A zero-cost, real-time, Windows signal laboratory

This paper introduces a Windows-based signal capture, display, and waveform synthesis package called “Win-eLab”. The software is able to run on a conventional desktop or laptop with no additional hardware, and can perform real-time Fourier analysis on audio-frequency signals. This paper is intended as an introduction to Win-eLab, aimed at motivating further use of it in both teaching and self-directed learning contexts. The use of the software to familiarize students with the concept of “laboratory” instrumentation is discussed, as well as the usefulness of a simultaneous time-domain/frequency-domain display for understanding signals, particularly in signal processing and communications systems courses. It is anticipated that applications may extend beyond electrical & electronic engineering – for example, as an aid to understanding mechanical vibrations, acoustics, and in other discipline areas

Throughput and fairness of multiple TCP connections in wireless networks

TCP suffers from poor throughput performance in wireless networks. Furthermore, when multiple TCP connections compete at the base station, link errors and congestion lead to serious unfairness among the connections. Although the issue of TCP performance in wireless networks has attracted significant attention, most reports focus only on TCP throughput and assume that there is only a single connection in a congestion-free network. This paper studies the throughput and fairness of popular improvement mechanisms (the Snoop [8] and ELN [5]) and TCP variants with multiple TCP connections. Simulation results show that the improvement mechanisms under investigation are effective to improve TCP throughput in a wireless network. However, they cannot provide fairness among multiple TCP connections. From the studies presented, it is concluded that mechanisms to enhance TCP fairness are needed in wireless network

Maternal psychological distress in primary care and association with child behavioural outcomes at age three

Observational studies indicate children whose mothers have poor mental health are at increased risk of socio-emotional behavioural difficulties, but it is unknown whether these outcomes vary by the mothers’ mental health recognition and treatment status. To examine this question, we analysed linked longitudinal primary care and research data from 1078 women enrolled in the Born in Bradford cohort. A latent class analysis of treatment status and self-reported distress broadly categorised women as (a) not having a common mental disorder (CMD) that persisted through pregnancy and the first 2 years after delivery (N = 756, 70.1 %), (b) treated for CMD (N = 67, 6.2 %), or (c) untreated (N = 255, 23.7 %). Compared to children of mothers without CMD, 3-year-old children with mothers classified as having untreated CMD had higher standardised factor scores on the Strengths and Difficulties Questionnaire (d = 0.32), as did children with mothers classified as having treated CMD (d = 0.27). Results were only slightly attenuated in adjusted analyses. Children of mothers with CMD may be at risk for socio-emotional and behavioural difficulties. The development of effective treatments for CMD needs to be balanced by greater attempts to identify and treat women. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00787-015-0777-2) contains supplementary material, which is available to authorized users

Impairment of Gradual Muscle Adjustment during Wrist Circumduction in Parkinson's Disease

Purposeful movements are attained by gradually adjusted activity of opposite muscles, or synergists. This requires a motor system that adequately modulates initiation and inhibition of movement and selectively activates the appropriate muscles. In patients with Parkinson's disease (PD) initiation and inhibition of movements are impaired which may manifest itself in e.g. difficulty to start and stop walking. At single-joint level, impaired movement initiation is further accompanied by insufficient inhibition of antagonist muscle activity. As the motor symptoms in PD primarily result from cerebral dysfunction, quantitative investigation of gradually adjusted muscle activity during execution of purposeful movement is a first step to gain more insight in the link between impaired modulation of initiation and inhibition at the levels of (i) cerebrally coded task performance and (ii) final execution by the musculoskeletal system. To that end, the present study investigated changes in gradual adjustment of muscle synergists using a manipulandum that enabled standardized smooth movement by continuous wrist circumduction. Differences between PD patients (N = 15, off-medication) and healthy subjects (N = 16) concerning the relation between muscle activity and movement performance in these groups were assessed using kinematic and electromyographic (EMG) recordings. The variability in the extent to which a particular muscle was active during wrist circumduction – defined as muscle activity differentiation - was quantified by EMG. We demonstrated that more differentiated muscle activity indeed correlated positively with improved movement performance, i.e. higher movement speed and increased smoothness of movement. Additionally, patients employed a less differentiated muscle activity pattern than healthy subjects. These specific changes during wrist circumduction imply that patients have a decreased ability to gradually adjust muscles causing a decline in movement performance. We propose that less differentiated muscle use in PD patients reflects impaired control of modulated initiation and inhibition due to decreased ability to selectively and jointly activate muscles

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Targets of wnt/ß-catenin transcription in penile carcinoma

Penile squamous cell carcinoma (PeCa) is a rare malignancy and little is known regarding the molecular mechanisms involved in carcinogenesis of PeCa. The Wnt signaling pathway, with the transcription activator ß-catenin as a major transducer, is a key cellular pathway during development and in disease, particularly cancer. We have used PeCa tissue arrays and multi-fluorophore labelled, quantitative, immunohistochemistry to interrogate the expression of WNT4, a Wnt ligand, and three targets of Wnt-ß-catenin transcription activation, namely, MMP7, cyclinD1 (CD1) and c-MYC in 141 penile tissue cores from 101 unique samples. The expression of all Wnt signaling proteins tested was increased by 1.6 to 3 fold in PeCa samples compared to control tissue (normal or cancer adjacent) samples (p<0.01). Expression of all proteins, except CD1, showed a significant decrease in grade II compared to grade I tumors. High magnification, deconvolved confocal images were used to measure differences in co-localization between the four proteins. Significant (p<0.04-0.0001) differences were observed for various permutations of the combinations of proteins and state of the tissue (control, tumor grades I and II). Wnt signaling may play an important role in PeCa and proteins of the Wnt signaling network could be useful targets for diagnosis and prognostic stratification of disease