Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating Maps of Science Using Contextual Proximity of Citations Based on Deep Contextualized Word Representation

The citation intent extraction and classification has long been studied as it is a good measure of relevancy. Different approaches have classified the citations into different classes; including weak and strong, positive and negative, important and unimportant. Others have gone further from binary classification to multi-classes, including extension, use, background, or comparison. Researchers have utilized various elements of the information, including both meta and contents of the paper. The actual context of any referred article lies within the citation context where a paper is referred. Various attempts have been made to study the citation context to capture the citation intent, but very few have encoded the words to their contextual representations. For automated classification, we need to train deep learning models, which take the citation context as input and provides the reason for citing a paper. Deep neural models work on numeric data, and therefore, we must convert the text information to its numeric representation. Natural languages are much complex than computer languages. Computer languages have a pre-defined fixed syntax where each word has a unique meaning. In contrast, every word in natural language may have a different meaning and may well be understood by understanding the position, previous discussion, and neighboring words. The extra information provides the context of a word within a sentence. We have, therefore, used contextual word representation, which is trained through deep neural networks. Deep models require massive data for generalizing the model, however, the existing state-of-the-art datasets don’t provide much information for the training models to get generalized. Therefore, we have developed our own scholarly dataset, Citation Context Dataset with Intent (C2D-I), an extension of the C2D dataset. We used a transformers based model for capturing the contextual representation of words. Our proposed method outperformed the existing benchmark methods with F1 score of 89%.
PhycoCanopy: An R Shiny tool for exploring primary production in macroalgal canopies

Macroalgal canopies are considered important for coastal food webs and may have a role in carbon sequestration. Until recently, measures of canopy photosynthesis have been relatively rare, and simulations have sometimes omitted key aspects (e.g. self‐shading, photosynthesis in air). PhycoCanopy offers a way of exploring how different algal parameters and environmental settings can affect net canopy photosynthesis. The model uses the approach of dividing the canopy into vertical layers, calculating the available light for photosynthesis in each layer with respect to attenuation by the water column and the canopy. A total of 23 parameters can be varied to investigate the consequences of changes in key processes such as the tidal cycle, position of algae relative to the low tide mark and photosynthesis in air. Predicted net photosynthesis can vary within a day as the timing of tides interacts with the light level at different times. The model offers a means of exploring the sensitivity of different parameters and building a fuller understanding of canopy photosynthesis. PhycoCanopy allows users to visualize net canopy photosynthesis and to make predictions in situations where parameters are well characterized. The results give an integrated insight into net photosynthesis, particularly as intertidal observations cannot be maintained continuously over the tidal cycle. The model also demonstrates important covariates, such as the area of algal thallus m−2 (thallus area index, TAI), that should be measured to interpret observed variation in canopy photosynthesis.
Multi-stage resilience analysis of the nexus flood-sanitation-public health in urban environments: a theoretical framework

ABSTRACT Water supply and wastewater systems are essential infrastructure affected by floods. Additional risk is posed in developing countries, where access to sanitation is not universal. Few studies assess the flood risk to the sanitation-health nexus. Therefore, this study aims to present a theoretical and general framework for assessing the resilience of flood-sanitation-public health nexus in urban environments, composed by risk estimation and risk management assessment. The framework was developed from a system analysis approach focusing on central supply systems. Regarding risk assessment, the main vulnerability and exposure factors identified were land use, social vulnerability, coverage of sanitation systems, occurrence of waterborne diseases, number of people affected by floods and intersection with the flood map. From the risk management assessment stage three main typologies of trade-offs and synergies were identified: urban territorial planning versus runoff control, water quality versus sanitation infrastructure and flood management policy versus social behavior.
Antimicrobial Resistance in Enterobacterales Recovered from Urinary Tract Infections in France

In the context of increasing antimicrobial resistance in Enterobacterales, the management of these UTIs has become challenging. We retrospectively assess the prevalence of antimicrobial resistance in Enterobacterales isolates recovered from urinary tract samples in France, between 1 September 2017, to 31 August 2018. Twenty-six French clinical laboratories provided the susceptibility of 134,162 Enterobacterales isolates to 17 antimicrobials. The most frequent species were E. coli (72.0%), Klebsiella pneumoniae (9.7%), Proteus mirabilis (5.8%), and Enterobacter cloacae complex (2.9%). The overall rate of ESBL-producing Enterobacterales was 6.7%, and ranged from 1.0% in P. mirabilis to 19.5% in K. pneumoniae, and from 3.1% in outpatients to 13.6% in long-term care facilities. Overall, 4.1%, 9.3% and 10.5% of the isolates were resistant to cefoxitin, temocillin and pivmecillinam. Cotrimoxazole was the less active compound with 23.4% resistance. Conversely, 4.4%, 12.9%, and 14.3% of the strains were resistant to fosfomycin, nitrofurantoin, and ciprofloxacin. However, less than 1% of E. coli was resistant to fosfomycin and nitrofurantoin. We identified several trends in antibiotics resistances among Enterobacterales isolates recovered from the urinary tract samples in France. Carbapenem-sparing drugs, such as temocillin, mecillinam, fosfomycin, cefoxitin, and nitrofurantoin, remained highly active, including towards ESBL-E.
Respiratory Muscle Training Can Improve Cognition, Lung Function, and Diaphragmatic Thickness Fraction in Male and Non-Obese Patients with Chronic Obstructive Pulmonary Disease: A Prospective Study

Patients with chronic obstructive pulmonary disease (COPD) are frequently comorbid with mild cognitive impairment (MCI). Whether respiratory muscle training (RMT) is helpful for patients with COPD comorbid MCI remains unclear. Inspiratory muscle training (IMT) with or without expiratory muscle training (EMT) was performed. Patients were randomly assigned to the full training group (EMT + IMT) or the simple training group (IMT only). A total of 49 patients completed the eight-week course of RMT training. RMT significantly improved the maximal inspiratory pressure (MIP), the diaphragmatic thickness fraction and excursion, lung function, scores in the COPD assessment test (CAT), modified Medical Research Council (mMRC) scale scores, and MMSE. The between-group difference in the full training and single training group was not significant. Subgroup analysis classified by the forced expiratory volume in one second (FEV1) level of patients showed no significant differences in MIP, lung function, cognitive function, and walking distance. However, a significant increase in diaphragmatic thickness was found in patients with FEV1 ≥ 30%. We suggest that patients with COPD should start RMT earlier in their disease course to improve physical activity.
Impact of Nutrition on Age-Related Epigenetic RNA Modifications in Rats

Nutrition plastically modulates the epigenetic landscape in various tissues of an organism during life via epigenetic changes. In the present study, to clarify whether this modulation involves RNA methylation, we evaluated global RNA methylation profiles and the expression of writer, reader, and eraser genes, encoding for enzymes involved in the RNA methylation. The study was carried out in the heart, liver, and kidney samples from rats of different ages in response to a low-calorie diet. We found that, although each tissue showed peculiar RNA methylation levels, a general increase in these levels was observed throughout the lifespan as well as in response to the six-month diet. Similarly, a prominent remodeling of the expression of writer, reader, and eraser genes emerged. Our data provide a comprehensive overview of the role exerted by diet on the tissue-specific epigenetic plasticity of RNA according to aging in rats, providing the first evidence that methylation of RNA, similarly to DNA methylation, can represent an effective biomarker of aging. What is more, the fact that it is regulated by nutrition provides the basis for the development of targeted approaches capable of guaranteeing the maintenance of a state of good health.
A Nash Equilibrium Approach to the Brazilian Seasonalization of Energy Certificates

This paper presents a Nash equilibrium approach to model a non-cooperative game that takes place among Brazilian hydro-generating companies in the annual process called “seasonalization”. We have “remade” the seasonalizations that occurred in the period of 2013–2020 by using our model and comparing the financial outcomes with the current ones that resulted from the seasonalizations the generators made each year, with financial improvements in almost every year. By using the Nash equilibrium approach, it is possible to achieve optimal decisions concerning the seasonalization process that were not evident by using traditional methods. This approach is useful for companies willing to enhance their income and to improve their risk management by making better choices in seasonalization.
Typical process discovery based on affinity propagation

A lot of repeated work existed in the design of manufacturing process for similar parts, and many kinds of process knowledge which were not reused effectively contained in the historical process data. In these conditions, in order to reuse the typical process effectively and enhance design efficiency, typical process discovery was studied. The problem of typical process discovery was described firstly, the attributed directed graph was used to model the process. And the similarity between processes could be measured with the similarity between process cells and the similarity between process routes by the process model. Based on the process similarity, affinity propagation method was used to cluster the process. For the purpose of getting the effective clustering results and making sure the best number of clusters, the Silhouette index and the in-group proportion index were separately adopted in the clustering analysis. Finally, we have experimented the validity of the discovery algorithm by clustering typical process of machining process for satellite plate.
Echocardiography Nomogram for Predicting Survival among Chronic Lung Disease Patients with Severe Pulmonary Hypertension

Severe pulmonary hypertension in chronic lung diseases (severe CLD-PH) differs significantly from other types of PH in physiology and prognosis. We aimed to assess whether echocardiography helps predict long-term survival in patients with severe CLD-PH. This single-centre, observational cohort study enrolled 100 patients with severe CLD-PH (mean pulmonary arterial pressure ≥35 mm Hg or ≥25 mm Hg with cardiac index <2.0 L/min/m2 or pulmonary vascular resistance ≥6 Wood units) between 2009 and 2014. The population was randomly divided into a derivation and validation cohort in a 2:1 ratio. To construct a nomogram, a multivariable logistic regression model was applied, and scores were assigned based on the hazard ratio of independent echocardiographic predictors. Multivariate Cox hazards analysis identified the strongest predictors of mortality as pulmonary arterial systolic pressure (PASP), tricuspid annular plane systolic excursion, and right ventricular end-diastolic transverse dimension. The three independent predictors were entered into the nomogram. Compared with PASP alone, the nomogram resulted in an integrated discrimination improvement of 15.5% (95% confidence interval, 5.52–25.5%, p = 0.002) with a net improvement in model discrimination (C-statistic from 0.591 to 0.746). Using echocardiographic parameters, we established and validated a novel nomogram to predict all-cause death for patients with severe CLD-PH.
A Modular Hepatitis E Virus Replicon System for Studies on the Role of ORF1-Encoded Polyprotein Domains

Zoonotic hepatitis E virus (HEV) infection is an emerging cause of acute viral hepatitis in developed countries. Known reservoirs of zoonotic genotype 3 (HEV-3) are mainly pigs and wild boar, and to a lesser extent rabbits and deer. Rabbit hepatitis E virus (HEV-3ra) is prevalent in rabbits worldwide and represents a particular risk for zoonotic infection. Current understanding of the molecular mechanisms of HEV pathogenesis is incomplete, particularly due to the limited availability of efficient and reliable cell culture systems. In order to identify genomic regions responsible for HEV propagation in cell culture, we developed a modular chimeric reporter replicon system based on cell culture-adapted (Kernow-C1/p6 and 47832mc) and rabbit-derived HEV strains. Replication in HepG2 cells was monitored on the basis of a Gaussia luciferase reporter gene that was inserted in place of the open reading frame (ORF) 2 of the HEV genome. Luciferase activity of rabbit HEV-derived replicons was significantly lower than that of Kernow-C1/p6 and 47832mc replicons. Serial exchanges of defined ORF1 segments within the Kernow-C1/p6 replicon backbone indicated that HEV replication in HepG2 cells is not determined by a single domain but rather by an interplay of longer segments of the ORF1-derived nonstructural polyprotein. This implies that a specific combination of viral factors is required for efficient HEV propagation in cell culture.
Application of Information Fusion Technologies in Intelligent Traffic Field

This paper systematically outlines the application of information fusion technologies in intelligent traffic,and summarizes common information fusion technologies to conclude 5 categories of information fusion technologies,i. e. neural network,Bayes fusion,reasoning fusion,spatial fusion and self-adaptive filter. Based on 5 different traffic application scenarios,i. e. information detection and acquisition,analysis of traffic flow,classification and recognition,induction control and location and navigation,the paper conducts literature summary of the application of information fusion technologies in intelligent traffic,and points out that fusion skills and algorithms vary with different traffic application scenarios.
An analysis of organism lifelines in an industrial bioreactor using Lattice‐Boltzmann CFD

Euler‐Lagrange CFD simulations, where the biotic phase is represented by computational particles (parcels), provide information on environmental gradients inside bioreactors from the microbial perspective. Such information is highly relevant for reactor scale‐down and process optimization. One of the major challenges is the computational intensity of CFD simulations, especially when resolution of dynamics in the flowfield is required. Lattice‐Boltzmann large‐eddy simulations (LB‐LES) form a very promising approach for simulating accurate, dynamic flowfields in stirred reactors, at strongly reduced computation times compared to finite volume approaches. In this work, the performance of LB‐LES in resolving substrate gradients in large‐scale bioreactors is explored, combined with the inclusion of a Lagrangian biotic phase to provide the microbial perspective. In addition, the hydrodynamic performance of the simulations is confirmed by verification of hydrodynamic characteristics (radial velocity, turbulent kinetic energy, energy dissipation) in the impeller discharge stream of a 29 cm diameter stirred tank. The results are compared with prior finite volume simulation results, both in terms of hydrodynamic and biokinetic observations, and time requirements.
The Mediating Effects of Work–Life Balance (WLB) and Ease of Using WLB Programs in the Relationship between WLB Organizational Culture and Turnover Intention

Work–life balance (WLB) is an important concern for all workers irrespective of their age, sex, education level, family structure, or occupation. This study analyzes WLB’s mediating effects and the ease of using WLB programs in the relationship between WLB organizational culture of hotels and turnover intention of its culinary staff. We conducted a survey featuring 320 culinary staff members at hotels in Incheon from 10 to 30 August 2020 and performed statistical analysis using 290 responses. We find that the company’s willingness for WLB, empathetic communication with colleagues, material support of colleagues for WLB, and the ease of using WLB programs in organizational culture had a positive impact on WLB. The company’s willingness for WLB, boss’s consideration for WLB, empathetic communication with colleagues, and material support of colleagues for WLB in organizational culture had a negative impact on turnover intention. The ease of using WLB programs had no indirect effect on the relationship between organizational culture and turnover intention. However, WLB had an indirect effect on the relationship between the four components except for the boss’s consideration for WLB and turnover intention. Hotel management should create an organizational culture that supports the WLB of culinary staff.
Calculation and analysis of 3D temperature fields of medium size high voltage asynchronous motor based on coupled field

Researching on temperature field and fluid field inside ventilation duct plays important part in guaranteeing motor high effective,secure and reliable operation.According to the theory of fluid dynamics and heat transfer,solved equations of heat transfer were given.A YKK400-6(690kW) medium size high voltage asynchronous motor was taken as an example.The mathematical model and physical model of 3D stator and rotor solved region were established,the bourdary conditions and assumptions of solved region were given,coupled equations can be solved using finite volume method.Fluid field distribution inside radial ventilation duct was shown.The rotor and stator 3D temperature field were computed.The calculated results were analyzed.The computed results were compared with measured value.The results show that the complicated fluid field can be known in the ventilation duct by coupled field.The calculative results of temperature field are more accurate.
Optimizing Social Visibility in OSNs With Anonymity Guarantees: Efficient Algorithms and Applications

Online social network (OSN) is an ideal venue to enhance one's visibility. This paper considers how a user (called requester) in an OSN selects a small number of users and invites them as new friends/followers so as to maximize her “social visibility”. More importantly, the requester has to do this under the anonymity setting, which means she is not allowed to know the neighborhood information of other users in the OSN. In this paper, we first develop a mathematical model to quantify the social visibility and formulate the problem of visibility maximization with anonymity guarantee, abbreviated as “VisMAX-A”. We prove that the VisMAX-A problem is NP-hard even with an “perfect query oracle” which knows users’ neighborhood information. Then we design an algorithmic framework named as “AdaExp,” which adaptively expands the requester's visible set in multiple rounds. In each round of the expansion, the algorithmic framework uses a query oracle with anonymity guarantee to select one user to increase the requester's visibility. We prove the theoretical guarantees of our algorithmic framework, which quantify how the query oracle may influence the solution guarantee. By using probabilistic data structures like the k-minimum values (KMV) sketch and online learning methods like multi-armed bandit (MAB), we design an efficient query oracle with anonymity guarantees to estimate the best candidate to increase requester's visibility. We also conduct experiments on real-world social networks and validate the effectiveness of our algorithms. Lastly, we demonstrate applications of our algorithm on real-world data and show that one can increase her social visibility significantly by only adding a few (e.g., one or two) friends/followers in the OSNs.
Cardiac Hypertrophy May Be a Risk Factor for the Development and Severity of Glaucoma

The purpose of this study was to examine the relationship between glaucoma and cardiac abnormalities. We evaluated 581 patients with open-angle glaucoma (285 men and 296 women) and 595 individuals without glaucoma (273 men and 322 women). All of the participants underwent visual field testing using a Humphrey Visual Field Analyzer (30-2 program), an electrocardiogram (ECG), and blood pressure measurement. We examined the ECG abnormalities and other factors (age, intraocular pressure (IOP) and systemic hypertension) involved in the development and severity of glaucoma. Logistic regression analyses revealed significant correlations of glaucoma with IOP (OR = 1.43; 95% CI: 1.36–1.51; p < 0.00001), atrial fibrillation (OR = 2.02; 95% CI: 1.01–4.04; p = 0.04), left ventricular hypertrophy (LVH) (OR = 2.21; 95% CI: 1.15–4.25; p = 0.02), and bradycardia (OR = 2.19; 95% CI: 1.25–4.70; p = 0.02). Regression analyses revealed significant correlations of the mean deviation of the visual field with age (t = –6.22; 95% CI: −0.15, −0.08; p < 0.00001), IOP (t = −6.47; 95% CI: −0.42, −0.23; p < 0.00001), and LVH (t = −2.15; 95% CI: −3.36, −0.29; p = 0.02). Atrial fibrillation, LVH and bradycardia may decrease the cerebral blood flow, and may also affect the ocular blood flow. Cardiac abnormalities may be associated with the development and severity of glaucoma.
Improved Admissibility Analysis of Takagi–Sugeno Fuzzy Singular Systems With Time-Varying Delays

This article investigates the admissibility analysis for Takagi–Sugeno fuzzy singular systems (T–S FSSs) with time-varying delays. First, according to the decomposed state vectors, a state decomposition Lyapunov–Krasovskii functional (LKF) is constructed, which possesses fewer decision variables. And, the LKF is augmented by considering more features of the second-order Bessel–Legendre inequality (BLI). Then, the second-order BLI and the generalized reciprocally convex matrix inequality are employed to dispose the derivative of the LKF, where the <inline-formula><tex-math notation="LaTeX">$d^{2}(t)$</tex-math></inline-formula>-dependent term exists. Meanwhile, by setting an adjustable parameter, the <inline-formula><tex-math notation="LaTeX">$d^{2}(t)$</tex-math></inline-formula>-dependent term of the condition is handled by a relaxed quadratic function negative-determination condition. As a result, a less conservative admissibility criterion for T–S FSSs is obtained. And, the relationship between the conservatism and the numerical burden is better considered. Finally, a numerical example is given to demonstrate the reduced conservatism and computational complexity.
Review of Antifouling Technologies for Aeroengine Fuel System

The serious effect of fuel fouling on aircraft and aeroengine were pointed out by analyzing the approach,method and mechanism of the fuel fouling.The control and design technologies of the aeroengine fuel system antifouling were proposed.The requirement and development trend of antifouling on the future aeroengine fuel system were discussed.