Global Registration of Subway Tunnel Point Clouds Using an Augmented Extended Kalman Filter and Central-Axis Constraint

Because tunnels generally have tubular shapes, the distribution of tie points between adjacent scans is usually limited to a narrow region, which makes the problem of registration error accumulation inevitable. In this paper, a global registration method is proposed based on an augmented extended Kalman filter and a central-axis constraint. The point cloud registration is regarded as a stochastic system, and the global registration is considered to be a process that recursively estimates the rigid transformation parameters between each pair of adjacent scans. Therefore, the augmented extended Kalman filter (AEKF) is used to accurately estimate the rigid transformation parameters by eliminating the error accumulation caused by the pair-wise registration. Moreover, because the scanning range of a terrestrial laser scanner can reach hundreds of meters, a single scan can cover a tunnel segment with a length of more than one hundred meters, which means that the central axis extracted from the scan can be employed to control the registration of multiple scans. Therefore, the central axis of the subway tunnel is first determined through the 2D projection of the tunnel point cloud and curve fitting using the RANSAC (RANdom SAmple Consensus) algorithm. Because the extraction of the central axis by quadratic curve fitting may suffer from noise in the tunnel points and from variations in the tunnel, we present a global extraction algorithm that is based on segment-wise quadratic curve fitting. We then derive the central-axis constraint as an additional observation model of AEKF to optimize the registration parameters between each pair of adjacent scans. The proposed approach is tested on terrestrial point clouds that were acquired in a subway tunnel. The results show that the proposed algorithm is capable of improving the accuracy of aligning multiple scans by 48%.     

A Systematic Composite Service Design Modeling Method Using Graph-Based Theory

The composite service design modeling is an essential process of the service-oriented software development life cycle, where the candidate services, composite services, operations and their dependencies are required to be identified and specified before their design. However, a systematic service-oriented design modeling method for composite services is still in its infancy as most of the existing approaches provide the modeling of atomic services only. For these reasons, a new method (ComSDM) is proposed in this work for modeling the concept of service-oriented design to increase the reusability and decrease the complexity of system while keeping the service composition considerations in mind. Furthermore, the ComSDM method provides the mathematical representation of the components of service-oriented design using the graph-based theoryto facilitate the design quality measurement. To demonstrate that the ComSDM method is also suitable for composite service design modeling of distributed embedded real-time systems along with enterprise software development, it is implemented in the case study of a smart home. The results of the case study not only check the applicability of ComSDM, but can also be used to validate the complexity and reusability of ComSDM. This also guides the future research towards the design quality measurement such as using the ComSDM method to measure the quality of composite service design in service-oriented software system.     

Using Acoustics to Determine Eelgrass Bed Distribution and to Assess the Seasonal Variation of Ecosystem Service

Eelgrass beds are an important source of primary production in coastal ecosystems. Understanding seasonal variation in the abundance and distribution of eelgrass is important for conservation, and the objectives of this study were to 1) monitor seasonal variation in eelgrass beds using an acoustic monitoring method (Quantitative echo sounder) and 2) broadly quantify the carbon circulation function. We obtained acoustic data of eelgrass beds in coastal areas north and east of Ikunojima Island. Surveys were conducted nine times over the 3-year period from 2011 to 2013 in order to monitor seasonal variation. Acoustic data were obtained and used to estimate the spatial distribution of eelgrass by geostatistical methods. To determine supporting services, we determined carbon sink and carbon fixation by eelgrass beds using data from the National Research Institute of Fisheries and Environment of Inland Sea (2011). The height and distribution of eelgrass beds were at a maximum in May and at a minimum in November of each year. Distribution trends were different between the north and east areas. Supporting services showed the same patterns throughout the year. The area of distribution was considered to be coincident with the life history of eelgrass. Distribution differed by area and changed yearly due to the effects of bottom characteristics and wind direction. Quantifying the supporting services of eelgrass beds was shown to be useful for managing the conservation of coastal ecosystems.     

Mapping Soil Erosion Prevention Using an Ecosystem Service Modeling Framework for Integrated Land Management and Policy

Current spatially explicit approaches to map and assess ecosystem services are often grounded on unreliable proxy data based on land use/cover to derive ecosystem service indicators. These approaches fail to make a distinction between the actual service provision and the underlying ecosystem capacity to provide the service. We present an integrative conceptual framework to estimate the provision of soil erosion prevention by combining the structural impact of soil erosion and the social–ecological processes that allow for its mitigation. The framework was tested and illustrated in the Portel municipality in Southern Portugal, a Mediterranean silvo-pastoral system that is prone to desertification and soil degradation. The results show a clear difference in the spatial and temporal distribution of the capacity for ecosystem service provision and the actual ecosystem service provision. It also shows that although the average actual ecosystem service provision in the region is sufficient to mitigate the existing structural impact, vulnerable areas can be identified where significant soil losses are not mitigated at present. This becomes more significant when comparing different land management intensities. Considering these results, we argue that the general assumption that there is an almost direct relation between the capacity for ecosystem service provision of a given area and the actual ecosystem service provision is wrong. We also discuss how the framework presented here could be used to support land management and policy, and how it can be adapted for other regulating services.     

Surface Modifications Created by Using Engineered Hydrophobins

Hydrophobins are small (ca. 100 amino acids) secreted fungal proteins that are characterized by the presence of eight conserved cysteine residues and by a typical hydropathy pattern. Class I hydrophobins self-assemble at hydrophilic-hydrophobic interfaces into highly insoluble amphipathic membranes, thereby changing the nature of surfaces. Hydrophobic surfaces become hydrophilic, while hydrophilic surfaces become hydrophobic. To see whether surface properties of assembled hydrophobins can be changed, 25 N-terminal residues of the mature SC3 hydrophobin were deleted (TrSC3). In addition, the cell-binding domain of fibronectin (RGD) was fused to the N terminus of mature SC3 (RGD-SC3) and TrSC3 (RGD-TrSC3). Self-assembly and surface activity were not affected by these modifications. However, physiochemical properties at the hydrophilic side of the assembled hydrophobin did change. This was demonstrated by a change in wettability and by enhanced growth of fibroblasts on Teflon-coated with RGD-SC3, TrSC3, or RGD-TrSC3 compared to bare Teflon or Teflon coated with SC3. Thus, engineered hydrophobins can be used to functionalize surfaces.     

Characterizing Cell Adhesion by Using Micropipette Aspiration

We have developed a technique to directly quantify cell-substrate adhesion force using micropipette aspiration. The micropipette is positioned perpendicular to the surface of an adherent cell and a constant-rate aspiration pressure is applied. Since the micropipette diameter and the aspiration pressure are our control parameters, we have direct knowledge of the aspiration force, whereas the cell behavior is monitored either in brightfield or interference reflection microscopy. This setup thus allows us to explore a range of geometric parameters, such as projected cell area, adhesion area, or pipette size, as well as dynamical parameters such as the loading rate. We find that cell detachment is a well-defined event occurring at a critical aspiration pressure, and that the detachment force scales with the cell adhesion area (for a given micropipette diameter and loading rate), which defines a critical stress. Taking into account the cell adhesion area, intrinsic parameters of the adhesion bonds, and the loading rate, a minimal model provides an expression for the critical stress that helps rationalize our experimental results.     

Correction of Eye-estimation by Using Shrunken Predictors

The eye-estimation method is widely used in practice. Several agronomic and biological measures are currently estimated by this method. If a simple linear regression is the kernel model a shrinkage technique can be used for correcting the bias associated with this method. Two predictors of the population total are proposed and the corresponding model-based errors are deduced. A simulation study fixes the behaviour of the predictors.     

Meeting Community Health Worker Needs for Maternal Health Care Service Delivery Using Appropriate Mobile Technologies in Ethiopia

Background

Mobile health applications are complex interventions that essentially require changes to the behavior of health care professionals who will use them and changes to systems or processes in delivery of care. Our aim has been to meet the technical needs of Health Extension Workers (HEWs) and midwives for maternal health using appropriate mobile technologies tools.

Methods

We have developed and evaluated a set of appropriate smartphone health applications using open source components, including a local language adapted data collection tool, health worker and manager user-friendly dashboard analytics and maternal-newborn protocols. This is an eighteen month follow-up of an ongoing observational research study in the northern of Ethiopia involving two districts, twenty HEWs, and twelve midwives.

Results

Most health workers rapidly learned how to use and became comfortable with the touch screen devices so only limited technical support was needed. Unrestricted use of smartphones generated a strong sense of ownership and empowerment among the health workers. Ownership of the phones was a strong motivator for the health workers, who recognised the value and usefulness of the devices, so took care to look after them. A low level of smartphones breakage (8.3%,3 from 36) and loss (2.7%) were reported. Each health worker made an average of 160 mins of voice calls and downloaded 27Mb of data per month, however, we found very low usage of short message service (less than 3 per month).

Conclusions

Although it is too early to show a direct link between mobile technologies and health outcomes, mobile technologies allow health managers to more quickly and reliably have access to data which can help identify where there issues in the service delivery. Achieving a strong sense of ownership and empowerment among health workers is a prerequisite for a successful introduction of any mobile health program.     

Protein-Folding Analysis Using Features Obtained by Persistent Homology

Understanding the protein-folding process is an outstanding issue in biophysics; recent developments in molecular dynamics simulation have provided insights into this phenomenon. However, the large freedom of atomic motion hinders the understanding of this process. In this study, we applied persistent homology, an emerging method to analyze topological features in a data set, to reveal protein-folding dynamics. We developed a new, to our knowledge, method to characterize the protein structure based on persistent homology and applied this method to molecular dynamics simulations of chignolin. Using principle component analysis or nonnegative matrix factorization, our analysis method revealed two stable states and one saddle state, corresponding to the native, misfolded, and transition states, respectively. We also identified an unfolded state with slow dynamics in the reduced space. Our method serves as a promising tool to understand the protein-folding process.     

应用PCR—SSCP快速鉴定结构分枝杆菌复合群

通过聚合酶链反应（ＰＣＲ）－单链的权象多态性（ＳＳＣＰ）技术分析结构分枝杆菌和非结构分枝杆菌临床株的１６Ｓ ｒＤＮＡ基因。６０例临床标本中,２０例为阳性,与传统方法比较无差异。其中分型：１８例为结核支杆菌,２例为结核分枝杆菌和非结核分枝杆菌双重感染。２０例阴性标本中,ＰＣＲ－ＳＳＣＰ又检查出５例阳性。２０例对照标本中,３种传统方法与ＰＣＲ－ＳＳＣＰ法均检测为阴性。全部试验３ｄ执行结果。结核分枝杆菌     

利用功能磁共振研究记忆功能的研究进展

功能磁共振成像(fMRI)作为一种无创伤,可反复实验的成像技术,已被广泛地应用于各项脑功能的研究。用fMRI进行脑功能研究的主要依据是血流敏感性和BOLD对比增强原理。记忆是人脑的高级功能,其过程分为编码加工、固化、存储和提取几个阶段。大脑皮质、海马、乳头体、丘脑是参与记忆的主要解剖结构。记忆的刺激方式对各个脑区的激活是具有差异性的,记忆功能的测量和分析方法也在不断的改进。年龄和性别的不同都会对记忆能力产生影响,同时激活的脑区也会有相应的改变。此外,情感和记忆的关系正越来越受到人们的关注。本文阐述利用功能磁共振成像研究记忆功能的最新进展。     

氨基酸为显色剂比色法测定京尼平的含量

建立了一种京尼平含量的快速测定方法。研究了京尼平与氨基酸的显色反应条件,京尼平(0.0768mg·mL1)与氨基酸溶液(0.2mg·mL1)体积比为1:1,100℃下显色反应10min,检测波长590nm。该方法检测线性范围为0.76～30.73·g·mL1,线性回归方程为Y=0.2409X 0.0036,相关系数为0.9998,最低检测限为0.38μg·mL1,精密度为1.6%。本方法操作简便、快速,且结果准确可靠。     

Detecting Isolation by Distance Using Phylogenies of Genes

We introduce a method for analyzing phylogenies of genes sampled from a geographically structured population. A parsimony method can be used to compute s, the minimum number of migration events between pairs of populations sampled, and the value of s can be used to estimate the effective migration rate M, the value of Nm in an island model with local populations of size N and a migration rate m that would yield the same value of s. Extensive simulations show that there is a simple relationship between M and the geographic distance between pairs of samples in one- and two-dimensional models of isolation by distance. Both stepping-stone and lattice models were simulated. If two demes k steps apart are sampled, then, s, the average value of s, is a function only of k/(Nm) in a one-dimensional model and is a function only of k/(Nm)2 in a two-dimensional model. Furthermore, log(M) is approximately a linear function of log(k). In a one-dimensional model, the regression coefficient is approximately -1 and in a two-dimensional model the regression coefficient is approximately -0.5. Using data from several locations, the regression of log(M) on log(distance) may indicate whether there is isolation by distance in a population at equilibrium and may allow an estimate of the effective migration rate between adjacent sampling locations. Alternative methods for analyzing DNA sequence data from a geographically structured population are discussed. An application of our method to the data of R. L. Cann, M. Stoneking and A. C. Wilson on human mitochondrial DNA is presented.     

Morpho-Functional Analysis Using Procrustes Superimposition by Static Reference

In conventional geometric morphometric analyses of limb long bones, differences in the evolutionary capacity of articular surfaces and non-articular structures often remain unrecognised. It can be shown that areas of high spatial variance dominate shape data, which is problematic for the functional interpretation of limb long bone shape. We herein introduce Procrustes superimposition by static reference (PSSR), a novel analysis strategy that aims to facilitate morpho-functional inference. This procedure exploits the spatial constraint of some reference structures (in our case, articular surfaces) for the superimposition of other subareas (e.g. muscle attachment sites) in relation to that static reference. PSSR allows for the transformation of raw scan data, enabling researchers to extract geometric models of two- and three-dimensional substructures that cannot effectively be integrated with landmarks. As we demonstrate by a simple model analysis for one muscle attachment site, this procedure can yield measures of direct functional relevance. Multivariate analysis of an extensive set of subareas indicates how this type of data relates to conventional shape coordinates. The shape evolution of xenarthran humeri, which has previously been subject to a detailed study (Milne et al., J Zool 278(1):48–56, 2009), serves as a test case. The concept of a variance-based separation of landmark subsets expands mathematical methods by incorporating knowledge about evolutionary constraints. PSSR could therefore find application far beyond the intuitive case study of long bone shape.     

利用捕获载体解析小鼠基因在生物发育过程中的功能

利用特殊构建的捕获载体(trapping vector)随机插入胚胎干细胞(ES细胞)的基因组,被插入基因的转录过程被迫中止,用这样的ES细胞制作出小鼠,可以得到被插入基因的小鼠变异系,通过对变异小鼠的表现型分析。阐明该基因在生长发育过程中的功能和作用。     

Ligand-Target Prediction by Structural Network Biology Using nAnnoLyze

Target identification is essential for drug design, drug-drug interaction prediction, dosage adjustment and side effect anticipation. Specifically, the knowledge of structural details is essential for understanding the mode of action of a compound on a target protein. Here, we present nAnnoLyze, a method for target identification that relies on the hypothesis that structurally similar binding sites bind similar ligands. nAnnoLyze integrates structural information into a bipartite network of interactions and similarities to predict structurally detailed compound-protein interactions at proteome scale. The method was benchmarked on a dataset of 6,282 pairs of known interacting ligand-target pairs reaching a 0.96 of area under the Receiver Operating Characteristic curve (AUC) when using the drug names as an input feature for the classifier, and a 0.70 of AUC for “anonymous” compounds or compounds not present in the training set. nAnnoLyze resulted in higher accuracies than its predecessor, AnnoLyze. We applied the method to predict interactions for all the compounds in the DrugBank database with each human protein structure and provide examples of target identification for known drugs against human diseases. The accuracy and applicability of our method to any compound indicate that a comparative docking approach such as nAnnoLyze enables large-scale annotation and analysis of compound–protein interactions and thus may benefit drug development.