https://www.europesays.com/afrique/244482/ Éducation : Moov Africa-ONATEL investit 16,5 millions de FCFA dans l’excellence scolaire #actualités #Afrique #burkina #culture #direct #divertissement #Économie #IbrahimTraore #info #International #Monde #MondialFoot #Politique #reportages #securité #Société #sport #terrorisme #WorldCup
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Eu já contribuí para esta bela ferramenta de auxílio à aprendizagem, faltam vocês 😉 👍
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We just had to get our HEX on at Critical Hit Games in Cleveland Heights before their big move to the Coventry neighborhood staring this week! Each hex supports the move and the shop has supported the geeks of the Cleveland area for many years!
(Yes, we are aware we goofed at sketching our logo art; we do tell you we're "Confused" for a reason!)
*This post is not sponsored by Critical Hit. They are are a community asset and supportive of many geeky groups in the Cleveland area. They are also friends of the troupe and one of their founders had previously been a Player of the Patchwork!
#Theater #Improv #Improvisation #Commedia #CommediaDellArte #Mimic #DnD #DungeonsAndDragons #BoardGames #Gaming #CriticalHit #CriticalHitGames #ShopSmall #ClevelandHeights #Cleveland #CLE
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NFL fullbacks scarce but Broncos’ Adam Prentice presses on
At some point there might be a museum display, and behind glass it will read “fullback.” There was…
#NFL #DenverBroncos #Denver #Broncos #AdamPrentice #BrandonJones #Football #JaylenWaddle #JustinStrnad #RileyMoss #SeanPayton #TalanoaHufanga
https://www.rawchili.com/nfl/1035995/ -
RE: https://fosstodon.org/@dantleech/117501478686180059
TIL Packagist protects the vendor once a package exists - you need to be a maintainer on at least one published package with that vendor to publish more
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Most businesses know how to track their Google rankings.
But what happens when a potential customer stops searching on Google and starts asking ChatGPT, Perplexity, or another AI assistant which product they should choose?
Your website might rank well. Your content might get traffic. Your competitors might even have fewer backlinks than you.
Yet when a customer asks an AI assistant for recommendations, your competitors appear while your brand is nowhere to be found.
That creates a new visibility problem: which questions are you losing in AI search?
I'm building Aurvikon to help answer that question.
The problem with measuring AI visibility
Traditional SEO gives us familiar metrics:- Keyword rankings
- Impressions and clicks
- Organic traffic
- Backlinks
- Search performance
These metrics remain valuable. But they don't fully explain how your brand appears inside AI-generated answers.
Imagine someone asking an AI assistant:
- What are the best tools for improving AI search visibility?
- Which platforms help SaaS companies monitor their brand in AI answers?
- Compare three alternatives for tracking brand recommendations in AI search.
- Which tool should a startup use to understand its visibility in ChatGPT?
Your brand might appear in one answer and disappear from the next.
A competitor might be recommended repeatedly. Another company might be described as the category leader. Your own product might be missing entirely.
Looking at a single AI-generated answer won't tell you the whole story.
You need to understand visibility across the questions your potential customers actually ask.
The shift: from keyword rankings to question-level visibility
I'm interested in a more useful way to think about AI search visibility.Instead of asking only:
"Does my brand appear in AI search?"
Ask:
"For which relevant buyer questions does my brand appear, where do competitors appear instead, and what can I do about it?"
That second question leads to much more actionable work.
Consider three possible findings from an AI visibility audit:
1. You're missing from important questions.
People ask questions directly related to your product category, but the AI response doesn't mention your company.
2. Your competitors are being recommended instead.
Your product may be relevant, but competing brands are consistently appearing in the answers you're trying to win.
3. Your brand appears, but not in the way you want.
An AI response might mention your company without accurately communicating its core use case, differentiator, or value.
These are different problems. They shouldn't all receive the same recommendation to "publish more content."
What we're building with Aurvikon
Aurvikon is an AI visibility tool focused on helping businesses understand how their brands appear across AI answer platforms.The core idea is straightforward:
Identify the questions where your brand is losing visibility, understand what appears instead, and turn those findings into an action plan.
A practical workflow looks like this:
Step 1: Identify the questions buyers ask
Start with questions your target customers might ask before choosing a product.Don't limit the research to your brand name. Include category searches, comparisons, alternatives, use cases, and purchasing decisions.
Step 2: Test those questions across AI platforms
Run relevant questions across the platforms you want to monitor, such as ChatGPT, Perplexity, and Gemini.Treat the responses as observations to analyze, not as permanent rankings.
Step 3: Identify where you're losing
Look for patterns:- Which questions mention your brand?
- Which questions mention competitors but not you?
- Where are you missing from relevant comparisons?
- Which product capabilities or use cases aren't being communicated?
- Which questions deserve attention first?
This is where an audit becomes more useful than a collection of screenshots.
Step 4: Turn findings into actions
Every visibility gap should lead to a hypothesis.Maybe a product page doesn't explain a use case clearly. Maybe your comparison content is weak. Maybe your product lacks supporting content for a particular buyer question.
Investigate the evidence, make the relevant improvement, and test again.
The goal isn't to manufacture mentions. It's to make your brand easier to understand, evaluate, and recommend when it genuinely fits the user's needs.
The difficult part isn't generating an AI visibility report
AI answers change. Results can vary by wording, location, model version, and time.That means a report saying "your brand was mentioned" is only a starting point.
A useful system should help you move from observation to diagnosis:
Buyer question → AI response → competitor comparison → visibility gap → action → retest.
That repeatable workflow is the problem space we're focused on at Aurvikon.
We're especially interested in making the results useful to founders and marketing teams who need to decide what to fix next, rather than simply collecting another dashboard of numbers.
What this means for SaaS founders
If you're building a SaaS company, think about the questions someone would ask immediately before buying your product.Not just:
"What is [your brand]?"
But:
- What is the best alternative to [competitor]?
- Which tools solve [specific customer problem]?
- Compare products that offer [important capability].
- What should a small business use for [desired outcome]?
- Which platform is best for [specific use case]?
These questions reveal how AI assistants represent your category and which products they surface for potential buyers.
They can also reveal gaps in your positioning and content strategy.
AI visibility isn't a replacement for SEO. It's an additional area to measure as customers discover products through AI-generated answers.
I'm building Aurvikon around one practical question
I believe the most useful starting point for AI visibility isn't another generic score.It's knowing which valuable questions your company is losing, which competitors show up instead, and what you should investigate next.
That's the problem we're working on with Aurvikon.
I'd love to hear from other founders, SEO professionals, and SaaS marketers:
If you could see every important buyer question where AI assistants recommend your competitors instead of you, what would you want the tool to tell you first?
Would you prioritize the competing brands, the missing content, the sources behind the answers, or the specific actions most likely to improve visibility?
I'm interested in how people are approaching this problem in practice.#ai #seo #startup #showdev #software #coding #development #engineering #inclusive #community
Your Brand Can Rank on Google and Still Be Invisible in AI Search -
DATE: October 25, 2026 at 12:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: How the menstrual cycle might alter ADHD symptoms in women taking stimulant medication
URL: https://www.psypost.org/how-the-menstrual-cycle-alters-adhd-symptoms-in-women-taking-stimulants/
The menstrual cycle appears to modulate the severity of attention-deficit/hyperactivity disorder (ADHD) traits in women taking common stimulant medications. A new small study suggests that these traits peak in severity during menstruation and ease soon after, pointing toward a need for hormone-aware treatment plans. The research was published in the Journal of Attention Disorders.
ADHD is a neurodevelopmental condition characterized by distraction, impulsivity, and hyperactive behavior. Medical professionals historically viewed the condition as something that primarily affected young boys. That diagnostic gap is rapidly closing, and women now make up nearly half of the adult ADHD population in the United States. Women often present with different behavioral patterns than men, leaning toward severe inattention and internalizing behaviors rather than disruptive hyperactivity.
Despite facing daily impairments in their careers and social lives, women remain largely underrepresented in ADHD research. One distinct biological variable separating women from men is the constant fluctuation of ovarian hormones. During the follicular phase of the menstrual cycle, estrogen levels rise and peak near ovulation. The subsequent luteal phase features elevated estrogen and progesterone, which then drop rapidly shortly before menstruation begins.
Researchers suspect these hormones play a direct role in brain chemistry. Low estrogen levels are thought to decrease dopamine signaling in the brain. Because dopamine is the primary neurotransmitter involved in focus and attention, these natural hormonal drops could theoretically worsen ADHD symptoms.
Researchers Rebecca Zaritsky, Stephanie C. Reed, and Suzette M. Evans wanted to understand how these hormonal variations interact with ADHD treatments. Prior laboratory work demonstrated that amphetamines, the most commonly prescribed class of ADHD medications, can be less effective during the luteal phase of the cycle. Case reports from clinical settings also hinted that some women experience worsening moods and fading concentration right before their periods.
The research team designed a study to track these daily changes prospectively. The investigators recruited participants through online advertisements to monitor their daily experiences. They screened for individuals between the ages of 18 and 40 who experienced regular menstrual cycles lasting between 21 and 35 days.
To join the study, participants had to report an ADHD diagnosis and currently use amphetamine salts (commonly known by brand names like Adderall) for treatment on at least five days of the week. The team excluded anyone taking hormonal birth control, as well as individuals using other psychiatric medications. After exclusions and dropouts, the researchers ended up with a small study of 30 participants who completed the required long-term tracking.
Each individual filled out an initial survey detailing their medical history, baseline mood, and general impulsive behaviors. Following this baseline assessment, participants completed a daily online survey for 35 consecutive days. This extended timeline ensured the researchers could capture data from one full menstrual cycle for every participant.
The daily questionnaires asked participants to rate their current ADHD symptoms on a standardized four-point scale. They evaluated 18 distinct symptoms, splitting them equally between inattentive traits and hyperactive-impulsive traits. Participants also rated their daily mood variations on a six-point scale measuring 17 distinct emotional states, and reported their exact medication dosage for the day. Finally, they noted whether they were actively menstruating or spotting.
The researchers averaged the daily survey responses and grouped them into three specific biological windows. These windows included the first five days of menstruation, the mid-follicular phase shortly after bleeding ends, and the late luteal phase just before the next period begins. Participants reported their most severe ADHD symptoms during the active menstruation phase. In contrast, they experienced comparatively milder symptoms during the mid-follicular phase.
When researchers separated the specific types of ADHD traits, hyperactive and impulsive behaviors showed variation across the cycle phases, but after adjusting for multiple comparisons this amounted only to a trend rather than a statistically significant difference. Inattentive symptoms also fluctuated, but the differences were not statistically significant. Participants did not report any differences in how much their symptoms generally impaired their daily lives across the different phases.
Mood tracking revealed a correlation between negative emotions and ADHD symptoms. Participants reported elevated negative moods during both the late luteal and menstruation phases compared to the mid-follicular phase. The individuals who experienced the largest drops in mood during menstruation also reported the greatest increases in ADHD symptoms. This correlation held true for both inattentive and hyperactive traits.
Daily amphetamine doses remained remarkably steady across the entire cycle. Participants did not instinctively take more medication to compensate for feeling more distracted or hyperactive during their periods. The research team had hypothesized that some participants using flexible dosing regimens might attempt to counteract their worsening symptoms with higher doses. This lack of adjustment might reflect strict prescribing practices, as many doctors do not encourage patients to alter their daily stimulant intake based on their menstrual cycles.
This research relied entirely on self-reported surveys. The investigators did not measure hormone levels in a laboratory to perfectly confirm each biological phase, opting instead to estimate phases based on reported bleeding days. The small sample size also limited the statistical power of the analysis, meaning the results require verification in larger populations. Because participants taking other psychiatric medications were excluded, the results might not represent individuals managing ADHD alongside conditions such as mood disorders or premenstrual dysphoric disorder.
The study design carried a few distinct demographic and methodological limitations. The researchers did not explicitly gather information on gender identity, meaning the relationship between gender identity, hormone cycles, and ADHD remains untested in this specific context. The standardized survey tool used to track daily symptoms was also based on older diagnostic criteria. This older framework lacks recent diagnostic updates designed to capture how ADHD presents in adults.
The research team also looked at baseline mental health using standardized questionnaires for depression and anxiety. They found a trend suggesting that individuals with higher baseline depression and anxiety scores might experience slightly smaller shifts in ADHD symptoms across their cycles. However, having a higher overall symptom count on average consistently predicted a lower ADHD-related quality of life.
Future studies will need to incorporate direct hormone sampling to precisely map biological changes to behavioral shifts. Researchers might also explore how oral contraceptives or specific antidepressants impact this hormonal cycle in neurodivergent populations. Some clinics have already begun testing symptom-based dosing regimens, where patients take slightly more medication during the specific weeks when their natural hormones work against them. Tracking these targeted interventions could eventually help doctors provide highly individualized care for women navigating adult ADHD.
The study, “Changes in ADHD Symptoms and Mood Across the Menstrual Cycle in Females Treated With Stimulants: A Pilot Study,” was authored by Rebecca Zaritsky, Stephanie C. Reed, and Suzette M. Evans.
URL: https://www.psypost.org/how-the-menstrual-cycle-alters-adhd-symptoms-in-women-taking-stimulants/
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Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #ADHD #WomensHealth #MenstrualCycle #ADHDWomen #MentalHealth #Neurodiversity #HormonalHealth #ADHDAwareness #StimulantMedication #HealthResearch
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Preventing duplicate customer messages when background jobs retry.
Push notifications are not financial ledger entries, but duplicates still damage trust. A customer should not receive the same failure alert three times because a worker retried, nor should two scheduler processes send the same campaign simultaneously.
Task queues normally provide at-least-once execution. Notification systems must design around that fact.
Claim the campaign before sending
Two workers can pick up the same scheduled campaign. Reading its status and then updating it is vulnerable to a race.Lock the campaign and transition it to sending inside one database transaction:
with database_transaction():
campaign = Campaign.objects.select_for_update().get(id=campaign_id)if campaign.status not in {"draft", "queued", "scheduled"}:
returncampaign.status = "sending"
campaign.save()Only the worker that successfully claims the campaign proceeds.
Deduplicate recipients by delivery destination
A user may have duplicate device records, or the same token may appear in customer and merchant contexts. Build the target list from active devices, validate token format, and retain one target per actual push token.Give each delivery a deterministic identity
Create a non-sensitive delivery key from the campaign and device token:delivery_key = sha256(f"{campaign_id}:{device_token}".encode()).hexdigest()
Store one delivery record per campaign and key under a unique database constraint. Create that record before calling the push provider.
If a duplicate task finds the record, it can inspect the existing status rather than sending again.
Record actual provider outcomes
Queued does not mean sent. The delivery record should distinguish pending, accepted, and failed outcomes and retain a safe error message.Campaign totals can then be calculated from delivery rows rather than optimistic task counts.
Handle partial failure
One invalid device token should not abort an entire campaign. Each delivery is an independent attempt, while the campaign summarizes the results.If the campaign-level task crashes, move the campaign out of a permanent sending state so operations can inspect or retry it safely. Existing delivery keys prevent already-sent targets from receiving the message again.
The design principle
Exactly-once delivery cannot be guaranteed across every external push platform, but the application can guarantee that it submits each campaign-device pair at most once under its own retry model.That requires transactional campaign claiming, target deduplication, deterministic delivery identities, and persistent per-device outcomes.#architecture #backend #database #softwareengineering #software #coding #development #engineering #inclusive #community
Exactly-Once Push Notifications on At-Least-Once Workers