Microfluidic immobilization and subcellular imaging of developing <Emphasis Type="Italic">Caenorhabditis elegans</Emphasis>

Caenorhabditis elegans has been an essential model organism in the fields of developmental biology, neuroscience, and aging. However, these areas have been limited by our ability to visualize and track individual C. elegans worms, especially at the subcellular scale, over the course of their lifetime. Here we present a microfluidic device to culture individual C. elegans in parallel throughout post-embryonic development. The device allows for periodic mechanical immobilization of the worm, enabling 3D imaging at subcellular precision. The immobilization is sufficient to enable fluorescence recovery after photobleaching (FRAP) measurements on organelles and other substructures within the same specific cells throughout larval development, without the use of chemical anesthetics. Using this device, we measure FRAP recovery of two nucleolar proteins in specific intestinal cells within the same worms during larval development. We show that these proteins exhibit different fluorescence recovery as the worm grows, suggesting differential protein interactions during development. We anticipate that this device will help expand the possible uses of C. elegans as a model organism, enabling its use in addressing fundamental questions at the subcellular scale.     

Optimization of design and characterization of a novel micro-pumping system with peristaltic motion

In this work, we present a novel design of peristalsis based micro pump with optimized fluid chambers possessing improved discharge efficiency per unit volume of the pumping architecture and reduced reverse flow. Such designs are very often important from the standpoint of blood cell sorting assays where a full delivery of fluid containment within the pumping chamber is critical. The paper uses FLUENT and COMSOL simulations to look at the fluid flow within the pumping chamber due to the deflecting actuator membrane during pumping cycle. The resulting effect of fluid-membrane interaction has been evaluated on different chamber designs for observing the lateral velocity distribution profile of fluid in the connecting channels. It has been observed through particle image velocimetry (PIV) that the optimized design has minimized chamber retainability with maximum deflection of the actuator membrane and minimum reverse flow component. Optimized geometrical profile formulated above was seen to allow the maximum contact area between actuating membrane and fluid containment thus reducing the problem of fluid retainability. Other experimental studies show that the new design has much lower percentage retainability of biological and other fluids contained within the chambers which makes it a comparatively high efficiency micropumping system with respect to the conventional design with circular membrane and chambers. The experimental evaluation of the new micro pump design has shown its least count to be 0.1 μl/min which is very well comparing with some of the other micropumping mechanisms like electro-osmotic, magneto-hydrodynamic mechanisms (Laser and Santiago in J Micromech Microeng 14:35, 2004; Iverson et al. 2008) and additionally provides better discharge efficiency per unit volume of the pumping architecture, lower retainability, minimized reverse flow and precise pumping of fluids.     

Model of community emergence in weighted social networks

Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.     

Driving mechanisms of CM-scaled PDMS boats of respective close and open reservoirs

A floating solid object may have a spontaneous motion on a water surface when a liquid, which has a surface tension lower than water, exits the solid object and has contact with water. This motion may be induced due to the difference between surface tensions of water and the liquid. In order to interpret this motion, it is important to know how the liquid exits the solid object. In this article, we reported in situ observation of exchange processes of water and isopropyl alcohol (IPA) inside both close and open reservoirs of cm-scaled polydimethylsiloxane (PDMS) boats. Based on this observation and force analysis, we interpreted driving mechanisms of these boats. We found that the exchange processes may be different in the PDMS boats of respective close and open reservoirs. The PDMS boat of a close reservoir might have a bubble trapped in its reservoir during the motion. This bubble slowed down the exiting process of the IPA from the reservoir, made the motion last longer, and enabled the boat to have a longer travel distance. Also, such a boat had gurgling-like motions (i.e., approximately periodic motions of deceleration and acceleration) after the majority of the IPA had exited the reservoir. The speeds of this boat had an order of 1?cm/s. On the other hand, neither bubbles nor gurgling-like phenomena were found in the motions of the PDMS boat of an open reservoir. The speeds of this boat were in the order of 1?cm/s as well. In addition, based on observed exiting processes of the IPA and experimentally determined speed-time relationships, we also set up a simple model to find force?Ctime relationships. Furthermore, we investigated the exiting process when the open reservoir of the cm-scaled PDMS boat was shallow. We found that, depending on the values of the height difference, h, between the bottom of the reservoir and the water surface outside the reservoir, three different phenomena might appear: (1) if h????1.33?mm, then the reservoir was empty at the end of the test and no water flowed into the reservoir during the test; (2) if 1.3?mm?<?h????2.3?mm, then the reservoir was empty at the end of the test while water flowed into the reservoir during the test; and (3) if 2.3?mm?<?h????3.0?mm, then the reservoir was filled by water at the end of the test. The difference in the filling results was induced by the interplay among Marangoni effect, free convection, and recovery of a hollow spot by surrounding water. The corresponding findings interpreted the exiting process of the IPA observed in the open reservoir of a mm-scaled SU-8 boat that we have previously developed, and also explained the filling result in the open reservoir of a PDMS boat.     

Mathematical modeling of endocrine regulation subject to circadian rhythm

The 2017 Nobel Prize in Physiology or Medicine awarded for discoveries of molecular mechanisms controlling the circadian rhythm has called attention to the challenging area of nonlinear dynamics that deals with synchronization and entrainment of oscillations. Biological circadian clocks keep time in living organisms, orchestrating hormonal cycles and other periodic rhythms. The periodic oscillations of circadian pacemakers are self-sustained; at the same time, they are entrainable by external periodic signals that adjust characteristics of autonomous oscillations. Whereas modeling of biological oscillators is a well-established research topic, mathematical analysis of entrainment, i.e. the nonlinear phenomena imposed by periodic exogenous signals, remains an open problem. Along with sustained periodic rhythms, periodically forced oscillators can exhibit various “irregular” behaviors, such as quasiperiodic or chaotic trajectories.This paper presents an overview of the mathematical models of circadian rhythm with respect to endocrine regulation, as well as biological background. Dynamics of the human endocrine system, comprising numerous glands and hormones operating under neural control, are highly complex. Therefore, only endocrine subsystems (or axes) supporting certain biological functions are usually studied. Low-order dynamical models that capture the essential characteristics and interactions between a few hormones can than be derived. Goodwin’s oscillator often serves as such a model and is widely regarded as a prototypical biological oscillator. A comparative analysis of forced dynamics arising in two versions of Goodwin’s oscillator is provided in the present paper: the classical continuous oscillator and a more recent impulsive one, capturing e.g. pulsatile secretion of hormones due to neural regulation. The main finding of this study is that, while the continuous oscillator is always forced to a periodic solution by a sufficiently large exogenous signal amplitude, the impulsive one commonly exhibits a quasiperiodic or chaotic behavior due to non-smooth dynamics in entrainment.     

Conceptual Combination with PUNC

Noun–noun compounds play a key role in the growth of language. In this article we present a system for producing and understanding noun–noun compounds (PUNC). PUNC is based on the Constraint theory of conceptual combination and the C ³ model. The new model incorporates the primary constraints of the Constraint theory in an integrated fashion, creating a cognitively plausible mechanism of interpreting noun–noun phrases. It also tries to overcome algorithmic limitations of the C ³ model in being more efficient in its computational complexity, and deal with a wider span of empirical phenomena, such as dimensions of word familiarity. We detail the model, including knowledge representation and interpretation production mechanisms. We show that by integrating the constraints of the Constraint theory of conceptual combination and prioritizing the knowledge available within a concept's representation, PUNC can not only generate interpretations that reflect those produced by people, but also mirror the differences in processing times for understanding familiar, similar and novel word combinations.     

基于高斯过程动态模型的人体节奏运动合成

提出一种新的基于高斯过程动态模型的节奏转移方法。该方法能够准确、有效地将现有运动中的节奏信息转移到新的运动中去,适用于各种不同类型的运动。首先,使用短时（short term）PCA计算源运动的节奏点,组合3种重要的运动特征求解目标运动的特征点;然后,使用动态规划算法来找到两者之间的最佳匹配,最大化减少计算时间及对目标运动的修改;最后,使用高斯过程动态模型对目标运动进行学习,并在隐空间进行节奏化插值,最终合成新的节奏化运动。     

Can k-NN imputation improve the performance of C4.5 with small software project data sets? A comparative evaluation

Missing data is a widespread problem that can affect the ability to use data to construct effective prediction systems. We investigate a common machine learning technique that can tolerate missing values, namely C4.5, to predict cost using six real world software project databases. We analyze the predictive performance after using the k-NN missing data imputation technique to see if it is better to tolerate missing data or to try to impute missing values and then apply the C4.5 algorithm. For the investigation, we simulated three missingness mechanisms, three missing data patterns, and five missing data percentages. We found that the k-NN imputation can improve the prediction accuracy of C4.5. At the same time, both C4.5 and k-NN are little affected by the missingness mechanism, but that the missing data pattern and the missing data percentage have a strong negative impact upon prediction (or imputation) accuracy particularly if the missing data percentage exceeds 40%.     

Microprocessor—controlled driving unit for artificial hearts

A driving unit for artificial hearts has been produced. This unit uses sodium solution for the transmission of force between the power source and the artificial ventricle instead of the commonly used compressed air and thus avoids the danger of an air embolism. The power source of the hydraulic driving unit is an electromagnet; its armature drives a rolling membrane pump (safety chamber) which moves the transmission fluid (sodium solution) to the artificial ventricle (ellipsoid heart). The incompressible connection between the safety chamber and the ellipsoid heart allows direct control of the membrane motion in the ellipsoid heart and of the volume of pumped blood by measuring the armature stroke. The stroke is measured continuously with an optical position sensor; preprogrammable positions determine the systole end and diastole end respectively, so that the membrane need not strike the housing and is not exposed to additional stress. This volume-controlled mode is characterized by automatic selfregulation according to Starling's law.The microcomputer is programmed in a two-level technique. In the interrupt level the solenoid current is calculated according to the operating mode and armature position every 10 ms which is sufficient to simulate continuous operation. In the main-program level every operational parameter (maximum force, systole end, diastole end; systole duration and beat frequency for the frequency-fixing mode) is displayed on the CRT and can be changed via keyboard entry without any interruption in pumping.The durations of systole and diastole, respectively, are determined by the pumping force, the friction in the hydraulic transmission system and the preload and afterload respectively. The preload and afterload can be calculated from a time-force relation without invasive measurements.The driving unit has shown its haemodynamic efficiency in several in vivo experiments and has been running for 8 months in an in vitro durability test.     

Evolving Self-Organizing Behaviors for a Swarm-Bot

In this paper, we introduce a self-assembling and self-organizing artifact, called a swarm-bot, composed of a swarm of s-bots, mobile robots with the ability to connect to and to disconnect from each other. We discuss the challenges involved in controlling a swarm-bot and address the problem of synthesizing controllers for the swarm-bot using artificial evolution. Specifically, we study aggregation and coordinated motion of the swarm-bot using a physics-based simulation of the system. Experiments, using a simplified simulation model of the s-bots, show that evolution can discover simple but effective controllers for both the aggregation and the coordinated motion of the swarm-bot. Analysis of the evolved controllers shows that they have properties of scalability, that is, they continue to be effective for larger group sizes, and of generality, that is, they produce similar behaviors for configurations different from those they were originally evolved for. The portability of the evolved controllers to real s-bots is tested using a detailed simulation model which has been validated against the real s-bots in a companion paper in this same special issue.     

Object joint detection and tracking using adaptive multiple motion models

This paper deals with the problem of detecting objects that may switch between different motion models. In order to accurately detect these moving objects taking into account possible changing motion models, we propose an adaptive multi-motion model in the joint detection and tracking (JDT) framework. The proposed technique differs from the existing JDT-based methods mainly in two ways. First we express the solution in the JDT framework via a formulation in the multiple motion model setting. Second, we introduce a new motion model prediction function which exploits the correlation between the motion model and object kinematic state. Experiments on both synthetic and real videos demonstrate that the JDT method employing the proposed adaptive multi-motion model can detect objects more accurately than the existing peer methods when objects change their motion models.     

A Fourier analysis of spurious mechanisms and locking in the finite element method

A Fourier analysis technique is used to examine spurious mechanisms and the element locking phenomena engendered by different finite element discretizations. It is shown that these phenomena can be identified by examining the uncoupled discrete Fourier operators and corresponding characteristic equations and are caused, in terms of discrete filter concepts, by either a spurious mode carrier or by violating the unlocking condition specified in the paper. The analysis is performed for two simple problems: wave propagation in a bar and vibration of a Timoshenko beam which, when discretized by linear shape functions, succinctly manifest the two phenomena as being directly traceable to specific components of the finite element discretizations.     

ICA方法用于脑电信号α波提取的研究

为在有效提取闭眼脑电信号α波的同时能够很好地保留原始信号中的其余信息,采用独立分量分析方法提取闭眼脑电信号中的α波。构造一组频率在α波频率之间的正弦和余弦信号作为对α波的参考信号,然后把这些信号以及实测闭眼脑电信号作为ICA混合矩阵的输入端,采用fastICA 算法进行信号分离,实现对α波的分离和提取,并进一步对所提取的α波进行了功率谱分析。结果表明,分离出的信号频率集中在8~13 Hz之间,完全符合α波形的特点,且去除α波后的其余信号与原始信号相关系数达到0.942,说明有效地保留了原始信号的其余信息。     

Spatio-temporal organization of a cellular automaton model for computer network

It was unveiled by Ren et al. [Comput. Phys. Comm. (2001)] that congestion transition emerges in cellular automaton models for computer network and this NaSch network model with Q=1 has similar behaviours as the NaSch traffic model with maximum velocity v_max=1. For these two NaSch models, the main difference lies in a node cell contained in the NaSch network model. In this paper, we will focus on our further investigation on spatio-temporal organization of the NaSch network model. More interesting phenomena of phase transition are discovered. Firstly, fundamental diagram illustrates that when Q>1 for the NaSch network model it is significantly different from its counterpart, i.e. the NaSch traffic model in a road traffic system. The addition of a node cell, which is allowed to have more than one packets, will lead to generating a new phase. Secondly, in order to characterize phase transition occurred in the NaSch network model, an order parameter is presented with the use of the time average density of nearest-neighbor pairs m. The computational results obtained show that criticality will disappear in a strict sense if noise exists. Finally, two other numerical features, i.e. spatial correlation functions G(r) and relaxation times τ, are analyzed so as to deeply describe behaviours near critical points.     

Integrating human observer inferences into robot motion planning

Our goal is to enable robots to produce motion that is suitable for human–robot collaboration and co-existence. Most motion in robotics is purely functional, ideal when the robot is performing a task in isolation. In collaboration, however, the robot’s motion has an observer, watching and interpreting the motion. In this work, we move beyond functional motion, and introduce the notion of an observer into motion planning, so that robots can generate motion that is mindful of how it will be interpreted by a human collaborator. We formalize predictability and legibility as properties of motion that naturally arise from the inferences in opposing directions that the observer makes, drawing on action interpretation theory in psychology. We propose models for these inferences based on the principle of rational action, and derive constrained functional trajectory optimization techniques for planning motion that is predictable or legible. Finally, we present experiments that test our work on novice users, and discuss the remaining challenges in enabling robots to generate such motion online in complex situations.     

Energy-Efficient Trajectory Generation for Space Manipulators with Reaction Wheels under a Fixed Base Orientation

We have developed an Energy-Efficient Trajectory Generation Algorithm for space manipulators with reaction wheels under the constraint of fixed base orientation. By defining the manipulator joint trajectories as B-splines and imposing a constraint that the reaction wheel should precisely compensate for the rotational disturbance caused by the manipulator motion, we reformulate an optimal control problem as a constrained parameter optimization problem where the cost function is defined as the total energy consumption of the motors. To address the problem with the direct method, we derive a novel analytic gradient computation algorithm which recursively computes the torque sensitivity and determines the reaction wheel motion by solving the momentum conservation constraint. The complexity of the gradient computation is O(n ² N _I ) where n is the number of bodies and N _I is the number of integration points. We show the effectiveness of the suggested method by two examples of trajectory optimization. In the first case, we verify the optimality of the solution trajectory using the planar space manipulator model with a two-joint arm and a reaction wheel. In the second case, we optimize the target berthing motion of the spatial space manipulator model with a seven-joint arm and three reaction wheels.     

Temperature effect of a-Si:H pH-ISFET

In this article, the hydrogenated amorphous silicon (a-Si:H) acted as the sensitive membrane of pH-ISFET. The a-Si:H membrane was deposited by plasma-enhanced chemical vapor deposition (PECVD). In our experiment, we use a Keithley 236 Semiconductor Parameter Analyzer to measure the drain-source current (I_DS) vs. gate voltage (V_G) curve of a-Si:H ISFET over a pH range from 1 to 7 and a temperature range from 25°C to 65°C. According to our experimental results, we can observe that the pH sensitivity of a-Si:H ISFET is proportional to the operating temperature. And then, we can also find that the temperature coefficient of a-Si:H ISFET is proportional to the pH value of buffer solution.