Designing highly conducting metal-organic frameworks (MOFs) is currently a subject of great interest for their potential applications in diverse areas encompassing energy storage and generation. ...Herein, a strategic design in which a metal-sulfur plane is integrated within a MOF to achieve high electrical conductivity, is successfully demonstrated. The MOF {Cu
(6-Hmna)(6-mn)·NH
}
(1, 6-Hmna = 6-mercaptonicotinic acid, 6-mn = 6-mercaptonicotinate), consisting of a two dimensional (-Cu-S-)
plane, is synthesized from the reaction of Cu(NO
)
, and 6,6'-dithiodinicotinic acid via the in situ cleavage of an S-S bond under hydrothermal conditions. A single crystal of the MOF is found to have a low activation energy (6 meV), small bandgap (1.34 eV) and a highest electrical conductivity (10.96 S cm
) among MOFs for single crystal measurements. This approach provides an ideal roadmap for producing highly conductive MOFs with great potential for applications in batteries, thermoelectric, supercapacitors and related areas.
Although numerous studies on the impacts of climate change on biodiversity have been published, only a handful are focused on the intraspecific level or consider population‐level models (separate ...models per population). We endeavored to fill this knowledge gap relative to the Qinghai‐Tibetan plateau (QTP) by combining species distribution modeling (SDMs) with population genetics (i.e., population‐level models) and phylogenetic methods (i.e., phylogenetic tree reconstruction and phylogenetic diversity analyses). We applied our models to 11 endemic and widely distributed herpetofauna species inhabiting high elevations in the QTP. We aimed to determine the influence of environmental heterogeneity on species’ responses to climate change, the magnitude of climate‐change impacts on intraspecific diversity, and the relationship between species range loss and intraspecific diversity losses under 2 shared socioeconomic pathways (SSP245 and SSP585) and 3 future periods (2050s, 2070s, and 2090s). The effects of global climatic change were more pronounced at the intraspecific level (22% of haplotypes lost and 36% of populations lost) than the morphospecies level in the SSP585 climate change scenario. Maintenance of genetic diversity was in general determined by a combination of factors including range changes, species genetic structure, and the part of the range predicted to be lost. This is owing to the fact that the loss and survival of populations were observed in species irrespective of the predicted range changes (contraction or expansion). In the southeast (mountainous regions), climate change had less of an effect on range size (>100% in 3 species) than in central and northern QTP plateau regions (range size <100% in all species). This may be attributed to environmental heterogeneity, which provided pockets of suitable climate in the southeast, whereas ecosystems in the north and central regions were homogeneous. Generally, our results imply that mountainous regions with high environmental heterogeneity and high genetic diversity may buffer the adverse impacts of climate change on species distribution and intraspecific diversity. Therefore, genetic structure and characteristics of the ecosystem may be crucial for conservation under climate change.
Impactos del cambio climático sobre la diversidad de herpetofauna en la meseta Qinghai‐Tíbet
Región
Aunque se han publicado numerosos estudios sobre los impactos del cambio climática en la biodiversidad, son muy pocos los que se enfocan en el nivel intraespecífico o que consideran modelos a nivel poblacional (modelos separados por población). Intentamos cerrar este vacío de conocimiento en relación con la meseta Qinghai‐Tíbet (MQT) con la combinación entre modelos de distribución de especies (MDE) y genética poblacional (modelos a nivel poblacional) y métodos filogenéticos (reconstrucción de árboles filogenéticos y análisis de diversidad filogenética). Aplicamos nuestros modelos a once especies endémicas de herpetofauna con distribución amplia en las elevaciones más altas de la MQT. Nos planteamos determinar la influencia de la heterogeneidad de las especies sobre la respuesta de las especies al cambio climático, la magnitud de los impactos del cambio climático sobre la diversidad intraespecífica y la relación entre la pérdida de distribución de la especie y las pérdidas de diversidad intraespecífica bajo dos vías socioeconómicas (SSP245 y SSP585) y tres periodos del futuro (2050s, 2070s y 2090s). Los efectos del cambio climático global fueron más pronunciados a nivel intraespecífico (22% de pérdida en los haplotipos y 36% en las poblaciones) que al nivel morfoespecie en el escenario de cambio climático SSP585. El mantenimiento de la diversidad genética casi siempre estuvo determinado por una combinación de factores que incluyen cambios en la distribución, estructura genética de las especies y la parte de la distribución que se pronosticó se perdería. Esto se debe a que observamos la pérdida y supervivencia de las poblaciones sin importar los cambios pronosticados en la distribución (contracción o expansión). En las regiones montañosas del sureste, el cambio climático tuvo un efecto menor sobre la distribución (>100% en tres especies) comparado con las regiones de la meseta central y del norte de la MQT (distribución <100% en todas las especies). Esto puede atribuirse a la heterogeneidad ambiental, la cual proporciona recovecos de clima adecuado en el sureste, mientras que los ecosistemas en las regiones central y norte fueron homogéneos. De manera general, nuestros resultados implican que las regiones montañosas con una elevada heterogeneidad ambiental y una gran diversidad genética podrían reducir los impactos adversos del cambio climático sobre la distribución de las especies y la diversidad intraespecífica. Por lo tanto, la estructura genética y las características del ecosistema pueden ser cruciales para conservar bajo el cambio climático.
【摘要】
尽管已有大量有关气候变化对生物多样性影响的研究发表, 但只有少数研究考虑种下或种群水平的模型。我们将物种分布模型(SDMs)与种群遗传学和系统发生学方法相结合, 填补青藏高原地区(QTP)在这一方面的研究空白。我们对11种栖息在青藏高原特有且分布广泛的两栖爬行动物进行了模型分析, 探究环境异质性对物种响应气候变化的影响、气候变化对种内多样性的影响程度、以及在SSP245和SSP585两种情景下, 未来(2050年、2070年和2090年)物种分布范围丧失与种内多样性丧失之间的关系。结果显示, 在SSP585气候变化情景中, 在种下有22%的单倍型和36%的种群将会丢失, 全球气候变化对种内多样性的影响比种间更为明显。遗传多样性是否能够维持一般由多种因素共同决定, 包括分布区的变化、物种遗传结构以及预测丢失的分布区。在青藏高原东南部山区, 气候变化对物种分布范围大小的影响(有3个物种的分布范围扩张)小于青藏高原北部和中部地区(所有物种的分布范围均缩小), 主要原因可能是东南部环境异质性更高, 物种可以选择较为合适的生境, 而北部和中部地区环境则趋于同质化。本研究结果表明, 环境异质性高、遗传多样性高的山区可以缓冲气候变化对物种分布和种内多样性的不利影响。因此, 生态系统的遗传结构和特征对于气候变化下的多样性保护至关重要。
Evaluating the impacts of genetically modified crops on biodiversity is a necessary step before their release to the field and obtaining environmental safety certificates. To assess the ecological ...safety of herbicide-resistant soybean ZUTS-33, we compared arthropod diversity, diseases occurrence, nodule number, and weed diversity through spraying herbicide or water on ZUTS-33, and its parental control receptor HC-3 and main cultivar soybean ZH-13 in a field experiment. The results showed that there was no significant difference of arthropod diversity (number of insects per 100 plants, Shannon index, Simpson index and Pielou index), diseases incidence rates and disease index, nodules and weed diversity between ZUTS-33 and non-genetically modified control soybean HC-3 and ZH-13. Spraying herbicide on ZUTS-33 had no significant effect on arthropod diversity, diseases and rhizobium compared with those treatments of spraying clear water on ZUTS-33, non-genetically modified control HC-3 and ZH-13, and the abundance
This paper proposes a multi-scale parameter identification algorithm for the lithium-ion battery (LIB) electric model by using a combination of particle swarm optimization (PSO) and ...Levenberg-Marquardt (LM) algorithms. Two-dimensional Poisson equations with unknown parameters are used to describe the potential and current density distribution (PDD) of the positive and negative electrodes in the LIB electric model. The model parameters are difficult to determine in the simulation due to the nonlinear complexity of the model. In the proposed identification algorithm, PSO is used for the coarse-scale parameter identification and the LM algorithm is applied for the fine-scale parameter identification. The experiment results show that the multi-scale identification not only improves the convergence rate and effectively escapes from the stagnation of PSO, but also overcomes the local minimum entrapment drawback of the LM algorithm. The terminal voltage curves from the PDD model with the identified parameter values are in good agreement with those from the experiments at different discharge/charge rates.
Fault location with the highest possible accuracy has a significant role in expediting the restoration process, after being exposed to any kind of fault in power distribution grids. This paper ...provides fault detection, classification, and location methods using machine learning tools and advanced signal processing for a radial distribution grid. The three-phase current signals, one cycle before and one cycle after the inception of the fault are measured at the sending end of the grid. A discrete wavelet transform (DWT) is employed to extract useful features from the three-phase current signal. Standard statistical techniques are then applied onto DWT coefficients to extract the useful features. Among many features, mean, standard deviation (SD), energy, skewness, kurtosis, and entropy are evaluated and fed into the artificial neural network (ANN), Multilayer perceptron (MLP), and extreme learning machine (ELM), to identify the fault type and its location. During the training process, all types of faults with variations in the loading and fault resistance are considered. The performance of the proposed fault locating methods is evaluated in terms of root mean absolute percentage error (MAPE), root mean squared error (RMSE), Willmott’s index of agreement (WIA), coefficient of determination ( R 2 ), and Nash-Sutcliffe model efficiency coefficient (NSEC). The time it takes for training and testing are also considered. The proposed method that discrete wavelet transforms with machine learning is a very accurate and reliable method for fault classifying and locating in both a balanced and unbalanced radial system. 100% fault detection accuracy is achieved for all types of faults. Except for the slight confusion of three line to ground (3LG) and three line (3L) faults, 100% classification accuracy is also achieved. The performance measures show that both MLP and ELM are very accurate and comparative in locating faults. The method can be further applied for meshed networks with multiple distributed generators. Renewable generations in the form of distributed generation units can also be studied.
This paper proposes a sensitivity-based group-wise parameter identification algorithm for the electrical model of Li-ion battery. A global sensitivity analysis method is first performed in the entire ...parameter space to evaluate the identifiability of the model parameters. Then, the parameters are sorted and grouped by the global sensitivity indices. Finally, a group-wise method embedded with the Levenberg-Marquardt algorithm is followed to identify the parameters. Numerical simulation results and comparisons demonstrate that the proposed group-wise identification algorithm can serve as a reliable tool for extracting parameters.
A field imaging spectrometer system (FISS; 380-870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The ...chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%-35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.
JMCT is a large-scale, high-fidelity, three-dimensional general neutron–photon–electron–proton transport Monte Carlo software system. It was developed based on the combinatorial geometry parallel ...infrastructure JCOGIN and the adaptive structured mesh infrastructure JASMIN. JMCT is equipped with CAD modeling and visualizes the image output. It supports the geometry of the body and the structured/unstructured mesh. JMCT has most functions, variance reduction techniques, and tallies of the traditional Monte Carlo particle transport codes. Two energy models, multi-group and continuous, are provided. In recent years, some new functions and algorithms have been developed, such as Doppler broadening on-the-fly (OTF), uniform tally density (UTD), consistent adjoint driven importance sampling (CADIS), fast criticality search of boron concentration (FCSBC) domain decomposition (DD), adaptive control rod moving (ACRM), and random geometry (RG) etc. The JMCT is also coupled with the discrete ordinate S
N
code JSNT to generate source-biasing factors and weight-window parameters. At present, the number of geometric bodies, materials, tallies, depletion zones, and parallel processors are sufficiently large to simulate extremely complicated device problems. JMCT can be used to simulate reactor physics, criticality safety analysis, radiation shielding, detector response, nuclear well logging, and dosimetry calculations etc. In particular, JMCT can be coupled with depletion and thermal-hydraulics for the simulation of reactor nuclear-hot feedback effects. This paper describes the progress in advanced modeling, high-performance numerical simulation of particle transport, multiphysics coupled calculations, and large-scale parallel computing.
Penalty function is well-known for constrained evolutionary optimization. An open question in the penalty function is how to tune the penalty coefficient. This paper proposes an adaptive fuzzy ...penalty method to address this issue, where the coefficient is adjusted at both the individual level and the population level. At the individual level, each individual chooses a penalty coefficient from a predefined domain according to some fuzzy rules. At the population level, the domain of the crisp output is adjusted adaptively by using population information. To enhance the population diversity, an effective mutation scheme is developed. Due to its numerous merits, differential evolution is used to design a search algorithm. By the above processes, a constrained optimization evolutionary algorithm called AFPDE is proposed. Since the objective function value and the degree of constraint violation are normalized, AFPDE is less problem-dependent than the seminal work of the fuzzy penalty method. AFPDE introduces a lower penalty value in the early stage of AFPDE while a higher one in the later stage. Thus, it can escape local optima in the infeasible region. Experiments on three well-known benchmark test sets and two mechanical design problems validate that AFPDE is competitive.
Postmenopausal bleeding and an endometrial thickness ≥ 5 mm on sonograms of menopausal women can indicate the presence of endometrial lesions. Diagnostic hysteroscopy is a powerful method for ...endometrial diseases.
To investigate the pathological pattern of endometrial abnormalities in postmenopausal women with bleeding or asymptomatic thickened endometrium diagnosed by hysteroscopy.
A total of 187 postmenopausal women with bleeding or asymptomatic thickened endometrium underwent diagnostic hysteroscopy. The women were subsequently divided into three groups: Postmenopausal bleeding (PMB) group (
= 84), asymptomatic group (
= 94), and additional group (
= 9). Women in the additional group manifested abdominal pain and leukorrhagia.
Among the 187 patients examined, 84 (44.9%) were diagnosed with PMB and 94 (50.3%) with asymptomatic thickened endometrium. Endometrial polyp was the most common endometrial abnormality, which was detected in 51.2%, 76.6% and 77.8% of the PMB, asymptomatic, and additional groups, respectively. In the PMB group, 7 (8.3%) women had hyperplasia with atypia and 14 (16.7%) had endometrial adenocarcinoma. Fewer malignant lesions were detected in the asymptomatic group. Endometrial hyperplasia without atypia was found in 8.3% of the PMB group and 7.4% of the asymptomatic group.
Endometrial polyp was the most common pathology in the PMB group. Diagnostic hysteroscopy is recommended for women with PMB and asymptomatic thickened endometrium.
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