Is the Oral Microbiome Important in HIV-Associated Inflammation?

Alterations in the gut microbiome during HIV infection have been implicated in chronic inflammation, but the role of the oral microbiome in this process is less clear. The article by M. K. Annavajhala, S. D. Khan, S. B. Sullivan, J. Shah, et al. (mSphere 5:e00798-19, 2020, https://doi.org/10.1128/mSphere.00798-19) investigated the relationship between oral and gut microbiome diversity and immune activation in patients with HIV on antiretroviral therapy. In this study, oral microbiome diversity was inversely associated with inflammatory markers such as soluble CD14 (sCD14), but surprisingly similar associations were not seen with gut microbiome diversity. Oral microbiome diversity was also associated with periodontitis in these patients. This study highlights the importance of continuing multisite examinations in studying the gastrointestinal tract microbiome and also stimulates important directions for future research defining the role of the oral-gut axis in HIV-associated inflammation

Feature-based time-series analysis

This work presents an introduction to feature-based time-series analysis. The time series as a data type is first described, along with an overview of the interdisciplinary time-series analysis literature. I then summarize the range of feature-based representations for time series that have been developed to aid interpretable insights into time-series structure. Particular emphasis is given to emerging research that facilitates wide comparison of feature-based representations that allow us to understand the properties of a time-series dataset that make it suited to a particular feature-based representation or analysis algorithm. The future of time-series analysis is likely to embrace approaches that exploit machine learning methods to partially automate human learning to aid understanding of the complex dynamical patterns in the time series we measure from the world.Comment: 28 pages, 9 figure

Protecting and Maintaining Silicon Valley’s Liquid Gold

Public sector leaders and decision makers in the California water industry have learned from previous severe drought conditions that to sustain water supplies during extremely dry seasons, there is a substantial need for behavioral changes associated with water conservation efforts among the businesses and residents of the community to maintain an adequate water supply. The intent of this study is to compare four California water agencies that have been designated as sustainable groundwater agencies (GSA), and determine what current programs and/or practices those agencies are using to meet the mandated requirements of the Sustainable Groundwater Management Act of 2014 (Act of 2014). Under the Act of 2014, GSAs have been given authority to enforce their GSA approved groundwater sustainability plan. This study goes on to examine some of the methods that are used by three other water districts, located outside of the state of California. This was done to determine best practices that have been implemented to address severe drought conditions, like the circumstances that Californians experienced from 2010 to 2016; a period when California experienced one of the worst droughts ever recorded in the state’s history (McCullough, 2015)

Low speed phaselock speed control system

A motor speed control system for an electronically commutated brushless dc motor is provided which includes a phaselock loop with bidirectional torque control for locking the frequency output of a high density encoder, responsive to actual speed conditions, to a reference frequency signal, corresponding to the desired speed. The system includes a phase comparator, which produces an output in accordance with the difference in phase between the reference and encoder frequency signals, and an integrator-digital-to-analog converter unit, which converts the comparator output into an analog error signal voltage. Compensation circuitry, including a biasing means, is provided to convert the analog error signal voltage to a bidirectional error signal voltage which is utilized by an absolute value amplifier, rotational decoder, power amplifier-commutators, and an arrangement of commutation circuitry

Automatic control of liquid cooling garment by cutaneous and external auditory meatus temperatures

An automatic control apparatus for a liquid cooling garment is described that is responsive to actual physiological needs during work and rest periods of a man clothed in the liquid cooling garment. Four skin temperature readings and a reading taken at the external portion of the auditory meatus are added and used in the control signal for a temperature control valve regulating inlet water temperature for the liquid cooling garment. The control apparatus comprises electronic circuits to which the temperatures are applied as control signals and an electro-pneumatic transducer attached to the control valve

Human Dimensions of Marine Fisheries: Using GIS to Illustrate Land-Sea Connections in the Northeast U.S. Herring, Clupea harengus, Fishery

Geographic Information Systems can help improve ocean literacy and inform our understanding of the human dimensions of marine resource use. This paper describes a pilot project where GIS is used to illustrate the connections between fish stocks and the social, cultural, and economic components of the fishery on land. This method of presenting and merging qualitative and quantitative data represents a new approach to assist fishery managers, participants, policy-makers, and other stakeholders in visualizing an often confusing and poorly understood web of interactions. The Atlantic herring fishery serves as a case study and maps from this pilot project are presented and methods reviewed

Highly comparative feature-based time-series classification

A highly comparative, feature-based approach to time series classification is introduced that uses an extensive database of algorithms to extract thousands of interpretable features from time series. These features are derived from across the scientific time-series analysis literature, and include summaries of time series in terms of their correlation structure, distribution, entropy, stationarity, scaling properties, and fits to a range of time-series models. After computing thousands of features for each time series in a training set, those that are most informative of the class structure are selected using greedy forward feature selection with a linear classifier. The resulting feature-based classifiers automatically learn the differences between classes using a reduced number of time-series properties, and circumvent the need to calculate distances between time series. Representing time series in this way results in orders of magnitude of dimensionality reduction, allowing the method to perform well on very large datasets containing long time series or time series of different lengths. For many of the datasets studied, classification performance exceeded that of conventional instance-based classifiers, including one nearest neighbor classifiers using Euclidean distances and dynamic time warping and, most importantly, the features selected provide an understanding of the properties of the dataset, insight that can guide further scientific investigation

Superheavy elements and an upper limit to the electric field strength

An upper limit to the electric field strength, such as that of the nonlinear electrodynamics of Born and Infeld, leads to dramatic differences in the energy eigenvalues and wave functions of atomic electrons bound to superheavy nuclei. For example, the 1s1/2 energy level joins the lower continuum at Z=215 instead of Z=174, the value obtained when Maxwell's equations are used to determine the electric field

If only it were true: the problem with the four conditionals

The traditional division of conditionals into four main types (zero, first, second, and third) has long been called into question. Unfortunately, the awareness that this description does not reflect conditional patterns in actual usage has not generally been reflected in EFL coursebooks. This article re-examines the arguments for a description of conditional patterns which reflects actual usage and uses corpus data to demonstrate the kind of patterns in frequent use. It then suggests two teaching approaches that may help teachers to tackle a variety of conditional patterns in the classroom