Using genus theory, the existence of infinitely many solutions for an anisotropic equation involves subcritical growth is proved. Also by using Krasnoselskii genus and Clark’s theorem, the existence of $k$-pairs of distinct solutions is proved. Finally, the anisotropic equation involves critical growth is considered and the existence of infinitely many solutions is proved.

The optical properties, electronic charge density, electronic structure of the new layered selenides materials, BaGdCuSe3, CsUCuSe3, CsZrCuSe3, and CsGdZnSe3 compounds have been calculated by using the full potential and linear augmented plane wave (FP-LAPW) methods as applied in the WIEN2k package, which is based on the density functional theory. The ALnMSe3 compound’s structure of these was (A= Cs, Ba; Ln = Zr, Gd, U; M= Cu, Zn) is composed of ] (n = 1, 2) layers, which might be separated by A atoms. It is to be observed that there is strong hybridization has been observed between the s, p, and d states of Zr, Gd, and Cu atoms. As the charge density contour, around the gadolinium atom, the charge density contours are completely circular, but the Gadolinium “Gd” atom shows an ionic nature. To calculate the refractive index, we used Kramer’s Kronig correlations with the imaginary part. The decrease in the refractive index is due to the lack of probability for direct excitation of the electrons, resulting in a loss of energy. The value of the static refractive index for all reference compounds is about 1.75 ~ 2.25.

A document by Chayma Soltani. Click on the document to view its contents.

This case report describes a patient with non-occlusive mesenteric ischemia that developed due to diabetic ketoacidosis. We believe that early diagnosis and intervention may improve the prognosis of non-occlusive mesenteric ischemia that has low vascular risk, with the major risk factor being dehydration due to diabetic ketoacidosis.

Desert expansions can cause tremendous losses to human well-being. However, the process of shifting from the non-desert state to the desert state, a representation of a system regime shift, remains unclear on the global scale. Clarifying the underpinning pattern, predictors and signals of this process is of great value in advancing understanding of both ecosystem resilience and sustainable developments. Here, we combine the climate classification map and long-term observational land cover data to assess the global desert distribution and its changes from 2000 to 2019. The identified desert areas cover approximately 7.53% of the global land in the past two decades. Only approximately 16.03% of these deserts shows expanding trends, especially in countries such as Tunisia, Tajikistan and Peru. After assessing 26 climatic, ecological and socioeconomic factors that could potentially modify desert expansion rates, vegetation cover diversity was identified as the strongest predictor in both hot and cold deserts, followed by cattle density in hot deserts and desert size in cold deserts. In addition, pronounced high fluctuation in satellite vegetation productivity and flickering between land cover states could serve as two signals for desert conversion and fast expansion, respectively. Our results provide not only a long-term overview of global desert changing patterns but also possible guidance for constraining desert expansion.

Implementation of the Natural Forest Protection Project and Grain for Green Programme in China has promoted forest restoration, increased productivity, and enhanced the carbon stocks. However, few studies have characterized temporal and spatial variation in productivity and ecological stability in planted and natural forests and evaluated the factors driving such variation. In this study, we used 1399 permanent forest plots to identify change patters in the productivity and temporal stability of above-ground biomass (AGB) and evaluated the factors driving these changes in planted and natural forests in Sichuan Province, China. The mean temporal stability of AGB was higher for natural forest than for planted forest from 1979 to 2017; While, the productivity of planted forest was higher. The stability decreased at a rate of -0.013 yr-1 in entire natural forest and -0.011 yr-1 in planted forests, and the productivity of natural forest decreased significantly over time, with a slope of -0.0065 Mg ha-1 yr-1 per calendar year. Altitude, latitude, annual precipitation, and stand age dominated variability in the productivity and AGB stability of natural forest. Richness, tree density, and stand age were the determinants of productivity and stability in planted forest. Our results suggest that selective thinning and enriching species richness and forest stand age can effectively balance the productivity and biomass temporal stability of planted forests. Older natural forests still need to be strictly protected under climate change.

Soft tissue malignant tumours of the foot and ankle are rare. Diagnostic imaging and interventional biopsy are vital to establish the nature and grading of a suspicious tumour prior to surgical intervention.

Chikungunya is an arboviral disease caused by a virus with wide geographical distribution in endemic areas. This case report documents a patient with Antisynthetase Syndrome post-chikungunya infection. Autoimmune diseases result from breakdown of immune tolerance. Among all triggers, viruses represent the greatest environmental potential to precipitate inflammatory myopathy.

We present a framework for derivation of closed-form continuum equations governing mesoscale dynamics of large particle systems. Balance equations for spatial averages such as density, linear momentum, and energy were previously derived by a number of authors. These equations are exact, but are not in closed form because the stress and the heat flux (e.g. stress in the momentum balance equation) cannot be evaluated without the knowledge of particle positions and velocities. Recently, we proposed a method for approximating exact fluxes by true constitutive equations, that is, using non-local operators acting only on the average density and velocity. In the paper, constitute operators are obtained by using filtered regularization methods from the theory of ill-posed problems. We also formulate conditions on fluctuation statistics which permit approximating these operators by local equations. The performance of the method is tested numerically using Fermi-Pasta-Ulam particle chains with two different potentials: the classical Lennard-Jones, and the purely repulsive potential used in granular materials modeling. The initial conditions incorporate velocity fluctuations on scales that are smaller than the size of the averaging window. Simulation results show good agreement between the exact stress and its closed form approximation.

Coccolithophores have global ecological and biogeochemical significance as the most important calcifying marine phytoplankton group. The structure and selection of prokaryotic communities associated with the most abundant coccolithophore and bloom-forming species, Emiliania huxleyi, are still poorly known. In this study, we assessed the diversity of bacterial communities associated with an E. huxleyi bloom in the Celtic Sea, exposed axenic E. huxleyi cultures to prokaryotic communities derived from bloom and non-bloom conditions and followed the dynamics of their microbiome composition over one year. Bloom-associated prokaryotic communities were dominated by SAR11, Marine group II Euryarchaeota, Rhodobacterales and contained substantial proportions of known indicators of phytoplankton bloom demises such as Flavobacteriaceae and Pseudoalteromonadaceae. Taxonomic richness of replicated co-cultures resulting from natural communities with axenic E. huxleyi rapidly shifted and then stabilized over time, presumably by ecological selection favoring more beneficial populations. Recruited microbiomes from the environment were consistently dependent on the composition of the initial bacterioplankton community. Phycosphere-associated communities derived from the E. huxleyi bloom depth were highly similar to one another, suggesting deterministic processes, whereas cultures from non-bloom conditions show an effect of both deterministic processes and stochasticity. Overall, this work sheds new light on the importance of the initial inoculum composition in microbiome recruitment and elucidates the temporal dynamics of its composition and long-term stability.

Despite sustained global efforts to avoid, reduce, and reverse land degradation, estimates of land degradation nationally and regionally vary considerably. Land degradation reduces agricultural productivity, impacts the provision of vital ecosystem services, and disproportionately affects vulnerable populations. The 2030 Agenda for Sustainable Development, through Sustainable Development Goal (SDG) 15.3, sets out to achieve land degradation neutrality (LDN) by improving the livelihoods of those most affected and building resilience in areas affected by or at risk from degradation. The United Nations Convention to Combat Desertification (UNCCD) leads the charge in creating a spatially-explicit framework for monitoring and reporting on LDN goals that countries can integrate into their land planning policies. However, it remains difficult to operationalize the integration of biophysical indicators of land degradation with climatic and socio-economic indicators to assess the impact of land degradation on vulnerable populations. We present an integrative framework that demonstrates how freely available global geospatial datasets can be leveraged through an open-source platform (Trends.Earth) to simplify and operationalize monitoring and reporting on progress towards achieving LDN. Then, we summarize a suite of datasets and approaches that can be used to understand and quantify the socio-ecological interactions between drought, land degradation and population exposed to desertification, land degradation and drought (DLDD). We discuss how improvements in Earth Observation (EO) datasets and algorithms will allow UNCCD land-based progress sub-indicators (changes in primary productivity, land cover, soil organic carbon, drought, and population exposure) to be computed at enhanced spatial resolutions.

Here, we propose a method to obtain local analytic approximate solutions of ordinary differential equations with variable coefficients, or even some non-linear equations, inspired in the Lyapunov method, where instead of polynomial approximations, we use truncated Fourier series with variable coefficients as approximate solutions. In the case of equations admitting periodic solutions, an averaging over the coefficients gives global solutions. We show that, under some restrictive condition, the method is equivalent to the Picard-Lindel\”of method. After some numerical experiments showing the efficiency of the method, we apply it to equations of interest in Physics, in which we show that our method possesses an excellent precision even with low iterations.

The use of sutureless valves in infective endocarditis has been previously reported. Singh et al have reported a single-center successful surgical treated pulmonary endocarditis in 2 cases with a sutureless bioprosthesis.

A document by Jordan Llerena-Velastegui. Click on the document to view its contents.

Modeling splicing is essential for tackling the challenge of variant interpretation as each nucleotide variation can be pathogenic by affecting pre-mRNA splicing via disruption/creation of splicing motifs such as 5’/3’ splice sites, branch sites or splicing regulatory elements. Unfortunately, most in silico tools focus on a specific type of splicing motif, which is why we developed the Splicing Prediction Pipeline (SPiP) to perform, in one single bioinformatic analysis based on machine learning approach, comprehensive assessment of variant effect on different splicing motifs. We gathered a curated set of 4,616 variants scattered all along the sequence of 227 genes, with their corresponding splicing studies. Bayesian analysis provided us the number of control variants, i.e. variants without impact on splicing, to mimic the deluge of variants from high throughput sequencing data. Results show that SPiP can deal with the diversity of splicing alterations, with 83.13% sensitivity and 99% specificity to detect spliceogenic variants. Overall performance as measured by area under the receiving operator curve was 0.986, significantly better than 0.965 spliceAI for the same dataset. SPiP lends itself to a unique suite for comprehensive prediction of spliceogenicity in the genomic medicine era. SPiP is available at: [https://sourceforge.net/projects/splicing-prediction-pipeline/](https://sourceforge.net/projects/splicing-prediction-pipeline/)

Exploring highly active and stable electrocatalyst for oxygen evolution reaction is important for the development of water splitting and rechargeable metal-air batteries. Herein, a hybrid electrocatalyst of CoFe alloy and CoxN heterojunction encapsulated and embedded in N-doped carbon support (CoFe-CoxN@NC) was in situ coupling via a pyrolysis process of a novel coordination polymer from lignin biomacromolecule. CoFe-CoxN@NC exhibited an excellent OER activity with a low overpotential of 270 mV at 10 mA•cm−2 and stability with increment of 20 mV, comparable to commercial Ir/C. DFT calculations revealed that CoxN and N-doped grapheme encapsulation can reduce the binding strength between *O and CoFe alloy, prevent metals leaching and agglomeration, and improve electron transfer efficiency, thereby, remarkably enhancing the OER activity and stability. In situ coupling strategy of alloy and nitride heterojunction on N-doped lignin-derived carbon provided a promising and universal catalyst design for the development of renewable energy conversion technologies.

This research paper is concerned with developing, analyzing, and implementing an adaptive optimized one-step block Nyström method for solving second-order initial value problems of ODEs and time-dependent partial differential equations. The new technique is developed through a collocation method with a new approach for selecting the collocation points. An embedding-like procedure is used to estimate the error of the proposed optimized method. The current approach has produced approximate solutions to real-world oscillatory, periodic and stiff application problems. The numerical experiments demonstrate that the introduced error estimation and stepsize control strategy presented in this manuscript has produced a good performance compared with some of the other existing numerical methods.

Organic materials are essential to increase soil organic carbon (SOC). However, it is unclear whether C sequestration is primarily affected by the form of organic materials or soil types. Wheat straw, tobacco straw, and their derived biochars were added to acidic soil, saline soil and calcareous soil in the same C concentration and incubated for 30, 90, and 180 days, respectively. The contents of humic substances (HS), the structural characteristic of SOC, and enzyme activities were investigated. The results revealed that both biochar-C and crop straw-C were mainly sequestered in humin (HU) across all soil types. Moreover, humic acid (HA) levels increased in straw treatments but not in biochar treatments. The cluster analysis and principal components analysis showed that HU had a significantly positive correlation with SOC. The aryl C of SOC increased in biochar treatments, while phenolic C and O-alkyl C of SOC increased in straw treatments. A positive correlation was found between aromatic C and SOC concentration, as well as between polyphenol oxidase activity and O-alkyl C. The formation of O-alkyl C was affected by polyphenol oxidase activity. These findings suggest that the form of organic materials and microbial activity, rather than soil types, influence the formation of HS and functional groups of SOC. Soil amended with biochar can sequester more recalcitrant C while also increasing the hydrophobicity of SOC.