Design-based stereology to quantify structural properties of artificial and natural snow using thin sections

The quantification of the structural properties of snow is traditionally based on model-based stereology. Model-based stereology requires assumptions about the shape of the investigated structure. Here, we show how the density, specific surface area, and grain boundary area can be measured using a design-based method, where no assumptions about structural properties are necessary. The stereological results were also compared to X-ray tomography to control the accuracy of the method. The specific surface area calculated with the stereological method was 19.8 ± 12.3% smaller than with X-ray tomography. For the density, the stereological method gave results that were 11.7 ± 12.1% larger than X-ray tomography. The statistical analysis of the estimates confirmed that the stereological method and the sampling used are accurate. This stereological method was successfully tested on artificially produced ice beads but also on several snow types. Combining stereology and polarisation microscopy provides a good estimate of grain boundary areas in ice beads and in natural snow, with some limitatio

Design, synthesis, and biological evaluation of somatostatin-based radiopeptides

The prototypes for tumor targeting with radiolabeled peptides are derivatives of somatostatin. Usually, they primarily have high affinity for somatostatin receptor subtype 2 (sst2), and they have moderate affinity for sst5. We aimed at developing analogs that recognize different somatostatin receptor subtypes for internal radiotherapy in order to extend the present range of accessible tumors. We synthesized DOTA-octapeptides based on octreotide by replacing Phe3 mainly with unnatural amino acids. The affinity profile was determined by using cell lines transfected with sst1-5. Internalization was determined by using AR42J, HEK-sst3, and HEK-sst5 cell lines, and biodistribution was studied in rat tumor models. Two of the derivatives thus obtained showed an improved binding affinity profile, enhanced internalization into cells expressing sst2 and sst3, respectively, and better tumor:kidney ratios in animals.

Model-based control of neuromuscular block using mivacurium: design and clinical verification

BACKGROUND: Short-acting agents for neuromuscular block (NMB) require frequent dosing adjustments for individual patient's needs. In this study, we verified a new closed-loop controller for mivacurium dosing in clinical trials. METHODS: Fifteen patients were studied. T1% measured with electromyography was used as input signal for the model-based controller. After induction of propofol/opiate anaesthesia, stabilization of baseline electromyography signal was awaited and a bolus of 0.3 mg kg-1 mivacurium was then administered to facilitate endotracheal intubation. Closed-loop infusion was started thereafter, targeting a neuromuscular block of 90%. Setpoint deviation, the number of manual interventions and surgeon's complaints were recorded. Drug use and its variability between and within patients were evaluated. RESULTS: Median time of closed-loop control for the 11 patients included in the data processing was 135 [89-336] min (median [range]). Four patients had to be excluded because of sensor problems. Mean absolute deviation from setpoint was 1.8 +/- 0.9 T1%. Neither manual interventions nor complaints from the surgeons were recorded. Mean necessary mivacurium infusion rate was 7.0 +/- 2.2 microg kg-1 min-1. Intrapatient variability of mean infusion rates over 30-min interval showed high differences up to a factor of 1.8 between highest and lowest requirement in the same patient. CONCLUSIONS: Neuromuscular block can precisely be controlled with mivacurium using our model-based controller. The amount of mivacurium needed to maintain T1% at defined constant levels differed largely between and within patients. Closed-loop control seems therefore advantageous to automatically maintain neuromuscular block at constant levels.

An Instrument Design for Space-Based Optical Observation of Space Debris

Currently, observations of space debris are primarily performed with ground-based sensors. These sensors have a detection limit at some centimetres diameter for objects in Low Earth Orbit (LEO) and at about two decimetres diameter for objects in Geostationary Orbit (GEO). The few space-based debris observations stem mainly from in-situ measurements and from the analysis of returned spacecraft surfaces. Both provide information about mostly sub-millimetre-sized debris particles. As a consequence the population of centimetre- and millimetre-sized debris objects remains poorly understood. The development, validation and improvement of debris reference models drive the need for measurements covering the whole diameter range. In 2003 the European Space Agency (ESA) initiated a study entitled “Space-Based Optical Observation of Space Debris”. The first tasks of the study were to define user requirements and to develop an observation strategy for a space-based instrument capable of observing uncatalogued millimetre-sized debris objects. Only passive optical observations were considered, focussing on mission concepts for the LEO, and GEO regions respectively. Starting from the requirements and the observation strategy, an instrument system architecture and an associated operations concept have been elaborated. The instrument system architecture covers the telescope, camera and onboard processing electronics. The proposed telescope is a folded Schmidt design, characterised by a 20 cm aperture and a large field of view of 6°. The camera design is based on the use of either a frame-transfer charge coupled device (CCD), or on a cooled hybrid sensor with fast read-out. A four megapixel sensor is foreseen. For the onboard processing, a scalable architecture has been selected. Performance simulations have been executed for the system as designed, focussing on the orbit determination of observed debris particles, and on the analysis of the object detection algorithms. In this paper we present some of the main results of the study. A short overview of the user requirements and observation strategy is given. The architectural design of the instrument is discussed, and the main tradeoffs are outlined. An insight into the results of the performance simulations is provided.

Orbits design for Leo space based solar power satellite system

Space Based Solar Power satellites use solar arrays to generate clean, green, and renewable electricity in space and transmit it to earth via microwave, radiowave or laser beams to corresponding receivers (ground stations). These traditionally are large structures orbiting around earth at the geo-synchronous altitude. This thesis introduces a new architecture for a Space Based Solar Power satellite constellation. The proposed concept reduces the high cost involved in the construction of the space satellite and in the multiple launches to the geo-synchronous altitude. The proposed concept is a constellation of Low Earth Orbit satellites that are smaller in size than the conventional system. For this application a Repeated Sun-Synchronous Track Circular Orbit is considered (RSSTO). In these orbits, the spacecraft re-visits the same locations on earth periodically every given desired number of days with the line of nodes of the spacecraft’s orbit fixed relative to the Sun. A wide range of solutions are studied, and, in this thesis, a two-orbit constellation design is chosen and simulated. The number of satellites is chosen based on the electric power demands in a given set of global cities. The orbits of the satellites are designed such that their ground tracks visit a maximum number of ground stations during the revisit period. In the simulation, the locations of the ground stations are chosen close to big cities, in USA and worldwide, so that the space power constellation beams down power directly to locations of high electric power demands. The j2 perturbations are included in the mathematical model used in orbit design. The Coverage time of each spacecraft over a ground site and the gap time between two consecutive spacecrafts visiting a ground site are simulated in order to evaluate the coverage continuity of the proposed solar power constellation. It has been observed from simulations that there always periods in which s spacecraft does not communicate with any ground station. For this reason, it is suggested that each satellite in the constellation be equipped with power storage components so that it can store power for later transmission. This thesis presents a method for designing the solar power constellation orbits such that the number of ground stations visited during the given revisit period is maximized. This leads to maximizing the power transmission to ground stations.

MODELING AND PROTOCOL DESIGN FOR EMERGING WIRELESS SYSTEMS

Mobile Mesh Network based In-Transit Visibility (MMN-ITV) system facilitates global real-time tracking capability for the logistics system. In-transit containers form a multi-hop mesh network to forward the tracking information to the nearby sinks, which further deliver the information to the remote control center via satellite. The fundamental challenge to the MMN-ITV system is the energy constraint of the battery-operated containers. Coupled with the unique mobility pattern, cross-MMN behavior, and the large-spanned area, it is necessary to investigate the energy-efficient communication of the MMN-ITV system thoroughly. First of all, this dissertation models the energy-efficient routing under the unique pattern of the cross-MMN behavior. A new modeling approach, pseudo-dynamic modeling approach, is proposed to measure the energy-efficiency of the routing methods in the presence of the cross-MMN behavior. With this approach, it could be identified that the shortest-path routing and the load-balanced routing is energy-efficient in mobile networks and static networks respectively. For the MMN-ITV system with both mobile and static MMNs, an energy-efficient routing method, energy-threshold routing, is proposed to achieve the best tradeoff between them. Secondly, due to the cross-MMN behavior, neighbor discovery is executed frequently to help the new containers join the MMN, hence, consumes similar amount of energy as that of the data communication. By exploiting the unique pattern of the cross-MMN behavior, this dissertation proposes energy-efficient neighbor discovery wakeup schedules to save up to 60% of the energy for neighbor discovery. Vehicular Ad Hoc Networks (VANETs)-based inter-vehicle communications is by now growingly believed to enhance traffic safety and transportation management with low cost. The end-to-end delay is critical for the time-sensitive safety applications in VANETs, and can be a decisive performance metric for VANETs. This dissertation presents a complete analytical model to evaluate the end-to-end delay against the transmission range and the packet arrival rate. This model illustrates a significant end-to-end delay increase from non-saturated networks to saturated networks. It hence suggests that the distributed power control and admission control protocols for VANETs should aim at improving the real-time capacity (the maximum packet generation rate without causing saturation), instead of the delay itself. Based on the above model, it could be determined that adopting uniform transmission range for every vehicle may hinder the delay performance improvement, since it does not allow the coexistence of the short path length and the low interference. Clusters are proposed to configure non-uniform transmission range for the vehicles. Analysis and simulation confirm that such configuration can enhance the real-time capacity. In addition, it provides an improved trade off between the end-to-end delay and the network capacity. A distributed clustering protocol with minimum message overhead is proposed, which achieves low convergence time.

DESIGN AND DEVELOPMENT OF BODIPY-BASED FLUORESCENT PROBES FOR SENSING AND IMAGING OF CYANIDE, Zn (II) IONS, LYSOSOMAL pH AND CANCER CELLS

BODIPY (4,4-Difluoro-3a,4a-diaza-s-indacene) dyes have gained lots of attention in application of fluorescence sensing and imaging in recent years because they possess many distinctive and desirable properties such as high extinction coefficient, narrow absorption and emission bands, high quantum yield and low photobleaching effect. However, most of BODIPY-based fluorescent probes have very poor solubilities in aqueous solution, emit less than 650 nm fluorescence that can cause cell and tissue photodamages compared with bio-desirable near infrared (650-900 nm) light. These undesirable properties extremely limit the applications of BODIPY-based fluorescent probes in sensing and imaging applications. In order to overcome these drawbacks, we have developed a very effective strategy to prepare a series of neutral highly water- soluble BODIPY dyes by enhancing the water solubilities of BODIPY dyes via incorporation of tri(ethylene glycol)methyl ether (TEG) and branched oligo(ethylene glycol)methyl ether (BEG) residues onto BODIPY dyes at 1,7-, 2,6-, 3,5-, 4- and meso- positions. We also have effectively tuned absorptions and emissions of BOIDPY dyes to red, deep red and near infrared regions via significant extension of π-conjugation of BODIPY dyes by condensation reactions of aromatic aldehydes with 2,6-diformyl BODIPY dyes at 1,3,5,7-positions. Based on the foundation that we built for enhancing water solubility and tuning wavelength, we have designed and developed a series of water-soluble, BODIPY-based fluorescent probes for sensitive and selective sensing and imaging of cyanide, Zn (II) ions, lysosomal pH and cancer cells. We have developed three BODIPY-based fluorescent probes for sensing of cyanide ions by incorporating indolium moieties onto the 6-position of TEG- or BEG-modified BOIDPY dyes. Two of them are highly water-soluble. These fluorescent probes showed selective and fast ratiometric fluorescent responses to cyanide ions with a dramatic fluorescence color change from red to green accompanying a significant increase in fluorescent intensity. The detection limit was measured as 0.5 mM of cyanide ions. We also have prepared three highly water-soluble fluorescent probes for sensing of Zn (II) ions by introducing dipicoylamine (DPA, Zn ion chelator) onto 2- and/or 6-positions of BEG-modified BODIPY dyes. These probes showed selective and sensitive responses to Zn (II) ion in the range from 0.5 mM to 24 mM in aqueous solution at pH 7.0. Particularly, one of the probes displayed ratiometric responses to Zn (II) ions with fluorescence quenching at 661 nm and fluorescence enhancement at 521 nm. This probe has been successfully applied to the detection of intracellular Zn (II) ions inside the living cells. Then, we have further developed three acidotropic, near infrared emissive BODIPY- based fluorescent probes for detection of lysosomal pH by incorporating piperazine moiety at 3,5-positions of TEG- or BEG-modified BODIPY dyes as parts of conjugation. The probes have low auto-fluorescence at physiological neutral condition while their fluorescence intensities will significant increase at 715 nm when pH shift to acidic condition. These three probes have been successfully applied to the in vitro imaging of lysosomes inside two types of living cells. At the end, we have synthesized one water- soluble, near infrared emissive cancer cell targetable BODIPY-based fluorescent polymer bearing cancer homing peptide (cRGD) residues for cancer cell imaging applications. This polymer exhibited excellent water-solubility, near infrared emission (712 nm), good biocompatibility. It also showed low nonspecific interactions to normal endothelial cells and can effectively detect breast tumor cells.

DESIGN AND IMPLEMENT DYNAMIC PROGRAMMING BASED DISCRETE POWER LEVEL SMART HOME SCHEDULING USING FPGA

With the development and capabilities of the Smart Home system, people today are entering an era in which household appliances are no longer just controlled by people, but also operated by a Smart System. This results in a more efficient, convenient, comfortable, and environmentally friendly living environment. A critical part of the Smart Home system is Home Automation, which means that there is a Micro-Controller Unit (MCU) to control all the household appliances and schedule their operating times. This reduces electricity bills by shifting amounts of power consumption from the on-peak hour consumption to the off-peak hour consumption, in terms of different “hour price”. In this paper, we propose an algorithm for scheduling multi-user power consumption and implement it on an FPGA board, using it as the MCU. This algorithm for discrete power level tasks scheduling is based on dynamic programming, which could find a scheduling solution close to the optimal one. We chose FPGA as our system’s controller because FPGA has low complexity, parallel processing capability, a large amount of I/O interface for further development and is programmable on both software and hardware. In conclusion, it costs little time running on FPGA board and the solution obtained is good enough for the consumers.

Design-based stereology: Planning, volumetry and sampling are crucial steps for a successful study

Quantitative data obtained by means of design-based stereology can add valuable information to studies performed on a diversity of organs, in particular when correlated to functional/physiological and biochemical data. Design-based stereology is based on a sound statistical background and can be used to generate accurate data which are in line with principles of good laboratory practice. In addition, by adjusting the study design an appropriate precision can be achieved to find relevant differences between groups. For the success of the stereological assessment detailed planning is necessary. In this review we focus on common pitfalls encountered during stereological assessment. An exemplary workflow is included, and based on authentic examples, we illustrate a number of sampling principles which can be implemented to obtain properly sampled tissue blocks for various purposes.

The influence of sampling design on tree-ring-based quantification of forest growth

Tree-rings offer one of the few possibilities to empirically quantify and reconstruct forest growth dynamics over years to millennia. Contemporaneously with the growing scientific community employing tree-ring parameters, recent research has suggested that commonly applied sampling designs (i.e. how and which trees are selected for dendrochronological sampling) may introduce considerable biases in quantifications of forest responses to environmental change. To date, a systematic assessment of the consequences of sampling design on dendroecological and-climatological conclusions has not yet been performed. Here, we investigate potential biases by sampling a large population of trees and replicating diverse sampling designs. This is achieved by retroactively subsetting the population and specifically testing for biases emerging for climate reconstruction, growth response to climate variability, long-term growth trends, and quantification of forest productivity. We find that commonly applied sampling designs can impart systematic biases of varying magnitude to any type of tree-ring-based investigations, independent of the total number of samples considered. Quantifications of forest growth and productivity are particularly susceptible to biases, whereas growth responses to short-term climate variability are less affected by the choice of sampling design. The world's most frequently applied sampling design, focusing on dominant trees only, can bias absolute growth rates by up to 459% and trends in excess of 200%. Our findings challenge paradigms, where a subset of samples is typically considered to be representative for the entire population. The only two sampling strategies meeting the requirements for all types of investigations are the (i) sampling of all individuals within a fixed area; and (ii) fully randomized selection of trees. This result advertises the consistent implementation of a widely applicable sampling design to simultaneously reduce uncertainties in tree-ring-based quantifications of forest growth and increase the comparability of datasets beyond individual studies, investigators, laboratories, and geographical boundaries.