Scanning electron microscope study of the developing microvasculature in the postnatal rat lung.

During postnatal growth the parenchymal septa of rat lung undergo an impressive restructuring. While immature septa are thick and contain two capillary layers, mature septa are slender and contain a single microvascular network. Using the Mercox casting technique and scanning electron microscopy, we investigated the mode and the timing of the transformation of the pulmonary capillary bed. During the third postnatal week the parenchymal septa rapidly mature to match adult morphology. Even in adult lungs, however, remnants of the immature status are present: A capillary bilayer is regularly found at the base and the tip of the septa. Our observations support the concept that reduction of intervening tissue, partial fusion of the two capillary networks, and preferential growth lead to the mature vascular arrangement. The fact that true mature interalveolar septa show a denser capillary network than alveolar walls abutting onto pleura, bronchi, or larger vessels is consonant with the fusion theory. Towards the nonparenchyma, the capillary network surrounding every airspace had no counterpart to fuse with. From quantitative data it can be calculated that owing to lung growth, mesh size should increase more than four times between birth and adult age. The adult lung network, however, is denser than the one in young animals. This means that new meshes must be added during growth. We propose that small holes observed in sheet-like regions of the microvasculature enlarge to form new capillary meshes. With this mechanism of in-itself or intussusceptional growth, sprouting of individual capillary segments to increase network size is no longer needed.

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Perceived organizational support and intention to stay in host countries among self-initiated expatriates: the role of career satisfaction and networks

Previous literature in SIE (self-initiated expatriation) has been mostly focused on an individual perspective. Studies on SIEs in organizational context are scarce. The current paper sought to examine the effect of perceived organizational support (POS) on SIE employees’ intention to stay in the host country, mediated by career satisfaction. Furthermore, we examined the moderating roles of career-related social networks with host and home country nationals on the effectiveness of POS. Data from 112 SIE employees in Germany were collected and analyzed. Empirical results partially supported our proposed model: there were significant negative indirect effect between POS and intention to stay, when career network size with home country nationals was high. The direct effect between POS and intention to stay was positive. For HR practice, our paper gave insight to understand SIE employees’ needs for support and mobility preferences, which can help organizations to develop more targeted HR development measures and assignment strategies for them.

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.

Real-time localization using software defined radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.

NEENAWA: Network in Eastern European Neolithic and Wetland Archaeology: first steps.

Neolithic and Bronze Age wetland sites around the Alps (so called pile-dwellings, Pfahlbauten or palafittes in German/French) are of outstanding universal value (UNESCO-world heritage since 2011). Typical sites are in lakes, rivers and bogs, dating between 5300 and 800 BC. Of common character is the perfect conservation of wood, textiles from plant fabrics and many other organic materials. Larger quantities of sub-fossilized wood, as in the peri-alpine sites, offer the possibility of high-precision dating by dendrochronology. Research in these wetland sites started in the mid-19th century. Through large scale rescue excavations since the 1970s and the evolution of underwater archaeology in the same period the Swiss accumulated a thorough experience with these specific sites. Research in wetland sites is shared between cantonal institutions and universities and led to a worldwide unique accumulation of knowledge. Comparable sites exist outside of the Alpine area, but in much smaller quantities. Regions like Russia (small lakes in NW-Russia) and Macedonia (medium size lakes in the border zone of Macedonia, Albania and Greece) have a high scientific potential; rivers in Ukraine are supposed to have the same type of sites.

GetReal in network meta-analysis: a review of the methodology.

Pairwise meta-analysis is an established statistical tool for synthesizing evidence from multiple trials, but it is informative only about the relative efficacy of two specific interventions. The usefulness of pairwise meta-analysis is thus limited in real-life medical practice, where many competing interventions may be available for a certain condition and studies informing some of the pairwise comparisons may be lacking. This commonly encountered scenario has led to the development of network meta-analysis (NMA). In the last decade, several applications, methodological developments, and empirical studies in NMA have been published, and the area is thriving as its relevance to public health is increasingly recognized. This article presents a review of the relevant literature on NMA methodology aiming to pinpoint the developments that have appeared in the field. Copyright © 2016 John Wiley & Sons, Ltd.

Fine-grained indoor positioning and tracking systems

Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.

Monitoreo de condiciones de higiene y seguridad del ambiente en entornos industriales usando redes de sensores inalámbricos

Resumen: Las redes de sensores inalámbricos han atraído mucha atención en los últimos años debido a la integración de tecnología inalámbrica, computación y tecnología de sensores. Estas redes consisten en una serie de nodos equipados con capacidades de procesamiento, comunicación y sensado. Utilizan protocolos especiales de radio para transmitir datos en un modo multisalto de operación. En este trabajo se propone utilizar una red de sensores para el monitoreo de las condiciones ambientales de Higiene y Seguridad en entornos industriales. Concretamente se monitorean Temperatura, Humedad, Ruido y Luminosidad. Se propone esta recolección de datos para dar soporte a la inspección anual de un auditor externo, por lo que no se considera esta recolección como crítica dado que no controlan ningún dispositivo. En primera instancia se aborda el problema utilizando una red de sensores con módulos que utilizan el protocolo 802.15 los cuales transmiten a un nodo maestro que sirve como gateway para enviar la información a un servidor que la almacena. La recolección de datos se realiza a través de una plataforma arduino como interface entre el módulo inalámbrico y los sensores. Esta primera propuesta es contrastada con un enfoque de Internet de las Cosas (IoT) utilizando módulos Arduino con WiFi embebido, denominados Wido, que permiten la comunicación de datos directamente al servidor de almacenaje. El trabajo comprende la caracterización del problema, elección del hardware, diseño de la red y la realización de pruebas para evaluar el funcionamiento de ambos enfoques.

Rural to Urban Migration: A District Level Analysis for India

Based on the recent census data this paper analyses the district level rural to urban migration rates (both intra-state and the inter-state) among males and females separately. Both the rates are closely associated irrespective of whether the migrants originate from the rural areas within the state or outside the state. This would suggest that women usually migrate as accompanists of the males. Though many of the relatively poor and backward states actually show large population mobility, which is primarily in search of a livelihood, the mobility of male population is also seen to be prominent in the relatively advanced states like Maharashtra and Gujarat. Rapid migration of rural females within the boundaries of the states is, however, evident across most of the regions. The social networks, which play an important role in the context of migration are prevalent among the short distance migrants and tend to lose their significance with a rise in the distance between the place of origin and destination though there are some exceptions to this phenomenon. Besides the north-south divide in the Indian context is indeed a significant phenomenon with a few exceptions of metropolitan cities. As regards the effect of factors at the place of destination, prospects for better job opportunities are a major determinant of male migration. Low castes and minority groups tend to pull migration through network effects. Among females also these effects are evident though with the inclusion of the male migration rate they become less significant. Finally the paper brings out the policy implications.

Multi-Resolution Texture Coding for Multi-Resolution 3D Meshes

We present an innovative system to encode and transmit textured multi-resolution 3D meshes in a progressive way, with no need to send several texture images, one for each mesh LOD (Level Of Detail). All texture LODs are created from the finest one (associated to the finest mesh), but can be re- constructed progressively from the coarsest thanks to refinement images calculated in the encoding process, and transmitted only if needed. This allows us to adjust the LOD/quality of both 3D mesh and texture according to the rendering power of the device that will display them, and to the network capacity. Additionally, we achieve big savings in data transmission by avoiding altogether texture coordinates, which are generated automatically thanks to an unwrapping system agreed upon by both encoder and decoder.

Topological measure locating the effective crossover between segregation and integration in a modular network

We introduce an easily computable topological measure which locates the effective crossover between segregation and integration in a modular network. Segregation corresponds to the degree of network modularity, while integration is expressed in terms of the algebraic connectivity of an associated hypergraph. The rigorous treatment of the simplified case of cliques of equal size that are gradually rewired until they become completely merged, allows us to show that this topological crossover can be made to coincide with a dynamical crossover from cluster to global synchronization of a system of coupled phase oscillators. The dynamical crossover is signaled by a peak in the product of the measures of intracluster and global synchronization, which we propose as a dynamical measure of complexity. This quantity is much easier to compute than the entropy (of the average frequencies of the oscillators), and displays a behavior which closely mimics that of the dynamical complexity index based on the latter. The proposed topological measure simultaneously provides information on the dynamical behavior, sheds light on the interplay between modularity and total integration, and shows how this affects the capability of the network to perform both local and distributed dynamical tasks.

Performance assessment of a kinetically-powered network for herd localization

Developing a herd localization system capable to operate unattended in communication-challenged areas arises from the necessity of improving current systems in terms of cost, autonomy or any other facilities that a certain target group (or overall users) may demand. A network architecture of herd localization is proposed with its corresponding hardware and a methodology to assess performance in different operating conditions. The system is designed taking into account an eventual environmental impact hence most nodes are simple, cheap and kinetically powered from animal movements-neither batteries nor sophisticated processor chips are needed. Other network elements integrating GPS and batteries operate with selectable duty cycles, thus reducing maintenance duties. Equipment has been tested on Scandinavian reindeer in Lapland and its element modeling is integrated into a simulator to analyze such localization network applicability for different use cases. Performance indicators (detection frequency, localization accuracy and delay) are fitted to assess the overall performance; system relative costs are enclosed also for a range of deployments.

Evaluación de protocolos de encaminamiento en una red inalámbrica mallada desplegada en una zona rural

The implementation of wireless communication systems in rural areas through the deployment of data networks in infrastructure mode is often inadequate due to its high cost and no fault tolerant centralized structure. Mesh networks can overcome these limitations while increases the coverage area in a more flexible way. This paper proposes the performance evaluation of the routing protocols IEEE 802.11s and Batman-Adv on an experimental wireless mesh network deployed in a rural environment called Lachocc, which is a community located at 4700 MASL in the Huancavelica region in Peru. The evaluation was based on the measurement of quality of service parameters such as bandwidth, delay and delay variation. As a result, it was determined that both protocols offer a good performance, but in most of the cases, Batman-Adv provides slightly better performance

ANN and Fuzzy c-Means applied to environmental pollution prediction

Salamanca, situated in center of Mexico is among the cities which suffer most from the air pollution in Mexico. The vehicular park and the industry, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Sulphur Dioxide (SO2). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of pollutant concentration. A database used to train the Neural Network corresponds to historical time series of meteorological variables and air pollutant concentrations of SO2. Before the prediction, Fuzzy c-Means and K-means clustering algorithms have been implemented in order to find relationship among pollutant and meteorological variables. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of SO2 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that the information obtained in the clustering step allows a prediction of an hour ahead, with data from past 2 hours.