A unified psychological space for human perception of physical and social events.

One of the great feats of human perception is the generation of quick impressions of both physical and social events based on sparse displays of motion trajectories. Here we aim to provide a unified theory that captures the interconnections between perception of physical and social events. A simulation-based approach is used to generate a variety of animations depicting rich behavioral patterns. Human experiments used these animations to reveal that perception of dynamic stimuli undergoes a gradual transition from physical to social events. A learning-based computational framework is proposed to account for human judgments. The model learns to identify latent forces by inferring a family of potential functions capturing physical laws, and value functions describing the goals of agents. The model projects new animations into a sociophysical space with two psychological dimensions: an intuitive sense of whether physical laws are violated, and an impression of whether an agent possesses intentions to perform goal-directed actions. This derived sociophysical space predicts a meaningful partition between physical and social events, as well as a gradual transition from physical to social perception. The space also predicts human judgments of whether individual objects are lifeless objects in motion, or human agents performing goal-directed actions. These results demonstrate that a theoretical unification based on physical potential functions and goal-related values can account for the human ability to form an immediate impression of physical and social events. This ability provides an important pathway from perception to higher cognition.

Exploring biological motion perception in two-stream convolutional neural networks.

Visual recognition of biological motion recruits form and motion processes supported by both dorsal and ventral pathways. This neural architecture inspired the two-stream convolutional neural network (CNN) model, which includes a spatial CNN to process appearance information in a sequence of image frames, a temporal CNN to process optical flow information, and a fusion network to integrate the features extracted by the two CNNs and make final decisions about action recognition. In five simulations, we compared the CNN model's performance with classical findings in biological motion perception. The CNNs trained with raw RGB action videos showed weak performance in recognizing point-light actions. Additional transfer training with actions shown in other display formats (e.g., skeletal) was necessary for CNNs to recognize point-light actions. The CNN models exhibited largely viewpoint-dependent recognition of actions, with a limited ability to generalize to viewpoints close to the training views. The CNNs predicted the inversion effect in the presence of global body configuration, but failed to predict the inversion effect driven solely by local motion signals. The CNNs provided a qualitative account of some behavioral results observed in human biological motion perception for fine discrimination tasks with noisy inputs, such as point-light actions with disrupted local motion signals, and walking actions with temporally misaligned motion cues. However, these successes are limited by the CNNs' lack of adaptive integration for form and motion processes, and failure to incorporate specialized mechanisms (e.g., a life detector) as well as top-down influences on biological motion perception.

Raman Spectroscopic Differences between Ephedrine and Pseudoephedrine.

Ephedrine (EPH) and pseudoephedrine (PSE) were studied by micro-Raman spectroscopy and UV resonance Raman spectroscopy excited at 785 and 360 nm, respectively. Raman bands at approximately 245 and 410 cm-1 for ephedrine have apparent differences from the same bands at approximately 215, 265, 350, 450, and 555 cm-1 for pseudoephedrine, and these differences can be applied to distinguish between EPH and PSE. Additionally, density functional theory was used for the Raman calculations to obtain results identical to the experimental spectra. This work is expected to expand the applications of Raman spectroscopy in forensic science.

Learning and Inferring "Dark Matter" and Predicting Human Intents and Trajectories in Videos.

This paper presents a method for localizing functional objects and predicting human intents and trajectories in surveillance videos of public spaces, under no supervision in training. People in public spaces are expected to intentionally take shortest paths (subject to obstacles) toward certain objects (e.g., vending machine, picnic table, dumpster etc.) where they can satisfy certain needs (e.g., quench thirst). Since these objects are typically very small or heavily occluded, they cannot be inferred by their visual appearance but indirectly by their influence on people's trajectories. Therefore, we call them "dark matter", by analogy to cosmology, since their presence can only be observed as attractive or repulsive "fields" in the public space. A person in the scene is modeled as an intelligent agent engaged in one of the "fields" selected depending his/her intent. An agent's trajectory is derived from an Agent-based Lagrangian Mechanics. The agents can change their intents in the middle of motion and thus alter the trajectory. For evaluation, we compiled and annotated a new dataset. The results demonstrate our effectiveness in predicting human intent behaviors and trajectories, and localizing and discovering distinct types of "dark matter" in wide public spaces.

Perception of Human Interaction Based on Motion Trajectories: From Aerial Videos to Decontextualized Animations.

People are adept at perceiving interactions from movements of simple shapes, but the underlying mechanism remains unknown. Previous studies have often used object movements defined by experimenters. The present study used aerial videos recorded by drones in a real-life environment to generate decontextualized motion stimuli. Motion trajectories of displayed elements were the only visual input. We measured human judgments of interactiveness between two moving elements and the dynamic change in such judgments over time. A hierarchical model was developed to account for human performance in this task. The model represents interactivity using latent variables and learns the distribution of critical movement features that signal potential interactivity. The model provides a good fit to human judgments and can also be generalized to the original Heider-Simmel animations (1944). The model can also synthesize decontextualized animations with a controlled degree of interactiveness, providing a viable tool for studying animacy and social perception.

[Analytical method for on-site test of drug precursor chemicals].

Thirteen kinds of common drug precursor chemicals were detected on the spot by transportable Raman spectrometer independently researched and developed. Changing analysis methods, such as the focal position of the instrument, analysis time, external light source, sample containers and the concentration of the analyte, the high quality Raman spectrums were obtained. The study shows that analysis method can be optimized to improve the detection efficiency, LOD (limit of detection) of 1-phenyl-2-acetone, toluene and chloroform was recorded for lower concentrations and the component contents of the mixture have a significant impact on the test results. Selecting the appropriate instrument conditions can be more effective and fast screening of precursor chemicals on site to provide help for those who are engaged in the anti-drug work.

Tunable gel formation by both sonication and thermal processing in a cholesterol-based self-assembly system.

A family of asymmetric cholesterol-based fluorescent organogelators containing naphthalimide, connected by two acylamines and different alkyl-chain spacers, have been designed and prepared. These compounds can gelate a variety of organic solvents with both ultrasound stimuli and general sol-gel processes. The self-assembly and gelling properties of the compounds depend on the length of the alkyl chains and can be controlled by ultrasound stimuli and renewed by a thermodynamic process. The morphologies and surface wetabilities of the xerogels prepared from these gelators are strongly affected by environmental stimuli. The mechanism of the process was investigated by confocal laser scanning microscopy, transmission or scanning electron microscopy, wide-angle X-ray scattering analysis, and rheological experiments. The studies reveal that the cooperation and relative competition of multiple intermolecular interactions, influenced by the sonication or thermal stimulus, are the main contributors for the aggregation or nucleation processes; this results in the macrodifferences in morphology and surface properties. These results provide a deeper understanding of the intermediate transition state of the gel during use of an ultrasound stimulus.

Inclusion of tetracycline hydrochloride within supramolecular gels and its controlled release to bovine serum albumin.

Three amphiphilic 3,4,5-trihydroxybenzoic derivatives with alkyl chains of different lengths were designed and synthesized. A small amount of these compounds can trap a large quantity of the water-soluble drug tetracycline hydrochloride (TH) within a stable gel in aqueous ethanol. Release experiments were carried out with solutions of bovine serum albumin (BSA) and various concentrations of L-isoleucine, L-phenylalanine, and L-tryptophan. The results indicate that the release rate of TH for a BSA solution (10 mg/mL) was faster than that with the other solutions because of the strong interaction between TH and BSA. Furthermore, to gain an insight into the release dynamics, we studied the release ratios as a function of the square root of time (t1/2). During the initial 1.75 h, diffusion is the dominant release process in water, whereas intermolecular interaction controls TH release in the BSA solution.