Immune factors and fatty acid composition in human milk from river/lake, coastal and inland regions of China

Breast milk fatty acid composition may be affected by maternal diet during gestation and lactation. The influence of dietary and breast milk fatty acids on breast milk immune factors is poorly defined. We determined the fatty acid composition and immune factor concentrations of breast milk from women residing in river & lake, coastal, and inland regions of China, which differ in their consumption of lean fish and oily fish. Breast milk samples were collected on days 3 to 5 (colostrum), 14 and 28 post-partum and analysed for soluble CD14 (sCD14), transforming growth factor (TGF)-β1, TGF-β2, secretory immunoglobulin A (sIgA) and fatty acids. The fatty acid composition of breast milk differed between regions and with time post-partum. The concentrations of all four immune factors in breast milk decreased over time, with sCD14, sIgA and TGF-β1 being highest in colostrum in the river & lake region. Breast milk DHA and arachidonic acid (AA) were positively associated, and γ-linolenic acid and EPA negatively associated, with the concentrations of each of the four immune factors. In conclusion, breast milk fatty acids and immune factors differ between regions in China characterised by different patterns of fish consumption and change during the course of lactation. A higher breast milk DHA and AA concentration is associated with higher concentrations of immune factors in breast milk, suggesting a role for these fatty acids in promoting gastrointestinal and immune maturation of the infant.

Networks, agency and (de)stabilisation: the issue of navigation on the River Wye, UK

This paper assesses the way in which an actor network presiding over the management of the River Wye has stabilized through accepting a particular view on the issue of navigation. The paper provides an account of how the network was challenged by a dissonant actor who, through reviving an old company, developed a counter network. It is argued that network stabilization is a form of consensus-building and it is contended that the way in which an issue is defined is crucial in terms of the successful enrolment of actors. The paper illustrates some of the conflicts and complexities encountered in resource planning, suggesting that research of this nature should trace actors back through time as well as through space if dynamics between actors involved in rural planning and management are to be effectively understood.

Modelling human visual navigation using multi-view scene reconstruction

It is often assumed that humans generate a 3D reconstruction of the environment, either in egocentric or world-based coordinates, but the steps involved are unknown. Here, we propose two reconstruction-based models, evaluated using data from two tasks in immersive virtual reality. We model the observer’s prediction of landmark location based on standard photogrammetric methods and then combine location predictions to compute likelihood maps of navigation behaviour. In one model, each scene point is treated independently in the reconstruction; in the other, the pertinent variable is the spatial relationship between pairs of points. Participants viewed a simple environment from one location, were transported (virtually) to another part of the scene and were asked to navigate back. Error distributions varied substantially with changes in scene layout; we compared these directly with the likelihood maps to quantify the success of the models. We also measured error distributions when participants manipulated the location of a landmark to match the preceding interval, providing a direct test of the landmark-location stage of the navigation models. Models such as this, which start with scenes and end with a probabilistic prediction of behaviour, are likely to be increasingly useful for understanding 3D vision.

Estimation of visual motion parameters used for bio-inspired navigation

Visual motion cues play an important role in animal and humans locomotion without the need to extract actual ego-motion information. This paper demonstrates a method for estimating the visual motion parameters, namely the Time-To-Contact (TTC), Focus of Expansion (FOE), and image angular velocities, from a sparse optical flow estimation registered from a downward looking camera. The presented method is capable of estimating the visual motion parameters in a complicated 6 degrees of freedom motion and in real time with suitable accuracy for mobile robots visual navigation.

Predicting solar disturbance effects on navigation systems

A variety of operational systems are vulnerable to disruption by solar disturbances brought to the Earth by the solar wind. Of particular importance to navigation systems are energetic charged particles which can generate temporary malfunctions and permanent damage in satellites. Modern spacecraft technology may prove to be particularly at risk during the next maximum of the solar cycle. In addition, the associated ionospheric disturbances cause phase shifts of transionospheric and ionosphere-reflected signals, giving positioning errors and loss of signal for GPS and Loran-C positioning systems and for over-the-horizon radars. We now have sufficient understanding of the solar wind, and how it interacts with the Earth's magnetic field, to predict statistically the likely effects on operational systems over the next solar cycle. We also have a number of advanced ways of detecting and tracking these disturbances through space but we cannot, as yet, provide accurate forecasts of individual disturbances that could be used to protect satellites and to correct errors. In addition, we have recently discovered long-term changes in the Sun, which mean that the number and severity of the disturbances to operational systems are increasing.

Impacts of uplift of northern Tibetan Plateau and formation of Asian inland deserts on regional climate and environment

Based on the geological evidence that the northern Tibetan Plateau (NTP) had an uplift of a finite magnitude since the Miocene and the major Asian inland deserts formed in the early Pliocene, a regional climate model (RegCM4.1) with a horizontal resolution of 50 km was used to explore the effects of the NTP uplift and the related aridification of inland Asia on regional climate. We designed three numerical experiments including the control experiment representing the present-day condition, the high-mountain experiment representing the early Pliocene condition with uplifted NTP but absence of the Asian inland deserts, and the low-mountain experiment representing the mid-Miocene condition with reduced topography in the NTP (by as much as 2400 m) and also absence of the deserts. Our simulation results indicated that the NTP uplift caused significant reductions in annual precipitation in a broad region of inland Asia north of the Tibetan Plateau (TP) mainly due to the enhanced rain shadow effect of the mountains and changes in the regional circulations. However, four mountainous regions located in the uplift showed significant increases in precipitation, stretching from the Pamir Plateau in the west to the Qilian Mountains in the east. These mountainous areas also experienced different changes in the rainfall seasonality with the greatest increases occurring during the respective rainy seasons, predominantly resulted from the enhanced orographically forced upwind ascents. The appearance of the major deserts in the inland Asia further reduced precipitation in the region and led to increased dust emission and deposition fluxes, while the spatial patterns of dust deposition were also changed, not only in the regions of uplift-impacted topography, but also in the downwind regions. One major contribution from this study is the comparison of the simulation results with 11 existing geological records representing the moisture conditions from Miocene to Pliocene. The comparisons revealed good matches between the simulation results and the published geological records. Therefore, we conclude that the NTP uplift and the related formation of the major deserts played a controlling role in the evolution of regional climatic conditions in a broad region in inland Asia since the Miocene.

Designing a Remote Navigation System

This project involves the design and implementation of a global electronic tracking system intended for use by trans-oceanic vessels, using the technology of the U.S. Government's Global Positioning System (GPS) and a wireless connection to a networked computer. Traditional navigation skills are being replaced with highly accurate electronics. GPS receivers, computers, and mobile communication are becoming common among both recreational and commercial boaters. With computers and advanced communication available throughout the maritime world, information can be shared instantaneously around the globe. This ability to monitor one's whereabouts from afar can provide an increased level of safety and efficiency. Current navigation software seldom includes the capability of providing upto-the-minute navigation information for remote display. Remote access to this data will allow boat owners to track the progress of their boats, land-based organizations to monitor weather patterns and suggest course changes, and school groups to track the progress of a vessel and learn about navigation and science. The software developed in this project allows navigation information from a vessel to be remotely transmitted to a land-based server, for interpretation and deployment to remote users over the Internet. This differs from current software in that it allows the tracking of one vessel by multiple users and provides a means for two-way text messaging between users and the vesseI. Beyond the coastal coverage provided by cellular telephones, mobile communication is advancing rapidly. Current tools such as satellite telephones and single-sideband radio enable worldwide communications, including the ability to connect to the Internet. If current trends continue, portable global communication will be available at a reasonable price and Internet connections on boats will become more common.

Machine learning and small robot navigation

Developing successful navigation and mapping strategies is an essential part of autonomous robot research. However, hardware limitations often make for inaccurate systems. This project serves to investigate efficient alternatives to mapping an environment, by first creating a mobile robot, and then applying machine learning to the robot and controlling systems to increase the robustness of the robot system. My mapping system consists of a semi-autonomous robot drone in communication with a stationary Linux computer system. There are learning systems running on both the robot and the more powerful Linux system. The first stage of this project was devoted to designing and building an inexpensive robot. Utilizing my prior experience from independent studies in robotics, I designed a small mobile robot that was well suited for simple navigation and mapping research. When the major components of the robot base were designed, I began to implement my design. This involved physically constructing the base of the robot, as well as researching and acquiring components such as sensors. Implementing the more complex sensors became a time-consuming task, involving much research and assistance from a variety of sources. A concurrent stage of the project involved researching and experimenting with different types of machine learning systems. I finally settled on using neural networks as the machine learning system to incorporate into my project. Neural nets can be thought of as a structure of interconnected nodes, through which information filters. The type of neural net that I chose to use is a type that requires a known set of data that serves to train the net to produce the desired output. Neural nets are particularly well suited for use with robotic systems as they can handle cases that lie at the extreme edges of the training set, such as may be produced by "noisy" sensor data. Through experimenting with available neural net code, I became familiar with the code and its function, and modified it to be more generic and reusable for multiple applications of neural nets.

Reducing The Risk Of Floods In Urban Areas With Combined Inland-River System

With the change of the water environment in accordance with climate change, the loss of lives and properties has increased due to urban flood. Although the importance of urban floods has been highlighted quickly, the construction of advancement technology of an urban drainage system combined with inland-river water and its relevant research has not been emphasized in Korea. In addition, without operation in consideration of combined inland-river water, it is difficult to prevent urban flooding effectively. This study, therefore, develops the uncertainty quantification technology of the risk-based water level and the assessment technology of a flood-risk region through a flooding analysis of the combination of inland-river. The study is also conducted to develop forecast technology of change in the water level of an urban region through the construction of very short-term/short-term flood forecast systems. This study is expected to be able to build an urban flood forecast system which makes it possible to support decision making for systematic disaster prevention which can cope actively with climate change.

Evaluation of the Cartographic Communication Performance of a Route Guidance and Navigation System

This study evaluates the influence of different cartographic representations of in-car navigation systems on visual demand, subjective preference, and navigational error. It takes into account the type and complexity of the representation, maneuvering complexity, road layout, and driver gender. A group of 28 drivers (14 male and 14 female) participated in this experiment which was performed in a low-cost driving simulator. The tests were performed on a limited number of instances for each type of representation, and their purpose was to carry out a preliminary assessment and provide future avenues for further studies. Data collected for the visual demand study were analyzed using non-parametric statistical analyses. Results confirmed previous research that showed that different levels of design complexity significantly influence visual demand. Non-grid-like road networks, for example, influence significantly visual demand and navigational error. An analysis of simple maneuvers on a grid-like road network showed that static and blinking arrows did not present significant differences. From the set of representations analyzed to assess visual demand, both arrows were equally efficient. From a gender perspective, women seem to took at the display more than men, but this factor was not significant. With respect to subjective preferences, drivers prefer representations with mimetic landmarks when they perform straight-ahead tasks. For maneuvering tasks, landmarks in a perspective model created higher visual demands.

Floristic relationships among inland swamp forests of Southeastern and Central-Western Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Methane and carbon dioxide seasonal cycles at urban Brazilian inland sites

Methane and carbon dioxide seasonal cycles during years 1998 and 1999 at two Brazilian urban and inland sites are presented. The mixing ratio averages over the studied period of time were 1.80 ppm CH4 and 384.7 ppm CO2. A comparison is made between continental averages and the averages of the three nearest global network background sites of NOAA-CMDL comprising Ascension Island, Namibia and Easter Island. Inland sites had 0.08 ppm or 4.9% more CH4 and 19.0 ppm or 4.9% more CO2 than background over the same time span. The CH4 summer minimum observed in remote sites was also detected inland. During the month of October 98 and 99 inland mixing ratios were frequently similar to background.

Comparing river basins world-wide and contrasting inland fisheries in Africa and Central Amazonia

An analysis of covariance relating basin area (A, km2) to river length (L, km) and discharge rate (D, m3 s-1) was performed for two continents and showed that the two covariates (L and D) were highly significant and that the strength of the relationship changed between continents. For comparison, D was excluded but the result remained the same. Although geomorphological models are useful for establishing global levels of production, these regressions should be applied with caution. Historically, simple statistical models were developed to predict fish catches in rivers. These, based upon regression of catches on channel length or basin area for Africa and Central Amazonia, are contrasted in this paper because of their generally similar approach.

Real time orbit determination using GPS navigation solution

This work analyses a real time orbit estimator using the raw navigation solution provided by GPS receivers. The estimation algorithm considers a Kalman filter with a rather simple orbit dynamic model and random walk modeling of the receiver clock bias and drift. Using the Topex/Poseidon satellite as test bed, characteristics of model truncation, sampling rates and degradation of the GPS receiver (Selective Availability) were analysed. Copyright © 2007 by ABCM.