bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep metric attention learning for skin lesion classification in dermoscopy images
Authors: He Xiaoyu , Wang Yong , Zhao Shuang , Yao Chunli 
Published: January 2022

AbstractCurrently, convolutional neural networks (CNNs) have made remarkable achievements in skin lesion classification because of their end-to-end feature representation abilities. However, precise skin lesion classification is still challenging because of the following three issues: (1) insufficient training samples, (2) inter-class similarities and intra-class variations, and (3) lack of the ability to focus on discriminative skin lesion parts. To address these issues, we propose a deep metric attention learning CNN (DeMAL-CNN) for skin lesion classification. In DeMAL-CNN, a triplet-based network (TPN) is first designed based on deep metric learning, which consists of three weight-shared embedding extraction networks. TPN adopts a triplet of samples as input and uses the triplet loss to optimize the embeddings, which can not only increase the number of training samples, but also learn the embeddings robust to inter-class similarities and intra-class variations. In addition, a mixed attention mechanism considering both the spatial-wise and channel-wise attention information is designed and integrated into the construction of each embedding extraction network, which can further strengthen the skin lesion localization ability of DeMAL-CNN. After extracting the embeddings, three weight-shared classification layers are used to generate the final predictions. In the training procedure, we combine the triplet loss with the classification loss as a hybrid loss to train DeMAL-CNN. We compare DeMAL-CNN with the baseline method, attention methods, advanced challenge methods, and state-of-the-art skin lesion classification methods on the ISIC 2016 and ISIC 2017 datasets, and test its generalization ability on the PH2 dataset. The results demonstrate its effectiveness.
ETHOS: a multi-label hate speech detection dataset
Authors: Mollas Ioannis , Chrysopoulou Zoe , Karlos Stamatis , Tsoumakas Grigorios 
Published: January 2022

AbstractOnline hate speech is a recent problem in our society that is rising at a steady pace by leveraging the vulnerabilities of the corresponding regimes that characterise most social media platforms. This phenomenon is primarily fostered by offensive comments, either during user interaction or in the form of a posted multimedia context. Nowadays, giant corporations own platforms where millions of users log in every day, and protection from exposure to similar phenomena appears to be necessary to comply with the corresponding legislation and maintain a high level of service quality. A robust and reliable system for detecting and preventing the uploading of relevant content will have a significant impact on our digitally interconnected society. Several aspects of our daily lives are undeniably linked to our social profiles, making us vulnerable to abusive behaviours. As a result, the lack of accurate hate speech detection mechanisms would severely degrade the overall user experience, although its erroneous operation would pose many ethical concerns. In this paper, we present ‘ETHOS’ (multi-labEl haTe speecH detectiOn dataSet), a textual dataset with two variants: binary and multi-label, based on YouTube and Reddit comments validated using the Figure-Eight crowdsourcing platform. Furthermore, we present the annotation protocol used to create this dataset: an active sampling procedure for balancing our data in relation to the various aspects defined. Our key assumption is that, even gaining a small amount of labelled data from such a time-consuming process, we can guarantee hate speech occurrences in the examined material.
Chaos coordinated neural key synchronization for enhancing security of IoT
Authors: Alahmadi Ahmed h. 
Published: January 2022

AbstractThe key exchange mechanism in this paper is built utilizing neural network coordination and a hyperchaotic (or chaotic) nonlinear dynamic complex system. This approach is used to send and receive sensitive data between Internet-of-Things (IoT) nodes across a public network. Using phishing, Man-In-The-Middle (MITM), or spoofing attacks, an attacker can easily target sensitive information during the exchange process. Furthermore, minimal research has been made on the exchange of input seed values for creating identical input at both ends of neural networks. The proposed method uses a 5D hyperchaotic or chaotic nonlinear complex structure to ensure the sharing of input seed value across two neural networks, resulting in the identical input on both ends. This study discusses two ways for sharing seed values for neural coordination. The first is a chaotic system with all real variables, whereas the second is a hyperchaotic system with at least one complex variable. Each neural network has its own random weight vector, and the outputs are exchanged. It achieves full coordination in some stages by altering the neuronal weights according to the mutual learning law. The coordinated weights are utilized as a key after the neural coordination technique. The network’s core structure is made up of triple concealed layers. So, determining the inner configuration will be tough for the intruder. The efficiency of the suggested model is validated by simulations, and the findings reveal that the suggested strategy outperforms current equivalent techniques.
High-pressure compacted recycled polymeric composite waste materials for marine applications
Authors: Clark Edward , Bleszynski Monika , Gordon Matt 
Published: January 2022

Abstract
Abstract
Options for recycling fiber composite polymer (FCP) materials are scarce, as these materials cannot be normally recycled and are toxic when improperly disposed. Additionally, reducing water usage is an increasing concern, as the concrete industry currently uses 10% of the world’s industrial water. Therefore, building upon our previous work, this research explores the use of polymer hybrid carbon and glass composite waste products as reinforcements in high-pressure compacted cement. Our material used nearly 70% less water during manufacturing and exhibited improved durability and salt corrosion resistance. Compression strength tests were performed on high-pressure compacted materials containing 6.0 wt% recycled admixtures before and after saltwater aging, and the results showed that the material retained 90% of its original compression strength after aging, as it contained fewer pores and cavities. Our experimental work was supplemented by molecular dynamics. Simulations, which indicated that the synergetic effects of compaction and FCP admixture addition slowed the diffusion of corrosive salt ions by an average of 84%. Thus, our high-pressure compacted cement material may be suitable for extended use in marine environments, while also reducing the amount of commercial fiber composite polymer waste material that is sent to the landfill.

Article Highlights

Fiber composite waste was successfully recycled into denser, high-pressure compacted ordinary Portland cement materials.

High-pressure compacted cement samples containing 6% recycled admixtures retained 90% of their compression strength after salt aging.

The high-pressure compaction method utilized 70% less water during specimen fabrication.
Wave propagation analysis of magnetic nanotubes conveying nanoflow
Authors: Bahaadini Reza , Saidi Ali Reza 
Published: January 2022

Abstract
According to the nonlocal strain gradient theory, wave propagation in magnetic nanotubes conveying magnetic nanoflow under longitudinal magnetic field is inspected. The nonlocal strain gradient Timoshenko beam model is coupled with magnetic nanoflow considering slip boundary condition to model fluid structure interaction. By applying Hamilton’s principle, the size-dependent governing equations of motion have been obtained. Calculation of the wave frequency as well as phase velocity has been carried out based on the harmonic solution. The influences of strain gradient length scale, nonlocal parameter, Knudsen number, longitudinal magnetic field and magnetic nanoflow on nanotubes’ wave propagation behavior have been examined. According to analytical results, the magnetic intensity related to the longitudinal magnetic field contributes significantly to increasing nanotubes’ wave frequency as well as phase velocity. Besides, the magnetic nanotubes conveying magnetic nanoflow predict the highest phase velocity and wave frequency. Also, the wave frequency decrease when the nonlocal parameter increases or the strain gradient length scale decreases. Moreover, an increase in fluid velocity reduces the wave frequency and phase velocity.

Article highlights

The nonlocal strain gradient Timoshenko beam model is considered.

Wave propagation in magnetic nanotubes conveying magnetic nanoflow is studied.

Longitudinal magnetic field and magnetic nanoflow with considering slip boundary condition is inspected.

Wave frequency decrease when the nonlocal parameter increases or the strain gradient length scale decreases.

Increase in fluid velocity reduces the wave frequency and phase velocity.
Interactions of stimulus quality and semantic context on N400 in visual word recognition
Authors: Zhang Yong , Xie Min , Chen Youguo , Xiong Rongmin , Yue Change , Wu Shuqiong , Ji Feng , Wang Quanhong 
Published: January 2022

AbstractThe joint effects of stimulus quality and semantic context in visual word recognition were examined with event-related potential (ERP) recordings. In one-character Chinese word recognition, we manipulated stimulus quality at two degradation levels (highly vs. slightly degraded) and semantic context at two priming levels (semantically related vs. unrelated). In a prime–target–probe trial flow, ERPs were recorded to the target character which was presented in either high or slight degradation and which was preceded by either a semantically related or unrelated prime character. The target character was then followed by a probe character which was either identical to or different from the target character. Subjects were instructed to make target–probe matching judgments. The ERP results demonstrated a degradation by priming interaction, with larger N400 semantic priming effects for slightly degraded targets. Moreover, the degradation effects were observed on the P200, N250, and N400. These findings provided evidence for the cascaded model of visual word recognition such that the visual processing cascaded into the semantic stage and thus interacted on the N400 amplitude. The results were compared to an earlier study with a null ERP degradation by priming interaction. The ramifications of these results for models of visual word recognition are discussed.
A multivariate modeling framework to quantify immune checkpoint context-dependent stimulation on T cells
Authors: Karpf Léa , Trichot Coline , Faucheux Lilith , Legbre Iris , Grandclaudon Maximilien , Lahoute Charlotte , Mattoo Hamid , Pasquier Benoit , Soumelis Vassili 
Published: January 2022

AbstractCells receive, and adjust to, various stimuli, which function as part of complex microenvironments forming their “context”. The possibility that a given context impacts the response to a given stimulus defines “context-dependency” and it explains large parts of the functional variability of physiopathological and pharmacological stimuli. Currently, there is no framework to analyze and quantify context-dependency over multiple contexts and cellular response outputs. We established an experimental system including a stimulus of interest, applied to an immune cell type in several contexts. We studied the function of OX40 ligand (OX40L) on T helper (Th) cell differentiation, in 4 molecular (Th0, Th1, Th2, and Th17) and 11 dendritic cell (DC) contexts (monocyte-derived DC and cDC2 conditions). We measured 17 Th output cytokines in 302 observations, and developed a statistical modeling strategy to quantify OX40L context-dependency. This revealed highly variable context-dependency, depending on the output cytokine and context type itself. Among molecular contexts, Th2 was the most influential on OX40L function. Among DC contexts, the DC type rather than the activating stimuli was dominant in controlling OX40L context-dependency. This work mathematically formalizes the complex determinants of OX40L functionality, and provides a unique framework to decipher and quantify the context-dependent variability of any biomolecule or drug function.
A tool for translating polygenic scores onto the absolute scale using summary statistics
Authors: Pain Oliver , Gillett Alexandra C. , Austin Jehannine C. , Folkersen Lasse , Lewis Cathryn M. 
Published: January 2022

AbstractThere is growing interest in the clinical application of polygenic scores as their predictive utility increases for a range of health-related phenotypes. However, providing polygenic score predictions on the absolute scale is an important step for their safe interpretation. We have developed a method to convert polygenic scores to the absolute scale for binary and normally distributed phenotypes. This method uses summary statistics, requiring only the area-under-the-ROC curve (AUC) or variance explained (R2) by the polygenic score, and the prevalence of binary phenotypes, or mean and standard deviation of normally distributed phenotypes. Polygenic scores are converted using normal distribution theory. We also evaluate methods for estimating polygenic score AUC/R2from genome-wide association study (GWAS) summary statistics alone. We validate the absolute risk conversion and AUC/R2estimation using data for eight binary and three continuous phenotypes in the UK Biobank sample. When the AUC/R2of the polygenic score is known, the observed and estimated absolute values were highly concordant. Estimates of AUC/R2from the lassosum pseudovalidation method were most similar to the observed AUC/R2values, though estimated values deviated substantially from the observed for autoimmune disorders. This study enables accurate interpretation of polygenic scores using only summary statistics, providing a useful tool for educational and clinical purposes. Furthermore, we have created interactive webtools implementing the conversion to the absolute (https://opain.github.io/GenoPred/PRS_to_Abs_tool.html). Several further barriers must be addressed before clinical implementation of polygenic scores, such as ensuring target individuals are well represented by the GWAS sample.
Sterically crowded 1,4-diiodobenzene as a precursor to difunctional hypervalent iodine compounds
Authors: Li Guobi , Smith Rhett , Gembicky Milan , Rheingold Arnold L. , Protasiewicz John D. 
Published: January 2022

Oxidation of a 1,4-di-iodobenzene having four adjacent p-tBu-C6H4 group (Ar′) substituents (1) yields the hypervalent iodine compound 1,4-[I(OAc)2]2-2,3,5,6-Ar′4-C6 (2), that undergoes cyclization to produce dicyclic di-iodonium salt (3).
Investigation of changes in the activity and function of dry eye-associated brain regions using the amplitude of low-frequency fluctuations method
Authors: Sun Tie , Shu Hui-Ye , Wu Jie-Li , Su Ting , Liu Yu-Ji , Zhang Li-Juan , Li Qiu-Yu , Pan Yi-Cong , Ge Qian-Min , Shao Yi 
Published: January 2022

Abstract
Objective: The local characteristics of spontaneous brain activity in patients with dry eye (DE) and its relationship with clinical characteristics were evaluated using the amplitude of low-frequency fluctuations (ALFF) method.
Methods: A total of 27 patients with DE (10 males and 17 females) and 28 healthy controls (HCs) (10 males and 18 females) were recruited, matched according to sex, age, weight and height, classified into the DE and HC groups, and examined using functional magnetic resonance imaging (fMRI) scans. Spontaneous brain activity changes were recorded using ALFF technology. Data were recorded and plotted on the receiver operating characteristic (ROC) curve, reflecting changes in activity in different brain areas. Finally, Pearson correlation analysis was used to calculate the potential relationship between spontaneous brain activity abnormalities in multiple brain regions and clinical features in patients with DE. GraphPad Prism 8 (GraphPad Software, Inc.) was used to analyze the linear correlation between the Hospital Anxiety and Depression Scale and ALFF value.
Results: Compared with HCs, the ALFF values of patients with DE were decreased in the right middle frontal gyrus (MFG)/right inferior orbitofrontal cortex (OFC), left triangle inferior frontal gyrus, left MFG, and right superior frontal gyrus. In contrast, the ALFF value of patients with DE was increased in the left calcarine.
Conclusion: There are significant fluctuations in the ALFF value of specific brain regions in patients with DE versus HCs. This corroborates previous evidence showing that the symptoms of ocular surface damage in patients with DE are related to dysfunction in specific brain areas.
Star formation in outer rings of S0 galaxies
Authors: Katkov Ivan Yu. , Kniazev Alexei Yu. , Sil’chenko Olga K. , Gasymov Damir 
Published: January 2022

Aims. Although S0 galaxies are usually considered “red and dead”, they often demonstrate star formation organized into ring structures. We aim to clarify the nature of this phenomenon and how it differs from star formation in spiral galaxies.
Methods. We investigated the nearby, moderate-luminosity S0 galaxy NGC 254 using long-slit spectroscopy taken with the South African Large Telescope and publicly available imaging data. Applying a full spectral fitting, we analyzed gaseous and stellar kinematics as well as ionized gas excitation and metallicity and stellar population properties resolved by radius. An advanced approach of simultaneously fitting spectra and photometric data allowed us to quantify the fraction of hidden counter-rotating stars in this galaxy.
Results. We find that the ionized gas is counter-rotating with respect to the stars throughout NGC 254 disk, indicating an external origin of the gas. We argue the gas-rich galaxy merger from retrograde orbit as a main source of counter-rotating material. The star formation fed by this counter-rotating gas occurs within two rings: an outer ring at R = 55″ − 70″ and an inner ring at R = 18″. The star formation rate is weak, 0.02 solar mass per year in total, and the gas metallicity is slightly subsolar. We estimated that the accretion of the gas occurred about 1 Gyr ago, and about 1% of all stars have formed in situ from counter-rotating gas.
MUSE crowded field 3D spectroscopy in NGC 300
Authors: González-Torà G. , Urbaneja M. A. , Przybilla N. , Dreizler S. , Roth M. M. , Kamann S. , Castro N. 
Published: January 2022

Aims.A quantitative spectral analysis of BA-type supergiants and bright giants in an inner spiral arm region of the nearby spiral galaxy NGC 300 is presented, based on observations with the Multi Unit Spectroscopic Explorer (MUSE) on the European Southern Obsevatory, Very Large Telescope. The flux-weighted gravity–luminosity relationship (FGLR), a stellar spectroscopic distance determination method for galaxies, is extended towards stars at lower luminosities.Methods.Point spread function fitting 3D spectroscopy was performed with PampelMUSE on the datacube. The 16 stars with the highest signal-to-noise ratios are classified with regard to their spectral type and luminosity class using Galactic templates. They were analysed using hybrid non-local thermodynamic equilibrium model spectra to fit the strongest observed hydrogen, helium, and metal lines in the intermediate-resolution spectra. Supplemented by photometric data, this facilitates fundamental stellar parameters and interstellar reddening which have yet to be determined.Results.Effective temperatures, surface gravities, reddeningE(B−V), bolometric magnitudes and luminosities, as well as radii and masses are presented for the sample stars. The majority of the objects follow the FGLR as established from more luminous BA-type supergiants in NGC 300. An increase in the scatter in the flux-weighted gravity–luminosity plane is observed at these lower luminosities, which is in line with predictions from population synthesis models.
Phytoconstituents in the Management of Covid-19: Demystifying the
Fact
Authors: Barkat Md. Abul , Kaushik Pawan , Barkat Harshita Abul , Khan Mohammad Idreesh , Hadi Hazrina Ab 
Published: January 2022

AbstractThe 2019-nCoV (COVID-19; novel coronavirus disease-2019) outbreak is caused by
the coronavirus, and its continued spread is responsible for increasing deaths,
social and economic burden. COVID-19 created a chaotic situation worldwide and
claimed the lives of over 5,027,183 and 248,467,363 confirmed cases have been
reported so far as per the data published by WHO (World Health Organization)
till 5th November 2021. Scientific communities all over the world are
toiling to find a suitable therapeutic drug for this deadly disease. Although
till date no promising drug has been discovered for this COVID-19. However, as
per the WHO, over 102 COVID-19 vaccines are in clinical development and 185 in
pre-clinical development. Naturally occurring phytoconstituents possess
considerable chemical richness in the form of anti-viral and anti-parasitic
potential and have been extensively exploited for the same globally. Still,
phytomedicine-based therapies are considered as the best available treatment
option to minimize and treat the symptoms of COVID-19 because of the least
possible side effects compared to synthetic drugs recommended by the
physicians/clinicians. In this review, the use of plant chemicals as a
possible therapeutic agent for severe acute respiratory syndrome coronavirus 2
(SARS CoV2) is highlighted with their proposed mechanism of action, which will
prove fruitful and effective in finding a cure for this deadly disease.
Trifluoroacetic Acid Promoted Ring Contraction in 2,3-Di-O-silylated O-Galactopyranosides and Hemiacetals
Authors: Abronina Polina I. , Kononov Leonid O. , Malysheva Nelly N. , Zinin Alexander I. , Karpenko Maxim Y. , Kolotyrkina Natalya G. 
Published: January 2022

AbstractA pyranose ring contraction of 2,3-di-O-silylated O-galactopyranosides with retention of aglycone promoted by anhydrous trifluoroacetic acid (TFA) in CH2Cl2 was demonstrated for the first time. In addition, TFA-promoted pyranose ring contraction of 2,3-bis-O-(triisopropylsilyl)-d-galactopyranose with formation of the corresponding anomeric triols in furanose form was successfully performed. A representative series of β-d-galactopyranosides with Me, Bn, allyl, or 3-(trifluoroacetamido)propyl aglycones has been investigated. TBDPS protective groups were found to be more stable than TIPS groups under conditions of TFA-promoted pyranose ring contraction. An easy access to 2,3-di-O-TBDPS-substituted allyl and benzyl galactofuranosides and 2,3-bis-O-(triisopropylsilyl)-β-d-galactofuranose may present an advantage in synthesis of selectively protected monosacharide building blocks, useful for the synthesis of biologically important oligosaccharides.
N-Iodosuccinimide-Promoted Selective Construction of Cyclopropyl and Dihydrofuranyl Spirooxindoles from Alkylidene Oxindoles and Annular β-Dicarbonyl Compounds
Authors: Xu Hui , Jin Ying , Zhang Ze , Chen Hong , He Zeng-Yang , Zou Peng , Huang Fei-Hong 
Published: January 2022

AbstractAn efficient N-iodosuccinimide-promoted cyclization of readily available alkylidene oxindoles with annular β-dicarbonyl compounds has been demonstrated. With five-membered cyclic β-dicarbonyl compounds as the starting materials, a series of cyclopropyl oxindoles can be obtained in good to excellent yields, whereas the method affords dihydrofuranyl spirooxindoles almost quantitatively when six- or seven-membered cyclic β-dicarbonyl compounds are employed. This protocol provides a new alternative to the practical synthesis of structurally diverse spirooxindoles.