bluuebunny/crossref_metadata_2025_split huggingface dataset:
Infection-Related Ventilator-Associated Complication and Possible Ventilator-Associated Pneumonia among Mechanically Ventilated Patients of Adult Medical and Surgical Intensive Care Units
Authors: Behera Bijayini , Mahapatra Ashoka , Kunjan Pillai Jawahar Sreevihar , Jena Jayanti , Rath Jyotirmayee , Biswala Jyotirmayee , Sahoo Chandramani , Panda Rajeswari , Kanungo Madhusmita 
Published: July 2022

Abstract
Objective An observational study was conducted to evaluate (1) the incidence rates of infection-related ventilator-associated complication (IVAC) and possible ventilator-associated pneumonia (PVAP) among mechanically ventilated patients of adult medical and surgical intensive care units (ICUs) and (2) the pathogen distribution in patients with PVAP.
Materials and Methods The IVAC and PVAP rates of medical and surgical ICUs, between July 1, 2017, and June 30, 2021, per 1,000 mechanical ventilator (MV) days were calculated. The significance of difference in IVAC and PVAP rates between medical and surgical ICUs was calculated. The level of significance was set at less than 0.05.
Results MV utilization ratios of adult medical and surgical ICUs were 0.32 and 0.26, respectively (p < 0.001). About 8 and 7 episodes of IVAC and 14 and 6 episodes of PVAP were reported from adult medical and surgical ICUs, accounting for IVAC rates of 3.17 and 1.8 per 1,000 MV (p > 0.05) and PVAP rates of 2.46 and 1.59 per 1,000 MV days in medical and surgical ICUs, respectively (p > 0.05). Acinetobacter baumannii complex either singly or in combination was isolated in 11/20 PVAP cases.
Conclusion IVAC and PVAP were more in medical compared with surgical ICUs. The most common pathogen in patients with PVAP was A. baumannii complex. More studies are warranted to monitor the significance of ventilator-associated event on patient outcomes.
Molecular Zeeman interactions in NMR spectra of methyl groups
Authors: Bernatowicz P. , Szymański S. 
Published: July 2022

Methyl groups in organic solids generally behave as uniaxial quantum rotors. The existing nuclear magnetic resonance (NMR) theory appears to be complete, capable of describing even the finest details of the temperature-dependent spectra of such objects. However, the once reported temperature effects in the carbon spectra of the C13-labeled methyl group in a single crystal of acetylsalicylic acid have still not been explained. As the temperature decreases, in the quartet corresponding to the rapid motional averaging regime, the inner lines first begin to broaden, but then, they narrow again, so that at 6 K, a pattern similar to that at room temperature was observed. In the present work, these puzzling effects are explained quantitatively by invoking the molecular Zeeman (MZ) interaction. Like the spin–rotation (SR) interaction long known to occur in methyl groups, it engages the magnetic moments generated by their torsional motions. However, it has not been considered in NMR spectroscopy until now. This is a surprising situation because in the magnetic fields currently used in NMR spectroscopy, the MZ interaction is orders of magnitude stronger than the (magnetic field independent) SR effects.
La Terre, de Émile Zola, o el desentierro de un caso de traducción y censura durante el franquismo
Authors: Meseguer Cutillas Purificación 
Published: July 2022

Abstract
Through the analysis of a case of translation and censorship, this study offers a recreation of the microhistory
of La terre (1883), by Émile Zola, at the time when this foreign
French novel was imported into the Francoist literary system, focusing on the processes of reception, conditioning and
appropriation to which this work was subjected by the Franco regime in order to ensure its ideological adequacy. The study of the
two Spanish versions published during the dictatorship will show that Zola’s controversial novel went through an exercise of
self-censorship and metacensorship which aimed mainly at silencing a clear anti-religious sentiment among the French peasant
community depicted in the original text, seen as unacceptable under the catholic and agrarian society ruled by Franco.
A game theory enhanced domain adaptation network for mechanical fault diagnosis
Authors: Sun Ruixue , Liu Xiaoyang , Liu Shulin , Xiang Jiawei 
Published: July 2022

Abstract
Transfer learning technology has been successfully applied to address the domain adaptation (DA) problem in machinery fault diagnosis. However, the partial DA problem is more suitable for industrial applications, where the target data only covers a subset of the source classes, which makes it difficult to know where to transfer the target data. To overcome this problem, a novel game theory enhanced DA network (GT-DAN) is proposed in this paper. Based on different metrics, including the maximum mean discrepancy, Jensen–Shannon divergence and Wasserstein distance, three attention matrices are constructed to describe the distribution discrepancies between the source domain and the target domain. The optimal coordination between these attention matrices is achieved by a combined weighting based on game theory to generate the optimal probability weights, which can act as a guide to filter out the irrelevant source examples in DA. Two experiments show that the proposed GT-DAN is superior to existing methods in partial DA diagnosis performance.
Development of a synthetic nanoparticle vaccine presenting the HIV-1 envelope glycoprotein
Authors: Ximba Phindile , Chapman Rosamund , Meyers Ann , Margolin Emmanuel , van Diepen Michiel T , Sander Adam F , Woodward Jeremy , Moore Penny L , Williamson Anna-Lise , Rybicki Edward P 
Published: July 2022

Abstract
Two-component self-assembling virus-like particles (VLPs) are promising scaffolds for achieving high-density display of HIV-1 envelope (gp140) trimers, which can improve the induction of neutralising antibodies (NAbs). In this study gp140 was displayed on the surface of VLPs formed by the AP205 phage coat protein. The CAP256 SU gp140 antigen was selected as the patient who this virus was isolated from developed broadly neutralising antibodies (bNAbs) shortly after superinfection with this virus. The CAP256 SU envelope is also sensitive to several bNAbs and has shown enhanced reactivity for certain bNAb precursors. A fusion protein comprising the HIV-1 CAP256 SU gp140 and the SpyTag (ST) (gp140-ST) was produced in HEK293 cells, and trimers were purified to homogeneity using gel filtration. SpyCatcher (SC)-AP205 VLPs were produced in Escherichia coli and purified by ultracentrifugation. The gp140-ST trimers and the SC-AP205 VLPs were mixed in varying molar ratios to generate VLPs displaying the glycoprotein (AP205-gp140-ST particles). Dynamic light scattering, negative stain electron microscopy and 2D classification indicated that gp140-ST was successfully bound to the VLPs, although not all potential binding sites were occupied. The immunogenicity of the coupled VLPs was evaluated in a pilot study in rabbits. One group was injected four times with coupled VLPs, and the second group was primed with DNA vaccines expressing Env and a mosaic Gag, followed by modified vaccinia Ankara expressing the same antigens. The animals were then boosted twice with coupled VLPs. Encouragingly, gp140-ST displayed on SC-AP205 VLPs was an effective boost to heterologously primed rabbits, leading to induction of autologous Tier 2 neutralising antibodies in 2/5 rabbits. However, four inoculations of coupled VLPs alone failed to elicit any Tier 2 antibodies. These results demonstrate that the native-like structure of HIV-1 envelope trimers and selection of a geometrically-suitable nanoparticle scaffold to achieve a high-density display of the trimers are important considerations that could improve the effect of nanoparticle-displayed gp140.
Saponin and fluorine-modified polycation as a versatile gene delivery system
Authors: Hasanzadeh Akbar , Vahabi Amir Hossein , Hooshmand Seyyed Emad , Hosseini Elaheh Sadat , Azar Behjat Kheiri Yeghaneh , Kiani Jafar , Saeedi Sara , Shahbazi Ali , Rudra Arnab , Hamblin Michael R , Karimi Mahdi 
Published: July 2022

Abstract
Despite the development of many novel carriers for the delivery of various types of genetic material, the lack of a delivery system with high efficiency and low cytotoxicity is a major bottleneck. Herein, low molecular weight polyethylenimine (PEI1.8k) was functionalized with saponin residues using phenylboronic acid (PBA) as an ATP-responsive cross-linker, and a fluorinated side chain to construct PEI-PBA-SAP-F polycation as a highly efficient delivery vector. This vehicle could transfect small plasmid DNA (∼3 kb) with outstanding efficiency into various cells, including HEK 293T, NIH3T3, A549, PC12, MCF7 and HT-29, as well as robust transfection of a large plasmid (∼9 kb) into HEK 293T cells. The carrier indicated good transfection efficacy even at high concentration of serum and low doses of plasmid. The use of green fluorescent protein (GFP) knock-out analysis demonstrated transfection of different types of CRISPR/Cas9 complexes (Cas9/sgRNA ribonucleoproteins RNP, plasmid encoding Cas9 plus sgRNA targeting GFP, Cas9 expression plasmid plus in vitro-prepared sgRNA). In summary, we report an effective PEI-PBA-SAP-F gene carrier with the appropriate lipophilic/cationic balance for biomedical applications.
Experimental and simulation study of a capacitively coupled radiofrequency plasma with a structured electrode
Authors: Ďurian Ján , Hartmann Peter , Matejčík Štefan , Gibson Andrew R , Donkó Zoltán 
Published: July 2022

Abstract
A low-pressure capacitively coupled radiofrequency (RF) helium discharge with a structured electrode is investigated experimentally and via kinetic simulations. In the experiment, phase resolved optical emission spectroscopy provides information about the excitation dynamics by high energy electrons, with high spatial and nanosecond temporal resolution within the RF (13.56 MHz) period. The numerical studies are based on a newly developed 2d3v particle-in-cell/Monte Carlo collisions code carried out on graphics processing units. The two approaches give consistent results for the penetration of the plasma into the trench situated in one of the electrodes and the particular electron dynamics resulting from the presence of the structured electrode. In addition, the fluxes of He+ ions and vacuum ultraviolet photons incident on the different surfaces in and around the trench structure are studied. These are discussed with respect to the homogeneous treatment of complex structures, relevant for advanced surface modification and disinfection processes.
Polymerization of nitrogen in two theoretically predicted high-energy compounds ScN6 and ScN7 under modest pressure
Authors: Guo Yanhui , Wei Shuli , Liu Zhipeng , Sun Haiyang , Yin Guowei , Chen Shiju , Yu Ziyue , Chang Qiang , Sun Yuping 
Published: July 2022

Abstract
Materials under high pressure usually exhibit unique chemical and physical properties. Polynitrogen compounds have received widespread attention as potential high energy density materials. This paper uses CALYPSO crystal structure prediction method to study the structures of ScN6 and ScN7 in 0–100 GPa. Theoretical calculations show that ScN6 is thermodynamically stable above 80 GPa, while ScN7 is thermodynamically stable from 30 GPa to 90 GPa. Furthermore, ScN7 is metastable under ambient conditions, demonstrating that it can be quenched to ambient conditions after high pressure synthesis. The P

1

¯

-ScN6 is a three-dimensional extended fold multi-nitrogen network, and the P

1

¯

-ScN7 contains a five-membered ring and a curved N4 molecular unit. Both P

1

¯

-ScN6 and P

1

¯

-ScN7 contain a lot of N–N single bonds and N=N double bonds. The energy densities of P

1

¯

-ScN6 and P

1

¯

-ScN7 are 3.97 kJ g−1 and 3.12 kJ g−1, respectively. The detonation velocity and detonation pressure of the P

1

¯

-ScN6 phase and P

1

¯

-ScN7 phase are also higher than that of TNT. Excellent energy storage properties and detonation performance show that they can be used as potential high-energy materials. These results opened up a new way for the synthesis of nitrogen-rich compounds.
Cosmological analysis of three-dimensional BOSS galaxy clustering and Planck CMB lensing cross correlations via Lagrangian perturbation theory
Authors: Chen Shi-Fan , White Martin , DeRose Joseph , Kokron Nickolas 
Published: July 2022

AbstractWe present a formalism for jointly fitting pre- and post-reconstruction redshift-space clustering (RSD) and baryon acoustic oscillations (BAO) plus gravitational lensing (of the CMB) that works directly with the observed 2-point statistics. The formalism is based upon (effective) Lagrangian perturbation theory and a Lagrangian bias expansion, which models RSD, BAO and galaxy-lensing cross correlations within a consistent dynamical framework. As an example we present an analysis of clustering measured by the Baryon Oscillation Spectroscopic Survey in combination with CMB lensing measured by Planck. The post-reconstruction BAO strongly constrains the distance-redshift relation, the full-shape redshift-space clustering constrains the matter density and growth rate, and CMB lensing constrains the clustering amplitude. Using only the redshift space data we obtain Ωm= 0.303 ± 0.008,H0= 69.21 ± 0.78 andσ8= 0.743 ± 0.043. The addition of lensing information, even when restricted to the Northern Galactic Cap, improves constraints to Ωm= 0.303 ± 0.008,H0= 69.21 ± 0.77 andσ8= 0.707 ± 0.035, in tension with CMB and cosmic shear constraints. The combination of ΩmandH0are consistent with Planck, though their constraints derive mostly from redshift-space clustering. The lowσ8value are driven by cross correlations with CMB lensing in the low redshift bin (z≃ 0.38) and at large angular scales, which show a 20% deficit compared to expectations from galaxy clustering alone. We conduct several systematics tests on the data and find none that could fully explain these tensions.
Multi-scale discriminative regions analysis in FDG-PET imaging for early diagnosis of Alzheimer’s disease
Authors: Zhang Jin , He Xiaohai , Qing Linbo , Xu Yining , Liu Yan , Chen Honggang 
Published: July 2022

Abstract

Objective. Alzheimer’s disease (AD) is a degenerative brain disorder, one of the main causes of death in elderly people, so early diagnosis of AD is vital to prompt access to medication and medical care. Fluorodeoxyglucose positron emission tomography (FDG-PET) proves to be effective to help understand neurological changes via measuring glucose uptake. Our aim is to explore information-rich regions of FDG-PET imaging, which enhance the accuracy and interpretability of AD-related diagnosis. Approach. We develop a novel method for early diagnosis of AD based on multi-scale discriminative regions in FDG-PET imaging, which considers the diagnosis interpretability. Specifically, a multi-scale region localization module is discussed to automatically identify disease-related discriminative regions in full-volume FDG-PET images in an unsupervised manner, upon which a confidence score is designed to evaluate the prioritization of regions according to the density distribution of anomalies. Then, the proposed multi-scale region classification module adaptively fuses multi-scale region representations and makes decision fusion, which not only reduces useless information but also offers complementary information. Most of previous methods concentrate on discriminating AD from cognitively normal (CN), while mild cognitive impairment, a transitional state, facilitates early diagnosis. Therefore, our method is further applied to multiple AD-related diagnosis tasks, not limited to AD vs. CN. Main results. Experimental results on the Alzheimer’s Disease Neuroimaging Initiative dataset show that the proposed method achieves superior performance over state-of-the-art FDG-PET-based approaches. Besides, some cerebral cortices highlighted by extracted regions cohere with medical research, further demonstrating the superiority. Significance. This work offers an effective method to achieve AD diagnosis and detect disease-affected regions in FDG-PET imaging. Our results could be beneficial for providing an additional opinion on the clinical diagnosis.
Enhanced diagnostics of radiating relativistic singularities and BISER by nonlinear post-compression of optical probe pulse
Authors: Kotov A.V. , Esirkepov T.Zh. , Soloviev A.A. , Sagisaka A. , Ogura K. , Bierwage A. , Kando M. , Kiriyama H. , Starodubtsev M.V. , Khazanov E.A. , Mironov S.Yu. , Pirozhkov A.S. 
Published: July 2022

Abstract
The enhancement of the resolution of pump-probe optical diagnostics for ultrafast processes by compressing the probe pulse duration using the CafCA approach [1] is considered on an example of the BISER soft-X-ray generation [2] with the J-KAREN-P laser [3].
Monitoring of Black Pepper Growth at Different Elevation using Ground Data and NDVI Time Series
Authors: Kamsan Siti Zul Lailee , Zainol Wan Nor Zanariah 
Published: July 2022

Abstract
Implementation of remote sensing in agriculture helps to enhance crop growth monitoring especially during the Covid-19 pandemic. To enhance black pepper growth condition, a study was conducted at two study sites in Bintulu, Sarawak. Hence, this study aims (i) to construct a black pepper growth monitoring at different levels of elevation in Suka Farm (SF) and Taime Farm (TF); and (ii) to integrate limited ground data and NDVI time series from Landsat 8OLI for black pepper growth monitoring. Elevation maps were generated using Natural Neighbor (NN) based on the ground data analysed using ArcGIS 10.4 Software. Three elevation levels were classified into the lower, middle, and upper levels. Observational ground data and NDVI time series of Landsat 8 OLI were calculated using SAS 9.4 software. All parameters then correlating with the elevation levels using Pearson Correlation Coefficient. Optimum growth of black pepper growth in SF and TF was identified at an elevation range between 39m–50m. The NDVI time series also indicated equivalent results as the ground data. This study proposed that the elevation of an area gives a significant impact on black pepper growth. Besides, the NDVI time series of Landsat 8 OLI was feasible for monitoring black pepper growth.
A review of GIS spatiotemporal analysis and web-based mapping for COVID-19
Authors: Isnan Sarah , Shariff Abdul Rashid Mohamed 
Published: July 2022

Abstract
The outbreak of diseases such as the pandemic Covid-19 is a critical problem that has emerged throughout the world. The outbreak is believed to be originated from Wuhan, China in December 2019. In February 2020, World Health Organization declared the name of the virus as Covid-19 and it has become a global pandemic in March 2020. This paper aims to review articles related to the application of GIS spatiotemporal analysis and web-based mapping for the Covid-19 pandemic. GIS spatiotemporal analysis is used to track the pattern of the Covid-19 and web-based mapping-based mapping is used to visualize the Covid-19 cases. This proves that GIS is a helpful tool to determine and track the transmission pattern and visualize the Covid-19 cases so that early mitigation can be done to combat the virus
Accuracy assessment of open-source global digital elevation models (GDEMs) with global navigation satellite system (GNSS) levelling
Authors: Rahman Mohd Faizuddin Abd , Din Ami Hassan Md , Hamid Amalina Izzati Abd , Alihan Nor Surayatul Atikah , Yazid Nornajihah Mohd , Ansar Andi Mohd Hairy , Pa’suya Muhammad Faiz , Yamen Siti Nurshahira Mohd , Khalid Nor Fadilla , Junid Muhammad Arif Husaini 
Published: July 2022

Abstract
Shuttle Radar Topography Mission (SRTM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER ), Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010), Advanced Land Observing Satellite World-3D (ALOSW3D), and TerraSAR-X Digital Elevation Measurement (TanDEM-X) are open-source Digital Elevation Model (DEM) datasets for environmental modelling and studies. The spatial resolution and vertical accuracy of DEM data sources play a significant role, particularly in dealing with land inundation, periodic flooding, and coastal erosion. In this study, the comparison between orthometric height, H from Global Navigation Satellite System (GNSS) observation, and DEM is performed to evaluate the accuracy of each DEM in terms of their Root Mean Square Error (RMSE) and correlation coefficient, R2 for monitoring the coastline. The result has indicated that TanDEM-X shows the smallest RMSE of 2.574 m compared to SRTM30, SRTM90, ASTER, GMTED10, and ALOSW3D with RMSE of 2.968 m, 3.006 m, 3.217 m, 2.975 m, and 2.876 m respectively. Furthermore, TanDEM-X illustrates the largest correlation coefficients, R2 of 0.959 m, compared to SRTM30, SRTM90, ASTER, GMTED10, and ALOSW3D at 0.891 m, 0.899 m, 0.590 m, 0.888 m 0.913 m respectively. Hence, the result has indicated that TanDEM-X is the best option among all DEMs for any topographic applications.
Multi-temporal satellite image correction based on CNN features and adaptive contrast enhancement
Authors: Saberi Zamfirdaus , Hashim Noramiza , Ali Aziah , Abdullah Junaidi , Isa Wan Noorshahida Mohd , Embi Zarina Che 
Published: July 2022

Abstract
In recent years, identifying changes in multi-temporal images in terms of land use and land cover has been significant in a variety of applications, including urban planning. Due to weather and environmental effects, optical remote sensing has limitations in obtaining images where the image quality may be degraded. It’s because the images being registered are taken at various times, viewpoints, and types of sensors. In this article, the pre-processing methods, which include radiometric correction and geometric correction, are introduced to enhance the quality of satellite images and identify correct spatial alignment. For radiometric correction, adaptive contrast enhancement is done by combining histogram- and non-linear transfer function-based approaches in CIELAB color space. A comparison study is done to see how the new method compared to other methods. For geometric correction, the features from two images are extracted using Convolutional Neural Network to match and align them. The introduced approach for radiometric correction gave the best average rank of BRISQUE scores and RMSE of contrast scores, and the geometric correction can align two images together with an average accuracy of improvement of 91.78 percent. The findings of this research will provide the preliminary step for any change detection activities.
Deforestation analysis using Random Forest and interactive supervised classification approach
Authors: Yogender  , Guliyeva Sona , Alaksarov Elman , Singh Arunima , Kushwaha S.K.P. 
Published: July 2022

Abstract
The increasing demand for forest resources leads to overexploitation to a greater extent, raising the alarm for the environmental consequences. The excessive use of forest resources results in deforestation, which needs to be addressed for maintaining the natural ecosystem balance. This research focuses on the deforestation analysis of a territory in the Tartar district in Azerbaijan. The changes in the forest area have been analyzed using the high-resolution Azersky satellite datasets for the three alternative years, 2017, 2019, and 2021. Two classification approaches, namely Random Forest (RF) and NDVI- based interactive supervised classification, were implemented for this purpose. The statistical analysis of the results indicates the gradual decrease in the forest area from the year 2017 to the year 2021, which has been evaluated by visual interpretation through the change maps of the forest area. From RF classification results, it has been observed that there has been an overall decrease of 9.5% from 2017 to 2021. Also, the NDVI-based interactive supervised classification approach indicates an overall deforestation rate of 4.79% from 2017 to 2021. This work shows that the forest area in the study region has considerably reduced over the years, and there is a need to closely monitor deforestation in the considered study area.