bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of quality management systems for educational institutions in the digital economy
Authors: Sherstobitova A A , Iskoskov M O 
Published: December 2020

Abstract
One of the priority tasks of education in the modern conditions of economic management is to provide quality technological and personnel reserves for the implementation of the tasks set by the Government of the Russian Federation in the field of development of the digital economy of the country. Considering the approaches to the transformation of all types of activities into a digital platform, it is possible to note the stage-by-stage transformation of the information infrastructure over the last period of development of market relations in the direction of digital transfer of information, knowledge and technologies. One of the barriers preventing a faster transition to new challenges to reality is the lack of compliance of the level of personnel training with the requirements of QMS standards, in particular the requirements of ISO 21001-2018 and ISO 9001-2015. The article considers the peculiarities of the requirements of the regulatory framework for the organization of QMS of higher education institutions, presented in the form of tasks described in the roadmap. The novelty of the proposed approaches consists in the integration of QMS requirements in the construction of a competency model. The proposed solutions to improve the processes of personnel training will ensure that society can implement the Passport “National Program “Digital Economy of the Russian Federation”.
Methodology of constructing highly adequate models of additively manufactured materials
Authors: Borovkov A I , Maslov L B , Ivanov K S , Kovaleva E N , Tarasenko F D , Zhmaylo M A , Thierry Barriere 
Published: December 2020

Abstract
In the this paper there is a description of the methodology of constructing highly adequate models of materials which are produced additively. The paper consists of introduction to the problem, demonstration of each step of the methodology and conclusions about the method and its applicability. The developed approach is presented on the two additively manufactured metal alloys. The modeling process is based on the orthotropic model of elasto-plastic material behavior. The list of material properties to be found was formulated according to proposed material model. These properties were found from several mechanical experiments. The developed mathematical models of the material studied were checked for compliance to experimental data with use of finite element simulations. Finite element modeling of a complicated 3d-printed lattice structure was performed and compared with the results of natural testing. In order to study the correlation between the material properties and manufacturing process the analysis of microstructure was done.
The Curing Simulation And Prediction Of Shape Distortion Of Thermoset Composite Reinforced With 3d Woven
Authors: Kiauka M , Pudeleva O , Tamm V A , Borovkov A 
Published: December 2020

Abstract
The general modeling methodology for thermoset composite reinforced with 3D woven is described. In this study the focus is on the curing simulation и prediction of shape distortion for thermoset composites in ABAQUS with user subroutines. The procedure of homogenization and determination of effective properties of a thermoset composite reinforced with 3D woven for the rubbery and glassy state of the matrix is also described in detail. Depending on the thermoset polymer type, the different cure reaction formulations are implemented. The temperature expansion and chemical shrinkage tensors at each time step are set depending on the degree of cure and the glass transition temperature. Curing model with piecewise constant elastic modules is used. The model takes into account the shape distortion of the part due to chemical shrinkage and thermal expansion of the material. Curing simulation and prediction of shape distortion results for U-shaped part for Kamal-Sourour reaction type is presented. The effective properties of the composite reinforced with 3D woven for the rubbery and glassy states of the matrix are obtained.
Electromagnetic compatibility of the on-board electrical complex as a key factor in ensuring the operational safety of vehicles
Authors: Kozlovsky V. N. , Nikolaev P. A. , Podgorny A. S. , Kritsky A. V. , Zhmaylo M.A. 
Published: December 2020

Abstract
The issues of functional safety of the on-board electrical complex of vehicles under exposure of electromagnetic interference are considered in this paper. Besides, the modern practice of organizing the process of assessing the immunity of electrical systems of cars is shown.
Simple and efficient preparation of uniformly dispersed Carbon nanotubes reinforced Copper matrix composite powders by in situ chemical vapor deposition without additional catalyst
Authors: Duan Pengyun , Xu Kai , Chen Xiaohong , Liu Ping , Zhou Honglei , Fu Shaoli , Bi Liming , Guo Xu 
Published: December 2020

Abstract
Carbon nanotubes (CNTs) reinforced Copper (Cu) matrix composite powders have been successfully prepared by in situ chemical vapor deposition (CVD) using Cu-0.6 wt% Al alloy powders without additional catalyst. The catalyst for CNTs growth is nano-copper particle (∼28 nm), and the interaction between Cu and Al2O3 would promote the formation of nano-copper particles (∼28 nm). The high quality multi-walled CNTs obtained dispersed uniformly on and well bonded to the composite powders. And the formation mechanism was discussed, the results show that part of the growth of CNTs follows tip-growth mode and the others without catalyst particles at the top follow the base-growth mode. This providing a simple and effective method for in situ preparation of CNTs/Cu composite powder with uniform dispersion of CNTs.
Highly efficient Yb:YAG microchip laser for direct generation of radially polarized vector vortices
Authors: Chen Dimeng , Cai Shu , Dong Jun 
Published: December 2020

Abstract
High beam quality, highly efficient radially polarized vector vortex beam has been generated in a Yb:YAG microchip laser pumped with an annular beam formed with a hollow focus lens. The output power of 2.15 W has been achieved at the absorbed pump power of 3.53 W. The optical-to-optical efficiency is 60.9%. The radially polarized vector vortex lasers working at 1030 nm, 1050 nm, 1030/1050 nm dual-wavelength depending on applied pump power. High polarization purity with degree of polarization of over 91% has been achieved for radially polarized vector vortex lasers. Our work provides an effective method for developing compact wavelength tunable, radially polarized vector vortex lasers.
Counterpoint: Epidemiology’s Dual Social Commitment—Science and Health
Authors: Saracci Rodolfo 
Published: December 2020

Abstract
Matching epidemiology’s aspirations to actual delivery of goods valuable for population health depends both on the scientific and operational capabilities of epidemiology and on the degree to which the goods meet its contract with society. Epidemiology’s capabilities have advanced remarkably in recent decades, although research gaps have appeared during the current coronavirus disease 2019 (COVID-19) pandemic. Epidemiology’s social contract reflecting a dual commitment to science and health could arguably be entirely met by producing research results under conditions variously described as objective, impartial, neutral, or independent and handing such results to decision makers and the public at large. However, a closer examination shows that those four terms address sharply distinct issues, with distinct practical implications, and that the epidemiologist responsibility is de facto involved beyond providing research results. Hence the epidemiologist’s engagement should encompass arguing from a science-for-health viewpoint and proactively driving the results into decision processes on public health issues.
Andrographis paniculata and Its Main Bioactive Ingredient Andrographolide Decrease Alcohol Drinking and Seeking in Rats Through Activation of Nuclear PPARγ Pathway
Authors: Stopponi Serena , Fotio Yannick , Cifani Carlo , Li Hongwu , Haass-Koffler Carolina L , Cannella Nazzareno , Demopulos Gregory , Gaitanaris George , Ciccocioppo Roberto 
Published: December 2020

Abstract

Background and aims
Andrographis paniculata is an annual herbaceous plant which belongs to the Acanthaceae family. Extracts from this plant have shown hepatoprotective, anti-inflammatory and antidiabetic properties, at least in part, through activation of the nuclear receptor Peroxisome Proliferator-Activated Receptor-gamma (PPAR γ). Recent evidence has demonstrated that activation of PPARγ reduces alcohol drinking and seeking in Marchigian Sardinian (msP) alcohol-preferring rats.

Methods
The present study evaluated whether A. paniculata reduces alcohol drinking and relapse in msP rats by activating PPARγ.

Results
Oral administration of an A. paniculata dried extract (0, 15, 150 mg/kg) lowered voluntary alcohol consumption in a dose-dependent manner and achieved ~65% reduction at the dose of 450 mg/kg. Water and food consumption were not affected by the treatment. Administration of Andrographolide (5 and 10 mg/kg), the main active component of A. paniculata, also reduced alcohol drinking. This effect was suppressed by the selective PPARγ antagonist GW9662. Subsequently, we showed that oral administration of A. paniculata (0, 150, 450 mg/kg) prevented yohimbine- but not cues-induced reinstatement of alcohol seeking.

Conclusions
Results point to A. paniculata-mediated PPARγactivation as a possible therapeutic strategy to treat alcohol use disorder.
Atlas: automatic modeling of regulation of bacterial gene expression and metabolism using rule-based languages
Authors: Santibáñez Rodrigo , Garrido Daniel , Martin Alberto J M 
Published: December 2020

Abstract

Motivation
Cells are complex systems composed of hundreds of genes whose products interact to produce elaborated behaviors. To control such behaviors, cells rely on transcription factors to regulate gene expression, and gene regulatory networks (GRNs) are employed to describe and understand such behavior. However, GRNs are static models, and dynamic models are difficult to obtain due to their size, complexity, stochastic dynamics and interactions with other cell processes.

Results
We developed Atlas, a Python software that converts genome graphs and gene regulatory, interaction and metabolic networks into dynamic models. The software employs these biological networks to write rule-based models for the PySB framework. The underlying method is a divide-and-conquer strategy to obtain sub-models and combine them later into an ensemble model. To exemplify the utility of Atlas, we used networks of varying size and complexity of Escherichia coli and evaluated in silico modifications, such as gene knockouts and the insertion of promoters and terminators. Moreover, the methodology could be applied to the dynamic modeling of natural and synthetic networks of any bacteria.

Availability and implementation
Code, models and tutorials are available online (https://github.com/networkbiolab/atlas).

Supplementary information
Supplementary data are available at Bioinformatics online.
Diffuse axonal injury has a characteristic multidimensional MRI signature in the human brain
Authors: Benjamini Dan , Iacono Diego , Komlosh Michal E , Perl Daniel P , Brody David L , Basser Peter J 
Published: December 2020

Abstract
Axonal injury is a major contributor to the clinical symptomatology in patients with traumatic brain injury. Conventional neuroradiological tools, such as CT and MRI, are insensitive to diffuse axonal injury (DAI) caused by trauma. Diffusion tensor MRI parameters may change in DAI lesions; however, the nature of these changes is inconsistent. Multidimensional MRI is an emerging approach that combines T1, T2, and diffusion, and replaces voxel-averaged values with distributions, which allows selective isolation of specific potential abnormal components. By performing a combined post-mortem multidimensional MRI and histopathology study, we aimed to investigate T1-T2-diffusion changes linked to DAI and to define their histopathological correlates. Corpora callosa derived from eight subjects who had sustained traumatic brain injury, and three control brain donors underwent post-mortem ex vivo MRI at 7 T. Multidimensional, diffusion tensor, and quantitative T1 and T2 MRI data were acquired and processed. Following MRI acquisition, slices from the same tissue were tested for amyloid precursor protein (APP) immunoreactivity to define DAI severity. A robust image co-registration method was applied to accurately match MRI-derived parameters and histopathology, after which 12 regions of interest per tissue block were selected based on APP density, but blind to MRI. We identified abnormal multidimensional T1-T2, diffusion-T2, and diffusion-T1 components that are strongly associated with DAI and used them to generate axonal injury images. We found that compared to control white matter, mild and severe DAI lesions contained significantly larger abnormal T1-T2 component (P = 0.005 and P &lt; 0.001, respectively), and significantly larger abnormal diffusion-T2 component (P = 0.005 and P &lt; 0.001, respectively). Furthermore, within patients with traumatic brain injury the multidimensional MRI biomarkers differentiated normal-appearing white matter from mild and severe DAI lesions, with significantly larger abnormal T1-T2 and diffusion-T2 components (P = 0.003 and P &lt; 0.001, respectively, for T1-T2; P = 0.022 and P &lt; 0.001, respectively, for diffusion-T2). Conversely, none of the conventional quantitative MRI parameters were able to differentiate lesions and normal-appearing white matter. Lastly, we found that the abnormal T1-T2, diffusion-T1, and diffusion-T2 components and their axonal damage images were strongly correlated with quantitative APP staining (r = 0.876, P &lt; 0.001; r = 0.727, P &lt; 0.001; and r = 0.743, P &lt; 0.001, respectively), while producing negligible intensities in grey matter and in normal-appearing white matter. These results suggest that multidimensional MRI may provide non-invasive biomarkers for detection of DAI, which is the pathological substrate for neurological disorders ranging from concussion to severe traumatic brain injury.
Filling the gap between risk assessment and molecular determinants of tumor onset
Authors: Chiara Federica , Indraccolo Stefano , Trevisan Andrea 
Published: December 2020

Abstract
In the past two decades, a ponderous epidemiological literature has causally linked tumor onset to environmental exposure to carcinogens. As consequence, risk assessment studies have been carried out with the aim to identify both predictive models of estimating cancer risks within exposed populations and establishing rules for minimizing hazard when handling carcinogenic compounds. The central assumption of these works is that neoplastic transformation is directly related to the mutational burden of the cell without providing further mechanistic clues to explain increased cancer onset after carcinogen exposure. Nevertheless, in the last few years, a growing number of studies have implemented the traditional models of cancer etiology, proposing that neoplastic transformation is a complex process in which several parameters and crosstalk between tumor and microenvironmental cells must be taken into account and integrated with mutagenesis. In this conceptual framework, the current strategies of risk assessment that are solely based on the ‘mutator model’ require an urgent update and revision to keep pace with advances in our understanding of cancer biology. We will approach this topic revising the most recent theories on the biological mechanisms involved in tumor formation in order to envision a roadmap leading to a future regulatory framework for a new, protective policy of risk assessment.
Indirect Standardization as a Case Mix Adjustment Method to Improve Comparison of Children’s Hospitals’ Antimicrobial Use
Authors: Wattier Rachel L , Thurm Cary W , Parker Sarah K , Banerjee Ritu , Hersh Adam L ,   Pediatric Health Information System Antimicrobial Stewardship Research Group, Brogan Thomas V , Courter Joshua D , Gerber Jeffrey S , Kronman Matthew P , Lee Brian R , Nakamura Mari M , Newland Jason G , Patel Sameer J , Shah Samir S , Smith Michael J , Spaulding Alicen B 
Published: December 2020

Abstract
Antimicrobial use (AU) in days of therapy per 1000 patient-days (DOT/1000 pd) varies widely among children’s hospitals. We evaluated indirect standardization to adjust AU for case mix, a source of variation inadequately addressed by current measurements. Hospitalizations from the Pediatric Health Information System were grouped into 85 clinical strata. Observed to expected (O:E) ratios were calculated by indirect standardization and compared with DOT/1000 pd. Outliers were defined by O:E z-scores. Antibacterial DOT/1000 pd ranged from 345 to 776 (2.2-fold variation; interquartile range [IQR] 552–679), whereas O:E ratios ranged from 0.8 to 1.14 (1.4-fold variation; IQR 0.93–1.05). O:E ratios were moderately correlated with DOT/1000 pd (correlation estimate 0.44; 95% confidence interval, 0.19–0.64; P = .0009). Using indirect standardization to adjust for case mix reduces apparent AU variation and may enhance stewardship efforts by providing adjusted comparisons to inform interventions.
A New Blind Watermark Embedding Model: Spiral Updated Rider Optimization Algorithm
Authors: Narasimhulu C Venkata 
Published: December 2020

Abstract
In this era, the exchanging of multimedia content has become much comfortable. Since the distribution and the illegal copying of digital multimedia content have become much easier, an author’s intellectual property copyrights have suffered from the violations that led to many damage to their benefits in many applications. This paper intends to propose a novel digital watermarking model for multimedia copyright protection that is based on 3D wavelet transformation. Initially, histogram-based motion frame extraction is conducted on the color video for which keyframes are extracted based on the extracted motion frames. To embed the watermark in the keyframes, 3D wavelet coefficients are selected followed by applying the spread spectrum technique. To conduct precise and effective embedding, it is planned to introduce fine-tuning aspects in the embedding process. As the intensity factor plays a major role in the embedding process, this paper tunes it rather than selecting randomly. Moreover, the Mersenne-Twister algorithm is known for spreading the power spectrum of watermark data to keep invisible. Hence, it is also intended to tune the seed factor of the respective algorithm to further effectuate the spreading process. These tuning processes can be solved as an optimization problem for which this paper proposes a new hybrid optimization algorithm named Spiral Updated Rider Optimization Algorithm (SU-ROA). SU-ROA is a hybrid variant of the Rider Optimization Algorithm (ROA) and Whale Optimization Algorithm (WOA). The performance of the proposed work is compared and proved over the state-of-the-art models in terms of both embedding and extracting effectiveness.
Knowledge, Communication, and Anti-Critical Publicity: The Friedmans’ Market Public
Authors: Asen Robert 
Published: December 2020

AbstractFocusing on the writings of Milton and Rose Friedman, this article explicates a model of a market public as the normative mode of public engagement in a neoliberal regime of governance. The Friedmans’ market public narrowly construes conceptions of knowledge as arising from direct experience and communication as information exchange. Knowledge as direct experience supports the putative universality of self-interest and the sovereignty of individuals as exclusive public actors. Presuming a uniformity of understanding, communication as information exchange dissociates advocates from messages and contributes to the Friedmans’ view of persuasion as an individualistic mode of interaction. Connecting the Friedmans’ model to contemporary scholarly critiques of neoliberalism, I argue that this model portends significant anti-democratic consequences. Citing former U.S. Education Secretary Betsy DeVos’ campaign to reorganize public education as a market, I illustrate the contemporary circulation of this model.
Large-scale regulatory and signaling network assembly through linked open data
Authors: Lefebvre M , Gaignard A , Folschette M , Bourdon J , Guziolowski C 
Published: December 2020

Abstract
Huge efforts are currently underway to address the organization of biological knowledge through linked open databases. These databases can be automatically queried to reconstruct regulatory and signaling networks. However, assembling networks implies manual operations due to source-specific identification of biological entities and relationships, multiple life-science databases with redundant information and the difficulty of recovering logical flows in biological pathways. We propose a framework based on Semantic Web technologies to automate the reconstruction of large-scale regulatory and signaling networks in the context of tumor cells modeling and drug screening. The proposed tool is pyBRAvo (python Biological netwoRk Assembly), and here we have applied it to a dataset of 910 gene expression measurements issued from liver cancer patients. The tool is publicly available at https://github.com/pyBRAvo/pyBRAvo.
Clinical pathways and outcomes of patients with Barrett’s esophagus in tertiary care settings: a prospective longitudinal cohort study in Australia, 2008–2016
Authors: Na Renhua , Miura Kyoko , O’Brien Suzanne , Eslick Guy D , Kendall Bradley J , Hourigan Luke F , Bourke Michael , Cox Michael R , Farrokhzadi Laal , Levert-Mignon Angelique J , Barbour Andrew P , Clemons Nicholas J , Duong Cuong P , Lord Reginald V , Phillips Wayne A , Watson David I , Whiteman David C 
Published: December 2020

Summary

Background
Clinical services for Barrett’s esophagus have been rising worldwide including Australia, but little is known of the long-term outcomes of such patients. Retrospective studies using data at baseline are prone to both selection and misclassification bias. We investigated the clinical characteristics and outcomes of Barrett’s esophagus patients in a prospective cohort.

Methods
We recruited patients diagnosed with Barrett’s esophagus in tertiary settings across Australia between 2008 and 2016. We compared baseline and follow-up epidemiological and clinical data between Barrett’s patients with and without dysplasia. We calculated age-adjusted incidence rates and estimated minimally and fully adjusted hazard ratios (HR) to identify those clinical factors related to disease progression.

Results
The cohort comprised 268 patients with Barrett’s esophagus (median follow-up 5 years). At recruitment, 224 (84%) had no dysplasia, 44 (16%) had low-grade or indefinite dysplasia (LGD/IND). The age-adjusted incidence of esophageal adenocarcinoma (EAC) was 0.5% per year in LGD/IND compared with 0.1% per year in those with no dysplasia. Risk of progression to high-grade dysplasia/EAC was associated with prior LGD/IND (fully adjusted HR 6.55, 95% confidence interval [CI] 1.96–21.8) but not long-segment disease (HR 1.03, 95%CI 0.29–3.58).

Conclusions
These prospective data suggest presence of dysplasia is a stronger predictor of progression to cancer than segment length in patients with Barrett’s esophagus.