scholarly journals A model-based high throughput method for fecundity estimation in fruit fly studies

2018 ◽  
Author(s):  
Enoch Ng’oma ◽  
Elizabeth G. King ◽  
Kevin M. Middleton
Keyword(s):  
Drosophila Melanogaster ◽  
Large Scale ◽  
Cross Validation ◽  
Large Data ◽  
Fruit Fly ◽  
Model Organisms ◽  
Data Set ◽  
Wide Range ◽  
High Throughput Method ◽  
The Media

AbstractThe ability to quantify fecundity is critically important to a wide range of experimental applications, particularly in widely-used model organisms such as Drosophila melanogaster. However, the standard method of manually counting eggs is time consuming and limits the feasibility of large-scale experiments. We develop a predictive model to automate the counting of eggs from images of eggs removed from the media surface and washed onto dark filter paper. A cross-validation approach demonstrates our method performs well, with a correlation between predicted and manually counted values of 0.88. We show how this method can be applied to a large data set where egg densities vary widely.

scholarly journals DEVELOPMENT OF HIGH-PERFORMANCE AND LARGE-SCALE VIETNAMESE AUTOMATIC SPEECH RECOGNITION SYSTEMS

2019 ◽  
Vol 34 (4) ◽  
pp. 335-348
Author(s):  
Do Quoc Truong ◽  
Pham Ngoc Phuong ◽  
Tran Hoang Tung ◽  
Luong Chi Mai
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Call Center ◽  
High Performance ◽  
Large Scale ◽  
System Development ◽  
Large Data ◽  
Training Data ◽  
Data Set ◽  
Wide Range

Automatic Speech Recognition (ASR) systems convert human speech into the corresponding transcription automatically. They have a wide range of applications such as controlling robots, call center analytics, voice chatbot. Recent studies on ASR for English have achieved the performance that surpasses human ability. The systems were trained on a large amount of training data and performed well under many environments. With regards to Vietnamese, there have been many studies on improving the performance of existing ASR systems, however, many of them are conducted on a small-scaled data, which does not reflect realistic scenarios. Although the corpora used to train the system were carefully design to maintain phonetic balance properties, efforts in collecting them at a large-scale are still limited. Specifically, only a certain accent of Vietnam was evaluated in existing works. In this paper, we first describe our efforts in collecting a large data set that covers all 3 major accents of Vietnam located in the Northern, Center, and Southern regions. Then, we detail our ASR system development procedure utilizing the collected data set and evaluating different model architectures to find the best structure for Vietnamese. In the VLSP 2018 challenge, our system achieved the best performance with 6.5% WER and on our internal test set with more than 10 hours of speech collected real environments, the system also performs well with 11% WER

scholarly journals Drosophila melanogaster Response to Feeding with Neomycin-Based Medium Expressed in Fluctuating Asymmetry

Insects ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 378
Author(s):  
Kemal Büyükgüzel ◽  
Ender Büyükgüzel ◽  
Ewa Chudzińska ◽  
Anetta Lewandowska-Wosik ◽  
Renata Gaj ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Fluctuating Asymmetry ◽  
Fruit Fly ◽  
Model Organisms ◽  
Control Group ◽  
Developmental Stress ◽  
Type D ◽  
Wide Range ◽  
Electron And Light Microscopy ◽  
Anal Papillae

The fruit fly Drosophila melanogaster is a model species used for a wide range of studies. Contamination of Drosophila cultures with bacterial infection is common and is readily eradicated by antibiotics. Neomycin antibiotics can cause stress to D. melanogaster’s larvae and imagoes, which may affect the interpretation of the results of research using culture from neomycin-based medium. In the present study, fluctuating asymmetry (FA), one of the important bioindicators of stress, was measured. Larvae and imagoes of a wild-type D. melanogaster strain were exposed to various concentrations of neomycin. The size of anal papillae and selected wing veins were measured using scanning electron and light microscopy, respectively. Next, the FA was checked. The values obtained for larval anal papillae appeared to be concentration-dependant; the FA indices increased with the concentration of neomycin. The wing FA presented a large but variable correlation, depending on the measured vein. However, the mean length of veins was the highest for the control group, with neomycin-exposed groups showing lower values. The research showed that neomycin may cause sublethal stress in D. melanogaster, which manifests in increased FA indices. This suggests that neomycin can cause physiological and developmental stress in insects, which should be taken into account when interpreting the results of studies using these model organisms.

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

scholarly journals Galaxy spin direction distribution in HST and SDSS show similar large-scale asymmetry

2020 ◽  
Vol 37 ◽  
Author(s):  
Lior Shamir
Keyword(s):  
Large Scale ◽  
Spiral Galaxies ◽  
Hubble Space Telescope ◽  
Gravitational Interaction ◽  
Large Data ◽  
Sloan Digital Sky Survey ◽  
Data Sets ◽  
Dipole Axis ◽  
Data Set ◽  
The Asymmetry

Abstract Several recent observations using large data sets of galaxies showed non-random distribution of the spin directions of spiral galaxies, even when the galaxies are too far from each other to have gravitational interaction. Here, a data set of $\sim8.7\cdot10^3$ spiral galaxies imaged by Hubble Space Telescope (HST) is used to test and profile a possible asymmetry between galaxy spin directions. The asymmetry between galaxies with opposite spin directions is compared to the asymmetry of galaxies from the Sloan Digital Sky Survey. The two data sets contain different galaxies at different redshift ranges, and each data set was annotated using a different annotation method. The results show that both data sets show a similar asymmetry in the COSMOS field, which is covered by both telescopes. Fitting the asymmetry of the galaxies to cosine dependence shows a dipole axis with probabilities of $\sim2.8\sigma$ and $\sim7.38\sigma$ in HST and SDSS, respectively. The most likely dipole axis identified in the HST galaxies is at $(\alpha=78^{\rm o},\delta=47^{\rm o})$ and is well within the $1\sigma$ error range compared to the location of the most likely dipole axis in the SDSS galaxies with $z>0.15$ , identified at $(\alpha=71^{\rm o},\delta=61^{\rm o})$ .

scholarly journals Deconstructing Gastrulation at the Single Cell Level

2021 ◽  
Author(s):  
Tomer Stern ◽  
Sebastian J Streichan ◽  
Stanislav Y Shvartsman ◽  
Eric F Wieschaus
Keyword(s):  
Large Scale ◽  
Drosophila Embryo ◽  
Cell Segmentation ◽  
Model Organisms ◽  
Specific Cell ◽  
Cell Behaviors ◽  
Animal Development ◽  
Wide Range ◽  
Cell Groups ◽  
Epithelial Sheets

Gastrulation movements in all animal embryos start with regulated deformations of patterned epithelial sheets. Current studies of gastrulation use a wide range of model organisms and emphasize either large-scale tissue processes or dynamics of individual cells and cell groups. Here we take a step towards bridging these complementary strategies and deconstruct early stages of gastrulation in the entire Drosophila embryo, where transcriptional patterns in the blastoderm give rise to region-specific cell behaviors. Our approach relies on an integrated computational framework for cell segmentation and tracking and on efficient algorithms for event detection. Our results reveal how thousands of cell shape changes, divisions, and intercalations drive large-scale deformations of the patterned blastoderm, setting the stage for systems-level dissection of a pivotal step in animal development.

Characterising RDF data sets

2017 ◽  
Vol 44 (2) ◽  
pp. 203-229 ◽  
Author(s):  
Javier D Fernández ◽  
Miguel A Martínez-Prieto ◽  
Pablo de la Fuente Redondo ◽  
Claudio Gutiérrez
Keyword(s):  
Data Structures ◽  
Large Scale ◽  
Open Data ◽  
Structural Features ◽  
Data Sets ◽  
Data Set ◽  
Wide Range ◽  
Rdf Data ◽  
Description Framework ◽  
Resource Description

The publication of semantic web data, commonly represented in Resource Description Framework (RDF), has experienced outstanding growth over the last few years. Data from all fields of knowledge are shared publicly and interconnected in active initiatives such as Linked Open Data. However, despite the increasing availability of applications managing large-scale RDF information such as RDF stores and reasoning tools, little attention has been given to the structural features emerging in real-world RDF data. Our work addresses this issue by proposing specific metrics to characterise RDF data. We specifically focus on revealing the redundancy of each data set, as well as common structural patterns. We evaluate the proposed metrics on several data sets, which cover a wide range of designs and models. Our findings provide a basis for more efficient RDF data structures, indexes and compressors.

scholarly journals A Universal, Genomewide GuideFinder for CRISPR/Cas9 Targeting in Microbial Genomes

mSphere ◽  
2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Michelle Spoto ◽  
Changhui Guan ◽  
Elizabeth Fleming ◽  
Julia Oh
Keyword(s):  
Gene Function ◽  
Large Scale ◽  
Essential Gene ◽  
Bacterial Species ◽  
Bacterial Genome ◽  
Model Organisms ◽  
Design Parameters ◽  
Bacterial Genomes ◽  
Wide Range ◽  
User Friendly

ABSTRACT The CRISPR/Cas system has significant potential to facilitate gene editing in a variety of bacterial species. CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) represent modifications of the CRISPR/Cas9 system utilizing a catalytically inactive Cas9 protein for transcription repression and activation, respectively. While CRISPRi and CRISPRa have tremendous potential to systematically investigate gene function in bacteria, few programs are specifically tailored to identify guides in draft bacterial genomes genomewide. Furthermore, few programs offer open-source code with flexible design parameters for bacterial targeting. To address these limitations, we created GuideFinder, a customizable, user-friendly program that can design guides for any annotated bacterial genome. GuideFinder designs guides from NGG protospacer-adjacent motif (PAM) sites for any number of genes by the use of an annotated genome and FASTA file input by the user. Guides are filtered according to user-defined design parameters and removed if they contain any off-target matches. Iteration with lowered parameter thresholds allows the program to design guides for genes that did not produce guides with the more stringent parameters, one of several features unique to GuideFinder. GuideFinder can also identify paired guides for targeting multiplicity, whose validity we tested experimentally. GuideFinder has been tested on a variety of diverse bacterial genomes, finding guides for 95% of genes on average. Moreover, guides designed by the program are functionally useful—focusing on CRISPRi as a potential application—as demonstrated by essential gene knockdown in two staphylococcal species. Through the large-scale generation of guides, this open-access software will improve accessibility to CRISPR/Cas studies of a variety of bacterial species. IMPORTANCE With the explosion in our understanding of human and environmental microbial diversity, corresponding efforts to understand gene function in these organisms are strongly needed. CRISPR/Cas9 technology has revolutionized interrogation of gene function in a wide variety of model organisms. Efficient CRISPR guide design is required for systematic gene targeting. However, existing tools are not adapted for the broad needs of microbial targeting, which include extraordinary species and subspecies genetic diversity, the overwhelming majority of which is characterized by draft genomes. In addition, flexibility in guide design parameters is important to consider the wide range of factors that can affect guide efficacy, many of which can be species and strain specific. We designed GuideFinder, a customizable, user-friendly program that addresses the limitations of existing software and that can design guides for any annotated bacterial genome with numerous features that facilitate guide design in a wide variety of microorganisms.

Opinion on Different Classification Algorithms Used in Internet of Things Environment for Large Data Set

2019 ◽  
Vol 9 (1) ◽  
pp. 51-60
Author(s):  
Akhil Bansal ◽  
Piyush Kumar Shukla ◽  
Manish Kumar Ahirwar
Keyword(s):  
Internet Of Things ◽  
Economic Benefit ◽  
Cross Validation ◽  
Large Data ◽  
Classification Algorithms ◽  
Large Dataset ◽  
Data Set ◽  
Survey Article ◽  
Internet Of Things Environment ◽  
The Internet Of Things

Nowadays, IoT is an emerging technique and has evolved in many areas such as healthcare, smart homes, agriculture, smart city, education, industries, automation, etc. Many sensor and actuator-based devices deployed in these areas collect data or sense the environment. This data is further used to classify the complicated problem related to the particular environment around us, which also increases efficiency, productivity, accuracy and the economic benefit of the devices. The main aim of this survey article is how the data collected by these sensors in the Internet of Things-based applications are handled and classified by classification algorithms. This survey article also identifies various classification algorithms such as KNN, Random forest logistic regression, SVM with different parameters, such as accuracy cross validation, etc., applied on the large dataset generated by sensor-based devices in various IoT-based applications to classify it. In addition, this article also gives a brief review on advance IoT called CIoT.

scholarly journals Exploring the relationship between avalanche hazard and large-scale terrain choices at a helicopter skiing operation – Insight from run list ratings

2019 ◽  
Author(s):  
Reto Sterchi ◽  
Pascal Haegeli ◽  
Patrick Mair
Keyword(s):  
Large Scale ◽  
Selection Process ◽  
Decision Aids ◽  
Large Data ◽  
Limited Attention ◽  
Data Set ◽  
Linear Mixed Effects Model ◽  
Linear Mixed Effects ◽  
Avalanche Hazard ◽  
The Relationship

Abstract. While guides in mechanized skiing operations use a well-established terrain selection process to limit their exposure to avalanche hazard and keep the residual risk at an acceptable level, the relationship between the open/closed status of runs and environmental factors is complex and has so far only received limited attention from research. Using a large data set of over 25 000 operational run list codes from a mechanized skiing operation, we applied a general linear mixed effects model to explore the relationship between acceptable skiing terrain (i.e., status open) and avalanche hazard conditions. Our results show that the magnitude of the effect of avalanche hazard on run list codes depends on the type of terrain that is being assessed by the guiding team. Ski runs in severe alpine terrain with steep lines through large avalanche slopes are much more susceptible to increases in avalanche hazard than less severe terrain. However, our results also highlight the strong effects of recent skiing on the run coding and thus the importance of prior first-hand experience. Expressing these relationships numerically provides an important step towards the development of meaningful decision aids, which can assist commercial operations to manage their avalanche risk more effectively and efficiently.

scholarly journals Hedgehog Signaling in Organogenesis and the Tumor Microenvironment

2020 ◽  
Vol 21 (8) ◽  
pp. 2788
Author(s):  
Tsuyoshi Shimo
Keyword(s):  
Drosophila Melanogaster ◽  
Tumor Microenvironment ◽  
Signaling Pathway ◽  
Genetic Screening ◽  
Hedgehog Signaling ◽  
Large Scale ◽  
Fruit Fly ◽  
Hedgehog Signaling Pathway ◽  
Body Segment ◽  
Larval Body

The Hedgehog signaling pathway was first discovered in 1980 during a large-scale genetic screening seeking to find mutations that affect larval body segment development in the fruit fly, Drosophila melanogaster [...]

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