bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-temperature experiments to ease analysis of heterogeneous binder solutions by surface plasmon resonance biosensing
Authors: Gaudreault Jimmy , Durocher Yves , Henry Olivier , De Crescenzo Gregory 
Published: August 2022

AbstractSurface Plasmon Resonance (SPR) biosensing is a well-established tool for the investigation of binding kinetics between a soluble species and an immobilized (bio)molecule. While robust and accurate data analysis techniques are readily available for single species, methods to exploit data collected with a solution containing multiple interactants are scarce. In a previous study, our group proposed two data analysis algorithms for (1) the precise and reliable identification of the kinetic parameters of N interactants present at different ratios in N mixtures and (2) the estimation of the composition of a given mixture, assuming that the kinetic parameters and the total concentration of all interactants are known. Here, we extend the first algorithm by reducing the number of necessary mixtures. This is achieved by conducting experiments at different temperatures. Through the Van’t Hoff and Eyring equations, identifying the kinetic and thermodynamic parameters of N binders becomes possible with M mixtures with M comprised between 2 and N and at least N/M temperatures. The second algorithm is improved by adding the total analyte concentration as a supplementary variable to be identified in an optimization routine. We validated our analysis framework experimentally with a system consisting of mixtures of low molecular weight drugs, each competing to bind to an immobilized protein. We believe that the analysis of mixtures and composition estimation could pave the way for SPR biosensing to become a bioprocess monitoring tool, on top of expanding its already substantial role in drug discovery and development.
Emotional profiling and cognitive networks unravel how mainstream and alternative press framed AstraZeneca, Pfizer and COVID-19 vaccination campaigns
Authors: Semeraro Alfonso , Vilella Salvatore , Ruffo Giancarlo , Stella Massimo 
Published: August 2022

AbstractCOVID-19 vaccines have been largely debated by the press. To understand how mainstream and alternative media debated vaccines, we introduce a paradigm reconstructing time-evolving narrative frames via cognitive networks and natural language processing. We study Italian news articles massively re-shared on Facebook/Twitter (up to 5 million times), covering 5745 vaccine-related news from 17 news outlets over 8 months. We find consistently high trust/anticipation and low disgust in the way mainstream sources framed “vaccine/vaccino”. These emotions were crucially missing in alternative outlets. News titles from alternative sources framed “AstraZeneca” with sadness, absent in mainstream titles. Initially, mainstream news linked mostly “Pfizer” with side effects (e.g. “allergy”, “reaction”, “fever”). With the temporary suspension of “AstraZeneca”, negative associations shifted: Mainstream titles prominently linked “AstraZeneca” with side effects, while “Pfizer” underwent a positive valence shift, linked to its higher efficacy. Simultaneously, thrombosis and fearful conceptual associations entered the frame of vaccines, while death changed context, i.e. rather than hopefully preventing deaths, vaccines could be reported as potential causes of death, increasing fear. Our findings expose crucial aspects of the emotional narratives around COVID-19 vaccines adopted by the press, highlighting the need to understand how alternative and mainstream media report vaccination news.
A study of degradation mechanisms in PVDF-based photovoltaic backsheets
Authors: Uličná Soňa , Owen-Bellini Michael , Moffitt Stephanie L. , Sinha Archana , Tracy Jared , Roy-Choudhury Kaushik , Miller David C. , Hacke Peter , Schelhas Laura T. 
Published: August 2022

AbstractCommercial backsheets based on polyvinylidene fluoride (PVDF) can experience premature field failures in the form of outer layer cracking. This work seeks to provide a better understanding of the changes in material properties that lead to crack formation and find appropriate accelerated tests to replicate them. The PVDF-based backsheet outer layer can have a different structure and composition, and is often blended with a poly(methyl methacrylate) (PMMA) polymer. We observed depletion of PMMA upon aging with sequential (MAST) and combined (C-AST) accelerated stress testing. In field-aged samples from Arizona and India, where PVDF crystallizes in its predominant α-phase, the degree of crystallinity greatly increased. MAST and C-AST protocols were, to some extent, able to replicate the increase in crystallinity seen in PVDF after ~ 7 years in the field, but no single-stress test condition (UV, damp heat, thermal cycling) resulted in significant changes in the material properties. The MAST regimen used here was too extreme to produce realistic degradation, but the test was useful in discovering weaknesses of the particular PVDF-based outer layer structure studied. No excessive β-phase formation was observed after aging with any test condition; however, the presence of β-phase was identified locally by Fourier transform infrared spectroscopy (FTIR). We conclude that both MAST and C-AST are relevant tests for screening outdoor failure mechanisms in PVDF backsheets, as they were successful in producing material degradation that led to cracking.
Basin-scale multi-decadal analysis of hydraulic fracturing and seismicity in western Canada shows non-recurrence of induced runaway fault rupture
Authors: Rodríguez-Pradilla Germán , Eaton David W. , Verdon James P. 
Published: August 2022

AbstractHydraulic fracturing (HF) is a reservoir stimulation technique that has been widely deployed in recent years to increase the productivity of light oil and/or natural gas from organic-rich, low-permeability formations. Although the process of fracturing a rock typically results in microseismic events of magnitude < 0, many cases of felt seismic events (typically magnitude 3.0 or larger) have also been reported. In the Western Canada Sedimentary Basin (WCSB), where more than 40,000 wells have been drilled and hydraulically fractured in the past two decades, the occurrence of HF-induced events has surged in some areas. Yet, many other areas of the WCSB have not experienced a significant increase in induced seismicity, despite a sharp increase in both the number of HF wells and the volumes of injected fluid. The relationship between injected volume and induced magnitudes can be quantified using the seismic efficiency ratio (SEFF), which describes the ratio between the net seismic moment release and the injected fluid volume. Runaway rupture, in which the fault rupture is dominated by the release of accumulated tectonic stresses, is inferred to be marked by an abrupt increase in SEFFto a value > 0.5. Most previous studies of induced earthquakes have been limited to a single operation and/or seismicity sequence. To better understand the observed variability of the seismic response to HF stimulations at a basin scale, we compiled HF data for all unconventional wells hydraulic fractured in the WCSB between 2000 and 2020, together with the seismicity reported during the same period. We grouped these observations into bins measuring 0.2° in longitude and 0.1° in latitude, or approximately 13 by 11 km. We identified 14 areas where large magnitude events resulted in high SEFFvalues, implying runaway rupture had taken place. However, we find that in these areas, sustained fluid injection did not lead to persistent high SEFFvalues. Instead, as injection continued, SEFFvalues returned to values less than 0.5. This suggests that there is a limited budget of tectonic strain energy available to generate runaway rupture events: once this is released, event magnitudes decrease even if high volume injection persists.
Influence of capillary tube length on the performance of domestic refrigerator with eco-friendly refrigerant R152a
Authors: Baskaran A. , Manikandan N. , Jule LetaTesfaye , Nagaprasad N. , Saka Abel , Badassa Bayissa , Ramaswamy Krishnaraj , Seenivasan Venkatesh 
Published: August 2022

AbstractThe household heating and cooling system often use the capillary device. The use of the helical capillary eliminates the need for lightweight refrigeration devices in the system. Capillary pressure is noticeably affected by the capillary geometric parameters, such as length, mean diameter, and pitch. This paper is concerned with the effects of the capillary length on the performance of the system. Three separate length capillary tubes were used in the experiment. The data on R152a were studied under various conditions to assess the impact of varying the length. Maximum COP is obtained at an evaporator temperature of − 12 °C and capillary length of 3.65 m. The result is drawn that the system performance enhances when the capillary length is improved to 3.65 m when compared to 3.35 m and 3.96 m. As a result, as the capillary length increases up to a specific amount, the system's performance improves. The findings from the experiment were compared with those from the computational fluid dynamics (CFD) analysis.
Heat and mass flux through a Reiner–Rivlin nanofluid flow past a spinning stretching disc: Cattaneo–Christov model
Authors: Moatimid Galal M. , Mohamed Mona A. A. , Elagamy Khaled 
Published: August 2022

AbstractThe current work scrutinizes a non-Newtonian nanofluid free convective flow induced by a rotating stretchable disc. The examination surveys the Stefan blowing and Cattaneo–Christov mass and heat fluxes, as a precise illustrative model. The innovative aspects of the ongoing project include the analysis of the border sheet nanofluid flow near a revolving disc through thermophoresis, Reiner–Rivlin prototype features, and random nanoparticle motion. The Reiner–Rivlin non-Newtonian model is considered together with the effect of an unvarying axial magnetic strength. The constitutive formulae of a Reiner–Rivlin liquid have been reproduced in the cylindrical coordinates. Through implementing the applicable relationship transformations, the controlling partial differential equations are transferred to ordinary differential equations (ODE). This procedure yields a group of coupled nonlinear ordinary differential equations in relation to speed, heat, and nanoparticle concentration profiles that are impacted by several physical characteristics. These equations are analyzed by using the homotopy perturbation method (HPM). Due to the analytical solution given by HPM, the current work enables us to take the infinity of the layer as a parameter of the problem and discuss its variation in the obtained distributions. Consequently, a physical significant graphical visualization of the data is emphasized. The rates of mass and temperature transmission are examined to understand if any of the relevant parameters may improve these rates. Additionally, the Stefan blowing causes extra particles diffusion, which enhances heat transfer and raises the nanoparticles concentration and could be useful in some medical therapies. Furthermore, the stretching of the rotating disc is concluded, which improves the fluid heat transfer.
Identification and construction of a multi-epitopes vaccine design against Klebsiella aerogenes: molecular modeling study
Authors: Alzarea Sami I. 
Published: August 2022

AbstractA rapid rise in antibiotic resistance by bacterial pathogens is due to these pathogens adaptation to the changing environmental conditions. Antibiotic resistance infections can be reduced by a number of ways such as development of safe and effective vaccine. Klebsiella aerogene is a gram-negative, rod-shaped bacterium resistant to a variety of antibiotics and no commercial vaccine is available against the pathogen. Identifying antigens that can be easily evaluated experimentally would be crucial to successfully vaccine development. Reverse vaccinology (RV) was used to identify vaccine candidates based on complete pathogen proteomic information. The fully sequenced proteomes include 44,115 total proteins of which 43,316 are redundant and 799 are non-redundant. Subcellular localization showed that only 1 protein in extracellular matrix, 7 were found in outer-membrane proteins, and 27 in the periplasm space. A total of 3 proteins were found virulent. Next in the B-cell-derived T-cell epitopes mapping phase, the 3 proteins (Fe2+− enterobactin, ABC transporter substrate-binding protein, and fimbriae biogenesis outer membrane usher protein) were tested positive for antigenicity, toxicity, and solubility. GPGPG linkers were used to prepare a vaccine construct composed of 7 epitopes and an adjuvant of toxin B subunit (CTBS). Molecular docking of vaccine construct with major histocompatibility-I (MHC-I), major histocompatibility-II (MHC-II), and Toll-like receptor 4 (TLR4) revealed vaccine robust interactions and stable binding pose to the receptors. By using molecular dynamics simulations, the vaccine-receptors complexes unveiled stable dynamics and uniform root mean square deviation (rmsd). Further, binding energies of complex were computed that again depicted strong intermolecular bindings and formation of stable conformation.
Influence of stress distribution in coal seams of non-uniform extremely thick key stratum and disaster-causing mechanisms
Authors: Ning Shan , Zhu Weibing , Xie Jianlin , Song Shikang , Wang Xiaozhen , Yu Dan , Lou Jinfu , Xu Jialin 
Published: August 2022

AbstractThis paper analyzes the influence of the overlying extremely thick primary key stratum on the strong mine pressure hazard at the large mining face in Gaojiapu coal mine. The analysis of the distribution characteristics of the primary key stratum in the Gaojiapu coal mine reveals the bow-shaped structural characteristics of the overlying thick primary key stratum. An elastodynamic model was developed using the variational method to calculate and analyze the influence of the movement of the primary key stratum on the stress and energy of the underlying weak rock. The results show that the arch structure of the overlying extremely thick primary key stratum can significantly affect the distribution pattern of stress and strain energy in the coal body, and the stress and strain energy in the coal body are transferred to the middle of the coal column, and the middle region of the coal column enters a high stress state. These results suggest that the change in thickness of the overlying primary key stratum at Gaojiapu in the coal column area is a major factor in the frequent occurrence of impact ground pressure events at the mine. This study explains the causes of frequent impact ground pressure in the lower coal rock mass of the extremely thick primary key stratum, and provides a reference for the prevention and control of impact hazards in the extremely thick primary key stratum.
Development of a portable toolkit to diagnose coral thermal stress
Authors: Meng Zhuolun , Williams Amanda , Liau Pinky , Stephens Timothy G. , Drury Crawford , Chiles Eric N. , Su Xiaoyang , Javanmard Mehdi , Bhattacharya Debashish 
Published: August 2022

AbstractCoral bleaching, precipitated by the expulsion of the algal symbionts that provide colonies with fixed carbon is a global threat to reef survival. To protect corals from anthropogenic stress, portable tools are needed to detect and diagnose stress syndromes and assess population health prior to extensive bleaching. Here, medical grade Urinalysis strips, used to detect an array of disease markers in humans, were tested on the lab stressed Hawaiian coral species, Montipora capitata (stress resistant) and Pocillopora acuta (stress sensitive), as well as samples from nature that also included Porites compressa. Of the 10 diagnostic reagent tests on these strips, two appear most applicable to corals: ketone and leukocytes. The test strip results from M. capitata were explored using existing transcriptomic data from the same samples and provided evidence of the stress syndromes detected by the strips. We designed a 3D printed smartphone holder and image processing software for field analysis of test strips (TestStripDX) and devised a simple strategy to generate color scores for corals (reflecting extent of bleaching) using a smartphone camera (CoralDX). Our approaches provide field deployable methods, that can be improved in the future (e.g., coral-specific stress test strips) to assess reef health using inexpensive tools and freely available software.
Investigation of novel passive methods of generation of swirl flow in supersonic separators by the computational fluid dynamics modeling
Authors: Shoghl Sina Nabati , Naderifar Abbas , Farhadi Fatola , Pazuki Gholamreza 
Published: August 2022

AbstractIn this paper, three passive methods for the generation of swirl flow in the supersonic separator (3S) were investigated, and their structures were optimized by computational fluid dynamics (CFD) modeling. The influence of the structural and operational parameters on the dew point depression, phase envelope diagram, rate of natural gas liquid (NGL) recovery, and separation efficiency have also been evaluated. The collection efficiency was significantly improved for the nozzle equipped with the passive swirler compared with the simple nozzle. The selection of passive swirler type played a crucial role in the natural gas liquefaction and separation. The side injected swirler, and serpentine swirler showed the most significant improvement in separation efficiency than the U-turn swirler. For the side injected swirler at the optimum injection angle, the maximum collection efficiency was about 89% at the pressure loss ratio (PLR) of 0.2. Besides, the simulation results demonstrated that for the serpentine 3S, with the increase in serpentine twist number, the highest improvement on the collection efficiency of the investigated nozzle was obtained. In addition, it was observed that, when the convergent section profile was designed according to the Witoszynski line-type, a larger refrigeration zone was obtained than other considered profiles.
Design and development of an open-source framework for citizen-centric environmental monitoring and data analysis
Authors: Mahajan Sachit 
Published: August 2022

AbstractCities around the world are struggling with environmental pollution. The conventional monitoring approaches are not effective for undertaking large-scale environmental monitoring due to logistical and cost-related issues. The availability of low-cost and low-power Internet of Things (IoT) devices has proved to be an effective alternative to monitoring the environment. Such systems have opened up environment monitoring opportunities to citizens while simultaneously confronting them with challenges related to sensor accuracy and the accumulation of large data sets. Analyzing and interpreting sensor data itself is a formidable task that requires extensive computational resources and expertise. To address this challenge, a social, open-source, and citizen-centric IoT (Soc-IoT) framework is presented, which combines a real-time environmental sensing device with an intuitive data analysis and visualization application. Soc-IoT has two main components: (1) CoSense Unit—a resource-efficient, portable and modular device designed and evaluated for indoor and outdoor environmental monitoring, and (2) exploreR—an intuitive cross-platform data analysis and visualization application that offers a comprehensive set of tools for systematic analysis of sensor data without the need for coding. Developed as a proof-of-concept framework to monitor the environment at scale, Soc-IoT aims to promote environmental resilience and open innovation by lowering technological barriers.
Critical hydraulic gradient and fine particle migration of sand under upward seepage flow
Authors: Wang Bo , Chen Long-wei , Niu Zhen 
Published: August 2022

AbstractIn order to study the mechanism of seepage-induced geotechnical damage and characteristics of fine particle migration in sandy soil, a one-dimensional upward seepage test device was used and a series of upward seepage flow tests of sand were conducted. In these experiments, the permeability, fine particle migration and redistribution under different hydraulic gradients were investigated. The results show that local hydraulic gradient in the sand sample is larger than the critical hydraulic gradient calculated by the Terzaghi’s Equation. The seepage force will induce the fine soil particles to migrate along water flow direction and then cause the redistribution and reconsolidation of sand particles. Under the test condition, fine particles (< 0.075 mm) and fine sand particles (0.075–0.25 mm) dominate in the lost soil particles. Soil particles larger than 0.6 mm are hardly to lose.
Cloud and snow detection of remote sensing images based on improved Unet3+
Authors: Yin Meijie , Wang Peng , Ni Cui , Hao Weilong 
Published: August 2022

AbstractCloud detection is an important step in remote sensing image processing and a prerequisite for subsequent analysis and interpretation of remote sensing images. Traditional cloud detection methods are difficult to accurately detect clouds and snow with very similar features such as color and texture. In this paper, the features of cloud and snow in remote sensing images are deeply extracted, and an accurate cloud and snow detection method is proposed based on the advantages of Unet3+ network in feature fusion. Firstly, color space conversion is performed on remote sensing images, RGB images and HIS images are used as input of Unet3+ network. Resnet 50 is used to replace the Unet3+ feature extraction network to extract remote sensing image features at a deeper level, and add the Convolutional Block Attention Module in Resnet50 to improve the network’s attention to cloud and snow. Finally, the weighted cross entropy loss is constructed to solve the problem of unbalanced sample number caused by high proportion of background area in the image. The results show that the proposed method has strong adaptability and moderate computation. The mPA value, mIoU value and mPrecision value can reach 92.76%, 81.74% and 86.49%, respectively. Compared with other algorithms, the proposed method can better eliminate all kinds of interference information in remote sensing images of different landforms and accurately detect cloud and snow in images.
Deep belief rule based photovoltaic power forecasting method with interpretability
Authors: Han Peng , He Wei , Cao You , Li YingMei , Zhang YunYi 
Published: August 2022

AbstractAccurate prediction of photovoltaic (PV) output power is of great significance for reasonable scheduling and development management of power grids. In PV power generation prediction system, there are two problems: the uncertainty of PV power generation and the inexplicability of the prediction result. The belief rule base (BRB) is a rule-based modeling method and can deal with uncertain information. Moreover, the modeling process of BRB has a certain degree of interpretability. However, rule explosion and the inexplicability of the optimized model limit the modeling ability of BRB in complex systems. Thus, a PV output power prediction model is proposed based on a deep belief rule base with interpretability (DBRB-I). In the DBRB-I model, the deep BRB structure is constructed to solve the rule explosion problem, and inefficient rules are simplified by a sensitivity analysis of the rules, which reduces the complexity of the model. Moreover, to ensure that the interpretability of the model is not destroyed, a new optimization method based on the projection covariance matrix adaptation evolution strategy (P-CMA-ES) algorithm is designed. Finally, a case study of the prediction of PV output power is conducted to illustrate the effectiveness of the proposed method.