ऑस्ट्रेलिया ने तीसरे वनडे में भारत को 43 रनों से जीत लिया है। इसी के साथ ऑस्ट्रेलिया की महिला क्रिकेट टीम ने तीन वनडे मैचों की सीरीज 2-1 से जीत ली है। तीसरा वनडे दिल्ली के अरुण जेटली स्टेडियम में खेला गया, जिसमें कंगारू टीम ने पहले खेलते हुए 412 रनों का विशाल स्कोर खड़ा किया था। इसके जवाब में पूरी भारतीय टीम 369 के स्कोर पर ऑलआउट हो गई। भारत के लिए इस मैच में स्मृति मंधाना ने 125 रनों की शतकीय पारी खेली, लेकिन अपनी टीम की जीत सुनिश्चित नहीं कर पाईं।
413 रनों के लक्ष्य का पीछा करने आई टीम इंडिया की शुरुआत अच्छी नहीं रही क्योंकि सलामी बल्लेबाज प्रतिका रावल 10 रन बनाकर आउट हो गईं। स्मृति मंधाना ने एक छोर संभाला हुआ था, लेकिन दूसरे छोर से धड़ाधड़ विकेट गिर रहे थे। हरलीन देओल भी 11 रन बनाकर आउट हो गईं। कप्तान हरमनप्रीत कौर ने 52 रन बनाए और मंधाना के साथ 121 रनों की पार्टनरशिप की।
दीप्ति शर्मा ने 72 रन बनाए, लेकिन उनका विकेट गिरने के बाद ही कहीं ना कहीं टीम इंडिया की हार निश्चित हो चली थी। 9 नंबर की बल्लेबाज स्नेह राणा ने भी 35 रनों की पारी के दौरान भारतीय टीम की जीत की उम्मीद बनाए रखी, लेकिन अपनी टीम को जीत तक नहीं ले जा पाईं।
मैच में बने 781 रन, लगीं 111 बाउंड्री
भारत बनाम ऑस्ट्रेलिया मैच में कुल 781 रन बने। दोनों टीमों ने कुल मिलाकर 99 चौके और 12 छक्के लगाए। यानी मैच में कुल 111 बाउंड्री लगीं। पहले ऑस्ट्रेलियाई टीम ने 60 चौके और 5 छक्के लगाए। उसके बाद टीम इंडिया ने भी ताबड़तोड़ बैटिंग करते हुए 39 चौके और 7 छक्के लगाए। इस तरह दोनों टीमों के बल्लेबाजों ने मिलकर 111 बाउंड्री लगाकर गदर मचाया।
इस मैच में स्मृति मंधाना पुरुष और महिला वनडे क्रिकेट में मिलाकर भारत के लिए सबसे तेज शतक लगाने वाली प्लेयर बन गई हैं। उन्होंने 50 गेंद में सेंचुरी पूरी कर विराट कोहली के 52 गेंदों में आए शतक का रिकॉर्ड तोड़ा। यह मंधाना के वनडे करियर का कुल 13वां शतक रहा।
Deca Durabolin: Uses, Benefits, And Side Effects
**Digital Health & eHealth – The Foundations**
—
### 1️⃣ What is Digital Health?
> **Digital health** refers to the use of digital technologies—software, data analytics, sensors, and cloud computing—to improve health outcomes,
streamline care delivery, and empower patients.
#### Key Characteristics
| Feature | Explanation |
|———|————-|
| **Technology‑centric** | Relies on devices (smartphones, wearables), platforms (apps, telehealth portals), and
data pipelines. |
| **Patient‑centered** | Gives individuals tools to monitor, manage, and understand their own health (e.g.,
self‑tracking apps). |
| **Data‑driven** | Generates large volumes of real‑world data that can be analyzed
for patterns, predictions, and personalized interventions.
|
| **Interoperable** | Designed to integrate with electronic health records (EHRs), clinical decision support systems, and other care ecosystem components.
|
Examples: Mobile health apps (e.g., MyFitnessPal), continuous glucose monitors, AI‑based
symptom checkers.
—
## 2. The Core Challenges in Integrating Digital Health into Clinical Practice
| # | Challenge | Why It Matters |
|—|———–|—————-|
| **1** | **Technical Interoperability** | Data from digital tools
must be accurately and securely transmitted to EHRs and other clinical
systems. |
| **2** | **Data Quality & Accuracy** | Incorrect or noisy data can lead to
wrong diagnoses, treatment plans, or patient safety incidents.
|
| **3** | **Clinical Workflow Integration** | Clinicians need easy
access to useful information without adding cognitive load or administrative burden. |
| **4** | **Regulatory and Privacy Compliance** | Digital health solutions
must meet HIPAA, GDPR, FDA (or other local regulators) standards for
data handling and device safety. |
| **5** | **Clinical Validation & Evidence Base** | Proven clinical benefit
is required to justify adoption and reimbursement.
|
| **6** | **Reimbursement & Payer Acceptance** | Without payer
coverage or evidence of cost‑effectiveness, many solutions fail
to gain traction. |
| **7** | **Patient Engagement & Usability** | For consumer‑direct products, design must be intuitive and supportive of behavior change.
|
| **8** | **Data Quality, Interoperability & Security**
| The system must provide high‑fidelity data that can safely
integrate into EMR workflows. |
—
## 2. How a “HealthTech Startup” Should Map the Landscape
### A. Define the *Value Proposition*
– What clinical problem is being solved?
– Which stakeholder (clinician, patient, payer) benefits most?
**Example**: A continuous glucose‑monitoring platform that
integrates with an insurer’s diabetes management program to reduce A1c and hypoglycemia events.
### B. Identify the Key “Gatekeepers” in the Journey
| Stage | Typical Decision Makers | Pain Points |
|——-|————————|————-|
| **Clinical Adoption** | Physicians, nurse‑practitioners,
clinic managers | Time constraints, evidence of benefit, ease of
use |
| **Patient Engagement** | Patients (self‑management), caregivers | Trust, usability, data
overload |
| **Reimbursement** | Payers, CMS, insurers | Cost‑effectiveness, demonstrated outcomes, coding support |
| **Data Security & Privacy** | IT security teams, compliance officers |
HIPAA, GDPR, audit trails |
### 2. Building the Narrative Around Each Decision Maker
– **Physician**: “I need a tool that quickly gives me actionable insights without adding to my documentation burden.”
– **Patient**: “The device should be simple and give me confidence in my own health data.”
– **Payer**: “Investing in this technology reduces hospital readmissions, so it’s a worthwhile cost.”
#### Tips for Storytelling
| Objective | How to Frame |
|———–|————–|
| **Credibility** | Use case studies, statistics from peer-reviewed journals.
|
| **Emotion** | Share personal anecdotes (e.g., a patient’s improved life).
|
| **Relevance** | Connect the product benefits directly to each stakeholder’s goals.
|
—
## 5. Marketing Communications
### 5.1 Content Strategy
– **Educational Blog Posts & Whitepapers**: Focus on industry pain points and how your solution addresses them.
– **Infographics & Data Visualizations**: Make complex data accessible and shareable.
– **Webinars & Live Demos**: Offer hands‑on experience; capture leads via registration.
### 5.2 Social Media Tactics
| Platform | Primary Goal | Typical Post Type |
|———-|————–|——————-|
| LinkedIn | B2B lead generation | Thought‑leadership articles, case studies |
| Twitter | Brand awareness & real‑time
engagement | Short insights, event updates |
| YouTube | Demonstrations & tutorials | Video
demos, customer testimonials |
### 5.3 Paid Campaigns
– **LinkedIn Sponsored Content**: Target by industry, job title,
and company size.
– **Google Display Network**: Retarget site visitors with tailored ads.
– **Twitter Amplify**: Promote key events or webinars.
—
## 6. Measurement & Optimization
| KPI | Definition | Target |
|—–|————|——–|
| Cost per Lead (CPL) | Total spend ÷ number of qualified leads | Y% |
| Lead Quality Score | Weighted score based on demographics, engagement
| >Z |
| Return on Ad Spend (ROAS) | Revenue attributed ÷ ad spend | ≥ 5:
1 |
**Data Sources:** Google Analytics, Facebook Ads Manager, CRM dashboards.
**Optimization Loop:**
1. **A/B Test Creatives** → Identify high-performing assets.
2. **Adjust Targeting** based on performance data.
3. **Refine Landing Pages** for better conversion rates.
4. **Reallocate Budget** to best-performing channels.
—
## 7. Sample Marketing Calendar (Quarterly)
| Week | Campaign | Creative Asset | Target Platform | KPI
|
|——|———-|—————-|—————–|—–|
| 1-2 | “Intro to AI” Video Series | Short explainer
videos | YouTube, LinkedIn | View count ≥ 10k |
| 3-4 | “AI in Everyday Life” Carousel Ads | Instagram
carousel | Instagram, Facebook | CTR ≥ 2% |
| 5 | Webinar: “Future of AI” | Live webinar registration page | Email, LinkedIn | Registrations ≥ 200
|
| 6-7 | Customer Success Stories | Case study PDF + video | Website, email | Downloads ≥ 150
|
| 8 | Interactive Quiz: “Which AI is Right for You?” | Web quiz
with instant results | Website, Twitter | Participation ≥
300 |
—
## 4. Budget Breakdown
**Total Annual Marketing Budget:** $750 k
| Category | % of Total | Annual Cost | Monthly Cost |
|———-|————|————-|————–|
| **Digital Advertising (Google Ads, LinkedIn, Facebook)** | 35% | $262 500 | $21 875
|
| **Content Production & Distribution** | 20% | $150 000 | $12 500 |
| **SEO / Technical Optimization** | 10% | $75 000 | $6 250 |
| **Email Marketing Platform + Automation** | 5% | $37 500 | $3 125 |
| **Events & Webinars (Sponsor, Host)** | 15% | $112 500 | $9 375 |
| **Market Research & Analytics Tools** | 10% | $75 000 |
$6 250 |
| **Miscellaneous / Contingency** | 10% | $75 000 | $6 250 |
| **Total** | 100% | **$525,000** | **$43,750** |
> **Note:**
> • The budget is **annual** and assumes a **mid‑level** company operating in the U.S.
market.
> • Allocation may shift depending on specific
industry (e.g., B2B SaaS vs. manufacturing) and geographic focus (global expansion vs.
domestic).
> • A contingency reserve of 10 % ensures flexibility for unforeseen opportunities or disruptions.
—
## 4. Strategic Recommendations
| **Area** | **Recommendation** | **Rationale** |
|———-|——————–|—————|
| **Talent Acquisition & Retention** | Offer
a **tiered compensation package** (base + performance bonuses) and invest in **continuous learning**
via sponsorships for certifications, conferences, or university courses.
| Attracts high‑skill talent; reduces turnover; aligns employees with company goals.
|
| **Leadership Development** | Implement a **structured mentorship program**
pairing senior leaders with emerging managers, coupled with formal
training on strategic thinking and people management.
| Builds future leaders, maintains continuity,
fosters internal promotion culture. |
| **Diversity & Inclusion (D&I)** | Set measurable D&I metrics (e.g., % of hires from underrepresented groups), provide unconscious bias training, and create employee resource groups (ERGs).
| Improves innovation, expands talent pool, enhances brand reputation. |
| **Talent Mobility** | Offer cross‑functional projects and rotational assignments to broaden skill sets and
expose employees to new domains. | Reduces skill silos, increases engagement, identifies hidden talents.
|
| **Learning & Development (L&D)** | Implement a blended learning platform: micro‑learning modules, instructor‑led courses, mentorship programs; track
completion rates and impact on performance. | Accelerates
upskilling, aligns with business goals, supports career progression. |
| **Performance Management** | Adopt continuous feedback loops: quarterly check‑ins, 360° reviews, calibrated goal setting aligned with OKRs/Key Results.
| Improves accountability, nurtures growth mindset, ties to rewards.
|
| **Succession Planning** | Maintain a dynamic talent pool database:
track competencies, experience, readiness scores; map critical
roles to potential successors. | Reduces risk of leadership gaps,
informs development focus. |
—
### 3. Implementation Roadmap (12‑Month Timeline)
| Month | Initiative | Owner / Team | Key Deliverables |
|——-|————|————-|—————–|
| **1–2** | *Talent Audit & Data Consolidation*
– Centralize ATS/HRIS data.
– Conduct skills matrix assessment. | HR Analytics
Lead, IT Integration | Comprehensive talent inventory dashboard.
|
| **3–4** | *Metrics Definition & Dashboard
Build*
– Finalize KPIs (e.g., time‑to‑fill, diversity %).
– Deploy real‑time analytics portal. | Data Science Team, BI Developers | Live KPI dashboard
accessible to leadership. |
| **5–6** | *Process Mapping & Standardization*
– Document end‑to‑end hiring workflow.
– Identify bottlenecks and non‑value‑added steps.
| Process Improvement Manager | Updated SOPs for recruitment pipeline.
|
| **7–8** | *Automation Pilot*
– Implement AI resume screening for high‑volume roles.
– Integrate interview scheduling bots. | IT &
Talent Acquisition Lead | Reduced manual tasks by X%; improved candidate experience.
|
| **9–10** | *Performance Review & Continuous Improvement*
– Evaluate impact on time‑to‑hire, cost‑per‑placement.
– Adjust metrics and refine processes. | HR Analytics Team |
Established KPI dashboard for ongoing monitoring. |
### 5. Expected Outcomes
| Outcome | Measurement |
|———|————-|
| Faster hiring cycles | Reduce average time‑to‑fill from Y to
Z days |
| Lower recruiting costs | Decrease cost per hire by A% |
| Higher quality hires | Improve new hire performance scores
by B% |
| Better candidate experience | Increase NPS for candidates by C
points |
### 6. Key Risks & Mitigation
| Risk | Impact | Mitigation |
|——|——–|————|
| Over‑automation may ignore nuance | Medium | Keep human review in critical stages |
| Data privacy concerns | High | Comply with GDPR, use anonymized data |
| Tool integration failure | Medium | Pilot test, maintain fallback
processes |
—
**In a nutshell:**
– **Data‑driven HR** uses the same analytical
mindset you already have: collect metrics → model patterns
→ predict outcomes → act.
– The biggest benefit is turning “human” decisions into repeatable, evidence‑based actions that
scale with growth.
Start small (e.g., automated interview scheduling or predictive attrition alerts), measure impact, then expand.
Your existing expertise in modeling and data pipelines will
be directly applicable—just shift the focus from financial risk
to talent risk. Let me know if you’d like a deeper dive into any specific area!
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