Many Types Of Analysis Research Articles

Building the Future with Earth – Herbarium CSEB as a Modern Self-Insulative, Eco-Friendly Material

Many types of analysis were undertaken in sustainability and passive energy, Reduction in Carbon emission and cost-effective style in summer cooling, it’s like rather than the usage of AC these days because of climate weather modification even this year and in coming years I needed to visualize whether or not the CSEB material is actually replacing AC system for a sustainable future. the rise of a movement against non-eco-friendly practices nowadays has woke up us to adapt to and incorporate practices that are pro-earth. we've got realized that the smaller steps taken nowadays, have a larger impact on our tomorrow. green practices within the housing industry will contribute towards a more robust and greener tomorrow. Construction using CSEBs is one in every of the various ways in which we are able to resort cut back the negative impact on mother earth. In this study, the effect of bulk viscosity and cement content on the thermal conductivity of cement- stabilized earth block CSEB is delved . Experimental results show that thermal conductivity increases with bulk viscosity. Changing the cement content slightly changes the thermal conductivity of CSEB at a specific bulk viscosity. No clear direct relationship was observed between thermal conductivity and cement content in CSEB. still, the CSEB compressive strength increased significantly with cement addition. Also, the compressive strength of CSEB increases as the cement content increases. CSEB shows pledge in earthen structures due to its increased compressive strength and reduced thermal conductivity. Keyword: Eco-friendly, Herbarium CSEB, Effective thermal comfort, Indoor thermal conductivity, passive material making, Herbs – Henna, Traditional techniques, Adobe earth blocks, Natural material.

A gap-free genome assembly of Chlamydomonas reinhardtii and detection of translocations induced by CRISPR-mediated mutagenesis

Genomic assemblies of the unicellular green alga Chlamydomonas reinhardtii have provided important resources for researchers. However, assembly errors, large gaps, and unplaced scaffolds as well as strain-specific variants currently impede many types of analysis. By combining PacBio HiFi and Oxford Nanopore long-read technologies, we generated a de novo genome assembly for strain CC-5816, derived from crosses of strains CC-125 and CC-124. Multiple methods of evaluating genome completeness and base-pair error rate suggest that the final telomere-to-telomere assembly is highly accurate. The CC-5816 assembly enabled previously difficult analyses that include characterization of the 17 centromeres, rDNA arrays on three chromosomes, and 56 insertions of organellar DNA into the nuclear genome. Using Nanopore sequencing, we identified sites of cytosine (CpG) methylation, which are enriched at centromeres. We analyzed CRISPR-Cas9 insertional mutants in the PF23 gene. Two of the three alleles produced progeny that displayed patterns of meiotic inviability that suggested the presence of a chromosomal aberration. Mapping Nanopore reads from pf23-2 and pf23-3 onto the CC-5816 genome showed that these two strains each carry a translocation that was initiated at the PF23 gene locus on chromosome 11 and joined with chromosomes 5 or 3, respectively. The translocations were verified by demonstrating linkage between loci on the two translocated chromosomes in meiotic progeny. The three pf23 alleles display the expected short-cilia phenotype, and immunoblotting showed that pf23-2 lacks the PF23 protein. Our CC-5816 genome assembly will undoubtedly provide an important tool for the Chlamydomonas research community.

The Sedimentary Geochemistry and Paleoenvironments Project.

The Sedimentary Geochemistry and Paleoenvironments Project.

Maxnodf: An R package for fair and fast comparisons of nestedness between networks

Abstract Nestedness is a widespread pattern in mutualistic networks that has high ecological and evolutionary importance due to its role in enhancing species persistence and community stability. Nestedness measures tend to be correlated with fundamental properties of networks, such as size and connectance, and so nestedness values must be normalised to enable fair comparisons between different ecological communities. Current approaches, such as using null‐corrected nestedness values and z‐scores, suffer from extensive statistical issues. Thus a new approach called NODFc was recently proposed, where nestedness is expressed relative to network size, connectance and the maximum nestedness that could be achieved in a particular network. While this approach is demonstrably effective in overcoming the issues of collinearity with basic network properties, it is computationally intensive to calculate, and current approaches are too slow to be practical for many types of analysis, or for analysing large networks. We developed three highly optimised algorithms, based on greedy, hill climbing and simulated annealing approaches, for calculation of NODFc, spread along a speed‐quality continuum. Users thus have the choice between a fast algorithm with a less accurate estimate, a slower algorithm with a more accurate estimate and an intermediate option. We outline the package and its implementation, as well as provide comparative performance benchmarking and two example analyses. We show that maxnodf enables speed increases of hundreds of times faster than existing approaches, with large networks seeing the biggest improvements. For example, for a large network with 3,000 links, computation time was reduced from 50 min using the fastest existing algorithm to 11 s using maxnodf. maxnodf makes correctly normalised nestedness measures feasible for complex analyses of even large networks. Analyses that would previously take weeks to complete can now be finished in hours or even seconds. Given evidence that correctly normalising nestedness values can significantly change the conclusions of ecological studies, we believe this package will usher in necessary widespread use of appropriate comparative nestedness statistics.

A Techno-Economic Perspective on Natural Gas and Its Value Chain

We describe the elements and actors in the global natural gas value chains with an emphasis on characteristics relevant for large-scale energy system and market modeling. We give backgrounds on natural gas as a hydrocarbon to provide a rationale and understanding for what functional representations in mathematical programming models aim to represent. Simply taking the most advanced and detailed functional forms for all value chain characteristics and activities will typically result in numerical intractability. One should carefully determine what is needed to address a research question or analyze a business case. Recent advances in mathematical programming do allow solving large models with adequate detail for many types of analysis. We discuss which functional forms and modeling approaches can be appropriate for representing various characteristics in different types of analysis and provide a succinct and general mathematical programming formulation reflecting the optimization problems for different types of actors in the value chain. We provide an implementation for a stylized network using GAMS.

Introductory guide to backgrounds in XPS spectra and their impact on determining peak intensities

Photoelectron and Auger peaks are central to most of the important uses of x-ray photoelectron spectroscopy (XPS), and thus, they receive the most attention in many types of analysis. Quantitative chemical analysis using XPS requires the assessment of the intensities of the photoemission peaks of the elements detected. Determination of peak intensities requires separation of the photoelectron peak signals from the background on which the peaks rest. For the determination of peak area intensities, the background is subtracted from overall signal intensity. The spectral background is also critical when peak fitting is used to determine intensities of overlapping peaks, and the model of background used in this process can impact the results. In addition to the impact on quantitative analysis, information about the depth distribution of elements in the near surface region can often be obtained by visual inspection of the background and quantified using appropriate modeling. This introductory guide provides some basic information about backgrounds in the XPS analysis, describes the types of background models that are commonly used, suggests some of their strengths and weaknesses, and provides examples of their use and misuse. Although the fundamental nature of some components of the background signals in XPS is not understood, indicating that none of the models in use are fully correct and the area is subject to active research, appropriate good practices have been established for most routine analysis. The guide describes good practices, identifies errors that frequently appear in the literature, and uses examples to demonstrate the impacts of background selections on determinations of peak intensities.

100 years of data is not enough to establish reliable drought thresholds

Drought research customarily uses statistics collected over a reference period to establish a threshold for declaring a region to be in a drought, or to estimate baseline return periods. Often these statistics involve quantile values from the tails of the distribution of reference period observations, such as 10th or even 1st percentile values. The length of the reference period is dictated by the available record length; often it is no longer than 50–100 years. Depending on the purpose for which the drought study is intended, the unit of time used as the averaging period for the hydrologic or meteorologic variables of interest is often as small as one month. In this circumstance, percentile values are each based on at most 100 data points. We show here that the statistical uncertainty resulting from these small sample sizes for estimating the threshold value is sufficient to compromise many types of analysis. We provide formulae for calculating the statistical uncertainties caused by limited record lengths and for estimating the record length needed to achieve a specified level of accuracy in an analysis. Our results show that datasets of 100 years or less are approximately 1/10 the length needed to achieve the level of reliability required for many applications. We also summarize options for augmenting the historical record when the existing record length is not long enough to support analysis at the desired level of accuracy.

Fast and accurate differential transcript usage by testing equivalence class counts

Background: RNA sequencing has enabled high-throughput and fine-grained quantitative analyses of the transcriptome. While differential gene expression is the most widely used application of this technology, RNA-seq data also has the resolution to infer differential transcript usage (DTU), which can elucidate the role of different transcript isoforms between experimental conditions, cell types or tissues. DTU has typically been inferred from exon-count data, which has issues with assigning reads unambiguously to counting bins, and requires alignment of reads to the genome. Recently, approaches have emerged that use transcript quantifications estimates directly for DTU. Transcript counts can be inferred from 'pseudo' or lightweight aligners, which are significantly faster than traditional genome alignment. However, recent evaluations show lower sensitivity in DTU analysis. Transcript abundances are estimated from equivalence classes (ECs), which determine the transcripts that any given read is compatible with. Recent work has proposed performing differential expression testing directly on equivalence class read counts (ECs). Methods: Here we demonstrate that ECs can be used effectively with existing count-based methods for detecting DTU. We evaluate this approach on simulated human and drosophila data, as well as on a real dataset through subset testing. Results: We find that ECs counts have similar sensitivity and false discovery rates as exon-level counts but can be generated in a fraction of the time through the use of pseudo-aligners. Conclusions: We posit that equivalence class read counts are a natural unit on which to perform many types of analysis.

Disaster Reporting and Alert System Using Tweets in a Social Media

The number of Social Media users have increased rapidly these days and a lot of valuable as well as non valuable information is shared in the social which is capable of reaching many people in a short period of time and hence the valuable information that are shared in the social media can be used for many types of analysis. In this paper the tweets that are shared in the name of a disaster is taken and then a alert system is build. This alert system gives alert to the users after checking the received data with the centralized database. This paper also gives a comparative study on the algorithm used in extracting the data from the social media which gives us the accuracy rate of different algorithm that can be used for text mining.

Informing energy consumption uncertainty: an analysis of energy data revisions

Quality energy consumption data are important for many types of analysis, and global data sets estimate trends of county level energy consumption, derived from country reported data and regional reports. We present a novel basis for informing uncertainty in energy data by quantifying the changes in reported energy consumption as countries update their previously reported data. We use 17 editions of the British Petroleum World Energy Statistics (2001–2017) to evaluate how reported energy consumption is revised over time in aggregate coal, oil, and natural gas consumption data. We find that 70% of non-zero data points are adjusted by an average of 1.3% of a country’s total fossil fuel use in the year after their first publication. Earlier data points are revised less often, but almost half of historical trends contain some revisions in later years. The size and rate of data revisions vary over countries and fuels: coal data points have larger, less frequent revisions while oil data points have smaller more frequent revisions, with natural gas in between. A k-means cluster analysis was performed to group together countries with similar revision patterns. These groups span income, economy classification, OECD membership, and regions. Standard country groupings, therefore, do not predict the extent to which a country’s energy data has undergone revisions in the past.

VSLM—The virtual sound level meter

Inexpensive sound level meters and low cost or free apps for smart phones and tables have made it much easier to introduce the concept of sound levels to a wide audience at very low cost. However, there are times when it is preferable to be able to take more complicated measurements that are generally only available on more expensive sound level meter. With fairly low cost digital recorders, one can now take a calibrated recording of an acoustic event and analyze the recording later. In this presentation, a free software package called VSLM: The Virtual Sound Level Meter is described. VSLM allows users to calibrate a recording and do many types of analysis including mimicking a sound level meter on fast, slow, Leq, octave, and 1/3 octave band analysis using fast FFT or digital meters that meet ANSI standards, high resolution spectral analysis, and create spectrograms.

Exponential scaling of single-cell RNA-seq in the past decade.

Measurement of the transcriptomes of single cells has been feasible for only a few years, but it has become an extremely popular assay. While many types of analysis can be carried out and various questions can be answered by single-cell RNA-seq, a central focus is the ability to survey the diversity of cell types in a sample. Unbiased and reproducible cataloging of gene expression patterns in distinct cell types requires large numbers of cells. Technological developments and protocol improvements have fueled consistent and exponential increases in the number of cells that can be studied in single-cell RNA-seq analyses. In this Perspective, we highlight the key technological developments that have enabled this growth in the data obtained from single-cell RNA-seq experiments.

Comparison of normalization and differential expression analyses using RNA-Seq data from 726 individual Drosophila melanogaster.

BackgroundA generally accepted approach to the analysis of RNA-Seq read count data does not yet exist. We sequenced the mRNA of 726 individuals from the Drosophila Genetic Reference Panel in order to quantify differences in gene expression among single flies. One of our experimental goals was to identify the optimal analysis approach for the detection of differential gene expression among the factors we varied in the experiment: genotype, environment, sex, and their interactions. Here we evaluate three different filtering strategies, eight normalization methods, and two statistical approaches using our data set. We assessed differential gene expression among factors and performed a statistical power analysis using the eight biological replicates per genotype, environment, and sex in our data set.ResultsWe found that the most critical considerations for the analysis of RNA-Seq read count data were the normalization method, underlying data distribution assumption, and numbers of biological replicates, an observation consistent with previous RNA-Seq and microarray analysis comparisons. Some common normalization methods, such as Total Count, Quantile, and RPKM normalization, did not align the data across samples. Furthermore, analyses using the Median, Quantile, and Trimmed Mean of M-values normalization methods were sensitive to the removal of low-expressed genes from the data set. Although it is robust in many types of analysis, the normal data distribution assumption produced results vastly different than the negative binomial distribution. In addition, at least three biological replicates per condition were required in order to have sufficient statistical power to detect expression differences among the three-way interaction of genotype, environment, and sex.ConclusionsThe best analysis approach to our data was to normalize the read counts using the DESeq method and apply a generalized linear model assuming a negative binomial distribution using either edgeR or DESeq software. Genes having very low read counts were removed after normalizing the data and fitting it to the negative binomial distribution. We describe the results of this evaluation and include recommended analysis strategies for RNA-Seq read count data.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2353-z) contains supplementary material, which is available to authorized users.

A New Ionosphere Tomography Algorithm With Two-Grid Virtual Observations Constraints and Three-Dimensional Velocity Profile

Ionosphere tomography is a typical ill-posed problem, and using the ionosphere priori information as the constraints to improve the state of normal equation is an effective approach to solve this problem. In this paper, we impose priori constraints by increasing the virtual observations in $n$-dimensional space. Then, after the inversion region to be gridded, we can form a stable structure between the grids with loose constraints, which greatly improve the state of normal equation. Based on that, to obtain the real-time velocity information of ionosphere electron density, we introduce the grid electron density velocity parameters, which can be estimated with electron density parameters simultaneously. The authors use the new algorithm and the global navigation satellite system data in Europe to inverse the 12 ionosphere electron density and velocity images on August 15, 2003, which reflects the ionosphere changes of electron density and velocity in whole day; in addition, we compare the results with the traditional algorithm multiplicative algorithm reconstruction technique's results. Furthermore, we compare the results with the changes time series of plasma frequency observed by ionosphere ionosonde among different layers, and many types of analysis and comparison verify the effectiveness and reliability of the new algorithm. The related research provides a new way for the real-time detection and prediction of ionosphere changes.

Let your data run free? The challenge of data redaction in paleontological collections

Abstract The data associated with museum collections are essential components for many types of analysis. Geodetic information, such as latitude and longitude, in particular, are necessary in the analysis of paleontological data sets when investigating the effect of climate change on biodiversity. However, the release of geodetic information can be problematic when those data are used to deplete paleontological resources. This problem and others (such as overcollecting and impact on sensitive ecosystems) are discussed in all disciplines of natural history. Herein we discuss the problem as it pertains to paleontological collections, with particular reference to collections and digitization objectives in the USA, discuss strategies employed for data redaction, and make the case for allowing almost all locality data to be released in the interest of science and an obligation to the public.

Atomic spectrometry updates: Review of advances in atomic spectrometry and related techniques

This review covers developments in ‘Atomic Spectrometry’. It covers atomic emission, absorption, fluorescence and mass spectrometry, but excludes material on speciation and coupled techniques which is included in a separate review. It should be read in conjunction with the other related reviews in the series.1–6 A critical approach to the selection of material has been adopted, with only novel developments in instrumentation, techniques and methodology being included. A number of themes have emerged from this year's review. Novel developments in sample preparation include the use of magnetic nanoparticles for solid phase extraction and an increase in the number of viable methods for use in quantitation of peptides, proteins and DNA by elemental tagging, particularly the development of multiplexed techniques. There were also some advances in electrochemical vapour generation, such as the use of reducing reagents immobilized on electrodes and development of electrolytic membrane diffusion cells. New instrumentation has been to the fore, with research into some novel and interesting miniaturized plasma sources being of particular interest, plus the development of a new distance of flight (DOF) mass spectrometer. There have been some insightful fundamental studies of particle atomization and ionization in ICP-MS, and subsequent space-charge effects after ion sampling, which should enable practical steps to solving some of these problems. One of the main drivers of research in isotope ratio analysis has been to increase detection power to enable smaller and smaller quantities of analyte to be measured, which yields advantages in geochronology and nuclear forensics. Laser ablation has played a large part in many types of analysis where high resolution is required, including analysis of single particles, small inclusions or elemental mapping of tissues, so the development of LA methods with extremely small spot sizes and efficient sample transport to the source has been key. In addition, several novel methods have been developed, such as laser ablation molecular isotopic spectrometry (LAMIS) for isotope ratio analysis, and stand-off LIBS techniques such as ‘underwater LIBS’. In contrast, very little research into the use of chemometrics has been reported, and fundamental studies are generally confined to characterization of new plasma sources.

Development of a robust method for establishing B cell lines using Epstein-Barr Virus

B lymphoblastoid cell lines (B-LCLs) are generally established from B lymphocytes by infection with Epstein-Barr virus (EBV). As their genomic structure is stable in culture, B-LCLs are a valuable resource for many types of analysis. The efficiency of establishing B-LCLs from freshly obtained blood samples from healthy individuals is almost 100%; however, for blood samples stored inappropriately after collection or held in long-term storage as peripheral blood mononuclear cells (PBMCs) in liquid nitrogen, the efficiency of B-LCL establishment can be considerably lower. To date, we have established more than 550 B-LCLs from 685 PBMC samples that have been stored in liquid nitrogen for over 20yr. The PBMCs were prepared from blood samples donated by individuals belonging to native minority ethnic groups in outlying regions of South America and elsewhere. The establishment of B-LCLs from this material is difficult, and failure results in the waste of valuable and rare samples. We sought to improve our success rate for establishing B-LCLs from these difficult and irreplaceable samples by a detailed examination of each step of the process. The analysis showed that two parameters were particularly critical to the success rate: the density of the PBMCs plated after EBV infection and the EBV titer. These observations shed light on cases where establishment of B-LCLs was hard due to the small number of PBMCs or damage to the cells.

Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology

BackgroundThe Matlab software is a one of the most advanced development tool for application in engineering practice. From our point of view the most important is the image processing toolbox, offering many built-in functions, including mathematical morphology, and implementation of a many artificial neural networks as AI. It is very popular platform for creation of the specialized program for image analysis, also in pathology. Based on the latest version of Matlab Builder Java toolbox, it is possible to create the software, serving as a remote system for image analysis in pathology via internet communication. The internet platform can be realized based on Java Servlet Pages with Tomcat server as servlet container.MethodsIn presented software implementation we propose remote image analysis realized by Matlab algorithms. These algorithms can be compiled to executable jar file with the help of Matlab Builder Java toolbox. The Matlab function must be declared with the set of input data, output structure with numerical results and Matlab web figure. Any function prepared in that manner can be used as a Java function in Java Servlet Pages (JSP). The graphical user interface providing the input data and displaying the results (also in graphical form) must be implemented in JSP. Additionally the data storage to database can be implemented within algorithm written in Matlab with the help of Matlab Database Toolbox directly with the image processing. The complete JSP page can be run by Tomcat server.ResultsThe proposed tool for remote image analysis was tested on the Computerized Analysis of Medical Images (CAMI) software developed by author. The user provides image and case information (diagnosis, staining, image parameter etc.). When analysis is initialized, input data with image are sent to servlet on Tomcat. When analysis is done, client obtains the graphical results as an image with marked recognized cells and also the quantitative output. Additionally, the results are stored in a server database. The internet platform was tested on PC Intel Core2 Duo T9600 2.8GHz 4GB RAM server with 768x576 pixel size, 1.28Mb tiff format images reffering to meningioma tumour (x400, Ki-67/MIB-1). The time consumption was as following: at analysis by CAMI, locally on a server – 3.5 seconds, at remote analysis – 26 seconds, from which 22 seconds were used for data transfer via internet connection. At jpg format image (102 Kb) the consumption time was reduced to 14 seconds.ConclusionsThe results have confirmed that designed remote platform can be useful for pathology image analysis. The time consumption is depended mainly on the image size and speed of the internet connections. The presented implementation can be used for many types of analysis at different staining, tissue, morphometry approaches, etc. The significant problem is the implementation of the JSP page in the multithread form, that can be used parallelly by many users. The presented platform for image analysis in pathology can be especially useful for small laboratory without its own image analysis system.

Towards unbiased parentage assignment: combining genetic, behavioural and spatial data in a Bayesian framework

Inferring the parentage of a sample of individuals is often a prerequisite for many types of analysis in molecular ecology, evolutionary biology and quantitative genetics. In all but a few cases, the method of parentage assignment is divorced from the methods used to estimate the parameters of primary interest, such as mate choice or heritability. Here we present a Bayesian approach that simultaneously estimates the parentage of a sample of individuals and a wide range of population-level parameters in which we are interested. We show that joint estimation of parentage and population-level parameters increases the power of parentage assignment, reduces bias in parameter estimation, and accurately evaluates uncertainty in both. We illustrate the method by analysing a number of simulated test data sets, and through a re-analysis of parentage in the Seychelles warbler, Acrocephalus sechellensis. A combination of behavioural, spatial and genetic data are used in the analyses and, importantly, the method does not require strong prior information about the relationship between nongenetic data and parentage.

APPLICATIONS OF NEGATIVE ION CHEMICAL IONIZATION MASS SPECTROMETRY TECHNIQUE IN ENVIRONMENTAL ANALYSIS

With the availability of Negative Ion Chemical Ionization (NCI) mode of ionization on most bench top Mass Spectrometry (MS), many analytical problems involving the analysis of electron capturing organic compounds can be easily resolved. The Negative Ion Chemical Ionization Mass Spectrometry (NCI/MS) technique has been utilized for many types of analysis at the Environmental Protection Laboratory on a regular basis for routine analysis and resolving sensitivity, matrix and interference problems. NCI/MS is shown to provide inroads in the identification and lowering of detection limits for halogenated pesticides, polychlorinated biphenyls (PCBs), dioxins and furans. NCI/MS specificity and selectivity are shown to eliminate interferences caused by substances such as plasticizers and other nonhalogenated compounds including petroleum products when analyzing contaminated sample extracts.