Diffusive search with spatially dependent resetting

We consider a stochastic search model with resetting for an unknown stationary target $a\in \mathbb{R}$ with known distribution $\mu$. The searcher begins at the origin and performs Brownian motion with diffusion constant $D$. The searcher is also armed with an exponential clock with spatially dependent rate $r=r\left(\cdot \right)$, so that if it has failed to locate the target by the time the clock rings, then its position is reset to the origin and it continues its search anew from there. Denote the position of the searcher at time $t$ by $X\left(t\right)$. Let $E_0^{\left(r\right)}$ denote expectations for the process $X\left(\cdot \right)$. The search ends at time $T_a=inf\{t\ge 0:X\left(t\right)=a\}$. The expected time of the search is then ${\int }_{\mathbb{R}}\left(E_0^{\left(r\right)}{T}_a\right)\mu \left(da\right)$. Ideally, one would like to minimize this over all resetting rates $r$. We obtain quantitative growth rates for $E_0^{\left(r\right)}{T}_a$ as a function of $a$ in terms of the asymptotic behavior of the rate function $r$, and also a rather precise dichotomy on the asymptotic behavior of the resetting function $r$ to determine whether $E_0^{\left(r\right)}{T}_a$ is finite or infinite. We show generically that if $r\left(x\right)$ is of the order ${\left|x\right|}^{2l}$, with $l>-1$, then $log{E}_0^{\left(r\right)}{T}_a$ is of the order ${\left|a\right|}^{l+1}$; in particular, the smaller the asymptotic size of $r$, the smaller the asymptotic growth rate of $E_0^{\left(r\right)}{T}_a$. The asymptotic growth rate of $E_0^{\left(r\right)}{T}_a$ continues to decrease when $r\left(x\right)\sim \frac{D\lambda }{x^2}$ with $\lambda >1$; now the growth rate of $E_0^{\left(r\right)}{T}_a$ is more or less of the order ${\left|a\right|}^{\frac{1+\sqrt{1+8\lambda }}{2}}$. Note that this exponent increases to $\infty$ when $\lambda$ increases to $\infty$ and decreases to 2 when $\lambda$ decreases to 1. However, if $\lambda =1$, then $E_0^{\left(r\right)}{T}_a=\infty$, for $a\ne 0$. Our results suggest that for many distributions $\mu$ supported on all of $\mathbb{R}$, a near optimal (or optimal) choice of resetting function $r$ in order to minimize ${\int }_{{\mathbb{R}}^d}\left(E_0^{\left(r\right)}{T}_a\right)\mu \left(da\right)$ will be one which decays quadratically as $\frac{D\lambda }{x^2}$ for some $\lambda >1$. We also give explicit, albeit rather complicated, variational formulas for ${inf}_{r\gneqq 0}{\int }_{{\mathbb{R}}^d}\left(E_0^{\left(r\right)}{T}_a\right)\mu \left(da\right)$. For distributions $\mu$ with compact support, one should set $r=\infty$ off of the support. We also discuss this case.     

空中目标多波段红外辐射特性描述与仿真分析

针对空中目标在复杂背景下的探测需求,根据实际目标的运动特性,分析目标在飞行高度、飞行姿态角改变时的辐射特点,基于MODTRAN计算得到大气辐射和衰减数据,建立目标的三维模型、热辐射和反射模型,搭建空中目标的红外成像仿真系统.分析和仿真结果表明:在中波波段,目标尾焰的红外辐射比蒙皮强很多,在长波波段,蒙皮的红外辐射比较强,仿真图像的细节比较多,尾焰的红外辐射虽然有所减弱,红外成像效果依旧很好;相同探测条件下,由于位置越高大气越稀薄,探测器的可探测距离会变得比较远.目标红外辐射特性的分析和红外仿真系统的搭建对缩短红外探测器的研制周期和进一步确定探测器波段和系统分辨率等指标提供了参考依据.     

基于气象卫星云图的红外吸收带火山特征分析

飞行目标在2.7和4.3 μm谱段附近具有较强的红外辐射，因此这两个波段是探测飞行目标的最佳波段, 但是由于这两个波段并非大气窗口，不被大多数遥感器包含。对这两个谱段的典型地物特性开展研究具有重要的价值，但由于缺乏必要的数据获取能力，经常面临数据缺乏的问题。世界范围内频频有各种程度的火山爆发，火山爆发时温度较高的火山口，是否对于天基红外探测系统典型目标探测有影响，其影响程度如何一直缺乏相关的分析和研究。基于大气辐射传输理论，利用多元统计分析得到波段转换模型，使用气象卫星已有波段获得红外吸收谱段数据。将火点像元视为明火和背景的混合像元，采用目标与背景分离的方式描述高温目标像元的热辐射。对高温目标辐射量，在气溶胶模式固定的情况下，选取观测天顶角、大气可降水量、大气廓线为自变量影响因子。对于背景辐射亮度关系，选取观测天顶角、大气可降水量、大气廓线、背景温度为自变量影响因子, 利用多元统计，建立相关模型。利用对地面热状态非常敏感的风云三号可见光红外扫描辐射计第3通道数据的统计特征探测火山口，获取高温目标在特定波段的表观多维特征并定量分析。火山的多维特征分析，主要从时间和空间两个维度展开。时间维度是对同一火山在不同时间的数据进行分析，空间维度上，主要统计火山口的辐射亮度和亮度温度的空间分布特征。一般气象卫星分辨率较低，单纯利用像元个数表示火山面积, 明显夸大了火山的实际面积，所以基于亚像元特性对火山进行分析，将混合像元火点视为明火和背景的组合，运用线性光谱混合模型，通过混合像元的辐射率精确计算火山高温点的面积和温度，提高定量分析精度。分析结果表明： 通过仿真手段结合多元统计分析方法建立高温目标的波段转换模型是一种可行的预研手段。在2.7~2.95 μm谱段，火山口在弱背景环境下可能会对高温目标造成干扰，而在4.2~4.45 μm谱段，火山口能量远高于一般地表类型，是不可忽视的干扰。     

Target cell extraction coupled with LC‐MS/MS analysis for screening potential bioactive components in Ginkgo biloba extract with preventive effect against diabetic nephropathy

A rapid and useful approach for screening potential bioactive components in Ginkgo biloba extract (GBE) with preventive effect against diabetic nephropathy (DN) was developed using mesangial cells extraction coupled with high‐performance liquid chromatography tandem mass spectrometry (LC‐MS/MS) analysis. Mesangial cells were first divided into two groups according to their treatments with high glucose or high glucose plus GBE. After incubation for 4, 8, 12, 16, 24 and 48 h, the cells were harvested and extracted with 40% acetic acid in water before LC‐MS/MS analysis. Then, 19 compounds and five metabolites were found to selectively combine with mesangial cells. Notably, compounds including quercetin and rutin were identified or tentatively characterized according to the results of retention time and MS spectra, which is highly consistent with our previous reports that quercetin and rutin are potent protective agents against glomerulosclerosis in DN. Therefore, all these results indicate that target cell extraction coupled with LC‐MS/MS analysis can be successfully applied for predicting the bioactive components in GBE with preventive effect against DN. Copyright © 2014 John Wiley & Sons, Ltd.     

基于粒子滤波的运动目标光电定位仿真研究

运动目标的光电定位不能像静止目标那样简单做均值滤波，鉴于此，引入粒子滤波算法，它不仅可以应用于线性系统，而且还适用于非线性系统。结合光电定位需求，详细推导了计算公式及初值和参数选取公式，对只含测量噪声以及含有测量和运动噪声等的海面运动目标光电无源定位算法进行了仿真计算，验证了算法的有效性，讨论了噪声强度对滤波效果的影响，滤波参数选择对滤波效果的影响，目标运动方式对滤波跟随性的影响，重采样算法对滤波效果的影响等。所得结论为:粒子滤波可用于运动目标光电定位过程，可有效降低定位误差；粒子滤波算法具有较强鲁棒性，适用于噪声较大、目标运动形态变化大等情况。     

Recent Advances in Nanotechnology for the Treatment of Melanoma

Melanoma is one of the most aggressive forms of skin cancer, with few possibilities for therapeutic approaches, due to its multi-drug resistance and, consequently, low survival rate for patients. Conventional therapies for treatment melanoma include radiotherapy, chemotherapy, targeted therapy, and immunotherapy, which have various side effects. For this reason, in recent years, pharmaceutical and biomedical research has focused on new sito-specific alternative therapeutic strategies. In this regard, nanotechnology offers numerous benefits which could improve the life expectancy of melanoma patients with very low adverse effects. This review aims to examine the latest advances in nanotechnology as an innovative strategy for treating melanoma. In particular, the use of different types of nanoparticles, such as vesicles, polymers, metal-based, carbon nanotubes, dendrimers, solid lipid, microneedles, and their combination with immunotherapies and vaccines will be discussed.     

Exploring the relationship between hub proteins and drug targets based on GO and intrinsic disorder

Protein–protein interactions (PPIs) play essential roles in many biological processes. In protein–protein interaction networks, hubs involve in numbers of PPIs and may constitute an important source of drug targets. The intrinsic disorder proteins (IDPs) with unstable structures can promote the promiscuity of hubs and also involve in many disease pathways, so they also could serve as potential drug targets. Moreover, proteins with similar functions measured by semantic similarity of gene ontology (GO) terms tend to interact with each other. Here, the relationship between hub proteins and drug targets based on GO terms and intrinsic disorder was explored. The semantic similarities of GO terms and genes between two proteins, and the rate of intrinsic disorder residues of each protein were extracted as features to characterize the functional similarity between two interacting proteins. Only using 8 feature variables, prediction models by support vector machine (SVM) were constructed to predict PPIs. The accuracy of the model on the PPI data from human hub proteins is as high as 83.72%, which is very promising compared with other PPI prediction models with hundreds or even thousands of features. Then, 118 of 142 PPIs between hubs are correctly predicted that the two interacting proteins are targets of the same drugs. The results indicate that only 8 functional features are fully efficient for representing PPIs. In order to identify new targets from IDP dataset, the PPIs between hubs and IDPs are predicted by the SVM model and the model yields a prediction accuracy of 75.84%. Further research proves that 3 of 5 PPIs between hubs and IDPs are correctly predicted that the two interacting proteins are targets of the same drugs. All results demonstrate that the model with only 8-dimensional features from GO terms and intrinsic disorder still gives a good performance in predicting PPIs and further identifying drug targets.     

Diversity‐Oriented Approach for Chemical Biology

Synthetic molecules that modulate and probe biological events are critical tools in chemical biology. Utilizing combinatorial and diversity‐oriented synthetic strategies, access to large numbers of small molecules is becoming more and more feasible, and research groups in this field can take advantage of the power of chemical diversity. Since the majority of early studies were focused on the discovery of compounds that perturb protein functions, diversity‐based approaches are often considered as therapeutic lead discovery tactics. However, the diversity‐oriented approach can also be applied to advance distinct aims, such as target protein identification, or the development of imaging probes and sensors. This review provides a personal perspective of the chemical‐diversity‐based approach and how this principle can be adapted to various chemical biology studies.     

An Organoruthenium Anticancer Agent Shows Unexpected Target Selectivity For Plectin

Organometallic metal(arene) anticancer agents require ligand exchange for their anticancer activity and this is generally believed to confer low selectivity for potential cellular targets. However, using an integrated proteomics-based target-response profiling approach as a potent hypothesis-generating procedure, we found an unexpected target selectivity of a ruthenium(arene) pyridinecarbothioamide (plecstatin) for plectin, a scaffold protein and cytolinker, which was validated in a plectin knock-out model in vitro. Plectin targeting shows potential as a strategy to inhibit tumor invasiveness as shown in cultured tumor spheroids while oral administration of plecstatin-1 to mice reduces tumor growth more efficiently in the invasive B16 melanoma than in the CT26 colon tumor model.