Altitudinal diversity of terrestrial plants has been widely studied, whereas little is known for the patterns of aquatic plants. Here, we used a standardised field dataset to quantify the altitudinal ...patterns in the diversity and structure of aquatic plant assemblages, as well as the relationships between diversity indices and environmental variables.
Large‐scale field investigations were carried out in 128 sites ranging from 2,280 to 5,020 m above sea level across the southern part of Qinghai‐Tibet Plateau, China. In total, 102 species of aquatic plants were recorded, belonging to 67 genera, 31 families. Five taxonomic, phylogenetic, and functional indices were calculated for each collection site. We firstly examined altitudinal patterns of these diversity indices, then quantified the variations of indices across water areas, water flow, and soil matrix, respectively. We also explored the relationships between diversity indices and environmental variables using redundancy and variance partitioning analysis, to detect the ecological variables that drove the diversity.
The results showed that taxonomic, phylogenetic, and functional diversity of aquatic plants decreased with increasing altitude. Net relatedness index of aquatic plants showed a hump pattern along the altitude gradient, with a peak around 3,800 m above sea level. There was no obvious trend in the net functional relatedness index of aquatic plants with altitude. Annual mean temperature was the most important variable associated with the taxonomic, phylogenetic, and functional diversity. Water area and water flow were significantly associated with functional structure, but not phylogenetic structure. Soil matrix also correlated with aquatic plant diversity.
A large‐scale altitudinal gradient can influence aquatic plant diversity. Environmental filtering and niche convergence might have played dominant roles in the increasing and decreasing stages of phylogenetic structure of aquatic plant assemblages, respectively, along the altitudinal gradient. Phylogenetic and functional structure of aquatic plant assemblages showed different patterns along the altitudinal gradient, and the environmental variables better explained the change of functional structure than did the phylogenetic variables.
This is the first comprehensive study on the species, phylogeny, and function of aquatic plant assemblages along a large‐scale altitudinal gradient. We found an altitudinal decline in the diversity of aquatic plants and different patterns in the phylogenetic and functional structures of aquatic plant assemblages. These findings indicate that functional traits have high phenotypic plasticity and are more affected by environments than phylogenetic relationships which are mainly shaped by evolutionary processes.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
In the DNA microarray research field, the increasing sample size and feature dimension of the gene expression data prompt the development of an efficient and robust feature selection algorithm for ...gene expression data classification. In this study, we propose a hybrid feature selection algorithm that combines the mutual information maximization (MIM) and the adaptive genetic algorithm (AGA). Experimental results show that the proposing MIMAGA-Selection method significantly reduces the dimension of gene expression data and removes the redundancies for classification. The reduced gene expression dataset provides highest classification accuracy compared to conventional feature selection algorithms. We also apply four different classifiers to the reduced dataset to demonstrate the robustness of the proposed MIMAGA-Selection algorithm.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Computer-empowered detection of possible faults for Heating, Ventilation and Air-Conditioning (HVAC) subsystems, e.g., chillers, is one of the most important applications in Artificial Intelligence ...(AI) integrated Internet of Things (IoT). The cyber-physical system greatly enhances the safety and security of the working facilities, reducing time, saving energy and protecting humans’ health. Under the current trends of smart building design and energy management optimization, Automated Fault Detection and Diagnosis (AFDD) of chillers integrated with IoT is highly demanded. Recent studies show that standard machine learning techniques, such as Principal Component Analysis (PCA), Support Vector Machine (SVM) and tree-structure-based algorithms, are useful in capturing various chiller faults with high accuracy rates. With the fast development of deep learning technology, Convolutional Neural Networks (CNNs) have been widely and successfully applied to various fields. However, for chiller AFDD, few existing works are adopting CNN and its extensions in the feature extraction and classification processes. In this study, we propose to perform chiller FDD using a CNN-based approach. The proposed approach has two distinct advantages over existing machine learning-based chiller AFDD methods. First, the CNN-based approach does not require the feature selection/extraction process. Since CNN is reputable with its feature extraction capability, the feature extraction and classification processes are merged, leading to a more neat AFDD framework compared to traditional approaches. Second, the classification accuracy is significantly improved compared to traditional methods using the CNN-based approach.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Premise
Determining how xylem vessel diameters vary among plants and across environments gives insights into different water‐use strategies among species and ultimately their distributions. Here, we ...tested the vessel dimorphism hypothesis that the simultaneous occurrence of many narrow and a few wide vessels gives lianas an advantage over trees in seasonally dry environments.
Methods
We measured the diameters of 13,958 vessels from 15 liana species and 10,430 vessels from 16 tree species in a tropical seasonal rainforest, savanna, and subtropical evergreen broadleaved forest. We compared differences in mean and hydraulically weighted vessel diameter (MVD and Dh), vessel density (VD), theoretical hydraulic conductivity (Kt), vessel area fraction (VAF), and wood density (WD) between lianas and trees and among three sites.
Results
Nine liana species and four tree species had dimorphic vessels. From the tropical seasonal rainforest to the savanna, liana MVD, Dh and Kt decreased, and VD and WD increased, while only tree WD increased. From the tropical seasonal rainforest to the subtropical forest, six wood traits remained unchanged for lianas, while tree MVD, Dh and Kt decreased and VD increased. Trait space for lianas and trees were more similar in the savanna and more divergent in the subtropical forest compared to the tropical seasonal rainforest.
Conclusions
These results suggest that lianas tend to possess greater vessel dimorphism, which may explain how lianas grow well during seasonal drought, influencing their unique distribution across tropical rainfall gradients.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
This brief discusses the adaptive multiple leaders time-varying formation tracking control (TVFTC) problem for multi-agent systems (MASs) with energy constraints and bounded unknown inputs. To begin ...with, a novel formation control algorithm with the distributed adaptive time-varying formation is deployed based on the states between neighboring agents. Then, the energy consumption function is constructed to calculate the energy consumption of the TVFTC with multiple leaders of MASs and the maximum energy supply value. Moreover, the convergence of the formation tracking error with the energy constraints is assured with respect to the linear matrix inequality (LMI) method and Lyapunov theory. Ultimately, the simulation results well validate the correctness of the theoretical results.
This article investigates the adaptive guaranteed‐performance consensus problem for high‐order nonlinear multi‐agent systems (MASs) with switching topologies, and briefly analyzes the special ...leader‐following situation. To further handle the problem of adaptive guaranteed‐performance consensus for higher‐order nonlinear MASs with switching topologies, two novel distributed control protocols are introduced, which are applied to the leaderless and leader tracking cases, respectively. In addition, the methods based on the linear matrix inequality (LMI) and Riccati inequality provide the judgment basis for the stability of Lyapunov function theorem. Eventually, the theoretical results are efficiently and successfully validated by numerical simulations.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
•Proposed chiller FDD method combines ARX and SVM.•Comparison with pure data-driven, regression+SVM, and ANN.•Our method outperforms alternatives (higher accuracy and lower false alarm).•We use only ...six variables (three independent and three dependent), far fewer than others.•After training for generic chiller types, algorithms can be integrated in BMS.
Efficient and robust fault detection and diagnosis (FDD) can potentially play an important role in developing building management systems (BMS) for high performance buildings. Our research indicates that, in comparison to traditional model-based or data-driven methods, the combination of time series modeling and machine learning techniques produces higher accuracy and lower false alarm rates in FDD for chillers. In this paper, we study a hybrid method incorporating auto-regressive model with exogenous variables (ARX) and support vector machines (SVM). A high dimensional parameter space is constructed by the ARX model and SVM sub-divides the parameter space with hyper-planes, enabling fault classification. Experimental results demonstrate the superiority of our method over conventional approaches with higher prediction accuracy and lower false alarm rates.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
A synthesis of a δ‐ketohydroperoxide is described, addressing potential functional‐group compatibilities in these elusive species relevant to combustion and atmospheric chemistries. The hydroperoxide ...is installed via sulfonylhydrazine substitution, which was found to be more effective than displacement of secondary halides. As part of this protocol, it was observed that 1,2‐dimethoxyethane is an advantageous medium for the reaction, avoiding the formation of a tetrahydrofuran hydroperoxide side product. This discovery facilitated the multigram synthesis (6 steps, 41 % yield overall) and discrete characterization of the target δ‐ketohydroperoxide.
Combustion time! The synthesis of a δ‐ketohydroperoxide is described, addressing the compatibilities of ketones and hydroperoxides in these elusive combustion‐relevant species. The hydroperoxide is installed through sulfonylhydrazine substitution, in which it is found that 1,2‐dimethoxyethane is an advantageous medium for the transformation. The synthesis is scalable and safe, providing material for future chemical kinetics studies.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The advent of click chemistry has had a profound impact on many fields and fueled a need for reliable reactions to expand the click chemistry toolkit. However, developing new systems to fulfill the ...click chemistry criteria remains highly desirable yet challenging. Here, we report the development of light-induced primary amines and o-nitrobenzyl alcohols cyclization (PANAC) as a photoclick reaction via primary amines as direct click handle, to rapid and modular functionalization of diverse small molecules and native biomolecules. With intrinsic advantages of temporal control, good biocompatibility, reliable chemoselectivity, excellent efficiency, readily accessible reactants, operational simplicity and mild conditions, the PANAC photoclick is robust for direct diversification of pharmaceuticals and biorelevant molecules, lysine-specific modifications of unprotected peptides and native proteins in vitro, temporal profiling of endogenous kinases and organelle-targeted labeling in living systems. This strategy provides a versatile platform for organic synthesis, bioconjugation, medicinal chemistry, chemical biology and materials science.
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