Miracle-dz/UniFAR-FTUs huggingface dataset:
E ﬀ ects of loading conditions on free surface roughening of AISI 420 martensitic stainless steel

Free surface roughening a ﬀ ects the tribological behavior of contacting bodies in multistage metal forming processes. This phenomenon was investigated on sheets of AISI 420 martensitic stainless steel by applying uniaxial and radial straining modes via tensile and Erichsen cupping tests, respectively. By means of focus variation microscopy, the free surface roughness evolution was studied for each sample at di ﬀ erent values of strain. Moreover, the microscopic deformation of grains was visualized using scanning electron microscopy and di ﬀ erential interference contrast microscopy. The results show that the free surface roughening rate in the uniaxial strain mode is higher than that in the radial one. Furthermore, the surface height distribution of the deformed surfaces was found to be dependent on the deforming strain and tended toward a Gaussian one at higher strains. Grain boundaries and chromium carbide particles were found to be responsible for the peaks formed in the roughened free surfaces. Analyses of the deformed free surfaces showed distortion of the grain morphology, which is the mechanism responsible for free surface roughening
Protective Effects of Grape Seed Procyanidin Extract on Fluoride-Induced nephrotoxicity and the possible role of Nrf2 signaling pathway

To investigate effects of uoride-induced renal damage and possible role of the Nrf2 signaling pathway and explore the protective activity of Grape Seed Procyanidin Extract (GSPE). A uoride-exposed rat model was established through drinking water. Oxidative stress parameters and serum markers that re�ect renal function were analyzed. Pathological changes were assessed using HE and TUNEL methods. Nrf2 signaling pathway-related and apoptosis-related cleaved Caspase-3 proteins were detected by Western blot. Fluoride exposure caused a signi�cant increase in serum markers of renal function, renal histopathological alterations, oxidative stress, and apoptosis. The protein expression levels of Nrf2, HO-1, and NQO-1 along the Nrf2 signaling pathway were depressed, while the cleaved Caspase-3 protein were upregulated after �uoride exposure. HE and TUNEL examination showed that the renal tissue of �uoride rats was repaired by GSPE. The level of MDA was decreased; while the level of GSH, activities of CAT, and SOD of the kidney were promoted by GSPE. Decreased serum markers such as BUN, UA, and Cr indicate a marked improvement in renal function. GSPE therapy up-regulated the expression levels of Nrf2, HO-1, NQO-1 and down-regulated cleaved Caspase-3 proteins in the kidney. Supplementary GSPE with �uoride signi�cantly alleviated its nephrotoxicity. The results above mentioned indicated that �uoride induced nephrotoxicity possibly through activate the Nrf2 signaling pathway and the presence of GSPE mitigate its nephrotoxicity.
The high-frequency limit of spectroscopy

We consider a quantum-mechanical system, initially in its ground-state, exposed to a time-dependent potential pulse, with a slowly varying envelope and a high carrier frequency. By working out a rigorous solution of the time-dependent Schrodinger equation in the high-frequency limit, we show that the linear response is completely suppressed after the switch-off of the pulse. We show, at the same time, that to the lowest order in the inverse frequency, observables are given in terms of the linear density response function, despite the problem's inherent nonlinearity. We propose a new spectroscopic technique based on these findings, which we name the Nonlinear High-Frequency Pulsed Spectroscopy (NLHFPS). An analysis of the jellium slab and jellium sphere models reveals very high surface sensitivity of NLHFPS, which produces a richer excitation spectrum than accessible within the linear regime. Combining the advantages of the extraordinary surface sensitivity, the absence of constraints by the conventional dipole selection rules, and the clarity of theoretical interpretation utilizing the linear response time-dependent density functional theory, NLHFPS emerges as a powerful characterization method in nanoscience and nanotechnology.
(2017). Circulating total bilirubin and future risk of hypertension in the general population: The prevention of renal and vascular end-stage disease (PREVEND) prospective study and a mendelian randomization approach. Journal of the American Heart Association, 6(11),

Background— Circulating total bilirubin is known to be inversely and independently associated with future risk of cardiovascular disease. However, the relationship of circulating total bilirubin with incident hypertension is uncertain. We aimed to assess the association of total bilirubin with future hypertension risk and supplemented this with a Mendelian randomization approach to investigate any causal relevance to the association. Methods and Results— Plasma total bilirubin levels were measured at baseline in the PREVEND (Prevention of Renal and Vascular End-Stage Disease) prospective study of 3989 men and women without hypertension. Hazard ratios (95% con ﬁ dence intervals) of total bilirubin with incident hypertension were assessed. New-onset hypertension was recorded in 1206 participants during a median follow-up of 10.7 years. Baseline total bilirubin was approximately log-linearly associated with hypertension risk. Age-and sex-adjusted hazard ratio for hypertension per 1-SD increase in log e total bilirubin was 0.86 (0.81 – 0.92; P < 0.001), which was attenuated to 0.94 (0.88 – 0.99; P = 0.040) after further adjustment for established risk factors and other potential confounders. The association was marginally signi ﬁ cant on further adjustment for high-sensitivity C-reactive protein (0.94; 0.88 – 1.00; P = 0.067). A genetic variant at the UGT1A1 * 28 locus consistently shown to be strongly associated with circulating bilirubin levels — rs6742078 — was not signi ﬁ cantly associated with blood pressure or hypertension ( P > 0.05 for all), arguing against a strong causal association of circulating bilirubin with blood pressure. Conclusions—
on the

Antarctic ice shelves are buttressed by numerous pinning points attaching to the otherwise freely-floating ice from below. Some of these kilometric-scale grounded features are unresolved in Antarctic-wide datasets of ice thickness and bathymetry, hampering ice flow models to fully capture dynamics at the grounding line and upstream. We investigate the role of an 8.7 km 2 pinning point at the front of the Roi Baudouin Ice Shelf, East Antarctica. Using ERS interferometry and ALOS-PALSAR speckle tracking, we derive, on a 125 m grid spacing, surface velocities deviating by − 5.2 ± 4.5 m a − 1 from 37 on-site global navigation satellite systems-derived velocities. We find no evidence for ice flow changes on decadal time scales and we show that ice on the pinning point virtually stagnates, deviating the ice stream and causing enhanced horizontal shearing upstream. Using the BISICLES ice-flow model, we invert for basal friction and ice rigidity with three input scenarios of ice velocity and geometry. We show that inversion results are the most sensitive to the presence/absence of the pinning point in the ba-thymetry; surface velocities at the pinning point are of secondary importance. Undersampling of pinning points results in erroneous ice-shelf properties in models initialised by control methods. This may impact prognostic modelling for ice-sheet evolution in the case of unpinning.
Model Study of Reservoir Riprap Stability

A series of large scale (1:15) experiments have been undertaken to assist the Societe d'Energie de la Baie James (SEBJ) in the development of new design guidelines for riprap. The stability of revetments resting on 1:1.8 and 1:2.25 (V:H) slopes is considered. In an attempt to quantify the relative roles of stone size, gradation and armour layer thickness, these tests were undertaken with stone gradations varying from (Mmax/Mmin ranging from 1 to 10) and with armour layers both 2.2Dn50 and 2.7Dn50 thick.
Mobility Aware Virtual Network Embedding

Over the last years, network virtualization has become one of the most promising solutions for sustainability towards the ongoing increase of data demand in mobile networks. Within that context, the virtual network embedding problem has recently been studied extensively and many different solutions have been proposed; but, mainly these studies have focused on wired networks. The main purpose of this paper is to provide an optimization framework for optimal virtual network embedding, including a heuristic algorithm with low computational complexity, by explicitly considering the effect of supporting the actual user mobility, assuming the emerging Distributed Mobility Management (DMM) scheme as well as a traditional Centralized Mobility Management (CMM) scheme. In addition to that, service differentiation is introduced, giving higher priority to time-critical over-the-top (OTT) services compared to more traditional elastic Internet applications. The performance of the proposed framework is compared to mobility agnostic greedy algorithms as well as virtual network embedding algorithms from the literature. Numerical investigations reveal that the effect of user mobility has a significant impact on the design of virtual networks. Additionally, the mobility aware scheme can provide tangible gains in the overall performance compared with the previous proposed schemes that do not take explicitly into account the effect of user mobility.
A Land and Ocean Microwave Cloud Classiﬁcation Algorithm Derived from AMSU-A and -B, Trained Using MSG-SEVIRI Infrared and Visible Observations

A statistical cloud classiﬁcation and cloud mask algorithm is developed based on Advanced Microwave Sounding Unit (AMSU-A and -B) microwave (MW) observations. The visible and infrared data from the Meteosat Third Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) are used to train the microwave classiﬁer. The goal of the MW algorithms is not to fully reproduce this MSG-SEVIRI cloud classiﬁcation, as the MW observations do not have enough information on clouds to reach this level of precision. The objective is instead to obtain a stand-alone MW cloud mask and classiﬁcation algorithm that can be used efﬁciently in forthcoming retrieval schemes of surface or atmospheric parameters from microwave satellite observations. This is an important tool over both ocean and land since the assimilation of the MW observations in the operational centers is independent from the other satellite observations. Clear sky and low, medium, and opaque–high clouds can be retrieved over ocean and land at a conﬁdence level of more than 80%. An information content analysis shows that AMSU-B provides signiﬁcant information over both land and ocean, especially for the classiﬁcation of medium and high clouds, whereas AMSU-A is more efﬁcient over ocean when discriminating clear situations and low clouds.
Enzymatic modi�cation of plant proteins for improved functional and bioactive properties

Plant-based proteins have shown great potential as an alternative substitute for animal proteins to meet the increasing global demand. Nevertheless, several limitations mitigate plant-based protein application and utilization. As a panacea to meeting the market demand, it is imperative to modify plant-based proteins to produce improved quality and techno-functionalities compared to conventional animal protein ingredients. Enzymatic, chemical, and physical modi�cations have been used for plant-based proteins, which has shown exciting results in improving their techno-functional properties, digestibility, and inherent allergenicity. Among these modi�cation methods, the low cost, limited time, high sensitivity, and high reproducibility give enzymatic modi�cation leverage over chemical and physical methods. This review gave a concise summary of the advantages and disadvantages of enzymatic modi�cations. The e�cacy of enzymatic modi�cation in producing protein ingredients from plant sources with improved techno-functional properties, digestibility, and alleviated allergenicity was discussed. Furthermore, the application of enzymatic modi�cation in the production of bioactive compounds with health-benecial properties adds in no small measure to the novelty of this review.
Optimization of the IIASA’s FLAM model to represent forest fires in South Korea

Global risk of forest fires is amplified by the climate change driven heat waves, leading to more intensive biomass burning, which create a vicious cycle by accelerating the climate change. Despite of the growing risk of forest fires, a response system in South Korea, where more than 60% of its land is forest, is still focusing on posterior measures. To improve preventive measures, forest fire model needs to be developed for assessment of future risks of forest fires and burned areas. In this context, this study aims at optimization of the IIASA’s FLAM – a processed based model integrating both biophysical and human impacts – to the environment of South Korea for projecting the pattern and scale of future forest fires. The following model developments were performed in the study: 1) optimization of probability algorithms in FLAM, including ignition probabilities conditional on population density, lightning frequency, and fuel taking into account distance to cropland, based on the national GIS data downscaled to 1 km 2 , and 2) improvement of fuel moisture computation by adjusting Fine Fuel Moisture Code (FFMC) used by FLAM to represent feedbacks with vegetation; this was done by fitting soil moisture to the daily remote sensing data, 3) deeper look at the fire frequency in addition to areas burned simulated by FLAM. Our results show that the optimization has considerably improved the modelling of seasonal pattern of forest fire frequency. After optimization Pearson’s correlation coefficient between monthly predictions and observations from national statistics was improved from 0.171 in non-optimized version to 0.893 in the optimized version of FLAM. These findings imply that even though FLAM already contained main algorithms for interpreting biophysical and human impact on forest fire at a global scale, they were applicable to South Korea only after optimization of all its modules. In addition, as the optimization succeed to reproduce the national specific pattern of forest fire, it should be followed by the research for developing adaptation strategies corresponding to the projected risks of future forest fires.
Ocean acidiﬁcation enhances primary productivity and nocturnal carbonate dissolution in intertidal rock pools

Human CO 2 emissions are modifying ocean carbonate chemistry, causing ocean acidiﬁcation and likely already impacting marine ecosystems. In particular, there is concern that coastal, benthic calcifying organisms will be negatively affected by ocean acidiﬁcation, a hypothesis largely supported by laboratory studies. The inter-relationships between carbonate chemistry and marine calcifying communities in situ are complex, and natural meso-cosms such as tidal pools can provide useful community-level insights. In this study, we manipulated the carbonate chemistry of intertidal pools to investigate the inﬂuence of future ocean acidiﬁcation on net community production (NCP) and calciﬁcation (NCC) at emersion. Adding CO 2 at the start of the tidal emersion to simulate future acidiﬁca-tion ( + 1500 µatm p CO 2 , target pH 7.5) modiﬁed net production and calciﬁcation rates in the pools. By day, pools were fertilized by the increased CO 2 ( + 20 % increase in NCP, from 10 to 12 mmol O 2 m − 2 h − 1 ), while there was no measurable impact on NCC. During the night, pools experienced net community dissolution (NCC < 0), even under present-day conditions, when waters were supersatu-rated with regard to aragonite. Adding CO 2 to the pools increased nocturnal dissolution rates by 40 % (from − 0.7 to − 1.0 mmol CaCO 3 m − 2 h − 1 ) with no consistent impact on nocturnal community respiration. Our results suggest that ocean acidiﬁcation is likely to alter temperate intertidal community metabolism on sub-daily timescales, enhancing both diurnal community production and nocturnal calcium carbonate dissolution
Three‐dimensional mantle circulations and lateral slab deformation in the southern Chilean subduction zone

The along‐strike variation in plate properties is a common feature in the subduction zones. The southern Chilean subduction is a notable example where the slab age and length, and the thickness of the overriding plate, vary substantially in the trench‐parallel direction. In this study the combined effects of these factors are examined using regional subduction zone models. In the models lateral slab deformation and along‐arc pressure gradient in the mantle occur in response to the differential slab retrograde motion due to variations in slab buoyancy and slab strength. The lower portion of the deep segments acts as a slab edge in part, while rollback of the neighboring, shallower segments influences the toroidal motion induced by the adjacent deep segments. These factors together give rise to complex flow patterns and lead to a great extent of trench‐parallel components in the mantle wedge and subslab mantle and significant upwelling in the back arc. Mantle circulations are characterized by variable length scales for both toroidal and poloidal motions extending over ~ 1500 km. Such three‐dimensional circulations may lead to complicated patterns of seismic anisotropy. The upwelling may result in decompression melting to cause the extensive Patagonian plateau basalts. Our model results indicate that certain segments of the Antarctic slab reach at least 100 km depth. The trajectories of passive tracers show intricate patterns such as helical streamlines and suggest that a recent input from the adjacent subduction zone for slab‐derived components of lavas from the Chilean Ridge cannot be ruled out.
Students’ Perception of Collaborative Project Management Tools in Programming-Based Projects: The Case of GitHub

Project management tools aim to support developers throughout the development phases and help them manage projects successfully. GitHub is the largest and most advanced software development platform developers and companies use to help with version control, collaborative development, task administration, project hosting, etc. GitHub is utilized in classrooms, coursework, and most often in group project assignments; students rely on GitHub in various coding and management activities such as collaborative coding, submitting assignments, sharing tasks, and code review. Applying such tools in education aroused the interest of educators and researchers in studying the implication on students' performance and measuring the adoption of this promising technology. The main goal of this paper is to demonstrate the effectiveness and the acceptance of using the collaborative project management tool (GitHub) for students in programming-based projects using the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model adopted with collaborative learning and learning value as external variables. Overall, the result shows that students' behavioral intention to use GitHub was significantly influenced by performance expectancy, collaborative learning, and habit. Besides, GitHub use was influenced considerably by facilitating conditions and habit. In addition, collaborative learning has a significant impact on students’ performance expectancy.
Opt-RNN-DBFSVM: Optimal recurrent neural network density based fuzzy support vector machine

When implementing SVMs, two major problems are encountered: (a) the number of local minima increases exponentially with the number of samples and (b) the quantity of required computer storage, required for a regular quadratic programming solver, increases by an exponential magnitude as the problem size expands. The Kernel-Adatron family of algorithms gaining attention lately which has allowed to handle very large classification and regression problems. However, these methods treat different types of samples (Noise, border, and core) with the same manner, which causes searches in unpromising areas and increases the number of iterations. In this work , we introduce a hybrid method to overcome these shortcoming, namely Optimal Recurrent Neural Network Density Based Support Vector Machine (Opt-RNN-DBSVM). This method consists of four steps: (a) characterization of different samples, (b) elimination of samples with a low probability of being a support vector, (c) construction of an appropriate recurrent neural network based on an original energy function, and (d) solution of the system of differential equations, managing the dynamics of the RNN, using the Euler-Cauchy method involving an optimal time step. Thanks to its recurrent architecture, the RNN remembers the regions explored during the search process. We demonstrated that RNN-SVM converges to feasible support vectors and Opt-RNN-DBSVM has a very low time complexity compared to RNN-SVM with constant time step, and KAs-SVM. Several experiments were performed on academic data sets. We used several classification performance measures to compare Opt-RNN-DBSVM to different classification methods and the results obtained show the good performance of the proposed method.
2P-FLIM unveils time-dependent metabolic shifts during osteogenic differentiation with a key role of lactate to fuel osteogenesis via glutaminolysis identi�ed

I. Background: Human mesenchymal stem cells (hMSCs) fuel discrete biosynthetic pathways to multiply and differentiate into speci�c cell lineages; with undifferentiated hMSCs showing reliance on glycolytic respiration. hMSCs differentiating towards an osteogenic phenotype rely on oxidative phosphorylation as an energy source. Two-photon �uorescence lifetime imaging (2P-FLIM) is a powerful technique for non-invasive probing and monitoring of cellular metabolism; and we hypothesize that we can use this approach to monitor the osteogenic differentiation of hMSCs to uncover potential routes to boost hMSC differentiation based on their metabolic behaviour. II. Methods: The metabolic pro�le of hMSCs was pro�led during osteogenic differentiation over 14 days using 2P-FLIM to image and measure NADH �uorescence. We validated this metabolic pro�le using qPCR and extracellular metabolite analysis. Upon revealing a higher dependence on glutaminolysis; we sought to drive glutaminolysis further during using the metabolite lactate. In order to establish the importance of glutaminolysis and lactate metabolism in osteogenic differentiation these metabolic pathways were shut down using Bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulphide (BPTES) and α -cyano-4-hydroxycinnamic acid ( α -CHC) respectively. III. Results: During osteogenesis, we observe a higher dependence on oxidative phosphorylation for cellular energy; and a higher reliance on glutaminolysis in the earlier time-points of osteogenic differentiation. Driving glutaminolysis further using lactate supplementation led to higher levels of mineral deposition and osteogenic gene expression. This supplementation promoted upregulation of lactate metabolism and increased the expression of transmembrane cellular lactate transporters. Higher rates of lactate dehydrogenase gene expression coupled with higher NADH �uorescence intensity demonstrate a conversion of lactate to pyruvate. During this conversion, NADH is formed by the reverse enzymatic reaction of lactate dehydrogenase resulting in increased