bluuebunny/crossref_metadata_2025_split huggingface dataset:
Durable superhydrophobic coatings for prevention of rain attenuation of 5G/weather radomes
Authors: Wei Jinfei , Zhang Jiaojiao , Cao Xiaojun , Huo Jinhui , Huang Xiaopeng , Zhang Junping 
Published: May 2023

AbstractSuperhydrophobic coatings are expected to solve the rain attenuation issue of 5G radomes. However, it is very challenging to design and construct such superhydrophobic coatings with good impalement resistance, mechanical robustness, and weather resistance, which remains as one of the main bottlenecks hindering their practical applications. Here, we report the design of superhydrophobic coatings with all these merits mentioned above by spray-coating a suspension of adhesive/fluorinated silica core/shell microspheres onto substrates. The core/shell microspheres are formed by phase separation of the adhesive and adhesion between the adhesive and fluorinated silica nanoparticles. The coatings have an approximately isotropic three-tier hierarchical micro-/micro-/nanostructure, a dense but rough surface at the nanoscale, and chemically inert composition with low surface energy. Consequently, the coatings show excellent impalement resistance, mechanical robustness and weather resistance compared with previous studies, and the mechanisms are revealed. Furthermore, we realize large-scale preparation, extension, and practical application of the coatings for efficiently preventing rain attenuation of 5G/weather radomes. By taking these advantages, we believe that the superhydrophobic coatings have great application potential and market prospect. The findings here will boost preparation and real-world applications of superhydrophobic coatings.
VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation
Authors: Madec Simon , Irfan Kamran , Velumani Kaaviya , Baret Frederic , David Etienne , Daubige Gaetan , Samatan Lucas Bernigaud , Serouart Mario , Smith Daniel , James Chrisbin , Camacho Fernando , Guo Wei , De Solan Benoit , Chapman Scott C. , Weiss Marie 
Published: May 2023

AbstractApplying deep learning to images of cropping systems provides new knowledge and insights in research and commercial applications. Semantic segmentation or pixel-wise classification, of RGB images acquired at the ground level, into vegetation and background is a critical step in the estimation of several canopy traits. Current state of the art methodologies based on convolutional neural networks (CNNs) are trained on datasets acquired under controlled or indoor environments. These models are unable to generalize to real-world images and hence need to be fine-tuned using new labelled datasets. This motivated the creation of the VegAnn - Vegetation Annotation - dataset, a collection of 3775 multi-crop RGB images acquired for different phenological stages using different systems and platforms in diverse illumination conditions. We anticipate that VegAnn will help improving segmentation algorithm performances, facilitate benchmarking and promote large-scale crop vegetation segmentation research.
67 million natural product-like compound database generated via molecular language processing
Authors: Tay Dillon W. P. , Yeo Naythan Z. X. , Adaikkappan Krishnan , Lim Yee Hwee , Ang Shi Jun 
Published: May 2023

AbstractNatural products are a rich resource of bioactive compounds for valuable applications across multiple fields such as food, agriculture, and medicine. For natural product discovery, high throughput in silico screening offers a cost-effective alternative to traditional resource-heavy assay-guided exploration of structurally novel chemical space. In this data descriptor, we report a characterized database of 67,064,204 natural product-like molecules generated using a recurrent neural network trained on known natural products, demonstrating a significant 165-fold expansion in library size over the approximately 400,000 known natural products. This study highlights the potential of using deep generative models to explore novel natural product chemical space for high throughput in silico discovery.
Ten years of morphodynamic data at a micro-tidal urban beach: Cala Millor (Western Mediterranean Sea)
Authors: Fernández-Mora Angels , Criado-Sudau Francisco Fabian , Gómez-Pujol Lluís , Tintoré Joaquín , Orfila Alejandro 
Published: May 2023

AbstractSystematic and sustained high quality measurements of nearshore waves and beach morphology are crucial to understand morphodynamic processes that determine beach evolution, to unravel the effects of global warming on sandy coasts and thus improve forecasting models. In 2011 a comprehensive beach monitoring program, the first in the Mediterranean Sea, started at Cala Millor Beach on the island of Mallorca (Spain). The aim was to provide long-term datasets of near-shore morphodynamics in a carbonate sandy micro-tidal and semi-embayed beach fronted by a Posidonia oceanica seagrass meadow. We present our morphological and hydrodynamical dataset of Cala Millor covering more than a decade. The dataset includes topobathymetries, shoreline positions obtained from video cameras, meteorological parameters from a weather station, currents, as well as waves and sea level from ADCP measurements and sediment size. This free and unrestricted archived dataset can be used to support the modelling of erosion-deposition patterns, calibrate beach evolution models, and as a result to propose adaptation and mitigation actions under different global change scenarios.
FOPPA: an open database of French public procurement award notices from 2010–2020
Authors: Potin Lucas , Labatut Vincent , Morand Pierre-Henri , Largeron Christine 
Published: May 2023

AbstractPublic Procurement refers to governments’ purchasing activities of goods, services, and construction of public works. In the European Union (EU), it is an essential sector, corresponding to 15% of the GDP. EU public procurement generates large amounts of data, because award notices related to contracts exceeding a predefined threshold must be published on the TED (EU’s official journal). Under the framework of the DeCoMaP project, which aims at leveraging such data in order to predict fraud in public procurement, we constitute the FOPPA (French Open Public Procurement Award notices) database. It contains the description of 1,380,965 lots obtained from the TED, covering the 2010–2020 period for France. We detect a number of substantial issues in these data, and propose a set of automated and semi-automated methods to solve them and produce a usable database. It can be leveraged to study public procurement in an academic setting, but also to facilitate the monitoring of public policies, and to improve the quality of the data offered to buyers and suppliers.
Biophotonic sensor for swift detection of malignant brain tissues by using nanocomposite YBa2Cu3O7/dielectric material as a 1D defective photonic crystal
Authors: Malek C. , Abdallah Suhad Ali Osman , Awasthi S. K. , Ismail M. A. , Sabra W. , Aly Arafa H. 
Published: May 2023

AbstractIn the present research work we have theoretically examined the biosensing capabilities of proposed one dimensional defective photonic crystal for swift detection of malignant brain tissues. The transfer matrix formulation and MATLAB computational tool have been used to examine the transmission properties of proposed structure. The identical buffer layers of nanocomposite superconducting material have been used either side of cavity region to enhance the interaction between incident light and different brain tissue samples poured into the cavity region. All the investigations have been carried out under normal incidence to suppress the experimental liabilities involved. We have investigated the biosensing performance of the proposed design by changing the values of two internal parameters (1) the cavity layer thickness (d4) and (2) volume fraction (η) of nanocomposite buffer layers one by one to get the optimum biosensing performance from the structure. It has been found that the sensitivity of the proposed design becomes 1.42607 μm/RIU when the cavity region of thickness 15dd is loaded with lymphoma brain tissue. This value of sensitivity can be further increased to 2.66136 μm/RIU with η = 0.8. The findings of this work are very beneficial for designing of various bio-sensing structures composed of nanocomposite materials of diversified biomedical applications.
Self-modulation of rectus femoris reflex excitability in humans
Authors: Kim Kyoungsoon , Akbas Tunc , Lee Robert , Manella Kathleen , Sulzer James 
Published: May 2023

AbstractHyperreflexia is common after neurological injury such as stroke, yet clinical interventions have had mixed success. Our previous research has shown that hyperreflexia of the rectus femoris (RF) during pre-swing is closely associated with reduced swing phase knee flexion in those with post-stroke Stiff-Knee gait (SKG). Thus, reduction of RF hyperreflexia may improve walking function in those with post-stroke SKG. A non-pharmacological procedure for reducing hyperreflexia has emerged based on operant conditioning of H-reflex, an electrical analog of the spinal stretch reflex. It is currently unknown whether operant conditioning can be applied to the RF. This feasibility study trained 7 participants (5 neurologically intact, 2 post-stroke) to down-condition the RF H-reflex using visual feedback. We found an overall decrease in average RF H-reflex amplitude among all 7 participants (44% drop, p < 0.001, paired t-test), of which the post-stroke individuals contributed (49% drop). We observed a generalized training effect across quadriceps muscles. Post-stroke individuals exhibited improvements in peak knee-flexion velocity, reflex excitability during walking, and clinical measures of spasticity. These outcomes provide promising initial results that operant RF H-reflex conditioning is feasible, encouraging expansion to post-stroke individuals. This procedure could provide a targeted alternative in spasticity management.
Ivermectin metabolites reduce Anopheles survival
Authors: Kobylinski Kevin C. , Tipthara Phornpimon , Wamaket Narenrit , Chainarin Sittinont , Kullasakboonsri Rattawan , Sriwichai Patchara , Phasomkusolsil Siriporn , Hanboonkunupakarn Borimas , Jittamala Podjanee , Gemmell Renia , Boyle John , Wrigley Stephen , Steele Jonathan , White Nicholas J. , Tarning Joel 
Published: May 2023

AbstractIvermectin mass drug administration to humans or livestock is a potential vector control tool for malaria elimination. The mosquito-lethal effect of ivermectin in clinical trials exceeds that predicted from in vitro laboratory experiments, suggesting that ivermectin metabolites have mosquito-lethal effect. The three primary ivermectin metabolites in humans (i.e., M1 (3″-O-demethyl ivermectin), M3 (4-hydroxymethyl ivermectin), and M6 (3″-O-demethyl, 4-hydroxymethyl ivermectin) were obtained by chemical synthesis or bacterial modification/metabolism. Ivermectin and its metabolites were mixed in human blood at various concentrations, blood-fed to Anopheles dirus and Anopheles minimus mosquitoes, and mortality was observed daily for fourteen days. Ivermectin and metabolite concentrations were quantified by liquid chromatography linked with tandem mass spectrometry to confirm the concentrations in the blood matrix. Results revealed that neither the LC50 nor LC90 values differed between ivermectin and its major metabolites for An. dirus or An. minimus., Additionally, there was no substantial differences in the time to median mosquito mortality when comparing ivermectin and its metabolites, demonstrating an equal rate of mosquito killing between the compounds evaluated. These results demonstrate that ivermectin metabolites have a mosquito-lethal effect equal to the parent compound, contributing to Anopheles mortality after treatment of humans.
Earthquake-induced soil landslides: volume estimates and uncertainties with the existing scaling exponents
Authors: Yunus Ali P. , Xinyu Chen , Catani Filippo , Subramaniam Srikrishnan Siva , Fan Xuanmei , Jie Dou , Sajinkumar K. S. , Gupta Ankita , Avtar Ram 
Published: May 2023

AbstractQuantifying landslide volumes in earthquake affected areas is critical to understand the orogenic processes and their surface effects at different spatio-temporal scales. Here, we build an accurate scaling relationship to estimate the volume of shallow soil landslides based on 1 m pre- and post-event LiDAR elevation models. On compiling an inventory of 1719 landslides for 2018 Mw 6.6 Hokkaido-Iburi earthquake epicentral region, we find that the volume of soil landslides can be estimated by γ = 1.15. The total volume of eroded debris from Hokkaido-Iburi catchments based on this new scaling relationship is estimated as 64–72 million m3. Based on the GNSS data approximation, we noticed that the co-seismic uplift volume is smaller than the eroded volume, suggesting that frequent large earthquakes (and rainfall extremes) may be counterbalancing the topographic uplift through erosion by landslides, especially in humid landscapes such as Japan, where soil properties are rather weak.
Intra-pulse difference frequency generation in ZnGeP2 for high-frequency terahertz radiation generation
Authors: Carnio B. N. , Zhang M. , Zawilski K. T. , Schunemann P. G. , Moutanabbir O. , Elezzabi A. Y. 
Published: May 2023

AbstractThe highly-nonlinear chalcopyrite crystal family has experienced remarkable success as source crystals in the mid-infrared spectral range, such that these crystals are primary candidates for producing high terahertz frequency (i.e., $$\gtrsim$$
≳
10 THz) electric fields. A phase-resolved terahertz electric field pulse is produced via intra-pulse difference frequency generation in a chalcopyrite (110) ZnGeP2 crystal, with phase-matching being satisfied by the excitation electric field pulse having polarizations along both the ordinary and extraordinary crystal axes. While maximum spectral power is observed at the frequency of 24.5 THz (in agreement with intra-pulse phase-matching calculations), generation nonetheless occurs across the wide spectral range of 23–30 THz. To our knowledge, this is the first time a chalcopyrite ZnGeP2 crystal has been used for the generation of phase-resolved high-frequency terahertz electric fields.
Bayesian forecasting of disease spread with little or no local data
Authors: Cook Jonathan D. , Williams David M. , Walsh Daniel P. , Hefley Trevor J. 
Published: May 2023

AbstractRapid and targeted management actions are a prerequisite to efficiently mitigate disease outbreaks. Targeted actions, however, require accurate spatial information on disease occurrence and spread. Frequently, targeted management actions are guided by non-statistical approaches that define the affected area by a pre-determined distance surrounding a small number of disease detections. As an alternative, we present a long-recognized but underutilized Bayesian technique that uses limited local data and informative priors to make statistically valid predictions and forecasts about disease occurrence and spread. As a case study, we use limited local data that were available after the detection of chronic wasting disease in Michigan, U.S. along with information rich priors obtained from a previous study in a neighboring state. Using these limited local data and informative priors, we generate statistically valid predictions of disease occurrence and spread for the Michigan study area. This Bayesian technique is conceptually and computationally simple, relies on little to no local data, and is competitive with non-statistical distance-based metrics in all performance evaluations. Bayesian modeling has added benefits because it allows practitioners to generate immediate forecasts of future disease conditions and provides a principled framework to incorporate new data as they accumulate. We contend that the Bayesian technique offers broad-scale benefits and opportunities to make statistical inference across a diversity of data-deficient systems, not limited to disease.
Discovery of andrographolide hit analog as a potent cyclooxygenase-2 inhibitor through consensus MD-simulation, electrostatic potential energy simulation and ligand efficiency metrics
Authors: Jain Priyanka , Satija Jitendra , Sudandiradoss C. 
Published: May 2023

AbstractCyclooxygenase-2 (COX-2) is the key enzyme responsible for the conversion of arachidonic acid to prostaglandins that display pro-inflammatory properties and thus, it is a potential target protein to develop anti-inflammatory drugs. In this study, chemical and bio-informatics approaches have been employed to find a novel potent andrographolide (AGP) analog as a COX-2 inhibitor having better pharmacological properties than aspirin and rofecoxib (controls). The full amino acid sequenced human Alpha fold (AF) COX-2 protein (604AA) was selected and validated for its accuracy against the reported COX-2 protein structures (PDB ID: 5F19, 5KIR, 5F1A, 5IKQ and 1V0X) followed by multiple sequence alignment analysis to establish the sequence conservation. The systematic virtual screening of 237 AGP analogs against AF-COX-2 protein yielded 22 lead compounds based on the binding energy score (< − 8.0 kcal/mol). These were further screened out to 7 analogs by molecular docking analysis and investigated further for ADMET prediction, ligand efficiency metrics calculations, quantum mechanical analysis, MD simulation, electrostatic potential energy (EPE) docking simulation, and MM/GBSA. In-depth analysis revealed that AGP analog A3 (3-[2-[(1R,4aR,5R,6R,8aR)-6-hydroxy-5,6,8a-trimethyl-2-methylidene-3,4,4a,5,7,8-hexahydro-1H-naphthalen-1-yl]ethylidene]-4-hydroxyoxolan-2-one) forms the most stable complex with the AF-COX-2 showing the least RMSD value (0.37 ± 0.03 nm), a good number of hydrogen bonds (protein–ligand H-bond = 11, and protein H-bond = 525), minimum EPE score (− 53.81 kcal/mol), and lowest MM-GBSA before and after simulation (− 55.37 and − 56.25 kcal/mol, respectively) value compared to other analogs and controls. Thus, we suggest that the identified A3 AGP analog could be developed as a promising plant-based anti-inflammatory drug by inhibiting COX-2.
Prosaposin PS18 reduces dopaminergic neurodegeneration in a 6-hydroxydopamine rat model of Parkinson’s disease
Authors: Wu Kuo-Jen , Hung Tsai-Wei , Wang Yu-Syuan , Chen Yun-Hsiang , Bae Eun-Kyung , Yu Seong-Jin 
Published: May 2023

AbstractSaposin and its precursor prosaposin are endogenous proteins with neurotrophic and anti-apoptotic properties. Prosaposin or its analog prosaposin-derived 18-mer peptide (PS18) reduced neuronal damage in hippocampus and apoptosis in stroke brain. Its role in Parkinson’s disease (PD) has not been well characterized. This study aimed to examine the physiological role of PS18 in 6-hydroxydopamine (6-OHDA) cellular and animal models of PD. We found that PS18 significantly antagonized 6-OHDA -mediated dopaminergic neuronal loss and TUNEL in rat primary dopaminergic neuronal culture. In SH-SY5Y cells overexpressing the secreted ER calcium—monitoring proteins, we found that PS18 significantly reduced thapsigargin and 6-OHDA-mediated ER stress. The expression of prosaposin and the protective effect of PS18 were next examined in hemiparkinsonian rats. 6-OHDA was unilaterally administered to striatum. The expression of prosaposin was transiently upregulated in striatum on D3 (day 3) after lesioning and returned below the basal level on D29. The 6-OHDA-lesioned rats developed bradykinesia and an increase in methamphetamine-mediated rotation, which was antagonized by PS18. Brain tissues were collected for Western blot, immunohistochemistry, and qRTPCR analysis. Tyrosine hydroxylase immunoreactivity was significantly reduced while the expressions of PERK, ATF6, CHOP, and BiP were upregulated in the lesioned nigra; these responses were significantly antagonized by PS18. Taken together, our data support that PS18 is neuroprotective in cellular and animal models of PD. The mechanisms of protection may involve anti-ER stress.
The perception of COVID-19, the Light Triad, harmony and ethical sensitivity in late adolescents: The role of meaning-making and stress
Authors: Krok Dariusz , Zarzycka Beata , Telka Ewa 
Published: May 2023

AbstractThe experiences of inner harmony and ethical sensitivity among late adolescents during the COVID-19 pandemic depend on the interplay of perceptive factors, personal resources and cognitive and stress mechanisms. Using a sample from Poland, the present study examined the relationships between the perceptions of COVID-19 and the Light Triad and the characteristics of inner harmony and ethical sensitivity from the mediational perspective of meaning-making and perceived stress. Three hundred and sixteen late adolescents were recruited in the cross-sectional study. They filled in questionnaires measuring the perception of COVID-19, the Light Triad, meaning-making, stress, inner harmony and ethical sensitivity, from April to September 2020. The perception of COVID-19 was negatively related to ethical sensitivity, whereas the Light Triad was positively related to inner harmony and ethical sensitivity. Perceived stress and meaning-making mediated the relationships between the perceptions of COVID-19, the Light Triad and the characteristic of inner harmony. Perception processes and the Light Triad dimensions directly influence ethical sensitivity, as well as indirectly affect inner harmony through meaning-making processes and perceived stress. This noticeably highlights the vital role played by meaning structures and emotional reactions in the experience of inner peace and calmness.
Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system
Authors: Mu Qianqian , Long Fei , Li Bin 
Published: May 2023

AbstractThis paper investigates the adaptive neural network prescribed performance control problem for a class of dual switching nonlinear systems with time-delay. By using the approximation of neural networks (NNs), an adaptive controller is designed to achieve tracking performance. Another research point of this paper is tracking performance constraints which can solve the performance degradation in practical systems. Therefore, an adaptive NNs output feedback tracking scheme is studied by combining the prescribed performance control (PPC) and backstepping method. With the designed controller and the switching rule, all signals of the closed-loop system are bounded, and the tracking performance satisfies the prescribed performance.
Development, fabrication and mechanical characterisation of auxetic bicycle handlebar grip
Authors: Novak Nejc , Plesec Vasja , Harih Gregor , Cupar Andrej , Kaljun Jasmin , Vesenjak Matej 
Published: May 2023

AbstractThe auxetic cellular structures are one of the most promising metamaterials for vibration damping and crash absorption applications. Therefore, their use in the bicycle handlebar grip was studied in this work. A preliminary computational design study was performed using various auxetic and non-auxetic geometries under four load cases, which can typically appear. The most representative geometries were then selected and fabricated using additive manufacturing. These geometries were then experimentally tested to validate the discrete and homogenised computational models. The homogenised computational model was then used to analyse the biomechanical behaviour of the handlebar grip. It was observed that handle grip made from auxetic cellular metamaterials reduce the high contact pressures, provide similar stability and hereby improve the handlebar ergonomics.