Monitoring, diagnosis, and control for advanced anesthesia management

Modern anesthesia management is a comprehensive and the most critical issue in medical care. During the past dacades, a large amount of research works have been focused on the problems of monitoring anesthesia depth, modeling the dynamics of anesthesia patient for the purpose of control, prediction, and diagnosis. Monitoring the anesthesia depth is not only for keeping the patient in adquate anesthesia level but also for preventing the patient from overdosing. Several EEG based indexes have been developed such as the BIS, and Entropy etc. for measuring depth. However, reports mentioned that those indexes in some cases fail in detecting the awareness of the the patient. In this research work, a new EEG based parameter, beta_2/theta-ratio, was introduced as a potential enhancement in measuring anesthesia depth. It was compared to the relative beta-ratio which had been commercially used in the BIS monitor and proved that the beta_2/theta-ratio has improved reliability and sensitivity in detecting the awareness than the beta-ratio does. Traditional modeling, diagnosis and control in anesthesia focus on a one-drug one-outcome scenario. In fact, Anesthesia drugs have impact on multiple outcomes of an anesthesia patient. Due to limited real-time data, real-time modeling in multi-outcome modeling requires low complexity model structures. A method of decision-oriented modeling which employs simplified and combined model functions in a Wiener structure to reduce model complexity was introduced. This model structure was implemented in device level and tested in operation room for real-time anesthesia monitoring, diagnosis, and prediction. Furthermore, the impact of wireless channels on patient control in anesthesia applications was also investigated. Such a system involves communication channels which introduce noises due to quantization, channel noises, and have limited communication bandwidth resources. Usually signal averaging can be used effectively in reducing the noise effects. However, when feedback was intended, we showed that signal averaging will lose its utility substantially. To explain this phenomenon, we analyzed stability margins under signal averaging and derived some optimal strategies for selecting window sizes. Finally, a mathematical model for the auditory system was introduced to characterize the impact of anesthesia on auditory systems, and analyze and diagnose hearing damage. The auditory system was represented by a black-box input-output system with external sound stimuli as the input and the neuron firing rates as the output. Two parallel subsystem models were developed for modeling the auditory system dynamics: an ARX (Auto-Regression with External Input) model for the auditory system under external stimuli and an ARMA (Auto-Regression and Moving Average) model for the spontaneous activities of the neurons on primary auditory cortex. These models provide a quantitative characterization of anesthesia\u27s impacts and diagnosis of hearing loss on auditory transmission channels

Inserting Extra Train Services on High-Speed Railway

With the aim of supporting future traffic needs, an account of how to reconstruct an existing cyclic timetable by inserting additional train services will be given in this paper. The Timetable-based Extra Train Services Inserting (TETSI) problem is regarded as an integration of railway scheduling and rescheduling problem. The TETSI problem therefore is considered involving many constraints, such as flexible running times, dwell times, headway and time windows. Characterized based on an event-activity graph, a general Mixed Integer Program model for this problem is formulated. In addition, several extensions to the general model are further proposed. The real-world constraints that concerning the acceleration and deceleration times, priority for overtaking, allowed adjustments, periodic structure and frequency of services are incorporated into the general model. From numerical investigations using data from Shanghai-Hangzhou High-Speed Railway in China, the proposed framework and associated techniques are tested and shown to be effective

Value Functions are Control Barrier Functions: Verification of Safe Policies using Control Theory

Guaranteeing safe behaviour of reinforcement learning (RL) policies poses significant challenges for safety-critical applications, despite RL's generality and scalability. To address this, we propose a new approach to apply verification methods from control theory to learned value functions. By analyzing task structures for safety preservation, we formalize original theorems that establish links between value functions and control barrier functions. Further, we propose novel metrics for verifying value functions in safe control tasks and practical implementation details to improve learning. Our work presents a novel method for certificate learning, which unlocks a diversity of verification techniques from control theory for RL policies, and marks a significant step towards a formal framework for the general, scalable, and verifiable design of RL-based control systems

Data Pruning via Moving-one-Sample-out

In this paper, we propose a novel data-pruning approach called moving-one-sample-out (MoSo), which aims to identify and remove the least informative samples from the training set. The core insight behind MoSo is to determine the importance of each sample by assessing its impact on the optimal empirical risk. This is achieved by measuring the extent to which the empirical risk changes when a particular sample is excluded from the training set. Instead of using the computationally expensive leaving-one-out-retraining procedure, we propose an efficient first-order approximator that only requires gradient information from different training stages. The key idea behind our approximation is that samples with gradients that are consistently aligned with the average gradient of the training set are more informative and should receive higher scores, which could be intuitively understood as follows: if the gradient from a specific sample is consistent with the average gradient vector, it implies that optimizing the network using the sample will yield a similar effect on all remaining samples. Experimental results demonstrate that MoSo effectively mitigates severe performance degradation at high pruning ratios and achieves satisfactory performance across various settings.Comment: Accepted by the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023

Differences in diversity and community assembly processes between planktonic and benthic diatoms in the upper reach of the Jinsha River, China

Comparing spatio-temporal patterns between planktonic and benthic algae is helpful for understanding their associations and differences. However, such studies are still rare especially in large rivers. We used a dataset collected in the upper reach of the Jinsha River in different seasons to explore biodiversity and assembly processes of planktonic and benthic diatom assemblages. We found that planktonic and benthic diatoms presented different seasonal variation in species richness and community compositions. We also found evidence that planktonic and benthic diatoms were coupled in the summer. Planktonic diatom assemblages were mainly affected by spatial processes via directional spatial dispersal, especially in the summer. By comparison, benthic diatom assemblages were more affected by environmental processes. Our findings suggest that mass effect and species sorting paradigms explain the assembly processes of planktonic and benthic diatom assemblages, respectively, but the explanatory powers of these two paradigms vary seasonally. To effectively monitor and assess ecological conditions of large rivers, we recommend using benthic algae as a biotic indicator group as they had stronger correlations with environmental factors.Peer reviewe

Quantitative risk assessment system (QRAS)

A quantitative risk assessment system (QRAS) builds a risk model of a system for which risk of failure is being assessed, then analyzes the risk of the system corresponding to the risk model. The QRAS performs sensitivity analysis of the risk model by altering fundamental components and quantifications built into the risk model, then re-analyzes the risk of the system using the modifications. More particularly, the risk model is built by building a hierarchy, creating a mission timeline, quantifying failure modes, and building/editing event sequence diagrams. Multiplicities, dependencies, and redundancies of the system are included in the risk model. For analysis runs, a fixed baseline is first constructed and stored. This baseline contains the lowest level scenarios, preserved in event tree structure. The analysis runs, at any level of the hierarchy and below, access this baseline for risk quantitative computation as well as ranking of particular risks. A standalone Tool Box capability exists, allowing the user to store application programs within QRAS

Sphingosine-1-phosphate promotes the differentiation of human umbilical cord mesenchymal stem cells into cardiomyocytes under the designated culturing conditions

<p>Abstract</p> <p>Background</p> <p>It is of growing interest to develop novel approaches to initiate differentiation of mesenchymal stem cells (MSCs) into cardiomyocytes. The purpose of this investigation was to determine if Sphingosine-1-phosphate (S1P), a native circulating bioactive lipid metabolite, plays a role in differentiation of human umbilical cord mesenchymal stem cells (HUMSCs) into cardiomyocytes. We also developed an engineered cell sheet from these HUMSCs derived cardiomyocytes by using a temperature-responsive polymer, poly(N-isopropylacrylamide) (PIPAAm) cell sheet technology.</p> <p>Methods</p> <p>Cardiomyogenic differentiation of HUMSCs was performed by culturing these cells with either designated cardiomyocytes conditioned medium (CMCM) alone, or with 1 μM S1P; or DMEM with 10% FBS + 1 μM S1P. Cardiomyogenic differentiation was determined by immunocytochemical analysis of expression of cardiomyocyte markers and patch clamping recording of the action potential.</p> <p>Results</p> <p>A cardiomyocyte-like morphology and the expression of α-actinin and myosin heavy chain (MHC) proteins can be observed in both CMCM culturing or CMCM+S1P culturing groups after 5 days' culturing, however, only the cells in CMCM+S1P culture condition present cardiomyocyte-like action potential and voltage gated currents. A new approach was used to form PIPAAm based temperature-responsive culture surfaces and this successfully produced cell sheets from HUMSCs derived cardiomyocytes.</p> <p>Conclusions</p> <p>This study for the first time demonstrates that S1P potentiates differentiation of HUMSCs towards functional cardiomyocytes under the designated culture conditions. Our engineered cell sheets may provide a potential for clinically applicable myocardial tissues should promote cardiac tissue engineering research.</p