Existence of solutions for a class of fourth-order m-point boundary value problems

Some existence criteria are established for a class of fourth-order $m$-point boundary value problem by using the upper and lower solution method and the Leray-Schauder continuation principle

The upper and lower solution method for nonlinear third-order three-point boundary value problem

This paper is concerned with the following nonlinear third-order three-point boundary value problem \left\{ \begin{array}{l} u^{\prime \prime \prime }(t)+f\left( t,u\left( t\right) ,u^{\prime}\left(t\right) \right) =0,\, t\in \left[ 0,1\right], \\ u\left( 0\right) =u^{\prime }\left( 0\right) =0,\, u^{\prime}\left( 1\right) =\alpha u^{\prime }\left( \eta \right),\label{1.1} \end{array} \right. where $0<\eta <1$ and $0\leq \alpha <1.$ A new maximum principle is established and some existence criteria are obtained for the above problem by using the upper and lower solution method

Lead isotope analysis of melt inclusions by LA-MC-ICP-MS

This study provides a method for measuring Pb isotopes of olivine-hosted melt inclusions with diameters larger than 40 micrometers.</p

The effects of fermentation and adsorption using lactic acid bacteria culture broth on the feed quality of rice straw

To improve the nutritional value and the palatability of air-dried rice straw, culture broth of the lactic acid bacteria community SFC-2 was used to examine the effects of two different treatments, fermentation and adsorption. Air-dried and chopped rice straw was treated with either fermentation for 30 d after adding 1.5 L nutrient solution (50 mL inocula L–1, 1.2×1012 CFU mL–1 inocula) kg–1 straw dry matter, or spraying a large amount of culture broth (1.5 L kg–1 straw dry matter, 1.5×1011 CFU mL–1 culture broth) on the straw and allowing it to adsorb for 30 min. The feed quality and aerobic stability of the resulting forage were examined. Both treatments improved the feed quality of rice straw, and adsorption was better than fermentation for preserving nutrients and improving digestibility, as evidenced by higher dry matter (DM) and crude protein (CP) concentrations, lower neutral detergent fiber (NDF), acid detergent fiber (ADF) and NH3-N concentrations, as well as higher lactic acid production and in vitro digestibility of DM (IVDMD). The aerobic stability of the adsorbed straw and the fermented straw was 392 and 480 h, respectively. After being exposed to air, chemical components and microbial community of the fermented straw were more stable than the adsorbed straw

Expansion of Thaumarchaeota habitat range is correlated with horizontal transfer of ATPase operons.

Thaumarchaeota are responsible for a significant fraction of ammonia oxidation in the oceans and in soils that range from alkaline to acidic. However, the adaptive mechanisms underpinning their habitat expansion remain poorly understood. Here we show that expansion into acidic soils and the high pressures of the hadopelagic zone of the oceans is tightly linked to the acquisition of a variant of the energy-yielding ATPases via horizontal transfer. Whereas the ATPase genealogy of neutrophilic Thaumarchaeota is congruent with their organismal genealogy inferred from concatenated conserved proteins, a common clade of V-type ATPases unites phylogenetically distinct clades of acidophilic/acid-tolerant and piezophilic/piezotolerant species. A presumptive function of pumping cytoplasmic protons at low pH is consistent with the experimentally observed increased expression of the V-ATPase in an acid-tolerant thaumarchaeote at low pH. Consistently, heterologous expression of the thaumarchaeotal V-ATPase significantly increased the growth rate of E. coli at low pH. Its adaptive significance to growth in ocean trenches may relate to pressure-related changes in membrane structure in which this complex molecular machine must function. Together, our findings reveal that the habitat expansion of Thaumarchaeota is tightly correlated with extensive horizontal transfer of atp operons

Association and interaction analysis of PPARGC1A and serum uric acid on type 2 diabetes mellitus in Chinese Han population

BACKGROUND: Peroxisome proliferator-activated receptor gamma coactivator-1α (PPARGC1A/ PGC-1α) is a ligand-activated transcription factor belonging to the nuclear hormone receptor superfamily. The activity of PGC-1α or genetic variations in the gene encoding the enzyme may contribute to individual variations in mitochondrial function and insulin resistance or diabetes. The objective of this study was to assess the extent to which PPARGC1A (rs8192678) and serum uric acid (UA) and its interaction impact on T2DM susceptibility in Chinese Han population. METHOD: We conducted a study in a cohort that included 1166 T2DM patients and 1135 controls, and was genotyped for the presence of the PPARGC1A rs8192678 polymorphisms. Genotyping was performed by iPLEX technology. The association between rs8192678 or UA and T2DM was assessed by univariate and multivariate logistic regression (MLR) analysis controlling for confounders. The interaction between rs8192678 and UA for T2DM susceptibility was also assessed by MLR analysis. RESULTS: The generalized linear regression analysis failed to show an association between the PPARGC1A rs8192678 polymorphisms and T2DM. Interestingly, the present study provided data suggesting that the minor A-allele of PPARGC1A (rs8192678) had a protective effect against T2DM in subjects with higher level of UA (OR(int) =1.50 95% CI: 1.06-2.12 for allele and P = 0.02, OR(int) =1.63 95% CI: 1.17-2.26 for genotype and P = 0.004). CONCLUSION: The combination of higher level of UA and PPARGC1A (rs8192678) was an independent predictor for T2DM

SSA-LHCD: a singular spectrum analysis-driven lightweight network with 2-D self-attention for hyperspectral change detection.

As an emerging research hotspot in contemporary remote sensing, hyperspectral change detection (HCD) has attracted increasing attention in remote sensing Earth observation, covering land mapping changes and anomaly detection. This is primarily attributable to the unique capacity of hyperspectral imagery (HSI) to amalgamate both the spectral and spatial information in the scene, facilitating a more exhaustive analysis and change detection on the Earth's surface, proving to be successful across diverse domains, such as disaster monitoring and geological surveys. Although numerous HCD algorithms have been developed, most of them face three major challenges: (i) susceptibility to inherent data noise, (ii) inconsistent accuracy of detection, especially when dealing with multi-scale changes, and (iii) extensive hyperparameters and high computational costs. As such, we propose a singular spectrum analysis-driven-lightweight network for HCD, where three crucial components are incorporated to tackle these challenges. Firstly, singular spectrum analysis (SSA) is applied to alleviate the effect of noise. Next, a 2-D self-attention-based spatial–spectral feature-extraction module is employed to effectively handle multi-scale changes. Finally, a residual block-based module is designed to effectively extract the spectral features for efficiency. Comprehensive experiments on three publicly available datasets have fully validated the superiority of the proposed SSA-LHCD model over eight state-of-the-art HCD approaches, including four deep learning models