Angular unconformity in Pennsylvanian strata from 3-D seismic interpretation,Goldsmith Field,West Texas

The Pennsylvanian unconformity,which is a detrital surface,separates the beds of the Permian-aged strata from the Lower Paleozoic in the Central Basin Platform.Seismic data interpretation indicates that the unconformity is an angular unconformity,overlying multiple normal faults,and accompanied with a thrust fault which maximizes the region's structural complexity.Additionally,the Pennsylvanian angular unconformity creates pinch-outs between the beds above and below.We computed the spectral decomposition and reflector convergence attributes and analyzed them to characterize the angular unconformity and faults.The spectral decomposition attribute divides the broadband seismic data into different spectral bands to resolve thin beds and show thickness variations.In contrast,the reflector convergence attribute highlights the location and direction of the pinch-outs as they dip south at angles between 2and 6.After reviewing findings from RGB blending of the spectrally decomposed frequencies along the Pennsylvanian unconformity,we observed channel-like features and multiple linear bands in addition to the faults and pinch-outs.It can be inferred that the identified linear bands could be the result of different lithologies associated with the tilting of the beds,and the faults may possibly influence hydrocarbon migration or act as a flow barrier to entrap hydrocarbon accumulation.The identification of this angular unconformity and the associated features in the study area are vital for the following reasons:1)the unconformity surface represents a natural stratigraphic boundary;2)the stratigraphic pinch-outs act as fluid flow connectivity boundaries;3)the areal extent of compartmentalized reservoirs'boundaries created by the angular unconformity are better defined;and 4)fault displacements are better understood when planning well locations as faults can be flow barriers,or permeability conduits,depending on facies heterogeneity and/or seal effectiveness of a fault,which can affect hydrocarbon production.The methodology utilized in this study is a further step in the characterization of reservoirs and can be used to expand our knowledge and obtain more information about the Goldsmith Field.

Infections Related to Health Care in Newborns: Documental Study Based on Analysis of Research Database

This documentary research aimed to describe the results of an epidemiological survey that sought to determine the prevalence of Infections Related to Health Care (IRHC) in newborns admitted to a Neonatal Intensive Care Unit (NICU) at the city of Rio de Janeiro. For methodology, the existing data in the original research database were used as the primary source. The method used was the case study in a quantitative approach. The data have been statistically arranged by odds ratio, which measured the possibility of IRHC development at the 102 newborns, by exposition at the risk factors. Results: IRHC prevalence with pneumonias, sepsis, navel’s infection and ocular infections predominance rises. Prematures are 4.10 more susceptible. Twelve hours after amniotic rupture there are 1.77 more chances of infections. Babies with more than 10 days of hospitalization are 4.70 more susceptible than those with 10 days. The registers examined were incipient at the IRHC’s characterization, beginning and duration, which make the IRHC’s diagnostic/notification difficult.

Three dimensional structure prediction and proton nuclear magnetic resonance analysis of toxic pesticides in human blood plasma

The purpose of this study was to investigate the nuclear magnetic resonance （NMR） assignments of hydrolyzed products extracted from human blood plasma. The correlations between chemical, functional and structural prop- erties of highly toxic pesticides were investigated using the PreADME analysis. We observed that toxic pesticides possessed higher molecular weight and, more hydrogen bond donors and acceptors when compared with less toxic pesticides. The occurrence of functional groups and structural properties was analyzed using ~H-NMR. The ~H- NMR spectra of the phosphomethoxy class of pesticides were characterized by methyl resonances at 3.7-3.9 ppm （8） with the coupling constants of 11-16 Hz （Je-cns）. In phosphoethoxy pesticides, the methyl resonance was about 1.4 ppm （8） with the coupling constant of 10 Hz （Je-cH2） and the methylene resonances was 4.2-4.4 ppm （8） with the coupling constant of 0.8 Hz （Jp-cH3）, respectively. Our study shows that the values of four parameters such as chemical shift, coupling constant, integration and relaxation time correlated with the concentration of toxic pesticides, and can be used to characterise the proton groups in the molecular structures of toxic pesticides.

Initial Stable State of Ocean Floor Deposits

Extensive oedometer tests and physical tests have been conducted on remolded and reconstituted marine soils with different initial water contents and liquid limits. The oedometer test data can be well fitted with a straight line in the bilogarithmic ln(1+ e ) ～ lg p plot. The initial effective stress corresponding to the initial void ratio is determined by extrapolation of the bilogarithmic compression line. This new way of extrapolating oedometer test data to the initial void ratio overcomes the difficulty of measuring the residual effective stress of soils in the remolded state. The initial stable compression line of ocean floor deposits under different deposition environments corresponds to the compression line at the sensitivity equal to one. This initial stable compression line obtained in this study is consistent with the available compression line at the sensitivity equal to one which is proposed based on the experimental data of remolded undrained strength and the theoretical concept of Cam clay critical state line.

Computational Approaches and Challenges in Spatial Transcriptomics

The development of spatial transcriptomics(ST)technologies has transformed genetic research from a single-cell data level to a two-dimensional spatial coordinate system and facilitated the study of the composition and function of various cell subsets in different environments and organs.The large-scale data generated by these ST technologies,which contain spatial gene expression information,have elicited the need for spatially resolved approaches to meet the requirements of computational and biological data interpretation.These requirements include dealing with the explosive growth of data to determine the cell-level and gene-level expression,correcting the inner batch effect and loss of expression to improve the data quality,conducting efficient interpretation and in-depth knowledge mining both at the single-cell and tissue-wide levels,and conducting multi-omics integration analysis to provide an extensible framework toward the in-depth understanding of biological processes.However,algorithms designed specifically for ST technologies to meet these requirements are still in their infancy.Here,we review computational approaches to these problems in light of corresponding issues and challenges,and present forward-looking insights into algorithm development.

Research and Design of a Fuzzy Neural Expert System

We have developed a fuzzy neural expert system that has the precisionand learning ability of a neural network. Knowledge is acquired from domainexperts as fuzzy rules and membership functions. Then, they are convertedinto a neural network which implements fuzzy inference without rule matching.The neural network is applied to problem-solving and learns from the dataobtained during operation to enhance the accuracy The learning ability of theneural network makes it easy to modify the membership functions defined bydomain experts. Also, by modifying the weights of neural networks adaptively,the problem of belief propagation in conventional expert systems can be solvedeasily. Converting the neural network back iato fuzzy rules and membershipfunctions helps explain the inner representation and operation of the neuralnetwork.

Mass spectrometry-based phosphoproteomics in cancer research

Phosphorylation is one of the most common post translational modifications （PTM）, participating in a large number of processes to regulate cellular functions. Phosphorylation is also one of the key factors in the origin and development of cancer. The rapid development of mass spectrometric-based phosphoproteomic technologies has made it possible for high-throughput identification and quantification of phosphorylation events. In this review, we provide a general introduction and summary of the achievements made in mass spectrometry based phosphoproteomic research, including the approaches for phosphopeptide identification and quantification, as well as instrumentation and data interpretation methods. We also review some discoveries in cancer research made possible by phosphoproteomic analysis technologies.