Definition Of Types Research Articles

Clinical, radiological, and genetic variation in pontocerebellar hypoplasia disorder and our clinical experience

Pontocerebellar hypoplasia (PCH) constitutes a heterogeneous neurodegenerative/neurodevelopmental disorder of the pons and cerebellum with onset in the prenatal period. Our study aimed to present different clinical and radiological manifestations of our genetically diagnosed PCH patients.Method: Six patients were enrolled in this study from September 2018 to March 2021. All the clinical radiological and genetic investigations were done at Cukurova University Medical School.Results: Five children were diagnosed genetically and categorized under one of the types of PCH (type 10,7,11). Homozygous mutations in CLP1 In PCH type 10, TOE1 in PCH type 7, and TBC1D23 in PCH type 11 were respectively detected. Pateint with PCH type 11 and female patient with PCH type 7 could walk and speak few words. Male patient with PCH type 7 had disorder of sex development.Conclusion: According to our study, PCH is a rare neurodegenerative disease, although some types are static as PCH11 male gender and PCH7 female gender. Some clinical features are specific to a definite type. PCH7 express disorders of sex development most apparent in 46 XY. Some ethnic groups could express distinct subtypes. PCH10 is seen in the Turkish population. Radiological imaging is beneficial in pre-diagnosis; all the patients had different pons and cerebellar hypoplasia degrees. Genetic testing like whole exome sequencing -next-generation sequencing is essential in setting the definite diagnosis and determining the type/subtype of PCH.

Numerical treatments for the optimal control of two types variable-order COVID-19 model

In this paper, a novel variable-order COVID-19 model with modified parameters is presented. The variable-order fractional derivatives are defined in the Caputo sense. Two types of variable order Caputo definitions are presented here. The basic reproduction number of the model is derived. Properties of the proposed model are studied analytically and numerically. The suggested optimal control model is studied using two numerical methods. These methods are non-standard generalized fourth-order Runge–Kutta method and the non-standard generalized fifth-order Runge–Kutta technique. Furthermore, the stability of the proposed methods are studied. To demonstrate the methodologies’ simplicity and effectiveness, numerical test examples and comparisons with real data for Egypt and Italy are shown.

Intralesional injection of purified protein derivative versus Candida antigen in treatment of genital warts.

The Genital warts are common sexually transmitted diseases caused by definite types of human papillomavirus. There are many strategies for the treatment of genital wart and intralesional immunotherapy is considered to be a safe and effective treatment modality. However, there are lack of studies that comparing the clinical effectiveness of intralesional purified protein derivative (PPD) and Candida antigen (CA) in genital wart treatment. To investigate the effectiveness and safety of PPD and CA in the treatment of genital warts. Eighty patients were enrolled in this study and were randomly divided into 2 groups with 40 patients in each. Each antigen was injected intralesionally at a dose of 0.1ml into the largest wart every 2 weeks until complete improvement or for a maximum of four sessions. Complete clinical response was demonstrated in 65%, 62.5% in PPD and CA groups, respectively. There was no statistically difference between both groups. After the 3-month follow-up period, 72.5%, 85% of patients showed complete clearance in PPD and CA groups respectively. Side effects were mild and insignificant in both groups. Recurrence was observed in only one patient in each group. Immunotherapy by intralesional PPD and CA injection is considered to be effective and well-tolerated modalities in treatment of genital wart with minimal side effects and recurrence rate compared to other modalities.

The “Lamprophyre Clan” Revisited

Abstract A sequential genetic diagram is proposed for lamprophyres adopting their definitions, classification, petrological and geochemical signatures from an elaborated literature survey. Based on the definition of individual lamprophyric types, the existence of “Lamprophyre clan” of rocks is supported as it was first proposed by Rock in 1991. A diagram has been created for this purpose. Characteristic examples from India and their approximate spatial distribution in the eastern Dharwar craton in particular, have also been presented.

A sustainable BIM-based multidisciplinary framework for underground pipeline clash detection and analysis

An urban underground pipeline system is widely applied to ensure the normal operation of urban functions. Building information modelling (BIM) can integrate a multi-disciplinary underground pipeline information system to improve the efficiency and quality of underground pipeline management and maintenance. This study therefore used BIM to establish a sustainable multi-disciplinary evaluation framework for underground pipeline clash detection and analysis. The framework integrated modules such as clash type definition and analysis, clash-rule definition, BIM clash detection, rule contribution and evaluation, irrelevant clash filtration, and clash coordination. The results showed that the proposed framework can effectively reduce design errors and burdens, and develop a knowledge-based rule for multiple participants and data objects, maximising multi-level and multi-factor optimisation for underground pipeline management and maintenance. The results also indicated that the sustainable BIM-aided urban underground pipeline optimisation framework plays an important role in advancing the infrastructural design process, and the exploration of greener measures to improve the underground built environment.

Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update.

Advertisement calls constitute the main acoustic signals emitted by frogs during reproductive seasons and are considered species-specific. Currently, many studies explore the advertisement calls in this group, including descriptions, taxonomy status, influence of social and ecological aspects, character displacement and plasticity. Although some patterns are detected in several anuran species, the possible intra and interpopulation variation is not well established for the group. Furthermore, new approaches have been proposed to standardize studies in the area and contribute to the description and interpretation of anuran calls, highlighting the urgency of a literature review. We aimed to review and update the advertisement calls of 18 anurans species from the megadiverse Atlantic Forest of Southeastern Brazil. We analyzed 1612 advertisement calls from 175 males of 18 anuran species recorded in ten communities between September 2018 and March 2019. We reviewed the information available in 23 scientific papers and describe each advertisement call based on recent papers. Our results include the definition of sound type for all species recorded, providing temporal and spectral parameters for each species along different localities, including intra and interpopulation variations. We provide new information on the frequency range (minimum and maximum frequencies) for eight species. A new description of the advertisement and territorial call of Boana bandeirantes is also provided based on our fieldwork observations. We emphasize that many species present interpopulation variance throughout their distribution in the megadiverse Atlantic Forest. We hope this information will contribute to future research on amphibian anuran bioacoustics and natural history.

Developmental Deconvolution for Classification of Cancer Origin.

Here we map the developmental trajectories of tumors. We deconvolute tumor transcriptomes into signals for mammalian developmental programs and use this information to construct a deep learning classifier that outputs tumor type. We apply the classifier to CUP and reveal the developmental origins of patient tumors. See related commentary by Wang, p. 2498. This article is highlighted in the In This Issue feature, p. 2483.

Diffusion-Slip Boundary Conditions for Isothermal Flows in Micro- and Nano-Channels.

Continuum description of flows in micro- and nano-systems requires ad hoc addition of effects such as slip at walls, surface diffusion, Knudsen diffusion and others. While all these effects are derived from various phenomenological formulations, a sound theoretical ground unifying these effects and observations is still lacking. In this paper, adopting the definition and existence of various type of flow velocities beyond that of the standard mass velocity, we suggest derivation of model boundary conditions that may systematically justify various diffusion process occurring in micro- and nano-flows where the classical continuum model breaks down. Using these boundary conditions in conjunction with the classical continuum flow equations we present a unified derivation of various expressions of mass flow rates and flow profiles in micro- and nano-channels that fit experimental data and provide new insights into these flow profiles. The methodology is consistent with recasting the Navier–Stokes equations and appears justified for both gas and liquid flows. We conclude that these diffusion type of boundary conditions may be more appropriate to use in simulating flows in micro- and nano-systems and may also be adapted as boundary condition models in other interfacial flow modelling.

FastMix: a versatile data integration pipeline for cell type-specific biomarker inference.

Flow cytometry (FCM) and transcription profiling are the two widely used assays in translational immunology research. However, there is no data integration pipeline for analyzing these two types of assays together with experiment variables for biomarker inference. Current FCM data analysis mainly relies on subjective manual gating analysis, which is difficult to be directly integrated with other automated computational methods. Existing deconvolutional analysis of bulk transcriptomics relies on predefined marker genes in the transcriptomics data, which are unavailable for novel cell types and does not utilize the FCM data that provide canonical phenotypic definitions of the cell types. We developed a novel analytics pipeline-FastMix-for computational immunology, which integrates flow cytometry, bulk transcriptomics and clinical covariates for identifying cell type-specific gene expression signatures and biomarker genes. FastMix addresses the 'large p, small n' problem in the gene expression and flow cytometry integration analysis via a linear mixed effects model (LMER) for both cross-sectional and longitudinal studies. Its novel moment-based estimator not only reduces bias in parameter estimation but also is more efficient than iterative optimization. The FastMix pipeline also includes a cutting-edge flow cytometry data analysis method-DAFi-for identifying cell populations of interest and their characteristics. Simulation studies showed that FastMix produced smaller type I/II errors than competing methods. Validation using real data of two vaccine studies showed that FastMix identified a consistent set of signature genes as in independent single-cell RNA-seq analysis, producing additional interesting findings. Source code of FastMix is publicly available at https://github.com/terrysun0302/FastMix. Supplementary data are available at Bioinformatics online.

Some New Types of Convergence Definitions for Random Variable Sequences

In this paper, we introduce the concepts of invariant convergence in probability, statistically invariant convergence in probability, invariant convergence almost surely, invariant convergence in distribution and invariant convergence in Lp-norm for sequences of random variables. Also, we investigate some inclusion relations.

Characterization of three novel cell lines derived from the brain of spotted sea bass: Focusing on cell markers and susceptibility toward iridoviruses

Despite tens of cell lines originating from fish brain tissue have been constructed, little is known about the definite cell types they belong to. Whether fish cell lines derived from the brain shares similar characteristics is not well-answered yet. Here, we constructed three cell lines designated as LMB-S, LMB-M, LMB-L using brain tissue of spotted sea bass (Lateolabrax maculatus). Among them, LMB-L was identified as astroglia-like cells considering the high expression of GFAP, DCX, PTX, S100b, which are regarded as astrocyte-specific or astrocyte-associated cell markers. LMB-M exhibited smooth muscle-like features showing strong expression of LMOD1, SLAMP, M-cadherin, MGP, which are confirmed as muscle-restricted or myogenesis-involved cell markers. Although LMB-S was not definitely identified, it appeared an activation of WNT/β-catenin pathway. Besides the distinct expression profiles of cell markers, the three cell lines also presented differences in transfection efficiency and susceptibility to iridovirus infection. Relying on the established cell lines, a novel megalocytivirus, named LMIV (Lateolabrax maculatus iridovirus), was first isolated from diseased spotted sea bass. Genetic analysis of major capsid protein (MCP) and adenosine triphosphatase (ATPase) manifested that LMIV was clearly distinguishable from other representative teleost iridoviruses. Further investigations revealed that LMIV could replicate most efficiently in LMB-L cells obtaining the highest viral load (2.16 × 1010 copy/mL). By contrast, LMB-S cells gave rise to the highest viral load up to 3.86 × 108 copy/mL, when the three cell lines were infected with MRV, a newly emerged ranavirus. Moreover, LMIV infection caused lots of cells to be detached from monolayers, generating adherent and non-adherent cells. An opposite expression profiling of type I IFN pathway-related genes (JAK1, STAT1, STAT2, IRF9, Mx1) was found between adherent and non-adherent cells. Combined with the analysis of MCP gene expression, it is speculated that inhibiting type I IFN pathway in non-adherent cells allowed the facilitation of virus duplication. Taken together, the present study broadens our understanding about the diversity of cell lines derived from fish brain tissue and screening cells more susceptible to virus is not only meaningful for the development of vaccine, but also provide clues for further clarification of cell-iridovirus interactions.

A Henstock Approach of the PUL-integra

The PUL-integral is a McShane type of definition in which the notion of a partition of unity is of great importance. It was first introduced by Kurzweil and Jarnik. Recently, Boonpogkrong revisited this definition and presented its, relatively, simplified approach. In this paper, a Henstock-Kurzweil approach of this integral including its fundamental properties will be presented.

STUDENT ERRORS IN WRITING THE ENGLISH MATHEMATICAL OPERATION IN HIGHER EDUCATION

English has been well-known as the world's international language. As a means of global communication, it should be actively mastered both orally and in writing. Writing is one of the skills that must be mastered by the students. It is related to the words, phrases, clauses and sentences. Then, if the meaning is unclear, people will misunderstand about the meaning of the sentences. The research investigated student errors in writing the English mathematical operations. The research is focused on the operation of addition, subtraction, multiplication and division. The research used qualitative approach using test and interview to collect the data. After conducting the research, it shows that there are some types of errors found such as incomplete materials error, technical errors, errors in understanding the previous material, and language misinterpretation. Meanwhile, student errors in the type of data misuse, theorems and definition of misuseand also unverified solutions are not found on the research.

The Effects of Using Education Technology Tools on Learning Grammar for Students in Secondary School

Technology has become an indispensable part of modern life, and this is also true in education, especially during today's Covid-19 pandemic when students have to study online and offline. Educational technology and especially technology tools are used in teaching and learning English to promote teachers' teaching process to be more active, proactive, and creative, and also to help students have a more active and effective way of learning. In addition, technology helps teachers design their lessons more lively and attractive and provide extra lessons outside of regular school hours to help students understand the content of the lectures deeply, complete their assignments and expand their knowledge, especially grammar. This study focuses on the effects of using technology and technology tools in cultivating grammar for students, remarkably in supporting students in online learning. In this article, researchers have given definitions of technology tools, grammar, and types of tools commonly used in the process of teaching and learning grammar; thereby, teachers have the right choice for each type of technology tool for their lesson. At the same time, it also significantly improves the teaching and learning process when technology is applied.

The geospatial and conceptual configuration of the natural environment impacts the association with health outcomes and behavior in children and adolescents

BackgroundStudies investigating associations between natural environments and health outcomes or health behaviors in children and adolescents yielded heterogenous results to date. This may be the result of different geospatial configurations of the natural environment and confounding characteristics of the study population. Thus, we investigated how the relationship between the natural environment and mental health, muscular fitness, and physical activity varies depending on the geospatial configuration of nature and children’s and adolescents’ characteristics.MethodsData were derived from the German Motorik-Modul (MoMo) cohort study (2018–2020) that investigates physical activity, muscular fitness, and health parameters in a national sample of children and adolescents (N = 2843) between four and 17 years (Mage = 10.46 ± 3.49 years; 48.3% girls). Mental health was assessed via questionnaire, muscular fitness via standing long jump, and physical activity with 7-day accelerometer measurement. Using geographic information systems, land cover, and land use data, three different nature definitions were applied. Both circular buffers (100–1000 m) and street-network buffers (1000–5000 m) were created for each of the nature definitions. Associations were explored with linear regression models, and interaction analysis was used to investigate how those relationships vary by gender, age, and socio-economic status.ResultsThe relationship between the three outcomes and the natural environment varied considerably depending on the nature definition, buffer size, and buffer type, as well as socio-demographic characteristics. Specifically, when comparing youth with a high socio-economic status to those with a medium socio-economic status, smaller circular buffer distances were related to less physical activity, but larger street-network buffer distances were related to greater mental health problems. Distinct relationships also occurred for youth with low socio-economic status in those relationships, with the pattern being less clear.ConclusionsFor future health research studies that investigate the role of the natural environment, we argue for the development of an a-priori model that integrates both geospatial considerations (nature definition, buffer type, and buffer size) and conceptual considerations (health outcome/behavior, sample characteristics) based on potentially underlying mechanisms that link the natural environment and the health outcome or behavior under investigation to theoretically underpin the geospatial configuration of the natural environment.

Color contour texture based peanut classification using deep spread spectral features classification model for assortment identification

Agriculture is one of great economic growth in India by producing variety of peanuts for various co products development. Peanut Crop and weed identification is an important step in developing a highly efficient automotive peanut production system. Most of the exiting classification fix the threshold margins to select the inappropriate features cause classification inaccuracy. Deep learning, as a powerful image processing technology, can extract conventional and characteristic features in layers. Spectral information is used as the input of the network, and the output spectral characteristics of the network are directly passed to the subsequent classifiers to achieve pixel-level classification. To resolve the classification categorization problem, we propose a Color contour texture based peanut classification using deep spread spectral features classification model for variety identification. Initial the Cascading subset Feature Filtering (CSFF) is applied to select the shape textures, color gradient rate form histogram equivalence and returns the feature scalar values. Based in CSFF the feature weight is attained to Social Spider Optimization to select the Impact Features Weight (SSO-IFW). The optimal object segmentation war applied based on cross fold object verification to select the shape projection features. Then Ada Boosting classifier generate the type of object structural for identifying type definition to generate pattern to produce peanut characteristic clusters. Based on Image Features recognition clusters, deep spread spectral neural classification is applied to train the features with soft-max logical activation function with Adaptive Convolution Neural Network (ACNN) to categorize the peanuts based on feature characteristics using image recognition, 20 varieties of peanut are collected through scanner type dataset to train the images into deep neural network. This produce high classification accuracy up to 89 %, high precision, recall rate under F-measure with low false rate. This achieves high classification than other existing methods.

Breakthrough Innovation: A Bibliometric Analysis of the literature and Proposed Framework

A surfeit of definitions for innovation types has resulted in the equivocal way breakthrough innovation is defined and used in the academic literature. The term breakthrough is often synonymously used with radical, disruptive, discontinuous, or stated results of radical innovations built to destroy past competencies. Such misperception may lead to several problems. First, it confuses breakthrough with competence destroying innovations, radical innovations, and product innovations. Second, if a breakthrough is equated with radical or competence destroying innovations, or new product launches, we assume that firms risk disbanding their existing technologies. Such activities without a clear path have shortcomings such as integration costs and information overload, leading to inconclusive results and the high complication of combining dissimilar innovations. Lastly, we do not know how these innovations relate to each other with a lack of comprehensive understanding. We analyze the extant literature using bibliometric method and propose a Configuration-Application-Performance framework that provides an evaluative assessment of types of innovations and their thematic linkages. This framework allows us to resolve some myths on how innovation has been conceptualized and operationalized. It also helps future researchers understand breakthroughs from an innovation performance perspective.

Clarifying a Fragmented Theoretical Landscape: A Process Model Approach to Workplace Bullying

Frequent reports around the globe continue to fuel scientific and social interest in the pandemic of workplace bullying. Despite this interest, reviewers of the literature still lament difficulty identifying a conceptualization that clearly differentiates bullying from other forms of workplace aggression and victimization (e.g., abusive supervision, harassment, social undermining, etc.). We diagnose the problem underlying this lack of clarity and propose a solution for it. First, we explain how inconsistent and imprecise integration of four qualifiers—incidence, interpretation, intent, and imbalance of power—result in too much distinctiveness between definitions of bullying as well as too little distinctiveness from definitions of other types of workplace aggression and victimization. We then propose and demonstrate how taking a process-theoretical approach to conceptualize workplace bullying mitigates both distinctiveness issues. Doing so leads us to provide a conceptually distinct definition of bullying: a response to goal conflict in which perpetrators falsely convince targets that they are too defenseless and powerless to refuse illegitimate outcomes. We conclude with a discussion regarding how clarifying the concept of workplace bullying this way facilitates progress in developing theories and practical interventions for it.

CellRegMap: a statistical framework for mapping context‐specific regulatory variants using scRNA‐seq

Single‐cell RNA sequencing (scRNA‐seq) enables characterizing the cellular heterogeneity in human tissues. Recent technological advances have enabled the first population‐scale scRNA‐seq studies in hundreds of individuals, allowing to assay genetic effects with single‐cell resolution. However, existing strategies to analyze these data remain based on principles established for the genetic analysis of bulk RNA‐seq. In particular, current methods depend on a priori definitions of discrete cell types, and hence cannot assess allelic effects across subtle cell types and cell states. To address this, we propose the Cell Regulatory Map (CellRegMap), a statistical framework to test for and quantify genetic effects on gene expression in individual cells. CellRegMap provides a principled approach to identify and characterize genotype–context interactions of known eQTL variants using scRNA‐seq data. This model‐based approach resolves allelic effects across cellular contexts of different granularity, including genetic effects specific to cell subtypes and continuous cell transitions. We validate CellRegMap using simulated data and apply it to previously identified eQTL from two recent studies of differentiating iPSCs, where we uncover hundreds of eQTL displaying heterogeneity of genetic effects across cellular contexts. Finally, we identify fine‐grained genetic regulation in neuronal subtypes for eQTL that are colocalized with human disease variants.

Reward Type Affects Dogs' Performance in the Cylinder Task

The cylinder task, which requires detouring around an obstacle to retrieve a reward, is a popular method for assessing inhibitory control in dogs and other species. However, performance on the cylinder task has poor construct validity represented by its lack of correlations with other inhibitory control measures, ceiling effects, and influence of non-cognitive factors. In the current study we examined whether reward type affected dogs’ performance in the cylinder task. We compared working-line Labrador retrievers' (n = 38) performance on two conditions of the cylinder task, one with a treat and another with a ball reward, and found that dogs performed significantly better when a treat was used. Our secondary goal was to determine if how we defined a dog’s response changed interpretation of the results. We found better performance when a narrower definition of an inhibitory control failure was used. Further, under one condition of reward type and response definition, cylinder task performance was predicted by another measure of inhibitory control (Dog Impulsivity Assessment Scale scores). These findings are the first to show the effect of reward type on cylinder task performance as well as a relationship between the cylinder task and another measure of inhibitory control in dogs. We discuss these results in relation to previous findings on the effects of task features on cylinder task performance and its construct validity.