Benchmarking Hyper-Breakpoints for Efficient Virtual Machine Introspection

Abstract: Virtual Machine Introspection (VMI) is a powerful technology used to detect and analyze malicious software inside Virtual Machines (VMs) from outside. Asynchronously accessing the VM ’s memory can be insufficient for efficiently monitoring what is happening inside of a VM. Active VMI introduces breakpoints to intercept VM execution at relevant points. Especially for frequently visited breakpoints, and even more so for production systems, it is crucial to keep their performance overhead as low as possible. In this paper, we provide a systematization of existing VMI breakpoint implementation variants, propose workloads to quantify the different performance penalties of breakpoints, and implement them in the benchmarking application bpbench. We used this benchmark to measure that, on an Intel Core i5 7300U, SmartVMI’s breakpoints take around 81 μs to handle, and keeping the breakpoint invisible costs an additional 21 μs per read access. The availability of bpbench facilitates the comparison of disparate breakpoint mechanisms and their performance optimization with immediate feedback

Demonstrating Surface and Plasma Chemistry with a Nonthermal Atmospheric Plasma

Abstract A low-cost plasma nozzle/setup was developed to allow demonstrations, and it invites hands-on experimentation with nonthermal plasmas of air and other gases. Several high-tech plasma applications, such as surface cleaning and activation, as well as mild but effective sterilization, will be explained and adapted to be eagerly explored by undergraduate and senior high school students. The results were surprisingly similar to those obtained with a commercial plasma treatment system. While the focus is on the experimental introduction to plasma physics and chemistry, it will be highlighted how a multidisciplinary approach enables the study and discussion of important concepts ranging from surface energies and contact angles to environmental or microbiological control

The Impact of Elevated Printing Speeds and Filament Color on the Dimensional Precision and Tensile Properties of FDM-Printed PLA Specimens

This study examines the effect of elevated printing speeds (100–600 mm/s) on the dimensional accuracy and tensile strength of PLA components fabricated via fused deposition modeling (FDM). To isolate the influence of printing speed, all other parameters were kept constant, and two filament variants—natural (unpigmented) and black PLA—were analyzed. ISO 527-2 type 1A specimens were produced and tested for dimensional deviations and ultimate tensile strength (UTS). The results indicate that printing speed has a marked impact on both geometric precision and mechanical performance. The optimal speed of 300 mm/s provided the best compromise between dimensional accuracy and tensile strength for both filaments. At speeds below 300 mm/s, under-extrusion caused weak layer bonding and air gaps, while speeds above 300 mm/s led to over-extrusion and structural defects due to thermal stress and rapid cooling. Black PLA yielded better dimensional accuracy at higher speeds, with cross-sectional deviations between 2.76% and 5.33%, while natural PLA showed larger deviations of up to 8.63%. However, natural PLA exhibited superior tensile strength, reaching up to 46.59 MPa, with black PLA showing up to 13.16% lower UTS values. The findings emphasize the importance of speed tuning and material selection for achieving high-quality, reliable, and efficient FDM prints

Ultrasonically Deposited Boron-Doped Silicon Decorated with Laser-Generated Iridium Nanoparticles as Manufacturing Approach for OER Electrodes in PEM Water Electrolysis

The study introduces flexible and scalable manufacturing approach for electrodes utilizing boron-doped silicon as conductive support for iridium nanoparticles, addressing the challenges of cost and scarcity associated with noble catalysts for oxygen evolution reaction (OER). Colloidal Ir nanoparticles are synthesized via pulsed-laser ablation (≈4–7 nm) and decorated on B-doped Si (≈100 nm) through electrostatic adsorption. Titanium substrates are ultrasonically sprayed with Si:B – Ir and Ir nanoparticles with very low iridium loading of 12 wt.%. Crystalline Ir phases (Ir(111), Ir(200)) are observed and known to enhance the OER mechanism. Additionally, atom probe tomography confirms that the Si support particles contained 0.03-0.5 at.% of boron throughout the entire particle, while electrical permittivity and through-plane measurements reveal a positive impact of B-doped Si on the electrical conductivity of the nanocatalysts and of the ultralow-loaded catalyst coated Ti substrates (0.12 mgIr cm−2), respectively. Rotating disk electrode results show pronounced oxidation peaks for decorated Ir nanoparticles. The Si:B-Ir 4 nm catalyst exhibits the highest turnover frequency (2.62 s−1) and a competitive electrochemical surface area (25 m2 gIr−1) compared to Si:B-Ir 7 nm (0.96 s−1; 37.5 m2 gIr−1) and Ir black (0.24 s−1; 5 m2 gIr−1). The overall analysis of the parameters highlights a performant catalytic efficiency, through balancing activity and reaction kinetics effectively

Dynamische Stromtarife zur Regelung EE-versorgten Stromverbrauchs : eine Analyse am Beispiel des Stromverbrauchs im Jahr 2024

Zusammenfassung Anlass dieser Studie ist die verpflichtende Einführung dynamischer Stromtarife gemäß §41 EnWG. Hierdurch soll ein Paradigmenwechsel im Hinblick auf den Stromverbrauch bewirkt werden: Der Stromverbrauch soll sich künftig bestmöglich an das überwiegend wettergeführte Stromangebot der Erneuerbare-Energien-Quellen anpassen, statt dass sich das Stromangebot wie bisher am Strombedarf orientiert. Die Studie untersucht, inwieweit dynamische Stromtarife das Stromverbraucher-Verhalten und die Gesamtstromkosten des Jahres 2024 hätten beeinflussen können, wenn diese bereits 2024 deutschlandweit genutzt worden wären

Comparative Analysis of Chemical Structure String Representations for Neural Machine Translation

In this work, we present a comparative analysis of SMILES, DeepSMILES, and SELFIES string representations for chemical struc-tures in neural machine translation tasks in cheminformatics. Using transformer-based models, we systematically evaluated their effective-ness in translating between these representations and the correspond-ing linguistic IUPAC nomenclature. The experimental results demon-strate comparable performance for all three string representations, with SMILES achieving a marginally higher accuracy (99.30% with stereo-chemical information, 99.21% without) compared to its alternatives. In scaling experiments with 1, 10, and 50 million compounds, the perfor-mance differences remained small, though the performance gap narrowed with larger datasets. These findings suggest that researchers can con-fidently continue using SMILES for neural machine translation tasks with transformers, which benefits from their extensive support in exist-ing chemical libraries, tools, and databases, rather than adopting newer representations. This work has a significant impact on developing more efficient chemical language models in drug discovery, material science, and chemical database curation

Electrodeposition of Mo-Rich NiMo Catalysts: Effect of Deposition Parameters and Oxygen Content on the Alkaline Hydrogen Evolution Reaction Activity

Electrodeposited Mo-rich NiMo catalysts offer enhanced catalytic activity for the alkaline hydrogen evolution reaction (HER) and provide an electrically conductive, binder-free substrate connection, making them promising catalysts for green hydrogen production. However, creating Mo-rich deposits is challenging, as the codeposition process typically favors Ni. Optimal deposition conditions for Mo-rich NiMo catalysts remain insufficiently explored. This article investigates Mo-rich NiMo electrodeposition from an ammonia-free citrate bath using NaSO4 as a chlorine-free support electrolyte. The effects of the deposition parameters, 1) sodium molybdate concentration in the electrolyte, 2) deposition current density, and 3) enhanced mass transport via working electrode rotation on the alkaline HER activity, were studied. The electrodeposits, containing 44–66 wt% Mo, exhibited increased surface area due to a rough, cracked morphology and variable oxygen content of the catalyst. The oxygen content was linked to HER activity, revealing an inhibiting effect. The lowest overpotential of 118 mV at −10  mA cm−2 for the alkaline HER was achieved using an electrolyte with 0.02 mol L−1 sodium molybdate, a deposition current density of 600 mA cm−2, without electrode rotation. Respective samples combined a favorable Ni:Mo ratio comprising 56 wt% Mo content with increased surface area and low oxygen content