A dynamic modeling method for helical gear systems

Dynamic modeling for gear systems is very important for accurately predicting the dynamic responses during the gear engagements. During the modeling, meshing force must be determined, and it is usually calculated by the product of the relative displacement along the line of action (LOA) and the meshing stiffness. At present, the relative displacement calculation for helical gear systems is very complicated by several existing methods because the complicated geometric relationships need to be derived for determining the spatial positions of two meshing points along LOA. In this study, a simple method for calculating the relative displacement along LOA is presented based on ANSYS software. And on this basis, a new finite element modeling method for a helical gear transmission system with multiple shafts is developed, where the influences of shafts and bearing flexibilities are considered. Moreover, the proposed method is validated by comparing the dynamic characteristics, such as natural characteristics and vibration responses, with those obtained from Kubur’s method and Zhang’s method

Vector-based siRNA delivery strategies for high-throughput screening of novel target genes

Application of siRNA in high-throughput fashion is still in its early phase although the principle has been established for three years. In this review, we outline the different vector-based siRNA delivery platforms as well as resources that are becoming available for high-throughput applications, and some initial outcomes of vector siRNA high-throughput screening efforts using vector encoded siRNA. It is expected that further improvement of the siRNA technology and availability of the siRNA resources will help to materialize the potential of siRNA for functional genomics and drug target validation

CycleAlign: Iterative Distillation from Black-box LLM to White-box Models for Better Human Alignment

Language models trained on large-scale corpus often generate content that is harmful, toxic, or contrary to human preferences, making their alignment with human values a critical concern. Reinforcement learning from human feedback (RLHF) with algorithms like PPO is a prevalent approach for alignment but is often complex, unstable, and resource-intensive. Recently, ranking-based alignment methods have emerged, offering stability and effectiveness by replacing the RL framework with supervised fine-tuning, but they are costly due to the need for annotated data. Considering that existing large language models (LLMs) like ChatGPT are already relatively well-aligned and cost-friendly, researchers have begun to align the language model with human preference from AI feedback. The common practices, which unidirectionally distill the instruction-following responses from LLMs, are constrained by their bottleneck. Thus we introduce CycleAlign to distill alignment capabilities from parameter-invisible LLMs (black-box) to a parameter-visible model (white-box) in an iterative manner. With in-context learning (ICL) as the core of the cycle, the black-box models are able to rank the model-generated responses guided by human-craft instruction and demonstrations about their preferences. During iterative interaction, the white-box models also have a judgment about responses generated by them. Consequently, the agreement ranking could be viewed as a pseudo label to dynamically update the in-context demonstrations and improve the preference ranking ability of black-box models. Through multiple interactions, the CycleAlign framework could align the white-box model with the black-box model effectively in a low-resource way. Empirical results illustrate that the model fine-tuned by CycleAlign remarkably exceeds existing methods, and achieves the state-of-the-art performance in alignment with human value

Global Optimization of Minority Game by Smart Agents

We propose a new model of minority game with so-called smart agents such that the standard deviation and the total loss in this model reach the theoretical minimum values in the limit of long time. The smart agents use trail and error method to make a choice but bring global optimization to the system, which suggests that the economic systems may have the ability to self-organize into a highly optimized state by agents who are forced to make decisions based on inductive thinking for their limited knowledge and capabilities. When other kinds of agents are also present, the experimental results and analyses show that the smart agent can gain profits from producers and are much more competent than the noise traders and conventional agents in original minority game.Comment: 5 pages, 5 figure

Analysis of siRNA specificity on targets with double-nucleotide mismatches

Although RNA interference as a tool for gene knockdown is a great promise for future applications, the specificity of small interfering RNA (siRNA)-mediated gene silencing needs to be thoroughly investigated. Most research regarding siRNA specificity has involved analysis of affected off-target genes instead of exploring the specificity of the siRNA itself. In this study we have developed an efficient method for generating a siRNA target library by combining a siRNA target validation vector with a nucleotide oligomix. We have used this library to perform an analysis of the silencing effects of a functional siRNA towards its target site with double-nucleotide mismatches. The results indicated that not only the positions of the mismatched base pair have an impact on silencing efficiency but also the identity of the mismatched nucleotide. Our data strengthen earlier observations of widespread siRNA off-target effects and shows that ∼35% of the double-mutated target sites still causes knockdown efficiency of >50%. We also provide evidence that there may be substantial differences in knockdown efficiency depending on whether the mutations are positioned within the siRNA itself or in the corresponding target site

The multiplexed light storage of Orbital Angular Momentum based on atomic ensembles

The improvement of the multi-mode capability of quantum memory can further improve the utilization efficiency of the quantum memory and reduce the requirement of quantum communication for storage units. In this letter, we experimentally investigate the multi-mode light multiplexing storage of orbital angular momentum (OAM) mode based on rubidium vapor, and demultiplexing by a photonic OAM mode splitter which combines a Sagnac loop with two dove prisms. Our results show a mode extinction ratio higher than 80$\%$ at 1 $\mu$s of storage time. Meanwhile, two OAM modes have been multiplexing stored and demultiplexed in our experimental configuration. We believe the experimental scheme may provide a possibility for high channel capacity and multi-mode quantum multiplexed quantum storage based on atomic ensembles

Electrochemical Monitoring of ROS/RNS Homeostasis Within Individual Phagolysosomes Inside Single Macrophages

International audienceReactive Oxygen/Nitrogen Species (ROS/RNS) produced by macrophages inside their phagolysosomes are closely related to immunity and inflammation by being involved in the removal of pathogens, altered cells, etc. The existence of a homeostatic mechanism regulating the ROS/RNS amounts inside phagolysosomes has been invoked to account for the efficiency of this crucial process but this could never be unambiguously documented. In this work, intracellular electrochemical analysis with platinized nanowires electrodes (Pt-NWEs) allowed monitoring ROS/RNS effluxes with sub-millisecond resolution from individual phagolysosomes randomly impacting onto the electrode inserted inside a living macrophage. This evidenced for the first time that the consumption of ROS/RNS by their oxidation at the nanoelectrode surface stimulates the production of significant ROS/RNS amounts inside phagolysosomes. These results established the existence of the long-time postulated ROS/RNS homeostasis and allowed quantifying its kinetics and efficiency. ROS/RNS concentrations may then be maintained at sufficiently high levels for sustaining proper pathogen digestion rates without endangering the macrophage internal structures