bluuebunny/crossref_metadata_2025 huggingface dataset:
A search for new back contacts for CdTe solar cells
Authors: Gorai Prashun , Krasikov Dmitry , Grover Sachit , Xiong Gang , Metzger Wyatt K. , Stevanović Vladan
Published: February 2023

There is widespread interest in reaching the practical efficiency of cadmium telluride (CdTe) thin-film solar cells, which suffer from open-circuit voltage loss due to high surface recombination velocity and Schottky barrier at the back contact. Here, we focus on back contacts in the superstrate configuration with the goal of finding new materials that can provide improved passivation, electron reflection, and hole transport properties compared to the commonly used material, ZnTe. We performed a computational search among 229 binary and ternary tetrahedrally bonded structures using first-principles methods and transport models to evaluate critical material design criteria, including phase stability, electronic structure, hole transport, band alignments, and p-type dopability. Through this search, we have identified several candidate materials and their alloys (AlAs, AgAlTe
2
, ZnGeP
2
, ZnSiAs
2
, and CuAlTe
2
) that exhibit promising properties for back contacts. We hope that these new material recommendations and associated guidelines will inspire new directions in hole transport layer design for CdTe solar cells.
Real-time (nanoseconds) determination of liquid phase growth during shock-induced melting
Authors: Renganathan Pritha , Sharma Surinder M. , Turneaure Stefan J. , Gupta Yogendra M.
Published: February 2023

Melting of solids is a fundamental natural phenomenon whose pressure dependence has been of interest for nearly a century. However, the temporal evolution of the molten phase under pressure has eluded measurements because of experimental challenges. By using the shock front as a fiducial, we investigated the time-dependent growth of the molten phase in shock-compressed germanium. In situ x-ray diffraction measurements at different times (1 to 6 nanoseconds) behind the shock front quantified the real-time growth of the liquid phase at several peak stresses. These results show that the characteristic time for melting in shock-compressed germanium decreases from ~7.2 nanoseconds at 35 gigapascals to less than 1 nanosecond at 42 gigapascals. Our melting kinetics results suggest the need to consider heterogeneous nucleation as a mechanism for shock-induced melting and provide an approach to measuring melting kinetics in shock-compressed solids.
A microbiota and dietary metabolite integrates DNA repair and cell death to regulate embryo viability and aneuploidy during aging
Authors: Sonowal Robert , Swimm Alyson I. , Cingolani Francesca , Parulekar Noyonika , Cleverley Tesia L. , Sahoo Anusmita , Ranawade Ayush , Chaudhuri Debalina , Mocarski Edward S. , Koehler Heather , Nitsche Karolina , Mesiano Sam , Kalman Daniel
Published: February 2023

During aging, environmental stressors and mutations along with reduced DNA repair cause germ cell aneuploidy and genome instability, which limits fertility and embryo development. Benevolent commensal microbiota and dietary plants secrete indoles, which improve healthspan and reproductive success, suggesting regulation of germ cell quality. We show that indoles prevent aneuploidy and promote DNA repair and embryo viability, which depends on age and genotoxic stress levels and affects embryo quality across generations. In young animals or with low doses of radiation, indoles promote DNA repair and embryo viability; however, in older animals or with high doses of radiation, indoles promote death of the embryo. These studies reveal a previously unknown quality control mechanism by which indole integrates DNA repair and cell death responses to preclude germ cell aneuploidy and ensure transgenerational genome integrity. Such regulation affects healthy aging, reproductive senescence, cancer, and the evolution of genetic diversity in invertebrates and vertebrates.
Dampening type 2 properties of group 2 innate lymphoid cells by a gammaherpesvirus infection reprograms alveolar macrophages
Authors: Loos Pauline , Baiwir Jérôme , Maquet Céline , Javaux Justine , Sandor Rémy , Lallemand François , Marichal Thomas , Machiels Bénédicte , Gillet Laurent
Published: February 2023

Immunological dysregulation in asthma is associated with changes in exposure to microorganisms early in life. Gammaherpesviruses (γHVs), such as Epstein-Barr virus, are widespread human viruses that establish lifelong infection and profoundly shape host immunity. Using murid herpesvirus 4 (MuHV-4), a mouse γHV, we show that after infection, lung-resident and recruited group 2 innate lymphoid cells (ILC2s) exhibit a reduced ability to expand and produce type 2 cytokines in response to house dust mites, thereby contributing to protection against asthma. In contrast, MuHV-4 infection triggers GM-CSF production by those lung ILC2s, which orders the differentiation of monocytes (Mos) into alveolar macrophages (AMs) without promoting their type 2 functions. In the context of γHV infection, ILC2s are therefore essential cells within the pulmonary niche that imprint the tissue-specific identity of Mo-derived AMs and shape their function well beyond the initial acute infection.
Hospital bed replacement for acute care of children at home during the COVID-19 pandemic through a Hospital-in-the-Home programme
Authors: Bryant Penelope A , Lawrence Joanna , Boyce Suzanne , Simpson Catherine M , Sinclair Gemma , Chong Candie , Lewis Phillipa , Lee Stephanie , Hughes Rebecca , Dalton Samuel , Lacey Cara , Nisbet Lauren C , Smith Tessa E , Chapman Sarah , Lakshminarayanan Swathi , Hurd Kahlia , Smith Katie , Savill Brenda , Ibrahim Laila F
Published: February 2023

Objectives

During the COVID-19 pandemic, we expanded our Hospital-in-the-Home (HITH) programme to increase capacity and manage COVID-19-positive children. We aimed to assess impact on overall HITH activity and COVID-19-positive outcomes.

Design

Prospective comparative cohort study.

Setting

The largest paediatric HITH in Australasia, at The Royal Children’s Hospital Melbourne.

Patients

Children 0–18 years admitted to HITH during the pandemic.

Intervention

We developed a COVID-19 responsive service, and a guideline for COVID-19-positive patients. We compared overall activity prior to and during the pandemic, and COVID-19-positive admissions with different variants.

Main outcomes

We compared outcomes for all HITH patients before and during the pandemic, and for COVID-19-positive patients admitted first to hospital versus directly to HITH.

Results

HITH managed 7319 patients from March 2020 to March 2022, a 21% increase to previously, with a 132% telehealth increase. 421 COVID-19-positive patients (3 days–18.9 years) were admitted to HITH, predominantly high risk (63%) or moderately unwell (33%). Rates of childhood infection in Victoria, with proportion admitted to HITH were: original/alpha variant—3/100 000/month, 0.7%; delta—92/100 000/month, 0.8%; omicron—593/100 000/month, 0.3%. Eligible parents of only 29 of 71 (41%) high-risk children were vaccinated. COVID-19-positive children admitted directly to HITH were less likely to receive COVID-19-specific treatment than those admitted to hospital first (14 of 113 (12%) vs 33 of 46 (72%), p<0.001), reflecting more severe respiratory, but not other features in inpatients. 15 of 159 (10%) were readmitted to hospital, but none deteriorated rapidly.

Conclusions

COVID-19-positive children at high risk or with moderate symptoms can be managed safely via HITH at home, the ideal place for children during the pandemic.
Unusual fusion gene rearrangements in patients with nodular fasciitis: a study of rare and novel USP6 fusion partners with a review of the literature
Authors: Balko Jan , Stanek Martin , Krskova Lenka , Zamecnik Josef
Published: February 2023

Aims

This retrospective non-randomised study aims to identify new and rare fusion partners withUSP6in the setting of nodular fasciitis. It has been proven, that nodular fasciitis can harbour different variants ofUSP6fusions, which can be used in routine diagnostics and even determine the biological behaviour of the process.

Methods

A total of 19 cases of nodular fasciitis examined between 2011 and 2022 at Motol University Hospital in Prague were included into this study. Next to the histopathological evaluation, all cases were assessed using immunohistochemistry, RT-PCR and Anchored multiplex RNA methods. Patient’s main demographic characteristics and corresponding clinical data were also analysed.

Results

This study presents one novel (KIF1A) and five rare examples (TMP4, SPARC, EIF5A, MIR22HG, COL1A2) of fusion partners withUSP6among 19 cases of nodular fasciitis.

Conclusion

Identification ofUSP6fusion partners in nodular fasciitis helps to understand the biology of such lesions. Moreover, it can be useful in routine histopathological practice of soft-tissues diagnostics, especially in preventing possible misdiagnosis of malignancy.
Scan rate and concentration dependence of the voltammograms of substituted phenols on electrodes with different size, diffusion coefficients of phenols in different solvents
Authors: Kiss László , Kunsági-Máté Sándor
Published: February 2023

In this work, the effects of the scan rate and the concentration of the substituted phenols on the peak currents or current plateaus have been investigated. Voltammetric curves recorded by a platinum microelectrode varied significantly under different experimental conditions in cases of 4-chlorophenol, 4- tert-butylphenol, and 4-nitrophenol. In the case of 4-methoxyphenol and 4- tert-butylphenol, when the experiments were performed in the lower concentration range in acetonitrile, the plateau current and peak current showed linear dependence on phenol concentration. Therefore, these ranges offer opportunity for further characterization. The electrode reaction of 4-methoxyphenol was found to be a diffusion-controlled process in the solvents applied (water, acetonitrile, dimethyl sulfoxide, dimethyl formamide, nitrobenzene, acetone, dichloromethane, methanol, ethanol, 1-propanol, 1-butanol, and 1-pentanol). Diffusion coefficients of 4-methoxyphenol were determined with a microelectrode using the steady-state voltammograms. Diffusion coefficients of other phenols were measured only in acetonitrile with a macroelectrode. In agreement with known theories, the diffusion coefficients showed inversely proportional relationships with the solvent viscosities. Special care was needed in 1-pentanol solvent since the increasing anodic peaks appeared after the first scan and overlaid with the sigmoidal-shaped regular microelectrode voltammograms. This observation is probably due to formation of adhering residual electroactive products.
Sustainability of Stack Exchange Q&A communities: the role of trust
Authors: Vranić Ana , Tomašević Aleksandar , Alorić Aleksandra , Mitrović Dankulov Marija
Published: February 2023

Knowledge-sharing communities are fundamental elements of a knowledge-based society. Understanding how different factors influence their sustainability is of crucial importance. We explore the role of the social network structure and social trust in their sustainability. We analyze the early evolution of social networks in four pairs of active and closed Stack Exchange communities on topics of physics, astronomy, economics, and literature and use a dynamical reputation model to quantify the evolution of social trust in them. In addition, we study the evolution of two active communities on mathematics topics and two closed communities about startups and compare them with our main results. Active communities have higher local cohesiveness and develop stable, better-connected, trustworthy cores. The early emergence of a stable and trustworthy core may be crucial for sustainable knowledge-sharing communities.
Using Virus Machines to Compute Pairing Functions
Authors: Ramírez-de-Arellano Antonio , Orellana-Martín David , Pérez-Jiménez Mario J.
Published: February 2023

Virus machines are computational devices inspired by the movement of viruses between hosts and their capacity to replicate using the resources of the hosts. This behavior is controlled by an external graph of instructions that opens different channels of the system to make viruses capable of moving. This model of computation has been demonstrated to be as powerful as turing machines by different methods: by generating Diophantine sets, by computing partial recursive functions and by simulating register machines. It is interesting to investigate the practical use cases of this model in terms of possibilities and efficiency. In this work, we give the basic modules to create an arithmetic calculator. As a practical application, two pairing functions are calculated by means of two different virus machines. Pairing functions are important resources in the field of cryptography. The functions calculated are the Cantor pairing function and the Gödel pairing function.
Particle shapes effects on Casson hybrid nanofluid flow over a cylinder with Cattaneo–Christov thermal model with Entropy optimization
Authors: Vijatha M. , Bala Anki Reddy P.
Published: February 2023

In this study, we investigate the effect of entropy generation on a Casson hybrid nanofluid over a stretching cylinder in the presence of linear thermal radiation and Cattaneo–Christov heat flux. We assumed [Formula: see text] and [Formula: see text] to be the nanoparticles suspended in the blood’s basic fluid for our model. Targeted drug delivery is one of the most proficient ways to diagnose and treat cancer. This is because attractive nanoparticles can be used as beneficial agents in the occurrence of both heat and an angled magnetic field. In addition, several form aspects have been taken into account. By making sure that the self-similarity transformations are accurate, the fundamental Partial Differential Equations (PDEs) are converted into Ordinary Differential Equations (ODEs). The Runge–Kutta fourth-order and firing approach are used to solve the ODEs. For the situations of cylinder and plate, homotopy perturbation method (HPM) and numerical method (NM) solutions on behalf of the nonlinear structure are obtained to compare one another. In this model, we compared the shapes of the sphere, the cylinder, the blade, the platelet and the lamina, which are all graphically represented. Additionally, the results are compared to those that have already been published and are found to be in great agreement. The performance of biological applications, particularly Radio-Frequency Identification (RFA), cancer therapy, MRI, tumor therapy and malaria disease, is improved by this kind of theoretical research.
The fluid flow characteristics around a triangular grooved cylinder
Authors: Becheffar Youcef , Chaib Khaled
Published: February 2023

The purpose of this research is to reveal the effects of roughness on the hydrodynamics of the fluid around a grooved cylinder by studying the drag and recirculation length. The main objectives are to reach the maximum reduction of the wind load. This work is carried out to investigate the effect of the number of grooves on the drag reduction of flow around a circular cylinder with triangular grooves. This investigation reports numerically on a laminar steady flow over a cylinder with 2, 4, 8, 12 and 16 triangular grooves regularly distributed around the cylinder circumference with wavelength and wave amplitude of 1/10, immersed in two-dimensional unconfined Newtonian fluid over the symmetry regimes. The predicted results showed an excellent agreement with the available data of literature for validation. The obtained results used for our investigations for a Reynolds number up to 40 suggest that the presence of the grooves on the smooth cylinder surface leads to a slight reduction over the drag coefficient and the recirculation length at the same Reynolds number, this trend is more pronounced as the number of grooves increase.
DO SMART PEOPLE PREFER TO CONSUME? THE ROLE OF COGNITIVE ABILITIES IN HOUSEHOLD CONSUMPTION
Authors: SU DONGWEI , XU SHULIN , YANG ZHEN , XIE XIN
Published: February 2023

Extant research has established that psychological factors such as risk attitude and peer effect are important antecedents of household consumption. In this paper, we investigate whether and to what extent cognitive ability affects household consumption expenditure. Using survey data in 2018 from the China Family Panel Studies (CFPS), we find that cognitive ability of the head of the household is positively related to overall consumption and non-durable consumption, i.e., smart people in China are more willing to consume. Our results are robust to controlling for level of education and accounting for potential endogeneity issues. In addition, the positive relationship between cognitive ability and household consumption is stronger for medium-income, elderly, urban and male-headed households. Moreover, wealth, information and social network play important mediating roles in the positive relationship between cognitive ability and household consumption. Overall, our study implies that broadening investment and consumption channels and enhancing information accessibility in the long term are important in stimulating household consumption.
A Weighted Inverse Minimum s − t Cut Problem with Value Constraint Under the Bottleneck-Type Hamming Distance
Authors: Ghalebala Elham Ramzani , Aman Massoud , Nasrabadi Nasim
Published: February 2023

Given a network [Formula: see text] and an [Formula: see text] cut [Formula: see text] with the capacity [Formula: see text] and the constant value [Formula: see text], an inverse minimum [Formula: see text] cut problem with value constraint is to modify the vector capacity [Formula: see text] as little as possible to make the [Formula: see text] cut [Formula: see text] become a minimum [Formula: see text] cut with the capacity [Formula: see text]. The distinctive feature of this problem with the inverse minimum cut problems is the addition of a constraint in which the capacity of the given cut has to equal to the preassumed value [Formula: see text]. In this paper, we investigate the inverse minimum [Formula: see text] cut problem with value constraint under the bottleneck weighted Hamming distance. We propose two strongly polynomial time algorithms based on a binary search to solve the problem. At each iteration of the first one, we solve a feasible flow problem. The second algorithm considers the problem in two cases [Formula: see text] and [Formula: see text]. In this algorithm, we first modify the capacity vector such that the given cut becomes a minimum [Formula: see text] cut in the network and then, by preserving optimality this [Formula: see text] cut, adjust it to satisfy value constraint.
Multi-photon-addition amplified coherent state
Authors: Zhan Xue-feng , Ke Qiang , Li Min-xiang , Xu Xue-xiang
Published: February 2023

State [Formula: see text] and state [Formula: see text] are same to state [Formula: see text], which is called as multi-photon-addition amplified coherent state (MPAACS) by us. Here, [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] are photon number operator, creation operator, coherent state, gain factor, and an integer, respectively. We study mathematical and physical properties for these MPAACSs, including normalization, photon component analysis, Wigner function, effective gain, quadrature squeezing, and equivalent input noise. Actually, the MPAACS, which contains more nonclassicality, is an amplified version of photon-added coherent state (PACS) introduced by Agarwal and Tara [Phys. Rev. A 43, 492 (1991)]. Our work provides theoretical references for implementing amplifiers for light fields.
Edge-Labeled and Node-Aggregated Graph Neural Networks for Few-Shot Relation Classification
Authors: Wang Jiayi , Yang Lina , Li Xichun , Wang Patrick Shen-Pei , Meng Zuqiang
Published: February 2023

Relation classification as a core technique for building knowledge graphs becomes a critical task in natural language processing. The fact that humans can learn by summarizing and generalizing limited knowledge motivates scholars to explore few-shot learning. Graph neural networks provide a method to measure the distance between nodes, which improves the model effect in the problem of few-shot relation classification. However, graph neural network methods focus only on node information and ignore edge information which implies inter-class and intra-class relations. This paper proposes edge-labeled and node-aggregated graph neural networks (ENGNNs) for few-shot relation classification: edge labels are encoded and used for node information aggregation. In addition, a process of semi-supervised learning is designed to discover a better solution for one-shot learning. Compared with previous methods, experimental results show that the proposed ENGNN model improves the performance of the graph neural network on the FewRel dataset.
Vision-Based Global Localization of Points of Gaze in Sport Climbing
Authors: Nguyen Tan-Nhu , Seifert Ludovic , Hacques Guillaume , Hammami Kölbl Maroua , Chahir Youssef
Published: February 2023

Investigating realistic visual exploration is quite challenging in sport climbing, but it promises a deeper understanding of how performers adjust their perception-action couplings during task completion. However, the samples of participants and the number of trials analyzed in such experiments are often reduced to a minimum because of the time-consuming treatments of the eye-tracking data. Notably, mapping successive points of gaze from local views to the global scene is generally performed manually by watching eye-tracking video data frame by frame. This manual procedure is not suitable for processing a large number of datasets. Consequently, this study developed an automatic method for solving this global point of gaze localization in indoor sport climbing. Particularly, an eye-tracking device was used for acquiring local image frames and points of gaze from a climber’s local views. Artificial landmarks, designed as four-color-disk groups, were distributed on the wall to facilitate localization. Global points of gaze were computed based on planar homography transforms between the local and global positions of the detected landmarks. Thirty climbing trials were recorded and processed by the proposed methods. The success rates (Mean[Formula: see text]±[Formula: see text]SD) were up to 85.72%[Formula: see text]±[Formula: see text]13.90%, and the errors (Mean[Formula: see text]±[Formula: see text]SD) were up to [Formula: see text][Formula: see text]m. The proposed method will be employed for computing global points of gaze in our current climbing dataset for understanding the dynamics intertwining of gaze and motor behaviors during the climbs.
An IoT-Enabled Ground Loop Detection System: Design, Implementation and Testing
Authors: Rahman Md. Saifur , Uddin Md. Palash , Kim Sikyung
Published: February 2023

The ground loop is a solemn problem in complex environments including laboratories and industries. In particular, it creates spurious signals, which interfere with low-level signals of instrumentation, and often imperil the human community. Manual ground loop detection is inefficient and requires more diagnosis time. As such, automatic ground loop detection is demanding although it is still a complex task in an environment of massive instruments. In this paper, we exploit the Internet of Things (IoT) technology to present a novel ground loop detection system to cope with such a difficult scenario. Specifically, the proposed scheme comprises an exciter block along with the IoT device to generate up to 100[Formula: see text]kHz ground loop current, and a detector module to regulate the affected cable by receiving the test current. We also use multiple detectors to give a virtual cable identity (ID) number in a complex area for recognizing the faulty cable accurately. After detecting the ground loop, the affected cable ID number is sent to the server for immediate action for prevention through the use of a smartphone (Android) application and website. The test results clarify the superiority of the proposed ground loop detection scheme in terms of accuracy, dependency and robustness.
LSTM Neural Network-Based Credit Prediction Method for Food Companies
Authors: Miao Luqi
Published: February 2023

As information technology expands across industries in the age of deep learning, companies face new changes in their credit assessment methods. One of the difficulties in financing food enterprises stems from the complexity of investment in reviewing enterprises’ credit. Therefore, this paper proposes a deep learning-based credit prediction and evaluation model for food enterprises, which performs well on the dataset and achieves 85.73% and 88.56% accuracy in verifying the performance and default test samples, respectively. In addition, the model was confirmed to have good robustness through ablation experiments. Finally, the paper concludes with relevant recommendations for food companies based on the study’s findings, offering new methods to improve their corporate credit assessment.
Identifying Notable Tuples in Multi-Concept Web Tables
Authors: Xi Yihai , Wang Ning
Published: February 2023

Identifying notable tuples in a web table is of great help for table understanding and table summarization. However, existing document-internal feature-based methods are inappropriate for identifying notable tuples in web tables. Additionally, for the web table describing multiple concepts, the notability evaluation of a tuple needs to take into account multiple entities as well as their importance in this tuple. In this paper, we investigate the task of identifying notable tuples in a multi-concept web table and propose a framework that includes three tasks: (1) identify multiple entity columns and their importance weights by building a column correlation graph based on types and relationships in the table; (2) obtain fine-grained entity notability scores based on entity link graph and provide solution for entity link failure and entity domain neglection; and (3) evaluate tuple notability by a weighted sum of notability scores of all entities in the tuple. Comprehensive evaluation of our approach is based on real-world web tables. The results demonstrate that our approach outperforms the state-of-the-art baselines by 4.6% on the precision of detecting multiple entity columns and by 12.5% on the metric normalized discounted cumulative gain (NDCG) of evaluating entity notability.
Automorphisms of affine Veronese surfaces
Authors: Aitzhanova Bakhyt , Umirbaev Ualbai
Published: February 2023

We prove that every derivation and every locally nilpotent derivation of the subalgebra [Formula: see text], where [Formula: see text], of the polynomial algebra [Formula: see text] in two variables over a field [Formula: see text] of characteristic zero is induced by a derivation and a locally nilpotent derivation of [Formula: see text], respectively. Moreover, we prove that every automorphism of [Formula: see text] over an algebraically closed field [Formula: see text] of characteristic zero is induced by an automorphism of [Formula: see text]. We also show that the group of automorphisms of [Formula: see text] admits an amalgamated free product structure.
Metaheuristic Algorithms in Optimal Power Flow Analysis: A Qualitative Systematic Review
Authors: Farag Mena Maurice , Alhamad Razan Adnan , Nassif Ali Bou
Published: February 2023

The optimal operation of any electrical power system is considered a crucial aspect in modern day optimization. The optimal power flow problem is widely known as an effective tool to plan the operation of these systems. However, due to the nonlinearity of variables such as generation cost and power losses, computation is difficult with conventional optimization methods. Therefore, various metaheuristic algorithms are implemented to solve the Optimal Power Flow (OPF) problem and overcome the possible drawback of conventional methods. This systematic review will explore various popular metaheuristic techniques that are employed to solve the optimal power flow problem such as Artificial Bee Colony (ABC), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) along with various newly introduced and emerging optimization techniques. Diverse techniques were reviewed for optimizing the OPF problem, however, deployment of artificial bee colony optimization algorithm has proved its popularity due to its fast computational speed and rate of convergence as compared to the previously established algorithms based on the reported qualitative data from existing studies. Furthermore, the qualitative data analyzed presented a higher frequency of studies adopting artificial bee colony optimization algorithm, presenting accurate results in critical power system aspects such as generation cost, real power losses, and total emissions. Additionally, this research provides the pathway for future research in improving the performance of metaheuristics when applied to the optimal power flow problem.
Deep Learning Approach for Multi-class Semantic Segmentation of UAV Images
Authors: Chouhan Avinash , Chutia Dibyajyoti , Aggarwal Shiv Prasad
Published: February 2023

Image understanding plays a very crucial role in remote sensing applications. For this, image semantic segmentation is one of the approaches where each pixel of an image is assigned to particular classes based on various features. Aerial semantic segmentation suffers from the class imbalance problem. Proper differentiation of least represented categories is challenging and a goal for the state-of-art approach. In this work, we present a novel deep learning method to perform this task. We proposed a lightweight encoder-decoder network residual depth separable UNet (RDS-UNet) and conditional random field for effective segmentation on very high-resolution aerial images. We proposed patch-with-multi-class sampling to handle the class imbalance problem without increasing the computational overhead during the training process. We created a semi-precise annotated UAV dataset named NESAC UAV Seg for the aerial semantic segmentation task. We demonstrated the efficacy of our model using the publicly available benchmark Drone Deploy dataset and our NESAC UAV Seg dataset. Our model required approximately half the number of trainable parameters and floating point operations compared to other methods. A detailed ablation study is presented to showcase the effectiveness of various modules utilized in our network.
The Ma–Qiu index and the Nakanishi index for a fibered knot are equal, and ω-solvability
Authors: Kadokami Teruhisa
Published: February 2023

For a knot [Formula: see text] in [Formula: see text], let [Formula: see text] be the knot group of [Formula: see text], [Formula: see text] the Ma–Qiu (MQ) index, which is the minimal number of normal generators of the commutator subgroup of [Formula: see text], and [Formula: see text] the Nakanishi index of [Formula: see text], which is the minimal number of generators of the Alexander module of [Formula: see text]. We generalize the notions for a pair of a group [Formula: see text] and its normal subgroup [Formula: see text], and we denote them by [Formula: see text] and [Formula: see text] respectively. Then it is easy to see [Formula: see text] in general. We also introduce a notion “[Formula: see text]-solvability” for a group that the intersection of all higher commutator subgroups is trivial. Our main theorem is that if [Formula: see text] is [Formula: see text]-solvable, then we have [Formula: see text]. As corollaries, for a fibered knot [Formula: see text], we have [Formula: see text], and we could determine the MQ indices of prime knots up to nine crossings completely.
Reconstruction and dynamical aspects of bouncing scenarios in f(T,𝒯 ) gravity
Authors: Zubair M. , Farooq Mushayydha
Published: February 2023

In this paper, our interest lies in investigating the possibilities of reconstructing analytical solutions for some familiar bouncing models in the flat Friedmann–Lemaître–Robertson–Walker (FLRW) geometry. We inspect the various gravitational Lagrangians, which are efficient enough for reproducing analytical solutions for symmetric, oscillatory, power law and bounce from loop quantum cosmology settings. Equation of state parameter, energy conditions, stability analysis have been performed for each model to examine its validity. The outcomes determine that the [Formula: see text] modified theory is the competitive candidate of extended theories on the cosmological scale.
WEAR RESISTANCE AND MICROSTRUCTURE OF THE CeO2-MODIFIED STELLITE6 BASE TUNGSTEN INERT GAS CLAD COMPOSITE COATINGS ON THE Ti–6Al–4V ALLOY
Authors: WANG MENG , LI JIANING , JING CAINIAN , FAN ZEYONG , PAN YU , ZHANG CHUNYU , LI YAJIANG
Published: February 2023

To improve the wear resistance of the titanium alloy, the tungsten inert gas cladding was used in this study. The Stellite6-CeO2-MnSi-B4C composite coatings were fabricated on the Ti–6Al–4V (TC4) alloy by the preset-powder cladding process. The scanning electron microscope analysis of the composite coatings showed the effect of the different compositions on the microstructure. The crack propagations could be retarded to some extent due to an action of B4C. The high-resolution transmission electron microscope revealed the formation of the amorphous phases and the nanocrystals. The formation of amorphous phases could be induced by the lattice distortions. The results of sliding wear tests on the samples showed that the wear resistance of TC4 could be improved due to the synergy effects of the fine grain/ dispersion/ solid solution strengthening.
Coarse computability, the density metric, Hausdorff distances between Turing degrees, perfect trees, and reverse mathematics
Authors: Hirschfeldt Denis R. , Jockusch Carl G. , Schupp Paul E.
Published: February 2023

For [Formula: see text], the coarse similarity class of A, denoted by [Formula: see text], is the set of all [Formula: see text] such that the symmetric difference of A and B has asymptotic density 0. There is a natural metric [Formula: see text] on the space [Formula: see text] of coarse similarity classes defined by letting [Formula: see text] be the upper density of the symmetric difference of A and B. We study the metric space of coarse similarity classes under this metric, and show in particular that between any two distinct points in this space there are continuum many geodesic paths. We also study subspaces of the form [Formula: see text] where [Formula: see text] is closed under Turing equivalence, and show that there is a tight connection between topological properties of such a space and computability-theoretic properties of [Formula: see text].

We then define a distance between Turing degrees based on Hausdorff distance in the metric space [Formula: see text]. We adapt a proof of Monin to show that the Hausdorff distances between Turing degrees that occur are exactly 0, [Formula: see text], and 1, and study which of these values occur most frequently in the senses of Lebesgue measure and Baire category. We define a degree a to be attractive if the class of all degrees at distance [Formula: see text] from a has measure 1, and dispersive otherwise. In particular, we study the distribution of attractive and dispersive degrees. We also study some properties of the metric space of Turing degrees under this Hausdorff distance, in particular the question of which countable metric spaces are isometrically embeddable in it, giving a graph-theoretic sufficient condition for embeddability.

Motivated by a couple of issues arising in the above work, we also study the computability-theoretic and reverse-mathematical aspects of a Ramsey-theoretic theorem due to Mycielski, which in particular implies that there is a perfect set whose elements are mutually 1-random, as well as a perfect set whose elements are mutually 1-generic.

Finally, we study the completeness of [Formula: see text] from the perspectives of computability theory and reverse mathematics.
Frequency Variation of Beam with an Internal Hinge of Rotational Restraint
Authors: Wang D.
Published: February 2023

The frequency variation problem of a classical beam with a rotationally restrained internal hinge arbitrarily located is studied intensively. The characteristic equations of the natural vibration are derived rigorously upon the corresponding boundary conditions and the compatibility conditions at the interconnecting point such that the effects of both the rotational restraint stiffness and the hinge position on the natural frequencies and mode shapes are described comprehensively. In the context, the critical locations of an internal hinge are investigated extensively to obtain the extreme values of a natural frequency of the beam system, and the associated requirements are explored in depth. It appears that the essential conditions for obtaining the critical points with regard to the maximum or minimum frequency come, respectively, from the same compatibility relation of the rotational flexibility in view of the opposite criteria. Numerical results are provided with two representative uniform beams to show the variations of their dynamic characteristics and to gain new insights into the transition conditions in the two distinct cases.
Optimum TLCD for Mitigation of Offshore Wind Turbine Dynamic Response Considering Soil–Structure Interaction
Authors: Mendes Maurício Vitali , Colherinhas Gino Bertollucci , Girão de Morais Marcus Vinícius , Pedroso Lineu José
Published: February 2023

The paper presents a parametric optimization of Tuned Liquid Column Damper (TLCD) to control the structural vibration of 5MW NREL offshore wind turbine (OWT) subject to the wind and waves random forces. In this work, the fluid–structure interaction of monopile with seawater are modeled as an added mass and the soil-structure interaction of monopile foundation is considered through simplified model of discrete coupled springs model. Using a proprietary genetic algorithm, the TLCD on nacelle has its parameters optimized to reduce the standard deviation or roots mean square (RMS) dynamic response on tower top. The displacement results are compared to the ones obtained by exhaustive search methods via a response map. From the stochastic analysis of the structure response, the ideal tuning ratio and damping ratio are determined for the liquid column damper to present its highest efficiency, i.e. the lowest RMS displacement at the tower top. The damper parameters achieved by both optimization methods show a significant agreement between them. In addition, the use of the genetic algorithm, a parametric optimization of the TLCD installed in OWT is carried out considering the random excitation of the wind, wave, and rotor forces (Kaimal, JONSWAP, and rotational spectra, respectively). In possession of the TLCD optimal parameters determined by the parametric study, the mitigation of displacements at the standard wind turbine top is analyzed. The fore-aft vibration at tower top with a TLCD attached shows a significant reduction for actions dynamic components. Finally, TLDC optimal parameters have a direct relation with the considered force spectrum and the turbine transfer function, and both must be considered for the damper optimization process.
Damage Identification of Multi-Span Bridges Using a Novel Damage Index Based on a New Algorithm for Prediction of Healthy State Displacement
Authors: Roustazadeh Soroush , Daneshjoo Farhad
Published: February 2023

Many damage identification methods are based on a comparison of structure response between healthy and damaged states. However, the healthy state response of especially old bridges is rarely available. In this paper, a new output-only damage identification approach is proposed to locate damage in multi-span bridges. In this method, only the damaged state strain and displacement influence lines are required. This approach is theoretically explained for a three-span girder. The middle span, the health condition of which is in quest, is modeled as a single-span beam, supported by rotational springs with unknown stiffness. A new algorithm is proposed to estimate the healthy state displacement influence line of the middle point of the span. In this algorithm, the ratio of the flexural stiffness of the girder to the spring’s rotational stiffness is determined in such a way that the estimated displacement, is as close to the measured response, as possible. Then, the estimated displacement is scaled based on two constraints. First, it is expected to be lower than the pseudo-static component of measured displacement because damage increases the response globally. Second, the difference between the scaled and pseudo-static component of the measured response is minimized. Eventually, damage is located using a novel damage index based on the local deviation of pseudo-static component of measured displacement from the estimated scaled response. The proposed method is numerically evaluated in a three-span girder. The damage is successfully identified in all different scenarios. Also, its application to Powder Mill Pond Bridge is numerically investigated which yielded promising results.
Effect of Axial Load and Thermal Heating on Dynamic Characteristics of Axially Moving Timoshenko Beam
Authors: Chen Hong-Yong , Wang Yuan-Cen , Wang Dong , Xie Ke
Published: February 2023

A thermoelastic coupling model of axially moving beam based on Timoshenko beam model is established, which comprehensively takes into account the length–diameter ratio, axial load and moving speed, and unify the axial tension and compression load into one governing equation, and study the influence of the length–diameter ratio, axial load, motion speed and thermal load of the beam model. The differential governing equations of transverse vibration of axially moving beam with considering the axial tensile and compressive loads are established based on the Timoshenko beam theory and Hamilton’s principle. The dynamic characteristics of different slender beams with axial load and pinned–pinned, clamped–clamped and clamped-free boundary conditions are investigated, respectively. The dimensionless frequencies of beam calculated numerically with the differential quadrature method (DQM) are compared with analytical solutions for some special cases. For axially moving beams working in the thermal environment, the temperature field inside the beam is simulated by the heat conduction equations, and the thermal effect on dynamic characteristics of beam is studied under different thermal heating cases.
Random Telegraph Noise-Based True Random Number Generator for Fully Integrated Systems
Authors: Wirth Gilson , Alves Pedro A. B. , da Silva Roberto
Published: February 2023

Generating streams of true random numbers is a critical component of many electronic and information systems. The design of fully integrated, area and power efficient true random number generators (TRNGs) is a challenge. We propose a fully integrated, lightweight implementation that uses the random telegraph noise (RTN) of standard MOSFET as entropy source. It is not analog-intensive, and without traditional post-processing algorithms, the generated random bit sequence passes the National Institute of Standards and Technology (NIST) tests.
The Price–Volume Dependences in the European and Chinese Carbon Markets: New Evidence from the Fractal Analysis
Authors: Zhu Pengfei , Wei Yu , Lu Tuantuan , Tang Yong , Zhang Chenyu
Published: February 2023

The price–volume nexus is essential for understanding and discriminating the structure of the carbon market. The current research investigates the price–volume dependences in the European carbon market and Chinese national carbon markets through fractal methods. The results demonstrate that prices have close connections with volumes at multi-time scales in both markets, and that the price–volume correlation coefficient series in the Chinese carbon market have more intense volatility, implying that it is more difficult for Chinese investors to reach consensus on prices at different time scales than European investors. In addition, there are bidirectional price–volume transmissions in both markets. Interestingly, in most cases, the influence from volume to price is much more apparent than that from price to volume in both markets, indicating that volume acts a more important role in the price–volume transmission. Finally, the European price–volume dependence has lower risk and higher efficiency than the Chinese price–volume dependence, which is due to the fact that the European market is more mature than the Chinese market. This study has both theoretical and practical applications for policymakers and investors to make optimum decisions relating to policy formation and risk management in the carbon market.
On quasi-n-ideals of commutative rings
Authors: Alhazmy K. , Almahdi F. A. A. , Bouba E. M. , Tamekkante M.
Published: February 2023

A proper ideal [Formula: see text] of a commutative ring [Formula: see text] is said to be a strongly quasi-primary ideal if, whenever [Formula: see text] with [Formula: see text], then [Formula: see text] or [Formula: see text] (see [S. Koc, U. Tekir and G. Ulucak, On strongly quasi primary ideals, Bull. Korean Math. Soc. 56(3) (2019) 729–743]). This paper studies the class of strongly quasi-primary ideals with a radical equal to the nil-radical of [Formula: see text], called the class of quasi-[Formula: see text]-ideals. Among other results, this new class of ideals is used to characterize when the nil-radical of [Formula: see text] is a maximal or a minimal ideal of [Formula: see text]. Many examples are given to illustrate the obtained results.
A Hybrid Evaluation Model for e-Learning Platforms Based on Extended TOE Framework
Authors: Ma Qi , Lin Chin-Tsai , Chen Zhixuan
Published: February 2023

E-learning platforms (ELPs) are revolutionizing the higher education system, as they offer tremendous potential to fulfill instructional plans, safeguard students’ learning rights, and improve teaching quality. Higher education institutions (HEIs) have to consider the selection of ELPs from an organizational perspective, which involves multiple stakeholders like university administrators, students, and educators. Therefore, one can take the ELP selection as a complex multi-criteria decision-making (MCDM) problem. This research proposes a new hybrid MCDM approach on the basis of the fuzzy analytic hierarchy process (FAHP) and the evaluation based on distance from the average solution (EDAS) method to select the best ELPs. First, from the organizational perspective, we extend the technology-organization-environment (TOE) framework by adding an auxiliary resource (AR) dimension and define and prioritize 4 criteria and 14 criteria for evaluating and selecting ELPs. Second, the study uses the fuzzy set theory to process the language evaluation of experts, the FAHP method to determine criteria and sub-criteria weights, and EDAS to rank the alternatives. Finally, based on the importance-performance analysis (IPA) method, we identify the most appropriate strategic options for enhancing competitiveness. Three practical cases of China’s ELP evaluation validate the proposed model’s applicability and superiority by comparing to the two other classic evaluation models. In addition, through analysis, we obtain some encouraging results that provide some references for universities to formulate ELP selection policies and offer suggestions for platform producers to further optimize the design.
Quaternionic quantum automata
Authors: Dai Songsong
Published: February 2023

Quaternionic quantum theory is a generalization of the standard complex quantum theory. Inspired by this, we study the quaternionic quantum computation using quaternions. We first develop a theory of quaternionic quantum automata as a model of quaternionic quantum computation. Quaternionic quantum automata also can be seen as an extension of complex quantum automata. Then we introduce some operations of quaternionic quantum automata and establish some of their basic properties.
Functional identities and their applications
Authors: Brešar Matej
Published: February 2023

This paper surveys the theory of functional identities and its applications. No prior knowledge of the theory is required to follow the paper.