#100+ minute sleep latency

[lost-estradiographer]

this is a fuckin mood. i have had a fuckin' existence lately.

i can’t believe i forgot to post this earlier

[jcmarchi]

Asynchronous LLM API Calls in Python: A Comprehensive Guide

New Post has been published on https://thedigitalinsider.com/asynchronous-llm-api-calls-in-python-a-comprehensive-guide/

Asynchronous LLM API Calls in Python: A Comprehensive Guide

As developers and dta scientists, we often find ourselves needing to interact with these powerful models through APIs. However, as our applications grow in complexity and scale, the need for efficient and performant API interactions becomes crucial. This is where asynchronous programming shines, allowing us to maximize throughput and minimize latency when working with LLM APIs.

In this comprehensive guide, we’ll explore the world of asynchronous LLM API calls in Python. We’ll cover everything from the basics of asynchronous programming to advanced techniques for handling complex workflows. By the end of this article, you’ll have a solid understanding of how to leverage asynchronous programming to supercharge your LLM-powered applications.

Before we dive into the specifics of async LLM API calls, let’s establish a solid foundation in asynchronous programming concepts.

Asynchronous programming allows multiple operations to be executed concurrently without blocking the main thread of execution. In Python, this is primarily achieved through the asyncio module, which provides a framework for writing concurrent code using coroutines, event loops, and futures.

Key concepts:

Coroutines: Functions defined with async def that can be paused and resumed.

Event Loop: The central execution mechanism that manages and runs asynchronous tasks.

Awaitables: Objects that can be used with the await keyword (coroutines, tasks, futures).

Here’s a simple example to illustrate these concepts:

import asyncio async def greet(name): await asyncio.sleep(1) # Simulate an I/O operation print(f"Hello, name!") async def main(): await asyncio.gather( greet("Alice"), greet("Bob"), greet("Charlie") ) asyncio.run(main())

In this example, we define an asynchronous function greet that simulates an I/O operation with asyncio.sleep(). The main function uses asyncio.gather() to run multiple greetings concurrently. Despite the sleep delay, all three greetings will be printed after approximately 1 second, demonstrating the power of asynchronous execution.

The Need for Async in LLM API Calls

When working with LLM APIs, we often encounter scenarios where we need to make multiple API calls, either in sequence or parallel. Traditional synchronous code can lead to significant performance bottlenecks, especially when dealing with high-latency operations like network requests to LLM services.

Consider a scenario where we need to generate summaries for 100 different articles using an LLM API. With a synchronous approach, each API call would block until it receives a response, potentially taking several minutes to complete all requests. An asynchronous approach, on the other hand, allows us to initiate multiple API calls concurrently, dramatically reducing the overall execution time.

Setting Up Your Environment

To get started with async LLM API calls, you’ll need to set up your Python environment with the necessary libraries. Here’s what you’ll need:

Python 3.7 or higher (for native asyncio support)

aiohttp: An asynchronous HTTP client library

openai: The official OpenAI Python client (if you’re using OpenAI’s GPT models)

langchain: A framework for building applications with LLMs (optional, but recommended for complex workflows)

You can install these dependencies using pip:

pip install aiohttp openai langchain <div class="relative flex flex-col rounded-lg">

Basic Async LLM API Calls with asyncio and aiohttp

Let’s start by making a simple asynchronous call to an LLM API using aiohttp. We’ll use OpenAI’s GPT-3.5 API as an example, but the concepts apply to other LLM APIs as well.

import asyncio import aiohttp from openai import AsyncOpenAI async def generate_text(prompt, client): response = await client.chat.completions.create( model="gpt-3.5-turbo", messages=["role": "user", "content": prompt] ) return response.choices[0].message.content async def main(): prompts = [ "Explain quantum computing in simple terms.", "Write a haiku about artificial intelligence.", "Describe the process of photosynthesis." ] async with AsyncOpenAI() as client: tasks = [generate_text(prompt, client) for prompt in prompts] results = await asyncio.gather(*tasks) for prompt, result in zip(prompts, results): print(f"Prompt: promptnResponse: resultn") asyncio.run(main())

In this example, we define an asynchronous function generate_text that makes a call to the OpenAI API using the AsyncOpenAI client. The main function creates multiple tasks for different prompts and uses asyncio.gather() to run them concurrently.

This approach allows us to send multiple requests to the LLM API simultaneously, significantly reducing the total time required to process all prompts.

Advanced Techniques: Batching and Concurrency Control

While the previous example demonstrates the basics of async LLM API calls, real-world applications often require more sophisticated approaches. Let’s explore two important techniques: batching requests and controlling concurrency.

Batching Requests: When dealing with a large number of prompts, it’s often more efficient to batch them into groups rather than sending individual requests for each prompt. This reduces the overhead of multiple API calls and can lead to better performance.

import asyncio from openai import AsyncOpenAI async def process_batch(batch, client): responses = await asyncio.gather(*[ client.chat.completions.create( model="gpt-3.5-turbo", messages=["role": "user", "content": prompt] ) for prompt in batch ]) return [response.choices[0].message.content for response in responses] async def main(): prompts = [f"Tell me a fact about number i" for i in range(100)] batch_size = 10 async with AsyncOpenAI() as client: results = [] for i in range(0, len(prompts), batch_size): batch = prompts[i:i+batch_size] batch_results = await process_batch(batch, client) results.extend(batch_results) for prompt, result in zip(prompts, results): print(f"Prompt: promptnResponse: resultn") asyncio.run(main())

Concurrency Control: While asynchronous programming allows for concurrent execution, it’s important to control the level of concurrency to avoid overwhelming the API server or exceeding rate limits. We can use asyncio.Semaphore for this purpose.

import asyncio from openai import AsyncOpenAI async def generate_text(prompt, client, semaphore): async with semaphore: response = await client.chat.completions.create( model="gpt-3.5-turbo", messages=["role": "user", "content": prompt] ) return response.choices[0].message.content async def main(): prompts = [f"Tell me a fact about number i" for i in range(100)] max_concurrent_requests = 5 semaphore = asyncio.Semaphore(max_concurrent_requests) async with AsyncOpenAI() as client: tasks = [generate_text(prompt, client, semaphore) for prompt in prompts] results = await asyncio.gather(*tasks) for prompt, result in zip(prompts, results): print(f"Prompt: promptnResponse: resultn") asyncio.run(main())

In this example, we use a semaphore to limit the number of concurrent requests to 5, ensuring we don’t overwhelm the API server.

Error Handling and Retries in Async LLM Calls

When working with external APIs, it’s crucial to implement robust error handling and retry mechanisms. Let’s enhance our code to handle common errors and implement exponential backoff for retries.

import asyncio import random from openai import AsyncOpenAI from tenacity import retry, stop_after_attempt, wait_exponential class APIError(Exception): pass @retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=4, max=10)) async def generate_text_with_retry(prompt, client): try: response = await client.chat.completions.create( model="gpt-3.5-turbo", messages=["role": "user", "content": prompt] ) return response.choices[0].message.content except Exception as e: print(f"Error occurred: e") raise APIError("Failed to generate text") async def process_prompt(prompt, client, semaphore): async with semaphore: try: result = await generate_text_with_retry(prompt, client) return prompt, result except APIError: return prompt, "Failed to generate response after multiple attempts." async def main(): prompts = [f"Tell me a fact about number i" for i in range(20)] max_concurrent_requests = 5 semaphore = asyncio.Semaphore(max_concurrent_requests) async with AsyncOpenAI() as client: tasks = [process_prompt(prompt, client, semaphore) for prompt in prompts] results = await asyncio.gather(*tasks) for prompt, result in results: print(f"Prompt: promptnResponse: resultn") asyncio.run(main())

This enhanced version includes:

A custom APIError exception for API-related errors.

A generate_text_with_retry function decorated with @retry from the tenacity library, implementing exponential backoff.

Error handling in the process_prompt function to catch and report failures.

Optimizing Performance: Streaming Responses

For long-form content generation, streaming responses can significantly improve the perceived performance of your application. Instead of waiting for the entire response, you can process and display chunks of text as they become available.

import asyncio from openai import AsyncOpenAI async def stream_text(prompt, client): stream = await client.chat.completions.create( model="gpt-3.5-turbo", messages=["role": "user", "content": prompt], stream=True ) full_response = "" async for chunk in stream: if chunk.choices[0].delta.content is not None: content = chunk.choices[0].delta.content full_response += content print(content, end='', flush=True) print("n") return full_response async def main(): prompt = "Write a short story about a time-traveling scientist." async with AsyncOpenAI() as client: result = await stream_text(prompt, client) print(f"Full response:nresult") asyncio.run(main())

This example demonstrates how to stream the response from the API, printing each chunk as it arrives. This approach is particularly useful for chat applications or any scenario where you want to provide real-time feedback to the user.

Building Async Workflows with LangChain

For more complex LLM-powered applications, the LangChain framework provides a high-level abstraction that simplifies the process of chaining multiple LLM calls and integrating other tools. Let’s look at an example of using LangChain with async capabilities:

This example shows how LangChain can be used to create more complex workflows with streaming and asynchronous execution. The AsyncCallbackManager and StreamingStdOutCallbackHandler enable real-time streaming of the generated content.

import asyncio from langchain.llms import OpenAI from langchain.prompts import PromptTemplate from langchain.chains import LLMChain from langchain.callbacks.manager import AsyncCallbackManager from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler async def generate_story(topic): llm = OpenAI(temperature=0.7, streaming=True, callback_manager=AsyncCallbackManager([StreamingStdOutCallbackHandler()])) prompt = PromptTemplate( input_variables=["topic"], template="Write a short story about topic." ) chain = LLMChain(llm=llm, prompt=prompt) return await chain.arun(topic=topic) async def main(): topics = ["a magical forest", "a futuristic city", "an underwater civilization"] tasks = [generate_story(topic) for topic in topics] stories = await asyncio.gather(*tasks) for topic, story in zip(topics, stories): print(f"nTopic: topicnStory: storyn'='*50n") asyncio.run(main())

Serving Async LLM Applications with FastAPI

To make your async LLM application available as a web service, FastAPI is an great choice due to its native support for asynchronous operations. Here’s an example of how to create a simple API endpoint for text generation:

from fastapi import FastAPI, BackgroundTasks from pydantic import BaseModel from openai import AsyncOpenAI app = FastAPI() client = AsyncOpenAI() class GenerationRequest(BaseModel): prompt: str class GenerationResponse(BaseModel): generated_text: str @app.post("/generate", response_model=GenerationResponse) async def generate_text(request: GenerationRequest, background_tasks: BackgroundTasks): response = await client.chat.completions.create( model="gpt-3.5-turbo", messages=["role": "user", "content": request.prompt] ) generated_text = response.choices[0].message.content # Simulate some post-processing in the background background_tasks.add_task(log_generation, request.prompt, generated_text) return GenerationResponse(generated_text=generated_text) async def log_generation(prompt: str, generated_text: str): # Simulate logging or additional processing await asyncio.sleep(2) print(f"Logged: Prompt 'prompt' generated text of length len(generated_text)") if __name__ == "__main__": import uvicorn uvicorn.run(app, host="0.0.0.0", port=8000)

This FastAPI application creates an endpoint /generate that accepts a prompt and returns generated text. It also demonstrates how to use background tasks for additional processing without blocking the response.

Best Practices and Common Pitfalls

As you work with async LLM APIs, keep these best practices in mind:

Use connection pooling: When making multiple requests, reuse connections to reduce overhead.

Implement proper error handling: Always account for network issues, API errors, and unexpected responses.

Respect rate limits: Use semaphores or other concurrency control mechanisms to avoid overwhelming the API.

Monitor and log: Implement comprehensive logging to track performance and identify issues.

Use streaming for long-form content: It improves user experience and allows for early processing of partial results.

[astrosblogs]

Super suave latest gadgets

Here’s our round-up of the latest gadgets that are a perfect addition to your shopping list

Audiophiles alert

Crescent is an elegant speaker, which also acts as an all-in-one sound system that compliments the interior of any room at home. Crescent supports wireless music streaming including Hi-Res options. The speaker also has Google Assistant built-in and connects via AirPlay, Chromecast, Spotify Connect, BT, Aux, and Optical input. cleeraudio.com

High impact gaming 

Benq’s TH690ST is a 1080p projector aimed squarely at gaming. The short-throw projector does take a bit of time to set up out of the box, but the results are worth it. Offering HDR 10 support and an LED light source rated at an excellent 2300 ANSI lumens with 3D support, images, and video are very good.

I was able to project a 100-inch image on my wall at a distance of about 5 feet. The low-latency gaming experience was smooth and exciting (connected via PS4). The in-built stereo speakers provide ample volume. A great option for avid gamers. amazon.in

Horological excellence

Panerai has launched the Luminor Due TuttoOro (PAM01326 and PAM01182) featuring a magnificent gold bracelet and dial. The 38mm case is ideal for most wrist sizes. The Due TuttoOro has a sun-brushed sandwich dial displaying hours, minutes, seconds and dates and is also water resistant up to 30m. The watch is powered by a P.900 automatic calibre providing extreme accuracy and three days of power reserve. panerai.com

New-gen wearables

Mivi’s Model E is an excellent smartwatch for the price. It sports an HD display (1.69”) and comes with 7+ days of battery life. Set up is easy and the watch syncs with the Mivi Health App seamlessly. The watch dial is bright and legible (500 nits) and works well in water and dusty environments as well (IP 68).

Metrics were reasonably accurate including SpO2, activity, and sleep tracking. Multi-sport mode pushes limits with compatibility with upto 120 sports activities. The watch is also available in six shades including a fantastic red option. flipkart.com

[antillonbukhari90]

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The Benefits of Using Wearable Technology for Health Tracking

You’re ready. To sit less, move more, sleep eight hours a night—to adopt new habits in order to become the healthiest you possible. As I shared recently, I recommend shrinking the change you want to make to set yourself up for success. Can wearable technology for health also help? Should you use these devices to aid you in achieving your wellness goals? Can tracking measures like your activity level, heart rate, and sleep really add up to big health gains?

Let’s explore some of the wearables currently on the market and discuss how making lifestyle shifts using the data they provide may mean you not only look and feel better today, but also avoid chronic disease down the road.

Do you use wearables to track your health? These devices can help you hit your wellness goals—when they’re tracking the right things. Check out this article for my recommendation on the best tech to track your sleep, stress, and activity levels. #healthylifestyle #chriskresser

What Are Wearables, and Do We Really Need More Technology?

Wearables are smart electronic devices that can be worn on the body to track a variety of health markers, such as:

Activity level: time spent sedentary, number of steps taken, etc.

Sleep patterns

Resting heart rate and heart rate variability

Stress level

Body temperature

A wide range of wearable health devices are available, from watches to rings—even shirts. I suspect we’ll see much more innovation in the coming years. After all, the industry is booming: analysts predict that more than 245 million devices will be purchased this year alone. Sales of smartwatches like the Apple Watch and products by Garmin, along with Fitbit’s watches and other fitness trackers, are on the rise, making these some of the most popular options today. (1)

And they do have merit. Although I often write about technology’s detrimental impact on health, these tech devices can support well-being.

They’re remarkable, really, in that they allow you to monitor wellness markers that not too long ago only doctors could track and measure. As a result, you gain important knowledge about your body that is vital to improving your health. What’s more, these devices take continuous, round-the-clock measurements, providing you with much more information than what you’ll get from annual trips to your physician, or even semi-regular visits to a healthcare practitioner. This wealth of data can also help your clinicians in making diagnoses and recommending treatments.

I see wearable health trackers as effective tools in your behavior-change toolkit. In this way, they integrate well into a Functional Medicine approach to healthcare. In Functional Medicine, we believe that for patients to overcome a persistent ailment, they must shift their behavior; we also know that behavior plays a major role in preventing—or contributing to—chronic disease.

Making the shift to an ancestral lifestyle that includes regular movement, quality sleep, and a focus on stress reduction—all trackable with today’s best wearables—is key to promoting general health and staving off chronic illness.

But Do Wearables Work? A Look at the Research

In some intervention studies, fitness trackers have a moderate effect on increasing step count and physical activity, leading to improved health outcomes for wearers.

Older patients who were given trackers increased their activity, lost weight, and had decreased LDL (“bad”) cholesterol levels after 12 to 14 weeks of use. (2)

Obese and overweight participants who wore trackers for 36 weeks and increased their step count lost weight and saw marked improvements in their body mass index (BMI), body fat percentage, waste and hip circumferences, and other body composition measures; they also saw a bump in their HDL (“good”) cholesterol. (3)

Overweight individuals who accumulated 10,000 steps per day over 12 weeks not only had lower body weight and BMI at the end of the study period than when they began, but they also experienced significant reductions in feelings of anxiety, depression, anger, fatigue, and confusion. (4)

However, the majority of the currently available research on activity trackers hasn’t concluded that they’re extraordinarily or overwhelmingly effective. In fact, some studies have found conflicting results to those mentioned above; in one, people wearing trackers lost less weight than those who used standard behavioral weight-loss approaches. (5)

All in all, the cumulative scientific results are mixed as to whether or not fitness trackers make people more fit. Even within studies, the results are often at odds and inconclusive. For instance, one study using the Fitbit generated tracker-damning headlines a couple of years ago. Yet, the results weren’t all bad: although wearers didn’t see improvements in weight or blood pressure, they did get more physical activity than non-wearers. (6) Another study published in 2018 found that the Fitbit increased wearers’ activity levels. But its authors noted that their research required participants to check in with a health coach (health coaches are extremely beneficial for behavior modification), and they suggested that it's possible being accountable to someone did more for increasing participants’ exercise levels than self-monitoring with the tracker. (7)

A grain of salt: The latter study brings up an important caveat to wearables research. Many previous studies were conducted with devices that are now several years old. They were essentially glorified pedometers without other meaningful function. They didn’t connect to your smartphone. They didn’t track sleep or measure heart rate variability (HRV)—more on those in a minute. They didn’t factor in practices that can be crucial for behavior change, like goal-setting or community support, as in the most recent study.

Fortunately, today’s wearables are much more sophisticated. The better ones address the points mentioned above and then some, and can track activity, heart rate variability, and sleep all in one device.

Regardless of what the studies show, you and I know that increasing physical activity and leading a less sedentary life—the aims of these trackers—are absolutely necessary for overall health and well-being and the prevention of chronic disease.

Why Wearable Technology for Health Tracking Needs to Include Sleep and HRV

It’s not enough for your device to simply count your steps; it should track other important health indicators, like your sleep quality and your heart rate variability (HRV).

Why Sleep Matters

Modern life is wrecking our sleep, with serious negative health consequences. Sleeping less than seven hours in a 24-hour period is associated with: (8)

Cardiovascular disease and diabetes risk

Depression

Learning and memory problems

An overall increase in mortality

Other research has shown that poor sleep can undo the benefits of a healthy diet and exercise. It’s the dealbreaker of all dealbreakers. (9)

What HRV Is, and Why It’s an Important Indicator to Track

HRV, which stands for “heart rate variability,” is a calculation of the time variation between each heartbeat. (It is not the same measurement as “heart rate,” which refers to the number of heart beats per second.) You may have heard about HRV in the context of assessing an athlete’s performance readiness. But it’s also useful in terms of evaluating stress in the human body. HRV involves measuring the function of the autonomic nervous system (ANS), part of the central nervous system that affects heart rate. To put it simply: if you’re stressed, you’ll have a low HRV; if you’re relaxed, a high HRV. (10)

No matter what diet you follow, what supplements you take, or how much exercise or sleep you get, if you don’t manage your stress, you’ll still be at risk for modern degenerative conditions like heart disease, diabetes, hypothyroidism, and autoimmunity. Low HRV specifically is tied to a host of chronic conditions, from chronic kidney disease to cardiovascular complications. (11, 12, 13)

My Recommendation: Find a Device That Tracks Everything

Of all the next-generation devices on the market that track a multitude of health indicators, I think the Oura smartring is the most effective, as it tracks your sleep, heart rate variability, body temperature, and activity level. I have one myself, and we use it extensively with patients at the California Center for Functional Medicine. (To my knowledge, it’s the only wearable with sleep-tracking technology that has been validated by a peer-reviewed study.) (14)

Each morning, the Oura ring displays a sleep score in its app. This is an overall calculation of how well you slept, which takes into account total sleep, efficiency, quality, disturbances, REM sleep, deep sleep, sleep latency, sleep timing, and your lowest resting heart rate during sleep. This data can be used to make changes that will lead to better slumber. For example, lowest resting heart rate measures the lowest 10-minute average heart rate you experience during the night. This ranges anywhere between 40 and 100 for adults, and you can determine your average by looking at your data history. If you are significantly high or low, it can signal an increased need for recovery from activity or that you are in an active stress response and may benefit from interventions like mind/body relaxation techniques or breathing exercises.

The Oura ring also tracks your body temperature, which plays a role in everything from fitness to ovulation and HRV. According to Oura’s creators, a ring—versus, say, a watch—can gather more accurate heart data because of its position on the finger.

If you do decide to try the Oura ring, enter the promo code KRESSER at checkout for $50 off.

My bottom line: All wearable devices will have pros and cons for you, and all can be helpful when used wisely. That’s the key. Wearables and the data they generate are only effective when truly put to use to change your behaviors.

To succeed in adopting new, healthier habits, I encourage you to combine wearable technology with the shrinking the change technique. For example, if your big objective is to get more regular physical activity, use a wearable to help break that change into smaller, more achievable goals. The right fitness tracker can nudge you to take breaks if you sit at your desk all day and stand, stretch, or move; to get in your daily steps; to schedule a regular run, bike ride, or other workout of your choice, etc. And it will record this physical activity in real time—daily data you can use to celebrate each incremental win, as you get closer and closer to your big objective.

It may seem ironic to use technology to create more balance in your life. But technology is just a tool, and it’s up to us how we employ it. I’m a big fan of using technologies like these to create harmony through healthy habits.

Do you use wearable technology for health tracking? Do you focus on your sleep, activity, or stress? What have you noticed about how these devices affect your habits? Comment below and let me know!

The post The Benefits of Using Wearable Technology for Health Tracking appeared first on Chris Kresser.

Source: http://chriskresser.com January 31, 2019 at 10:24PM

[brookszifz768]

The Very Best Child Monitors.

The Most Effective Baby Screens Of 2020.

Out of package, we located it simple to download the app to our cell phone, connect to the display and attach it to wifi, as well as obtain points up and running. A couple notes below - first, your wifi password requires to be shorter than 32 characters or the app will not accept it, and also 2nd, there is no way to manually set an IP address for the electronic camera. When we utilized it on our residence wifi network, we located that the images were clear and decently fast, and also the evening vision was top quality as well as not also grainy. We particularly liked the pan and also tilt features from the app, which allows you to move the camera's view angle around without going into the nursery (and it utilizes a cool screen-swipe motion to do it). Once we left our home's wifi connection and tried to connect to the electronic camera from a 4G LTE or a different wifi network, that's when we started to encounter problems. It was choppy and laggy, which to be honest is what we anticipated when attempting to stream 1080p HD video outside of your residence network.

Make use of the compatible mobile phone application to track your child's breathing, sound, motion, room temperature, and also moisture, plus obtain actual time signals that notify you to modifications in your infant's vitals and also baby room conditions. Every one of this details can be easily tracked by means of firmly saved summaries, charts, as well as video that you can download and install as well as share directly from your tool.

Various Other Child Video Clip Checks We Tested.

It's not inexpensive, being available in at around $160, yet offered its attributes and top quality, we are super delighted to display this child display near the top of our checklist! Out of the box, every little thing feels very excellent quality and very easy to construct as well as use. The battery charger cords are nice and long, the base unit's kick-stand style leg is tough, and the antenna is quickly folded out and also changed. Combine that incredible function established with truly excellent quality daytime and also evening vision video top quality, as well as you have actually obtained an absolutely stellar child screen that can compete head-to-head with any type of various other monitor on the market. Allow's discuss battery life, due to the fact that it's extremely remarkable. We were extremely pleased, as well as VAVA is additionally pleased with the reality that it consists of a super-capacity 4500mAh battery. They should boast of that, it's really outstanding battery life for a child monitor with such a huge display dimension!

After our lasting screening, the VAVA has just had some minor connection concerns, and the kick-stand broke on among the 3 systems we're examining. You can have a look at the incredible VAVA Child Display display here, and watch our extensive video clip evaluation of the VAVA Child Monitor below. From most inexpensive to most pricey this includes the iBaby Monitors M2, M2S, and M2 Plus, iBaby M6, M6T, as well as M6S, as well as the new iBaby M7. The M2 collection is usually under $100 and also is quite badly assessed overall.

Merely download and also mount the totally free Miku application on your Apple device or from Google Play store, and also plug in as well as activate the Miku electronic camera. Start up the Miku application and you'll be guided with a couple of simple steps to get the electronic camera connected to your wifi and also begin streaming on your smart phone. We examined the streaming on our home wifi as well as outdoors on a 4G link, and also both worked actually well. The 4G connection created a somewhat lower quality as well as higher latency video clip stream, yet definitely on-par with the other wifi monitors on our list.

Out of the box, everything feels extremely high quality and easy to assemble as well as utilize.

We obtained our hands on this baby screen for testing late last year, as well as we were really blown away by the high quality, battery life, range, screen size, and versatility of this infant screen.

It's not inexpensive, coming in at around $160, yet given its features as well as top quality, we are super delighted to showcase this baby screen near the top of our list!

Out of all the infant monitors on this listing, this set has the very best battery life.

Generally, we assume this is an excellent option for parents on a spending plan, as well as we'll upgrade this testimonial after longer-term screening! Seeking the versatility of a wifi baby display with the peace of mind of a baby breathing screen?

Budget friendly as well as dependable, the screen includes three lenses that enable individuals to pick a regular, broad or zoomed-in view. The display has a huge screen and user-friendly design that enables moms and dads to tilt as well as pan, adjust the volume, focus, as well as speak with the child utilizing the talk function. Users can set the display to time out after a couple of minutes to assist in saving the battery life, yet the quantity will continue to be on to ensure that parents can still hear their child.

Detractors claims VOX can wake them out of an audio sleep when the display turns on, also if there is simply some random noise. We should mention that the DXR-8 does have an audio-only night mode. but that suggests the sound is on constantly, not triggered by noise. With the Eufy Video Clip Baby Display, moms and dads can lastly quit scrunching up your eyes to find out whether their child has actually ultimately closed their https://dreamweaverspot.com/el-embarazo/salud-de-maternidad/mapeo-del-vientre/ eyes as well as gone to sleep. The displays' remarkable 5-inch LCD display and also sharp image give 10 times a lot more detail than the typical child display, making it very easy for parents to obtain a detailed and also clear look at their youngster.

In our screening, we really did not experience any type of problems with lag, bad video quality, connectivity, or anything else. If your net does go down however your home wifi network is still functioning, you will still be able to stream video clip in your area on your wifi network as long as you're still in your home as well as attached to wifi. One terrific feature about the Nanit is that every one of the sleep monitoring abilities are subscription-free, which means you will not have to pay for functions once a test duration finishes. We were truly pleased with the Miku and also assume it is very deserving of this spot on our listing! The only drawbacks right here are the truth that there are no remote zoom or pan/tilt features, and the price is truly high.

[tech-battery]

HP EliteBook x360 1030 G7 Convertible Review: A Spectre Dragonfly Hybrid

The EliteBook x360 1030 G7 is HP's latest high-end ultra-thin business subnotebook positioned to be above the more affordable EliteBook 830 or ProBook families. It is, in many ways, the gray version of the more visually ravishing HP Elite Dragonfly. Nonetheless, the EliteBook x360 1030 G7 introduces several changes both inside and out to make it better than both the outgoing EliteBook x360 1030 G4 and first generation Dragonfly.

SKUs are plentiful ranging from the 10th gen Core i5-10210U up to the Core i7-10810U CPU with vPro, FHD to 4K UHD AMOLED touchscreen, 8 GB to 32 GB of LPDDR4-2933 RAM, and up to 2 TB of storage with optional Optane 3D Xpoint. All configurations come with Comet Lake-U CPUs, Gorilla Glass, and integrated UHD Graphics 620. Our specific test unit is a mid-range SKU with the Core i7-10810U CPU, FHD display, and 16 GB of RAM for approximately $2400 USD.

Competitors to the EliteBook x360 1030 G7 include the Lenovo ThinkPad X13 Yoga, Dell XPS 13 2-in-1, Asus ZenBook S Flip, and other ultra-thin subnotebooks designed for office use.

Case

If you've held an EliteBook in the past, then you already have a good idea of how the EliteBook x360 1030 G7 looks and feels. HP's design philosophy for the EliteBook series hasn't changed for a sense of consistency between generations. The aluminum-magnesium skeleton may be getting smaller and lighter, but it still feels rigid with only a bit of flexing and creaking when twisting its sides. Larger and heavier business clamshells like the Dell Latitude 7400 feel sturdier.

The easiest way to distinguish the EliteBook x360 1030 G7 from the x360 1030 G4 is by looking at the rear corners and bottom "chin" bezel. HP has incorporated the "diamond-cut" visual design of the Spectre series while reducing the thickness of the bottom bezel even further to trim down overall volume.

The narrower bottom bezel has cut 11 mm off the length of the chassis. Consequently, the newer system is also lighter by about 100 grams (1.3 kg vs. 1.2 kg). The gen-to-gen changes may sound minor, but they're certainly tangible especially when traveling or on-the-go where every gram and millimeter counts. Note that thickness hasn't changed from the last generation model.

Connectivity

Port options and positioning are slightly different from the x360 1030 G4. HP has added a second USB-A port while the DriveLock port is now along the left edge. Note that there is still no SD card reader as HP is encouraging owners to use its QuickDrop software instead. QuickDrop allows a direct Wi-Fi connection between the PC and smartphone for much faster file transfers than Bluetooth, but users who rely on camera SD cards will still be out of luck.

Communication

Built-in wired and wireless communication modules, alternative solutions available (UMTS)?, Irregularities (radio reception)?

Security

This generation introduces HP Presence Aware on top of the usual fingerprint reader, webcam shutter, DriveLock, and HP Client security features. Presence Aware can detect when a user is nearby by up to a few feet in front of the laptop to automatically put the laptop to sleep if nobody is around. Conversely, it can also automatically login when combined with Windows Hello should it detect a nearby user. It is essentially HP's version of Dell ExpressSign-In as found on sound high-end Latitude systems albeit with a wider field-of-view in front of the laptop (60 degrees vs. 40 degrees)

Maintenance

The bottom panel is secured by six accessible T5 Torx screws for easy servicing. Though RAM and WLAN are soldered, the WWAN module and M.2 SSD are removable.

Accessories and Warranty

The packaging includes a USB-C to USB-A cable and an HP L04729-003 active pen. The pen attaches to the left edge of the laptop magnetically, but we prefer to just put it in our pocket as it feels much more secure that way.

A one-year limited warranty comes standard instead of the three-year timeframe that we've come to expect from high-end business systems.

Input Devices

Keyboard

Keyboard size and feedback remain the same as on the EliteBook x360 1030 G4 which is a good thing because we found the laptop to be more comfortable for typing than the softer keys on the Asus ZenBook Flip and most other Ultrabooks. Instead, the bigger changes relate to the secondary functions on the first row of keys. The video conferencing and calendar keys on the last generation model in particular have now been replaced with a camera shutter toggle, airplane mode toggle, and a customizable programmable key. Such functions are arguably more versatile.

Touchpad

Clickpad size has changed ever so slightly from the x360 1030 G4 (11.6 x 6.3 cm vs. 11.1 x 6.5 cm). Its surface is completely smooth and with almost no sticking even if gliding at very slow speeds in contrast to most other laptops. A little bit of sticking would have been preferable for more accurate dragging and dropping, but that is merely a personal taste.

Meanwhile, the integrated mouse clicks are relatively soft in both feedback and clatter with shallow travel overall. Stronger feedback would have made clicking easier and more ergonomic. We definitely miss the TrackPoint and dedicated mouse buttons on traditional business laptops like the EliteBook 840 G5, but we can understand their omission here on a convertible designed for touchscreen use.

Display

Our EliteBook x360 1030 G7 uses a Chi Mei panel as opposed to the InfoVision panel on the older EliteBook x360 1030 G4. However, HWiNFO is unable to identify the exact panel name here other than the Chi Mei CMN13A9 controller. Our specific configuration comes with the base 400-nit 1080p panel which is already better than most subnotebook displays in terms of contrast and sharpness. Response times remain somewhat slow for noticeable ghosting, though this isn't an issue for most office workloads

Color space covers >95 percent of sRGB while the pricier 4K UHD OLED configuration is expected to offer deeper colors covering all of AdobeRGB. We're just glad to not see any cheap panels even on the entry-level configurations.

X-Rite colorimeter measurements reveal a decently calibrated display out of the box. Gamma, however, could be better as it's unusually low. Calibrating the panel ourselves would improve colors and grayscale noticeably from average DeltaE values of 4.39 and 3.9 to 1.65 and 1.9, respectively.

Outdoor visibility is average due to the glossy Gorilla Glass overlay. Luckily, HP offers 1000-nit display options which should improve visibility dramatically albeit at the cost of higher power consumption. All 1000-nit SKUs at the moment come with Sure View meaning you can't have one without the other. Business subnotebooks from Dell or Lenovo have yet to carry such options.

Performance

HP is sticking with the 10th gen Intel Comet Lake-U series at the moment due its support for vPro in contrast to the newer 11th gen Tiger Lake options. Users won't be seeing any Iris Plus or Iris Xe graphics options here as a result. It's too bad that there is no "EliteBook x360 1035" series with AMD options as that would have boosted graphics performance.

RAM is soldered meaning users must choose their configurations carefully. Our system was set to HP Optimized prior to running any performance benchmarks below.

Processor

CPU performance is faster than expected for short benchmarks while scores are a bit lower for longer benchmarks due to the short-lived Turbo Boost performance of the laptop. CineBench R20 xT, for example, is within 10 percent of the average Core i7-10810U in our database while shorter benchmarks like GeekBench or 7-Zip show favor our HP slightly more. Nonetheless, raw multi-thread performance is only slightly faster than the Core i7-1065G7 and even slower than the cheaper Ryzen 5 4500U in the HP ProBook x360 435 G7.

See our dedicated page on the Core i7-10810U for more technical information and benchmark comparisons.

System Performance

PCMark benchmarks are where we expect them to be relative to other Comet Lake-U systems. Core i7 Ice Lake and Tiger Lake systems like the XPS 13 and ZenBook Flip S are able to edge out the HP likely due to the faster RAM and integrated Iris GPUs.

We experienced no software or hardware issues during our time with the test unit. HP Presence Aware is enabled by default, but this can be easily toggled through the software.

DPC Latency

LatencyMon shows DPC latency issues when opening multiples tabs on our homepage. 4K UHD playback is otherwise smooth and with no dropped frames during our minute-long YouTube test.

Storage Devices

Our configuration comes equipped with the Samsung PM981a which is one of the fastest PCIe 3 NVMe SSDs available for consumers. Drives from Toshiba and Western Digital tend to be cheaper, but they are also slower as well.

See our table of HDDs and SSDs for more benchmark comparisons.

GPU Performance

Graphics performance is the same integrated UHD Graphics 620 that we've been familiar with for nearly half a decade. The GPU has become outdated especially in the face of newer Radeon RX or Iris Xe solutions, but this shouldn't be a huge issue for the target audience of light office users. HP has yet to offer higher graphics options for its EliteBook convertible subnotebooks.

Emissions

System Noise

The fans range from being silent at 28.1 dB(A) up to 31.3 dB(A) when running undemanding loads. Such low levels are essentially inaudible in a typical office or conference room. Higher loads equivalent to gaming will boost fan noise up to 35 or 37 dB(A) which is not uncommon on Ultrabooks with no dedicated graphics. Fan noise is slightly higher-pitched than we would like since the individual fans are so small in diameter.

Temperature

Surface temperatures are never uncomfortable as the hot spot is close to the rear where skin and hands are unlikely to touch. A specific area of the keyboard can become as warm as 37 C when running extreme loads compared to 43 C on the 2020 Lenovo ThinkPad X13 Yoga.

Stress Test

HP EliteBook subnotebooks typically can't maintain very high clock rates when under stress and our Prime95 stress test proves it. Clock rates and temperature would boost to 3.1 GHz and 100 C, respectively, for just the first few seconds before quickly dropping to the 2.0 to 2.1 GHz range in order to maintain a cooler core temperature of 76 C as shown by our screenshots below.

Running on batteries will impact CPU performance slightly. A 3DMark 11 test on battery power would return Physics and Graphics scores of 8173 and 1893 points, respectively, compared to 8534 and 1942 points when on mains.

Energy Management

Power Consumption

Idling on desktop demands between 1.5 W and 10 W depending on the power profile and brightness setting to be slightly more power efficient than than what we recorded on the older x360 1030 G4 model. We're able to record a temporary maximum draw of 68.9 W from the small (~8.8 x 5.3 x 2 cm) 65 W CA adapter when running Prime95 which is similar to many other Ultrabooks powered by Ice Lake or Comet Lake-U CPUs. Note that the Tiger Lake-powered Asus ZenBook Flip S is able to offer 150 percent faster GPU performance without necessarily drawing more power.

Battery Life

Though battery capacity hasn't really changed from the older Whiskey Lake-U-powered EliteBook x360 1030 G4, WLAN runtimes are still about an hour longer on the newer G7 model for a total runtime of almost 10.5 hours. Charging from empty to full capacity takes about 1.5 hours.

Verdict

The HP EliteBook x360 1030 G7 is a tough convertible to beat. It's got 4G LTE, proximity sensor, and 1000-nit panel options that most competing alternatives don't offer. Its long list of features is impressive considering the small form factor involved. When compared to the outgoing EliteBook x360 1030 G4, the G7 is a worthy step up.

The main drawbacks to the HP convertible are the limited graphics performance, spongy clickpad, and high starting price. Owners will be stuck with the outdated UHD Graphics 620 while the clickpad is nowhere near as easy to use as the touchpad on the EliteBook 845. Be prepared to pay close to $2000 USD or more even for the least expensive Core i5 configuration. We understand that processor performance has never been a key selling point for any EliteBook convertible, but the fact that a cheap Ryzen 5 4500U can outperform the best Comet Lake-U Core i7 option available on this $2000 system is hard to ignore.

Where will HP go from here? We predict that future models might make the jump to 16:10, incorporate eSIM, wireless charging, or upgrade to Thunderbolt 4 via Intel's 11th gen Core platform. But until then, this is easily one of our favorite 13.3-inch convertibles for both office and travel.

[avilalily94]

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How To Stop Premature Ejaculation Without Medicine

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Oura ring review + is it worth it?

Sharing my thoughts and full review of the Oura Ring. Pros, cons, sleep tracking, fit, and is it worth it?

If you see me out and about right now (jk, we don’t go anywhere) you’ll see me sporting some intense bling: my new Oura ring.

(Ok not really *bling* but it’s a giant ring!)

After hearing so many rave reviews about the Oura ring, I finally decided to give it a try. I’ve been listening to Superhuman on Audible, and Dave Asprey is a huge fan (and now investor) of the company, and Dr. Minkoff also said he loves his Oura ring when I interviewed him for the podcast. I decided to go for it and was so pumped when it arrived last week!

Oura ring review + is it worth it?

What is the Oura ring and how does it work?

The Oura ring measures blood volume and uses this info to calculate respiratory rate, heart rate, and heart rate variability

Time of day

Movement and

Body temperature

From here, it also collects data regarding sleep, including your heart rate variability, time in bed, time asleep, and the stages of sleep (deep sleep, light sleep, etc.).

The things that really convinced me to order the ring is that it can be an excellent tool for improving sleep and performance. It gives you a “readiness score” each morning depending on your sleep and how you recovered from the previous day’s activity. You can use this information to notice habits that affect how you recover and how you feel, and also know when it’s a good day to push yourself and when it’s a good time to scale back.

Here’s what the ordering process is like:

You order and pay for the ring, but before you receive the actual ring, you receive a sizing kit in the mail. The sizing kit recommends picking a sample plastic ring and wearing it for 24 hours before determining your size, since our fingers can swell during the day.

This part was a little tricky for me because my fingers are small. I wear a size 4.5 on my ring finger and the smallest size they offer is a 6. This one works even though it is a bit loose. Heads up: the Oura is large and in charge.

At the same time, it’s truly incredible that they packed this technology into a ring.

Here’s a full review of the Oura ring and what to expect:

Set-up: Setup was fairly easy. After selecting my size online, the actual ring arrived about 5 days later. Once you get the ring plugged in and the app set up on your phone, it’s very straightforward from here. I received the ring late afternoon and was excited to wear it to sleep and view my sleep stats.

App use: The app is incredible. It’s so easy to navigate and I was in nerd heaven with all of the data they provide. It’s really cool to see your heart rate variability while you’re sleeping. The app provides helpful tips based on your score (like why a certain number may be higher or lower than usual) and encourages you to alternate your workout intensities. (<— vs my apple watch which tells me to stop being lazy when I really need an off day.) For example, if my readiness score is low, it automatically sets a lower activity goal for that day, encouraging me to rest and recover.

Pros:

– Readiness score (0-100). The readiness score is based on how well you slept, how well you’ve been sleeping in general, your body temperature, resting heart rate, previous day activity, activity balance, and recovery index (how your heart rate stabilizes throughout the night). When you click the readiness score, you can get detailed information on each component plus applicable tips. I can already tell that this will significantly help with my personal workouts. On a day that I had a 94 readiness score, I was feeling awesome and hopped on the Peloton bike. I got my first 30-minute PR in a LONG time!! (When you’ve had the bike for 2+ years, it gets harder and harder to set new records.)

– Sleep tracking. When you click your sleep score for the day (0-100), you get detailed info on total sleep, efficiency, restfulness, REM sleep, deep sleep, latency and timing. Just like the readiness score, you can click to get more information on sleep stages and resting heart rate throughout the night. This has been insightful for me and also proved what I already knew to be true: I sleep like a rockstar when Tom is home and sleep like trash when he’s traveling.

– The app syncs with your Apple Watch health app. For example, if do a barre workout but am not wearing the ring, my watch will send the data to my Oura app and I still get credit. I think this is amazing because I don’t think I’ll wear my ring for super heavy lifting workouts.

– Battery life and charging. The battery lasts about a week and charges extremely fast.

– Temperature tracking. This is an interesting component that can play a part in detecting sickness. Also, for women, it can be helpful for those who are tracking their temperature for their menstrual cycles. I’ve been tracking my cycle for about 10 years now so I know the second I ovulate lol but still an interesting addition to the ring.

Cons:

– Size. TBH, I was disappointed when I pulled the ring out of the box because it’s so giant. I thought it would drive me bonkers, but after a day or so, I’m used to it. Also, the nice thing is that you don’t have to wear it all the time. They can collect more data if you do, but if you’re going out or dressed up, you can skip it. For now, it hasn’t been a problem to wear it 24/7.

– Step counter is off. I don’t find the step counter to be as accurate as my Apple watch, but that’s not really my purpose for owning an Oura ring.

– Price. At $299, it’s not a cheap fitness gadget. Do I think it’s worth the cost? It depends on your goals and budget. If you’re looking for a step counter and basic exercise tracker, I would go with a Fitbit or something similar. If you want to deep dive into your sleep and activity habits and make some changes, I highly recommend it.

– Data, but not as many recommendations. The data is only helpful if you know what to do with it. For example, if I have two giant glasses of wine before bed and my sleep rating is lower, I know that I need to stick to one glass and have it earlier in the evening. A heavy meal, too much screen time, and caffeine can all affect my sleep score, which in turn, affects my readiness score. You definitely have to pay attention to your day’s structure and see how it affects sleep, performance, and how you feel. The ring is there for guidance and information.

All in all, I’ve been extremely happy and in nerd heaven with the ring and all of the data. I feel like I’ve been smarter about my sleep and workouts, which was the goal.

Are you into wearable fitness gadgets? What’s your fave?

xo

Gina

Note: this post is not sponsored and the ring wasn’t gifted. Just wanted to share my thoughts and review if anyone is considering adding it to their collection. 

The post Oura ring review + is it worth it? appeared first on The Fitnessista.

Oura ring review + is it worth it? published first on https://olimpsportnutritionde.tumblr.com/

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WEDNSDAY 16:29- May 24 2017 Did I mention Mack became an adult? Either way, he is a very happy grown-up boy now and still loves his walks. Having spent a good month with him so far, here are some quick thoughts pertaining to the rb and how I feel about them as robots

Very cute, even from infancy

A few steps back were taken from the Ugobe PLEO, and I feel Innvo’s vision of PLEO is very different from what Ugobe wanted from the robot

Blatant software quirks were ignored. Glitches in PLEOPM are abhorrently common.

Sound is handled very poorly, both software noises and motor noise

Latency is weirdly distributed? As of yet I have found no correlation between the different lag times Mack suffers from, especially when using his NFC compatibility. The first rb I had before swapping had absolutely no NFC latency. Sometimes Mack has some, other times has none, and yet other times it can take a full minute before opening his mouth for the toy. This is ridiculous as there is no reason for the response time to be so long I imagine this is just poor resource management in “LifeOS”

Paint chips really fast

Aside from all the negatives I think PLEOrb really does do it’s job well as a ‘pet’ simulation. The sleep/wakeup times, different foods, and responsiveness really do their job well aside from the technical downfalls

The DNA differences are nice and I would go as far as to say necessary for something like this, but I haven’t seen much of a difference in behavior aside from the amount of walking PLEO likes to do when playing with these attributes. I will do more research in this respect and perhaps look within PLEOPM itself

“PLEO is in bad shape” occurs all the time regardless of how PLEO acts. Mack has been in “good shape” only once

Sound/voice recognition is really, really bad 

“scared of the dark” is cute but dumb and always should be patched

Quality control is seriously unacceptable

I know I just said a lot of very negative things about the PLEOrb but I really do enjoy Mack both as a companion and as a hackable robot. I love him with all my heart, but I think these are reasonable expectations to make of a commercial product and I don’t think PLEOrb always hits the mark.

Does this make PLEOrb a bad robot?

By no means. But I don’t think I could ever see myself paying the full 450-500 dollars for PLEO. By these standards I think they are overpriced. I will be buying a Sony AIBO for 500 dollars.I was lucky enough to receive my PLEO at a serious bargain and I think I paid more or less fair money for him (~280 USD).

Mind you that this is in fully working condition and with all working accessories.

In that respect I would 100% recommend getting a PLEO- but from the secondhand market. If you are seriously into the raising from a baby stuff the NIB PLEO is really the only way to go, which is completely A-OK, but keep in mind that PLEO has many problems.

Okay, I think this it. Reblogs seriously appreciated, feel free to add your own opinions about the PLEOrb, I’d really like to hear them

[ellymackay]

How Machine Learning Could Transform the Way We Diagnose Narcolepsy

How Machine Learning Could Transform the Way We Diagnose Narcolepsy See more on: www.ellymackay.com

Researchers at Virtual SLEEP 2020 explained machine learning’s potential in sleep medicine.

By Lisa Spear

Even under the care of a sleep medicine clinician, narcolepsy patients may have a long wait before receiving a correct diagnosis. Researchers think that machine learning and the use of neural network analysis could speed up the diagnostic process, and pave the way for more precise care.

“Within the next few years, sleep scoring by technician will be replaced by automatic deep learning networks that will automatically annotate the sleep study and the task of the technician or doctor will only be to verify the event,” sleep scientist Emmanuel Mignot, MD, director of the Stanford Center for Narcolepsy, said during a presentation.

During Virtual SLEEP 2020, Mignot and a panel of other experts spoke about the future of artificial intelligence and machine learning in sleep medicine.

The panel discussed how these tools could potentially improve treatment for countless patients, lead to the use of phenotyping for diagnosing obstructive sleep apnea, and speed up the diagnostic process for those who experience narcolepsy with cataplexy, also known as type 1 narcolepsy.

By using statistical methods to find features unique to narcolepsy type 1, including a short REM latency period, researchers can build machine learning systems to help diagnose the disorder, Mignot explained. In the future, he said, all narcolepsy type 1 cases will be able to be detected remotely, from the patient’s home, over the course of a few days.

“We believe that this will be applied soon, where you will be able to wear a simplified device that you will wear at home for an entire weekend. Then, maybe you will have a blood test, combined with a deep learning algorithm, and that will get a beautiful diagnosis for narcolepsy.”

[RELATED: Linking Narcolepsy to the Flu? Researchers Make Progress Identifying Molecular Mimicry]

During his presentation, Mignot spoke about how he and his Stanford team have been working on creating machine learning systems to pinpoint narcolepsy type 1 cases. According to work presented during SLEEP, his team has demonstrated that using deep learning with polysomnography (PSG) could help clinicians bypass the multiple sleep latency test (MSLT), while producing an accurate diagnosis.

The team created a score for a sample of PSG recordings to reflect how close the recordings are to narcolepsy type 1 patterns. “The model generalized remarkably and had a high predictability for diagnosing narcolepsy,” said Mignot, professor of psychiatry and behavioral science at Stanford University.

Machine learning, the researchers said, can analyze large swaths of data without human bias. By applying machine learning and analyzing the data further during nocturnal PSG in narcolepsy type 1, clinicians could raise the specificity of detecting different sleep stages and transitions, Mignot said.

Another advantage is the ability of machine learning to score very brief periods of time. Instead of the 30-second epoch, which is typically scored by a human technician, machine learning can score up to a 5-second window, said Mignot, who is leading a sleep analytics project called the Stanford Technology Analytics and Genomics of Sleep (STAGES).

“Similarly, also you can compare the performance of the machine learning network to each technician. What you can show, in fact, is that the machine learning routine is closer to the consensus of all technicians than any single technician. In summary, machine learning is doing better than any single technician at recognizing all the sleep stages,” Mignot explained. “It has a superior performance.”

[RELATED: How Does Cataplexy Change Over Time?]

While it is known that narcolepsy with cataplexy is caused by a hypocretin deficiency, measuring hypocretin requires a lumbar puncture, an invasive procedure that is unpleasant for patients and not commonly used as a sleep medicine diagnostic tool.

Typically, diagnosis instead involves an overnight stay for an in-lab p PSG, followed by a daytime MSLT. The MSLT measures excessive daytime sleepiness by asking patients to nap 4 to 5 times for 20 minutes every 2 hours during the day. During these naps, sleep latency and the presence of REM sleep are observed.

Unfortunately, the MSLT can produce both false positive and false negative results, says Mignot.

“The fact that the MSLT is not a perfect test for narcolepsy, and the fact that it takes quite awhile for the MSLT, PSG to be conducted, during the night and then during the day, led us to believe that there might be a better way to analyze the data of a patient with narcolepsy and maybe diagnose narcolepsy with only one night of sleep using machine learning,” Mignot said.

Another flaw in the current diagnostic process for detecting narcolepsy type 1 is using the observation of cataplexy as diagnostic criteria.

“The problem with cataplexy is that it is subjective, so it cannot be 100% certain as a predictor,”  Mignot said.

Cataplexy is also not present in all cases of hypocretin deficiency, said Nathaniel Watson, MD, MSc, director of the Harborview Sleep Clinic and co-director of the University of Washington Medicine Sleep Center in Seattle, during the Virtual SLEEP 2020 session.

Watson explained that machine learning systems “could save time and increase the probability of diagnosing patients in sleep clinics.”

Lisa Spear is associate editor of Sleep Review.

from Sleep Review https://www.sleepreviewmag.com/sleep-disorders/hypersomnias/narcolepsy/machine-learning-diagnose-narcolepsy/

from Elly Mackay - Feed https://www.ellymackay.com/2020/09/14/how-machine-learning-could-transform-the-way-we-diagnose-narcolepsy/

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but did you know it's also prescribed to treat premature ejaculation?. Sertraline is an antidepressant that's part of the selective serotonin reuptake. With a 50mg dose, the men's mean ejaculatory interval increased to 13.1 minutes.. The stop- start strategy is exactly what it sounds like-during sex, when.

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This drug is known for its high specificity and selectivity for the SERT [13] .. Relation between blood vitamin B12 levels with premature ejaculation: Case- control study. Some subtypes (5-HT1a) reduce ejaculatory latency, and other subtypes.

Over the past 20-30 years, the premature ejaculation (PE) treatment paradigm, reduce performance anxiety, and modify his maladaptive sexual scripts.. These drugs block axonal reuptake of serotonin from the synaptic cleft of central. administration of an SSRI, increased synaptic 5-HT levels are downregulated by .

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 · Premature (early) ejaculation-also referred to as rapid ejaculation-is the most common type of sexual dysfunction in men younger than 40 years. An occasional instance of premature ejaculation might not be cause for concern, but, if the problem occurs with more than 50% of attempted sexual relations, a dysfunctional pattern usually exists for.

An occasional instance of premature ejaculation might not be cause for. Topical anesthetics may reduce penile sensitivity and excitability and delay ejaculation.. the increased synaptic content of serotonin and norepinephrine at the level of.

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The inhibitory effect of serotonin on libido, ejaculation, and orgasm. premature ejaculation have marked high serum leptin levels compared to controls, been reported to reduce plasma leptin levels in rats [8] and it has been noted that leptin .

When serotonin is injected into some parts of the rat brain, it causes a delay in ejaculation. In other areas of the brain, it causes ejaculation to take place. Dopamine also plays a role in ejaculation, although its role has not been as thoroughly explored as that of serotonin.

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Hot Bath 90 Minutes Before Bed May Help Improve Sleep

Taking a very hot bath or shower (104 to 109 degrees Fahrenheit) around 90 minutes before bedtime can help you fall asleep more quickly and even improve your sleep quality, according to a new analysis of thousands of studies. As a comparison, the average hot tub is set around 100 to 102 degrees F.

Research has shown that around 35 percent of Americans don’t get the recommended minimum amount of sleep (7 hours) per night. Around 20 percent of Americans are affected by a sleep disorder.

For the analysis, biomedical engineers at The University of Texas at Austin analyzed 5,322 studies linking water-based passive body heating, or bathing and showering with warm/hot water, with improved sleep quality.

“When we looked through all known studies, we noticed significant disparities in terms of the approaches and findings,” said Shahab Haghayegh, a Ph.D. candidate in the Department of Biomedical Engineering and lead author on the paper.

“The only way to make an accurate determination of whether sleep can in fact be improved was to combine all the past data and look at it through a new lens.”

The research team explored the effects of water-based passive body heating on a number of sleep-related conditions: sleep onset latency  the length of time it takes to accomplish the transition from full wakefulness to sleep; total sleep time; sleep efficiency — the amount of time spent asleep relative to the total amount of time spent in bed intended for sleep; and subjective sleep quality.

The team discovered that the optimum temperature of between 104 and 109 degrees Fahrenheit improved overall sleep quality. When scheduled 1 to 2 hours before bedtime, it can also hasten the speed of falling asleep by an average of 10 minutes.

According to the study, the optimal timing of bathing is about 90 minutes before going to bed. This allows the core body temperature to cool down enough to sleep.

Warm baths and showers stimulate the body’s thermoregulatory system, causing a marked increase in the circulation of blood from the internal core of the body to the peripheral sites of the hands and feet, resulting in efficient removal of body heat and decline in body temperature.

Therefore, if baths are taken at the right biological time — 1-2 hours before bedtime — they will aid the natural circadian process and increase one’s chances of not only falling asleep quickly but also of experiencing better quality sleep.

The findings are published in the journal Sleep Medicine Reviews.

Source: University of Texas at Austin

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