Mean Path Length Research Articles

Evolution of Centrality Measurements for the Detection of Essential Proteins in Biological Networks.

Current breakthroughs in high-throughput technologies have propelled the development of databases that systematically store knowledge of how genes, proteins, and metabolites interact. To elucidate the mechanisms of molecular interaction, such data can be represented through networks where nodes are biological entities (e.g., gene, protein, miRNA, transcription factor, and metabolites) and edges are associations/interactions between them (e.g., co-expression, signaling, regulation, and physical interaction). One approach to use such networks is to analyze their topological structure and try to relate this to biological function. Topological analysis hints at the possible behavior of a network in the regulation of biological processes or phenotypes and help in unveiling the core mechanisms. Broadly speaking, topological parameters can be used to explore: (1) collective behaviors (global properties such as diameter, small-world and scale-free properties of a network), (2) subnetwork behaviors (functional motif discovery), and (3) individual behaviors (prioritization of important nodes by centrality indices) of various network components (Ma and Gao, 2012). One of the first attempts found in the literature considered centrality related to lethality, and is known as the centrality–lethality rule proposed by Jeong et al. indicating a positive correlation between connectivity and indispensability in the yeast protein-protein interaction map (Jeong et al., 2001). Similarly, Wagner and Fell analyzed the structure of a large metabolic network of E. coli using metabolite node degree and shortest mean path length and observed small world like properties that follow power-law distributions (Wagner and Fell, 2001). In these two comprehensive studies, an old metric system (centrality index) was applied with different strategies, aiming to answer the following question: Do centrality indices predict the essential nodes in the biological networks? Remarkably, topological analyses carried out in transcriptional regulatory (TR) and metabolic networks have been a valuable guide to identify those biological components, called essential nodes, that play a major role in vital functional activities for some microorganisms (Resendis-Antonio et al., 2005, 2012). The relationship between nodes topological features, such as their degree, and their essentiality remains however debated (Coulomb et al., 2005). Prediction of essential proteins is a challenging task because it needs experimental approaches that are expensive, time-consuming, and laborious (Zhong et al., 2013; Li et al., 2014). To optimize the search of essential nodes in biological networks, a series of computational methods that include topological criteria have been proposed. In this paper, we review the cutting edge computational methods by categorizing them according to their underlying strategies to identify essential components. In each case, we discuss their predictive experimental power and identify shortcomings.

Bundled-optode implementation for 3D imaging in functional near-infrared spectroscopy.

The paper presents a functional near-infrared spectroscopy (fNIRS)-based bundled-optode method for detection of the changes of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) concentrations. fNIRS with 32 optodes is utilized to measure five healthy male subjects' brain-hemodynamic responses to arithmetic tasks. Specifically, the coordinates of 256 voxels in the three-dimensional (3D) volume are computed according to the known probe geometry. The mean path length factor in the Beer-Lambert equation is estimated as a function of the emitter-detector distance, which is utilized for computation of the absorption coefficient. The mean values of HbO and HbR obtained from the absorption coefficient are then applied for construction of a 3D fNIRS image. Our results show that the proposed method, as compared with the conventional approach, can detect brain activity with higher spatial resolution. This method can be extended for 3D fNIRS imaging in real-time applications.

Social networks in the Little Scrub Island ground lizard (Ameiva corax)

Ameiva corax is a diurnal, widely foraging lizard endemic to a small (<2 ha) Caribbean island and is known for social foraging, whereby individuals aggregate at large food items (e.g., bird eggs and cactus fruits). We characterized the social network for A. corax through focal observations and surveys, which delineated associations for 82 known individuals. Lizards varied greatly in the extent to which they were linked to the social network. Approximately 31 % of individuals were not observed in any associations while one individual associated with 22 % (n = 18) of the animals in the study area. Larger lizards tended to be more central to the social network; body size was positively correlated with number of associations (degree) and centrality (betweenness), but negatively correlated with average distance between an individual and its associates (mean path length). Larger individuals were also associated with lower clustering coefficients, indicating that their associates were less closely interconnected. Sex was not related to number of associations (degree), but did help explain some patterns. The extent to which a lizard’s associates were of the same sex (homophily) was related to both sex and body size. Females had lower homophily scores than males; within each sex larger lizards tended to have lower homophily.

Consequences of air around an ionization chamber: Are existing solid phantoms suitable for reference dosimetry on an MR-linac?

A protocol for reference dosimetry for the MR-linac is under development. The 1.5 T magnetic field changes the mean path length of electrons in an air-filled ionization chamber but has little effect on the electron trajectories in a surrounding phantom. It is therefore necessary to correct the response of an ionization chamber for the influence of the magnetic field. Solid phantoms are used for dosimetry measurements on the MR-linac, but air is present between the chamber wall and phantom insert. This study aimed to determine if this air influences the ion chamber measurements on the MR-linac. The absolute response of the chamber and reproducibility of dosimetry measurements were assessed on an MR-linac in solid and water phantoms. The sensitivity of the chamber response to the distribution of air around the chamber was also investigated. Measurements were performed on an MR-linac and replicated on a conventional linac for five chambers. The response of three waterproof chambers was measured with air and with water between the chamber and the insert to measure the influence of the air volume on absolute chamber response. The distribution of air around the chamber was varied indirectly by rotating each chamber about the longitudinal chamber axis in a solid phantom and a water phantom (waterproof chambers only) and measuring the angular dependence of the chamber response, and varied directly by displacing the chamber in the phantom insert using a paper shim positioned at different orientations between the chamber casing and the insert. The responses of the three waterproof chambers measured on the MR-linac were 0.7%-1.2% higher with water than air in the chamber insert. The responses of the chambers on the conventional linac changed by less than 0.3% when air in the insert was replaced with water. The angular dependence of the chambers ranged from 0.6% to 1.9% in the solid phantom on the MR-linac but was less than 0.5% in water on the MR-linac and less than 0.3% in the solid phantom on the conventional linac. Inserting a shim around the chamber induced changes of the chamber response in a magnetic field of up to 2.2%, but the change in chamber response on the conventional linac was less than 0.3%. The interaction between the magnetic field and secondary electrons in the air around the chamber reduces the charge collected from 0.7% to 1.2%. The large angular dependence of ion chambers measured in the plastic phantom in a magnetic field appears to arise from a change of air distribution as the chamber is moved within the insert, rather than an intrinsic isotropy of the chamber sensitivity to radiation. It is recommended that reference dosimetry measurements on the MR-linac can be performed only in water, rather than in existing plastic phantoms.

Creating interconnect topologies by algorithmic edge removal: MOD and SMOD graphs

We introduce a method of constructing classes of graphs by algorithmic removal of entire groups of edges. Our approach to creating new classes of graphs is to focus entirely on the structure and properties of an adjacency matrix. At an initialisation step of the algorithm we start with a complete fully connected graph. In Part I we present MOD and arrested MOD graphs resulting from removal of square blocks of edges at each iteration and substitution of removed blocks with a diagonal matrix with one extra pivotal element along the main diagonal. The MOD graphs possess unique and useful properties. All important graph measures are easily expressed in analytical form and are presented in the paper. Several important properties of MOD graphs are compared very favourably with graphs representing common interconnect topologies: hypercube, 3D and 5D tori, TOFU and dragonfly. This lead us to consider MOD and arrested MOD graphs as interesting candidates for effective supercomputer interconnects. In Part II, at each iterative step we successively remove triangular shapes from the adjacency matrix. This iterative process leads to the final matrix which has two Sierpinski gaskets aligned along the main diagonal. It will be shown below that this new class of graphs is not a Sierpinski graph, since it is the adjacency matrix which has a structure of a Sierpinski gasket, and not a graph described by this matrix. We call this new class of graphs Sierpinski-Michalewicz-Or lowski-Deng SMOD graphs. The most remarkable property of the SMOD class of graphs, is that irrespective of the graph order, the diameter is constant and equals 2. The size of the graph, or the total number of edges, is about 10% of the size of a complete graph of the same order. We analyse important graph theoretic characteristics related to the topology such as diameter as a function of graph order, size, mean path length, ratio of the graph size to the size of a complete graph of the same order, and some spectral properties.

Stability vs. organization: Potential of a trophic model for the management of shallow tropical streams

Streams in the Hondo River basin (Mexico–Belize) face ecological disturbances caused by use of fertilizers and pesticides, as well as invasion by exotic species. These threats can affect ecosystem functioning, with loss of biotic integrity. Mass-balance trophic models were developed to quantify the energy flow and assess the maturity and health states for three locations in the basin, in two seasons. Quantitative sampling was carried out for plankton, fish, macrobenthos, insects, benthic autotrophs, detritus, and exported organic matter. Field sampling was supplemented with a literature review to define functional groups and their diets. Results showed that more than 50% of the energy flow originated from detritus, which suggests that the systems are bottom-up controlled. Low values of energy transfer efficiency, connectivity, omnivory, recycling, mean path length, and ascendency suggest that the freshwater bodies in this basin are oligotrophic, but they are not in a good health and thus have low stability and are susceptible to disturbance, despite the fact that they also have a high number of specialized functional groups, indicative of a well-organized food web, supposed to be representative of healthy ecosystems. The potential of these models to manage shallow tropical streams is discussed.

Multiscale Geonavigational Approach to Understand Organ Biosystems and their Cellular Inhabitants in Health and Disease

Recent cutting edge advances have led to the development of multibeam electron microscopy (mSEM), a method enabling nanometer resolution electron microscopy imaging of macroscopic samples in feasible time frames [1]. In an industry-university-clinical collaboration, we have recently created the first geonavigational map of the human hip, enabling understanding of organ scale human health in context of cellular inhabitants. Through implementation of geonavigational techniques including Google Maps API and dropping of pins to mark relevant landmarks including viable and pyknotic cells, as well as blood vessels, current hypotheses can be tested within each dataset (single patient) and between patients, allowing an unprecedented systems biology approach to understand human organ and ecosystem health and disease.[2] Using this approach in the first fully mapped dataset, we showed that subtle but statistically significant differences are observable between viable and dying osteocytes and their nearest neighboring cell. In contrast, no significant differences were observed in mean path lengths of viable and dying cells to the nearest blood supply. These data implicate cellular connectivity as a measure of cell health. This study may pave the way for development of automated diagnostic measures for assessment of emergent pathologies and disease diagnosis, from cell to organ length scales.

基于生态通道模型的长江口水域生态系统结构与能量流动分析

PDF HTML阅读 XML下载 导出引用 引用提醒 基于生态通道模型的长江口水域生态系统结构与能量流动分析 DOI: 10.5846/stxb201501150129 作者: 作者单位: 中国科学院生态环境研究中心,南京水利科学研究院,中国水产科学研究院东海水产研究所,南京水利科学研究院,三峡大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金资助项目（51425902，51409242）；国家重点基础研究发展计划973项目（2010CB429000） Analysis of the ecosystem structure and energy flow of the Yangtze River estuary and adjacent seas, based on the Ecopath model Author: Affiliation: RCEES,NHRI,,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:利用Ecopath with Ecosim在前期研究的基础上构建了3个时期（2000年秋、2006年秋、2012年秋）长江口水域生态系统的生态通道模型，分析对比了三峡工程蓄水前中后期，长江口水域生态系统结构与能量流动特征。模型将长江口水域生态系统划分为鱼类、虾类、蟹类、头足类、底栖动物、浮游动物、浮游植物、碎屑等17个功能组，基本覆盖了长江口生态系统能量流动的主要途径。模型结果分析表明：蓄水前中后期，长江口水域生态系统各功能组营养级组成和分布相近，但由于长江口渔业过度捕捞，蓄水中后期多数功能组的生态营养转换率被动提高。长江口渔获物的组成未发生明显变化，但渔获物的平均营养级降低，渔获量减少。蓄水中后期，生态系统中牧食食物链的重要性增加，碎屑食物链的重要性降低，这与蓄水之后长江入海径流改变、泥沙量减少、陆源污染增加关系密切。结果表明，蓄水前中后期，生态系统均处于不成熟阶段，蓄水后生态系统总生物量、初级生产量及流向碎屑的能量呈降低趋势，但系统的净效率和再循环率升高。 Abstract:The cumulative impacts of water conservancy projects in the Yangtze River basin, especially the Three Gorges Reservoir, have had a significant effect on the biological and ecological integrity of the Yangtze River estuarine ecosystem. This research establishes three ecopath models of the Yangtze River estuary and adjacent seas before (the autumn of 2000), during (the autumn of 2006), and after (the autumn of 2012) the impoundments of the Three Gorges Reservoir, using Ecopath and Ecosim software to characterize and compare the estuarine ecosystem's food web structure and energy flow. Sensitivity analyses were carried out to evaluate the uncertainty levels of the models. The three models consisted of 17 functional groups covering the main paths of the ecosystem food web, including piscivorous fishes, generalist predators, shrimp predators, zooplanktivores, crab predators, other pelagic fishes, other demersal fishes, other benthic fishes, shrimp, crabs, jellyfish, cephalopods, macrobenthos, meiobenthos, zooplankton, phytoplankton, and detritus. The simulated results showed that the values of trophic levels (TL) ranged from 1.000 to 3.802 in 2000 (before the impoundments), from 1.000 to 4.058 in 2006 (during the impoundments), and from 1.000 to 4.019 in 2012 (after the impoundments). This indicates that the TLs distributions of the functional groups were similar under all three conditions. However, the ecotrophic efficiencies of commercial species, such as Pseudosciaena polyactis, were elevated because of the increased fishing intensity in the Yangtze River estuary. The structure of catches did not change noticeably during this period, but the mean trophic level of the catch decreased from 3.406 to 3.369, as did the number of catches (from 1.026 t km-2 a-1 to 0.719 t km-2 a-1). Meanwhile, after the impoundments the role of the detritus food chain became less important to the energy transfer process than that of the grazing food chain, and over 90% of the energy flows were assembled in TL I and II, most of which flow into detritus and could be a source of internal pollution. The total transfer efficiency of the Yangtze River estuary ecosystem was 10.2% in 2000, 10.0% in 2006 and 9.4% in 2012. All of these negative effects are likely to be closely related to reductions in freshwater and sediment discharges, as well as the increase of land-based pollution in the Yangtze River Basin. Furthermore, the result also showed that the parameters of total biomass, total primary production, and the sum of all flows into detritus gradually decreased; however, the gross efficiency, Finn cycling index, Finn's mean path length, and system omnivory index increased. The ecosystems (before, during, and after impoundments) were found to remain in the immature stage. 参考文献 相似文献 引证文献

Role of topology in the spontaneous cortical activity

Spontaneous cortical activity can show very complex collective emerging features, with, in some cases, the alternation of of network quiescence and of generalized spiking and neuronal depolarization [1]. Results on in vitro and in vivo up states has suggested that this spontaneous activity occurs in a highly structured way, with repeating spatiotemporal patterns of cellular activity [1,2]. Because of their stereotyped spatio-temporal dynamics, it has been conjectured that network up states are circuit attractors that could implement memory states [1]. The precise mechanisms by which these up states transitions occur is still unclear, but it seems to rely on network mechanisms [1]. Previous papers [3,4] have studied a leaky IF model whose connectivity was designed in such a manner as to favor the spontaneous emergence of collective oscillatory spatio-temporal patterns of spikes. In this model the alternation of up and down states does not depend on a kind of neuron bistability, nor on synaptic depression, but is rather a network effect. The model consists in N leaky IF units, with Poissonian noise. Structured connections Jij was fixed with a [3,4] inspired to spike time dependent plasticity (STDP). After the learning and pruning procedure [3], about 12% of the N(N-1) connections survive as positive connections, and about 27% as negative connections. There's a balance condition, such that the sum of connections entering on a single neuron ΣjJij is of order 1/√N, and therefore vanishes in the thermodynamic limit. In order to check if the transition region with bimodal distribution of the firing rate survive even after changes in the topology of the network, in this work we reshuffle a fraction of the connections. For each chosen connection we change the presynaptic neuron, choosing as the new presynaptic neuron a random neuron of the network. After reshuffling a fraction f of connections, not only the number of excitatory and inhibitory connections is the same as before, but also the strengths of the connections are the same, and only the topology (number of loops, mean path length, clustering coefficient, etc.) is changed. We observe that reshuffling the connections changes the features of the dynamics dramatically. Before reshuffling, i.e. with f = 0 and connections dictated by the learning rule of [3], the system has a transition from a regime of Poissonian noise activity to a regime of spontaneous persistent collective replay, and at the transition point the network dynamics shows an intermittent reactivation of the stored patterns, with alternation of up and down state, and bimodal distribution of spiking rate (fig. ​(fig.1A).1A). Reshuffling a small fraction of connections, leaving all the other parameters unchanged, we observe that the transition region with bimodal distribution disappears, and the dynamics is Poissonian with unimodal rate distribution for all the parameters investigated. These results shows the role of topology in dictating the emerging collective dynamics of neural circuits. Figure 1 Distribution of the spiking rates for the model with (A) no reshuffling f = 0, (B) reshuffling a fraction f = 0.1 of connections, and (C) all connections reshuffled f = 1. All other parameters are the same (N = 3000 neurons, H0/Θ = 0.221, noise ...

Complex network analysis of resting state EEG in amnestic mild cognitive impairment patients with type 2 diabetes.

Purpose: Diabetes is a great risk factor for dementia and mild cognitive impairment (MCI). This study investigates whether complex network-derived features in resting state EEG (rsEEG) could be applied as a biomarker to distinguish amnestic mild cognitive impairment (aMCI) from normal cognitive function in subjects with type 2 diabetes (T2D).Method: In this study, EEG was recorded in 28 patients with T2D (16 aMCI patients and 12 controls) during a no-task eyes-closed resting state. Pair-wise synchronization of rsEEG signals were assessed in six frequency bands (delta, theta, lower alpha, upper alpha, beta, and gamma) using phase lag index (PLI) and grouped into long distance (intra- and inter-hemispheric) and short distance interactions. PLI-weighted connectivity networks were also constructed, and characterized by mean clustering coefficient and path length. The correlation of these features and Montreal Cognitive Assessment (MoCA) scores was assessed.Results: Main findings of this study were as follows: (1) In comparison with controls, patients with aMCI had a significant decrease of global mean PLI in lower alpha, upper alpha, and beta bands. Lower functional connection at short and long intra-hemispheric distance mainly appeared on the left hemisphere. (2) In the lower alpha band, clustering coefficient was significantly lower in aMCI group, and the path length significantly increased. (3) Cognitive status measured by MoCA had a significant positive correlation with cluster coefficient and negative correlation with path length in lower alpha band.Conclusions: The brain network of aMCI patients displayed a disconnection syndrome and a loss of small-world architecture. The correlation between cognitive states and network characteristics suggested that the more in deterioration of the diabetes patients' cognitive state, the less optimal the network organization become. Hence, the complex network-derived biomarkers based on EEG could be employed to track cognitive function of diabetic patients and provide a new diagnosis tool for aMCI.

Indirect Energy Flows in Niche Model Food Webs: Effects of Size and Connectance.

Indirect interactions between species have long been of interest to ecologists. One such interaction type takes place when energy or materials flow via one or more intermediate species between two species with a direct predator-prey relationship. Previous work has shown that, although each such flow is small, their great number makes them important in ecosystems. A new network analysis method, dynamic environ approximation, was used to quantify the fraction of energy flowing from prey to predator over paths of length greater than 1 (flow indirectness or FI) in a commonly studied food web model. Web structure was created using the niche model and dynamics followed the Yodzis-Innes model. The effect of food web size (10 to 40 species) and connectance (0.1 to 0.48) on FI was examined. For each of 250 model realizations run for each pair of size and connectance values, the FI of every predator-prey interaction in the model was computed and then averaged over the whole network. A classification and regression tree (CART) analysis was then used to find the best predictors of FI. The mean FI of the model food webs is 0.092, with a standard deviation of 0.0279. It tends to increase with system size but peaks at intermediate connectance levels. Of 27 potential predictor variables, only five (mean path length, dominant eigenvalue of the adjacency matrix, connectance, mean trophic level and fraction of species belonging to intermediate trophic levels) were selected by the CART algorithm as best accounting for variation in the data; mean path length and the dominant eigenvalue of the adjacency matrix were dominant.

A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

This paper reviews the most relevant works that have investigated robustness in power grids using Complex Networks (CN) concepts. In this broad field there are two different approaches. The first one is based solely on topological concepts, and uses metrics such as mean path length, clustering coefficient, efficiency and betweenness centrality, among many others. The second, hybrid approach consists of introducing (into the CN framework) some concepts from Electrical Engineering (EE) in the effort of enhancing the topological approach, and uses novel, more efficient electrical metrics such as electrical betweenness, net-ability, and others. There is however a controversy about whether these approaches are able to provide insights into all aspects of real power grids. The CN community argues that the topological approach does not aim to focus on the detailed operation, but to discover the unexpected emergence of collective behavior, while part of the EE community asserts that this leads to an excessive simplification. Beyond this open debate it seems to be no predominant structure (scale-free, small-world) in high-voltage transmission power grids, the vast majority of power grids studied so far. Most of them have in common that they are vulnerable to targeted attacks on the most connected nodes and robust to random failure. In this respect there are only a few works that propose strategies to improve robustness such as intentional islanding, restricted link addition, microgrids and Energies 2015, 8 9212 smart grids, for which novel studies suggest that small-world networks seem to be the best topology.

Collisional statistics and dynamics of two-dimensional hard-disk systems: From fluid to solid.

We perform extensive MD simulations of two-dimensional systems of hard disks, focusing on the collisional statistical properties. We analyze the distribution functions of velocity, free flight time, and free path length for packing fractions ranging from the fluid to the solid phase. The behaviors of the mean free flight time and path length between subsequent collisions are found to drastically change in the coexistence phase. We show that single-particle dynamical properties behave analogously in collisional and continuous-time representations, exhibiting apparent crossovers between the fluid and the solid phases. We find that, both in collisional and continuous-time representation, the mean-squared displacement, velocity autocorrelation functions, intermediate scattering functions, and self-part of the van Hove function (propagator) closely reproduce the same behavior exhibited by the corresponding quantities in granular media, colloids, and supercooled liquids close to the glass or jamming transition.

Baicalin alleviates diabetes‑associated cognitive deficits via modulation of mitogen-activated protein kinase signaling, brain‑derived neurotrophic factor and apoptosis.

Baicalin is an important active component of the medicinal herb Scutellaria baicalensis Georgi and has shown a variety of pharmacological actions. The present study aimed to evaluate the neuroprotective effects of baicalin against diabetes‑associated cognitive deficits (DACD) in rats and to elucidate the potential molecular mechanisms of action. A rat model of diabetes mellitus was prepared by intraperitoneal injection of streptozotocin. After the successful establishment of the diabetic rat model, baicalin (50, 100 and 200 mg/kg) or vehicle was administrated for seven weeks. Learning and memory function were assessed using the Morris water maze test. At the end of the experiment, the activities of acetylcholinesterase (AChE) and choline acetylase (ChAT) were determined using commercial kits. Furthermore, the expression of proteins involved in mitogen‑activated protein kinase (MAPK) cascades [extracellular signal‑regulated kinase (ERK), c‑Jun N‑terminal kinase (JNK) and p38], brain‑derived neurotrophic factor (BDNF) and apoptosis‑associated proteins [caspase‑3, B-cell lymphoma 2 (Bcl‑2) and Bcl-2-associated X protein (Bax)] were detected by western blot analysis. Caspase‑3 activity was also analyzed using a commercial kit. The results demonstrated that diabetic rats exhibited decreases in body weight, decreases in the percentage of time spent in the target quadrant and the number of times of crossing the platform in the water maze test, as well as decreases in neuronal survival, ChAT, phosphorylated (p)ERK, BDNF and Bcl‑2. Furthermore, diabetic rats showed increases in escape latency and mean path length in the water maze test, increases in the levels of hippocampal AChE, p‑JNK, p‑p38, caspase‑3 and Bax as well as plasma glucose. However, in diabetic rats treated with baicalin, all of the abovementioned observations were obviously reversed. The findings suggested that baicalin exerts neuroprotective effects against DACD via modulation of MAPK cascades, BDNF and apoptosis.

Brain Default Mode Network Changes after Renal Transplantation: A Diffusion-Tensor Imaging and Resting-State Functional MR Imaging Study.

To investigate structural and functional alterations of the default mode network (DMN) in the brain after renal transplantation in patients with end-stage renal disease by using diffusion-tensor imaging and resting-state functional MR imaging. This prospective study was approved by the local medical research ethics committee, and written informed consent was obtained. Twenty-one patients with end-stage renal disease (15 men, six women; mean age ± standard deviation, 32 years ± 9.5) who were scheduled to undergo renal transplantation and 21 healthy control subjects (15 men, six women; mean age, 31 years ± 6.5) were included. Diffusion-tensor imaging and resting-state functional MR imaging were performed in all subjects. Patients were imaged both before and 1 month after renal transplantation. Structural (mean diffusivity, fractional anisotropy, path length, and number of tracts derived from diffusion-tensor imaging tractography) and functional (temporal correlation coefficient derived from resting-state functional MR imaging) connectivity of the DMN were quantitatively compared with two-sample t tests or paired t tests. Intergroup correlation analysis was performed to compare structural or functional indexes and results of neuropsychological or blood biochemistry tests. Mean diffusivity was decreased in the fiber bundles connecting the posterior cingulate cortex and the precuneus to the bilateral inferior parietal lobules in patients after renal transplantation compared with that in patients before transplantation (P < .05). Temporal correlation coefficients for patients after renal transplantation nearly reached the levels of those for control subjects (all, P > .05). The change in mean diffusivity of the fiber bundles connecting the posterior cingulate cortex and the precuneus to the right inferior parietal lobule positively correlated with the change in hematocrit levels (r = 0.522, P = .015), the change in temporal correlation coefficients between the posterior cingulate cortex or precuneus and left or right inferior parietal lobules correlated with changes in number connection test type A scores (r = -0.549, P = .010) and digit symbol test scores (r = 0.533, P = .013). Functional connectivity changes in the DMN, which were associated with improved hematocrit levels and cognitive function, may recover earlier than structural connectivity changes do 1 month after renal transplantation.

Exploratory social network analysis of affiliation networks of Indian listed companies

Interlocking directorates play a crucial role in the corporate governance system. In this paper we analyse the structural characteristics of the network of the interlocking directorate of National Stock Exchange (NSE) listed Indian companies using the tools of social network analysis to examine the effects of the underlying network on the performance of companies and directors. A component analysis of the network shows that 78.5% of the companies fall under one giant component with the largest island containing 6 companies. The giant component was further analysed for clusters and centrality measures. The results show that the highly boarded directors who constitute just 2.25% of the director population are associated with 42% of the total listed companies which account for 65.5% of the total market capitalisation. The top central actors in both director as well as company networks have been identified. The calculated values of mean path length and global clustering coefficient provide evidence for the existence of small world structure in the Indian corporate field.

Analysis of the enzyme network involved in cattle milk production using graph theory.

Understanding cattle metabolism and its relationship with milk products is important in bovine breeding. A systemic view could lead to consequences that will result in a better understanding of existing concepts. Topological indices and quantitative characterizations mostly result from the application of graph theory on biological data. In the present work, the enzyme network involved in cattle milk production was reconstructed and analyzed based on available bovine genome information using several public datasets (NCBI, Uniprot, KEGG, and Brenda). The reconstructed network consisted of 3605 reactions named by KEGG compound numbers and 646 enzymes that catalyzed the corresponding reactions. The characteristics of the directed and undirected network were analyzed using Graph Theory. The mean path length was calculated to be4.39 and 5.41 for directed and undirected networks, respectively. The top 11 hub enzymes whose abnormality could harm bovine health and reduce milk production were determined. Therefore, the aim of constructing the enzyme centric network was twofold; first to find out whether such network followed the same properties of other biological networks, and second, to find the key enzymes. The results of the present study can improve our understanding of milk production in cattle. Also, analysis of the enzyme network can help improve the modeling and simulation of biological systems and help design desired phenotypes to increase milk production quality or quantity.

Reliability of modified sensory interaction test as measured with force platform.

The test–retest reliability of the modified sensory interaction test on a force platform was performed in a group of 26 young and 15 elderly females for four sensory conditions: standing on firm and compliant surface with eyes open and closed. The test–retest reliability was good to excellent in both groups, with higher level of test–retest reliability in more demanding conditions. The most reliable time-domain variables for standing on firm surface with eyes open were: sway area from principal components (ICC = 0.77) for young and mean velocity, medio-lateral and total path lengths (ICC = 0.91) for elderly. For eyes closed, the most reliable variables were antero-posterior path length and sway area calculated by Fourier coefficients (ICC = 0.85) for young and medio-lateral path length (ICC = 0.93) for elderly. For compliant surface with open eyes, the most reliable variable was medio-lateral variability (ICC = 0.83) for young and total path length and mean velocity (ICC = 0.92) for elderly participants, whereas for eyes closed the most reliable variables were mean velocity, total and medio-lateral path lengths for young, and mean velocity for elderly group, all with ICC = 0.90. Modified sensory interaction test is therefore a reliable measure for balance and could be recommended as an outcome measure for balance retraining programmes.

Effect of shoes with rounded soft soles in the anterior–posterior direction on the center of pressure during static standing

Shoes with curved rocker bottom soles may induce an unstable standing posture. This study was aimed to mainly examine the effect of such shoes on the center of pressure (COP) during static standing. Ten healthy young male adults had their COP measured during static standing with four types of shoe conditions (Stretch Walker®: SW (shoes with curved rocker bottom soles), Masai Barefoot Technology®: MBT (similar to SW in form and material), more conventionally soled shoes with a typical toe-spring: MCS, and bare feet: BF) for 60s. The mean path length and mean velocity of Y (front-back) axis were significantly greater when wearing the MBT than when wearing the SW, and when wearing the SW than when BF or when wearing the MCS. In addition, mean velocity of X (left-right) axis, area surrounding root mean square, root mean square, and root mean square of Y-axis were significantly greater when wearing the MBT than when wearing the SW, MCS, or when BF. In conclusion, when wearing the MBT or SW with rounded sole, static standing posture becomes unstable because of their characteristics as compared with wearing MCS or when BF, but the MBT has a larger sway in the front-back direction than the SW.

Accommodating off Nominal Conditions when Working to a Metered Schedule

In a schedule based Air Traffic Management (ATM) system, minor disruptions to the traffic flow could have a wider impact than would be expected as aircraft are linked temporally. However, given the frequency of these minor disruptions, the extent of their impact on operations needs to be scoped. In a human-in-the-loop (HITL) simulation, four TRACON controllers worked arrival traffic to Phoenix airport (PHX), aided by a schedule and controller sequencing and spacing tools. In approximately two-thirds of the runs, either one or two disrupting events that were local or global in nature, were set in motion. Controllers were asked to manage the disruptions and bring the traffic back onto the schedule. The research questions were exploratory: to observe the impact of the disruption, watch how controllers solved these problems and whether the controller tools assisted them. Global events were observed to have a greater impact on TRACON operations than local events as they led to a greater mean path length flown by aircraft through the TRACON and, although reported workload levels remained manageable overall global events created higher reported loads. Controller strategies for resolving events followed a similar pattern: with controllers often solving local problems with speed and moving to using vectors more often during global events. Controllers used their tools in a similar manner to those observed in nominal-operations studies, with the slot marker being the preferred aid regardless of the event. However, due to the range of factors influencing the event, e.g., environmental conditions, aircraft density in the TRACON, etc., sometimes the plan required revision and occasionally events had a wide-reaching effect.