bluuebunny/crossref_metadata_2025_split huggingface dataset:
Auto-Processing of Filtered Rayleigh Scattering Images Including Mie and Background Scattering Contributions
Authors: Powers Sean , Byun Gwibo , Lowe K. Todd 
Published: December 2022

Abstract
A comprehensive and efficient post-processing framework is presented for obtaining aerodynamics measurements of three-component velocity, static temperature, and static density using filtered Rayleigh scattering (FRS). This framework contains several steps which culminate in an optimization process for iterative minimization of errors between the experimentally measured FRS spectra and spectra generated by models, providing an inverse solution to determine the local measurement values. Robustness is gained using a multi-level processing technique for successive spatial resolution refinement of measurements. An assessment of the speed and spectral outputs of several published laser Rayleigh scattering models is provided and resulted in the recommendation that Doll's analytic Tenti-S6 model be adopted as the best trade-off in speed and consistency. A distinguishing feature of the approach is the inclusion of methods for interpreting FRS spectra that contain significant scattering contributions from particles and surfaces.
The performance of the methods has been quantified for uncertainties using Monte Carlo simulations, while planar results from two experiments are presented for validation and demonstration of robustness, respectively: a benchtop free jet and the exhaust plume of a miniature turbojet engine. Monte Carlo simulations show that at a signal-to-noise ratio (SNR) of 30 dB the approximate uncertainty in scattering angle is 0.3°, 2.5 K for static temperature, 1.5 m/s for velocity, 0.01 kg/m3 for static density, and 0.01 for both Mie and background scattering intensity ratios. The free jet results show differences of 1.5 K for total temperature, 1 m/s for axial velocity, 0.005 kg/m3 for total density, and 200 Pa for total pressure when compared to probe data. All results fall within the 95% confidence bounds of the a priori uncertainties. The small turbojet (JetCat) results are included to show that the processor is robust and accurate even when used with non-ideal data sets from realistic applications such as vitiated exhausts. The JetCat results show differences of 20 K for total temperature, 8 m/s for axial velocity, 0.01 kg/m3 for total density, and 500 Pa for total pressure when compared to probe data. All results except near the edge of the jet plume fall within the 95% confidence bounds of the a priori uncertainties.
Evaluation of the antiviral effect of exogenous human IFN-lambda mRNA against influenza virus in vitro
Authors: Plotnikova Marina A. , Klotchenko Sergey A. , Lozhkov Alexey A. , Dobrovolskaya Olga A. , Romanovskaya-Romanko Ekaterina A. , Vysochinskaya Vera V. , Vasin Andrey V. 
Published: December 2022

Abstract
Objective: Despite the fact that exogenous mRNA has great prospects for the development of therapeutic medicine, its use is still limited. As the immediate protein precursor, positive-stranded mRNA may represent a suitable alternative to prevent of viral infections.
Results: Here, we focused our efforts on making the exogenous RNA encoding human interferon lambda (hIFN-λ1). Using the in vitro transcription method, we obtained hIFN-λ1 RNA and showed that it is capable to rapid translation in transfected cells. We compared the translation efficiency of mRNAs containing unmodified and modified (pseudouridine and 5-methyl-cytidine) nucleosides. Our results showed that the level of hIFN-λ1 during translation from containing modified nucleosides mRNA was 10-fold or more times higher compare to unmodified mRNA.
We found that the delivery of exogenous mRNA encoding GFP and hIFN-λ1 in cells resulted in an increase of MDA5, MxA, OAS-1, and IFN-αexpression, which indicate to the activation of innate immune response.
At last it was shown that mRNA encoding hIFN-λ1 significantly reduced the reproduction of A/California/07/09 (H1N1pdm09) in comparison with the nonspecific mRNA encoding GFP.
Features and Supervised Machine Learning-Based Method for Singleton Design Pattern Variants Detection
Authors: Nacef Abir , Bahroun Sahbi , Khalfallah Adel , Ahmed Samir Ben 
Published: December 2022

Abstract
Design patterns codify standard solutions to common problems in software design and architecture. Given their importance in improving software quality and facilitating code reuse, many types of research are proposed on their automatic detection. In this paper, we focus on singleton pattern recovery by proposing a method that can identify orthodox implementations and non-standard variants. The recovery process is based on specific data created using a set of relevant features. These features are specific information defining each variant which is extracted from the java program by structural and semantic analysis. We are based on the singleton analysis and different proposed features presented by Nacef et al. in [1] to create structured data. This data contains a combination of feature values defining each singleton variant to train a supervised Machine Learning (ML) algorithm. The goal is not limited to detecting the singleton pattern but also the specification of the implemented variant as so as the incorrect structure that is incoherent with the pattern intent. We use different ML algorithms to create the Singleton Detector (SD) to compare their performance. The empirical results demonstrate that our method for automatically training the (SD) based on features and supervised ML, can identify any singleton implementation with the specific variant’s name achieving 99% of precision, and recall. We have compared the proposed approach to similar studies namely DPDf and GEML. The results show that the SD outperforms the state-of-the-art approaches by more than 20% on evaluated data constructed from different repositories; PMART, DPB and DPDf corpus in terms of precision.
Investigation on Automatic Music Generation Using Gan and Lstm Networks
Authors: Tony Suman Maria , Sasikumar S 
Published: December 2022

Abstract
In this article, the authors propose a few methodologies for composing music using deep learning algorithms and Long-short term memory (LSTM) neural network and Generative Adversarial Networks (GANs). The LSTM model is created by training with a set of input files from a music library. The trained model then synthesizes music when an arbitrary note is provided. The GAN and other variants are trained using a set of midi file accumulated from the piano dataset. The pre-trained GAN model is then used to generate music similar to piano roll. The quality of the music is calculated by comparing the harmony and few other parameters of the synthesized music with the trained files. The music library is made with a set of midi files and based on the chosen library, a unique model shall be created. For the model creation, the library files are converted into a suitable format and encoded in order to make it compatible with the LSTM network. Though the outcome of this experiment is a continuous music, the harmony and notes can still be improved to solve the discontinuity problem. The outcome of this experiment is evaluated using conventional evaluators and also the aesthetics by human observer.
Genome insights from the Amazonian rhizobacterium Bacillus paramycoides RZ3MS14 reveal plant growth-promoting multi-traits and bioprotection against phytopathogens and environmental stresses
Authors: Apaza-Castillo Gladys Angélica , Hosaka Guilherme Kenichi , Quecine Maria Carolina 
Published: December 2022

Abstract
Bacillus paramycoides is poorly understood bacterium with potential application as plant growth promoter and agent control bacterium to a more sustainable agriculture. B. paramycoides strain RZ3MS14 was previously isolated from guarana´s rhizosphere on Amazonian rainforest. The obtained RZ3MS14 draft genome comprised 28 scaffolds with a genome size estimated of 5,493,110 bp and a G + C content of 34.9%. We predicted 5,637 coding sequences (CDS). From phylogenomic analysis was observed that RZ2MS14 clustered in a monophyletic group with B. paramycoides strains. The ANI and digital DNA-DNA hybridization comparing RZ3MS14 and the B. paramycoides strain type NH24A2 was 98.5% and 73-80.6% respectively. RZ3MS14 harbors different genes related with plant growth-promoting as instance phosphorus solubilization and mineralization as well as auxin production by IPA pathway and others. Moreover, the RZ3MS14 draft genome presented the putative micrococcin, cerecidin, and paeninodin gene clusters, antibiotics related with pathogen control in addition of genes to VOCs production. Our results contribute to improve the knowledge concerning the molecular basis of B. paramycoides related with its vast application on agriculture.
Eukaryotic Initiation Factor 5A2 localizes in actively translating ribosomes to promote cell protrusions and invasion of cancer cells
Authors: Martínez-Férriz Arantxa , Gandía Carolina , Pardo-Sánchez José Miguel , Fathinajafabadi Alihamze , Ferrando Alejandro , Farràs Rosa 
Published: December 2022

Abstract

Background Eukaryotic Initiation Factor 5A (eIF-5A), an essential translation factor, is post-translationally activated by the polyamine spermidine. Two human genes encode eIF-5A, being eIF5-A1 constitutively expressed whereas eIF5-A2 is frequently found overexpressed in human tumours. The contribution of both isoforms with regard to cellular proliferation and invasion in non-small cell lung cancer remains to be characterized. Methods We have evaluated the use of eIF-5A2 gene as prognosis marker in lung adenocarcinoma (LUAD) patients and validated in immunocompromised mice. We have used cell migration and cell proliferation assays in LUAD lines after silencing each eIF-5A isoform to monitor their contribution to both phenotypes. Cytoskeleton alterations were analysed in the same cells by rhodamine-phalloidin staining and fluorescence microscopy. Polysome profiles were used to monitor the effect of eIF-5A2 overexpression on translation. Western blotting was used to study the levels of eIF-5A2 client proteins involved in migration upon TGFB1 stimulation. Finally, we have co-localized eIF-5A2 with puromycin to visualize the subcellular pattern of actively translating ribosomes. Results We describe the differential functions of both eIF-5A isoforms, to show that eIF5-A2 properties on cell proliferation and migration are coincident with its features as a poor prognosis marker. Silencing of eIF-5A2 leads to more dramatic consequences of cellular proliferation and migration compared to eIF-5A1. Overexpression of eIF-5A2 leads to enhanced global translation. We also show that TGFb signalling enhances the expression and activity of eIF-5A2 which promotes the translation polyproline rich proteins involved in cytoskeleton and motility features as it is the case of Fibronectin, SNAI1, Ezrin and FHOD1. With the use of puromycin labelling we have co-localized active ribosomes with eIF-5A2 not only in cytosol but also in areas of cellular protrusion. We have shown the bulk invasive capacity of cells overexpressing eIF-5A2 in mice. Conclusions We propose the existence of a coordinated temporal and positional interaction between TFGB and eIF-5A2 pathways to promote cell migration in NSCLC. We suggest that the co-localization of actively translating ribosomes with hypusinated eIF-5A2 facilitates the translation of key proteins not only in the cytosol but also in areas of cellular protrusion.
Children of New Immigrants in Taiwan: Educational Mobility in Adolescence
Authors: Tsou Tzung-Ruei 
Published: December 2022

Abstract
The academic achievement of children of new immigrants in Taiwan is well explored in the extant literature. It is generally found that children of Southeast Asian mothers are more disadvantaged than children of mainland Chinese mothers. However, other aspects of educational mobility such as the type of high school a student attend, which has important implications for future occupational status in the labour market as the Taiwanese educational system begins to sort students into either a general or vocational track when they reach high school, are underinvestigated in the literature. Using the Taiwan Upper Secondary Education Database, this study shows that while children of mainland Chinese mothers do not differ significantly from students with native parents in class ranking, GPA, public and general high school attendance, and expected educational attainment, children of Southeast Asian mothers are indeed disadvantaged. Further analysis of Southeast Asian subgroups reveals that children of Thai mothers are the most advantaged whereas children of Vietnamese and Indonesian mothers are the most disadvantaged. An important factor contributing to the disadvantage of children of Southeast Asian mothers is family background, which is particularly salient to children of Vietnamese and Indonesian mothers. Due to this heterogeneity, policymakers and educators may need to understand the specific needs of each subgroup when designing educational programs.
Incorporating Ion Pairing in an Extended Specific Ion Theory: 2-2 Electrolytes
Authors: De Visscher Alex , Chavoshpoor Nazli 
Published: December 2022

Abstract
The specific ion theory (SIT) is a relatively simple model for the description of activity coefficients of ions in electrolyte solutions. However, the SIT model does not account for ion pairing, a phenomenon that is pronounced in 2–2 electrolytes. In this work, a recent extension of the SIT model is further extended to account for ion pairing. The model extension is tested with reported data for BeSO2, MgSO4, MnSO4, NiSO4, CuSO4, ZnSO4, and CdSO4. The standard error of the fit is typically around 1%. To get this accuracy in model fits of the activity coefficients that are consistent with literature data of the MgSO40 ion pair concentration, it was necessary to work in a modified molality scale and to reduce the SIT parameter B from 1.5 to 1.2. The drawback of this choice is that a value of B equal to 1.2 leads to worse predictions of the activity coefficients of 1–1 electrolytes. It is concluded that not accounting for ion pairing in 2–2 electrolytes leads to overestimations of the ionic strength of up to 30% and leads to overestimations of the Debye-Huckel term for the activity coefficient of 2–2 electrolytes by up to 20%.
Spatial Resolution Limitations of Particle Image Velocimetry in High Reynolds Number Turbulent Boundary Layers
Authors: Vishwanathan Vidya , Fritsch Daniel J. , Devenport William J. , Lowe K. Todd 
Published: December 2022

Abstract
Particle image velocimetry (PIV) has become a standard technique in turbulence experiments for its non-intrusive ability to simultaneously measure multiple points in a flow field. However, inherent volume averaging of the interrogation windows as well as fixed limitations of camera spatial resolution and related hardware set the minimum and maximum scales of structures that can be resolved with this measurement technique. Resolution limitations present themselves as an attenuation of the measured turbulence statistics, seen particularly in the Reynolds wall-normal stress components. This experimental study investigates the impact of hardware-level resolution limitations on the resolved turbulence statistics of PIV measurements made of both rough and smooth wall turbulent boundary layers influenced by external pressure gradients. Velocity fields are measured with PIV using two lens magnifications; one with a baseline lens and one with the addition of a teleconverter lens to view the same flow-field with double magnification (i.e. a finer spatial resolution). A comparison of the turbulence statistics between the rough and smooth wall, components of velocity, and pressure gradient magnitudes are analyzed. The smooth wall turbulence data consistently show a much higher sensitivity to the spatial resolution, particularly for the wall-normal component, due to the smaller eddy length-scales. A fixed camera resolution limits the measured range of scales which affects comparative magnitudes of turbulence for flows with different local Reynolds numbers. The rough wall data measurements show a variable sensitivity to the camera resolution depending on local Reynolds number and streamwise flow history. A statistical convergence study based on the anistropy of turbulence scales is necessary in experimental design for the study of turbulent boundary layers.
Two-Mode Subharmonic Generator Coupled to Thermal Reservoir
Authors: Belay Negasa 
Published: December 2022

Abstract
In this article, we have studied the squeezing and statistical properties of the light produced by a two mode subharmonic generator coupled to thermal reservoir via a single port-mirror. Finally, we have found that the degree of squezing is in deed affected by the present of thermal light. However the mean photon number of the system under consideration increases with increasing n̄.
LES MOTS DE LA CRISE : REGIMES DE CROYANCE ET FONCTIONNEMENT PASSIONNEL DANS LA PRESSE FRANÇAISE EN 2008
Authors: Verger-de Oliveira Christelle , Troqe Rovena 
Published: December 2022

Le concept de crise est souvent traité en termes de crise de culture, de problèmes de représentation ou de recherche de valeurs. Le présent article aborde la question de la crise économico-financière telle qu’elle s’est manifestée en 2008 et examine la problématique de sa prise en charge thymique dans le discours journalistique. L’application d’outils d’analyse sémiotextuelle à un corpus d’articles de presse française (sur le Rapport Attali et le cas Madoff) permet d’identifier l’apparition d’une situation de crise ainsi que de tracer son évolution. La théorie des régimes de croyance est ainsi conjuguée à une approche microtextuelle, dont les tenants et les aboutissants sont questionnés et problématisés de la façon suivante : comment réagissent les régimes de croyance et les systèmes axiologiques face à la crise ? De quelle manière cette dernière surdétermine-t-elle l’expression des identités des acteurs au sein de la presse ?
Anti-microbial Peptides against Methicillin-resistant Staphylococcus
aureus: Promising Therapeutics
Authors: Kumar Niraj Ravi Ranjan , Sharma Vinay , Sinoliya Priyanka , Solanki Pooran Singh , Piplani Sakshi 
Published: December 2022

Background:
Multidrug-resistant (MDR) methicillin-resistant Staphylococcus aureus (MRSA) has become a prime health concern globally. These bacteria are found in hospital areas where they are regularly dealing with antibiotics. This brings many possibilities for its mutation, so drug resistance occurs.

Introduction:
Nowadays, these nosocomial MRSA strains spread into the community and live stocks. Resistance in Staphylococcus aureus is due to mutations in their genetic elements.

Methods:
As the bacteria become resistant to antibiotics, new approaches like antimicrobial peptides (AMPs) play a vital role and are more efficacious, economical, time, and energy saviours.

Result:
Machine learning approaches of Artificial Intelligence are the in-silico technique which has their importance in better prediction, analysis, and fetching of important details regarding AMPs.

Conclusion:
Anti-microbial peptides could be the next-generation solution to combat drug resistance among Superbugs. For better prediction and analysis, implementing the in-silico technique is beneficial for fast and more accurate results.
Searching the Blood Lead Level in Children with Attention Deficit Hyperactivity Disorder: A Case-control Study in Tehran, Iran
Authors: Vafaee-Shahi Mohammad , Noorbakhsh Samileh , Shirazi Elham , Purfallah Mehrnoosh , Ghasemi Saeideh , Riahi Aina 
Published: December 2022

Background:
Attention deficit hyperactivity disorder (ADHD) is a common behavioral problem in children. Identifying the associated risk factors of ADHD is very important for the prognosis and early diagnosis of the disease. Here, we evaluated the association between lead exposure and growth indexes in children with ADHD.

Materials and Methods:
This case-control study was conducted on 30 children with ADHD and 50 healthy subjects. The patient’s age was between 5-12 years. Demographic and clinical information of children were recorded. Blood lead levels were measured in all samples by atomic absorption spectrometry.

Results:
Children with ADHD had significantly higher mean BMI than the control group (16.54 ± 2.8 kg/m2 vs. 14.82 ± 1.68 kg/m2; p=0.001). The mean of blood lead in children with ADHD was significantly higher than the normal group (10.58 ± 8.06 μg/dl vs. 7.52 ± 2.26 μg/dl; p=0.01). Multiple logistic analysis revealed one unit increase in BMI was associated with a higher risk of ADHD by 1.5 times (P=0.005; OR = 1.50), while one unit increase in blood lead level increased the risk of ADHD by 1.15 times (P=0.03, OR=1.15).

Conclusion:
Higher BMI and blood lead concentration are risk factors for ADHD among Iranian children.
An Insight into the Immunomodulatory Effects of Probiotics in the
Prevention of COVID-19 Disease
Authors: Das Jyotirmoy , Bordoloi Smita , Pathak Kalyani 
Published: December 2022

Abstract:
The coronavirus pandemic hit the world with different variants of SARS-CoV-2; reliable
therapeutics are needed every hour to control and minimize the infection. To date, the way to menace
the chaos of post-COVID infection is not confined rationally. Researchers are still on their way
to the progression of an efficient way to eradicate the disease. However, to prevent it from causing
infection post-entry into the body, there have been a few strategies to maintain and boost the immune
system. At the onset of infection when no antiviral therapeutics were available, convalescent
plasma therapies as a proposed mechanism were adapted to treat the post-COVID infection. Researchers
have formulated the administration of different types of vaccines based on attenuated or
inactivated nucleic acids or subunits after approval from the FDA and still continue to find the best
reliable vaccines for better enhancement in inducing immunogenicity of the immune system to fight
against the disease. The COVID-19 infection affects the gut and lung axis and there has been
dysbiosis of microbiota which leads to cause secondary infections. To accomplish homeostasis of
essential microbiota in the body, the administration of different strains of probiotic bacteria has
been one way to induce immunogenicity and combat the disease.