Agent-based modeling to investigate the disposition effect in financial markets

One of the behavioral patterns that deviate from what is predicted by traditional financial theories is the disposition effect. Although most empirical studies have reported a significant disposition effect, researchers have yet to conduct a conclusive test of thiseffect because a competing hypothesis or confounding effects might explain the documented significance. Thus, we use the tools of computational intelligence, instead of empirical approaches, to explore market behavior. In particular, we allow agents with different investment strategies to interact and to compete with each other in an artificial futures market. We found that the S-shaped value curve proposed by prospect theory may be one of the causes of the observed behavior of the disposition effect. However, rational expectation such as short-term mean reversion can even be more decisive

Understanding the Bloggers’ Continuance Usage: Integrating Flow into the Expectation-Confirmation Theory Information System Model

Blogs are very popular nowadays. Many big website portals, such as Yahoo Blog, PC home Blog, try to offer different functions and personal services to attract the potential users to be their Blog member, because this will bring more advertising income. For the portals, how to obtain users to continue use is very important to survival. Most previous articles focused on investigating system function and information quality issues on Blogs, but these technologies are very steady already. There are fewer studies to discuss the users’ flow experience on using Blogs. The aim of this study investigated whether the users’ flow experience affected the Bloggers’ satisfaction and intention to continue using. 303 Bloggers were surveyed online. The research findings indicated that confirmation, perceived usefulness, flow, challenge, and arousal were positively affected to the Bloggers’ satisfaction in using that Blog; perceived usefulness, satisfaction, flow were also positively influenced to the Bloggers’ intention to continue using. In addition, the findings point out that the flow factors which we extend into ECTIS model weak positively influence satisfaction. The higher satisfaction users have, the more are continuance intention users get. Recommendations are given on how to make the Bloggers continue using Blogs for the service providers

Microfluidic assisted synthesis of silver nanoparticle–chitosan composite microparticles for antibacterial applications

AbstractSilver nanoparticle (Ag NP)-loaded chitosan composites have numerous biomedical applications; however, fabricating uniform composite microparticles remains challenging. This paper presents a novel microfluidic approach for single-step and in situ synthesis of Ag NP-loaded chitosan microparticles. This proposed approach enables obtaining uniform and monodisperse Ag NP-loaded chitosan microparticles measuring several hundred micrometers. In addition, the diameter of the composites can be tuned by adjusting the flow on the microfluidic chip. The composite particles containing Ag NPs were characterized using UV–vis spectra and scanning electron microscopy-energy dispersive X-ray spectrometry data. The characteristic peaks of Ag NPs in the UV–vis spectra and the element mapping or pattern revealed the formation of nanosized silver particles. The results of antibacterial tests indicated that both chitosan and composite particles showed antibacterial ability, and Ag NPs could enhance the inhibition rate and exhibited dose-dependent antibacterial ability. Because of the properties of Ag NPs and chitosan, the synthesized composite microparticles can be used in several future potential applications, such as bactericidal agents for water disinfection, antipathogens, and surface plasma resonance enhancers

Compensating for the Threshold Voltages of Both the Driving Thin-Film Transistor and the Organic Light-Emitting Diode for Active-Matrix Organic Light-Emitting Diode Displays

This paper proposes a novel pixel circuit design and driving method for active-matrix organic light-emitting diode (AM-OLED) displays that use low-temperature polycrystalline-silicon thin-film transistors (LTPS-TFTs) as driving element. The automatic integrated circuit modeling simulation program with integrated circuit emphasis (AIM-SPICE) simulator was used to verify that the proposed pixel circuit, which comprises five transistors and one capacitor, can supply uniform output current. The voltage programming method of the proposed pixel circuit comprises three periods: reset, compensation with data input, and emission periods. The simulated results reflected excellent performance. For instance, when Δ TH = ±0.33 V, the average error rate of the OLED current variation was low (< 0.8%), and when Δ TH OLED = +0.33 V, the error rate of the OLED current variation was 4.7%. Moreover, when the × (current × resistance) drop voltage of a power line was 0.3 V, the error rate of the OLED current variation was 5.8%. The simulated results indicated that the proposed pixel circuit exhibits high immunity to the threshold voltage deviation of both the driving poly-Si TFTs and OLEDs, and simultaneously compensates for the × drop voltage of a power line

Assistive Navigation Using Deep Reinforcement Learning Guiding Robot With UWB/Voice Beacons and Semantic Feedbacks for Blind and Visually Impaired People

Facilitating navigation in pedestrian environments is critical for enabling people who are blind and visually impaired (BVI) to achieve independent mobility. A deep reinforcement learning (DRL)–based assistive guiding robot with ultrawide-bandwidth (UWB) beacons that can navigate through routes with designated waypoints was designed in this study. Typically, a simultaneous localization and mapping (SLAM) framework is used to estimate the robot pose and navigational goal; however, SLAM frameworks are vulnerable in certain dynamic environments. The proposed navigation method is a learning approach based on state-of-the-art DRL and can effectively avoid obstacles. When used with UWB beacons, the proposed strategy is suitable for environments with dynamic pedestrians. We also designed a handle device with an audio interface that enables BVI users to interact with the guiding robot through intuitive feedback. The UWB beacons were installed with an audio interface to obtain environmental information. The on-handle and on-beacon verbal feedback provides points of interests and turn-by-turn information to BVI users. BVI users were recruited in this study to conduct navigation tasks in different scenarios. A route was designed in a simulated ward to represent daily activities. In real-world situations, SLAM-based state estimation might be affected by dynamic obstacles, and the visual-based trail may suffer from occlusions from pedestrians or other obstacles. The proposed system successfully navigated through environments with dynamic pedestrians, in which systems based on existing SLAM algorithms have failed

The Development of Spatial Attention U-Net for The Recovery of Ionospheric Measurements and The Extraction of Ionospheric Parameters

We train a deep learning artificial neural network model, Spatial Attention U-Net to recover useful ionospheric signals from noisy ionogram data measured by Hualien's Vertical Incidence Pulsed Ionospheric Radar. Our results show that the model can well identify F2 layer ordinary and extraordinary modes (F2o, F2x) and the combined signals of the E layer (ordinary and extraordinary modes and sporadic Es). The model is also capable of identifying some signals that were not labeled. The performance of the model can be significantly degraded by insufficient number of samples in the data set. From the recovered signals, we determine the critical frequencies of F2o and F2x and the intersection frequency between the two signals. The difference between the two critical frequencies is peaking at 0.63 MHz, with the uncertainty being 0.18 MHz.Comment: 17 pages, 7 figures, 3 table

TRPC5 channels participate in pressure-sensing in aortic baroreceptors

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