Depicting community perspectives: repeat photography and participatory research as tools for assessing environmental services in Sagarmatha National Park, Nepal

Efforts have been made to provide a scientific basis for using environmental services as a conceptual tool to enhance conservation and improve livelihoods in protected mountain areas (MtPAS). Little attention has been paid to participatory research or locals’ concerns as environmental service (ES) users and providers. Such perspectives can illuminate the complex interplay between mountain ecosystems, environmental services and the determinants of human well-being. Repeat photography, long used in geographical fieldwork, is new as a qualitative research tool. This study uses a novel application of repeat photography as a diachronic photo-diary to examine local perceptions of change in ES in Sagarmatha National Park. Results show a consensus among locals on adverse changes to ES, particularly protection against natural hazards, such as landslides and floods, in the UNESCO World Heritage Site. We argue that our methodology could complement biophysical ecosystem assessments in MtPAS, especially since assessing ES, and acting on that, requires integrating diverse stakeholders’ knowledge, recognizing power imbalances and grappling with complex social-ecological systems.

Using Smalltalk as a Reflective Executable Meta-Language

Object-oriented meta-languages such as MOF or EMOF are often used to specify domain specific languages. However, these meta-languages lack the ability to describe behavior or operational semantics. Several approaches used a subset of Java mixed with OCL as executable meta-languages. In this paper, we report our experience of using Smalltalk as an executable and integrated meta-language. We validated this approach in incrementally building over the last decade, Moose, a meta-described reengineering environment. The reflective capabilities of Smalltalk support a uniform way of letting the base developer focus on his tasks while at the same time allowing him to meta-describe his domain model. The advantage of our this approach is that the developer uses the same tools and environment

Computer-assisted arthroplasty using bioengineered autografts

Recent advances in tissue-engineered cartilage open the door to new clinical treatments of joint lesions. Common to all therapies with in-vitro-engineered autografts is the need for optimal fit of the construct to allow screwless implantation and optimal integration into the live joint. Computer-assisted surgery (CAS) techniques are prime candidates to ensure the required accuracy, while at the same time simplifying the procedure. A pilot study has been conducted aiming at assembling a new set of methods to support ankle joint arthroplasty using bioengineered autografts. Computer assistance allows planning of the implant shape on a computed tomography (CT) image, manufacturing the construct according to the plan, and interoperatively navigating the surgical tools for implantation. A rotational symmetric model of the joint surface was used to avoid segmentation of the CT image; new software was developed to determine the joint axis and make the implant shape parameterizable. A complete cycle of treatment from planning to operation was conducted on a human cadaveric foot, thus proving the feasibility of computer-assisted arthroplasty using bioengineered autografts

DISTRIBUTED REPRODUCIBLE RESEARCH USING CACHED COMPUTATIONS

The ability to make scientific findings reproducible is increasingly important in areas where substantive results are the product of complex statistical computations. Reproducibility can allow others to verify the published findings and conduct alternate analyses of the same data. A question that arises naturally is how can one conduct and distribute reproducible research? This question is relevant from the point of view of both the authors who want to make their research reproducible and readers who want to reproduce relevant findings reported in the scientific literature. We present a framework in which reproducible research can be conducted and distributed via cached computations and describe specific tools for both authors and readers. As a prototype implementation we introduce three software packages written in the R language. The cacheSweave and stashR packages together provide tools for caching computational results in a key-value style database which can be published to a public repository for readers to download. The SRPM package provides tools for generating and interacting with "shared reproducibility packages" (SRPs) which can facilitate the distribution of the data and code. As a case study we demonstrate the use of the toolkit on a national study of air pollution exposure and mortality.

USING THE R PACKAGE crlmm FOR GENOTYPING AND COPY NUMBER ESTIMATION

Genotyping platforms such as Affymetrix can be used to assess genotype-phenotype as well as copy number-phenotype associations at millions of markers. While genotyping algorithms are largely concordant when assessed on HapMap samples, tools to assess copy number changes are more variable and often discordant. One explanation for the discordance is that copy number estimates are susceptible to systematic differences between groups of samples that were processed at different times or by different labs. Analysis algorithms that do not adjust for batch effects are prone to spurious measures of association. The R package crlmm implements a multilevel model that adjusts for batch effects and provides allele-specific estimates of copy number. This paper illustrates a workflow for the estimation of allele-specific copy number, develops markerand study-level summaries of batch effects, and demonstrates how the marker-level estimates can be integrated with complimentary Bioconductor software for inferring regions of copy number gain or loss. All analyses are performed in the statistical environment R. A compendium for reproducing the analysis is available from the author’s website (http://www.biostat.jhsph.edu/~rscharpf/crlmmCompendium/index.html).

INTERACTING WITH LOCAL AND REMOTE DATA RESPOSITORIES USING THE stashR PACKAGE

The stashR package (a Set of Tools for Administering SHared Repositories) for R implements a simple key-value style database where character string keys are associated with data values. The key-value databases can be either stored locally on the user's computer or accessed remotely via the Internet. Methods specific to the stashR package allow users to share data repositories or access previously created remote data repositories. In particular, methods are available for the S4 classes localDB and remoteDB to insert, retrieve, or delete data from the database as well as to synchronize local copies of the data to the remote version of the database. Users efficiently access information from a remote database by retrieving only the data files indexed by user-specified keys and caching this data in a local copy of the remote database. The local and remote counterparts of the stashR package offer the potential to enhance reproducible research by allowing users of Sweave to cache their R computations for a research paper in a localDB database. This database can then be stored on the Internet as a remoteDB database. When readers of the research paper wish to reproduce the computations involved in creating a specific figure or calculating a specific numeric value, they can access the remoteDB database and obtain the R objects involved in the computation.

Haptics in forensics: the possibilities and advantages in using the haptic device for reconstruction approaches in forensic science

Non-invasive documentation methods such as surface scanning and radiological imaging are gaining in importance in the forensic field. These three-dimensional technologies provide digital 3D data, which are processed and handled in the computer. However, the sense of touch gets lost using the virtual approach. The haptic device enables the use of the sense of touch to handle and feel digital 3D data. The multifunctional application of a haptic device for forensic approaches is evaluated and illustrated in three different cases: the representation of bone fractures of the lower extremities, by traffic accidents, in a non-invasive manner; the comparison of bone injuries with the presumed injury-inflicting instrument; and in a gunshot case, the identification of the gun by the muzzle imprint, and the reconstruction of the holding position of the gun. The 3D models of the bones are generated from the Computed Tomography (CT) images. The 3D models of the exterior injuries, the injury-inflicting tools and the bone injuries, where a higher resolution is necessary, are created by the optical surface scan. The haptic device is used in combination with the software FreeForm Modelling Plus for touching the surface of the 3D models to feel the minute injuries and the surface of tools, to reposition displaced bone parts and to compare an injury-causing instrument with an injury. The repositioning of 3D models in a reconstruction is easier, faster and more precisely executed by means of using the sense of touch and with the user-friendly movement in the 3D space. For representation purposes, the fracture lines of bones are coloured. This work demonstrates that the haptic device is a suitable and efficient application in forensic science. The haptic device offers a new way in the handling of digital data in the virtual 3D space.

Simulation in training: one-year experience using an efficiency index to assess interventional radiology fellow training status

PURPOSE: To compare objective fellow and expert efficiency indices for an interventional radiology renal artery stenosis skill set with the use of a high-fidelity simulator. MATERIALS AND METHODS: The Mentice VIST simulator was used for three different renal artery stenosis simulations of varying difficulty, which were used to grade performance. Fellows' indices at three intervals throughout 1 year were compared to expert baseline performance. Seventy-four simulated procedures were performed, 63 of which were captured as audiovisual recordings. Three levels of fellow experience were analyzed: 1, 6, and 12 months of dedicated interventional radiology fellowship. The recordings were compiled on a computer workstation and analyzed. Distinct measurable events in the procedures were identified with task analysis, and data regarding efficiency were extracted. Total scores were calculated as the product of procedure time, fluoroscopy time, tools, and contrast agent volume. The lowest scores, which reflected efficient use of tools, radiation, and time, were considered to indicate proficiency. Subjective analysis of participants' procedural errors was not included in this analysis. RESULTS: Fellows' mean scores diminished from 1 month to 12 months (42,960 at 1 month, 18,726 at 6 months, and 9,636 at 12 months). The experts' mean score was 4,660. In addition, the range of variance in score diminished with increasing experience (from a range of 5,940-120,156 at 1 month to 2,436-85,272 at 6 months and 2,160-32,400 at 12 months). Expert scores ranged from 1,450 to 10,800. CONCLUSIONS: Objective efficiency indices for simulated procedures can demonstrate scores directly comparable to the level of clinical experience.

Detection of apoptosis in vivo using antibodies against caspase-induced neo-epitopes

Cell death induction by apoptosis is an important process in the maintenance of tissue homeostasis as well as tissue destruction during various pathological processes. Consequently, detection of apoptotic cells in situ represents an important technique to assess the extent and impact of cell death in the respective tissue. While scoring of apoptosis by histological assessment of apoptotic cells is still a widely used method, it is likely biased by sensitivity problems and observed-based variations. The availability of caspase-mediated neo-epitope-specific antibodies offers new tools for the detection of apoptosis in situ. Here, we discuss the use of immunohistochemical detection of cleaved caspase 3 and lamin A for the assessment of apoptotic cells in paraffin-embedded liver tissue. Furthermore, we evaluate the effect of tissue pretreatment and antigen retrieval on the sensitivity of apoptosis detection, background staining and maintenance of tissue morphology.

New molecular detection tools adapted to emerging rhinoviruses and enteroviruses

Human rhinoviruses (HRV), and to a lesser extent human enteroviruses (HEV), are important respiratory pathogens. Like other RNA viruses, these picornaviruses have an intrinsic propensity to variability. This results in a large number of different serotypes as well as the incessant discovery of new genotypes. This large and growing diversity not only complicates the design of real-time PCR assays but also renders immunofluorescence unfeasible for broad HRV and HEV detection or quantification in cells. In this study, we used the 5' untranslated region, the most conserved part of the genome, as a target for the development of both a real-time PCR assay (Panenterhino/Ge/08) and a peptide nucleic acid-based hybridization oligoprobe (Panenterhino/Ge/08 PNA probe) designed to detect all HRV and HEV species members according to publicly available sequences. The reverse transcription-PCR assay has been validated, using not only plasmid and viral stocks but also quantified RNA transcripts and around 1,000 clinical specimens. These new generic detection PCR assays overcame the variability of circulating strains and lowered the risk of missing emerging and divergent HRV and HEV. An additional real-time PCR assay (Entero/Ge/08) was also designed specifically to provide sensitive and targeted detection of HEV in cerebrospinal fluid. In addition to the generic probe, we developed specific probes for the detection of HRV-A and HRV-B in cells. This investigation provides a comprehensive toolbox for accurate molecular identification of the different HEV and HRV circulating in humans.

Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

Development of one-dimensional and two-dimensional computational tools that simulate steady internal condensing flows in terrestrial and zero-gravity environments

This dissertation presents an effective quasi one-dimensional (1-D) computational simulation tool and a full two-dimensional (2-D) computational simulation methodology for steady annular/stratified internal condensing flows of pure vapor. These simulation tools are used to investigate internal condensing flows in both gravity as well as shear driven environments. Through accurate numerical simulations of the full two dimensional governing equations, results for laminar/laminar condensing flows inside mm-scale ducts are presented. The methodology has been developed using MATLAB/COMSOL platform and is currently capable of simulating film-wise condensation for steady (and unsteady flows). Moreover, a novel 1-D solution technique, capable of simulating condensing flows inside rectangular and circular ducts with different thermal boundary conditions is also presented. The results obtained from the 2-D scientific tool and 1-D engineering tool, are validated and synthesized with experimental results for gravity dominated flows inside vertical tube and inclined channel; and, also, for shear/pressure driven flows inside horizontal channels. Furthermore, these simulation tools are employed to demonstrate key differences of physics between gravity dominated and shear/pressure driven flows. A transition map that distinguishes shear driven, gravity driven, and “mixed” driven flow zones within the non-dimensional parameter space that govern these duct flows is presented along with the film thickness and heat transfer correlations that are valid in these zones. It has also been shown that internal condensing flows in a micro-meter scale duct experiences shear driven flow, even in different gravitational environments. The full 2-D steady computational tool has been employed to investigate the length of annularity. The result for a shear driven flow in a horizontal channel shows that in absence of any noise or pressure fluctuation at the inlet, the onset of non-annularity is partly due to insufficient shear at the liquid-vapor interface. This result is being further corroborated/investigated by R. R. Naik with the help of the unsteady simulation tool. The condensing flow results and flow physics understanding developed through these simulation tools will be instrumental in reliable design of modern micro-scale and spacebased thermal systems.

Evaluation of surface defect detection in reinforced concrete bridge decks using terrestrial LiDAR

Routine bridge inspections require labor intensive and highly subjective visual interpretation to determine bridge deck surface condition. Light Detection and Ranging (LiDAR) a relatively new class of survey instrument has become a popular and increasingly used technology for providing as-built and inventory data in civil applications. While an increasing number of private and governmental agencies possess terrestrial and mobile LiDAR systems, an understanding of the technology’s capabilities and potential applications continues to evolve. LiDAR is a line-of-sight instrument and as such, care must be taken when establishing scan locations and resolution to allow the capture of data at an adequate resolution for defining features that contribute to the analysis of bridge deck surface condition. Information such as the location, area, and volume of spalling on deck surfaces, undersides, and support columns can be derived from properly collected LiDAR point clouds. The LiDAR point clouds contain information that can provide quantitative surface condition information, resulting in more accurate structural health monitoring. LiDAR scans were collected at three study bridges, each of which displayed a varying degree of degradation. A variety of commercially available analysis tools and an independently developed algorithm written in ArcGIS Python (ArcPy) were used to locate and quantify surface defects such as location, volume, and area of spalls. The results were visual and numerically displayed in a user-friendly web-based decision support tool integrating prior bridge condition metrics for comparison. LiDAR data processing procedures along with strengths and limitations of point clouds for defining features useful for assessing bridge deck condition are discussed. Point cloud density and incidence angle are two attributes that must be managed carefully to ensure data collected are of high quality and useful for bridge condition evaluation. When collected properly to ensure effective evaluation of bridge surface condition, LiDAR data can be analyzed to provide a useful data set from which to derive bridge deck condition information.

Using water balance models to approximate the effects of climate change on spring catchment discharge : Mt. Hanang, Tanzania

This project addresses the potential impacts of changing climate on dry-season water storage and discharge from a small, mountain catchment in Tanzania. Villagers and water managers around the catchment have experienced worsening water scarcity and attribute it to increasing population and demand, but very little has been done to understand the physical characteristics and hydrological behavior of the spring catchment. The physical nature of the aquifer was characterized and water balance models were calibrated to discharge observations so as to be able to explore relative changes in aquifer storage resulting from climate changes. To characterize the shallow aquifer supplying water to the Jandu spring, water quality and geochemistry data were analyzed, discharge recession analysis was performed, and two water balance models were developed and tested. Jandu geochemistry suggests a shallow, meteorically-recharged aquifer system with short circulation times. Baseflow recession analysis showed that the catchment behavior could be represented by a linear storage model with an average recession constant of 0.151/month from 2004-2010. Two modified Thornthwaite-Mather Water Balance (TMWB) models were calibrated using historic rainfall and discharge data and shown to reproduce dry-season flows with Nash-Sutcliffe efficiencies between 0.86 and 0.91. The modified TMWB models were then used to examine the impacts of nineteen, perturbed climate scenarios to test the potential impacts of regional climate change on catchment storage during the dry season. Forcing the models with realistic scenarios for average monthly temperature, annual precipitation, and seasonal rainfall distribution demonstrated that even small climate changes might adversely impact aquifer storage conditions at the onset of the dry season. The scale of the change was dependent on the direction (increasing vs. decreasing) and magnitude of climate change (temperature and precipitation). This study demonstrates that small, mountain aquifer characterization is possible using simple water quality parameters, recession analysis can be integrated into modeling aquifer storage parameters, and water balance models can accurately reproduce dry-season discharges and might be useful tools to assess climate change impacts. However, uncertainty in current climate projections and lack of data for testing the predictive capabilities of the model beyond the present data set, make the forecasts of changes in discharge also uncertain. The hydrologic tools used herein offer promise for future research in understanding small, shallow, mountainous aquifers and could potentially be developed and used by water resource professionals to assess climatic influences on local hydrologic systems.

Space trajectories optimization using variable-chromosome-length genetic algorithms

The problem of optimal design of a multi-gravity-assist space trajectories, with free number of deep space maneuvers (MGADSM) poses multi-modal cost functions. In the general form of the problem, the number of design variables is solution dependent. To handle global optimization problems where the number of design variables varies from one solution to another, two novel genetic-based techniques are introduced: hidden genes genetic algorithm (HGGA) and dynamic-size multiple population genetic algorithm (DSMPGA). In HGGA, a fixed length for the design variables is assigned for all solutions. Independent variables of each solution are divided into effective and ineffective (hidden) genes. Hidden genes are excluded in cost function evaluations. Full-length solutions undergo standard genetic operations. In DSMPGA, sub-populations of fixed size design spaces are randomly initialized. Standard genetic operations are carried out for a stage of generations. A new population is then created by reproduction from all members based on their relative fitness. The resulting sub-populations have different sizes from their initial sizes. The process repeats, leading to increasing the size of sub-populations of more fit solutions. Both techniques are applied to several MGADSM problems. They have the capability to determine the number of swing-bys, the planets to swing by, launch and arrival dates, and the number of deep space maneuvers as well as their locations, magnitudes, and directions in an optimal sense. The results show that solutions obtained using the developed tools match known solutions for complex case studies. The HGGA is also used to obtain the asteroids sequence and the mission structure in the global trajectory optimization competition (GTOC) problem. As an application of GA optimization to Earth orbits, the problem of visiting a set of ground sites within a constrained time frame is solved. The J2 perturbation and zonal coverage are considered to design repeated Sun-synchronous orbits. Finally, a new set of orbits, the repeated shadow track orbits (RSTO), is introduced. The orbit parameters are optimized such that the shadow of a spacecraft on the Earth visits the same locations periodically every desired number of days.