posture recognition has aroused great interest in the academic community. Thus, we designed a triboelectric nanogenerator based on PDMS layer and MXene/PDMS layer (PM-TENG) to obtain mechanical energy and sense human posture. According to the results, the open-circuit voltage ([Formula: see text] of PM-TENG can arrive at 372 V, and the short-circuit current ([Formula: see text] of PM-TENG can reach 16.21 [Formula: see text]A, respectively. Due to its highly sensitive sensor to complex human motor states like folding, stretching, squeezing, and tapping, it can not only be used to harvest mechanical energy from its surroundings, but also to monitor human movement and behavior. Thus, human motion behaviors like walking, leg lifting, and light and high jumps may be tracked and identified by reading pulse electrical signal production. This research will provide a new idea for human motion posture monitoring.
Investigation of electrophysical, photo- and gas-sensitive properties of ZnO–SnO2 sol–gel films
Authors: Gulyaeva Irina A. , Ivanisheva Alexandra P. , Volkova Maria G. , Storozhenko Victoria Yu. , Khubezhov Soslan A. , Bayan Ekaterina M. , Petrov Victor V.
Published: February 2023

Thin nanocomposite films based on tin dioxide with a low content of zinc oxide (0.5–5[Formula: see text]mol.%) were obtained by the sol–gel method. The synthesized films are 300–600[Formula: see text]nm thick and contains pore sizes of 19–29[Formula: see text]nm. The resulting ZnO–SnO2 films were comprehensively studied by atomic force and Kelvin probe force microscopy, X-ray diffraction, scanning electron microscopy, and high-resolution X-ray photoelectron spectroscopy spectra. The photoconductivity parameters on exposure to light with a wavelength of 470[Formula: see text]nm were also studied. The study of the photosensitivity kinetics of ZnO–SnO2 films showed that the film with the Zn:Sn ratio equal to 0.5:99.5 has the minimum value of the charge carrier generation time constant. Measurements of the activation energy of the conductivity, potential barrier, and surface potential of ZnO–SnO2 films showed that these parameters have maxima at ZnO concentrations of 0.5[Formula: see text]mol.% and 1[Formula: see text]mol.%. Films with 1[Formula: see text]mol.% ZnO exhibit high response values when exposed to 5–50[Formula: see text]ppm of nitrogen dioxide at operating temperatures of [Formula: see text]C and [Formula: see text]C.
Effects of Mn-doping on the structure and electrical properties of Sm-PMN-PT piezoceramics
Authors: Wu Chaofeng , Gong Wen , Geng Jinfeng , Cui Jianye , Mi Lipeng , Nie Jingkai , He Qiang , Li Jiajiu , Yao Fang-Zhou
Published: February 2023

Mn[Formula: see text]-modified [Formula: see text] ceramics were prepared via a solid-state reaction approach. Results of detailed characterizations revealed that the addition of Mn[Formula: see text] has influence on the grain size, and all samples exhibit a pure perovskite structure. As the content of manganese increases, the volume of tetragonal phase increases. The ceramics with 1.5 mol.% Mn[Formula: see text] show a high electro-strain of 0.151% at 2 kV/mm. Therefore, this study provides a new insight into the role of Mn[Formula: see text] addition in tailoring the electrical properties of the Sm-PMN-PT ceramics by acceptor doping.
Analysis of mechanical response of triple continuous nested tube energy absorber under low-speed compression of rigid plate
Authors: Huang Ying , Sun Bo-Hua
Published: February 2023

The nested tube system is a cost-efficient energy absorbing device that is particularly crucial for applications with constrained squeeze zones and space. Using the triple continuous nested tube (TCNT) method for nesting is quite useful. The single-stage mode and two-stage mode are its two distinctive force–displacement curve forms. In this study, finite element models suitable for TCNT structures were developed using Abaqus software, and several control groups were constructed according to different initial collapse loads. Through an in-depth analysis of each component of the TCNT, it is discovered that the stiffness competition between the two inner rings is the primary factor contributing to the step-like mechanical response. The TCNT system comprehensively outperforms the conventional single ring design for specific energy absorption (SEA). The prediction equation regarding the initial collapse load of this system is also discussed in this paper. Since the relative errors of the theoretical and numerical solutions are more concentrated, the accuracy can be increased by the amplification factor. The final polynomial fit equation obtained gives a glimpse of the full force–displacement curve.
Efficient and Effective Academic Expert Finding on Heterogeneous Graphs through (
k
, 𝒫)-Core based Embedding
Authors: Wang Yuxiang , Liu Jun , Xu Xiaoliang , Ke Xiangyu , Wu Tianxing , Gou Xiaoxuan
Published: February 2023

Expert finding is crucial for a wealth of applications in both academia and industry. Given a user query and trove of academic papers, expert finding aims at retrieving the most relevant experts for the query, from the academic papers. Existing studies focus on embedding-based solutions that consider academic papers’ textual semantic similarities to a query via document representation and extract the top-
n
experts from the most similar papers. Beyond implicit textual semantics, however, papers’ explicit relationships (e.g., co-authorship) in a heterogeneous graph (e.g., DBLP) are critical for expert finding, because they help improve the representation quality. Despite their importance, the explicit relationships of papers generally have been ignored in the literature. In this article, we study expert finding on heterogeneous graphs by considering both the explicit relationships and implicit textual semantics of papers in one model. Specifically, we define the cohesive (
k
, 𝒫)-core community of papers w.r.t. a meta-path 𝒫 (i.e., relationship) and propose a (
k
, 𝒫)-core based document embedding model to enhance the representation quality. Based on this, we design a proximity graph-based index (PG-Index) of papers and present a threshold algorithm (TA)-based method to efficiently extract top-
n
experts from papers returned by PG-Index. We further optimize our approach in two ways: (1) we boost effectiveness by considering the (
k
, 𝒫)-core community of experts and the diversity of experts’ research interests, to achieve high-quality expert representation from paper representation; and (2) we streamline expert finding, going from “extract top-
n
experts from top-
m
(
m> n
) semantically similar papers” to “directly return top-
n
experts”. The process of returning a large number of top-
m
papers as intermediate data is avoided, thereby improving the efficiency. Extensive experiments using real-world datasets demonstrate our approach’s superiority.
Representation Learning of Enhanced Graphs Using Random Walk Graph Convolutional Network
Authors: Li Xing , Wei Wei , Zhang Ruizhi , Shi Zhenyu , Zheng Zhiming , Feng Xiangnan
Published: February 2023

Nowadays, graph structure data has played a key role in machine learning because of its simple topological structure, and therefore, the graph representation learning methods have attracted great attention. And it turns out that the low-dimensional embedding representation obtained by graph representation learning is extremely useful in various typical tasks, such as node classification and content recommendation. However, most of the existing methods do not further dig out potential structural information on the original graph structure. Here, we propose wGCN, which utilizes random walk to obtain the node-specific mesoscopic structures (high-order local structure) of the graph and utilizes these mesoscopic structures to enhance the graph and organize the characteristic information of the nodes. Our method can effectively generate node embedding for data of previously unknown categories, which has been proven in a series of experiments conducted on many types of graph networks. And compared to baselines, our method shows the best performance on most datasets and achieves competitive results on others. It is believed that combining the mesoscopic structure to further explore the structural information of the graph will greatly improve the learning efficiency of the graph neural network.
Automated Identification of Toxic Code Reviews Using ToxiCR
Authors: Sarker Jaydeb , Turzo Asif Kamal , Dong Ming , Bosu Amiangshu
Published: February 2023

Toxic conversations during software development interactions may have serious repercussions on a Free and Open Source Software (FOSS) development project. For example, victims of toxic conversations may become afraid to express themselves, therefore get demotivated, and may eventually leave the project. Automated filtering of toxic conversations may help a FOSS community maintain healthy interactions among its members. However, off-the-shelf toxicity detectors perform poorly on a software engineering dataset, such as one curated from code review comments. To counter this challenge, we presentToxiCR, a supervised learning based toxicity identification tool for code review interactions. ToxiCR includes a choice to select one of the 10 supervised learning algorithms, an option to select text vectorization techniques, eight preprocessing steps, and a large-scale labeled dataset of 19,651 code review comments. Two out of those eight preprocessing steps are software engineering domain specific. With our rigorous evaluation of the models with various combinations of preprocessing steps and vectorization techniques, we have identified the best combination for our dataset that boosts 95.8% accuracy and an 88.9% F1-score in identifying toxic texts. ToxiCR significantly outperforms existing toxicity detectors on our dataset. We have released our dataset, pre-trained models, evaluation results, and source code publicly, which is available athttps://github.com/WSU-SEAL/ToxiCR.
Travel Matrix Decomposition for Understanding Spatial Long-Distance Travel Structure
Authors: Yamaguchi Hiromichi , Shibata Mashu , Nakayama Shoichiro
Published: February 2023

Mobile phone location data enable us to obtain accurate and temporally detailed long-distance travel distribution. However, the traditional long-distance travel distribution model cannot normally handle this detailed temporal information. This study proposes an approach for handling temporally detailed information of long-distance travel distribution. Considering this approach, the origin-destination matrix decomposes into two variables (indicators): destination amenity and travel cost. They can be interpreted as composite indicators of several variables that are treated in the travel-destination choice multinomial logit model. Because they are calculated only from the origin destination, we can discuss their detailed temporal variations. In this study, time changes in destination amenities and travel costs of interprefectural travel in Japan are calculated to confirm the value of this approach. These indicators have succeeded in describing the pattern of domestic long-distance travel in Japan. These quantified indicators have facilitated the understanding of the national land structure. They are useful as outcome measures for policy-making. Moreover, these indicators explain the temporal applicability of the destination choice model. Specifically, the results of destination amenities have a large seasonal variation. This indicates that the parameters of the destination amenity model (i.e., the coefficients of the destination variables) are not seasonally stable. Therefore, this must be considered when dealing with destination choice for long-distance travel.
Systematic Review and Meta-Analysis of Clinically Relevant Executive Functions Tests Performance after COVID-19
Authors: Velichkovsky Boris B. , Razvaliaeva Anna Y. , Khlebnikova Alena A. , Manukyan Piruza A. , Kasatkin Vladimir N. , Barmin Artem V.
Published: February 2023

It is widely known that COVID-19 has a number of prolonged effects on general health, wellbeing, and cognitive functioning. However, studies using differentiated performance measures of cognitive functions are still not widely spread making it hard to assess the exact functions that get impaired. Taking into account the similarities between post-COVID ‘brain fog’ and chemofog, we hypothesized that executive functions (EF) would be impaired. Literature search yielded six studies with 14 effect sizes of interest; pooled effect size was small to medium (d=−0.35). Combined with a narrative synthesis of six studies without a comparison group, these results show that EF get impaired after COVID-19; although, in most cases the impairment is transient and does not seem to be severe. These results specify the picture of ‘brain fog’ and may help to discover its mechanisms and ways of helping people with long COVID.
Wireless Binocular Stereovision Measurement System Based on Improved Coarse-to-Fine Matching Algorithm
Authors: Wang Cheng , Xiao Teng , Gong Zhiqun , Yang Shiting , Zhang Dongliang , Deng Fei
Published: February 2023

To cope with the challenges some commonly used displacement sensors may face in structural health monitoring, we proposed a wireless binocular stereovision measurement system based on the improved coarse-to-fine matching algorithm. The vision measurement system can perceive multipoint three-dimensional displacement and consists of two cameras, one remote control unit, and a solar panel. The improved coarse-to-fine matching algorithm only requires a flat surface with some painted textures instead of designed markers with refined patterns (circle, square, and chessboard). Omitting the textures keeps a balance between measurement accuracy and the burden of the target installation in the actual field of structural health monitoring. The proposed coarse-to-fine matching algorithm utilizes scale-invariant feature transform (SIFT) points to generate a robust initial guess and combines improved least squares matching (LSM) algorithm for advanced corresponding point matching. A precalculated look-up table for interpolation and parallel computation is used for higher matching precision and computational efficiency. Several experiments were conducted to present the accuracy and feasibility of the proposed metering system. A simulation test, an indoor shaking table test with several commonly used displacement sensors, and an outdoor experiment consider the natural condition. Experimental results verified that the proposed matching methodology could achieve 0.2-pixel matching accuracy, 0.1 mm measuring precision in a laboratory, and millimeter-level precision in real conditions.
Dysgerminoma Masquerading as Gestational Trophoblastic Neoplasia
Authors: Blackwell Conner , McLeish Shian , Iglesias David , Armbruster Shannon D.
Published: February 2023

Background. Persistent elevation in beta-human chorionic gonadotropin (β-hCG) following a pregnancy is concerning for gestational trophoblastic neoplasia (GTN). However, the differential diagnosis should remain broad during the evaluation process. Case. A 34-year-old G3P3 presented with elevated β-hCG four months after cesarean delivery with bilateral tubal ligation. The patient was treated with methotrexate for a presumed new ectopic pregnancy. Due to persistent β-hCG elevation, she received actinomycin-D for GTN treatment. After completing chemotherapy, her β-hCG increased. The patient underwent a laparoscopic hysterectomy with unplanned left oophorectomy due to its nodular appearance at the time of surgery. Pathology confirmed a dysgerminoma of the ovary and benign uterus. Conclusion. Although dysgerminomas are uncommon, they should be considered when β-hCG levels remain elevated despite therapies for more common pathologies.
A Case of Hepatic Malignant Solitary Fibrous Tumor: A Case Report and Review of the Literature
Authors: Fu Zhiyan , Henderson-Jackson Evita B. , Centeno Barbara A. , Lauwers Gregory Y. , Druta Mihaela , Anaya Daniel A. , Nakanishi Yukihiro
Published: February 2023

A 73-year-old man with a history of atrial myxoma and basal cell carcinoma presented with unexplained fever. Contrast-enhanced CT abdomen showed a large left hepatic lobe mass with early enhancement and delayed venous washout, concerning for hepatocellular carcinoma. Fine needle aspiration showed numerous spindle cells with malignant nuclear features, suggestive of malignant spindle cell neoplasm. The patient underwent left hepatectomy. The surgical specimen showed a well-circumscribe solid mass (

14.6
×
13.0
×
10.0
 
cm

) with necrosis. Histopathological examination revealed a proliferation of spindle tumor cells with characteristic staghorn-shaped blood vessels, frequent mitoses, and necrosis. The tumor cells showed strong and diffuse expression of CD34 and STAT6, confirming the diagnosis of malignant solitary fibrous tumor. Solitary fibrous tumor is a rare fibroblastic tumor characterized by a staghorn vasculature and NAB2-STAT6 gene rearrangement. Solitary fibrous tumor of the liver is a rare occurrence. Although most solitary fibrous tumors behave in a benign fashion, solitary fibrous tumors might act aggressively. This case is unique in that it demonstrates an excellent correlation between radiologic, macroscopic, and microscopic features which can contribute to the improvement of radiologic and pathologic diagnostic accuracy.
A Miniaturized Dual-Band Short-Ended ZOR Antenna with Backed Ground Plane for Improved Bandwidth and Radiation Efficiency
Authors: Kumar Rajkishor , Chandra Avinash , Thummaluru Sreenath Reddy , Khan Mohammad Monirujjaman , Chaudhary Raghvendra Kumar
Published: February 2023

This paper presents a miniaturized planar dual-band short-ended metamaterial antenna with the backed ground plane to improve antenna bandwidths and radiation characteristics. The proposed dual-band metamaterial (MTM) antenna has been made up of the composite right- or left-handed transmission line (CRLH-TL) concept. Here, the backed ground plane has been employed to generate an extra coupling capacitance (CC), which shifts the ZOR frequency in the lower band while also improving ZOR matching and increasing the impedance bandwidth of the higher-order mode. In this proposed MTM antenna, interdigital capacitance (IDC) has been used in place of a simple series gap, which shifts the higher-order impedance bandwidth into a lower frequency band for second-band Wi-MAX applications (3.3–3.7 GHz). The proposed antenna offers a short-ended MTM, and hence the ZOR frequency is controlled by a series of LC lumped parameters. The proposed antenna offers dual-band behavior with measured −10 dB impedance bandwidths of 5.55% and 41.57% at centered frequencies of 2.70 GHz and 4.33 GHz, respectively. The overall electrical size of the designed antenna is 0.225λ0 × 0.144λ0 × 0.0144λ0 at ZOR (f0 = 2.70 GHz), where λ0 is the free space wavelength; therefore, it is applicable for different Wi-MAX application bands (2.5–2.7 GHz/3.3–3.8 GHz). Furthermore, the proposed dual-band MTM antenna provides compactness, low loss, stable gain, and radiation efficiency, and also offers omnidirectional radiation patterns in the E-plane and dipolar type radiation patterns in the H-plane, respectively.
Extended Framework for Preventive Maintenance Planning: Risk and Behaviour Analysis of a Proposed Optimization Model
Authors: Viveros Pablo , Espinoza Marco , Mena Rodrigo , Kristjanpoller Fredy
Published: February 2023

The considerable increase in the complexity associated with the formulation of maintenance plans has enabled the development of new techniques to bring maintenance scheduling optimization models to more realistic environments. In this sense, a previous optimization model was proposed considering the use of time windows for the formation of grouping schemes under an opportunistic strategy for maintenance activities considering non-negligible execution times, thus offering the possibility of analysing scenarios with limited resources. This article proposes a risk analysis based on the failure probability of each component involved in the maintenance scheduling optimization model, which has the particularity of enabling a greater number of combinations of grouped PM activities. Moreover, it seeks to identify the general behaviour of the optimization model against different scenarios of periodicities and execution times of each maintenance activity. The proposed optimization model is formulated under a mixed integer linear programming (MILP) paradigm and its objective function seeks to minimize the unavailability of the system associated with the execution times of the activities developed, generating different experimental cases, and varying the start time scheduling under a tolerance factor from 0% up to a maximum of 25% for advance or delay. Results show in contrast with the base optimization model, an 8% less unavailability when the tolerance factor is 10%. Finally, it was possible to quantify the risk present in each maintenance schedule, at the same time a behaviour towards advancing PM activities is evidenced by the optimization model proposed over the delay.
Kalman Filter-Based Multitype Measurement Data Fusion for Stress Intensity Factor Evaluation in Marine Structures
Authors: Dai Tong-Tong , Jia Zi-Guang , Ren Liang , Fu Xing
Published: February 2023

Fracture is the main form of marine structural failure due to the action of waves and oceans. It is necessary to monitor the initiation and extension of cracks in a timely and accurate manner, and the stress intensity factor (SIF) is an important indicator for analysing the propagation of cracks. Based on existing research, this paper combines the calculation method of the SIF based on a single strain gauge (SSG) and maximum crack opening displacement (CMOD) and proposes a method based on the Kalman filter (KF). Numerical simulation and experimental verifications of this method have been carried out. The results show that the method can be used for a variety of configurations of precracked specimens. The KF-based method obtains more accurate results than the SSG-based and CMOD-based methods, and the relative error (RE) is not greater than 1.2%.
Antiproliferative Activity of PEG-PEI-SWCNTs against AMJ13 Breast Cancer Cells
Authors: Jwameer Marwa R. , Salman Sabah A. , Noori Farah T. M. , Sulaiman Ghassan M. , Jabir Majid S. , Khalil Khalil A. A. , Ahmed Elsadig M. , Soliman Mohamed T. A.
Published: February 2023

Single-walled carbon nanotubes (SWCNTs) involving polyethylene glycol (PEG) and polyethyleneimine (PEI), which contain amines, were produced and analyzed using X-ray diffraction (XRD), UV–vis spectroscopy, Raman spectroscopy (RS), and transmission electron microscopy (TEM) for the spectral and structural analyses of PEG-PEI-SWCNTs. PEG-PEI-SWCNTs demonstrated peaks using UV–vis spectroscopy at 300.98 nm, have a broad peak at 2θ = 23.51, linked to 002 with d-spacing (3.7816), and have crystalline sizes of 8.48 nm. In PEG-PEI-SWCNTs, TEM images demonstrated the accumulation of SWCNTs with PEG-PEI due to an increased main grain size with functionalization to 80.68 nm. The D and G bands in PEG-PEI-SWCNTs moved to 1,292 and 1,586 cm−1, respectively. SWCNTs are observed as a bundle of inhomogeneous, long-curved accumulates containing multitudes of tubes. The PEG-PEI-SWCNTs have a tubular structure that demonstrates particles scattered alongside the carbon nanotube sidewalls, which indicate that PEG and PEI are conjugated to the SWCNTs. Cytotoxicity evaluation of PEG-PEI-SWCNTs (6.25–100 µg/mL) in the breast cancer AMJ13 cell line was conducted for 24 and 72 hr, and the results showed enhanced toxicity to the tumor cells and decreased cytotoxicity against rhabdomyosarcoma (RD) normal cells.
Ionic Liquid-Intercalated Montmorillonite Interfacial-Reinforced Polymer Composite Scaffold
Authors: Li Dongying , Li Pin , Wang Haoyu , Du Haocheng , Liu Lixuan , Li Bin , Xu Yong , Li Mengqi , Zhou Yanrong
Published: February 2023

Montmorillonite is often used to enhance the mechanical and biological properties of polymer materials, but the weak interaction between the enhanced phase and the matrix limits the enhancement effect. Herein, ionic liquids were introduced as interfacial compatibilizer to improve the dispersion of the enhanced phase in the matrix and interaction between them, and a composite scaffold with enhanced mechanical properties was prepared by selective laser sintering. Specifically, the positively charged terminations of 1-n-butyl-3-methylimidazolium in ionic liquids were anchored to the montmorillonite interlayer domain under electrostatic action. At the same time, the long carbon chain at the other end extends in the opposite direction to increase the layer spacing of the montmorillonite, which provides enough space for the intercalation of the polyetheretherketone molecular chain. First, the blue shift of the diffraction peak in the small-angle X-ray diffraction pattern proves the successful insertion of ionic liquids into the interlayered domain of montmorillonite. In addition, the compression test results show that the compressive strength of the modified composite scaffold was increased by 23%, reaching 31.53 MPa. Besides, the composite scaffold exhibits good biomineralization capacity, which may be attributed to ion modification providing more apatite-shaped nucleation sites. These results suggested that the method of modifying inorganic fillers with ionic liquids to enhance mechanical properties and promote mineralization may be an effective means for bone scaffold modification.
Mechanism and Control Technology of Rockburst Induced by Thick Hard Roof and Residual Coal Pillar: A Case Study
Authors: Liu Wenjie , Yang Ke , He Xiang , Zhang Zhainan , Xu Rijie
Published: February 2023

Rockburst caused by the fracture of thick hard roof and the instantaneous instability of residual coal pillar seriously jeopardize the deep coal mining safety. This study takes Boertai Coal Mine, Shendong, China, as the engineering background, in which dynamic instability mechanisms of the gob-side roadway surrounding rock are analyzed by integrating field research, theoretical analysis, and numerical simulation. The results show that the overlying residual coal pillar, side abutment pressures, and front abutment pressures together induce high static stresses in the surrounding rock of the gob side roadway, with peak values exceeding the in situ stress by one order of magnitude. High stresses accumulated in the goaf-side roadway surrounding rock can easily induce dynamic disaster. With the working face advanced, overburdens are caved in succession, resulting in a continuously decreasing of the overlying residual coal pillar width, once the working face entered the influence area of the residual coal pillar. As the morphology of abutment pressure in the residual coal pillar changes from “unimodal distribution” to “bimodal distribution,” the residual coal pillar gradually changes from elastic state to plastic state. When the width of the overlying residual coal pillar is less than the critical width, the thick hard roof and residual coal pillar structure (THRRCPS) lose stability suddenly, resulting in strong dynamic load on the surrounding rock of gob-side roadway. In order to prevent the rockburst of the gob-side roadway under the influence of THRRCPS, regional and local prevention measures are adopted to mitigate the accumulation of stress in the thick hard roof and gob-side roadway surrounding rock by hydraulic fracturing technology and large diameter pressure relief drilling hole.
Preclinical Trial of Ocotea puberula (Rich.) Nees (“Canela‐Guaicá”) in Wound Healing: Validation of a Traditional Medicine Practice Used by Indigenous Groups in Southern Brazil
Authors: Arcaro Guilherme , Koga Adriana Yuriko , Carletto Bruna , Budel Giovana Manfron , Rocha Gaspar Maria Dagmar da , Nadal Jessica Mendes , Novatski Andressa , Lipinski Leandro Cavalcante , Farago Paulo Vitor , Pinheiro Luís Antonio
Published: February 2023

Background. “Canela‐guaicá,” “guaicá,” or “canela‐sebo” [Ocotea puberula (Rich.) Nees] is a native species that is traditionally used by Kaingang indigenous groups for wound healing in southern Brazil. The aim of this study was to extract the mucilage from O. puberula barks, perform its phytochemical and physicochemical characterization, and investigate its healing potential. Methods. A murine wound model was used as a preclinical trial for authentication of the traditional knowledge from Kaingang indigenous communities. Results. Alkaloids and polysaccharides were identified by usual qualitative reactions and Fourier‐transform infrared spectroscopy. This natural product showed thermal stability and pseudoplastic properties that were considered suitable for the intended use. A higher initial exacerbation of inflammatory response after 7 days, an improved angiogenesis after 14 days, and an increased wound shrinkage after 21 days were statistically significant for the “canela‐guaicá” bark extract in the preclinical trial when compared to the silver calcium alginate dressing (positive control). Conclusion. The healing potential of the “canela‐guaicá” bark extract, traditionally used by the Kaingang indigenous community from southern Brazil, was preclinically validated. This study paves the way for designing novel wound dressings containing this natural product in order to treat acute and chronic wounds.