Inference of gene regulatory networks with multi-objective cellular genetic algorithm

Reverse engineering of biochemical networks remains an important open challenge in computational systems biology. The goal of model inference is to, based on time-series gene expression data, obtain the sparse topological structure and parameters that quantitatively understand and reproduce the dynamics of biological systems. In this paper, we propose a multi-objective approach for the inference of S-System structures for Gene Regulatory Networks (GRNs) based on Pareto dominance and Pareto optimality theoretical concepts instead of the conventional single-objective evaluation of Mean Squared Error (MSE). Our motivation is that, using a multi-objective formulation for the GRN, it is possible to optimize the sparse topology of a given GRN as well as the kinetic order and rate constant parameters in a decoupled S-System, yet avoiding the use of additional penalty weights. A flexible and robust Multi-Objective Cellular Evolutionary Algorithm is adapted to perform the tasks of parameter learning and network topology inference for the proposed approach. The resulting software, called MONET, is evaluated on real-based academic and synthetic time-series of gene expression taken from the DREAM3 challenge and the IRMA in vivo datasets. The ability to reproduce biological behavior and robustness to noise is assessed and compared. The results obtained are competitive and indicate that the proposed approach offers advantages over previously used methods. In addition, MONET is able to provide experts with a set of trade-off solutions involving GRNs with different typologies and MSEs.     

Community detection in social networks based on improved Label Propagation Algorithm and balanced link density

Nowadays, community detection has been raised as one of the key research areas in the online social networks mining. One of the most common algorithms in this field is label propagation algorithm (LPA). Even though the LPA method has advantages such as simplicity in understanding and implementation, as well as linear time complexity, it has an important disadvantage of the uncertainty and instability in outcomes, that is, the algorithm detects and reports different combinations of communities in each run. This problem originates from the nature of random selection in the LPA method. In this paper, a novel method is proposed based on the LPA method and the inherent structure, that is, link density feature, of the input network. The proposed method uses a sensitivity parameter (balance parameter); by choosing the appropriate values for it, the desired qualities of the identified communities can be achieved. The proposed method is called Balanced Link Density-based Label Propagation (BLDLP). In comparison with the basic LPA, the proposed method has an advantage of certainty and stability in the output results, whereas its time complexity is still comparable with the basic LPA and of course lowers than many other approaches. The proposed method has been evaluated on real-world known datasets, such as the Facebook social network and American football clubs, and by comparing it with the basic LPA, the effectiveness of the proposed method in terms of the quality of the communities found and the time complexity has been shown.     

基于红外光谱聚类分析的纳滤膜污染动态发展行为研究

污水再生利用是解决水资源短缺问题的有效对策。纳滤技术由于能够生产高质量的再生水,成为污水深度处理、再生利用的有效方法之一。然而,在纳滤过程中存在复杂的、动态的膜污染现象,会导致产水通量、产水质量下降等问题。研究膜污染动态发展的行为,对于膜污染的分阶段针对性控制具有重要意义。有机物是污染层动态发展过程的重要指示性成分,红外光谱是表征污染层发展过程中表面有机物官能团变化情况的重要手段。但由于红外光谱中峰的数量多,系列样品之间峰强度的差别较小（尤其是当膜污染过程中的采样间隔较小时）,利用直观观察不易甄别不同样品间的谱图差异及其变化趋势,在此水平上难以对膜污染阶段进行准确识别、对各阶段特征进行有说服力的分类概括。为探索膜污染的动态发展过程,本研究将傅里叶变换红外光谱与统计学聚类分析相结合,对膜污染过程中不同时间点的膜样本进行红外光谱分析,再对红外光谱数据进行一系列预处理和系统聚类分析,从而客观解读膜污染动态发展过程中系列样品红外光谱分阶段变化规律。考虑到类别间距离度量方法、红外吸收峰强度标准化、峰之间自相关性、峰与样本之间交互作用等因素的影响,研究采用对应分析对红外数据进行预处理,提取各样本在主要维度上的得分,随后基于标准化欧式距离对各样本进行聚类。在为期一个月的城市污水深度处理纳滤试验过程中,由于污染物在膜表面累积,纳滤膜发生了较为严重的污染。通过对13个不同时间点的膜样本进行红外光谱聚类发现,膜污染可清晰划分为如下阶段：空白膜、阶段Ⅰ（3 h～8 d）、阶段Ⅱ（10～15 d）和阶段Ⅲ（20～30 d）。采用红外聚类,得到膜表面X射线光电子能谱（XPS）和三磷酸腺苷（ATP）含量分析等方法的交互验证。结果表明,随着膜污染的发展,膜表面有机物成分与共存微生物量发生协同变化,各阶段大致特征为：阶段Ⅰ各类有机污染物初步覆盖,微生物开始富集;阶段Ⅱ多糖类污染物比例上升,微生物的富集趋于稳定;阶段Ⅲ整体污染趋于成熟,有机污染物氢键特征更加明显。该研究通过对红外数据进行聚类分析,能够灵敏地探测各红外图谱之间的差别,有助于对红外光谱规律的深度挖掘,为膜污染阶段的识别和划分提供了一种客观、自动、可量化的辅助性方法,并且有助于归纳出不同阶段的污染层特征,可作为膜污染时序特征的侦查手段。此外,除了膜污染的研究,在材料、吸附等领域,只要有一系列变化的红外光谱,均可尝试采用红外光谱聚类分析方法,获取基于红外特征的定类信息或分阶段规律。     

EPR study of the diluted magnetic semiconductor CuGa1−xMnxTe2

Electron paramagnetic resonance (EPR) experiments were made in the diluted magnetic semiconductor CuGa_1−xMn_xTe₂, in the temperature range 70<T<300 K. The samples were synthesized by direct fusion of stoichiometric mixtures of the elements, with Mn composition from x=0.0 to 0.25. The EPR spectra were measured as function of temperature, Mn composition, and field orientation. The temperature variation of the resonance field shows a critical point at about 235 K, and is associated with a transition from the ferromagnetic to the superparamagnetic state. The resonance field was also measured as a function of the field angle, and displays a well-defined uniaxial symmetry. This uniaxial field depends on the Mn concentration and is due to tetragonal distortions induced by Mn²⁺ at Ga sites, and the demagnetizing effects due to formation of ferromagnetism (FM) Mn-clusters.     

Cavity control as a new quantum algorithms implementation treatment

Based on recent experiments [Nature 449, 438 (2007) and Nature Physics 6, 777 (2010)], a new approach for realizing quantum gates for the design of quantum algorithms was developed. Accordingly, the operation times of such gates while functioning in algorithm applications depend on the number of photons present in their resonant cavities. Multi-qubit algorithms can be realized in systems in which the photon number is increased slightly over the qubit number. In addition, the time required for operation is considerably less than the dephasing and relaxation times of the systems. The contextual use of the photon number as a main control in the realization of any algorithm was demonstrated. The results indicate the possibility of a full integration into the realization of multi-qubit multiphoton states and its application in algorithm designs. Furthermore, this approach will lead to a successful implementation of these designs in future experiments.     

The Performance of Orthogonal Multi-Matching Pursuit under the Restricted Isometry Property

The orthogonal multi-matching pursuit (OMMP) is a natural extension of the orthogonal matching pursuit (OMP).We denote the OMMP with the parameter $M$ as OMMP($M$) where $M$ ≥ 1 is an integer. The main difference between OMP and OMMP($M$) is that OMMP($M$) selects $M$ atoms per iteration, while OMP only adds one atom to the optimal atom set. In this paper, we study the performance of orthogonal multi-matching pursuit under RIP. In particular, we show that, when the measurement matrix $A$ satisfies (25$s$, 1/10)-RIP, OMMP($M_0$) with $M_0$ = 12 can recover $s$-sparse signals within $s$ iterations. We furthermore prove that OMMP($M$) can recover $s$-sparse signals within $O(s/M)$ iterations for a large class of $M$.     

组合优化若干经典问题新进展

组合优化是20世纪中后期发展起来的一个运筹学与计算机科学交叉学科分支, 研究具有离散结构的优化问题解的性质和求解方法. 由于不同离散问题的结构差异, 出现了各种各样的研究手段和技巧. 针对组合优化的若干经典问题, 简述了算法和复杂性理论的研究进展.