Supporting Go/No-Go decisions prior to launch requires assessing real-time telemetry data against redline limits established during the design qualification phase. Family data from ground testing or previous flights is commonly used to detect initiating failure modes and their timing; however, this approach relies heavily on engineering judgment and is more error-prone for new launch vehicles. To address these limitations, we utilize Long-Term Short-Term Memory (LSTM) networks for supervised classification of time-series anomalies. Although, initial training labels derived from simulated anomaly data may be suboptimal due to variations in anomaly strength, anomaly settling times, and other factors. In this work, we propose a novel statistical detector based on the Mahalanobis distance and forward-backward detection fractions to adjust the supervised training labels. We demonstrate our method on digital twin simulations of a ground-stage propulsion system with 20.8 minutes of operation per trial and O(10^8) training timesteps. The statistical data relabeling improved precision and recall of the LSTM classifier by 7% and 22% respectively.

When you purchase through links in our articles, we may earn a small commission. Valve has spent the last decade tunneling into Microsoft's vault. Now, the heist is on. Microsoft's big focus for Windows is AI integration . Meanwhile, Valve has been not-so-quietly pilfering the entire PC gaming ecosystem from Microsoft, turning the Linux-based SteamOS into a real competitor to Windows.

Transcatheter Aortic Valve Replacement (TAVR) has emerged as a minimally invasive treatment option for patients with severe aortic stenosis, a life-threatening cardiovascular condition. Multiple transcatheter heart valves (THV) have been approved for use in TAVR, but current guidelines regarding valve type prescription remain an active topic of debate. We propose a data-driven clinical support tool to identify the optimal valve type with the objective of minimizing the risk of permanent pacemaker implantation (PPI), a predominant postoperative complication. We synthesize a novel dataset that combines U.S. and Greek patient populations and integrates three distinct data sources (patient demographics, computed tomography scans, echocardiograms) while harmonizing differences in each country's record system. We introduce a leaf-level analysis to leverage population heterogeneity and avoid benchmarking against uncertain counterfactual risk estimates. The final prescriptive model shows a reduction in PPI rates of 26% and 16% compared with the current standard of care in our internal U.S. population and external Greek validation cohort, respectively. To the best of our knowledge, this work represents the first unified, personalized prescription strategy for THV selection in TAVR.

Laboratory Automation (LA) has the potential to accelerate solid-state materials discovery by enabling continuous robotic operation without human intervention. While robotic systems have been developed for tasks such as powder grinding and X-ray diffraction (XRD) analysis, fully automating powder handling at the milligram scale remains a significant challenge due to the complex flow dynamics of powders and the diversity of laboratory tasks. To address this challenge, this study proposes a novel, funnel-shaped, flexible robotic hand that preserves the softness and conical sheet designs in prior work while incorporating a controllable valve at the cone apex to enable precise, incremental dispensing of milligram-scale powder quantities. The hand is integrated with an external balance through a feedback control system based on a model of powder flow and online parameter identification. Experimental evaluations with glass beads, monosodium glutamate, and titanium dioxide demonstrated that 80% of the trials achieved an error within 2 mg, and the maximum error observed was approximately 20 mg across a target range of 20 mg to 3 g. In addition, by incorporating flow prediction models commonly used for hoppers and performing online parameter identification, the system is able to adapt to variations in powder dynamics. Compared to direct PID control, the proposed model-based control significantly improved both accuracy and convergence speed. These results highlight the potential of the proposed system to enable efficient and flexible powder weighing, with scalability toward larger quantities and applicability to a broad range of laboratory automation tasks.

Abstract--Transcatheter valve repair presents significant challenges due to the mechanical limitations and steep learning curve associated with manual catheter systems. This paper investigates the use of robotics to facilitate transcatheter procedures in the context of mitral valve edge-to-edge repair . The complex handle-based control of a clinical repair device is replaced by intuitive robotic joint-based control via a game controller . Manual versus robotic performance is analyzed by decomposing the overall device delivery task into motion-specific steps and comparing capabilities on a step-by-step basis in a phantom model of the heart and vasculature. Metrics include procedure duration and clip placement accuracy. Results demonstrate that the robotic system can reduce procedural time and motion errors while also improving accuracy of clip placement. These findings suggest that robotic assistance can address key limitations of manual systems, offering a more reliable and user-friendly platform for complex transcatheter procedures. Transcatheter valve repair procedures are complex to perform and involve substantial learning curves. For example, in transcatheter edge-to-edge repair (TEER) of mitral regurgitation (Figure 1), clinical experience demonstrates that operators improve significantly over their first 50 cases and their performance continues to improve out to their 200th case [1]. A major component of mastering a transcatheter procedure is learning how to precisely control catheter positioning.

After the smash hit that is the Steam Deck, all eyes are on Valve for its next hardware move. A console to take on Sony and Nintendo? A new trademark filing for the "Steam Frame" has gamers and press alike turning the speculation up to 11. And yeah, I couldn't resist doing some of my own. The United States Patent and Trademark Office has a public filing for the Steam Frame name, assigned to Valve Corporation and its corporate office in Bellevue, Washington, and began on September 2nd.

We present a customizable soft haptic system that integrates modular hardware with an information-theoretic algorithm to personalize feedback for different users and tasks. Our platform features modular, multi-degree-of-freedom pneumatic displays, where different signal types, such as pressure, frequency, and contact area, can be activated or combined using fluidic logic circuits. These circuits simplify control by reducing reliance on specialized electronics and enabling coordinated actuation of multiple haptic elements through a compact set of inputs. Our approach allows rapid reconfiguration of haptic signal rendering through hardware-level logic switching without rewriting code. Personalization of the haptic interface is achieved through the combination of modular hardware and software-driven signal selection. To determine which display configurations will be most effective, we model haptic communication as a signal transmission problem, where an agent must convey latent information to the user. We formulate the optimization problem to identify the haptic hardware setup that maximizes the information transfer between the intended message and the user's interpretation, accounting for individual differences in sensitivity, preferences, and perceptual salience. We evaluate this framework through user studies where participants interact with reconfigurable displays under different signal combinations. Our findings support the role of modularity and personalization in creating multimodal haptic interfaces and advance the development of reconfigurable systems that adapt with users in dynamic human-machine interaction contexts.

Breakthroughs, discoveries, and DIY tips sent every weekday. Animals constantly adapt to their environments, but keeping up with humanity's dramatic influence on the natural world poses unique challenges. While this unfortunately ends in disaster for many species, some populations are figuring out new ways to navigate urban spaces. Back in 2022, wildlife biologists confirmed that a community of wild, sulfur-crested cockatoos in Sydney, Australia had learned how to open the lids of curbside trash bins on garbage day in order to snack on locals' leftovers. But that's not all these birds can do.

Gabe Newell, co-founder and CEO of Valve, has been working on a new brain-computer interface project through his Starfish Neuroscience company for several years. The company just announced that it plans to launch its first brain chip by the end of 2025, reports The Verge. This chip isn't a complete implant solution, but a specially designed "electrophysiological" component that can both read and stimulate brain activity. Unlike competitors, such as Elon Musk's Neuralink, Starfish aims to create a less invasive solution that doesn't require a battery and can reach multiple brain regions at once using wireless energy transfer. Starfish is also developing technology to treat neurological disorders such as depression and bipolar disorder, as well as a method to destroy tumors using targeted heat.

Valve's Half-Life 2 is still a wonderful milestone of PC gaming more than 20 years after its original release, but it recently got its dated visuals pumped up with a mod that lets you flex the power of a cutting-edge graphics card. In a video sponsored by Nvidia, PCWorld's Adam goes through the new ray tracing and graphical enhancements and talks with the developers who implemented them. Half-Life 2 RTX is a free upgrade if you already own the original (and after a million Steam sales, who doesn't?), though you won't get all the enhanced goodies unless you're lucky enough to have an RTX 50-series card. We're talking ray tracing and path tracing for incredible lighting, plus new in-game assets with more polygons and better textures so you have something nice for those rays to bounce off. Naturally, this is going to make your gaming PC sweat a little more than the unmodified 20-year-old game.