bluuebunny/crossref_metadata_2025 huggingface dataset:
Personalized Re-ranking for Recommendation with Mask Pretraining
Authors: Han Peng , Zhou Silin , Yu Jie , Xu Zichen , Chen Lisi , Shang Shuo
Published: September 2023

Re-ranking is to refine the candidate ranking list of recommended items, such that the re-ranked list attracts users to purchase or click more items than the candidate one without re-ranking. Items in the candidate list are often ranked by their relevance to users’ interests. It is thus important to exploit the mutual influence between items in the re-ranking process. Existing re-ranking models focus on only the pairwise influence between two items, and have limited capability to exploit the local mutual influence in a group of items. Users often show successive interests on a group of relevant items, e.g., mobile phone, phone covers, wireless headset, namely scene. We propose a novel re-ranking model that jointly exploits the local mutual influence in scenes and the global mutual influence between different scenes. Scene representations are learned by GNN and multi-head attention, where GNN aims to learn local mutual influence while multi-head attention is to learn global mutual influence. To study the interaction between users and scenes, matrix factorization on users is utilized to obtain the user preference, which can be further applied to scenes to compute the scene scores. The final re-ranking list is generated by sorting the predicted scores of all scenes. To further mine user history information and item related user information, we also develop the extension pretraining module which relies on mask mechanism to support users and items high-quality embedding generation. We conduct a comprehensive evaluation on several real-world datasets. The experimental results demonstrate that our model substantially outperforms existing approaches.
Learning with Small Data: Subgraph Counting Queries
Authors: Zhao Kangfei , He Zongyan , Yu Jeffrey Xu , Rong Yu
Published: September 2023

Deep Learning (DL) has been widely used in many applications, and its success is achieved with large training data. A key issue is how to provide a DL solution when there is no large training data to learn initially. In this paper, we explore a meta-learning approach for a specific problem, subgraph isomorphism counting, which is a fundamental problem in graph analysis to count the number of a given pattern graph, p, in a data graph, g, that matches p. There are various data graphs and pattern graphs. A subgraph isomorphism counting query is specified by a pair, (g, p). This problem is NP-hard and needs large training data to learn by DL in nature. We design a Gaussian Process (GP) model which combines Graph Neural Network with Bayesian nonparametric, and we train the GP by a meta-learning algorithm on a small set of training data. By meta-learning, we can obtain a generalized meta-model to better encode the information of data and pattern graphs and capture the prior of small tasks. With the meta-model learned, we handle a collection of pairs (g, p), as a task, where some pairs may be associated with the ground-truth, and some pairs are the queries to answer. There are two cases. One is there are some with ground-truth (few-shot), and one is there is none with ground-truth (zero-shot). We provide our solutions for both. In particular, for zero-shot, we propose a new data-driven approach to predict the count values. Note that zero-shot learning for our regression tasks is difficult, and there is no hands-on solution in the literature. We conducted extensive experimental studies to confirm that our approach is robust to model degeneration on small training data, and our meta-model can fast adapt to new queries by few-shot and zero-shot learning.
Deep reinforcement learning for autonomous vehicles: lane keep and overtaking scenarios with collision avoidance
Authors: Ashwin S. H. , Naveen Raj Rashmi
Published: September 2023

Numerous accidents and fatalities occur every year across the world as a result of the reckless driving of drivers and the ever-increasing number of vehicles on the road. Due to these factors, autonomous cars have attracted enormous attention as a potentially game-changing technology to address a number of persistent problems in the transportation industry. Autonomous vehicles need to be modeled as intelligent agents with the capacity to observe, and perceive the complex and dynamic environment on the road, and decide an action with the highest priority to the lives of people in every scenarios. The proposed deep deterministic policy gradient-based sequential decision algorithm models the autonomous vehicle as a learning agent and trains it to drive on a lane, overtake a static and a moving vehicle, and avoid collisions with obstacles on the front and right side. The proposed work is simulated using a TORC simulator and has shown the expected performance under the above-said scenarios.
The long-term effects of multidrug immunosuppressive protocols based on calcineurin inhibitors and conversion to rapamycin on the morphology, apoptosis, and proliferation of rat salivary glands
Authors: Grabowska Marta , Kędzierska-Kapuza Karolina , Kram Andrzej , Gill Kamil , Teresiński Leszek , Sipak Olimpia , Piasecka Małgorzata
Published: September 2023

Background

The effect of multidrug immunosuppressive protocols on the salivary glands is still unknown. This study aimed to determine the influence of immunosuppressive regimens based on calcineurin inhibitors (CNIs) and conversion to rapamycin on the morphology, apoptosis, and proliferation of rat salivary glands.

Methods

Male rats received cyclosporin A (CsA), tacrolimus (FK-506), mycophenolate mofetil (MMF), rapamycin (Rapa), and prednisone (Pre) according to three-drug protocols: CMP (CsA, MMF, and Pre), CMP/R (CsA, MMF, and Pre with conversion to Rapa), TMP (FK-506, MMF, and Pre), and TMP/R (FK-506, MMF, and Pre with conversion to Rapa). Morphological and immunohistochemical and quantitative analyses of the salivary glands were performed.

Results

Structural changes in salivary glands were observed in all experimental groups, especially in the submandibular gland. In the salivary glands, the percentages of collagen fibers and TUNEL-, Ki67- and PCNA-positive cells were higher in the experimental groups vs. the control but were lower in the CMP/R and TMP/R groups vs. the CMP and TMP groups, with the exception of collagen fibers in the parotid gland in the TMP/R group vs. the TMP group.

Conclusions

Long-term administration of CNIs in triple regimens and after conversion to rapamycin monotherapy, causes morphological changes in the salivary glands of rats. Immunosuppressive treatment based on CNIs is associated with an increase in collagen accumulation. The effects of the conversion of treatment with CNIs to rapamycin in immunosuppressive protocols in rat salivary glands lead to decreased fibrosis, apoptosis, and proliferation. These changes may possibly prevent abnormalities resulting from the application of CNIs.
Antipathogenic copper coatings: electrodeposition process and microstructure analysis
Authors: Bigos Agnieszka , Bugajska Monika , Kwiecien Izabella , Janusz-Skuza Marta , Szczerba Maciej , Ozga Piotr , Wierzbicka-Miernik Anna , Dyner Marcin , Misztela Andrzej , Dyner Aneta , Wojewoda-Budka Joanna
Published: September 2023

Copper coatings are an important group of decorative-protective materials characterised by high corrosion resistance, excellent thermal and electrical conductivity, which lately gained more significance due to their antimicrobial activity. The main aim of the presented research was to electrodeposit homogenous copper coatings from the non-cyanide electrolyte solution in galvanostatic conditions on steel (1.4024) and nickel (Ni201) substrates, commercially used for surgical instruments. The effect of substrate finishes used in the production line, by shot peening with glass balls, corundum treatment and brushing on the coatings surface formation, was investigated. The substrates’ and coatings’ microstructural properties were analyzed by scanning and transmission electron microscopy, atomic force microscopy, and X-ray diffraction analysis. The current efficiency of the copper reduction on nickel and steel substrates was found to be above 95%. The copper layers adhere to both substrates, except those deposited on a brushed surface. Regardless of the substrate used, they have a nanocrystalline structure with an average crystallite size of 30 nm. Moreover, the coating surface morphology, which affects the nature of interaction with microorganisms, was effectively modified by the appropriate substrate finishing without changing the electrodeposition conditions.
Sampling locally, hypothesis globally: accurate 3D point cloud registration with a RANSAC variant
Authors: Cheng Yuxin , Huang Zhiqiang , Quan Siwen , Cao Xinyue , Zhang Shikun , Yang Jiaqi
Published: September 2023

Correspondence-based six-degree-of-freedom (6-DoF) pose estimation remains a mainstream solution for 3D point cloud registration. However, the heavy outliers pose great challenges to this problem. In this paper, we propose a random sample consensus (RANSAC) variant based on sampling locally and hypothesis globally (SLHG) for 6-DoF pose estimation and 3D point cloud registration. The key novelties are efficient sampling by guiding the sampling process locally and accurate pose estimation by generating hypotheses with global information. SLHG first generates a correspondence subset via compatibility clustering on the initial set. Second, locally guided graph sampling is performed. Third, 6-DoF hypotheses are generated by incorporating global information with a voting scheme. The best hypothesis serves as the estimation result by repeating the second and third steps. Extensive experiments on four popular datasets and comparisons with state-of-the-art methods confirm that: SLHG manages to 1) achieve accurate registrations with a few iterations, and 2) yield better accuracy performance than most competitors.
Enhancements in Cloud Condensation Nuclei Activity From Turbulent Fluctuations in Supersaturation
Authors: Anderson Jesse C. , Beeler Payton , Ovchinnikov Mikhail , Cantrell Will , Krueger Steven , Shaw Raymond A. , Yang Fan , Fierce Laura
Published: September 2023

The effect of aerosols on the properties of clouds is a large source of uncertainty in predictions of weather and climate. These aerosol‐cloud interactions depend critically on the ability of aerosol particles to form cloud droplets. A challenge in modeling aerosol‐cloud interactions is the representation of interactions between turbulence and cloud microphysics. Turbulent mixing leads to small‐scale fluctuations in water vapor and temperature that are unresolved in large‐scale atmospheric models. To quantify the impact of turbulent fluctuations on cloud condensation nuclei (CCN) activation, we used a high‐resolution Large Eddy Simulation of a convective cloud chamber to drive particle‐based cloud microphysics simulations. We show small‐scale fluctuations strongly impact CCN activity. Once activated, the relatively long timescales of evaporation compared to fluctuations causes droplets to persist in subsaturated regions, which further increases droplet concentrations.
Characterizing the Importance of Porosity of Large Woody Debris Accumulations at Single Bridge Piers on Localized Scour
Authors: Panici D. , Kripakaran P.
Published: September 2023

The accumulation of large woody debris (LWD) at bridge piers is a serious hazard to the structural integrity of bridges across watercourses worldwide. The exacerbated scour that can directly result from LWD accumulations can lead to major structural damage or even catastrophic collapse. Recent research has led to empirical equations to estimate the scour depth for given LWD accumulation size; however these are mostly based on experimental tests with prismatic and impervious solid LWD accumulations, ignoring field observations that have shown that accumulations are neither impervious nor prismatic but are porous with inverted conical shapes. In this study, we therefore investigate the effects of porous LWD accumulations having shapes commonly observed in the field on scour holes. Results reveal that LWD size and shape, and flow characteristics are the primary factors influencing the erosion of sediments at the base of bridge piers. However, the porosity of accumulations is also observed to have a considerable effect on the size and maximum depth of scour holes. In particular, porous LWD reduce the maximum scour depth by up to 50% (and on average in the range of 5%–25%) relative to the respective solid impervious accumulation. The results shown in this study also provide a practical tool for arriving at more realistic and less conservative estimates of scour depths at bridge piers when affected by LWD accumulations.
Underground Heat Could Be a Problem, or a Perk, for Chicago Buildings
Authors: Cartier Kimberly
Published: September 2023

Heat released by old and inefficient Chicago buildings could, if harnessed, be an energy solution.
Quantifying the Rightward Bias Extent of Tropical Cyclones' Cold Wakes
Authors: Ma Zhanhong , Yan Xinyue , Fei Jianfang
Published: September 2023

Although the cold wake of tropical cyclones (TCs) is recognized to be typically rightward biased relative to TC track (in the North Hemisphere), it remains unclear to what extent the rightward bias should be for specified TCs. Based on numerical simulations and observational statistics, this study shows that the distance of cold wake rightward bias is closely related to latitude, translation speed and radius of maximum wind (RMW) of a TC, but is independent from maximum surface wind and radial wind profile outside the RMW, namely TC intensity and size. A semi‐empirical equation is derived to represent the rightward bias extent of cold wakes. For TCs with slower translation speed, smaller RMW, or at higher latitudes, the cold wakes are less asymmetric relative to the TC track. Atmospheric simulations also show that the TC tends to be weaker and more asymmetric as the cold wake is closer to TC center.
Impact of Domain Size on Tropical Precipitation Within Explicit Convection Simulations
Authors: Jones Richard W. , Sanchez Claudio , Lewis Huw , Warner James , Webster Stuart , Macholl Joshua
Published: September 2023

We investigate the sensitivity of modeled tropical precipitation accumulation, intensity and structures to the extent of convection‐permitting limited area model (LAM) domain size. Our comparison focusses on two LAM domains, with identical physical parameterization schemes and using 2.2 km grid spacing. One LAM domain spans almost the full tropical belt while the other focusses on southeast Asia. We show that the LAMs both capture the complex diurnal cycle of precipitation and that the timing and intensity of precipitation are comparable with satellite observations. Systematic differences between the LAMs are largest within ∼1,000 km of the western and eastern boundaries of the southeast Asia LAM. This is due to convective spin‐up at the western boundary of the southeast Asia LAM and a lack of propagating deep convection. We highlight that showing the added value of global storm‐resolving models by comparing with LAMs will help to accelerate their operational implementation.
Typical Synoptic Patterns Responsible for Summer Regional Hourly Extreme Precipitation Events Over the Middle and Lower Yangtze River Basin, China
Authors: Zeng Jingwen , Huang Anning , Wu Peili , Huang Danqing , Zhang Yan , Tang Jian , Zhao Dajun , Yang Ben , Chen Shuang
Published: September 2023

Based on the hourly rainfall gauge data and ERA5 reanalysis for the period 1980–2020, typical synoptic patterns responsible for summer regional hourly extreme precipitation events (RHEPE) over the middle and lower Yangtze River basin have been objectively identified using a circulation clustering method. It is found that the Meiyu front with different locations and intensities imbedded in the East Asian summer monsoon, and landfalling typhoons are the leading contributors. As the dominant synoptic pattern, the Meiyu front pattern is associated with ∼92% of the total RHEPE occurrence and can be categorized into a southerly strong‐Meiyu type and a northerly weak‐Meiyu type. The RHEPE occurrence shows a predominant morning peak associated with the southerly strong‐Meiyu type and a secondary late afternoon peak related to the northerly weak‐Meiyu type, in which the Meiyu front is pushed northward by the strengthened western North Pacific subtropical high accompanied by accelerated low‐level southwesterly flow.
Parametric Dependence of Topside Ionospheric Empirical Scale Height and Electron Density Profiles in NeQuick2 Model Over the Equatorial and Low Latitudes and Its Consequences on the Estimation of TEC
Authors: Venkatesh K. , Pallamraju D. , Pant T. K. , Suryawanshi P.
Published: September 2023

Constructing realistic vertical electron density profiles is a crucial step in accurately estimating the ionospheric total electron content (TEC) in empirical models. Inadequate representation of electron density profiles leads to under‐ or over‐estimation of TEC in model outputs. One of the widely used ionospheric empirical model, the NeQuick2 exhibits large uncertainties over equatorial and low latitudes, particularly in the topside ionosphere. The NeQuick2 model employs semi Epstein type of polynomials to characterize the topside ionospheric structure, wherein, the scale height (H) is the key parameter. NeQuick2 model estimates H value using empirical formulations, which contain three major parameters namely, Ho—the scale height at the F‐layer peak, g—height gradient in H, and r—which controls the increase in H at higher altitudes. In this study, a systematic analysis has been carried out with particular focus on the equatorial and low latitudes to explore the variability of topside scale height and electron density profiles on the above three empirical parameters using COSMIC observations over Trivandrum and Ahmedabad, in India. Model uncertainties in estimating Ho and their impacts on the estimation of TEC are investigated. Data assimilation analysis has been carried out to obtain a quantitative understanding on the effect of deviations in topside scale height on the uncertainties in accurate estimation of TEC over equatorial and low latitudes. This study reveals the impact of scale height uncertainties on errors in modeled TEC and demonstrates the need for improvement in empirical formulations for improving accuracies in ionospheric modeling over equatorial and low latitude sectors.
Interhemispheric Observations of ULF Waves Caused by Foreshock Transients Under Quiet Solar Wind Conditions
Authors: Noh Sung Jun , Kim Hyomin , Ozturk Dogacan , Kuzichev Ilya , Xu Zhonghua , Zhang Hui , Vu Andrew , Liu Terry , Weygand James M. , Hartinger Michael D. , Shi Xueling , Engebretson Mark , Gerrard Andrew , Kim Eun‐Hwa , Lessard Marc , Russell Christopher T.
Published: September 2023

Foreshock transient (FT) events are frequently observed phenomena that are generated by discontinuities in the solar wind. These transient events are known to trigger global‐scale magnetic field perturbations (e.g., ULF waves). We report a series of FT events observed by the Magnetospheric Multiscale mission in the upstream bow shock region under quiet solar wind conditions. During the event, ground magnetometers observed significant Pc1 wave activity as well as magnetic impulse events in both hemispheres. Ground Pc1 wave observations show ∼8 min time delay (with some time differences) from each FT event which is observed at the bow shock. We also find that the ground Pc1 waves are observed earlier in the northern hemisphere compared to the southern hemisphere. The observation time difference between the hemispheres implies that the source region of the wave is the off‐equatorial region.
Sudden Stratospheric Warmings in the Northern Hemisphere Observed With IASI
Authors: Bouillon Marie , Safieddine Sarah , Clerbaux Cathy
Published: September 2023

Sudden Stratospheric Warming events (SSW) are extreme phenomena during which stratospheric temperature can increase by tens of degrees in a few days. They are due to the propagation and breaking of the planetary waves, leading to a perturbation of the polar vortex. SSWs also influence polar ozone concentrations and midlatitude weather. The Infrared Atmospheric Sounding Interferometers (IASI) monitor atmospheric composition and temperature globally since 2007, and they are ideal to observe the changes of temperature and ozone during SSWs. Since the launch of the first IASI, there have been several SSWs in the Northern Hemisphere, including eight major events that are investigated in this study. We find that during major SSWs, the temperature anomaly propagates from 10 hPa to the lower stratosphere and the maximum anomaly at 200 hPa is correlated to the maximum anomaly at 10 hPa. During these events, negative anomalies of temperature in Europe and Russia and positive anomalies in Canada and Greenland are often observed at 750 hPa. The cold air outbreaks that usually follow major SSWs are responsible for anomalies of −15 K. Finally, we look at the evolution of the total ozone column following major events. Major SSWs lead to higher springtime ozone concentrations and the ozone anomaly in March is correlated to the duration of the positive temperature anomaly at 10 hPa. These results show the potential of the IASI mission and its successors, IASI‐New Generation, for the study of SSWs and their effects on weather and atmospheric composition.
Teardrop and Parabolic Lens Yield Curves for Viscous‐Plastic Sea Ice Models: New Constitutive Equations and Failure Angles
Authors: Ringeisen Damien , Losch Martin , Tremblay L. Bruno
Published: September 2023

Most viscous‐plastic sea ice models use the elliptical yield curve. This yield curve has a fundamental flaw: it excludes acute angles between deformation features at high resolution. Conceptually, the teardrop (TD) and parabolic lens (PL) yield curves offer an attractive alternative. These yield curves feature a non‐symmetrical shape, a Coulombic behavior for the low‐medium compressive stress, and a continuous transition to the ridging‐dominant mode, but their published formulation leads to negative or zero bulk and shear viscosities and, consequently, poor numerical convergence with stress states at times outside the yield curve. These issues are a consequence of the original assumption that the constitutive equations of the commonly used elliptical yield curve are also applicable to non‐symmetrical yield curves and yield curves with tensile strength. We derive a corrected formulation for the constitutive relations of the TD and PL yield curves. Results from simple uni‐axial loading experiments show that with the new formulation the numerical convergence of the solver improves and much smaller nonlinear residuals after a smaller number of total solver iterations can be reached, resulting in significant improvements in numerical efficiency and representation of the stress and deformation fields. The TD and PL yield curves lead to smaller angles of failure that better agree with observations. They are promising candidates to replace the elliptical yield curve in high‐resolution pan‐Arctic sea ice simulations.
Soil Moisture Estimation by Assimilating In‐Situ and SMAP Surface Soil Moisture Using Unscented Weighted Ensemble Kalman Filter
Authors: Fu Xiaolei , Zhang Yuchen , Zhong Qi , Lü Haishen , Ding Yongjian , Li Zhaoguo , Yu Zhongbo , Jiang Xiaolei
Published: September 2023

Highly accurate soil moisture information is necessary to understand land surface processes. However, observational techniques do not produce adequately accurate spatial‐temporal continuous regional soil moisture data. The data assimilation method can be used to improve the soil moisture estimations by merging multi‐source observed data, but its performance is affected by error covariance and the quality of assimilated data. We designed eight numerical experiments to analyze how to improve the filter performance through soil moisture assimilation using the unscented weighted ensemble Kalman filter (UWEnKF) and 1‐D Richards equation at Maqu and Erlinghu (ELH) observational sites in the source region of Yellow River (SRYR), China. The experimental results show that the filter performance improves as the quality of assimilated data increases in the soil moisture assimilation experiment when assimilating in‐situ surface soil moisture (SSM) observations, SMAP SSM data and downscaled SMAP SSM data. In other aspects, filter performance is readily affected by model and observation error covariances in soil moisture assimilation. If the SMAP SSM data are taken to be perfect (i.e., small bias), UWEnKF performs differently between different sites because of the underestimation or overestimation of SMAP SSM and model simulations compared to the in‐situ observations. Additionally, different soil moisture assimilation results can be obtained with different initial values at the beginning of the assimilation period. Overall, filter performance can be improved primarily by improving the quality of assimilated data (e.g., downscaling the remote sensing data), and by creating a reasonable and effective method for determining error covariance.
RBM47 restrains renal cell carcinoma progression and chemoresistance through interacting with lncRNA HOXB-AS1
Authors: Su Qingfu , Pan Zhenliang , Chen Heyi , Chen Jiabi , Zhang Yanmei , Zhuang Wei
Published: September 2023

RNA binding proteins have the critical role in renal cell carcinoma (RCC) progression. However, the role of RBM47 in RCC has not been elucidated. In this study, we found that RBM47 was downregulated in RCC tissues and its expression was negatively correlated with the prognosis of RCC patients. Also, we found that the expression of RBM47 was regulated by CBP/P300-mediated H3K27ac in RCC. Functionally, RBM47 restrained RCC cells proliferation and metastasis. Mechanistically, RBM47 interfered with the interaction between HOXB-AS1 and p53 proteins via directly binding with HOXB-AS1, finally promoted the entry of p53 into the nucleus and therefore activated the p53 signaling. Moreover, RBM47 had a synergistic anticancer effect with sunitinib both in vivo and in vitro.
Organophotocatalysed synthesis of 2-piperidinones in one step via [1 + 2 + 3] strategy
Authors: Du Yi-Dan , Wang Shan , Du Hai-Wu , Chang Xiao-Yong , Chen Xiao-Yi , Li Yu-Long , Shu Wei
Published: September 2023

Six-membered N-containing heterocycles, such as 2-piperidinone derivatives, with diverse substitution patterns are widespread in natural products, drug molecules and serve as key precursors for piperidines. Thus, the development of stereoselective synthesis of multi-substituted 2-piperidinones are attractive. However, existing methods heavily rely on modification of pre-synthesized backbones which require tedious multi-step procedure and suffer from limited substitution patterns. Herein, an organophotocatalysed [1 + 2 + 3] strategy was developed to enable the one-step access to diverse substituted 2-piperidinones from easily available inorganic ammonium salts, alkenes, and unsaturated carbonyl compounds. This mild protocol exhibits exclusive chemoselectivity over two alkenes, tolerating both terminal and internal alkenes with a wide range of functional groups.
Ascl1 and Ngn2 convert mouse embryonic stem cells to neurons via functionally distinct paths
Authors: Vainorius Gintautas , Novatchkova Maria , Michlits Georg , Baar Juliane Christina , Raupach Cecilia , Lee Joonsun , Yelagandula Ramesh , Wernig Marius , Elling Ulrich
Published: September 2023

Ascl1 and Ngn2, closely related proneural transcription factors, are able to convert mouse embryonic stem cells into induced neurons. Despite their similarities, these factors elicit only partially overlapping transcriptional programs, and it remains unknown whether cells are converted via distinct mechanisms. Here we show that Ascl1 and Ngn2 induce mutually exclusive side populations by binding and activating distinct lineage drivers. Furthermore, Ascl1 rapidly dismantles the pluripotency network and installs neuronal and trophoblast cell fates, while Ngn2 generates a neural stem cell-like intermediate supported by incomplete shutdown of the pluripotency network. Using CRISPR-Cas9 knockout screening, we find that Ascl1 relies more on factors regulating pluripotency and the cell cycle, such as Tcf7l1. In the absence of Tcf7l1, Ascl1 still represses core pluripotency genes but fails to exit the cell cycle. However, overexpression of Cdkn1c induces cell cycle exit and restores the generation of neurons. These findings highlight that cell type conversion can occur through two distinct mechanistic paths, even when induced by closely related transcription factors.
Comparative mucomic analysis of three functionally distinct Cornu aspersum Secretions
Authors: Cerullo Antonio R. , McDermott Maxwell B. , Pepi Lauren E. , Liu Zhi-Lun , Barry Diariou , Zhang Sheng , Yang Xu , Chen Xi , Azadi Parastoo , Holford Mande , Braunschweig Adam B.
Published: September 2023

Every animal secretes mucus, placing them among the most diverse biological materials. Mucus hydrogels are complex mixtures of water, ions, carbohydrates, and proteins. Uncertainty surrounding their composition and how interactions between components contribute to mucus function complicates efforts to exploit their properties. There is substantial interest in commercializing mucus from the garden snail, Cornu aspersum, for skincare, drug delivery, tissue engineering, and composite materials. C. aspersum secretes three mucus—one shielding the animal from environmental threats, one adhesive mucus from the pedal surface of the foot, and another pedal mucus that is lubricating. It remains a mystery how compositional differences account for their substantially different properties. Here, we characterize mucus proteins, glycosylation, ion content, and mechanical properties that could be used to provide insight into structure-function relationships through an integrative “mucomics” approach. We identify macromolecular components of these hydrogels, including a previously unreported protein class termed Conserved Anterior Mollusk Proteins (CAMPs). Revealing differences between C. aspersum mucus shows how considering structure at all levels can inform the design of mucus-inspired materials.
A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image Classification
Authors: Wang Dequan , Wang Xiaosong , Wang Lilong , Li Mengzhang , Da Qian , Liu Xiaoqiang , Gao Xiangyu , Shen Jun , He Junjun , Shen Tian , Duan Qi , Zhao Jie , Li Kang , Qiao Yu , Zhang Shaoting
Published: September 2023

Foundation models, often pre-trained with large-scale data, have achieved paramount success in jump-starting various vision and language applications. Recent advances further enable adapting foundation models in downstream tasks efficiently using only a few training samples, e.g., in-context learning. Yet, the application of such learning paradigms in medical image analysis remains scarce due to the shortage of publicly accessible data and benchmarks. In this paper, we aim at approaches adapting the foundation models for medical image classification and present a novel dataset and benchmark for the evaluation, i.e., examining the overall performance of accommodating the large-scale foundation models downstream on a set of diverse real-world clinical tasks. We collect five sets of medical imaging data from multiple institutes targeting a variety of real-world clinical tasks (22,349 images in total), i.e., thoracic diseases screening in X-rays, pathological lesion tissue screening, lesion detection in endoscopy images, neonatal jaundice evaluation, and diabetic retinopathy grading. Results of multiple baseline methods are demonstrated using the proposed dataset from both accuracy and cost-effective perspectives.
Standardised images of novel objects created with generative adversarial networks
Authors: Cooper Patrick S. , Colton Emily , Bode Stefan , Chong Trevor T.-J.
Published: September 2023

An enduring question in cognitive science is how perceptually novel objects are processed. Addressing this issue has been limited by the absence of a standardised set of object-like stimuli that appear realistic, but cannot possibly have been previously encountered. To this end, we created a dataset, at the core of which are images of 400 perceptually novel objects. These stimuli were created using Generative Adversarial Networks that integrated features of everyday stimuli to produce a set of synthetic objects that appear entirely plausible, yet do not in fact exist. We curated an accompanying dataset of 400 familiar stimuli, which were matched in terms of size, contrast, luminance, and colourfulness. For each object, we quantified their key visual properties (edge density, entropy, symmetry, complexity, and spectral signatures). We also confirmed that adult observers (N = 390) perceive the novel objects to be less familiar, yet similarly engaging, relative to the familiar objects. This dataset serves as an open resource to facilitate future studies on visual perception.
Differing responses of osteogenic cell lines to β-glycerophosphate
Authors: Yevlashevskaya Olga S. , Scheven Ben A. , Walmsley A. Damien , Shelton Richard M.
Published: September 2023

Ascorbic acid (Asc), dexamethasone (Dex) and β-glycerophosphate (β-Gly) are commonly used to promote osteogenic behaviour by osteoblasts in vitro. According to the literature, several osteosarcoma cells lines appear to respond differently to the latter with regards to proliferation kinetics and osteogenic gene transcription. Unsurprisingly, these differences lead to contrasting data between publications that necessitate preliminary studies to confirm the phenotype of the chosen osteosarcoma cell line in the presence of Asc, Dex and β-Gly. The present study exposed Saos-2 cells to different combinations of Asc, Dex and β-Gly for 14 days and compared the response with immortalised human mesenchymal stromal/stem cells (MSCs). Cell numbers, cytotoxicity, mineralised matrix deposition and cell proliferation were analysed to assess osteoblast-like behaviour in the presence of Asc, Dex and β-Gly. Additionally, gene expression of runt-related transcription factor 2 (RUNX2); osteocalcin (OCN); alkaline phosphatase (ALP); phosphate regulating endopeptidase homolog X-linked (PHEX); marker of proliferation MKI67 and proliferating cell nuclear antigen (PCNA) was performed every two days during the 14-day cultures. It was found that proliferation of Saos-2 cells was significantly decreased by the presence of β-Gly which contrasted with hMSCs where no change was observed. Furthermore, unlike hMSCs, Saos-2 cells demonstrated an upregulated expression of late osteoblastic markers, OCN and PHEX that suggested β-Gly could affect later stages of osteogenic differentiation. In summary, it is important to consider that β-Gly significantly affects key cell processes of Saos-2 when using it as an osteoblast-like cell model.
Characterization of dielectric properties of residual ashes obtained from rice husk and annoni grass
Authors: Pereira Vinícius Macedo , Heckler Marcos V. Thomas , Vasconcellos Marcos A. Z. , de Menezes Eliana W. , Armas Luis E. G.
Published: September 2023

This paper presents a study about the characterization of dielectric properties (dielectric constant $${\varepsilon }_{r}$$

ε
r

and dielectric-loss constant $$\mathrm{tan}\delta$$

tan
δ

) of samples derived from two different biomass types: rice husk ash (RHA) and annoni grass ash (AGA).The procedure is carried out using the resonant cavity method along with a vector network analyzer. For this purpose, four different ashes were produced, by burning rice husk and annoni grass at two different temperatures and burning times: 400 °C/30 min (RHA40030 and AGA40030) and 800 °C/5 h (RHA8005h and AGA8005h). These ashes were combined with Bakelite to produce cylindrical samples with diameter of 30 mm and thickness of 4.5 mm, which were characterized considering the frequency in the test band for 5G technologies ($${f}_{o}=3.5$$

f
o

=
3.5

GHz). Experimental results showed that the samples burnt at high temperature showed very high $$\mathrm{tan \delta }$$

tan
δ

when compared to the samples burnt at low temperature, mainly for AGA8005h. These values are $$\mathrm{tan \delta }=$$

tan
δ

=

0.1690 and 1.4900 for RHA8005h and AGA8005h, respectively. The resulting dielectric constants are $${\varepsilon }_{r}$$

ε
r

= 3.87 for RHA8005h and $${\varepsilon }_{r}$$

ε
r

= 15.14 for AGA8005h). These very high dielectric loss tangent, indicate that these materials exhibit formidable properties for electromagnetic energy absorption, hence allowing the application as radiation-absorbent material (RAM).
At-sea distribution patterns of the Peruvian diving petrel Pelecanoides garnotii during breeding and non-breeding seasons
Authors: Fernández Claudia E. , Luna-Jorquera Guillermo , Suazo Cristián G. , Quillfeldt Petra
Published: September 2023

At-sea distributions of seabird species are strongly associated with the distribution patterns of their prey, which are influenced by physical oceanic features. During breeding and non-breeding seasons, seabirds move extraordinary distances among different environments. However, foraging site fidelity by seabirds appears to be high in areas of known high productivity, such as frontal zones and upwellings. Here, we present a tracking study for the Peruvian diving-petrel Pelecanoides garnotii, an endemic seabird of the highly productive Humboldt Current System, to assess whether adults use the same foraging areas throughout the year, combining data from nest monitoring and global location sensors (GLS) deployed on 12 individuals between two breeding seasons (2013–2014 and 2014–2015), in Choros Island (29°15′S; 71°32′W), Chile. Two main foraging areas were registered. During the breeding season, adults moved in the northern direction, between 60 to 144 km away from their colony, foraging in areas with high primary productivity. During the non-breeding period, they moved to southern latitudes (~ 1200 km). Adults spent 37% and 63% of their time in flight/land and on/underwater activities, respectively. We determined that birds move northward from their colony during breeding, where prey availability seems more predictable throughout the year. However, during the non-breeding period, it is likely that other environmental factors influence the distribution pattern of the Peruvian diving-petrel.
An efficient churn prediction model using gradient boosting machine and metaheuristic optimization
Authors: AlShourbaji Ibrahim , Helian Na , Sun Yi , Hussien Abdelazim G. , Abualigah Laith , Elnaim Bushra
Published: September 2023

Customer churn remains a critical challenge in telecommunications, necessitating effective churn prediction (CP) methodologies. This paper introduces the Enhanced Gradient Boosting Model (EGBM), which uses a Support Vector Machine with a Radial Basis Function kernel (SVMRBF) as a base learner and exponential loss function to enhance the learning process of the GBM. The novel base learner significantly improves the initial classification performance of the traditional GBM and achieves enhanced performance in CP-EGBM after multiple boosting stages by utilizing state-of-the-art decision tree learners. Further, a modified version of Particle Swarm Optimization (PSO) using the consumption operator of the Artificial Ecosystem Optimization (AEO) method to prevent premature convergence of the PSO in the local optima is developed to tune the hyper-parameters of the CP-EGBM effectively. Seven open-source CP datasets are used to evaluate the performance of the developed CP-EGBM model using several quantitative evaluation metrics. The results showed that the CP-EGBM is significantly better than GBM and SVM models. Results are statistically validated using the Friedman ranking test. The proposed CP-EGBM is also compared with recently reported models in the literature. Comparative analysis with state-of-the-art models showcases CP-EGBM's promising improvements, making it a robust and effective solution for churn prediction in the telecommunications industry.
Searching for intra-cloud positive leaders in VHF
Authors: Scholten O. , Hare B. M. , Dwyer J. , Liu N. , Sterpka C. , Mulrey K. , Veen S. Ter
Published: September 2023

We have used the LOw-Frequency ARray (LOFAR) to search for the growing tip of an intra-cloud (IC) positive leader. Even with our most sensitive beamforming method, where we coherently add the signals of about 170 antenna pairs, we were not able to detect any emission from the tip. Instead, we put constraints on the emissivity of very-high frequency (VHF) radiation from the tip at 0.5 pJ/MHz at 60 MHz, integrated over 100 ns. The limit is independent on whether this emission is in the form of short pulses or continuously radiating. The non-observation of VHF radiation from intra-cloud positive leaders implies that they proceed in an extremely gradual process, which is in sharp contrast with the observations of other parts of a lightning discharge.
Winner-loser effects improve social network efficiency between competitors with equal resource holding power
Authors: Hermanussen M. , Dammhahn M. , Scheffler C. , Groth D.
Published: September 2023

Animal societies are structured of dominance hierarchy (DH). DH can be viewed as networks and analyzed by graph theory. We study the impact of state-dependent feedback (winner-loser effect) on the emergence of local dominance structures after pairwise contests between initially equal-ranking members (equal resource-holding-power, RHP) of small and large social groups. We simulated pairwise agonistic contests between individuals with and without a priori higher RHP by Monte-Carlo-method. Random pairwise contests between equal-ranking competitors result in random dominance structures (‘Null variant’) that are low in transitive triads and high in pass along triads; whereas state-dependent feedback (‘Winner-loser variant’) yields centralized ‘star’ structured DH that evolve from competitors with initially equal RHP and correspond to hierarchies that evolve from keystone individuals. Monte-Carlo simulated DH following state-dependent feedback show motif patterns very similar to those of a variety of natural DH, suggesting that state-dependent feedback plays a pivotal role in robust self-organizing phenomena that transcend the specifics of the individual. Self-organization based on state-dependent feedback leads to social structures that correspond to those resulting from pre-existing keystone individuals. As the efficiency of centralized social networks benefits both, the individual and the group, centralization of social networks appears to be an important evolutionary goal.
The reliability of assistance systems modulates the sense of control and acceptability of human operators
Authors: Vantrepotte Quentin , Chambon Valérian , Berberian Bruno
Published: September 2023

Individuals are increasingly required to interact with complex and autonomous technologies, which often has a significant impact on the control they experience over their actions and choices. A better characterization of the factors responsible for modulating the control experience of human operators is therefore a major challenge to improve the quality of human-system interactions. Using a decision-making task performed in interaction with an automated system, we investigated the influence of two key properties of automated systems, their reliability and explicability, on participants' sense of agency (SoA), as well as the perceived acceptability of system choices. The results show an increase in SoA associated with the most explicable system. Importantly, the increase in system explicability influenced participants' ability to regulate the control resources they engaged in the current decision. In particular, we observed that participants' SoA varied with system reliability in the "explained" condition, whereas no variation was observed in the "non-explained" condition. Finally, we found that system reliability had a direct impact on system acceptability, such that the most reliable systems were also considered the most acceptable systems. These results highlight the importance of studying agency in human–computer interaction in order to define more acceptable automation technologies.
Enhancing stability control of inverted pendulum using Takagi–Sugeno fuzzy model with disturbance rejection and input–output constraints
Authors: Nguyen Thi-Van-Anh , Dong Bao-Trung , BUI Ngoc-Tam
Published: September 2023

The Takagi–Sugeno (T–S) fuzzy model is a versatile approach widely used in system control, often in combination with other strategies. This paper addresses key control challenges linked to the T–S system and presents important considerations to ensure its successful application using the Lyapunov theorem. One crucial aspect is determining the optimal number of premise variables and selecting accurate fuzzy rules for the T–S model. Additionally, the theorem based on Linear Matrix Inequality (LMI) is developed to enable effective disturbance rejection. To enhance stability control, constraints are imposed on the output angle and control input of a rotary inverted pendulum (RIP). By integrating T–S fuzzy control, disturbance rejection, and input/output constraints, robust stability in controlling the RIP is achieved. Extensive simulations are performed to showcase the efficiency of the suggested method, and the simulation results are thoroughly discussed and analyzed to verify the efficacy of the control method.
Deep neural architecture for natural language image synthesis for Tamil text using BASEGAN and hybrid super resolution GAN (HSRGAN)
Authors: Diviya M. , Karmel A.
Published: September 2023

Tamil is a language that has the most extended history and is a conventional language of India. It has antique origins and a distinct tradition. A study reveals that at the beginning of the twenty-first century, more than 66 million people spoke Tamil. In the present time, image synthesis from text emerged as a promising advancement in computer vision applications. The research work done so far in intelligent systems is trained in universal language but still has not achieved the desired development level in regional languages. Regional languages have a greater scope for developing applications and will enhance more research areas to be explored, ruling out the barrier. The current work using Auto Encoders failed at the point of providing vivid information along with essential descriptions of the synthesised images. The work aims to generate embedding vectors using a language model headed by image synthesis using GAN (Generative Adversarial Network) architecture. The proposed method is divided into two stages: designing a language model TBERTBASECASE model for generating embedding vectors. Synthesising images using Generative Adversarial Network called BASEGAN, the resolution has been improved through two-stage architecture named HYBRID SUPER RESOLUTION GAN. The work uses Oxford-102 and CUB-200 datasets. The framework efficiency has been measured using F1 Score, Fréchet inception distance (FID), and Inception Score (IS). Language and image synthesis architecture proposed can bridge the gap between the research ideas in regional languages.