2.5D multi-view gait recognition based on point cloud registration

This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM

Painful faces-induced attentional blink modulated by top-down and bottom-up mechanisms

Pain-related stimuli can capture attention in an automatic (bottom up) or intentional (top down) fashion. Previous studies have examined attentional capture by pain-related information using spatial attention paradigms that involve mainly a bottom up mechanism. In the current study, we investigated the pain information-induced attentional blink (AB) using a rapid serial visual presentation (RSVP) task, and compared the effects of task-irrelevant and task-relevant pain distractors. Relationships between accuracy of target identification and individual traits (i.e., empathy and catastrophizing thinking about pain) were also examined. The results demonstrated that task-relevant painful faces had a significant pain information-induced AB effect, whereas taskirrelevant faces showed a near-significant trend of this effect, supporting the notion that pain-related stimuli can influence the temporal dynamics of attention. Furthermore, we found a significant negative correlation between response accuracy and pain catastrophizing score in task-relevant trials. These findings suggest that active scanning of environmental information related to pain produces greater deficits in cognition than does unintentional attention toward pain, which may represent the different ways in which healthy individuals and patients with chronic pain process pain-relevant information. These results may provide insight into the understanding of maladaptive attentional processing in patients with chronic pain

Poly[μ4-succinato-μ2-succinato-bis[diamminecopper(II)]]

In the title compound, [Cu(C4H4O4)(NH3)2]n, the Cu atom is coordinated by the N atoms of two ammonia mol­ecules and four O atoms from three different succinate ligands in a highly distorted octa­hedral geometry. The Cu atom and the C and O atoms of the succinate ligands lie on a mirror plane. Two adjacent CuO4N2 octa­hedra share one common O–O edge, forming a Cu2O6N4 biocta­hedron with a Cu⋯Cu separation of 3.524 (2) Å. Neighboring biocta­hedra are connected by bis-unidentate succinate anions in the a-axis direction, while in the c-axis direction biocta­hedra are connected by bis-bidentate succinate anions, leading to an infinite two-dimensional network structure. These networks are further connected along the a-axis direction by hydrogen bonds between ammonia ligands and carboxyl­ate O atoms of neighboring network layers, forming a three-dimensional lamellar structure

Depression Shows Divergent Effects on Evoked and Spontaneous Pain Behaviors in Rats

Although it has been accepted that depression and pain are common comorbidities, their interaction is not fully understood. The present study was aimed to investigate the effects of depression on both evoked pain behavior (thermal-induced nociception and hyperalgesia) and spontaneous pain behavior (formalin pain) in rats. An unpredictable chronic mild stress (UCMS) paradigm was employed to develop a classical depression. The emotional behaviors were assessed by sucrose preference test, open field test, and elevated plus-maze test. The results showed that the depressed rats always exhibited stronger tolerance to noxious thermal stimulation under both normal and complete Freund's adjuvant (CFA)-induced chronic pain conditions, when compared to nondepressed animals. Interestingly, the spontaneous nociceptive behaviors induced by formalin injection were significantly enhanced in rats exposed to UCMS in comparison to those without UCMS. Systemic administration of antidepressant fluoxetine significantly restored the nociceptive behaviors to normal level in depressed animals. An additional finding was that the inflammatory rats tended to display depressive-like behaviors without being exposed to UCMS. These results demonstrated that depression can have different effects on stimulus-evoked pain and spontaneous pain, with alleviation in the former while aggravation in the latter

Neuronal nociceptive responses in thalamocortical pathways

The sensation of pain is critical for the survival of animals and humans. However, the brain mechanisms underlying pain perception remain largely unknown. How does the brain decode the pain-evoked activity into a particular sensory experience? Over the past decade, attempts have been made to answer these questions by employing electrophysiological, functional brain imaging, and behavioral approaches, and some basic properties of pain formation have been revealed. Researchers have gradually recognized that there exists a distributed neural network that participates in the transmission and processing of pain information. These studies will further guide the development of more effective treatment for many disorders such as chronic pain

Optimization of Three-dimensional Face Recognition Algorithms in Financial Identity Authentication

Identity authentication is one of the most basic components in the computer network world. It is the key technology of information security. It plays an important role in the protection of system and data security. Biometric recognition technology provides a reliable and convenient way for identity authentication. Compared with other biometric recognition technologies, face recognition has become a hot research topic because of its convenience, friendliness and easy acceptance. With the maturity and progress of face recognition technology, its commercial application has become more and more widespread. Internet finance, e-commerce and other asset-related areas have begun to try to use face recognition technology as a means of authentication, so people’s security needs for face recognition systems are also increasing. However, as a biometric recognition system, face recognition system still has inherent security vulnerabilities and faces security threats such as template attack and counterfeit attack. In view of this, this paper studies the application of threedimensional face recognition algorithm in the field of financial identity authentication. On the basis of feature extraction of face information using neural network algorithm, K-L transform is applied to image high-dimensional vector mapping to make face recognition clearer. Thus, the image loss can be reduced