Boundaries For Regions Research Articles

SCN1A: bioinformatically informed revised boundaries for promoter and enhancer regions.

Pathogenic variations in the sodium voltage-gated channel alpha subunit 1 (SCN1A) gene are responsible for multiple epilepsy phenotypes, including Dravet syndrome, febrile seizures (FS) and genetic epilepsy with FS plus. Phenotypic heterogeneity is a hallmark of SCN1A-related epilepsies, the causes of which are yet to be clarified. Genetic variation in the non-coding regulatory regions of SCN1A could be one potential causal factor. However, a comprehensive understanding of the SCN1A regulatory landscape is currently lacking. Here, we summarized the current state of knowledge of SCN1A regulation, providing details on its promoter and enhancer regions. We then integrated currently available data on SCN1A promoters by extracting information related to the SCN1A locus from genome-wide repositories and clearly defined the promoter and enhancer regions of SCN1A. Further, we explored the cellular specificity of differential SCN1A promoter usage. We also reviewed and integrated the available human brain-derived enhancer databases and mouse-derived data to provide a comprehensive computationally developed summary of SCN1A brain-active enhancers. By querying genome-wide data repositories, extracting SCN1A-specific data and integrating the different types of independent evidence, we created a comprehensive catalogue that better defines the regulatory landscape of SCN1A, which could be used to explore the role of SCN1A regulatory regions in disease.

What does the NRTL model look like? Determination of boundaries for different fluid phase equilibrium regions

AbstractThe adequate correlation of experimental phase equilibrium data by using any thermodynamic model represents a key point for the rigorous design of the chemical processes. However, this data correlation process remains a challenging problem, due to the high nonlinearity of the models used and the consequent problems of convergence. The present work analyzes the nonrandom two‐liquids mode (NRTL) model to check the relation between the values of the binary interaction parameters and the corresponding phase equilibria that the NRTL model can or cannot reproduce. Additionally, in the case of the LLE, empirical equations have been established as a function of the nonrandomness parameter, to model the trajectory of the different miscibility boundaries observed. These functions can be used as constraints in the experimental data correlation procedure to reduce the search space and guarantee the consistency of the obtained binary interaction parameters with the experimental behavior of the system under study.

To cognition of the scientific contribution of Professor L.I. Malyshev to the floristic research of Siberia and other territories: a brief analytical review

Analytical review of scientific contribution of Professor Malyshev is performed and presented on the floristic research of Siberia and other territories (Ural Mountains, Mongolia, Russian Far East, etc.). It was shown, that there were several stages in these researches: from Eastern Sayan to Stanovoy Uplands, Putorana Plateau, and then Central (Baikalian Siberia and Dahuria) Siberia, Siberia in whole, and joined flora of Siberia and Russian Far East, usung different methodical approaches (method of concrete flora of A.I. Tolmachev adopted to mountain regions, and various techniques of multivariate statistics, such as rank correlations for familiesspecies, families-genera, and genera-species in head parts of taxonomic spectra, usually consists of 10 to 20 taxa (families or genera). To solve some florogenetic issues, the concept of floristic complexes as stable groups of species located in a certain belt of mountains (for example, alpine and mountain-steppe) was proposed and applied. At all stages of floristic research, the task was set to maximally identify the species composition on territories of various sizes for subsequent subdivision, with the identification of the boundaries for floristic regions, subregions, provinces and sub-provinces. The local floras and working floristic districts were taken as the basic elements of such division.

BRR-Net: A tandem architectural CNN-RNN for automatic body region localization in CT images.

Automatic identification of consistently defined body regions in medical images is vital in many applications. In this paper, we describe a method to automatically demarcate the superior and inferior boundaries for neck, thorax, abdomen, and pelvis body regions in computed tomography (CT) images. For any three-dimensional (3D) CT image I, following precise anatomic definitions, we denote the superior and inferior axial boundary slices of the neck, thorax, abdomen, and pelvis body regions by NS(I), NI(I), TS(I), TI(I), AS(I), AI(I), PS(I), and PI(I), respectively. Of these, by definition, AI(I)=PS(I), and so the problem reduces to demarcating seven body region boundaries. Our method consists of a two-step approach. In the first step, a convolutional neural network (CNN) is trained to classify each axial slice in I into one of nine categories: the seven body region boundaries, plus legs (defined as all axial slices inferior to PI(I)), and the none-of-the-above category. This CNN uses a multichannel approach to exploit the interslice contrast, providing the neural network with additional visual context at the body region boundaries. In the second step, to improve the predictions for body region boundaries that are very subtle and that exhibit low contrast, a recurrent neural network (RNN) is trained on features extracted by CNN, limited to a flexible window about the predictions from the CNN. The method is evaluated on low-dose CT images from 442 patient scans, divided into training and testing sets with a ratio of 70:30. Using only the CNN, overall absolute localization error for NS(I), NI(I), TS(I), TI(I), AS(I), AI(I), and PI(I) expressed in terms of number of slices (nS) is (mean±SD): 0.61±0.58, 1.05±1.13, 0.31±0.46, 1.85±1.96, 0.57±2.44, 3.42±3.16, and 0.50±0.50, respectively. Using the RNN to refine the CNN's predictions for select classes improved the accuracy of TI(I) and AI(I) to: 1.35±1.71 and 2.83±2.75, respectively. This model outperforms the results achieved in our previous work by 2.4, 1.7, 3.1, 1.1, and 2 slices, respectively for TS(I), TI(I), AS(I), AI(I)=PS(I), and PI(I) classes with statistical significance. The model trained on low-dose CT images was also tested on diagnostic CT images for NS(I), NI(I), and TS(I) classes; the resulting errors were: 1.48±1.33, 2.56±2.05, and 0.58±0.71, respectively. Standardized body region definitions are a prerequisite for effective implementation of quantitative radiology, but the literature is severely lacking in the precise identification of body regions. The method presented in this paper significantly outperforms earlier works by a large margin, and the deviations of our results from ground truth are comparable to variations observed in manual labeling by experts. The solution presented in this work is critical to the adoption and employment of the idea of standardized body regions, and clears the path for development of applications requiring accurate demarcations of body regions. The work is indispensable for automatic anatomy recognition, delineation, and contouring for radiation therapy planning, as it not only automates an essential part of the process, but also removes the dependency on experts for accurately demarcating body regions in a study.

Upper boundaries of active galactic nucleus regions in optical diagnostic diagrams

ABSTRACT The distribution of galaxies in optical diagnostic diagrams can provide information about their physical parameters when compared with ionization models under proper assumptions. By using a sample of central emitting regions from the Mapping Nearby Galaxies at Apache Point Observatory survey (MaNGA), we find evidence of the existence of upper boundaries for narrow-line regions (NLRs) of active galactic nuclei (AGNs) in optical Baldwin, Phillips & Terlevich (BPT) diagrams, especially in diagrams involving [S ii]λλ6716, 6731/Hα. Photoionization models can reproduce the boundaries well, as a consequence of the decrease of [S ii]λλ6716, 6731/Hα and [O iii]λ5007/Hβ ratios at very high metallicity. Whilst the exact location of the upper boundary in the [S ii] BPT diagram depends only weakly on the electron density of the ionized cloud and the secondary nitrogen prescription, its dependence on the shapes of the input spectral energy distributions (SEDs) is much stronger. This allows us to constrain the power-law index of the AGN SED between 1 Ryd and ∼100 Ryd to be less than or equal to −1.40 ± 0.05. The coverage of photoionization models in the [N ii] BPT diagram has a stronger dependence on the electron density and the secondary nitrogen prescription. With the density constrained by the [S ii] doublet ratio and the input SED constrained by the [S ii] BPT diagram, we find that the extent of the data in the [N ii] BPT diagram favours those prescriptions with high N/O ratios. Although shock-ionized clouds can produce line ratios similar to those from photoionization, the resulting shapes of the upper boundaries, if they exist, would likely be different from those of photoionizing origin.

Sulcal Depth in Lateral Prefrontal Cortex Predicts Working Memory in Childhood

Sulci, the indentations in the brain, develop over childhood (Zilles et al., 1988; Alemán‐Gómez et al., 2013), and demonstrate individual differences linked to cognition (Cachia et al., 2018; Im et al., 2011). Previous neuroimaging work implicates prefrontal cortex (PFC) in working memory, a key facet of cognition. In particular, maintaining items in working memory (e.g., keeping a series of digits in mind) engages ventrolateral prefrontal cortex (VLPFC), whereas maintaining items in working memory (e.g., reversing a series of digits) engages both VLPFC and dorsolateral prefrontal cortex (DLPFC; Crone et. al, 2006). We propose to examine the relationship between sulcal depth in these regions and working memory for two tasks: Digit Span Forwards, which taxes maintenance, and Digit Span Backwards, which taxes manipulation and maintenance. Sulcal morphology of the PFC has been classically proposed to be functionally relevant to cognition that engages this region (Sanides, 1964). Thus, we hypothesized that there would be a relationship between sulcal depth and behavioral performance, whereby greater sulcal depth would predict better working memory. Cortical morphometric analyses were performed on high resolution T1‐weighted MPRAGE anatomical scans in 60 participants ages 6–18, from a previously published dataset (Wendelken et al., 2017). Cortical surface reconstructions were generated using Freesurfer. Sulci in lateral PFC were manually defined based on recently proposed definitions (Petrides & Pandya, 2012; Petrides, 2019), resulting in 2,157 labels (~18 labels per hemisphere, per subject). Mean sulcal depth was extracted for each sulcus. Relevant sulci for task performance were determined using a least absolute shrinkage and selection operator (LASSO) regression, fit separately for each hemisphere with each task condition using leave‐one‐out cross‐validation. Our analysis approach revealed four main findings. First, there is a relationship between PFC sulcal depth and Digit Span Backwards, but not Digit Span Forwards scores. Second, the depth of eight sulci (five in the left hemisphere and three in the right hemisphere) predict working memory manipulation. Third, while greater sulcal depth predicted better performance for six of these sulci, shallower sulcal depth predicted better performance for the other two sulci, which were restricted to the right hemisphere. Finally, these sulci are located around the contours of functionally‐defined DLPFC and VLPFC as proposed by Amiez and Petrides (2007). Taken together, these findings reveal that the depth of specific sulci in the lateral PFC can predict behavioral performance on a working memory manipulation task. Importantly, using a data‐driven approach we show that these sulci are also boundaries for functional regions known to be engaged in working memory manipulation. These results begin to shed light on the complex relationship between sulcal morphology in lateral PFC, functional parcellations of lateral PFC, and the development of working memory skills in children.

Evaluating flood resilience in rural communities: a case-based assessment of Dyer County, Tennessee

Communities everywhere are being subjected to a variety of natural hazard events that can result in significant disruption to critical functions. As a result, community resilience assessment in these locations is gaining popularity as a means to help better prepare for, respond to, and recover from potentially disruptive events. The objective of this study was to identify key vulnerabilities relevant to addressing rural community resilience through conducting an initial flood impact analysis, with a specific focus on emergency response and transportation network accessibility. It included a use case involving the flooding of a rural community along the US inland waterway system. Special consideration was given to impacts experienced by at-risk populations (e.g., low economic status, youth, and elderly), given their unique vulnerabilities. An important backdrop to this work is recognition that Federal Emergency Management Agency’s Hazus, a free, publicly available tool, is commonly recommended by the agency for counties, particularly those with limited resources (i.e., rural areas), to use in developing their hazard mitigation plans. The case study results, however, demonstrate that Hazus, as currently utilized, has some serious deficiencies in that it: (1) likely underestimates the flood extent boundaries for study regions in a Level 1 analysis (which solely relies upon filling digital elevation models with precipitation), (2) may be incorrectly predicting the number and location of damaged buildings due to its reliance on out-of-date census data and the assumption that buildings are evenly distributed within a census block, and (3) is incomplete in its reporting of the accessibility of socially vulnerable populations and response capabilities of essential facilities. Therefore, if counties base their flood emergency response plans solely on Hazus results, they are likely to be underprepared for future flood events of significant magnitude. An approach in which Hazus results can be augmented with additional data and analyses is proposed to provide a more risk-informed assessment of community-level flood resilience.

Inhomogeneous Image Segmentation Using Hybrid Active Contours Model With Application to Breast Tumor Detection

The most fatal and frequent cancer amongst women is breast cancer. Mammography provides timely detection of lumps and masses in breast tissue, but effective diagnosis requires accurately identifying malignant tumor boundaries, which remains challenging, particularly for images with inhomogeneous regions. Therefore, we propose an active contour method based on a reformed combined local and global fitted function to address breast tumor segmentation. This combined function is strengthened by a proposed average energy driving function to capture obscure boundaries for regions of interest more precisely from inhomogeneous images. Including a p-Laplace term eliminates reinitialization requirements and suppresses false contours in the segmentation. Bias field signal, which causes image homogeneity corruption, is estimated by bias field initialization to ensure independence from the initial contour position. Local and global fitted models are incorporated by introducing bias fields within them. The proposed method was tested on the MIAS MiniMammographic Database, with quantitative analysis to calculate its accuracy, effectiveness, and efficiency. Experimentation confirmed the proposed method provided superior results compared with previous state-of-the-art methods.

In Situ Macroscopic Tensile Testing in SEM and Electron Channeling Contrast Imaging: Pencil Glide Evidenced in a Bulk β-Ti21S Polycrystal

In this paper, we report the successful combination of macroscopic uniaxial tensile testing of bulk specimen combined with In situ dislocation-scale observations of the evolution of deformation microstructures during loading at several stress states. The dislocation-scale observations were performed by Accurate Electron Channeling Contrast Imaging in order to follow the defects evolution and their interactions with grain boundaries for several regions of interest during macroscopic loading. With this novel in situ procedure, the slip systems governing the deformation in polycrystalline bulk β-Ti21S are tracked during the macroscopic uniaxial tensile test. For instance, curved slip lines that are associated with “pencil glide” phenomenon and tangled dislocation networks are evidenced.

Extremal properties of conditional entropy and quantum discord for XXZ, symmetric quantum states

For the XXZ subclass of symmetric two-qubit X states, we study the behavior of quantum conditional entropy $$S_{cond}$$ as a function of measurement angle $$\theta \in [0,\pi /2]$$ . Numerical calculations show that the function $$S_{cond}(\theta )$$ for X states can have at most one local extremum in the open interval from zero to $$\pi /2$$ (unimodality property). If the extremum is a minimum, the quantum discord displays region with variable (state-dependent) optimal measurement angle $$\theta ^*$$ . Such $$\theta $$ -regions (phases, fractions) are very tiny in the space of X-state parameters. We also discover the cases when the conditional entropy has a local maximum inside the interval $$(0,\pi /2)$$ . It is remarkable that the maxima exist in surprisingly wide regions, and the boundaries for such regions are defined by the same bifurcation conditions as for those with a minimum.

Возбуждение конвекции в слоях жидкости и насыщенной пористой среды в модулированном поле силы тяжести

The effect of periodic modulation of gravitational acceleration on convection excitation in a two-layer system that is heated from below and consists of a horizontal pure fluid layer and a homogeneous porous medium saturated with the same fluid is investigated. The linear stability problem for mechanical equilibrium of fluid in the layers is solved numerically by the Galerkin method and the shooting method. A rectangular modulation of gravitational acceleration is established. Boundaries for resonance regions of equilibrium instability with respect to perturbations of synchronous and subharmonic responses of the system to periodic vibrational actions are demined as modulation amplitude and frequency change for various critical perturbation wavelengths. A boundary of the main instability region with respect to synchronous perturbations is found. It is shown that the modulation amplitude corresponding to the threshold of convection excitation strongly depends on perturbation wavelength. Perturbations of shorter wavelength (short-wave perturbations) localized in the fluid layer are more susceptible to the gravity modulation effect than perturbations of larger wavelength (long-wave perturbations) penetrating the porous layer. The occurrence of narrow resonance stability regions as heat intensity increases for short-wave perturbations is much earlier than for long-wave perturbations.Received 22.10.2016; accepted 03.11.2016

On Oenological Authenticity: Making Wine Real and Making Real Wine

On Oenological Authenticity: Making Wine Real and Making Real Wine

An Approach for Fuzzy Modeling based on Self-Organizing Feature Maps Neural Network

Exploration of large and high-dimensional data sets is one of the main problems in data analysis. Self-organizing feature maps (SOFM) is a powerful technique for clustering analysis and data mining. Competitive learning in the SOFM training process focuses on finding a neuron that its weight vector is most similar to that of a n input vector. SOFM can be used to map large data sets to a simpler, usually one or two-dimensional topological structure. In this pa per, we present a new approach to acquisition of initial fuzzy rules using SOFM learning algorithm, not only for its vector feature, but also for its topological. In general, fuzzy modeling requires two stages: structure identification and parameter learning. First, the algor ithm partitions the input space into some local regions by using SOFM, then it determines the decision boundaries for local input regions, and finally, based on the decision boundaries, it learns the fuzzy rule for each local region by recursive least squares algo rithm. The simulation results show that the proposed method can provide good model structure for fuzzy modeling and has high computing efficiency.

Cournot equilibria in a model of a two-hub homogeneous commodity market

The article considers existence and uniqueness of Cournot equilibria in a model of a two-hub homogeneous commodity market with affine demand functions. Explicit boundaries for the existence regions of Cournot equilibria of all possible types are derived in the case when identical firms with constant marginal costs exist in each hub (i.e., symmetrical oligopoly). Ignoring commodity losses during transfers between hubs, we reduce the number of model input parameters to two and generate a phase-plane description of the coexistence region of two Cournot equilibria and the region where no equilibria exist.

‘Eco-civic’ optimisation: A nested framework for planning and managing landscapes

An important institution for regional resource governance is civic engagement in local affairs, including resource use issues. Local civic engagement has traditionally been structured around local government and, more recently, to catchment-based decision-making bodies. If citizens are to participate in regional resource management in ways that are meaningful to them, it is important that both the landscape units being discussed and the jurisdictional boundaries are meaningful. We have been examining how boundaries for resource management regions might be identified. Three considerations are believed to be important if regional resource management is to be meaningful to the citizens involved. Firstly, that the regional boundaries maximise the areal proportion of the region that residents consider to be part of their ‘community’, which should lead to greater commitment to civic engagement in resource management. Secondly, that the character of the landscape units within the region possess a high degree of homogeneity, reflecting greater coincidence of interest among the inhabitants of the region. The third consideration is a hierarchical multi-scaling capacity to deal with externalities of resource use. The approach was tested through identification of a series of nested ‘eco-civic’ resource management regions for north-eastern New South Wales in Australia. The results delineate resource governance regions that nest at local to regional scales for integrated natural resource management. Such ‘eco-civic’ regions demonstrate a better spatial representation of social and ecological characteristics than existing regional frameworks.

Nonlinear system modeling by competitive learning and adaptive fuzzy inference system

Modeling nonlinear systems by neural networks and fuzzy systems encounters problems such as the conflict between overfitting and good generalization and low reliability, which requires a great number of fuzzy rules or neural nodes and uses very complicated learning algorithms. A new adaptive fuzzy inference system, combined with a learning algorithm, is proposed to cope with these problems. First, the algorithm partitions the input space into some local regions by competitive learning, then it determines the decision boundaries for local input regions, and finally, based on the decision boundaries, it learns the fuzzy rule for each local region by recursive least squares (RLS). In the learning algorithm, the key role of the decision boundaries is highly emphasized. To demonstrate the validity of the proposed learning approach and the new adaptive fuzzy inference system, four examples are studied by the proposed method and compared with the previous results.

Identification of specificity‐determining residues in antibodies

The successful identification of the residues that contact ligand has important implications, especially in view of the increasing use of antibodies in various medical and industrial applications. Analysis of the crystallographically derived, three-dimensional structures of five antibody-antigen complexes and of the available amino acid sequence data on antibody variable regions reveals that the residues that contact antigen are in the main also the most variable. It is proposed that a good first guess of the identity of the specificity-determining residues can be made from an examination of the variability values at sequence positions. New boundaries for the complementarity-determining regions are proposed.

Phenomenological trends for heavy Fermi liquids and narrow-band metals.

A phenomenological correlation is presented for the magnetic susceptibility ${\ensuremath{\chi}}^{\mathrm{*}}$ and the electronic heat-capacity coefficient ${\ensuremath{\gamma}}^{\mathrm{*}}$ of a large number of narrow-band and heavy-fermion metals. A novel method of plotting ${\ensuremath{\chi}}^{\mathrm{*}}$/${\ensuremath{\gamma}}^{\mathrm{*}}$ vs ${\ensuremath{\gamma}}^{\mathrm{*}}$ reveals quantitative boundaries for distinct regions of superconducting, magnetically ordered, and paramagnetic ground states. It is suggested that magnetic interactions are a primary limitation for the ${T}_{c}$ of ``conventional'' superconductors, whereas a more delicate interplay exists between magnetic order, paramagnetism, and superconductivity above a threshold value of ${\ensuremath{\gamma}}^{\mathrm{*}}$ which defines the onset of magnetic order.

Phase Boundaries of Microemulsion Systems as a Way of Characterizing Hydrocarbon Mixtures

Abstract Phase behavior of microemulsions composed of TRS 10-80, brine (10.6 mg/g NaCl), isopropyl alcohol, and mixtures of pure hydrocarbons was studied to determine the location of phase boundaries of the single-phase microemulsion region. Studies were conducted on pseudoternary phase diagrams where the pseudocomponents were isopropanol, brine, and a constant ratio of surfactant to hydrocarbon (S/H). Phase boundaries were determined by the titration method developed by Bowcott and Schulman,1 which was extended to systems of interest for oil recovery by Dominguez et al.2,3 The titration method involves the addition of brine to a single-phase microemulsion until phase separation occurs. Then the system is titrated to transparency by addition of isopropanol. Dominguez et al.2,3 demonstrated the applicability of the titration method for systems containing pure alkanes. They found upper and lower phase boundaries (high and low alcohol concentrations) for the microemulsion regions on S/H pseudoternary diagrams that were represented by linear relationships between the volume of alcohol and the volume of brine required to attain a single-phase microemulsion. This region, termed Region 4, bounded by linear phase boundaries, extends over a wide range of brine concentrations including regions of interest to enhanced oil-recovery processes. The research reported in this paper extends the work of Dominguez et al.2,3 to mixtures of pure hydrocarbons. The locations of the lower phase boundaries for Region 4 were determined for four types of mixtures prepared with pure hydrocarbons ranging from C6 to C18. In all phase behavior experiments, the lower phase boundary of Region 4 was a straight line when volume of alcohol was plotted against volume of brine. Furthermore, the slope of this phase boundary was found to be a linear function of alkane carbon number (ACN) for pure hydrocarbons and equivalent alkane carbon number (EACN) for mixtures of pure hydrocarbons. The correlation of a property of the phase diagram (the slope of the lower phase boundary) with EACN suggests a new approach to characterization of hydrocarbon/surfactant systems. In our experience, the EACN determined from phase behavior studies is more reproducible than the EACN determined from methods involving measurements of interfacial tensions. This method has potential for characterization of surfactant/hydrocarbon systems for complex mixtures of hydrocarbons, including crude oils.

Techniques for defining geographic boundaries for health regions

Many federal and state programs require the geographic partitioning of states into regions for health services planning, monitoring, and/or administration. A common consideration for such programs is that region boundaries should be drawn so as to maximize the proportion of the state's population that receives health care services in its region of residence. Defining region boundaries thus may be viewed as a problem of partitioning a set of N small areal units (e.g. counties) into M subsets (regions) so as to minimize interactions (patient flow) among subsets. This paper describes three algorithms for region design and compares them in terms of computer-processing efficiency and solution value based on results from a number of test cases. Application of two of the algorithms, one based on the greedy heuristic and the other incorporating a max-flow/min-cut procedure, to a problem of dividing a metropolitan region into separate service areas for clusters of hospitals is also described.