Digital Commons Network^™

Functional And Developmental Identification Of A Molecular Subtype Of Brain Serotonergic Neuron Specialized To Regulate Breathing Dynamics, Rachael D. Brust, Andrea E. Corcoran, George B. Richerson, Eugene Nattie, Susan M. Dymecki

Dartmouth Scholarship

Serotonergic neurons modulate behavioral and physiological responses from aggression and anxiety to breathing and thermoregulation. Disorders involving serotonin (5HT) dysregulation are commensurately heterogeneous and numerous. We hypothesized that this breadth in functionality derives in part from a developmentally determined substructure of distinct subtypes of 5HT neurons each specialized to modulate specific behaviors. By manipulating developmentally defined subgroups one by one chemogenetically, we find that the Egr2-Pet1 subgroup is specialized to drive increased ventilation in response to carbon dioxide elevation and acidosis. Furthermore, this subtype exhibits intrinsic chemosensitivity and modality-specific projections-increasing firing during hypercapnic acidosis and selectively projecting to respiratory chemosensory …

Distributed Owl El Reasoning: The Story So Far, Raghava Mutharaju, Pascal Hitzler, Prabhaker Mateti

Computer Science and Engineering Faculty Publications

Automated generation of axioms from streaming data, such as traffic and text, can result in very large ontologies that single machine reasoners cannot handle. Reasoning with large ontologies requires distributed solutions. Scalable reasoning techniques for RDFS, OWL Horst and OWL 2 RL now exist. For OWL 2 EL, several distributed reasoning approaches have been tried, but are all perceived to be inefficient. We analyze this perception. We analyze completion rule based distributed approaches, using different characteristics, such as dependency among the rules, implementation optimizations, how axioms and rules are distributed. We also present a distributed queue approach for the classification …

Don't Fear The Leaker: Thoughts On Bureaucracy And Ethical Whistleblowing, Glenn Harlan Reynolds

Scholarly Works

In this brief Essay, I argue that rather than trying to eliminate leaks entirely, which experience demonstrates is impossible, we should instead try to channel leaks so that they provide the maximum benefit to transparency while reducing risks to national security and other secrecy concerns. I also offer some preliminary suggestions about how to accomplish this goal.

Application Of Data Mining For Reverse Osmosis Process In Seawater Desalination, Jaewuk Koo, Yonghyun Shin, Sangho Lee, Juneseok Choi

International Conference on Hydroinformatics

Reverse osmosis (RO) membrane process has been considered a promising technology for water treatment and desalination. However, it is difficult to predict the performance of pilot- or full-scale RO systems because numerous factors are involved in RO performance, including variations in feed water (quantity, quality, temperature, etc), membrane fouling, and time-dependent changes (deteriorations). Accordingly, this study intended to develop a practical approach for the analysis of operation data in pilot-scale reverse osmosis (RO) processes. Novel techniques such as artificial neural network (ANN) and genetic programming (GP) technique were applied to correlate key operating parameters and RO permeability statistically. The ANN …

Deep Learning For Neuroimaging: A Validation Study, Sergey M. Plis, Devon R. Hjelm, Ruslan Salakhutdinov, Elena A. Allen, Henry J. Bockholt, Jeffrey D. Long, Hans J. Johnson, Jane S. Paulsen, Jessica A. Turner, Vince D. Calhoun

Neuroscience Institute Faculty Publications

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager’s toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building …

Identifying Latent Structures In Panel Data, Liangjun Su, Zhentao Shi, Peter C. B. Phillips

Research Collection School Of Economics

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized regression techniques. We focus on linear models where the slope parameters are heterogeneous across groups but homogenous within a group and the group membership is unknown. Two approaches are considered — penalized least squares (PLS) for models without endogenous regressors, and penalized GMM (PGMM) for models with endogeneity. In both cases we develop a new variant of Lasso called classifier-Lasso (C-Lasso) that serves to shrink individual coefficients to the unknown group-specific coefficients. C-Lasso achieves simultaneous classification and consistent estimation in a single …

Collaborative Online Multitask Learning, Guangxia Li, Steven C. H. Hoi, Kuiyu Chang, Wenting Liu, Ramesh Jain

Research Collection School Of Computing and Information Systems

We study the problem of online multitask learning for solving multiple related classification tasks in parallel, aiming at classifying every sequence of data received by each task accurately and efficiently. One practical example of online multitask learning is the micro-blog sentiment detection on a group of users, which classifies micro-blog posts generated by each user into emotional or non-emotional categories. This particular online learning task is challenging for a number of reasons. First of all, to meet the critical requirements of online applications, a highly efficient and scalable classification solution that can make immediate predictions with low learning cost is …

Better Physical Activity Classification Using Smartphone Acceleration Sensor, Muhammad Arif, Mohsin Bilal, Ahmed Kattan, Sheikh Iqbal Ahamed

Mathematics, Statistics and Computer Science Faculty Research and Publications

Obesity is becoming one of the serious problems for the health of worldwide population. Social interactions on mobile phones and computers via internet through social e-networks are one of the major causes of lack of physical activities. For the health specialist, it is important to track the record of physical activities of the obese or overweight patients to supervise weight loss control. In this study, acceleration sensor present in the smartphone is used to monitor the physical activity of the user. Physical activities including Walking, Jogging, Sitting, Standing, Walking upstairs and Walking downstairs are classified. Time domain features are extracted …

How To Deal With Published Maps In Your Collection, Katherine Rankin

Library Faculty Presentations

This program is aimed at archivists and other special collections staff who have published maps as opposed to manuscript maps as part of their collections but do not have much expertise in map librarianship. The program includes information on kinds of maps, the basic parts of a map including those found mainly on pre-19th century maps, how to store and preserve maps, why they should be cataloged, how cataloging rare maps differs from cataloging current maps, why maps should be classified with a standard classification system, how Library of Congress call numbers can be used to locate certain kinds of …

A Functional Framework For Improved Management Of Western North American Aspen (Populus Tremuloides Michx.), Paul C. Rogers, Simon M. Landhausser, Bradley D. Pinno, Ronald J. Ryel

Wildland Resources Faculty Publications

Quaking or trembling aspen (Populus tremuloides Michx.) forests occur in highly diverse setting across North America. However, management of distinct communities has long relied on a single aspen to-conifer successional model. We examine a variety of aspen dominated stand types in the western portion of its range as ecological systems; avoiding an exclusive focus on seral dynamics or single species management. We build a case for a large-scale functional aspen typology based on existing literature. Aspen functional types are defined as aspen communities that differ markedly in their physical and biological processes. The framework presented here describes two “functional types” …

Identification Of Biomarkers That Distinguish Chemical Contaminants Based On Gene Expression Profiles, Xiaomou Wei, Junmei Ai, Youping Deng, Xin Guan, David R. Johnson, Choo Y. Ang, Chaoyang Zhang, Edward J. Perkins

Faculty Publications

Background: High throughput transcriptomics profiles such as those generated using microarrays have been useful in identifying biomarkers for different classification and toxicity prediction purposes. Here, we investigated the use of microarrays to predict chemical toxicants and their possible mechanisms of action.

Results: In this study, in vitro cultures of primary rat hepatocytes were exposed to 105 chemicals and vehicle controls, representing 14 compound classes. We comprehensively compared various normalization of gene expression profiles, feature selection and classification algorithms for the classification of these 105 chemicals into14 compound classes. We found that normalization had little effect on the averaged …

Discovering Jewish Studies Collections In Academic Libraries: A Practical Guide, Izabella Taler

Publications and Research

The U.S. colleges and universities offering non-sectarian educational programs in Jewish Studies rely on the support of their academic libraries for research materials and library services. For college libraries which use Library of Congress Classification scheme, it is a common practice to integrate "studies" resources into their general library collections. Since Jewish Studies sources span a vast number of subjects within all major disciplines, shelving integration leads to the dispersion of all relevant sources and such dispersion in turn leads to a variety of problems for library professionals and library users. For collection development librarians the problems range from lack …

Online Feature Selection And Its Applications, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Rong Jin

Research Collection School Of Computing and Information Systems

Feature selection is an important technique for data mining. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficient and scalable machine learning algorithms for large-scale applications. Most existing studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of online feature selection (OFS) in …

A Preliminary Checklist, Classification, And Four New Country Records For The Elateridae (Coleoptera) Of Ecuador, María P. Aguirre-Tapiero, P. J. Johnson

Insecta Mundi

A checklist and classifi cation of the species of Elateridae reported from mainland Ecuador are given. Anchastus boulardi Chassain, Cardiorhinus apicalis Golbach, Physorhinus marginatus Candèze, and P. sexnotatus Steinheil are reported from Ecuador for the first time. The recorded elaterid fauna of Ecuador is now represented by 140 species, 38 genera, and 9 subfamilies, which are low taxon richness numbers when compared to those of neighboring countries.

Se les da una lista de verifi cación y clasifi cación de las especies de Elateridae reportados desde el Ecuador continental. Anchastus boulardi Chassain, Cardiorhinus apicalis Golbach, Physorhinus marginatus Candèze, y P. sexnotatus …

A Ga-Svm Hybrid Classifier For Multiclass Fault Identification Of Drivetrain Gearboxes, Dingguo Lu, Wei Qiao

Department of Electrical and Computer Engineering: Faculty Publications

This paper presents a genetic algorithm (GA)- support vector machine (SVM) hybrid classifier for multiclass fault identification of drivetrain gearboxes in variable-speed operational conditions. An adaptive feature extraction algorithm is employed to effectively extract the features of gearbox faults from the stator current signal of an AC machine connected to the gearbox. The multiclass GA-SVM classifier is used to identify the faults in the gearbox according to the fault features extracted. A GA is designed to find the optimal parameters of the SVM to obtain the best classification accuracy. The proposed hybrid classifier is validated on a gearbox connected with …

Measures Of Tactical Efficiency In Water Polo, James Graham, John Mayberry

College of the Pacific Faculty Articles

We present a notational analysis of offensive tactics commonly employed in elite men's water polo and address three questions related to this objective: which tactics are most effective?, which tactical performance indicators best classify the winning team?, and how accurate are predictive models based on these performance indicators? We define a new statistic, Efficiency Rating, which quantifies the importance of a tactic via a weighted average of direct and indirect goals generated by its use. By this measure, direct shot is the most efficient even strategy despite being employed far less frequently than centre or perimeter tactics. We address our …

Abc Analysis For Inventory Management: Bridging The Gap Between Research And Classroom, Handanhal Ravinder, Ram B. Misra

Department of Management Faculty Scholarship and Creative Works

ABC analysis is a well-established categorization technique based on the Pareto Principle for determining which items should get priority in the management of a company's inventory. In discussing this topic, today's operations management and supply chain textbooks focus on dollar volume as the sole criterion for performing the categorization. The authors argue that today's businesses and supply chains operate in a world where the ability to deliver the right products rapidly to very specific markets is key to survival. With suppliers, intermediaries, and customers all over the globe, and product lives decreasing rapidly, this focus on a single criterion is …

Separating Mangrove Species And Conditions Using Laboratory Hyperspectral Data: A Case Study Of A Degraded Mangrove Forest Of The Mexican Pacific, Chunhua Zhang, John M. Kovacs, Yali Liu, Francisco Flores-Verdugo, Francisco Flores-De-Santiago

ETSU Faculty Works

Given the scale and rate of mangrove loss globally, it is increasingly important to map and monitor mangrove forest health in a timely fashion. This study aims to identify the conditions of mangroves in a coastal lagoon south of the city of Mazatlán, Mexico, using proximal hyperspectral remote sensing techniques. The dominant mangrove species in this area includes the red (Rhizophora mangle), the black (Avicennia germinans) and the white (Laguncularia racemosa) mangrove. Moreover, large patches of poor condition black and red mangrove and healthy dwarf black mangrove are commonly found. Mangrove leaves were collected from this forest representing all of …

Implementation Of A National Casemix Classification And Funding Model Into Palliative Care In Australia, Kathy Eagar

Australian Health Services Research Institute

[extract] The starting point for the Australian western health care system New South Wales became a (penal) colony in 1788, followed progressively by the other Australian States. Australia didn't became a country until 1901.

Coronary Artery Bypass Grafts And Diagnosis Related Groups: Patient Classification And Hospital Reimbursement In 10 European Countries, James Gaughan, Conrad Kobel

Australian Health Services Research Institute

The prospective reimbursement of hospitals through the grouping of patients into a finite number of categories (Diagnosis Related Groups, DRGs), is common to many European countries. However, the specific categories used vary greatly across countries, using different characteristics to define group boundaries and thus those characteristics which result in different payments for treatment. In order to assist in the construction and modification of national DRG systems, this study analyses the DRG systems of 10 European countries.

Developing A Classification For Artificial Limb Services: Final Report, Robert Gordon, Michael Navakatikyan, Janette Green

Australian Health Services Research Institute

No abstract provided.

Decoding Individual Natural Scene Representations During Perception And Imagery, Matthew R. Johnson, Marcia K. Johnson

Department of Psychology: Faculty Publications

We used a multi-voxel classification analysis of functional magnetic resonance imaging (fMRI) data to determine to what extent item-specific information about complex natural scenes is represented in several category-selective areas of human extrastriate visual cortex during visual perception and visual mental imagery. Participants in the scanner either viewed or were instructed to visualize previously memorized natural scene exemplars, and the neuroimaging data were subsequently subjected to a multi-voxel pattern analysis (MVPA) using a support vector machine (SVM) classifier. We found that item-specific information was represented in multiple scene-selective areas: the occipital place area (OPA), parahippocampal place area (PPA), retrosplenial cortex …

Influences Of The Digest Classification System: What Can We Know?, Richard A. Danner

Faculty Scholarship

Robert C. Berring has called West Publishing Company’s American Digest System “the key aspect of the new form of legal literature” that West and other publishers developed in the last quarter of the nineteenth century. Berring argued that West’s digests provided practicing lawyers not only the means for locating precedential cases, but a “paradigm for thinking about the law itself” that influenced American lawyers until the development of online legal research systems in the 1970s. This article discusses questions raised by Berring’s scholarship, and examines the late nineteenth and early twentieth century legal environment in which the West digests were …

The Earliest Colubroid-Dominated Snake Fauna From Africa: Perspectives From The Late Oligocene Nsungwe Formation Of Southwestern Tanzania, Jacob A. Mccartney, Nancy J. Stevens, Patrick M. O'Connor

Biology

The extant snake fauna has its roots in faunal upheaval occurring across the Paleogene - Neogene transition. On northern continents, this turnover is well established by the late early Miocene. However, this transition is poorly documented on southern landmasses, particularly on continental Africa, where no late Paleogene terrestrial snake assemblages are documented south of the equator. Here we describe a newly discovered snake fauna from the Late Oligocene Nsungwe Formation in the Rukwa Rift Basin of Tanzania. The fauna is small but diverse with eight identifiable morphotypes, comprised of three booids and five colubroids. This fauna includes Rukwanyoka holmani gen. …

Identification Of Unknowns Within A Probabilistic System: The Diagnostic Value Of Attributes, D W. Goodall

Research outputs 2014 to 2021

Using a data base underpinned by probability considerations in which a variety of attributes, some of which may be quantitative, are recorded for a number of “operational taxonomic units” (OTUs), a key system is described by which an unnamed specimen may quickly be identified. The concept of “diagnostic power” is introduced, by which each attribute is evaluated in terms of its potential contribution to identifying the unnamed specimen. Besides coverage of different types of attributes and the introduction of “diagnostic power”, the system has the advantages of incorporating multiple values of an attribute for each OTU and offering short-cuts to …

Multiple Kernel Learning In The Primal For Multimodal Alzheimer's Disease Classification, Fayao Liu, Luping Zhou, Chunhua Shen, Jianping Yin

Faculty of Engineering and Information Sciences - Papers: Part A

To achieve effective and efficient detection of Alzheimer's disease (AD), many machine learning methods have been introduced into this realm. However, the general case of limited training samples, as well as different feature representations typically makes this problem challenging. In this work, we propose a novel multiple kernel learning framework to combine multi-modal features for AD classification, which is scalable and easy to implement. Contrary to the usual way of solving the problem in the dual, we look at the optimization from a new perspective. By conducting Fourier transform on the Gaussian kernel, we explicitly compute the mapping function, which …

Hep-2 Cell Image Classification With Multiple Linear Descriptors, Lingqiao Liu, Lei Wang

Faculty of Engineering and Information Sciences - Papers: Part A

The automatic classification of the HEp-2 cell stain patterns from indirect immunofluorescence images has attracted much attention recently. As an image classification problem, it can be well solved by the state-of-the-art bag-of-features (BoF) model as long as a suitable local descriptor is known. Unfortunately, for this special task, we have very limited knowledge of such a descriptor. In this paper, we explore the possibility of automatically learning the descriptor from the image data itself. Specifically, we assume that a local patch can be well described by a set of linear projections performed on its pixel values. Based on this assumption, …

Discriminative Sparse Inverse Covariance Matrix: Application In Brain Functional Network Classification, Luping Zhou, Lei Wang, Philip O. Ogunbona

Faculty of Engineering and Information Sciences - Papers: Part A

Recent studies show that mental disorders change the functional organization of the brain, which could be investigated via various imaging techniques. Analyzing such changes is becoming critical as it could provide new biomarkers for diagnosing and monitoring the progression of the diseases. Functional connectivity analysis studies the covary activity of neuronal populations in different brain regions. The sparse inverse covariance estimation (SICE), also known as graphical LASSO, is one of the most important tools for functional connectivity analysis, which estimates the interregional partial correlations of the brain. Although being increasingly used for predicting mental disorders, SICE is basically a generative …

Development Of An-Snap Version 4: Activity Based Funding Classification Workshop, Janette P. Green, Robert Gordon

Australian Health Services Research Institute

Project aims and objectives

- To develop a fully revised and contemporary version of the AN-SNAP classification suitable for implementing as a national sub-acute and non-acute ABF model

- To ensure that the revised classification is acceptable across the sub-acute sector including States and Territories

Qualification Of Taxable Entities And Treaty Protection, Anthony C. Infanti, Bernard Moens

Articles

This report was prepared for the 2014 International Congress of the International Fiscal Association. The general reporters for the Congress asked IFA branches around the world to prepare a report designed to provide information on how countries address (1) the question of when domestic and foreign entities are treated as transparent or taxable and (2) conflicts between different countries’ treatment of entities as transparent or taxable for treaty purposes. This report constitutes the IFA U.S.A. Branch’s submission to the general reporters.

The report is divided into two sections. The first section of the report provides a general description of how …