Potential effects of pneumatic fracturing on existing structures and utilities

This thesis develops a mathematical design model for predicting ground deformations resulting from pneumatic fracturing. Pneumatic fracturing is a patented process developed for the purpose of enhancing the in situ treatment and removal of hazardous contaminants from geologic formations. During pneumatic injections, measurable ground deformations are experienced both during and after the process. Safe application of pneumatic fracturing to contaminated plumes occurring beneath existing structures and utilities requires that the elastic deformation behavior of the geologic formation and overlying structures be quantified. Data from five pneumatic fracturing sites were regressed to establish the characteristic polynomial describing the curvature of ground deformation. A model was then developed using theories of elastic plate bending and ground deformations by igneous laccolith intrusions. The deformed geologic formation is modeled as a circular plate subjected to a linear tapering pressure distribution. Comparison of the model results with actual field data displayed reasonable agreement. An instrumented field test was performed beneath an actual contaminated industrial facility to obtain data on the dynamic response of the structure. Based on the field test results, as well as experience from over 40 additional pneumatic fracturing sites, a systematic design guideline was developed. The guideline classifies structures as either flexible or rigid, and then categorizes them into one of three characteristic design cases

These are not the k-mers you are looking for: efficient online k-mer counting using a probabilistic data structure

K-mer abundance analysis is widely used for many purposes in nucleotide sequence analysis, including data preprocessing for de novo assembly, repeat detection, and sequencing coverage estimation. We present the khmer software package for fast and memory efficient online counting of k-mers in sequencing data sets. Unlike previous methods based on data structures such as hash tables, suffix arrays, and trie structures, khmer relies entirely on a simple probabilistic data structure, a Count-Min Sketch. The Count-Min Sketch permits online updating and retrieval of k-mer counts in memory which is necessary to support online k-mer analysis algorithms. On sparse data sets this data structure is considerably more memory efficient than any exact data structure. In exchange, the use of a Count-Min Sketch introduces a systematic overcount for k-mers; moreover, only the counts, and not the k-mers, are stored. Here we analyze the speed, the memory usage, and the miscount rate of khmer for generating k-mer frequency distributions and retrieving k-mer counts for individual k-mers. We also compare the performance of khmer to several other k-mer counting packages, including Tallymer, Jellyfish, BFCounter, DSK, KMC, Turtle and KAnalyze. Finally, we examine the effectiveness of profiling sequencing error, k-mer abundance trimming, and digital normalization of reads in the context of high khmer false positive rates. khmer is implemented in C++ wrapped in a Python interface, offers a tested and robust API, and is freely available under the BSD license at github.com/ged-lab/khmer

No Brain No Game? Altered Sensorimotor and Fronto-Limbic Circuitry in Individuals with ACL Rupture

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Lipid peroxidation and nitric oxide metabolites in a group of subjects with obstructive sleep apnea syndrome

It is known that in OSAS the plasma lipid peroxidation has an opposite behavior in comparison with nitric oxide metabolites. In the re-examination of our survey of OSAS infjects we calculated the ratio between thiobarbituric acid reactive infstances (TBARS) and nitric oxide metabolites (NOx) in relation to OSAS severity. The study has regarded 48 OSAS infjects infdivided in two infgroups according to the apnea/hypopnea index-AHI-(Low=21 infjects with AHI 30). From the obtained data it is evident that the TBARS/NOx ratio is significantly higher in the H infgroup compared to L infgroup as well as this ratio is reduced in L infgroup in comparison with the whole group of OSAS infjects. In the entire group of OSAS infjects the TBARS/NOx ratio results positively correlated with AHI and ODI and inversely correlated with mSO2

Sensorimotor Cortical Thickness Moderates Corticospinal Excitability

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Numerical modeling of bifacial PV string performance: Perimeter effect and influence of uniaxial solar trackers

The bifacial photovoltaic (PV) systems have recently met large interest. The performance of such systems heavily depends on the installation conditions and, in particular, on the albedo radiation collected by the module rear side. Therefore, it is of crucial importance to have an accurate performance model. To date, in the scientific literature, numerous models have been proposed and experimental data collected to study and optimize bifacial PV system performance. Currently, 3D and 2D models of bifacial PV devices exist. Though the former are more mathematically complex, they can lead to more accurate results, since they generally allow to fully consider the main aspects influencing a bifacial PV system performance. Recently, we have proposed and validated through experimental data a 3D model tested as a function of module height, tilt angle, and ground albedo. In this work, through such a model, we studied the role played by the perimeter zones surrounding the PV string, by considering PV strings of 30 or 60 modules. We considered the cases of fixed installation with optimal PV module tilt and of installation with uniaxial horizontal solar tracker. We evaluated the PV energy yield as a function of the size of the perimeter zones for the two cases, i.e., both with and without the solar tracker. In optimal perimeter conditions, we then studied the behavior of bifacial and mono-facial PV strings by varying the geographical location in a large latitude range

Residual vein thrombosis and onset of post-thrombotic syndrome: Influence of the 4G/5G polymorphism of plasminogen activator inhibitor-1 gene

BACKGROUND: Plasminogen activator inhibitor-1 (PAI-1) is the most important inhibitor of plasminogen activator. The functional 4G/5G polymorphism of the gene coding for PAI-1 may affect PAI-1 plasmatic activity, influencing the imbalance between coagulation and fibrinolysis cascades. In this prospective cohort analytic study, we investigated the role of this single nucleotide polymorphism in the persistence of thrombotic lesion and the occurrence of post-thrombotic syndrome. PATIENTS/METHODS: In a group of 168 patients with post-surgical deep vein thrombosis of the legs, we analyzed the 4G/5G polymorphism in the promoter of PAI-1 gene and plasmatic PAI-1 activity. Enrolled patients were divided in two groups: patients with 4G/5G polymorphism and increased PAI-1 activity (n=85) and patients without 4G/5G polymorphism and normal PAI-1 activity (n=83). All patients were treated according to current protocols and re-examined after 3, 12 and 36months in order to evaluate the persistence of thrombotic lesion and the occurrence of post-thrombotic syndrome. RESULTS: We found a significantly increased PAI activity in carrier of the 4G allele, who experienced much more frequently a persistence of thrombosis after 3, 12 and 36months and/or the development of post-thrombosis syndrome, in spite of the anticoagulant treatment. CONCLUSIONS: These data not only confirm the role played by PAI-1 activity and by the 4G/5G SNP of the PAI-1 gene, but also suggest that current therapeutic protocols, recommending the administration of low weight molecular heparin and oral anticoagulant for the treatment of deep vein thrombosis, could be non sufficient for patients genetically predisposed to a less efficient clot lysis

Gelatinases and their tissue inhibitors in a group of subjects with obstructive sleep apnea syndrome

Obstructive sleep apnea syndrome (OSAS) is associated with an elevated risk of cardiovascular events and stroke. Matrix metalloproteinases (MMPs) are endopeptidases involved in extracellular matrix degradation and then in the development and progression of cardiovascular diseases. Our aim was to evaluate plasma levels of gelatinases (MMP-2 and MMP-9) and their tissue inhibitors (TIMP-1 and TIMP-2) in a group of subjects with OSAS. We enrolled 48 subjects (36 men and 12 women; mean age 49.7 \ub1 14.68 yrs) with OSAS diagnosed with a 1-night cardiorespiratory study and then we subdivided these subjects into two subgroups according to the apnea/hypopnea index (AHI): Low (L = 21 subjects with AHI <30) and High (H = 27 subjects with AHI >30). We measured plasma concentration of the gelatinases and their inhibitors using ELISA kits. We observed a significant increase in plasma concentration of MMP-9, MMP-2, TIMP-1 and TIMP-2 in the entire group of OSAS subjects and in the two subgroups, with higher levels in the H in comparison with the L subgroup. In the whole group of OSAS subjects we also noted a significant decrease in MMP-9/TIMP-1 ratio in comparison with normal controls. Only MMP-9 was significantly correlated with the severity of the disease, expressed as AHI, with the oxygen desaturation index and also with the mean oxygen saturation. MMPs pattern is altered in OSAS and significantly influenced by the severity of the disease; it probably contributes to the vascular remodeling that leads to the atherosclerotic disease and cardiovascular complications

Scaling metagenome sequence assembly with probabilistic de Bruijn graphs

Deep sequencing has enabled the investigation of a wide range of environmental microbial ecosystems, but the high memory requirements for {\em de novo} assembly of short-read shotgun sequencing data from these complex populations are an increasingly large practical barrier. Here we introduce a memory-efficient graph representation with which we can analyze the k-mer connectivity of metagenomic samples. The graph representation is based on a probabilistic data structure, a Bloom filter, that allows us to efficiently store assembly graphs in as little as 4 bits per k-mer, albeit inexactly. We show that this data structure accurately represents DNA assembly graphs in low memory. We apply this data structure to the problem of partitioning assembly graphs into components as a prelude to assembly, and show that this reduces the overall memory requirements for {\em de novo} assembly of metagenomes. On one soil metagenome assembly, this approach achieves a nearly 40-fold decrease in the maximum memory requirements for assembly. This probabilistic graph representation is a significant theoretical advance in storing assembly graphs and also yields immediate leverage on metagenomic assembly