Vibrational Spectroscopy Can Be Vulnerable to Adversarial Attacks.

Nondestructive detection methods based on vibrational spectroscopy have been widely used in many critical applications in a variety of fields such as the chemical industry, pharmacy, national defense, security, and so on. As these methods/applications rely on machine learning models for data analysis, studying the threats associated with adversarial examples in vibrational spectroscopy and defenses against them is of great importance. In this paper, we propose a novel adversarial method to attack vibrational spectroscopy, named SynPat, where synthetic peaks produced by a physical model are placed at key locations to form adversarial perturbations.

Unactuated and Actuated States Simultaneously Constrained Optimal Trajectory Planning-Based Path-Following Control for Underactuated Robots.

For underactuated robots working in complex environments, an important objective is to drive all variables (particularly for unactuated end-effectors) to move along the specific path and restrict positions/velocities to avoid obstacles, rather than using only point-to-point control. Unfortunately, most path planning methods are only suitable to fully actuated systems or depend on linearized models. The main motivations of our work are to directly fulfill motion constraints and achieve path following for both actuated and unactuated states (e.

Mind the Gap: Learning Modality-Agnostic Representations With a Cross-Modality UNet.

Cross-modality recognition has many important applications in science, law enforcement and entertainment. Popular methods to bridge the modality gap include reducing the distributional differences of representations of different modalities, learning indistinguishable representations or explicit modality transfer. The first two approaches suffer from the loss of discriminant information while removing the modality-specific variations.

Reconstructing Randomly Masked Spectra Helps DNNs Identify Discriminant Wavenumbers.

Nondestructive detection methods, based on vibrational spectroscopy, are vitally important in a wide range of applications including industrial chemistry, pharmacy and national defense. Recently, deep learning has been introduced into vibrational spectroscopy showing great potential. Different from images, text, etc.

Concurrent Learning-Based Adaptive Control of Underactuated Robotic Systems With Guaranteed Transient Performance for Both Actuated and Unactuated Motions.

With the wide applications of underactuated robotic systems, more complex tasks and higher safety demands are put forward. However, it is still an open issue to utilize "fewer" control inputs to satisfy control accuracy and transient performance with theoretical and practical guarantee, especially for unactuated variables. To this end, for underactuated robotic systems, this article designs an adaptive tracking controller to realize exponential convergence results, rather than only asymptotic stability or boundedness; meanwhile, unactuated states exponentially converge to a small enough bound, which is adjustable by control gains.

A Reinforcement Learning-Based Strategy of Path Following for Snake Robots with an Onboard Camera.

For path following of snake robots, many model-based controllers have demonstrated strong tracking abilities. However, a satisfactory performance often relies on precise modelling and simplified assumptions. In addition, visual perception is also essential for autonomous closed-loop control, which renders the path following of snake robots even more challenging.

A Novel Learning-Based Trajectory Generation Strategy for a Quadrotor.

In this article, a learning-based trajectory generation framework is proposed for quadrotors, which guarantees real-time, efficient, and practice-reliable navigation by online making human-like decisions via reinforcement learning (RL) and imitation learning (IL). Specifically, inspired by human driving behavior and the perception range of sensors, a real-time local planner is designed by combining learning and optimization techniques, where the smooth and flexible trajectories are online planned efficiently in the observable area. In particular, the key problems in the framework, temporal optimality (time allocation), and spatial optimality (trajectory distribution) are solved by designing an RL policy, which provides human-like commands in real-time (e.

Neural Network-Based Hybrid Three-Dimensional Position Control for a Flapping Wing Aerial Vehicle.

This article presents a novel neural network-based hybrid mode-switching control strategy, which successfully stabilizes the flapping wing aerial vehicle (FWAV) to the desired 3-D position. First, a novel description for the dynamics, resolved in the proposed vertical frame, is proposed to facilitate further position loop controller design. Then, a radial base function neural network (RBFNN)-based adaptive control strategy is proposed, which employs a switching strategy to keep the system away from dangerous flight conditions and achieve efficient flight.

Low concentrations of the antidepressant venlafaxine affect courtship behaviour and alter serotonin and dopamine systems in zebrafish (Danio rerio).

Venlafaxine, a serotonin-noradrenaline reuptake inhibitor, is a widely used antidepressant drug routinely detected in aquatic environments. However, its potential impact on courtship behaviour in zebrafish is unknown. We tested the hypothesis that venlafaxine disrupts brain monoamine levels and molecular responses essential for courtship behaviour in zebrafish.

Neuroadaptive Control for Complicated Underactuated Systems With Simultaneous Output and Velocity Constraints Exerted on Both Actuated and Unactuated States.

Due to limited workspace and safety requirements for practical underactuated mechanical systems, it is necessary to restrict all to-be-controlled variables and their velocities within preset ranges, avoid collisions/overshoots, and improve braking performance. However, due to fewer available control inputs, it is quite challenging to ensure error elimination and full-state constraints for both actuated/unactuated variables, including displacements/angles and their derivatives (i.e.

Adaptive Fuzzy Control for a Class of MIMO Underactuated Systems With Plant Uncertainties and Actuator Deadzones: Design and Experiments.

In the field of modern industrial engineering, many mechanical systems are underactuated, exhibiting strong nonlinear characteristics and high flexibility. However, the lack of control inputs brings about many difficulties for controller design and stability/convergence analysis., some unavoidable practical issues, e.

An automated vertical drift correction algorithm for AFM images based on morphology prediction.

The atomic force microscope (AFM) has become a powerful tool in many fields. However, environmental noise and other disturbances are very likely to cause the AFM probe to vibrate, which lead to vertical drift in AFM imaging and limit its further application. Therefore, to correct image distortion caused by vertical drift, a morphology prediction based image correction algorithm is proposed in this paper.

Integrated navigation of GPS/INS based on fusion of recursive maximum likelihood IMM and Square-root Cubature Kalman filter.

Information fusion of the GPS/INS integrated system is always related to characteristics of the inertial system and the sensor feature, yet prior knowledge is still difficult to obtain in real applications. To deal with the uncertainty of error covariance and state noise in vehicle navigation, this paper presents a novel approach, wherein the integration of Square-root Cubature Kalman Filters (SCKF) and Interacting Multiple Model (IMM) are also introduced. In the framework of IMM, the SCKFs with different covariance are designed to reflect various vehicle dynamics.

A high-speed atomic force microscopy with super resolution based on path planning scanning.

An atomic force microscopy generally adopts a raster scanning method to obtain the image of the sample morphology. However, the raster method takes too much time on the base part without focusing enough on the object, thereby restricting the scanning speed of an AFM. To solve this problem, this paper proposes a novel path planning based scanning method to achieve high-speed scanning with super resolution for AFMs.

Rongchang and Xifeng capsules suppress pentylenetetrazole-induced seizures and change rest/wake behavior in zebrafish larvae.

Objective: To evaluate the effects of Rongchang capsule and Xifeng capsule on pentylenetetrazole- induced epilepsy in zebrafish larvae and to explore the possible mechanisms behind their actions.

Methods: We utilized a trajectory tracking system to monitor seizures in zebrafish larva to confirm that certain concentrations of Rongchang capsule and Xifeng capsule produce antiepileptic effects. c-fos expression was assessed by quantitative reverse transcription-polymerase chain reaction to validate the efficacy of the capsules.

A Path-Integral-Based Reinforcement Learning Algorithm for Path Following of an Autoassembly Mobile Robot.

Reinforcement learning (RL) combined with deep neural networks has led to a number of great achievements for robot control in virtual computer environments, where sufficient data can be obtained without any difficulty to train various models. However, thus far, only few and relatively simple tasks have been accomplished for practical robots, which is mainly caused by the following two reasons. First, training with real robots, especially with dynamic systems, is too complicated to be fully and accurately represented in simulations.

Neural Network-Based Adaptive Antiswing Control of an Underactuated Ship-Mounted Crane With Roll Motions and Input Dead Zones.

As a type of indispensable oceanic transportation tools, ship-mounted crane systems are widely employed to transport cargoes and containers on vessels due to their extraordinary flexibility. However, various working requirements and the oceanic environment may cause some uncertain and unfavorable factors for ship-mounted crane control. In particular, to accomplish different control tasks, some plant parameters (e.

The effects of fluorene-9-bisphenol on female zebrafish (Danio rerio) reproductive and exploratory behaviors.

Endocrine disruptor chemicals induce adverse effects to animals' development, reproduction and behavior in environment. We investigated the effects of fluorene-9-bisphenol (BHPF), one substitute of bisphenol A, on courtship behavior and exploratory behavior of adult zebrafish. Customized apparatus was used to evaluate courtship behavior.

Visual Servoing of Wheeled Mobile Robots Without Desired Images.

This paper proposes a novel monocular visual servoing strategy, which can drive a wheeled mobile robot to the desired pose without a prerecorded desired image. Compared with existing methods that adopt the teaching pattern for visual regulation, this scheme can still work well in the situation that the desired image has not been previously acquired. Thus, with the aid of this method, it is more convenient for mobile robots to execute visual servoing tasks.

Behavioural effect of low-dose BPA on male zebrafish: Tuning of male mating competition and female mating preference during courtship process.

The ubiquity of environmental pollution by endocrine disrupting chemicals (EDCs) such as bisphenol A (BPA) is progressively considered as a major threat to aquatic ecosystems worldwide. Numerous toxicological studies have proved that BPA are hazardous to aquatic environment, along with alterations in the development and physiology of aquatic vertebrates. However, generally, there is a paucity in knowledge of behavioural and physiological effects of BPA with low concentration, for example, 0.

Sterilization of polydimethylsiloxane surface with Chinese herb extract: a new antibiotic mechanism of chlorogenic acid.

Coating of polydimethylsiloxane (PDMS) surface with a traditional Chinese herb extract chlorogenic acid (CA) solves the contemporary problem of sterilization of PDMS surface. The E. coli grows slower and has a higher death rate on the CA-coated PDMS surfaces.

Stacked Multilayer Self-Organizing Map for Background Modeling.

In this paper, a new background modeling method called stacked multilayer self-organizing map background model (SMSOM-BM) is proposed, which presents several merits such as strong representative ability for complex scenarios, easy to use, and so on. In order to enhance the representative ability of the background model and make the parameters learned automatically, the recently developed idea of representative learning (or deep learning) is elegantly employed to extend the existing single-layer self-organizing map background model to a multilayer one (namely, the proposed SMSOM-BM). As a consequence, the SMSOM-BM gains several merits including strong representative ability to learn background model of challenging scenarios, and automatic determination for most network parameters.

Development of functional biointerfaces by surface modification of polydimethylsiloxane with bioactive chlorogenic acid.

The effect of physicochemical surface properties and chemical structure on the attachment and viability of bacteria and mammalian cells has been extensively studied for the development of biologically relevant applications. In this study, we report a new approach that uses chlorogenic acid (CA) to modify the surface wettability, anti-bacterial activity and cell adhesion properties of polydimethylsiloxane (PDMS). The chemical structure of the surface was obtained by X-ray photoelectron spectroscopy (XPS), the roughness was measured by atomic force microscopy (AFM), and the water contact angle was evaluated for PDMS substrates both before and after CA modification.

Genetic polymorphisms in CYP3A4 are associated with withdrawal symptoms and adverse reactions in methadone maintenance patients.

Aim: Methadone maintenance therapy is one of the standard treatments for heroin addiction. The isozyme CYP3A4 of the CYP system is one of the metabolic enzymes, as well as CYP2B6, responsible for the metabolism of methadone. The aim of the present study is to evaluate the potential use of genetic polymorphisms in CYP3A4 as biomarkers for the prediction of methadone treatment responses.

Note: A novel atomic force microscope fast imaging approach: variable-speed scanning.

Imaging speed is one of the key factors limiting atomic force microscope's (AFM) wide applications. To improve its performance, a variable-speed scanning (VSS) method is designed in this note for an AFM. Specifically, in the VSS mode, the scanning speed is tuned online according to the feedback information to properly distribute imaging time along sample surface.