Adaptive neuro-fuzzy inference system: Estimation of soil aggregates stability

In present study, the capabilities of multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) in developing pedotransfer functions (PTFs) for estimating geometric mean diameter (GMD) and mean weight diameter (MWD), from routine soil properties and combination of routine soil properties and fractal dimension of aggregates were evaluated. For this reason 101 samples were collected form the Northwest of Iran and some their properties such as soil texture, pH, cation exchange capacity (CEC), and organic matter (OM), fractal dimension of aggregates between number-diameter (Dn), mass-diameter (Dmt), and bulk density-diameter (Dmy) were determined and used as an input variables for determining of mean weight diameter (MWD) and geometric mean diameter (GMD) by MLR and ANFIS PTFs. Results showed that the application of fractal dimension of aggregates as a predictor in two methods improved the accuracy of PTFs. As well as, results showed that ANFIS have greater potential for determination of the relationships between soil aggregate stability indices and other soil properties in compared with MLR. Therefore using of adaptive neuro-fuzzy inference system (ANFIS) in developing pedotransfer functions is recommended.     

Wide‐field optical property mapping and structured light imaging of the esophagus with spatial frequency domain imaging

As the incidence of esophageal adenocarcinoma continues to rise, there is a need for improved imaging technologies with contrast to abnormal esophageal tissues. To inform the design of optical technologies that meet this need, we characterize the spatial distribution of the scattering and absorption properties from 471 to 851 nm of eight resected human esophagi tissues using Spatial Frequency Domain Imaging. Histopathology was used to categorize tissue types, including normal, inflammation, fibrotic, ulceration, Barrett's Esophagus and squamous cell carcinoma. Average absorption and reduced scattering coefficients of normal tissues were 0.211 ± 0.051 and 1.20 ± 0.18 mm^?1, respectively at 471 nm, and both values decreased monotonically with increasing wavelength. Fibrotic tissue exhibited at least 68% larger scattering signal across all wavelengths, while squamous cell carcinoma exhibited a 36% decrease in scattering at 471 nm. We additionally image the esophagus with high spatial frequencies up to 0.5 mm^?1 and show strong reflectance contrast to tissue treated with radiation. Lastly, we observe that esophageal absorption and scattering values change by an average of 9.4% and 2.7% respectively over a 30 minute duration post‐resection. These results may guide system design for the diagnosis, prevention and monitoring of esophageal pathologies.      

Diffuse and nonlinear imaging of multiscale vascular parameters for in vivo monitoring of preclinical mammary tumors

Diffuse optical imaging (DOI) techniques provide a wide‐field or macro assessment of the functional tumor state and have shown substantial promise for monitoring treatment efficacy in cancer. Conversely, intravital microscopy provides a high‐resolution view of the tumor state and has played a key role in characterizing treatment response in the preclinical setting. There has been little prior work in investigating how the macro and micro spatial scales can be combined to develop a more comprehensive and translational view of treatment response. To address this, a new multiscale preclinical imaging technique called diffuse and nonlinear imaging (DNI) was developed. DNI combines multiphoton microscopy with spatial frequency domain imaging (SFDI) to provide multiscale data sets of tumor microvascular architecture coregistered within wide‐field hemodynamic maps. A novel method was developed to match the imaging depths of both modalities by utilizing informed SFDI spatial frequency selection. An in vivo DNI study of murine mammary tumors revealed multiscale relationships between tumor oxygen saturation and microvessel diameter, and tumor oxygen saturation and microvessel length (|Pearson's ρ| ≥ 0.5, P < 0.05). Going forward, DNI will be uniquely enabling for the investigation of multiscale relationships in tumors during treatment.      

Does body size predict the buzz‐pollination frequencies used by bees?

Body size is an important trait linking pollinators and plants. Morphological matching between pollinators and plants is thought to reinforce pollinator fidelity, as the correct fit ensures that both parties benefit from the interaction. We investigated the influence of body size in a specialized pollination system (buzz‐pollination) where bees vibrate flowers to release pollen concealed within poricidal stamens. Specifically, we explored how body size influences the frequency of buzz‐pollination vibrations. Body size is expected to affect frequency as a result of the physical constraints it places on the indirect flight muscles that control the production of floral vibrations. Larger insects beat their wings less rapidly than smaller‐bodied insects when flying, but whether similar scaling relationships exist with floral vibrations has not been widely explored. This is important because the amount of pollen ejected is determined by the frequency of the vibration and the displacement of a bee's thorax. We conducted a field study in three ecogeographic regions (alpine, desert, grassland) and recorded flight and floral vibrations from freely foraging bees from 27 species across four families. We found that floral vibration frequencies were significantly higher than flight frequencies, but never exceeded 400 Hz. Also, only flight frequencies were negatively correlated with body size. As a bee's size increased, its buzz ratio (floral frequency/flight frequency) increased such that only the largest bees were capable of generating floral vibration frequencies that exceeded double that of their flight vibrations. These results indicate size affects the capacity of bees to raise floral vibration frequencies substantially above flight frequencies. This may put smaller bees at a competitive disadvantage because even at the maximum floral vibration frequency of 400 Hz, their inability to achieve comparable thoracic displacements as larger bees would result in generating vibrations with lower amplitudes, and thus less total pollen ejected for the same foraging effort.     

Absolute fitness, relative fitness, and utility

It is well known that (1) natural selection typically favors an allele with both a large mean fitness and a small variance in fitness; and (2) investors typically prefer a portfolio with both a large mean return and a small variance in returns. In the case of investors, this mean-variance trade-off reflects risk aversion; in the case of evolution, the mathematics is straightforward but the result is harder to intuit. In particular, it is harder to understand where, in the mathematics of natural selection, risk aversion arises. Here I present a result that suggests a simple answer to this question. Although my answer is essentially identical to one offered previously, my path to it differs somewhat from previous approaches. Some may find this new approach easier to intuit.     

Crystal structure of a bacterial albumin-binding domain at 1.4 A resolution

The albumin-binding domain, or GA module, of the peptostreptococcal albumin-binding protein expressed in pathogenic strains of Finegoldia magna is believed to be responsible for the virulence and increased growth rate of these strains. Here we present the 1.4A crystal structure of this domain, and compare it with the crystal structure of the GA-albumin complex. An analysis of protein-protein interactions in the two crystals, and the presence of multimeric GA species in solution, indicate the GA module is "sticky", and is capable of forming contacts with a range of protein surfaces. This might lead to interactions with different host proteins.     

A modified resonant recognition model to predict protein-protein interaction

Proteins are fundamental components of all living cells and the protein-protein interaction plays an important role in vital movement. This paper briefly introduced the original Resonant Recognition Model (RRM), and then modified it by using the wavelet transform to acquire the Modified Resonant Recognition Model (MRRM). The key characteristic of the new model is that it can predict directly the protein-protein interaction from the primary sequence, and the MRRM is more suitable than the RRM for this prediction. The results of numerical experiments show that the MRRM is effective for predicting the protein-protein interaction. Translated from Journal of Shanghai University (Natural Science), 2006, 12(1): 69–73 [译自: 上海大学学报(自然科学版)]     

水淹频率变化对鄱阳湖增强型植被指数的影响

水淹状况是湿地植被动态的重要影响因素。该研究基于谷歌地球引擎(GEE)平台, 利用2000-03-01至2020-02-29所有覆盖研究区域的MODIS遥感影像数据, 分析20年间水淹频率(IF)、增强型植被指数(EVI)的时空变化以及湿地植被对IF变化的响应, 得出以下结论: (1) 20年来鄱阳湖水文节律发生了明显改变, 高IF (IF > 75%)水域面积呈现下降趋势, 从2000年1 435.3 km²下降至2019年的510.25 km², 降幅为64.45%; (2)区域平均EVI呈显著上升趋势, 植被扩张主要集中在中部IF下降区域; (3)分析不同总水淹频率区域中平均EVI年际变化, 发现EVI与水淹状况的变化趋势相似, 2009年之后鄱阳湖水域面积萎缩趋势缓解, EVI增长速度出现下降; (4)鄱阳湖湿地植被主要沿水域面积萎缩方向扩张, 基于像元统计20年间IF与EVI的变化趋势, 发现它们在空间分布上高度吻合, 这种空间异质性进一步证实水淹状况起到调节植被动态变化的作用。     

研究报告：鳗弧菌（Vibrio anguillarum）核酸适配体的筛选及其结合蛋白的分离鉴定

目的鳗弧菌（Vibrio anguillarum）是水产养殖中的重要条件致病菌,每年给水产养殖业造成巨大的经济损失,研究其致病机制、对其进行快速的检测鉴定是其病害防治的前提和基础。核酸适配体因其高亲和力、高特异性等多种优点,在微生物的靶标分析、检测鉴定以及致病机制等多个领域都呈现出较好的应用潜力。因此,筛选鳗弧菌的核酸适配体,利用核酸适配体对鳗弧菌相关位点进行分析鉴定,不仅能为鳗弧菌的检测鉴定提供一个新的手段,对于探索鳗弧菌相关位点在其病害防治中的作用也具有重要意义。方法以鳗弧菌为靶目标,采用每轮测序的SELEX筛选方法,从高频序列中筛选鳗弧菌的核酸适配体;采用单链DNA浓度法测定核酸适配体的亲和力,研究核酸适配体对鳗弧菌的亲和特异性;采用Origin软件、选择反比例函数（Hyperbola函数）进行非线性拟合,获得核酸适配体的亲和常数（K_d）和最大亲和力（A_m）;采用磁分离技术和聚丙烯酰胺凝胶电泳分离纯化出核酸适配体H5的结合蛋白,通过质谱对该蛋白质进行分析鉴定,并利用Prabi、Phyre2、Psortb 3.0等在线网站分析该结合蛋白的...