Chemistry and Apparent Quality of Surface Water and Ground Water Associated with Coal Basins

Personnel of the Arkansas Mining and Mineral Resources Research Institute conducted preliminary investigations on the chemistry and quality of surface and ground water associated with 12 coal-bearing sub-basins in the Arkansas Valley coal field. The coal field is approximately 60 miles long and 33 miles wide but only in 12 areas coal is thick enough and has proper quality to be termed commercial. Both surface and underground sample sites were established in each of the sub-basins with some minor variations in four areas where not all types of sites could be located. Water was collected from 19 surface points and 19 underground points in the established areas. Both field and laboratory analyses were made and elemental contents are reported herein. In the main, the chemistry and water quality suggests that all water is suitable for agricultural and industrial uses. To obtain potable water, treatment must be made to reduce calcium, magnesium, sodium sulfate and iron. The mineral content of the water is due to its contact with coal-bearing zones and, as such, reflects the mineral content of the coal. However, it is recommended that additional studies on the petrography and geochemistry of the coal, overburden and underburden is in order. Also, it is recommended that at least one detailed study be made of one of the coal sub-basins where geologic parameters can be completely established with regard to hydrogeology. This report is an important first step in determining the character and quality of Arkansas coal which must be fully understood to fully utilize this important mineral resource

Evaluation of Thermal Imaging Technology for Commercial Vehicle Screening

Brake and tire violations are common problems identified through commercial vehicle inspections. Identifying and correcting these types of problems before a crash occurs can produce significant safety benefits. Thermal imaging technology can be used by commercial vehicle enforcement to screen vehicles as they approach a weigh station to determine if they may have flat tires and inoperable brakes. The vehicles do not have to be stopped at a weigh station to be screened. Kentucky currently has three stations outfitted with thermal imaging technology. The objectives of this study were to evaluate the benefits of using the thermal imaging cameras to identify brake and tire problems and to develop recommendations for how enforcement personnel can receive the most benefits from this technology. The data presented in this report include: 1) a summary of previous research, 2) evaluations of the technology, 3) on-site data collection at a Kentucky weigh station, 4) an interview with one of Kentucky’s primary users of the technology, and 5) an analysis of Kentucky inspection data, specifically, brake and tire violations and vehicle out-of-service (OOS) rates. A Federal Motor Carrier Safety Administration (FMCSA) evaluation concluded that the OOS rate for vehicles pinpointed via thermal imaging camera systems was 59 percent, whereas the OOS rate for conventional inspection was only 19 percent. Facilities with a thermal imaging system recorded a higher percentage of tire and brake violations per inspection as well as a higher vehicle out-of-service (VOOS) rate than facilities without a thermal imaging camera. However, the effectiveness of thermal imaging technology was significantly influenced by whether law enforcement embraced it as well as by inspectors’ proficiency operating the systems. This study recommends that enforcement staff who can access thermal imaging technology receive periodic training on its operation, then graduate to a practicum that lets them use the technology under expert supervision. Promotional materials that highlight the value of thermal imaging technologies should be distributed to all Kentucky enforcement personnel. In addition, methods and enforcement mechanisms should be identified so that personnel can be held accountable for using the technology

VistaClara: an expression browser plug-in for Cytoscape

Summary: VistaClara is a plug-in for Cytoscape which provides a more flexible means to visualize gene and protein expression within a network context. An extended attribute browser is provided in the form of a graphical and interactive permutation matrix that resembles the heat map displays popular in gene-expression analysis. This extended browser permits a variety of display options and interactions not currently available in Cytoscape

Elucidation of Directionality for Co-Expressed Genes: Predicting Intra-Operon Termination Sites

We present a novel framework for inferring regulatory and sequence-level information from gene co-expression networks. The key idea of our methodology is the systematic integration of network inference and network topological analysis approaches for uncovering biological insights. We determine the gene co-expression network of Bacillus subtilis using Affymetrix GeneChip time series data and show how the inferred network topology can be linked to sequence-level information hard-wired in the organism's genome. We propose a systematic way for determining the correlation threshold at which two genes are assessed to be co-expressed by using the clustering coefficient and we expand the scope of the gene co-expression network by proposing the slope ratio metric as a means for incorporating directionality on the edges. We show through specific examples for B. subtilis that by incorporating expression level information in addition to the temporal expression patterns, we can uncover sequence-level biological insights. In particular, we are able to identify a number of cases where (i) the co-expressed genes are part of a single transcriptional unit or operon and (ii) the inferred directionality arises due to the presence of intra-operon transcription termination sites.Comment: 7 pages, 8 figures, accepted in Bioinformatic

Dynamics of gene expression and the regulatory inference problem

From the response to external stimuli to cell division and death, the dynamics of living cells is based on the expression of specific genes at specific times. The decision when to express a gene is implemented by the binding and unbinding of transcription factor molecules to regulatory DNA. Here, we construct stochastic models of gene expression dynamics and test them on experimental time-series data of messenger-RNA concentrations. The models are used to infer biophysical parameters of gene transcription, including the statistics of transcription factor-DNA binding and the target genes controlled by a given transcription factor.Comment: revised version to appear in Europhys. Lett., new titl

Determining the Quantitative Principles of T Cell Response to Antigenic Disparity in Stem Cell Transplantation

Alloreactivity compromising clinical outcomes in stem cell transplantation is observed despite HLA matching of donors and recipients. This has its origin in the variation between the exomes of the two, which provides the basis for minor histocompatibility antigens (mHA). The mHA presented on the HLA class I and II molecules and the ensuing T cell response to these antigens results in graft vs. host disease. In this paper, results of a whole exome sequencing study are presented, with resulting alloreactive polymorphic peptides and their HLA class I and HLA class II (DRB1) binding affinity quantified. Large libraries of potentially alloreactive recipient peptides binding both sets of molecules were identified, with HLA-DRB1 generally presenting a greater number of peptides. These results are used to develop a quantitative framework to understand the immunobiology of transplantation. A tensor-based approach is used to derive the equations needed to determine the alloreactive donor T cell response from the mHA-HLA binding affinity and protein expression data. This approach may be used in future studies to simulate the magnitude of expected donor T cell response and determine the risk for alloreactive complications in HLA matched or mismatched hematopoietic cell and solid organ transplantation

Unravelling the Yeast Cell Cycle Using the TriGen Algorithm

Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior under the conditions tested. Biclustering emerges as an improvement of classical clustering since it relaxes the constraints for grouping allowing genes to be evaluated only under a subset of the conditions and not under all of them. However, this technique is not appropriate for the analysis of temporal microarray data in which the genes are evaluated under certain conditions at several time points. In this paper, we present the results of applying the TriGen algorithm, a genetic algorithm that finds triclusters that take into account the experimental conditions and the time points, to the yeast cell cycle problem, where the goal is to identify all genes whose expression levels are regulated by the cell cycle