bluuebunny/crossref_metadata_2025 huggingface dataset:
Autoantibodies associated with systemic sclerosis in three autoimmune diseases imprinted by type I interferon gene dysregulation: a comparison across SLE, primary Sjögren’s syndrome and systemic sclerosis
Authors: Andraos Rama , Ahmad Awais , Eriksson Per , Dahlström Örjan , Wirestam Lina , Dahle Charlotte , Hesselstrand Roger , Bengtsson Anders A , Jönsen Andreas , Andréasson Kristofer , Sjöwall Christopher
Published: December 2022

Objective

SLE, primary Sjögren’s syndrome (pSS) and systemic sclerosis (SSc) are heterogeneous autoimmune diseases with a dysregulated type I interferon (IFN) system. The diseases often show overlapping clinical manifestations, which may result in diagnostic challenges. We asked to which extent SSc-associated autoantibodies are present in SLE and pSS, and whether these link to serum IFN-α, clinical phenotypes and sex. Samples with clinical data from patients with SSc and healthy blood donors (HBDs) served as controls. Finally, the diagnostic performance of SSc-associated autoantibodies was evaluated.

Methods

Samples from well-characterised subjects with SLE (n=510), pSS (n=116), SSc (n=57) and HBDs (n=236) were analysed using a commercially available immunoassay (EuroLine Systemic Sclerosis Profile (IgG)). IFN-α was quantified by ELISA. Self-reported data on Raynaud’s phenomenon (RP) were available.

Results

With exceptions for anti-Ro52/SSA and anti-Th/To, SSc-associated autoantibodies were more frequent in SSc than in SLE, pSS and HBDs regardless of sex. IFN-α levels correlated with the number of positive SSc-associated autoantibodies (r=0.29, p<0.0001) and associated with Ro52/SSA positivity (p<0.0001). By using data from SLE, SSc and HBDs, RP was significantly associated with topoisomerase I, centromere protein (CENP)-B, RNA polymerase III 11 kDa, RNA polymerase III 155 kDa and PM-Scl100 whereas Ro52/SSA associated inversely with RP. In SLE, CENP-A was associated with immunological disorder, CENP-B with serositis and Ku with lupus nephritis. By combining analysis of ANA (immunofluorescence) with SSc-associated autoantibodies, the diagnostic sensitivity reached 98% and the specificity 33%.

Conclusions

The 13 specificities included in the EuroLine immunoassay are commonly detected in SSc, but they are also frequent among individuals with other diseases imprinted by type I IFNs. These findings are valuable when interpreting serological data on patients with suspected SSc, especially as patients may present with disease manifestations overlapping different rheumatological diseases. In SLE, we observed associations between manifestations and SSc-associated autoantibodies which have not previously been reported.
Glucocorticoid tapering and associated outcome in patients with newly diagnosed systemic lupus erythematosus: the real-world GULP prospective observational study
Authors: Floris Alberto , Chessa Elisabetta , Sebastiani Gian Domenico , Prevete Immacolata , Iannone Florenzo , Coladonato Laura , Govoni Marcello , Bortoluzzi Alessandra , Mosca Marta , Tani Chiara , Doria Andrea , Iaccarino Luca , Franceschini Franco , Fredi Micaela , Conti Fabrizio , Spinelli Francesca Romana , Bellisai Francesca , D'Alessandro Roberto , Zanetti Anna , Carrara Greta , Scirè Carlo Alberto , Cauli Alberto , Piga Matteo
Published: December 2022

Objective

A subanalysis of the multicentre Early Lupus inception cohort was performed to investigate the real-world Glucocorticoids (GCs) Use in newly diagnosed systemic lupus erythematosus (SLE) Patients (GULP).

Methods

Patients starting prednisone (PDN) ≥5 mg/day and concomitant hydroxychloroquine or immunosuppressant within 12 months of SLE classification were enrolled. Core set variables were recorded at baseline and every 6 months, including changes in PDN dose, European Consensus Lupus Activity Measurement (ECLAM) and Systemic Lupus International Collaborating Clinics damage index. Regression models analysed predictors of tapering PDN<5 mg/day at any time and outcomes associated with different patterns of GCs tapering.

Results

The GULP study included 127 patients with SLE; 73 (57.5%) tapered and maintained PDN <5 mg/day, and 17 (13.4%) discontinued PDN within a 2-year follow-up. Renal involvement (HR: 0.41; p=0.009) and lower C3 serum levels (HR: 1.04; p=0.025) predicted a lack of PDN tapering below 5 mg/day. High ECLAM scores were associated with a greater probability of increasing PDN dose (OR: 1.6; p=0.004), independently of daily intake. Disease relapse rate did not statistically differ (p=0.706) between patients tapering PDN <5 mg/day (42/99, 42.4%) and those tapering PDN without dropping below 5 mg/day (13/28, 46.4%). Every month on PDN <5 mg/day associated with lower damage accrual (IRR: 0.96; p=0.007), whereas never tapering PDN <5 mg/day associated with a higher risk of developing GC-related damage (OR 5.9; p=0.014).

Conclusion

Tapering PDN <5 mg/day was achieved and maintained in half of newly diagnosed patients with SLE and may represent a good balance between the need to prevent damage accrual and the risk of disease relapse.
AN ANALYSIS OF THE INITIAL PRESALE RATE IN HOUSING PROJECTS USING A REGIME-SWITCHING MODEL
Authors: KIM MYEONG HYEON , BANG DOO WON , KWON HYUCK SHIN
Published: December 2022

We analyzed to identify the determinants affecting the presale rate in the housing projects and verified whether there are differences in the determinants of that by regimes. We found that the effects of determinants, such as the ratio of the new apartments’ sales price to existing apartments’ prices, educational environment, the number of unsold houses, and the interest rate of a mortgage on the initial presale rate, could have been different depending on which regime the housing market belongs to. This suggests that the government in Korea and Asian countries should consider the differentiation in effects of the determinants depending on the regime when the government tries to make housing policies.
ASYMMETRIC MULTIFRACTAL CROSS-CORRELATION DYNAMICS BETWEEN FIAT CURRENCIES AND CRYPTOCURRENCIES
Authors: FERNANDES LEONARDO H. S. , KRISTJANPOLLER WERNER , TABAK BENJAMIN MIRANDA
Published: December 2022

This paper performs the asymmetric multifractal cross-correlation analysis to examine the COVID-19 effects on three relevant high-frequency fiat currencies, namely euro (EUR), yen (YEN) and the Great Britain pound (GBP), and two cryptocurrencies with the highest market capitalization and traded volume (Bitcoin and Ethereum) considering two periods (Pre-COVID-19 and during COVID-19). For both periods, we find that all pairs of these financial assets are characterized by overall persistent cross-correlation behavior [Formula: see text]. Moreover, COVID-19 promoted an increase in the multifractal spectrum’s width, which implies an increase in the complexity for all pairs considered here. We also studied the Generalized Cross-correlation Exponent, which allows us to verify that there is no asymmetric behavior between Bitcoin and fiat currencies and between Ethereum and fiat currencies. We conclude that investing simultaneously in major fiat currencies and leading cryptocurrencies can reduce the portfolio risk, leading to improvement in the investment results.
On stopping rules for tree-indexed quantum Markov chains
Authors: Souissi Abdessatar
Published: December 2022

In the present paper, we introduce stopping rules and related notions for quantum Markov chains on trees (QMCT). We prove criteria for recurrence, accessibility and irreducibility for QMCT. This work extends to trees the notion of stopping times for quantum Markov chains (QMC) introduced by Accardi and Koroliuk, which plays a key role in the study of many properties of QMC. Moreover, we illustrate the obtained results for a concrete model of XY-Ising type.
CLOUDS IN THE BASINS OF FULLY ASYNCHRONOUS CELLULAR AUTOMATA
Authors: ROY SOUVIK , DAS SUKANTA
Published: December 2022

This paper studies the basins of attraction of fully asynchronous cellular automata (ACAs) that converge to point attractor. Unlike traditional (synchronous) cellular automata (CAs), an ACA may approach to different point attractors from the same initial condition for different runs. In this direction, this paper introduces the notion of cloud behavior in convergence dynamics of ACAs. Depending on the cloud behavior, we classify the convergent ACAs into three classes—eccentric cloud, partially eccentric cloud and deterministic cloud system. In addition, this study observes the computational ability of addressing density classification problem (i.e. distributed consensus problem) of this asynchronous cloud system.
Fabrication of Micro-Hole in 3D Printed CFRP Composite by Electrical Discharge Machining Process
Authors: Debnath Kishore , Behera Bikash Chandra , Rout Matruprasad , Rao Gorrepotu Surya
Published: December 2022

Carbon fiber-reinforced polymer (CFRP) composite has extensive application in several industries, including the automotive and aerospace industries. Fabrication of micro-features in CFRP composite is an important process that is frequently performed for various applications including for micro-products and micro-components. The fabrication of precise micro-features in CFRP composite is difficult to achieve by conventional means, even by additive manufacturing (AM). Thus, in this study, the machinability characteristics of the CFRP composite were experimentally investigated. CFRP composite was fabricated by using the AM technique. The different process parameters of 3D printing (infill density and layer sequence) and micro-EDM (voltage, capacitance, and tool rotation) were considered to investigate their effect on the hole quality and productivity. The optimization of the different parameters chosen for the purpose of the investigation was also carried out. The important process parameters that have an impact on the process were identified and analyzed. The better machining performance of CFRP composite was noticed at higher infill density and alternative fiber arrangement. The capacitance was the most significant parameter among all the EDM parameters to produce good quality micro-holes in CFRP composite.
A robust method for coherent and non-coherent source number detection using a special Hankel-based covariance matrix
Authors: Fazli Roohallah , Owlia Hadi , Sheikhpour Razieh
Published: December 2022

A robust algorithm for source number estimation based on the formation of the Hankel covariance matrix is presented. First, multiple data snapshots are taken successively from overlapped subarrays in a way similar to the forward spatial smoothing method to construct the special Hankel covariance matrix and for the total number of subarrays, these special covariance matrices are generated. Then, the average of these matrices is employed in singular value decomposition to generate the corresponding eigenvalues. Finally, the resulting eigenvalues are evaluated via the rule presented in this paper as the Moving Gradient Criterion (MGC) to estimate the number of sources by detection of the largest singular values. The greatest difference between the proposed algorithm and the other conventional methods is the form of the covariance matrix with the observed signal that can handle both non-coherent as well as fully coherent sources. Also, the proposed MGC rule adopted with this form of the covariance matrix is the strength of this work. Numerical simulations demonstrate the high superiority of the proposed approach over the competing methods such as MDL, AIC, SORTE, RAE and MSEE methods, especially in the cases of very closely spaced sources, low SNR values, low sensors number and low snapshots number.
Complex dynamics of a discrete-time SIR model with nonlinear incidence and recovery rates
Authors: Yu Xiao , Liu Ming , Zheng Zhaowen , Hu Dongpo
Published: December 2022

In this paper, a discrete-time SIR epidemic model with nonlinear incidence and recovery rates is obtained by using the forward Euler’s method. The existence and stability of fixed points in this model are well studied. The center manifold theorem and bifurcation theory are applied to analyze the bifurcation properties by using the discrete time step and the intervention level as control parameters. We discuss in detail some codimension-one bifurcations such as transcritical, period-doubling and Neimark–Sacker bifurcations, and a codimension-two bifurcation with 1:2 resonance. In addition, the phase portraits, bifurcation diagrams and maximum Lyapunov exponent diagrams are drawn to verify the correctness of our theoretical analysis. It is found that the numerical results are consistent with the theoretical analysis. More interestingly, we also found other bifurcations in the model during the numerical simulation, such as codimension-two bifurcations with 1:1 resonance, 1:3 resonance and 1:4 resonance, generalized period-doubling and fold-flip bifurcations. The results show that the dynamics of the discrete-time model are richer than that of the continuous-time SIR epidemic model. Such a discrete-time model may not only be widely used to detect the pathogenesis of infectious diseases, but also make a great contribution to the prevention and control of infectious diseases.
On finite rings with a certain number of centralizers
Authors: Chan Tai Chong , Qua Kiat Tat , Wong Denis Chee Keong
Published: December 2022

Let [Formula: see text] denote the set of all distinct centralizers in a ring [Formula: see text]. A ring [Formula: see text] is said to be [Formula: see text]-centralizer ring if [Formula: see text], where [Formula: see text]. In this paper, we illustrate some connections between the centralizers and pairwise non-commuting elements of a finite ring. Besides that, we characterize all [Formula: see text]-centralizer finite rings for [Formula: see text], and also compute the commuting probability for all [Formula: see text]-centralizer finite rings for [Formula: see text].
Effect of compaction pressure on electrochemical performance of layered lithium-rich oxide
Authors: Gao Shengqing , Chen Dongrui , Zhou Jinhua , Zhang Shenwei
Published: December 2022

Lithium-rich oxide cathode material focuses the attention of many researchers due to its excellent electrochemical performance for lithium–ion batteries. Further improvement on the performance with a strong operability approach can be beneficial to its industrialization and commercialization. In this work, the effect of powder compaction pressure in sintering process on the electrochemical performance of Li[Formula: see text]Mn[Formula: see text]Ni[Formula: see text]Co[Formula: see text]O2 cathode material is investigated. Four cathode materials under different powder compaction pressure are synthesized by sol–gel method. The XRD analysis results reveal their consistency on the crystal structure. But there is a slight difference on particle size and microstructure found by SEM analysis. Electrochemical tests show that a cathode material under medium compaction pressure exhibits the best performance with a discharge capacity of 170.3 mAh⋅g[Formula: see text] at the rate of 200 mA⋅g[Formula: see text] with 89.35% retention after 100 cycles. This work reveals that the powder compaction pressure does have influence on the cycle and rate performance and this relation is not proportional and linear.
Functional Properties of Cobalt-Based Amorphous Ribbons with Different Demagnetizing Factor
Authors: Pasynkova A. A. , Timofeeva A. V. , Lukshina V. A.
Published: December 2022

Co-based rapidly quenched amorphous ribbons are soft ferromagnets with well-adjustable functional properties. Their effective magnetic anisotropy and magnetization processes depend on the preparation conditions and geometrical parameters. It was found that giant magnetoimpedance effect (MI) for the FeCoCrSiB ribbons without heat treatments after relaxation annealing and after stress annealing at 350∘C shows critical dependence on the value of the demagnetizing factor. The range of FeCoCrSiB ribbons lengths with a significant change in properties is considered in a comparative analysis of the experimental results and model calculations. Quantitative analysis of the contribution of the demagnetizing fields and surface magnetic charges are discussed as the main mechanism for reducing the GMI properties of amorphous ribbons. These data are important for the development of the ribbon-based devices for practical applications of microelectronics.
Communication Channels and their Challenges
Authors: Neves de Souza Adriano , Ferreira da Silva Sírius Thadeu , Baptista dos Santos França Juliana , Fonseca da Silva Dias Angélica , Oliveira Jonice , Vivacqua Adriana S.
Published: December 2022

Software development teams depend on the constant and varied use of technological tools that contribute to the fluidity of development activities. The communication channels provided by these tools contribute to the participatory culture of software development, where requirements include getting involved, learning and co-producing the code. However, the choice of channels to support development is still an open question in the scientific community. Through an investigation of closed remote software teams from a large public educational institution in Brazil during the COVID-19 Pandemic, we identified their preferred communication channels and analyzed them to learn how to improve collaboration. We also drew some comparison with social developers and took a look at the challenges that these channels impose and solutions adopted to mitigate these problems.
Duty to Respond
Authors: Caddle Xavier V. , Naher Nurun , Miller Zachary P. , Badillo-Urquiola Karla , Wisniewski Pamela J.
Published: December 2022

Social service providers play a vital role in the developmental outcomes of underprivileged youth as they transition into adulthood. Educators, mental health professionals, juvenile justice officers, and child welfare caseworkers often have first-hand knowledge of the trials uniquely faced by these vulnerable youth and are charged with mitigating harmful risks, such as mental health challenges, child abuse, drug use, and sex trafficking. Yet, less is known about whether or how social service providers assess and mitigate the
online
risk experiences of youth under their care. Therefore, as part of the National Science Foundation (NSF) I-Corps program, we conducted interviews with 37 social service providers (SSPs) who work with underprivileged youth to determine what (if any) online risks are most concerning to them given their role in youth protection, how they assess or become aware of these online risk experiences, and whether they see value in the possibility of using artificial intelligence (AI) as a potential solution for online risk detection. Overall, online sexual risks (e.g., sexual grooming and abuse) and cyberbullying were the most salient concern across all social service domains, especially when these experiences crossed the boundary between the digital and the physical worlds. Yet, SSPs had to rely heavily on youth self-reports to know whether and when online risks occurred, which required building a trusting relationship with youth; otherwise, SSPs became aware only after a formal investigation had been launched. Therefore, most SSPs found value in the potential for using AI as an early detection system and to monitor youth, but they were concerned that such a solution would not be feasible due to a lack of resources to adequately respond to online incidences, access to the necessary digital trace data (e.g., social media), context, and concerns about violating the trust relationships they built with youth. Thus, such automated risk detection systems should be designed and deployed with caution, as their implementation could cause youth to mistrust adults, thereby limiting the receipt of necessary guidance and support. We add to the bodies of research on adolescent online safety and the benefits and challenges of leveraging algorithmic systems in the public sector.
Explaining Why Fake Photos are Fake
Authors: Ruffin Margie , Wang Gang , Levchenko Kirill
Published: December 2022

Today's disinformation campaigns may use deceptively altered photographs to promote a false narrative. In some cases, viewers may be unaware of the alteration and thus may more readily accept the promoted narrative. In this work, we consider whether this effect can be lessened by explaining to the viewer how an image has been manipulated. To explore this idea, we conduct a two-part study. We started with a survey (n=113) to examine whether users are indeed bad at identifying manipulated images. Our result validated this conjecture as participants performed barely better than random guessing (60% accuracy). Then we explored our main hypothesis in a second survey (n=543). We selected manipulated images circulated on the Internet that pictured political figures and opinion influencers. Participants were divided into three groups to view the original (unaltered) images, the manipulated images, and the manipulated images with explanations, respectively. Each image represents a single case study and is evaluated independently of the others. We find that simply highlighting and explaining the manipulation to users was not always effective. When it was effective, it did help to make users less agreeing with the intended messages behind the manipulation. However, surprisingly, the explanation also had an opposite (e.g.,negative) effect on users' feeling/sentiment toward the subjects in the images. Based on these results, we discuss open-ended questions which could serve as the basis for future research in this area.
Group Effect Aspects in Digitalisation Production Contexts
Authors: Pinatti de Carvalho Aparecido Fabiano , Reichel Sarah , Sanchez Martin Marcel Manuel , Allen Eva Sonja , Schweitzer Marcus
Published: December 2022

Across the years, production systems have recurrently turned to new digital technologies in the search for enhanced productivity and competitiveness. More recently, a prelude to a Fourth Industrial Revolution has been heard, announcing Industry 4.0 as the future of production and manufacture. It has been claimed that cyber-physical production systems would bring drastic changes in the way that people go about engaging in work. It is therefore sensible to think that the way that cooperation is accomplished within production contexts will be also affected. Based on an in-depth interview study featuring 21 participants from different companies, we go on to discuss which challenges have been emerging from recent digitalisation of production work in regard to the way that workers cooperate in accomplishing their productive activities. Our results suggest that there are associated group effects - e.g., group polarisation, hidden profiles, and exclusion - that pose relevant challenges for cooperation within these settings. In this contribution, we go on to present and discuss these results and to propose articulation spaces, which conceptually bring together aspects of coordination mechanisms and common information spaces, as a potential solution for some of those challenges.
Tech Worker Perspectives on Considering the Interpersonal Implications of Communication Technologies
Authors: Maris Elena , Wagman Kelly B. , Bergmann Rachel , Bragg Danielle
Published: December 2022

Communication technologies, from social media to video conferencing, are used by billions of people globally and contribute to shaping relationships between people. As these technologies become increasingly ubiquitous, the tech workers building them are increasingly making product decisions that can have far-reaching interpersonal ramifications. At the same time, few workplace tools and support exist to help tech workers understand and navigate these potential ramifications, and tech worker perspectives on such tools are not fully understood. In this work, we explore the needs, challenges, and opportunities encountered by tech workers in thinking through the interpersonal implications of their products. To do this, we ran a semi-structured interview study with 10 diverse tech workers. To ground the discussion, study participants interacted with a design probe prototype, InterAct, which provides research-grounded information about interpersonal implications of product features. Our findings suggest a desire by tech workers to consider the social implications of the technologies they build, and the potential for structured tooling to help provide the required knowledge and build organizational support. Based on these findings, we provide design considerations for creating future workplace tools to support thinking about the social implications of technologies.
Graph Attention Transformer Network for Multi-label Image Classification
Authors: Yuan Jin , Chen Shikai , Zhang Yao , Shi Zhongchao , Geng Xin , Fan Jianping , Rui Yong
Published: December 2022

Multi-label classification aims to recognize multiple objects or attributes from images. The key to solving this issue relies on effectively characterizing the inter-label correlations or dependencies, which bring the prevailing graph neural network. However, current methods often use the co-occurrence probability of labels based on the training set as the adjacency matrix to model this correlation, which is greatly limited by the dataset and affects the model’s generalization ability. This article proposes a Graph Attention Transformer Network, a general framework for multi-label image classification by mining rich and effective label correlation. First, we use the cosine similarity value of the pre-trained label word embedding as the initial correlation matrix, which can represent richer semantic information than the co-occurrence one. Subsequently, we propose the graph attention transformer layer to transfer this adjacency matrix to adapt to the current domain. Our extensive experiments have demonstrated that our proposed methods can achieve highly competitive performance on three datasets.
SSR-Net: A Spatial Structural Relation Network for Vehicle Re-identification
Authors: Xu Zheming , Wei Lili , Lang Congyan , Feng Songhe , Wang Tao , Bors Adrian G. , Liu Hongzhe
Published: December 2022

Vehicle re-identification (Re-ID) represents the task aiming to identify the same vehicle from images captured by different cameras. Recent years have seen various feature learning-based approaches merely focusing on feature representations including global features or local features to obtain more subtle details to identify highly similar vehicles. However, few such methods consider the spatial geometrical structure relationship among local regions or between the global and local regions. By contrast, in this study, we propose a Spatial Structural Relation Network (SSR-Net) that explores the above-mentioned two kinds of relations simultaneously to learn more discriminative features by modeling the spatial structure information and global context information. In this article, we propose to adopt a Graph Convolution Network (GCN), for modeling spatial structural relationships among characteristic features. The GCN model aggregating the local and global features is shown to be more discriminative and robust to several car image transformations. To improve the performance of our proposed network, we jointly combine the classification loss with metric learning loss. Extensive experiments conducted on the public VehicleID and VeRi-776 datasets validate the effectiveness of our approach in comparison with recent works.
A Universal Law of Robustness via Isoperimetry
Authors: Bubeck Sébastien , Sellke Mark
Published: December 2022

Classically, data interpolation with a parametrized model class is possible as long as the number of parameters is larger than the number of equations to be satisfied. A puzzling phenomenon in deep learning is that models are trained with many more parameters than what this classical theory would suggest. We propose a partial theoretical explanation for this phenomenon. We prove that for a broad class of data distributions and model classes, overparametrization is
necessary
if one wants to interpolate the data
smoothly
. Namely we show that
smooth
interpolation requires
d
times more parameters than mere interpolation, where
d
is the ambient data dimension. We prove this universal law of robustness for any smoothly parametrized function class with polynomial size weights, and any covariate distribution verifying isoperimetry (or a mixture thereof). In the case of two-layer neural networks and Gaussian covariates, this law was conjectured in prior work by Bubeck, Li, and Nagaraj. We also give an interpretation of our result as an improved generalization bound for model classes consisting of smooth functions.
Antioxidative Effect of Amomum testaceum Ridl. Extract for Protecting against Vascular Dementia
Authors: Kaewkaen Pratchaya
Published: December 2022

Vascular dementia is caused by decreased blood flow to the brain, which leads to neuronal damage and subsequent death. Therefore, development of alternative neuroprotective agents is critical. This study is aimed at investigating the effects of Amomum testaceum Ridl. extract or Siam cardamom extract (SCE) on oxidative markers in a rat model of vascular dementia. The phenolic content of SCE, represented as gallic acid equivalent (mg/100 GAE), was discovered to be

128.56
±
0.58

 mg/100 GAE. The EC50 values for the 2,2-diphenyl-1-picrylhydrazyl radical scavenging activities of SCE were

32.48
±
0.39

 ug/mL. In addition, the reducing power of SCE, via a ferric reducing antioxidant power assay, was also determined, with an EC50 value of

142.55
±
0.56

 ug/mL. SCE was administered orally to adult male Wistar rats weighing 250–300 g at doses of 100, 300, and 500 mg/kg over the course of 14 days; then, the rats underwent surgery of the right middle cerebral artery, producing an occlusion imitating vascular dementia in a controlled environment. All rats were euthanized to obtain brain tissue for biochemical testing and analysis. The results showed that malondialdehyde decreased and superoxide dismutase, catalase, and glutathione peroxidase increased at all doses (100, 300, and 500 mg/kg) of SCE (

P
<
0.05

). In addition, SCE was shown to lower the expression level of S100B, a marker of neurologic injury (

P
<
0.05

). The free radical scavenging and anti-inflammatory capabilities of SCE suggest that it has the potential to be used as a food supplement to protect against oxidative damage in vascular dementia. However, further clinical investigations are essential to elucidate this in clinical trials.
Clustering Ant Colony-Based Edge-Server Location Strategy in Mobile Crowdsensing
Authors: Gad-Elrab Ahmed. A. A. , Noaman Amin Y.
Published: December 2022

Recently, edge-based mobile crowdsensing has become an important sensing technology that takes advantage of mobile devices to collect information about surroundings based on using a group of mobile edge servers that are deployed at the network edge as a link between users and the central server for data filtering and aggregation. Each user may collect multiple data types in mobile collective sensing. For facilitating data aggregation, the same data type carried by various users is assumed to be uploaded to the same mobile edge server. The main problem is determining the server which should be activated to process each data type for reducing the overall cost. In this paper, the problem is formulated as one form of the unqualified multicommodity facility location problem. To solve this problem, two edge-server location strategies are proposed, which use a clustering method for dividing the set of mobile users with data items into clusters and use the ant colony approach to select a mobile edge server for each data type in each cluster. Extensive simulations are conducted based on widely used real data sets. The simulation results show that the proposed strategy achieves better performance than the existing methods in terms of service and facility costs.
Refined Voting and Scene Feature Fusion for 3D Object Detection in Point Clouds
Authors: Yu Hang , Su Jinhe , Piao Yingchao , Cai Guorong , Lin Yangbin , Liu Niansheng , Liu Weiquan
Published: December 2022

An essential task for 3D visual world understanding is 3D object detection in lidar point clouds. To predict directly bounding box parameters from point clouds, existing voting-based methods use Hough voting to obtain the centroid of each object. However, it may be difficult for the inaccurately voted centers to regress boxes accurately, leading to the generation of redundant bounding boxes. For objects in indoor scenes, there are several co-occurrence patterns for objects in indoor scenes. Concurrently, semantic relations between object layouts and scenes can be used as prior context to guide object detection. We propose a simple, yet effective network, RSFF-Net, which adds refined voting and scene feature fusion for indoor 3D object detection. The RSFF-Net consists of three modules: geometric function, refined voting, and scene constraint. First, a geometric function module is used to capture the geometric features of the nearest object of the voted points. Then, the coarse votes are revoted by a refined voting module, which is based on the fused feature between the coarse votes and geometric features. Finally, a scene constraint module is used to add the association information between candidate objects and scenes. RSFF-Net achieves competitive results on indoor 3D object detection benchmarks: ScanNet V2 and SUN RGB-D.
A Network Pharmacology-Based Study of Potential Targets of Angelicae Pubescentis-Herba Taxilli Compound for the Treatment of Osteoarthritis
Authors: Zhao Jie , Zhao Fu-Chang , Li Gang
Published: December 2022

Objective. Using network pharmacology and molecular docking, we explored the mechanism of Angelicae Pubescentis- (AP-) Herba Taxilli (HT) in the treatment of osteoarthritis (OA). Methods. We selected Traditional Chinese Medicine Systems Pharmacology platform (TCMSP) to filtrate the practical components and targets of AP-HT. The disease targets of “osteoarthritis (OA)” were collected by GeneCards, DrugBank, TTD, OMIM, and PharmGKB databases, and the component-target interaction network was established by Cytoscape 3.9.1. Then, we set the protein-protein interaction (PPI) network by the STRING platform and visualized by Cytoscape 3.9.1. We also conducted Gene Ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis via the bioinformatics platform. Finally, we performed molecular docking using PyMOL 2.3.0 and AutoDock Vina software. Results. 11 potential compounds were selected, and 1007 OA disease targets were collected. Ninety-four main targets of the AP-HT compound in the treatment of OA have been defined. PPI network demonstrated that JUN, RELA, TNF, IL6, MAPK1, TP53, AKT1, FOS, IL10, and MYC might serve as the critical targets of AP-HT for the treatment of OA. Moreover, membrane raft, membrane microdomain, cellular response to chemical stress, and cytokine receptor binding may play essential roles in the treatment of OA via GO analysis. The main functional pathways involved in these critical targets include fluid shear stress and atherosclerosis, lipid and atherosclerosis, IL-17 signaling pathway, age-range signaling pathway in diabetic composites, and TNF signaling pathway via KEGG analysis. The results of molecular docking showed that the critical ingredients of AP-HT had an excellent affinity to related nuclear genes.
Application of Mathematical Morphology in Solving the Profile of Forming Grinding Wheel
Authors: You Minglin , Yao Bin
Published: December 2022

In the development of modern tools, the flute (or profiling flute) after design optimization is often obtained by grooving with a forming grinding wheel. At present, the main method of reverse forming wheel profile is the analytical method, which needs to solve the contact line equation according to the contact conditions. It is difficult to solve the equation. The solution value is unstable, which leads to the design error of the grinding wheel profile. In order to solve this problem, this paper proposes a new algorithm, called the pixel matrix method for short. This method is based on the spiral motion envelope method and mathematical morphology. First, the cross-section of the flute is discretized into a point cloud, and then, the envelope motion is carried out in the grinding wheel coordinate system. Second, the point cloud of the grinding wheel radial section is collected and converted into a binary image of pixel points. Finally, the profile of the binary image is extracted by erosion and dilation. The optimized profile of the formed grinding wheel reaches the accuracy requirements of the design and processing in the actual machining verification. This method can accurately reverse the profile of the forming grinding wheel. The calculation process is intuitive, avoiding the solution of the contact line equation, and the solution value is stable. It provides a new way to reverse the profile of the machining tool for cylindrical spiral products.
Wireless Communications and Mobile Computing Multitrack Music Generation Network Based on Music Rules
Authors: Tie Yun , Wang Tao , Jin Cong , Li Xiaobing , Yang Ping
Published: December 2022

Multitrack music generation technology is becoming more and more mature, but the existing generation technology cannot reach the desired effect in terms of harmony and matching degree, and most of the generated music does not conform to the music theory knowledge. In order to solve these problems, we propose a multitrack music generation network based on transformer to produce music with high musicality under the guidance of music theory rules. This paper uses an improved version of transformer to learn the information inside a single-track sequence and between different tracks. Then, a combination of music theory rules and crossentropy loss is used to guide the training of the generated network, and the well-designed loss objective function is optimized while the discrimination network is trained. Compared with other multitrack music generation models, the validity of our model is proved.
Composite Terminal Guidance Law for Supercavitating Torpedoes with Impact Angle Constraints
Authors: Xu Dongxue , Zhang Jingyuan , Wang Peng , Yan Xiaojia , Dong Haidi
Published: December 2022

A novel composite terminal guidance law with impact angle constraints is proposed for supercavitating torpedoes to intercept maneuvering warships. Based on an adaptive super-twisting algorithm and nonsingular terminal sliding mode (NTSM), the proposed guidance law can guarantee the finite-time convergence of line-of-sight (LOS) angle error and the LOS angular rate error. The new guidance law is a combination of finite-time stability theory, sliding mode control (SMC), tracking differentiator (TD), disturbance observer (DO), and dynamic surface control. A high-order sliding mode TD is used for denoising, tracking, and differentiating the measured target heading angle. A novel DO, with its finite-time stability proved, is designed to estimate the target lateral acceleration for feedforward compensation to attenuate chattering in control input. In the case of a first-order-lag autopilot, a new kind of tracking differentiator is adopted to compute the first-order time derivative of the virtual control command, which can improve the accuracy of dynamic surface control and avoid the “explosion of items” problem encountered with the backstepping control. Finally, numerical simulation results are presented to validate the effectiveness and superiority of the proposed TD, DO, and the composite guidance law.
Breast Cancer and Arsenic Anticancer Effects: Systematic Review of the Experimental Data from In Vitro Studies
Authors: Skoczynska Anna , Skoczynska Marta
Published: December 2022

Arsenic is a known environmental carcinogenic agent. However, under certain circumstances, it may exert anticancer effects. In this systematic review, we aim to provide information on recent developments in studies on arsenic antitumor effects in breast cancer. Research included in the review refers to experimental data from in vitro studies. The data was collected using search terms “breast cancer,” “arsenic,” and “anticancer” (25.05.2021). Only studies in English and published in the last 10 years were included. The search identified 123 studies from the EBSCOhost, PubMed, and Scopus databases. In the selection process, thirty full‐texts were evaluated as eligible for the review. The literature of the last decade provides a lot of information on mechanisms behind anticancer effects of arsenic on breast cancer. Similar to arsenic‐induced carcinogenesis, these mechanisms include the activation of the redox system and the increased production of free radicals. Targets of arsenic action are systems of cell membranes, mitochondria, pathways of intracellular transmission, and the genetic apparatus of the cell. Beneficial effects of arsenic use are possible due to significant metabolic differences between cancer and healthy cells. Further efforts are needed in order to establish modes and doses of treatment with arsenic that would provide anticancer activity with minimal toxicity.
Acrylic Rubber-Reinforced Halloysite Nanotubes/Carbon Black Hybrid Fillers for Oil Seal Applications: Thermal Stability and Dynamic Mechanical Properties
Authors: Senthilvel K. , Prabu B. , Moganapriya C. , Rajasekar R. , Francis Luther King M. , Uddin Md. Elias
Published: December 2022

In this study, we show that adding halloysite nanotubes (HNT) to carbon black (CB)-packed acrylic rubber (ACM) composites improves their thermal properties. The thermo-oxidative stability, thermal stability, and dynamic mechanical properties of ACM composites (filled simply with 70 phr CB) and ACM hybrid composites comprising a fixed amount of CB (60 phr) and a variable amount of halloysite nanotubes (HNT) (2, 4, 6, 8, and 10 phr) were investigated. As evidenced by the oxidation induction time analysis, hybrid structures support a higher degree of antioxidation in composites reinforced with twin fillers than composites reinforced just with CB. ACM composites with dual fillers had greater breakdown temperatures (temperatures at 10% weight loss (T10) and 50% weight loss (T50)) and char residue concentration at 600°C than ACM conventional composites, according to thermogravimetric tests. The activation energy of the thermal disintegration of ACM composites, as determined by the Kissinger and Flynn–Wall–Ozawa techniques, shows that the addition of HNT improves the thermal stability of ACM composites. The storage modulus of ACM composites was increased by 79 percent at 30°C when 10 phr of black filler was replaced with 6 phr of tubular HNT, according to additional viscoelastic experiments.
Proton Pump Inhibitor Treatment Has Little Effects on Secretion of Saliva in Patients with Proton Pump Inhibitor-Responsive Mild Reflux Esophagitis and Non-Erosive Reflux Disease
Authors: Hoshikawa Yoshimasa , Momma Eri , Hoshino Shintaro , Kawami Noriyuki , Kitasako Yuichi , Ikeda Masaomi , Iwakiri Katsuhiko
Published: December 2022

Introduction: The secretion of saliva, which is triggered by acid reflux into the esophagus via the esophagosalivary reflex, plays a crucial role in the defensive mechanisms of the esophagus. The volume of saliva secreted in patients with gastroesophageal reflux disease (GERD) is reduced. However, the effects of proton pump inhibitors (PPI) on the secretion of saliva have rarely been reported. Therefore, the present study investigated changes in the volume and pH of saliva after the cessation of PPI. Materials and Methods: We retrospectively reviewed the records of consecutive patients previously diagnosed with mild reflux esophagitis (RE) or non-erosive reflux disease (NERD) controlled with PPI (including vonoprazan) who performed the salivary secretion test before and after a 2-week cessation of PPI. The volume, pH, and pH after acid loading (buffering capacity) of saliva were compared before and after the cessation of PPI. Results: Thirty-two patients (25 NERD, 7 mild RE) were included. The second saliva test was performed a median interval of 14 months [12.0–15.3] after the first test. No significant differences were observed in the volume of saliva secreted before and after the cessation of PPI (before 4.0 mL [2.7–6.0] vs. after 4.0 mL [2.3–5.9], p = 0.894). No significant differences were noted in pH or changes in pH after acid loading before and after the cessation of PPI (pH: before 7.1 ± 0.24 vs. after 7.0 ± 0.24, p = 0.1. Delta pH after acid loading: before 1.0 [0.8–1.2] vs. after 1.0 [0.8–1.2], p = 0.844). Conclusion: The cessation of PPI did not appear to affect the volume, pH, or buffering capacity of saliva in patients with PPI-responsive mild RE and NERD.
Retinal Ganglion Cell Topography and Spatial Resolution in Three Indian Pteropodid Bats
Authors: Murugavel Baheerathan , Mitkus Mindaugas , Somanathan Hema , Kelber Almut
Published: December 2022

Pteropodidae is the only phytophagous bat family that predominantly depends on visual and olfactory cues for orientation and foraging. During daytime, pteropodids of different species roost in sites with varying light exposure. Pteropodids have larger eyes relative to body size than insectivorous bats. Retinal topography has been studied in less than 10% of the approximately 200 pteropodid species, a behavioural estimation of spatial resolution is available only for Pteropus giganteus, and little is known about the relationship between their roost site preference and visual ecology. We present retinal ganglion cell topographic maps and anatomical estimates of spatial resolution in three southern Indian pteropodid species with different roosting preferences. Ganglion cell densities are between 1,000 and 2,000 cells/mm2 in the central retina and lower in the dorsal and ventral periphery. All three species have a temporal area in the retina with peak ganglion cell densities of 4,600–6,600 cells/mm2. As a result, the foliage-roosting Cynopterus sphinx and the cave-roosting Rousettus leschenaultii have similar anatomical resolution (2.7 and 2.8 cycles/degree, respectively). The anatomical estimate for the larger tree-roosting P. giganteus (4.0 cycles/degree) is higher than the spatial resolution determined earlier in behavioural tests. Like other pteropodids and unlike other vertebrates, all three species have choroidal papillae. Based on 15 pteropodid species studied to date, we find no relationship between roost type and eye size or visual acuity. For a general understanding of the sensory ecology of pteropodids that perform key ecosystem services in the tropics, it will be essential to study additional species.