The location of paravertebral catheters placed using the landmark technique

The aim of this prospective clinical study was to evaluate the location of paravertebral catheters that were placed using the classical landmark puncture technique and to correlate the distribution of contrast dye injected through the catheters with the extent of somatic block. Paravertebral catheter placement was attempted in 31 patients after video-assisted thoracic surgery. In one patient, an ultrasound-guided approach was chosen after failed catheter placement using the landmark method. A fluoroscopic examination in two planes using contrast dye was followed by injection of local anaesthetic and subsequent clinical testing of the extent of the anaesthetised area. In nine patients (29%), spread of contrast dye was not seen within the paravertebral space as intended. Misplaced catheters were in the epidural space (three patients), in the erector spinae musculature (five patients), and in the pleural space (one patient). There was also a discrepancy between the radiological findings and the observed distribution of loss of sensation. We have demonstrated an unacceptably high misplacement rate of paravertebral catheters using the landmark method. Additional research is required to compare the efficacy and safety of continuous paravertebral block using ultrasound-guided techniques or surgical inserted catheters.

Using Micro-Gravity Techniques to Map Alluvium Thickness and Pleistocene Location of the West Branch of the Susquehanna River Near Muncy, Pennsylvania

Laurentide glaciation during the early Pleistocene (~970 ka) dammed the southeast-flowing West Branch of the Susquehanna River (WBSR), scouring bedrock and creating 100-km-long glacial Lake Lesley near the Great Bend at Muncy, Pennsylvania (Ramage et al., 1998). Local drill logs and well data indicate that subsequent paleo-outwash floods and modern fluvial processes have deposited as much as 30 meters of alluvium in this area, but little is known about the valley fill architecture and the bedrock-alluvium interface. By gaining a greater understanding of the bedrock-alluvium interface the project will not only supplement existing depth to bedrock information, but also provide information pertinent to the evolution of the Muncy Valley landscape. This project determined if variations in the thickness of the valley fill were detectable using micro-gravity techniques to map the bedrock-alluvium interface. The gravity method was deemed appropriate due to scale of the study area (~30 km2), ease of operation by a single person, and the available geophysical equipment. A LaCoste and Romberg Gravitron unit was used to collect gravitational field readings at 49 locations over 5 transects across the Muncy Creek and Susquehanna River valleys (approximately 30 km2), with at least two gravity base stations per transect. Precise latitude, longitude and ground surface elevation at each location were measured using an OPUS corrected Trimble RTK-GPS unit. Base stations were chosen based on ease of access due to the necessity of repeat measurements. Gravity measurement locations were selected and marked to provide easy access and repeat measurements. The gravimeter was returned to a base station within every two hours and a looping procedure was used to determine drift and maximize confidence in the gravity measurements. A two-minute calibration reading at each station was used to minimize any tares in the data. The Gravitron digitally recorded finite impulse response filtered gravity measurements every 20 seconds at each station. A measurement period of 15 minutes was used for each base station occupation and a minimum of 5 minutes at all other locations. Longer or multiple measurements were utilized at some sites if drift or other externalities (i.e. train or truck traffic) were effecting readings. Average, median, standard deviation and 95% confidence interval were calculated for each station. Tidal, drift, latitude, free-air, Bouguer and terrain corrections were then applied. The results show that the gravitational field decreases as alluvium thickness increases across the axes of the Susquehanna River and Muncy Creek valleys. However, the location of the gravity low does not correspond with the present-day location of the West Branch of the Susquehanna River (WBSR), suggesting that the WBSR may have been constrained along Bald Eagle Mountain by a glacial lobe originating from the Muncy Creek Valley to the northeast. Using a 3-D inversion model, the topography of the bedrock-alluvium interface was determined over the extent of the study area using a density contrast of -0.8 g/cm3. Our results are consistent with the bedrock geometry of the area, and provide a low-cost, non-invasive and efficient method for exploring the subsurface and for supplementing existing well data.

POOR PERFORMANCE OF BOOTSTRAP CONFIDENCE INTERVALS FOR THE LOCATION OF A QUANTITATIVE TRAIT LOUCS

The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTLs) that contribute to variation in a quantitative trait (such as body weight). Confidence intervals for the locations of QTLs are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. Likelihood support intervals are the most widely used method to obtain confidence intervals for QTL location, but the non-parametric bootstrap has also been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals are poorly behaved and so should not be used in this context. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers; this contributes to the poor behavior of the bootstrap. Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately.

Polymorphism and chromosomal location of the MC4R (melanocortin-4 receptor) gene in the dog and red fox

The melanocortin-4 receptor (MC4R) is expressed in the hypothalamus and regulates energy intake and body weight. In silico screening of the canine chromosome 1 sequence and a comparison with the porcine MC4R sequence by BLAST were performed. The nucleotide sequence of the whole coding region and 3'- and 5'-flanking regions of the dog (1214 bp) and red fox (1177 bp) MC4R gene was established and high conservation of the nucleotide sequences was revealed (99%). Five sets of PCR primers were designed and a search for polymorphism was performed by the SSCP technique in a group of 31 dogs representing nineteen breeds and 35 farm red foxes. Sequencing of DNA fragments, representing the identified SSCP patterns, revealed three single nucleotide polymorphisms (including a missense one) in dogs and four silent SNPs in red foxes. An average SNP frequency was approx. 1/400 bp in the dog and 1/300 bp in the red fox. We mapped the MC4R gene by FISH to the canine chromosome 1 (CFA1q1.1) and to the red fox chromosome 5 (VVU5p1.2).

Pleomorphic adenoma in an atypical location near the temporomandibular joint: a case report

Pleomorphic adenomas primarily arise in the major salivary glands, especially in the parotid. The most common area is the lower pole superficial to the plane of the facial nerve. In this report, a pleomorphic adenoma in an atypical location--the region of the temporomandibular joint (TMJ)--is presented. The tumor was solitary, closely attached to the capsule of the TMJ and superior to the parotid gland, with clear demarcation. Clinically, the tumor resembled TMJ pathology, but MRI examination led to diagnosis of a benign tumor attached to the TMJ. This report shows that pleomorphic adenoma can be a possible diagnosis for lesions at the joint capsule.

Quantitative (1)H magnetic resonance spectroscopy of myoglobin de- and reoxygenation in skeletal muscle: reproducibility and effects of location and disease

1H-magnetic resonance spectroscopy ((1)H-MRS) of deoxymyoglobin (DMb) provides a means to noninvasively monitor the oxygenation state of human skeletal muscle in work and disease. As shown in this work, it also offers the opportunity to measure the absolute tissue content of DMb, the basic oxygen consumption of resting muscle, and the reperfusion characteristics after release of a pressure cuff. The methodology to determine these tissue properties simultaneously at two positions along the calf is presented. The obtained values are in agreement with invasive determinations. The reproducibility of the (1)H-MRS measurements is established for healthy controls and patients with peripheral arterial disease (PAD). A location dependence in axial direction, as well as differences between controls and patients are demonstrated for all parameters. The reoxygenation time in particular is expected to provide a means to quantitatively monitor therapies aimed at improving muscular perfusion in these patients.

Resource management in location aware cognitive radio networks

Dynamic spectrum access (DSA) aims at utilizing spectral opportunities both in time and frequency domains at any given location, which arise due to variations in spectrum usage. Recently, Cognitive radios (CRs) have been proposed as a means of implementing DSA. In this work we focus on the aspect of resource management in overlaid CRNs. We formulate resource allocation strategies for cognitive radio networks (CRNs) as mathematical optimization problems. Specifically, we focus on two key problems in resource management: Sum Rate Maximization and Maximization of Number of Admitted Users. Since both the above mentioned problems are NP hard due to presence of binary assignment variables, we propose novel graph based algorithms to optimally solve these problems. Further, we analyze the impact of location awareness on network performance of CRNs by considering three cases: Full location Aware, Partial location Aware and Non location Aware. Our results clearly show that location awareness has significant impact on performance of overlaid CRNs and leads to increase in spectrum utilization effciency.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.