Statistics anxiety, trait anxiety, learning behavior, and academic performance

The present study investigated the relationship between statistics anxiety, individual characteristics (e.g., trait anxiety and learning strategies), and academic performance. Students enrolled in a statistics course in psychology (N=147) filled in a questionnaire on statistics anxiety, trait anxiety, interest in statistics, mathematical selfconcept, learning strategies, and procrastination. Additionally, their performance in the examination was recorded. The structural equation model showed that statistics anxiety held a crucial role as the strongest direct predictor of performance. Students with higher statistics anxiety achieved less in the examination and showed higher procrastination scores. Statistics anxiety was related indirectly to spending less effort and time on learning. Trait anxiety was related positively to statistics anxiety and, counterintuitively, to academic performance. This result can be explained by the heterogeneity of the measure of trait anxiety. The part of trait anxiety that is unrelated to the specific part of statistics anxiety correlated positively with performance.

Subsurface transport behavior of micro-nano bubbles and potential applications for groundwater remediation.

Micro-nano bubbles (MNBs) are tiny bubbles with diameters on the order of micrometers and nanometers, showing great potential in environmental remediation. However, the application is only in the beginning stages and remains to be intensively studied. In order to explore the possible use of MNBs in groundwater contaminant removal, this study focuses on the transport of MNBs in porous media and dissolution processes. The bubble diameter distribution was obtained under different conditions by a laser particle analyzer. The permeability of MNB water through sand was compared with that of air-free water. Moreover, the mass transfer features of dissolved oxygen in water with MNBs were studied. The results show that the bubble diameter distribution is influenced by the surfactant concentration in the water. The existence of MNBs in pore water has no impact on the hydraulic conductivity of sand. Furthermore, the dissolved oxygen (DO) in water is greatly increased by the MNBs, which will predictably improve the aerobic bioremediation of groundwater. The results are meaningful and instructive in the further study of MNB research and applications in groundwater bioremediation.

Impact of donor traps on the 2DEG and electrical behavior of AlGaN/GaN MISFETs

As an important step in understanding trap-related mechanisms in AlGaN/GaN transistors, the physical properties of surface states have been analyzed through the study of the transfer characteristics of a MISFET. This letter focused initially on the relationship between donor parameters (concentration and energy level) and electron density in the channel in AlGaN/GaN heterostructures. This analysis was then correlated to dc and pulsed measurements of the transfer characteristics of a MISFET, where the gate bias was found to modulate either the channel density or the donor states. Traps-free and traps-frozen TCAD simulations were performed on an equivalent device to capture the donor behavior. A donor concentration of 1.14× 1013 ∼ cm-2 with an energy level located 0.2 eV below the conduction band edge gave the best fit to measurements. With the approach described here, we were able to analyze the region of the MISFET that corresponds to the drift region of a conventional HEMT. © 1980-2012 IEEE.

The effect of incomplete ionization on the turn-off behavior of FS IGBTs

This letter demonstrates for the first time the effect of the incomplete ionization (I.I.) of the transparent p-anode layer on the static and dynamic characteristics of the field-stop insulated gate bipolar transistors (FS IGBTs). This effect needs to be considered in FS IGBTs TCAD modeling to match accurately the device characteristics across a wide range of temperatures. The acceptor ionization energy (EA) governing the I.I. mechanism for the p-anode is extracted via matching the experimental turn-off waveforms and the static performance with Medici simulator. © 1980-2012 IEEE.

Behavior of RC beams retrofitted with CARDIFRC after thermal cycling

This study investigates the effect of thermal cycling on the performance of concrete beams retrofitted with CARDIFRC, a new class of high performance fiber-reinforced cement-based material that is compatible with concrete. Twenty four beams were subjected to 24 h thermal cycles between 25 and 90°C. One third of the beams were reinforced either in flexure only or in flexure and shear with conventional steel reinforcement and used as control specimens. The remaining sixteen beams were retrofitted with CARDIFRC strips to provide external flexural and/or shear strengthening. All beams were exposed to a varied number of 24 h thermal cycles ranging from 0 to 90 and were tested in four-point bending at room temperature. The tests indicated that the retrofitted members were stronger and stiffer than control beams, and more importantly, that their failure initiated in flexure without any signs of interfacial delamination cracking. The results of these tests are presented and compared to analytical predictions. The predictions show good correlation with the experimental results. © 2010 ASCE.

Unified analytic model for current-voltage behavior in amorphous oxide semiconductor TFTs

We present a simple and semi-physical analytical description of the current-voltage characteristics of amorphous oxide semiconductor thin-film transistors in the above-threshold and sub-threshold regions. Both regions are described by single unified expression that employs the same set of model parameter values directly extracted from measured terminal characteristics. The model accurately reproduces measured characteristics of amorphous semiconductor thin film transistors in general, yielding a scatter of < 4%. © 1980-2012 IEEE.

Hydrolysis and coagulation behavior of polyferric sulfate and ferric sulfate

The hydrolysis behaviors of polyferric sulfate (PFS) and ferric sulfate (FS) under conditions similar to raw wastewater were investigated and the coagulation of biologically pretreated molasses wastewater using PFS and FS was evaluated by studying coagulation efficiency, zeta potential and microscopic surface morphology of flocs. Experimental results show that the hydrolysis behavior of PFS is different from that of FS on the basis of ferron assay. In the case of FS, fast-reacting Fe(III) polymers were the dominant polynuclear species while large fraction of slow-reacting iron polymers is present in PFS. Despite slightly fewer dosages of PFS required as compared to FS, there is no marked difference in the coagulation of molasses effluent between PFS and FS, especially at the optimum dosages. Both coagulants destabilize organic compounds predominantly through charge neutralization-precipitation mechanism. Hydrolysis rate of PFS in synthetic solution is appreciably different from that in raw wastewater. This may due to the effect of sulfate anion introduced as counter-ion as well as depolymerization of larger polymeric Fe(III) species by the organic ligands present in molasses effluent.

Does temporal discounting explain unhealthy behavior? A systematic review and reinforcement learning perspective.

The tendency to make unhealthy choices is hypothesized to be related to an individual's temporal discount rate, the theoretical rate at which they devalue delayed rewards. Furthermore, a particular form of temporal discounting, hyperbolic discounting, has been proposed to explain why unhealthy behavior can occur despite healthy intentions. We examine these two hypotheses in turn. We first systematically review studies which investigate whether discount rates can predict unhealthy behavior. These studies reveal that high discount rates for money (and in some instances food or drug rewards) are associated with several unhealthy behaviors and markers of health status, establishing discounting as a promising predictive measure. We secondly examine whether intention-incongruent unhealthy actions are consistent with hyperbolic discounting. We conclude that intention-incongruent actions are often triggered by environmental cues or changes in motivational state, whose effects are not parameterized by hyperbolic discounting. We propose a framework for understanding these state-based effects in terms of the interplay of two distinct reinforcement learning mechanisms: a "model-based" (or goal-directed) system and a "model-free" (or habitual) system. Under this framework, while discounting of delayed health may contribute to the initiation of unhealthy behavior, with repetition, many unhealthy behaviors become habitual; if health goals then change, habitual behavior can still arise in response to environmental cues. We propose that the burgeoning development of computational models of these processes will permit further identification of health decision-making phenotypes.

Using the moving window incorporated neural network to forecast the population behavior of Nostocales spp. in the River Darling, Australia

The paper demonstrates the nonstationarity of algal population behaviors by analyzing the historical populations of Nostocales spp. in the River Darling, Australia. Freshwater ecosystems are more likely to be nonstationary, instead of stationary. Nonstationarity implies that only the near past behaviors could forecast the near future for the system. However, nonstionarity was not considered seriously in previous research efforts for modeling and predicting algal population behaviors. Therefore the moving window technique was incorporated with radial basis function neural network (RBFNN) approach to deal with nonstationarity when modeling and forecasting the population behaviors of Nostocales spp. in the River Darling. The results showed that the RBFNN model could predict the timing and magnitude of algal blooms of Nostocales spp. with high accuracy. Moreover, a combined model based on individual RBFNN models was implemented, which showed superiority over the individual RBFNN models. Hence, the combined model was recommended for the modeling and forecasting of the phytoplankton populations, especially for the forecasting.

Experimental and numerical investigation of the seismic behavior of rectangular tunnels in soft soils

Underground structures constitute crucial components of the transportation networks. Considering their significance for modern societies, their proper seismic design is of great importance. However, this design may become very tricky, accounting of the lack of knowledge regarding their seismic behavior. Several issues that are significantly affecting this behavior (i.e. earth pressures on the structure, seismic shear stresses around the structure, complex deformation modes for rectangular structures during shaking etc.) are still open. The problem is wider for the non-circular (i.e. rectangular) structures, were the soilstructure interaction effects are expected to be maximized. The paper presents representative experimental results from a test case of a series of dynamic centrifuge tests that were performed on rectangular tunnels embedded in dry sand. The tests were carried out at the centrifuge facility of the University of Cambridge, within the Transnational Task of the SERIES EU research program. The presented test case is also numerically simulated and studied. Preliminary full dynamic time history analyses of the coupled soil-tunnel system are performed, using ABAQUS. Soil non-linearity and soil-structure interaction are modeled, following relevant specifications for underground structures and tunnels. Numerical predictions are compared to experimental results and discussed. Based on this comprehensive experimental and numerical study, the seismic behavior of rectangular embedded structures is better understood and modeled, consisting an important step in the development of appropriate specifications for the seismic design of rectangular shallow tunnels.

Self-organization of reflexive behavior from spontaneous motor activity.

In mammals, the development of reflexes is often regarded as an innate process. However, recent findings show that fetuses are endowed with favorable conditions for ontogenetic development. In this article, we hypothesize that the circuitry of at least some mammalian reflexes can be self-organized from the sensory and motor interactions brought forth in a musculoskeletal system. We focus mainly on three reflexes: the myotatic reflex, the reciprocal inhibition reflex, and the reverse myotatic reflex. To test our hypothesis, we conducted a set of experiments on a simulated musculoskeletal system using pairs of agonist and antagonist muscles. The reflex connectivity is obtained by producing spontaneous motor activity in each muscle and by correlating the resulting sensor and motor signals. Our results show that, under biologically plausible conditions, the reflex circuitry thus obtained is consistent with that identified in relation to the analogous mammalian reflexes. In addition, they show that the reflex connectivity obtained depends on the morphology of the musculoskeletal system as well as on the environment that it is embedded in.

Morphological computation for adaptive behavior and cognition

Traditionally, in robotics, artificial intelligence and neuroscience, there has been a focus on the study of the control or the neural system itself. Recently there has been an increasing interest in the notion of embodiment not only in robotics and artificial intelligence, but also in the neurosciences, psychology and philosophy. In this paper, we introduce the notion of morphological computation, and demonstrate how it can be exploited on the one hand for designing intelligent, adaptive robotic systems, and on the other hand for understanding natural systems. While embodiment has often been used in its trivial meaning, i.e. "intelligence requires a body", the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. Morphological computation is about connecting body, brain and environment. A number of case studies are presented to illustrate the concept. We conclude with some speculations about potential lessons for neuroscience and robotics. © 2006 Elsevier B.V. All rights reserved.

Behavior learning of a face robot based on the characteristics of human instruction

Computer simulation experiments were performed to examine the effectiveness of OR- and comparative-reinforcement learning algorithms. In the simulation, human rewards were given as +1 and -1. Two models of human instruction that determine which reward is to be given in every step of a human instruction were used. Results show that human instruction may have a possibility of including both model-A and model-B characteristics, and it can be expected that the comparative-reinforcement learning algorithm is more effective for learning by human instructions.

Effects of several organic acids on the feeding behavior of Tilapia nilotica

Automatic recording of the frequency of feeding 'bites' was used to evaluate the effects of several organic acids (citric, metacectonic, lactic, acetic, and oxalic) on the stimulatory feeding behavior of Tilapia nilotica . Some of these acids are added to food stocks to retard spoilage. The results showed that citric acid at a concentration of 10(-2) to 10(-6) m, metacetonic acid at 10(-4) to 10(-6) m, and lactic acid at 10(-2) to 10(-5) m stimulated feeding. Fish tended to avoid metacetonic acid at 10(-3) m and acetic acid at 10(-3) m. Acetic acid at 10(-5) m and oxalic acid at 10(-6) m had no significant effects on fish feeding.