Part 3 completes the core CRiskManagement class for MetaTrader 5, moving from UI to a modular engine in Risk_Management.mqh that tracks losses/profits and enforces limits. The design centers on clear enums and a Loss_Profit structure supporting fixed-money or percentage-based limits, with selectable reference metrics (balance, equity, free margin, net profit). It models daily/weekly/total loss caps, per-trade risk, and daily profit targets, plus prop-firm rules where daily loss is evaluated dynamically against equity and can expand with intraday gains (FTMO-style). Implementation details include a CTrade wrapper, magic-number scoping, profit time windows, and lifecycle-safe constructor/destructor. Initialization and setters configure stop loss, calculation modes, and percentage application, enabling lot sizing from per-trade risk and optionally stop-... #MQL5 #MT5 #RiskMgmt #AlgoTrade https://lnkd.in/dJTs38Eh

💡 Pro Tip: Redesigned Property fields Managing your asset properties just got easier! Chip-based lists make adding and editing values faster, three input states, normal, empty, and error, give you clear feedback, and dates and times can now be entered quickly and accurately using input masks. #assetmanagement #dataquality #productivityboost #qbilon

On-demand credit only helps if your systems can actually use it. From an engineering perspective, “real-time” credit is useless if every bureau behaves differently and every pull needs custom handling. CRS normalizes those differences upstream, so on-demand credit can be consumed consistently across systems. That’s what allows teams to make faster decisions without sacrificing reliability or control. We cover this in detail in the post.

Which BET method best fits your QC strategy? Whether you rely on gel-clot, kinetic, or automated BET methods, one question remains: Are you balancing compliance, efficiency, and sustainability effectively? Our Essential Guide to BET Testing helps QC and production leaders: 🔹 Compare methods and identify the best fit for their operations 🔹 Understand data integrity, compliance and validation challenges 🔹 See how Sievers Eclipse automates without complexity 📘 Download the guide: https://lnkd.in/exQBTxnS #SieversEclipse

If the morning was about the "What," the afternoon is about the "How." Handling a single SIGTERM is a start, but production environments are messy. Now,, we look at the nuances of signal handling, the potential for deadlocks during shutdown, and how to ensure your cleanup code is as robust as your business logic.

A quick screen recording demonstrating the core flow of the fault ticket tracking application. This shows how faults are logged, tracked, and followed up in one centralized system reducing missed reports, delays, and manual follow-ups. Still an early-stage build, but focused on solving real operational problems. Feedback and suggestions are welcome.

Traditional BOD testing methods demand precision, time, and accurate data handling. MANTECH’s BOD Pro Software helps labs work smarter by simplifying every step of the process: • Automated calculations • Auto-populating data entry with YSI meter integration • 5- and 7-day tracking • Email notifications of run completed, results and more Available as a standalone solution, the BOD Pro Software is a cost-effective way to improve efficiency and confidence in your BOD testing process. Discover how BOD Pro can streamline your workflow and transform your lab operations. 👉 https://hubs.li/Q041NTNy0

PSP Question #5️⃣8️⃣ During a schedule update, several non-critical activities gain float, while no logic or durations were changed. The project finish date also remains unchanged. What is the MOST likely reason? 🅰 Progress was applied using remaining durations 🅱 Constraints were removed from near-critical activities 🅲 Actual dates were inserted causing logic recalculation 🅳 The data date was advanced and the schedule recalculated

What you see on install is rarely what you face six months later. We capture asset condition at installation, then track how it changes under real conditions. Rainfall, surcharge, structural response. Measured, not assumed. That live data is fed back into the platform and assessed against how the asset has historically behaved, so risk is re-prioritised as conditions evolve. This is how monitoring becomes understanding. And how understanding leads to timely intervention. The monitor collects the truth. The software turns it into action.

PSP Question #5️⃣7️⃣ After several update cycles, a scheduler notices that free float is always zero for most activities, while total float exists only on one long path. What does this MOST likely indicate? 🅰 The schedule is perfectly optimized 🅱 Activities are progressing faster than planned 🅲 Logic is overly constrained or improperly sequenced 🅳 Resource leveling is disabled ✔ Answer to PSP Question #56: 🅰 – Resource leveling is being applied during calculation Explanation: Resource leveling redistributes float even without logic changes. 755