bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-resolution precipitation monitoring with a dense seismic nodal array
Authors: Hua Junlin , Wu Mengxi , Mulholland Jake P. , Neelin J. David , Tsai Victor C. , Trugman Daniel T. 
Published: July 2023

AbstractAccurate precipitation monitoring is crucial for understanding climate change and rainfall-driven hazards at a local scale. However, the current suite of monitoring approaches, including weather radar and rain gauges, have different insufficiencies such as low spatial and temporal resolution and difficulty in accurately detecting potentially destructive precipitation events such as hailstorms. In this study, we develop an array-based method to monitor rainfall with seismic nodal stations, offering both high spatial and temporal resolution. We analyze seismic records from 1825 densely spaced, high-frequency seismometers in Oklahoma, and identify signals from nine precipitation events that occurred during the one-month station deployment in 2016. After removing anthropogenic noise and Earth structure response, the obtained precipitation spatial pattern mimics the one from a nearby operational weather radar, while offering higher spatial (~ 300 m) and temporal (< 10 s) resolution. We further show the potential of this approach to monitor hail with joint analysis of seismic intensity and independent precipitation rate measurements, and advocate for coordinated seismological-meteorological field campaign design.
Araucaria heterophylla oleogum resin essential oil is a novel aldose reductase and butyryl choline esterase enzymes inhibitor: in vitro and in silico evidence
Authors: Soliman Amal F. , Sabry Mohamed A. , Abdelwahab Gehad 
Published: July 2023

AbstractThe essential oil isolated by hydrodistillation of the oleogum resin of Araucaria heterophylla has been analyzed by GC–MS. Twenty-four components accounting to 99.89% of the total detected constituents of this essential oil were identified. The major ones were: caryophyllene oxide (14.8%), ( +)-sabinene (12.07%), D-limonene (11.22%), caryophyllene (10.36%), α-copaene (8.00%), β-pinene (6.44%), trans-verbenol (5.88%) and α-pinene oxide (5.18%). The in vitro inhibitory activities of this oil against aldose reductase, BuCHE, COX-2 and SARS-CoV-2 Mpro enzymes were evaluated. This revealed promising inhibitory activity of the essential oil against both aldose reductase and BuCHE enzymes. The molecular docking study of the major components of the Araucaria heterophylla essential oil was carried out to correlate their binding modes and affinities for aldose reductase and BuCHE enzymes with the in vitro results. In conclusion, the in vitro inhibitory activity of the essential oil attributed to the synergistic effect between its components and the in silico study suggested that compounds containing epoxide and hydroxyl groups may be responsible for this activity. This study is preliminary screening for the oil to be used as antidiabetic cataract and Alzheimer’s disease therapeutics and further investigations may be required.
Machine learning-based guilt detection in text
Authors: Meque Abdul Gafar Manuel , Hussain Nisar , Sidorov Grigori , Gelbukh Alexander 
Published: July 2023

AbstractWe introduce a novel Natural Language Processing (NLP) task called guilt detection, which focuses on detecting guilt in text. We identify guilt as a complex and vital emotion that has not been previously studied in NLP, and we aim to provide a more fine-grained analysis of it. To address the lack of publicly available corpora for guilt detection, we created VIC, a dataset containing 4622 texts from three existing emotion detection datasets that we binarized into guilt and no-guilt classes. We experimented with traditional machine learning methods using bag-of-words and term frequency-inverse document frequency features, achieving a 72% f1 score with the highest-performing model. Our study provides a first step towards understanding guilt in text and opens the door for future research in this area.
Noradrenergic projections regulate the acquisition of classically conditioned eyelid responses in wild-type and are impaired in kreisler mice
Authors: Porras-García Elena , Mas-Nieto Magdalena , Delgado-García José María , Domínguez-del-Toro Eduardo 
Published: July 2023

AbstractDuring embryonic development, heterozygous mutant kreisler mice undergo ectopic expression of the Hoxa3 gene in the rostral hindbrain, affecting the opioid and noradrenergic systems. In this model, we have investigated behavioral and cognitive processes in their adulthood. We confirmed that pontine and locus coeruleus neuronal projections are impaired, by using startle and pain tests and by analyzing immunohistochemical localization of tyrosine hydroxylase. Our results showed that, even if kreisler mice are able to generate eyelid reflex responses, there are differences with wild-types in the first component of the response (R1), modulated by the noradrenergic system. The acquisition of conditioned motor responses is impaired in kreisler mice when using the trace but not the delay paradigm, suggesting a functional impairment in the hippocampus, subsequently confirmed by reduced quantification of alpha2a receptor mRNA expression in this area but not in the cerebellum. Moreover, we demonstrate the involvement of adrenergic projection in eyelid classical conditioning, as clonidine prevents the appearance of eyelid conditioned responses in wild-type mice. In addition, hippocampal motor learning ability was restored in kreisler mice by administration of adrenergic antagonist drugs, and a synergistic effect was observed following simultaneous administration of idazoxan and naloxone.
COVID-19 infection inference with graph neural networks
Authors: Song Kyungwoo , Park Hojun , Lee Junggu , Kim Arim , Jung Jaehun 
Published: July 2023

AbstractInfectious diseases spread rapidly, and epidemiological surveys are vital to detect high-risk transmitters and reduce transmission rates. To enhance efficiency and reduce the burden on epidemiologists, an automatic tool to assist with epidemiological surveys is necessary. This study aims to develop an automatic epidemiological survey to predict the influence of COVID-19-infected patients on future additional infections. To achieve this, the study utilized a dataset containing interaction information between confirmed cases, including contact order, contact times, and movement routes, as well as individual properties such as symptoms. Graph neural networks (GNNs) were used to incorporate interaction information and individual properties. Two variants of GNNs, graph convolutional and graph attention networks, were utilized, and the results showed that the graph-based models outperformed traditional machine learning models. For the area under the curve, the 2nd, 3rd, and 4th order spreading predictions showed higher performance by 0.200, 0.269, and 0.190, respectively. The results show that the contact information of an infected person is crucial data that can help predict whether that person will affect future infections. Our findings suggest that incorporating the relationships between an infected person and others can improve the effectiveness of an automatic epidemiological survey.
Diacerein ameliorates cholestasis-induced liver fibrosis in rat via modulating HMGB1/RAGE/NF-κB/JNK pathway and endoplasmic reticulum stress
Authors: Abdelfattah Amira Mohammed , Mahmoud Shireen Sami , EL-wafaey Dalia Ibrahim , Abdelgeleel Heba Mahmoud , Abdelhamid Amira Mohamed 
Published: July 2023

AbstractDiacerein is an interleukin (IL)-1β inhibitor approved for osteoarthritis. This study aimed to investigate the potential anti-fibrotic effect of diacerein against bile duct ligation (BDL)-induced liver fibrosis. Forty male Wistar rats were divided into: sham-operated group, BDL group, and BDL groups treated with diacerein at 10, 30, and 50 mg/kg/day starting two days before surgery and continued for 4 weeks. Diacerein decreased the hepatic injury markers and alleviated oxidative stress triggered by BDL by reducing hepatic malondialdehyde (MDA) and increasing hepatic superoxide dismutase (SOD) levels. Diacerein mitigated BDL-induced inflammation via lowering hepatic levels and mRNA expression of high mobility group box 1 (HMGB1), nuclear factor-κB (NF-κB), and IL-1β. The hepatic gene expression of Advanced Glycation End products Receptor (RAGE) gene and immunohistochemical expression of some ER stress markers, e.g., glucose-regulated protein 78 (GRP78), inositol-requiring enzyme 1 (IRE1α), protein kinase RNA-like endoplasmic reticulum kinase (PERK), CCAAT/enhancer-binding protein homologous protein (CHOP), and phosphorylated c-Jun N-terminal kinase protein contents were lowered by diacerein. Furthermore, diacerein suppressed the hepatic levels of fibrogenic mediators, e.g., Transforming growth factor β1 (TGF˗β1), α- smooth muscle actin (α-SMA), collagen 1, and hydroxyproline, as well as the apoptotic caspase 3 and BAX immunostaining in BDL rats. The histopathological abnormalities induced by BDL significantly improved. Our study demonstrated that diacerein exhibited an antifibrotic effect by inhibiting HMGB1/RAGE/NF-κB/JNK pathway, and ER stress. Better protection was observed with increasing the dose.
Reverse transcription-quantitative PCR (RT-qPCR) without the need for prior removal of DNA
Authors: Đermić Damir , Ljubić Sven , Matulić Maja , Procino Alfredo , Feliciello Maria Chiara , Ugarković Đurđica , Feliciello Isidoro 
Published: July 2023

AbstractThe procedure illustrated in this paper represents a new method for transcriptome analysis by PCR (Polymerase Chain Reaction), which circumvents the need for elimination of potential DNA contamination. Compared to the existing methodologies, our method is more precise, simpler and more reproducible because it preserves the RNA’s integrity, does not require materials and/or reagents that are used for elimination of DNA and it also reduces the number of samples that should be set up as negative controls. This novel procedure involves the use of a specifically modified primer during reverse transcription step, which contains mismatched bases, thus producing cDNA molecules that differ from genomic DNA. By using the same modified primer in PCR amplification, only cDNA template is amplified since genomic DNA template is partially heterologous to the primer. In this way, amplification by PCR is unaffected by any potential DNA contamination since it is specific only for the cDNA template. Furthermore, it accurately reflects the initial RNA concentration of the sample, which is prone to changes due to various physical or enzymatic treatments commonly used by the current methodologies for DNA elimination. The method is particularly suitable for quantification of highly repetitive DNA transcripts, such as satellite DNA.
Aesthetics and neural network image representations
Authors: Janik Romuald A. 
Published: July 2023

AbstractWe analyze the spaces of images encoded by generative neural networks of the BigGAN architecture. We find that generic multiplicative perturbations of neural network parameters away from the photo-realistic point often lead to networks generating images which appear as “artistic renditions” of the corresponding objects. This demonstrates an emergence of aesthetic properties directly from the structure of the photo-realistic visual environment as encoded in its neural network parametrization. Moreover, modifying a deep semantic part of the neural network leads to the appearance of symbolic visual representations. None of the considered networks had any access to images of human-made art.
Analysis of macerated ticks using Boolean logic gating colorimetric isothermal nucleic acid assays for Lyme Borrelia and Ixodes scapularis ticks
Authors: Bhadra Sanchita , Esteve-Gasent Maria D. , Ellington Andrew D. 
Published: July 2023

AbstractLyme disease, one of the most common tickborne diseases, has been rapidly spreading in parallel with the expansion of the range of its tick vector. Better tick surveillance efforts are needed to accurately estimate disease risk and to guide public health and clinical management. We have developed two multiplex loop-mediated isothermal amplification (LAMP) reactions coupled with oligonucleotide strand displacement (OSD) probes to identify the tick host, Ixodes scapularis, and the Lyme disease pathogen, Borrelia burgdorferi, they carry. In each multiplex LAMP-OSD assay the co-presence of two target sequences is computed at the DNA level by linking the two corresponding amplicons and detecting the co-product on colorimetric lateral flow dipsticks. In tests with synthetic DNA, the co-presence of as few as four copies of input DNA could be detected, without producing spurious signals. Most importantly, though, the LAMP-OSD assay is amenable to being carried out directly with macerated tick samples, without any sample preparation. In such field conditions, assays performed robustly and demonstrated 97–100% sensitivity and 100% specificity with both field-collected and lab-raised artificially infected ticks. Such easy-to-use, arthropod and pathogen-specific assays would be well suited to field and near patient use without relying on complex instrumentation or infrastructure.
Green nanocoating-based polysaccharides decorated with ZnONPs doped Egyptian kaolinite for antimicrobial coating paper
Authors: Hasanin Mohamed S. , El Saied Houssni , Morsy Fatma A. , Hassan Abdel Latif Rokbaa Hanaa 
Published: July 2023

AbstractPaper coating plays an important role in the paper properties, printability and application. The nanocoating is a multifunction layer that provides the paper with unique features. In this work, nanocoating formulas were prepared using a green method and component. The nanocoating formulas were based on biopolymers nanostarch NSt and nanochitosan NCh (NCS) decorated with Egyptian kaolinite Ka doped with zinc nanoparticles NCS@xka/ZnONPs (x represents different ratios) support for multifunctional uses. The nanocoating formulas were characterized using a physiochemical analysis as well as a topographical study. FTIR, XRD, SEM and TEM techniques were used. Additionally, the antimicrobial activity of the tested samples was assessed against six microorganisms including Gram-negative and Gram-positive bacteria. The prepared nanocoating formulas affirmed excellent antimicrobial activity as a broad-spectrum antimicrobial active agent with excellent activity against all representative microbial communities. The nanocoating with the highest ratio of Ka/ZnONPs (NCS@40 ka/ZnONPs) showed excellent antimicrobial activity with an inhibition percentage of more than 70% versus all microorganisms presented. The paper was coated with the prepared suspensions and characterized concerning optical, mechanical and physical properties. When Ka/ZnONPs were loaded into NCS in a variety of ratios, the characteristics of coated paper were enhanced compared to blank paper. The sample NCS@40 ka/ZnONPs increased tensile strength by 11%, reduced light scattering by 12%, and improved brightness and whiteness by 1%. Paper coated with NCh suspension had 35.32% less roughness and 188.6% less porosity. When coated with the sample NCS@10 ka/ZnONPs, the coated paper's porosity was reduced by 94% and its roughness was reduced by 10.85%. The greatest reduction in water absorptivity was attained by coating with the same sample, with a reduction percentage of 132%.
Visual experience shapes the Bouba-Kiki effect and the size-weight illusion upon sight restoration from congenital blindness
Authors: Piller Sophia , Senna Irene , Ernst Marc O. 
Published: July 2023

AbstractThe Bouba-Kiki effect is the systematic mapping between round/spiky shapes and speech sounds (“Bouba”/“Kiki”). In the size-weight illusion, participants judge the smaller of two equally-weighted objects as being heavier. Here we investigated the contribution of visual experience to the development of these phenomena. We compared three groups: early blind individuals (no visual experience), individuals treated for congenital cataracts years after birth (late visual experience), and typically sighted controls (visual experience from birth). We found that, in cataract-treated participants (tested visually/visuo-haptically), both phenomena are absent shortly after sight onset, just like in blind individuals (tested haptically). However, they emerge within months following surgery, becoming statistically indistinguishable from the sighted controls. This suggests a pivotal role of visual experience and refutes the existence of an early sensitive period: A short period of experience, even when gained only years after birth, is sufficient for participants to visually pick-up regularities in the environment, contributing to the development of these phenomena.
Identifying oscillatory brain networks with hidden Gaussian graphical spectral models of MEEG
Authors: Paz-Linares Deirel , Gonzalez-Moreira Eduardo , Areces-Gonzalez Ariosky , Wang Ying , Li Min , Martinez-Montes Eduardo , Bosch-Bayard Jorge , Bringas-Vega Maria L. , Valdes-Sosa Mitchell , Valdes-Sosa Pedro A. 
Published: July 2023

AbstractIdentifying the functional networks underpinning indirectly observed processes poses an inverse problem for neurosciences or other fields. A solution of such inverse problems estimates as a first step the activity emerging within functional networks from EEG or MEG data. These EEG or MEG estimates are a direct reflection of functional brain network activity with a temporal resolution that no other in vivo neuroimage may provide. A second step estimating functional connectivity from such activity pseudodata unveil the oscillatory brain networks that strongly correlate with all cognition and behavior. Simulations of such MEG or EEG inverse problem also reveal estimation errors of the functional connectivity determined by any of the state-of-the-art inverse solutions. We disclose a significant cause of estimation errors originating from misspecification of the functional network model incorporated into either inverse solution steps. We introduce the Bayesian identification of a Hidden Gaussian Graphical Spectral (HIGGS) model specifying such oscillatory brain networks model. In human EEG alpha rhythm simulations, the estimation errors measured as ROC performance do not surpass 2% in our HIGGS inverse solution and reach 20% in state-of-the-art methods. Macaque simultaneous EEG/ECoG recordings provide experimental confirmation for our results with 1/3 times larger congruence according to Riemannian distances than state-of-the-art methods.
Novel Zn metal–organic framework with the thiazole sites for fast and efficient removal of heavy metal ions from water
Authors: Karbalaee Hosseini Akram , Tadjarodi Azadeh 
Published: July 2023

AbstractPollution of water by heavy metal ions such as Pb2+ and Hg2+ is considered as an important issue, because of the potential toxic effects these ions impose on environmental ecosystems and human health. A new Zn-based metal–organic framework, [Zn2(DPTTZ) (OBA)2] (IUST-2), was synthesized through a solvothermal method by the reaction of 2, 5-di (4- pyridyl) thiazolo [5, 4-d] thiazole ligand (DPTTZ), the “V-shape” 4,4'-oxybis (benzoic acid) ligand (OBA) and zinc nitrate (Zn(NO3)2·6H2O). This novel MOF has been characterized by several analysis techniques such as fourier transform infrared spectroscopy (FT-IR), elemental analysis (EA), powder x-ray diffraction (PXRD), thermogravimetry analysis (TGA), differential thermal analysis (DTA), field emission scanning electron microscopy (FE-SEM), Brunauer–Emmett–Teller (BET) surface area analysis and single-crystal X-ray diffraction (SXRD). This 3D MOF was tested for removing Pb2+ and Hg2+ ions from water. The factors that were investigated on the elimination of Pb2+ and Hg2+ ions were of pH, adsorption time, and the effect of initial ions concentration. According to the results, this particular Zn-MOF had significant performance in eliminating Pb2+ and Hg2+ ions from water with a removal efficiency of more than 97% and 87% within 3 min, respectively.
Efficient machine learning of solute segregation energy based on physics-informed features
Authors: Ma Zongyi , Pan Zhiliang 
Published: July 2023

AbstractMachine learning models solute segregation energy based on appropriate features of segregation sites. Lumping many features together can give a decent accuracy but may suffer the curse of dimensionality. Here, we modeled the segregation energy with efficient machine learning using physics-informed features identified based on solid physical understanding. The features outperform the many features used in the literature work and the spectral neighbor analysis potential features by giving the best balance between accuracy and feature dimension, with the extent depending on machine learning algorithms and alloy systems. The excellence is attributed to the strong relevance to segregation energies and the mutual independence ensured by physics. In addition, the physics-informed features contain much less redundant information originating from the energy-only-concerned calculations in equilibrium states. This work showcases the merit of integrating physics in machine learning from the perspective of feature identification other than that of physics-informed machine learning algorithms.
Establishing and testing a robot-based platform to enable the automated production of nanoparticles in a flexible and modular way
Authors: Dembski Sofia , Schwarz Thomas , Oppmann Maximilian , Bandesha Shahbaz Tareq , Schmid Jörn , Wenderoth Sarah , Mandel Karl , Hansmann Jan 
Published: July 2023

AbstractRobotic systems facilitate relatively simple human–robot interaction for non-robot experts, providing the flexibility to implement different processes. In this context, shorter process times, as well as an increased product and process quality could be achieved. Robots short time-consuming processes, take over ergonomically unfavorable tasks and work efficiently all the time. In addition, flexible production is possible while maintaining or even increasing safety. This study describes the successful development of a dual-arm robot-based modular infrastructure and the establishment of an automated process for the reproducible production of nanoparticles. As proof of concept, a manual synthesis protocol for silica nanoparticle preparation with a diameter of about 200 nm as building blocks for photonic crystals was translated into a fully automated process. All devices and components of the automated system were optimized and adapted according to the synthesis requirements. To demonstrate the benefit of the automated nanoparticle production, manual (synthesis done by lab technicians) and automated syntheses were benchmarked. To this end, different processing parameters (time of synthesis procedure, accuracy of dosage etc.) and the properties of the produced nanoparticles were compared. We demonstrate that the use of the robot not only increased the synthesis accuracy and reproducibility but reduced the personnel time and costs up to 75%.