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Carp have dominated the Murray-Darling Basin since the s, and now make up per cent of the fish biomass in the river system.

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Space to play or pause, M to mute, left and right arrows to seek, up and down arrows for volume. While researchers are now confident infected fish won't pass on diseases directly to humans, there are growing concerns about how millions of dead fish could affect water quality. Concern about water health has seen critics of the plan emerging in the iconic Lower Lakes and Coorong region of SA, who believe releasing the virus into the Murray-Darling system is fraught with danger. Local fisherman Gary Hera-Singh, who lives at Meningie on Lake Albert, near the mouth of the River Murray, says the virus will be a shock to the basin's ecosystem.

Coorong fisherman Gary Hera-Singh is worried releasing a strain or herpes virus into the Murray Darling Basin will have unintended consequences. Mr Hera-Singh is worried about a potential "blackwater" event , which occurs when large populations of fish die, decompose and remove oxygen from waterways, killing other fish in a system. Coorong Mayor Neville Jaensch said the possibility of that happening frightens many in his community. However, Mr Barwick said it is impossible to give assurances to stakeholders that there will be no adverse outcomes. However, Mr Barwick defended that admission by saying leaving the carp in the river is equally — if not more — risky, as it will continue to put pressure on the system.


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To test the likelihood of a blackwater event caused by dead carp, earlier this year the NCCP dumped dead carp in a small wetland near Berri in South Australia, waited until they decomposed, and then assessed water quality. The trial, which involved filling a 2. Early estimates show there could be between , and 2 million tonnes of carp in the river system. The NCCP is currently trying to clarify that, then determine what percentage of that would be killed by the virus.

Coorong mayor Neville Jaensch says this is the biggest concern for communities downstream in the River Murray, or those who live near weirs where the river is blocked. More worrying for Mr Jaensch is that downstream communities like his are being considered as possible sites for the first release of the virus should the plan go ahead.

Fisherman Gary Hera-Singh said he is doubtful claims of native fish returning once the carp are destroyed will eventuate, because problems with the river go beyond just European carp. We have created a whole series of lakes, a series of gallon lakes from the top of the river all the way down," he said. Mr Barwick said the fact the Murray-Darling is made up a system of dams should be seen as an opportunity, as it means the virus can be released in phases in different sections, making it easier to contain.

Although much effort is focused on improving the technical performance of artificial intelligence, there are compelling reasons to focus more on the implementation of this technology class to solve real-world applications. Instead of viewing artificial intelligence development as a linear one of algorithm development through to eventual deployment, there are strong reasons to take a more agile approach, iteratively developing and testing artificial intelligence within the context in which it finally will be used. Background: Digital tools provide a unique opportunity to increase access to eye care.

We developed a Web-based test that measures visual acuity and both spherical and cylindrical refractive errors. The purpose of this study was to compare the efficacy of this Web-based tool with traditional subjective manifest refraction in a prospective open-label noninferiority clinical trial. Objective: The aim of this study was to evaluate the outcome of a Web-based refraction compared with a manifest refraction golden standard.

Review ARTICLE

Each participant performed the Web-based test, and the reference test was performed by an optometrist. Conclusions: Our results indicate that Web-based eye testing is a valid and safe method for measuring visual acuity and refractive error in healthy eyes, particularly for mild myopia. This tool can be used for screening purposes, and it is an easily accessible alternative to the subjective manifest refraction test. Clinical Trial: Clinicaltrials. Background: Patient online drug reviews are a resource for other patients seeking information about the practical benefits and drawbacks of drug therapies.

Patient reviews may also serve as a source of postmarketing safety data that are more user-friendly than regulatory databases. However, the reliability of online reviews has been questioned, because they do not undergo professional review and lack means of verification. Objective: We evaluated online reviews of hypnotic medications, because they are commonly used and their therapeutic efficacy is particularly amenable to patient self-evaluation. Our primary objective was to compare the types and frequencies of adverse events reported to the Food and Drug Administration Adverse Event Reporting System FAERS with analogous information in patient reviews on the consumer health website Drugs.

The secondary objectives were to describe patient reports of efficacy and adverse events and assess the influence of medication cost, effectiveness, and adverse events on user ratings of hypnotic medications. Methods: Patient ratings and narratives were retrieved from reviews on Drugs. Reviews were coded to preferred terms in the Medical Dictionary for Regulatory Activities. Results: Similar adverse events were reported to both Drugs. Both resources identified a lack of efficacy as a common complaint for all five drugs. Both resources revealed that amnesia commonly occurs with eszopiclone, zaleplon, and zolpidem, while nightmares commonly occur with suvorexant.

Compared to FAERS, online reviews of zolpidem reported a much higher frequency of amnesia and partial sleep activities. User ratings were highest for zolpidem and lowest for suvorexant. Statistical analyses showed that patient ratings are influenced by considerations of efficacy and adverse events, while drug cost is unimportant. Online reviewers rated drugs based on perception of efficacy and adverse events.

We conclude that online patient reviews of hypnotics are a valid source that can supplement traditional adverse event reporting systems. Background: The personalization of conversational agents with natural language user interfaces is seeing increasing use in health care applications, shaping the content, structure, or purpose of the dialogue between humans and conversational agents. Objective: The goal of this systematic review was to understand the ways in which personalization has been used with conversational agents in health care and characterize the methods of its implementation.

The studies were included if they: 1 were primary research studies that focused on consumers, caregivers, or health care professionals; 2 involved a conversational agent with an unconstrained natural language interface; 3 tested the system with human subjects; and 4 implemented personalization features. Results: The search found publications. After abstract and full-text screening, 13 studies were included in the review. Common examples of personalized content included feedback, daily health reports, alerts, warnings, and recommendations.

The personalization features were implemented without a theoretical framework of customization and with limited evaluation of its impact.

Journal of Medical Internet Research

While conversational agents with personalization features were reported to improve user satisfaction, user engagement and dialogue quality, the role of personalization in improving health outcomes was not assessed directly. Conclusions: Most of the studies in our review implemented the personalization features without theoretical or evidence-based support for them and did not leverage the recent developments in other domains of personalization. Future research could incorporate personalization as a distinct design factor with a more careful consideration of its impact on health outcomes and its implications on patient safety, privacy, and decision-making.

Background: Almost a decade ago, Sweden became the first country to implement a national system enabling student health care centers across all universities to routinely administer via email an electronic alcohol screening and brief intervention to their students. The original analyses adopted the conventional null hypothesis framework, and the results were consistently in the expected direction. However, since for some tests the P values did not pass the conventional.

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The aim of this paper was to reanalyze the two primary outcomes of the AMADEUS-1 trial AUDIT-C scores and prevalence of risky drinking , using the same models used in the original publication but applying a Bayesian inference framework and interpretation. Methods: The same regression models used in the original analysis were employed in this reanalysis linear and logistic regression.

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Model parameters were given uniform priors. Markov chain Monte Carlo was used for Bayesian inference, and posterior probabilities were calculated for prespecified thresholds of interest. Results: Where the null hypothesis tests showed inconclusive results, the Bayesian analysis showed that offering an intervention at baseline was preferable compared to offering nothing. Conclusions: The Bayesian analysis allows for a more consistent perspective of the data collected in the trial, since dichotomization of evidence is not looked for at some arbitrary threshold.

Results are presented that represent the data collected in the trial rather than trying to make conclusions about the existence of a population effect. Thus, policy makers can think about the value of keeping the national system without having to navigate the treacherous landscape of statistical significance.

Background: Although the availability and use of mobile mental health apps has grown exponentially in recent years, little data are available regarding their efficacy. Objective: This study aimed to evaluate the effectiveness of an app developed to promote stress management and well-being among working women compared with a control app.

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Methods: Female employees at a private hospital were invited to participate in the study via mailing lists and intranet ads. A total of individuals self-enrolled through the website.

The well-being mobile app provides an 8-week program with 4 classes per week including a brief theoretical portion and a min guided practice. The active control app also provided 4 assessments per week that encouraged participants to self-observe how they were feeling for 20 min. Both apps were fully automated without any human involvement. Outcomes from the control and intervention conditions at the 3 time points were analyzed using a repeated measures analysis of variance.

Conclusions: The well-being mobile app was effective in reducing employee stress and improving well-being. These studies seek to collect passive and active sensor signals from participants' smartphones for the purposes of modelling and predicting health outcomes, with a specific focus on mental health. We also highlight features of the current research landscape that recommend the coordinated development of such platforms, including the significant technical and resource costs of development, and we identify specific considerations relevant to the design of platforms for digital phenotyping.

In addition, we describe trade-offs relating to data quality and completeness versus the experience for patients and public users who consent to their devices being used to collect data. We summarize distinctive features of the resulting platform, InSTIL Intelligent Sensing to Inform and Learn , which includes universal ie, cross-platform support for both iOS and Android devices and privacy-preserving mechanisms which, by default, collect only anonymized participant data.

We conclude with a discussion of recommendations for future work arising from learning during the development of the platform. The development of the InSTIL platform is a key step towards our research vision of a population-scale, international, digital phenotyping bank. With suitable adoption, the platform will aggregate signals from large numbers of participants and large numbers of research studies to support modelling and machine learning analyses focused on the prediction of mental illness onset and disease trajectories. This field is now quickly expanding thanks to advances in neural interfaces, machine learning techniques, and robotics.

Despite many clinical successes, and multiple innovations in animal models, brain-machine interfaces remain mainly confined to sophisticated laboratory environments indicating a necessary step forward in the used technology. Interestingly, Elon Musk and Neuralink have recently presented a new brain-machine interface platform with thousands of channels, fast implantation, and advanced signal processing.

Here, how their work takes part in the context of the restoration of sensory-motor functions through neuroprostheses is commented.