Nanofluid based on 1-dodecylpyridinium chloride for enhanced oil recovery

The use of nanoparticles is considered promising for enhanced oil recovery(EOR),especially when they are combined with surfactants.However,the combination of nano-sized material with surface-active ionic liquids(SAILs)is an unexplored EOR method.In this work,the advantages of mixing Al2O3 nanoparticles with the SAIL 1-dodecylpyridinium chloride were investigated.Stable nanofluids in brine could only be achieved using the polymer polyvinylpyrrolidone(PVP)as a stabilizing agent.It was found that the addition of nanoparticles(and PVP)to the surfactant formulation helped to:slightly increase its viscosity,enhance its water-oil interfacial tension(IFT)reduction capacity,and reduce the adsorption on carbonate rocks(adsorption on sandstone was found to be excessive).IFT was selected as target property to minimize for the design of EOR formulations.Core flooding tests were carried out with surfactant(0.5 wt%[C_(12)py]Cl),surfactant-polymer(0.5 wt%[C_(12)py]Cl,1.0 wt%PVP)and nanofluid(0.05 wt%Al_(2)O_(3),1.0 wt%PVP,0.5 wt%[C12py]Cl)formulations in brine(0.5 wt%NaCl).Additional oil recoveries of 3.4%,7.4%and 12.0%OOIP were achieved,respectively,the nanofluid formulation being the most promising for the application.Moreover,it was found capable of changing the wettability of carbonate rocks from oilwet to intermediate-wet.The significance of this work lies in showing the new possibilities resulting from the combination of SAILs and nanoparticles for EOR,specifically the combination of[C_(12)py]Cl with Al_(2)O_(3).

Numerical Simulation of Bed Load and Suspended Load Sediment Transport Using Well-Balanced Numerical Schemes

Sediment transport can be modelled using hydrodynamic models based on shallow water equations coupled with the sediment concentration conservation equation and the bed con-servation equation.The complete system of equations is made up of the energy balance law and the Exner equations.The numerical solution for this complete system is done in a seg-regated manner.First,the hyperbolic part of the system of balance laws is solved using a finite volume scheme.Three ways to compute the numerical flux have been considered,the Q-scheme of van Leer,the HLLCS approximate Riemann solver,and the last one takes into account the presence of non-conservative products in the model.The discretisation of the source terms is carried out according to the numerical flux chosen.In the second stage,the bed conservation equation is solved by using the approximation computed for the system of balance laws.The numerical schemes have been validated making comparisons between the obtained numerical results and the experimental data for some physical experiments.The numerical results show a good agreement with the experimental data.

Phylogeography of SARS-CoV-2 pandemic in Spain:a story of multiple introductions,micro-geographic stratification,founder effects,and super-spreaders

Spain has been one of the main global pandemic epicenters for coronavirus disease 2019(COVID-19).Here,we analyzed>41000 genomes(including>26000 high-quality(HQ)genomes)downloaded from the GISAID repository,including 1245(922 HQ)sampled in Spain.The aim of this study was to investigate genome variation of novel severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)and reconstruct phylogeographic and transmission patterns in Spain.Phylogeographic analysis suggested at least 34 independent introductions of SARS-CoV-2 to Spain at the beginning of the outbreak.Six lineages spread very successfully in the country,probably favored by super-spreaders,namely,A2 a4(7.8%),A2 a5(38.4%),A2 a10(2.8%),B3 a(30.1%),and B9(8.7%),which accounted for 87.9% of all genomes in the Spanish database.One distinct feature of the Spanish SARS-Cov-2 genomes was the higher frequency of B lineages(39.3%,mainly B3 a+B9)than found in any other European country.While B3 a,B9,(and an important sub-lineage of A2 a5,namely,A2 a5 c)most likely originated in Spain,the other three haplogroups were imported from other European locations.The B3 a strain may have originated in the Basque Country from a B3 ancestor of uncertain geographic origin,whereas B9 likely emerged in Madrid.The time of the most recent common ancestor(TMRCA)of SARS-CoV-2 suggested that the first coronavirus entered the country around 11 February 2020,as estimated from the TMRCA of B3 a,the first lineage detected in the country.Moreover,earlier claims that the D614 G mutation is associated to higher transmissibility is not consistent with the very high prevalence of COVID-19 in Spain when compared to other countries with lower disease incidence but much higher frequency of this mutation(56.4% in Spain vs.82.4% in rest of Europe).Instead,the data support a major role of genetic drift in modeling the micro-geographic stratification of virus strains across the country as well as the role of SARS-CoV-2 super-spreaders.

CONTROLLABILITY AND OPTIMALITY OF LINEAR TIME-INVARIANT NEUTRAL CONTROL SYSTEMS WITH DIFFERENT FRACTIONAL ORDERS

Control systems governed by linear time-invariant neutral equations with different fractional orders are considered. Sufficient and necessary conditions for the controllability of those systems are established. The existence of optimal controls for the systems is given. Finally, two examples are provided to show the application of our results.

Local and generalized height-diameter models with random parameters for mixed,uneven-aged forests in Northwestern Durango,Mexico

Background:We used mixed models with random components to develop height-diameter(h-d) functions for mixed,uneven-aged stands in northwestern Durango(Mexico),considering the breast height diameter(d) and stand variables as predictors.Methods:The data were obtained from 44 permanent plots used to monitor stand growth under forest management in the study area.Results:The generalized Bertalanffy-Richards model performed better than the other generalized models in predicting the total height of the species under study.For the genera Pinus and Quercus,the models were successfully calibrated by measuring the height of a subsample of three randomly selected trees close to the mean d,whereas for species of the genera Cupressus,Arbutus and Alnus,three trees were also selected,but they are specifically the maximum,minimum and mean d trees.Conclusions:The presented equations represent a new tool for the evaluation and management of natural forest in the region.

Developing a dynamic growth model for teak plantations in India

Background： Tectono grandis （teak） is one of the most important tropical timber species occurring naturally in India. Appropriate growth models, based on advanced modeling techniques, are not available but are necessary for the successful management of teak stands in the country. Long-term forest planning requires mathematical models and the principles of Dynamical System Theory provide a solid foundation for these. Methods： The state-space approach makes it possible to accommodate disturbances and avarying environment. In this paper, an attempt has been made to develop a dynamic growth model based on the limited data, consisting of three annual measurements, collected from 22 teak sample plots in Karnataka, Southern India. Results： A biologically consistent whole-stand growth model has been presented which uses the state-space approach for modelling rates of change of three state-variables viz., dominant height, stems per hectare and stand basal area. Moreover, the model includes a stand volume equation as an output function to estimate this variable at any point in time. Transition functions were fitted separately and simultaneously. Moreover, a continuous autoregressive error structure is also included in the modelling process. For fitting volume equation, generalized method of moments was used to get efficient parameter estimates under heteroscedastic conditions. Conclusions： A simple model containing few free parameters performed well and is particularly well suited to situations where available data is scarce.

Serotonin controls axon and neuronal regeneration in the nervous system:lessons from regenerating animal models

Traumatic brain injury （TBI） is a mechanical injury to brain tissue that leads to an impairment of function and a broad spectrum of symptoms and disabilities; often, it is followed by diffuse axonal injury, which causes denaturation of the white matter and axon retraction, leaving patients with severe brain damage or even in a persistent vegetative state.

Is the present cut-point to define type 2 diabetes appropriate in Latin-Americans?

The diagnosis of diabetes mellitus type 2(DM2) is based either on increased plasma glucose or Glycated hemoglobin levels. Since these measures are the only means for diagnosis of DM2, they must be well adapted to each population according to their metabolic characteristics, given that these may vary in each population. The World Health Organization(WHO) determined the cut-points of plasma glucose levels for the diagnosis of DM2 by associating hyperglycemia with the risk of a specific microvascular complication-retinopathy. Cardiovascular diseases are however the principal causes of mortality in patients with DM2 and we reported that in the Colombo-Ecuadorian population impaired fasting glucose and impaired glucose tolerance are both riskmarkers for myocardial infarction. We propose that the current cut-points accepted by the WHO need to be revaluated in populations such as Latin America and that there should be lower cut points for glycaemia in this population, to reduce the prevalence of cardiovascular complications associated with DM2.

Alzheimer’s Disease Diagnosis Based on a Semantic Rule-Based Modeling and Reasoning Approach

Alzheimer’s disease(AD)is a very complex disease that causes brain failure,then eventually,dementia ensues.It is a global health problem.99%of clinical trials have failed to limit the progression of this disease.The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms.Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction.In this regard,the need becomes more urgent for biomarker-based detection.A key issue in understanding AD is the need to solve complex and high-dimensional datasets and heterogeneous biomarkers,such as genetics,magnetic resonance imaging(MRI),cerebrospinal fluid(CSF),and cognitive scores.Establishing an interpretable reasoning system and performing interoperability that achieves in terms of a semantic model is potentially very useful.Thus,our aim in this work is to propose an interpretable approach to detect AD based on Alzheimer’s disease diagnosis ontology(ADDO)and the expression of semantic web rule language(SWRL).This work implements an ontology-based application that exploits three different machine learning models.These models are random forest(RF),JRip,and J48,which have been used along with the voting ensemble.ADNI dataset was used for this study.The proposed classifier’s result with the voting ensemble achieves a higher accuracy of 94.1%and precision of 94.3%.Our approach provides effective inference rules.Besides,it contributes to a real,accurate,and interpretable classifier model based on various AD biomarkers for inferring whether the subject is a normal cognitive(NC),significant memory concern(SMC),early mild cognitive impairment(EMCI),late mild cognitive impairment(LMCI),or AD.

EXISTENCE OF SOLUTIONS OF nTH-ORDER NONLINEAR DIFFERENCE EQUATIONS WITH GENERAL BOUNDARY CONDITIONS

The aim of this paper is to prove the existence of one or multiple solutions of nonlinear difference equations coupled to a general set of boundary conditions.Before to do this,we construct a discrete operator whose fixed points coincide with the solutions of the problem we are looking for.Moreover,we introduce a strong positiveness condition on the related Green's function that allows us to construct suitable cones where to apply adequate fixed point theorems.Once we have the general existence result,we deduce,as a particular case,the existence of solutions of a second order difference equation with nonlocal perturbed Dirichlet conditions.

Oil recovery tests with ionic liquids: A review and evaluation of 1-decyl-3-methylimidazolium triflate

The main advantages of the use of ionic liquids in enhanced oil recovery are their tunability and stability in harsh environmental conditions. In this work, a comprehensive review of ionic liquids proposed to improve current chemical oil recovery methods has been presented, focusing on core flooding experiments. With an almost infinite number of possible ionic liquids, the amount of experiments carried out up to now has been very limited. However, results are promising, with additional recovery after secondary flooding of up to 32% of the original oil in place. Most formulations with ionic liquids have been proposed for sandstone reservoirs, the number of studies with carbonate cores being very scarce. The possibilities of a new room temperature surface active ionic liquid, 1-decyl-3-methylimidazolium triflate,for this application were analyzed. It was shown that it is able to drastically reduce the water/oil interfacial tension. An optimized formulation was proposed for carbonate reservoirs. After secondary flooding with brine, an additional recovery of 10.5% of original oil in place was achieved at room conditions. A combination of the proposed method followed by a polymer flooding step with polyacrylamide led to a lesser but still significant recovery, reducing the costs associated to the ionic liquid.

Modelling fuel loads of understorey vegetation and forest floor components in pine stands in NW Spain

In this study,310 destructively sampled plots were used to develop two equation systems for the three main pine species in NW Spain(P.pinaster;P.radiata and P.sylvestris):one for estimating loads of understorey fuel components by size and condition(live and dead)and another one for forest floor fuels.Additive systems of equations were simultaneously fitted for estimating fuel loads using overstorey,understorey and forest floor variables as regressors.The systems of equations included both the effect of pine species and the effect of understorey compositions dominated by ferns-brambles or by woody species,due to their obvious structural and physiological differences.In general,the goodness-of-fit statistics indicated that the estimates were reasonably robust and accurate for all of the fuel fractions.The best results were obtained for total understorey vegetation,total forest floor and raw humus fuel loads,with more than 76%of the observed variability explained,whereas the poorest results were obtained for coarse fuel loads of understory vegetation with a 53%of observed variability explained.To reduce the overall costs associated with the field inventories necessary for operational use of the models,the additive systems were fitted again using only overstorey variables as potential regressors.Only relationships for fine(<6 mm)and total understorey vegetation and total forest floor fuel loads were obtained,indicating the complexity of the forest overstorey-understorey and overstorey-forest floor relationships.Nevertheless,these models explained around 52%of the observed variability.Finally,equations estimating the total understorey vegetation and the total forest floor fuel loads based only on canopy cover were fitted.These models explained only 26%-32%of the observed variability;however,their main advantage is that although understorey vegetation in forested landscapes is largely invisible to remote sensing,canopy cover can be estimated with moderate accuracy,allowing for landscape-scale estimates of total fuel loads.The equations represent an appreciable advance in understorey and forest floor fuel load assessment in the region and areas with similar characteristics and may be instrumental in generating fuel maps,fire management improvement and better C storage assessment by vegetation type,among many other uses.

Overlapping Shadow Rendering for Outdoor Augmented Reality

Realism rendering methods of outdoor augmented reality(AR)is an interesting topic.Realism items in outdoor AR need advanced impacts like shadows,sunshine,and relations between unreal items.A few realistic rendering approaches were built to overcome this issue.Several of these approaches are not dealt with real-time rendering.However,the issue remains an active research topic,especially in outdoor rendering.This paper introduces a new approach to accomplish reality real-time outdoor rendering by considering the relation between items in AR regarding shadows in any place during daylight.The proposed method includes three principal stages that cover various outdoor AR rendering challenges.First,real shadow recognition was generated considering the sun’s location and the intensity of the shadow.The second step involves real shadow protection.Finally,we introduced a shadow production algorithm technique and shades through its impacts on unreal items in the AR.The selected approach’s target is providing a fast shadow recognition technique without affecting the system’s accuracy.It achieved an average accuracy of 95.1%and an area under the curve(AUC)of 92.5%.The outputs demonstrated that the proposed approach had enhanced the reality of outside AR rendering.The results of the proposed method outperformed other state-of-the-art rendering shadow techniques’outcomes.

Pitfalls of barcodes in the study of worldwide SARSCoV-2 variation and phylodynamics

DEAR EDITOR,Analysis of SARS-CoV-2 genome variation using a minimal number of selected informative sites conforming a genetic barcode presents several drawbacks.We show that purely mathematical procedures for site selection should be supervised by known phylogeny(i)to ensure that solid tree branches are represented instead of mutational hotspots with poor phylogeographic proprieties,and(ii)to avoid phylogenetic redundancy.We propose a procedure that prevents information redundancy in site selection by considering the cumulative informativeness of previously selected sites(as a proxy for phylogenetic-based criteria).This procedure demonstrates that,for short barcodes(e.g.,11 sites),there are thousands of informative site combinations that improve previous proposals.We also show that barcodes based on worldwide databases inevitably prioritize variants located at the basal nodes of the phylogeny,such that most representative genomes in these ancestral nodes are no longer in circulation.Consequently,coronavirus phylodynamics cannot be properly captured by universal genomic barcodes because most SARS-CoV-2 variation is generated in geographically restricted areas by the continuous introduction of domestic variants.

Semantic Pneumonia Segmentation and Classification for Covid-19 Using Deep Learning Network

Early detection of the Covid-19 disease is essential due to its higher rate of infection affecting tens of millions of people,and its high number of deaths also by 7%.For that purpose,a proposed model of several stages was developed.The first stage is optimizing the images using dynamic adaptive histogram equalization,performing a semantic segmentation using DeepLabv3Plus,then augmenting the data by flipping it horizontally,rotating it,then flipping it vertically.The second stage builds a custom convolutional neural network model using several pre-trained ImageNet.Finally,the model compares the pre-trained data to the new output,while repeatedly trimming the best-performing models to reduce complexity and improve memory efficiency.Several experiments were done using different techniques and parameters.Accordingly,the proposed model achieved an average accuracy of 99.6%and an area under the curve of 0.996 in the Covid-19 detection.This paper will discuss how to train a customized intelligent convolutional neural network using various parameters on a set of chest X-rays with an accuracy of 99.6%.

Study of Human Serum Albumin-SPIONs Loaded PLGA Nanoparticles for Protein Delivery

The Biodegradable nanoparticles from poly(lactic-co-glycolic acid) (PLGA) have been extensively investigated for sustained and targeted/localized delivery of different agents. Many parameters are required in the synthesis of a biodegradable polymeric nanoparticle. We report the synthesis of human serum albumin (HSA)-superparamagnetic iron oxide nanoparticles (SPIONs) loaded PLGA nanoparticles. All nanoparticles were characterized using a TEM image, UV-Vis spectroscopy measurements, Zeta Potential, and PPMS for magnetizations. This study described and investigated the interesting phenomenon in the synthesis development of HSA-SPIONs loaded PLGA nanoparticles. The result showed that the stability of HSA-SPIONs loaded PLGA nanoparticles for potential applications such as in protein delivery.

Performances of an Active Target GEM-Based TPC for the AMADEUS Experiment

In this paper, we present the R & D activity on a new GEM-based Time Projection Chamber (GEM-TPC) detector for the inner region of the AMADEUS experiment, which is aiming to perform measurements of low-energy negative kaon interactions in nuclei at the DAΦNE e+ e- collider at LNF-INFN. A novel idea of using a GEM-TPC as a low mass target and detector at the same time comes motivated by the need of studying the low energy interactions of K- with nuclei in a complete way, tracking and identifying all of the produced particles. Even more, what makes the experimental proposal revolutionary is the possibility of using different gaseous targets without any other substantial intervention on the experimental setup, making it a flexible multipurpose device. This new detection technique applied to the nuclear physics requires the use of low-radiation length materials and very pure light gases such as Hydrogen, Deuterium, Helium-3, Helium-4, etc. In order to evaluate the GEM-TPC performances, a 10 × 10 cm2 prototype with a drift gap of 15 cm has been realized. The detector was tested at the πM1 beam facility of the Paul Scherrer Institut (PSI) with low momentum pions and protons. Detection efficiency and spatial resolution, as a function of gas mixture, gas gain and ionazing particle, are reported and discussed.

Synthesis and applications of lanthanoid complexes of pentadentate and hexadentate N_(5) and N_(6) macrocycles:A review

In this paper,the lanthanoid complexes of N_(5) and N_(6) macrocycle ligands,without pendant arms or additional heteroatoms,are surveyed.This review covers the period from 2015 to the current date,since in 2014 Schiff base macrocyclic ligands incorporating the pyridine moiety,and their complexes,were revised,and in 2015 the chemistry of pentaaza macrocycle ligands with rare earth metals was also summarized.Porphyrin and phthalocyanine ligands are not included in this review,which primarily focuses on complexes with Schiff bases and amines without pendant arms or any additional donor other than nitrogen.The synthetic methods,structural characterization,based on single X-ray crystal data,and properties of the lanthanoid complexes,with special attention to magneto-structural correlations,are presented herein.

Land-use change and windstorms legacies drove the recolonization dynamics of laurel forests in Tenerife, Canary islands

Laurel forests are quite relevant for biodiversity conservation and are among the island ecosystems most severely damaged by human activities.In the past,Canary laurel forests have been greatly altered by logging,livestock and agriculture.The remains of laurel forests are currently protected in the Canary Islands(Spain).However,we miss basic information needed for their restoration and adaptive management,such as tree longevity,growth potential and responsiveness to natural and anthropogenic disturbances.Using dendrochronological methods,we studied how forest dynamic is related to land-use change and windstorms in two well-preserved laurel forests on Tenerife Island.Wood cores were collected from over 80 trees per stand at three stands per forest.We used ring-width series to estimate tree ages and calculate annual basal area increments(BAI),cumulative diameter increases,and changes indicative of released and suppressed growth.Twelve tree species were found in all stands,with Laurus novocanariensis,Ilex canariensis and Morella faya being the most common species.Although some individuals were over 100 years old,61.8%-88.9% of the trees per stand established between 1940 and 1970,coinciding with a post-war period of land abandonment,rural exodus and the onset of a tourism economy.Some trees have shown growth rates larger than 1 cm diameter per year and most species have had increasing BAI trends over the past decades.Strong growth releases occurred after windstorms at both sites,but the effects of windstorms were site-dependent,with the 1958 storm affecting mainly the eastern tip of the island(Anaga massif)and the 1991 storm the western tip(Teno massif).Given the great ability of laurel forest trees to establish after land use cessation and to increase growth after local disturbances such as windstorms,passive restoration may be sufficient to regenerate this habitat in currently degraded areas.

Search for the doubly heavy baryon Ξ_(bc)^(+)→ decaying to J/ψΞ_(c)^(+)

A first search for the Ξ_(bc)^(+)J/ψΞ_(c)^(+) decay is performed by the LHCb experiment with a data sample of proton-proton collisions, corresponding to an integrated luminosity of 9 fb−1 recorded at centre-of-mass energies of 7, 8, and 13 TeV. Two peaking structures are seen with a local (global) significance of 4.3(2.8) and 4.1(2.4) standard deviations at masses of 6571 and 6694 MeV/c2, respectively. Upper limits are set on the Ξ+bc baryon production cross-section times the branching fraction relative to that of the B+c→J/ψD+s decay at centre-of-mass energies of 8 and 13 TeV, in the Ξ+bc and in the B+c rapidity and transverse-momentum ranges from 2.0 to 4.5 and 0 to 20GeV/c, respectively. Upper limits are presented as a function of the Ξ+bc mass and lifetime.