Distinct leaf functional traits of Tamarix chinensis at different habitats in the hinterland of the Taklimakan desert

Leaf functional traits reflect plant adaptive strategies towards environmental heterogeneity. However, which factor play the key role of plasticity of leaf functional traits among various variable environmental factors remains unclear in desert hinterland oasis area. Here, we analyzed variations in leaf water content (LWC), δ13C values of leaves (δ13C), specific leaf area (SLA), leaf organic carbon concentration (LOC), leaf total nitrogen concentration (LTN), leaf total phosphorus concentration (LTP), and leaf C: N: P stoichiometry in Tamarix chinensis growing in five habitats at the Daliyabuyi, a natural pristine oasis in northwestern China, that differ abiotically and biotically. The spatial heterogeneity of leaf functional traits was evident. Abiotic factors vitally influence leaf functional traits, of which groundwater depth (GWD) and soil C: N stoichiometry (SOC: STN) are crucial. GWD exhibited close relationships with LWC (P < 0.05) and LOC: LTP (P < 0.01), but not δ13C. Soil water content (SWC) and SOC: STN were negatively related to SLA (P < 0.01; P < 0.05). While, SOC: STN showed positive relationships with LOC: LTN (P < 0.05). As for biological factors, we found T. chinensis in habitat with Sophora alopecuroidies had the highest LTN, possibly as a result of N fixation of leguminous plants (S. alopecuroidies) promotes the N concentration of T. chinensis. Close relationships also existed between leaf functional traits, LWC showed significantly negatively relatd to δ13C, LOC: LTN and LOC: LTP (P < 0.05), whereas δ13C had positively correlated with LOC: LTN (P < 0.01) but negatively correlated with LTN (P < 0.05). T. chinensis had relative higher LWC couple with lower δ13C, and exhibiting lower C, N, P in leaves and their stoichiometric ratios, and also lower SLA which compared with other terrestrial plant. Such coordinations suggesting that T. chinensis develops a suite of trait combinations mainly tends to more conservative to response local habitats in Daliyabuyi, which is contribute to understand desert plant resource acquisition and utilization mechanisms in extremely arid and barren environments

Thermocapillary convection in a shallow annular pool of silicone oil

Thermocapillary flow in a shallow annular pool (Ri=20 mm, Ro=40 mm and depth d=1.0 mm) of silicone oil (0.65 cSt, Pr=6.7), heated from the outer wall and cooled at the inner wall, is investigated by numerical simulation. Numerical results clarified details of pattern formation and oscillatory behavior of hydrothermal waves (HTW) as well as the critical conditions for their incipience. In non-rotating pool, the critical Marangoni number Mac for the incipience of the HTW is 8.396×10^3(ΔTc=5.03K). The critical azimuthal wave number mc is 27. At slightly super critical conditions, a single group of HTW propagating in the azimuthal direction is dominant after a long calculation time. Further increase in Ma causes coexistence of several groups of HTW with different wave numbers and propagation directions. Effect of a slow rotation of the pool around its central axis destabilizes the basic steady axisymmetric flow against HTW. At Ta=0.322 (corresponding to a rotation rate of 2 r.p.m.), the Mac was determined as 8.096×10^3(ΔTc=4.85K) with mc=30. Over a range of Ma from 8.76×10^3 to 2.0×10^4, numerical simulations indicate that the HTW propagates azimuthally opposite to the direction of the pool rotation in a rotating coordinate. This phenomenon, i.e. a selection of propagation direction, is caused by the azimuthal velocity component in the basic flow field induced by the Coriolis force. At Ma=1.34×10^4, the azimuthal wave number m increases up to 54 accompanied by an appearance of finger-shaped patterns. At Ma=2.0×10^4, two groups of HTW with greatly different wave numbers (m=48 and m=5) coexist and propagate in the opposite azimuthal directions

Thermocapillary convection in a shallow annular pool of silicone oil

Thermocapillary flow in a shallow annular pool (Ri=20 mm, Ro=40 mm and depth d=1.0 mm) of silicone oil (0.65 cSt, Pr=6.7), heated from the outer wall and cooled at the inner wall, is investigated by numerical simulation. Numerical results clarified details of pattern formation and oscillatory behavior of hydrothermal waves (HTW) as well as the critical conditions for their incipience. In non-rotating pool, the critical Marangoni number Mac for the incipience of the HTW is 8.396×10^3(ΔTc=5.03K). The critical azimuthal wave number mc is 27. At slightly super critical conditions, a single group of HTW propagating in the azimuthal direction is dominant after a long calculation time. Further increase in Ma causes coexistence of several groups of HTW with different wave numbers and propagation directions. Effect of a slow rotation of the pool around its central axis destabilizes the basic steady axisymmetric flow against HTW. At Ta=0.322 (corresponding to a rotation rate of 2 r.p.m.), the Mac was determined as 8.096×10^3(ΔTc=4.85K) with mc=30. Over a range of Ma from 8.76×10^3 to 2.0×10^4, numerical simulations indicate that the HTW propagates azimuthally opposite to the direction of the pool rotation in a rotating coordinate. This phenomenon, i.e. a selection of propagation direction, is caused by the azimuthal velocity component in the basic flow field induced by the Coriolis force. At Ma=1.34×10^4, the azimuthal wave number m increases up to 54 accompanied by an appearance of finger-shaped patterns. At Ma=2.0×10^4, two groups of HTW with greatly different wave numbers (m=48 and m=5) coexist and propagate in the opposite azimuthal directions

A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems

To solve the nonlinear constrained optimization problem, a particle swarm optimization algorithm based on the improved Deb criterion (CPSO) is proposed. Based on the Deb criterion, the algorithm retains the information of ‘excellent’ infeasible solutions. The algorithm uses this information to escape from the local best solution and quickly converge to the global best solution. Additionally, to further improve the global search ability of the algorithm, the DE strategy is used to optimize the personal best position of the particle, which speeds up the convergence speed of the algorithm. The performance of our method was tested on 24 benchmark problems from IEEE CEC2006 and three real-world constraint optimization problems from CEC2020. The simulation results show that the CPSO algorithm is effective

A robust framework for enhancing cardiovascular disease risk prediction using an optimized category boosting model

Cardiovascular disease (CVD) is a leading cause of mortality worldwide, and it is of utmost importance to accurately assess the risk of cardiovascular disease for prevention and intervention purposes. In recent years, machine learning has shown significant advancements in the field of cardiovascular disease risk prediction. In this context, we propose a novel framework known as CVD-OCSCatBoost, designed for the precise prediction of cardiovascular disease risk and the assessment of various risk factors. The framework utilizes Lasso regression for feature selection and incorporates an optimized category-boosting tree (CatBoost) model. Furthermore, we propose the opposition-based learning cuckoo search (OCS) algorithm. By integrating OCS with the CatBoost model, our objective is to develop OCSCatBoost, an enhanced classifier offering improved accuracy and efficiency in predicting CVD. Extensive comparisons with popular algorithms like the particle swarm optimization (PSO) algorithm, the seagull optimization algorithm (SOA), the cuckoo search algorithm (CS), K-nearest-neighbor classification, decision tree, logistic regression, grid-search support vector machine (SVM), grid-search XGBoost, default CatBoost, and grid-search CatBoost validate the efficacy of the OCSCatBoost algorithm. The experimental results demonstrate that the OCSCatBoost model achieves superior performance compared to other models, with overall accuracy, recall, and AUC values of 73.67%, 72.17%, and 0.8024, respectively. These outcomes highlight the potential of CVD-OCSCatBoost for improving cardiovascular disease risk prediction

The complete chloroplast genome of Callianthe picta (Malvaceae)

Callianthe picta likes a warm and humid climate, is resistant to barrenness, and is easy to reproduce. Its petals and leaves can promote blood circulation and remove blood stasis, and can also be used to relax the muscles and collaterals. In this study, we sequenced the complete chloroplast genome sequence of C. picta to investigate its phylogenetic relationship in the family Abutilon. The complete chloroplast size of C. picta is 160,398 bp, including a large single-copy (LSC) region of 89,088 bp, a small single-copy (SSC) region of 20,138 bp, a pair of invert repeats (IRs) regions of 25,586 bp. The GC content of the whole complete chloroplast genome is 37.0%. We annotated 128 genes in the genome in detail, including 84 protein-coding genes, 36 tRNA genes, and 8 rRNA genes. Phylogenetic analysis indicated that C. picta was closely related to Abutilon theophrati

Ti-40Al-10Nb-10Cr Porous Microfiltration Membrane with Hierarchical Pore Structure for Particulate Matter Capturing from High-Temperature Flue Gas

TiAl-based porous microfiltration membranes are expected to be the next-generation filtration materials for potential applications in high-temperature flue gas separation in corrosive environments. Unfortunately, the insufficient high-temperature oxidation resistance severely limits their industrial applications. To tackle this issue, a Ti-40Al-10Nb-10Cr porous alloy was fabricated for highly effective high-temperature flue gas purification. Benefited from microstructural changes and the formation of two new phases, the Ti-40Al-10Nb-10Cr porous alloy demonstrated favorable high-temperature anti-oxidation performance with the incorporation of Nb and Cr high-temperature alloying elements. By the separation of a simulated high-temperature flue gas, we achieved an ultra-high PM-removal efficiency (62.242% for PM<2.5 and 98.563% for PM>2.5). These features, combined with our experimental design strategy, provide a new insight into designing high-temperature TiAl-based porous materials with enhanced performance and durability