Electrophysiological Correlates of Visual Object Category Formation in a Prototype-Distortion Task

In perceptual learning studies, participants engage in extensive training in the discrimination of visual stimuli in order to modulate perceptual performance. Much of the literature in perceptual learning has looked at the induction of the reorganization of low-level representations in V1. However, much remains to be understood about the mechanisms behind how the adult brain (an expert in visual object categorization) extracts high-level visual objects from the environment and categorically represents them in the cortical visual hierarchy. Here, I used event-related potentials (ERPs) to investigate the neural mechanisms involved in object representation formation during a hybrid visual search and prototype distortion category learning task. EEG was continuously recorded while participants performed the hybrid task, in which a peripheral array of four dot patterns was briefly flashed on a computer screen. In half of the trials, one of the four dot patterns of the array contained the target, a distorted prototype pattern. The remaining trials contained only randomly generated patterns. After hundreds of trials, participants learned to discriminate the target pattern through corrective feedback. A multilevel modeling approach was used to examine the predictive relationship between behavioral performance over time and two ERP components, the N1 and the N250. The N1 is an early sensory component related to changes in visual attention and discrimination (Hopf et al., 2002; Vogel & Luck, 2000). The N250 is a component related to category learning and expertise (Krigolson et al., 2009; Scott et al., 2008; Tanaka et al., 2006). Results indicated that while N1 amplitudes did not change with improved performance, increasingly negative N250 amplitudes did develop over time and were predictive of improvements in pattern detection accuracy

The Tragedy of the Commons in a Fishery when Relative Performance Matters

This paper presents a simple model of a common access fishery where fishermen care about relative performance as well as absolute profits. Our specification captures the idea that status (which depends on relative performance) in a community infuences a person's well-being. We consider two alternative specifications of relative performance. In our first specication, relative performance is equated to relative after-tax profits. In our second specification, it is relative harvests that matter. We show that overharvesting resulting from the tragedy of the commons problem is exacerbated by the desire for higher relative performance, leading to a smaller steady-state fish stock and smaller steady-state profit for all the fishermen. We examine a tax package, consisting of a tax on relative profit and a tax on effort, and an individual quota as alternatives to implement the socially effcient equilibrium.relative income, relative performance, status, fishery, tragedy of the commons

Zeros of some level 2 Eisenstein series

The zeros of classical Eisenstein series satisfy many intriguing properties. Work of F. Rankin and Swinnerton-Dyer pinpoints their location to a certain arc of the fundamental domain, and recent work by Nozaki explores their interlacing property. In this paper we extend these distribution properties to a particular family of Eisenstein series on Gamma(2) because of its elegant connection to a classical Jacobi elliptic function cn(u) which satisfies a differential equation. As part of this study we recursively define a sequence of polynomials from the differential equation mentioned above that allow us to calculate zeros of these Eisenstein series. We end with a result linking the zeros of these Eisenstein series to an L-series.Comment: 14 pages, 1 figur

Building Object Representations: Mechanisms of Perceptual Learning in Human Visual Cortex

Extensive literature in the cognitive neurosciences has been dedicated to understanding the neural processes involved in object category learning. However, much remains to be learned regarding the mechanisms by which high-level visual patterns are extracted from a crowded visual scene, segregated into discrete object categories, and represented in the cortical visual hierarchy. Here, we used event-related potentials (ERPs) to investigate the neural underpinnings of visual object category extraction in a cluttered visual environment. Electroencephalography (EEG) was continuously recorded while subjects were given a hybrid of an object category learning and visual search task. In this hybrid task, a peripheral array of four dot patterns was flashed. In 50% of trials, one position of the array contained a distortion of a prototype dot pattern. The remaining trials consisted entirely of randomly generated dot patterns. After hundreds of trials, observers learned to detect the dot pattern object category via correct or incorrect feedback given on each trial. We assessed improvements in dot pattern detection (d’) in conjunction with three component ERPs, N250, P3, and FRN, to examine the neural mechanisms of visual object category formation. Our results revealed a sequence of effects during the course of learning to detect the pattern. First, FRN amplitude was greatest at the beginning of learning (low d’) and then decreased over time. Following the FRN effect, a P3 effect developed as learning continued. Finally, an N250 effect appeared at the peak of learning (where d’ peaked), following the beginning of the P3 effect. The underlying neural mechanisms of these components suggest a correlational relationship between these components and contribute to how the brain learns to represent a novel object

Evaluating Alternatives for Augmented Water Quality Improvement Utilizing Oyster Restoration as Best Management Practice (BMP)

Due to several anthropogenic influences, the Chesapeake Bay has experienced a marked decrease in water quality since the colonists arrived at the Jamestown settlement in Virginia during the 1600s. Higher concentrations of nitrogen and phosphorus have enriched the estuaries and coastal waters via point sources (sewage treatment plants and industrial wastes), nonpoint sources (agricultural run-off and septic tank discharges) and the atmosphere (Newell et al., 2005). Restoring oyster beds is considered a Best Management Practice (BMP) to improve water quality as well as provide physical habitat for aquatic species and a healthier estuarine system (USACE Native Oyster Restoration Master Plan, 2012). Efforts to assist water quality improvement in conjunction with the fisheries include declaring sanctuaries for brood-stocks, supplementing hard substrate on the bottom and aiding natural populations with the addition of hatchery-reared and disease-resistant stocks in most of the coastal states in United States (Coen & Luckenbach, 2000). An economic assessment of oyster reefs suggests that restoring the ecological functions will improve water quality, stabilize shorelines, reduce predation (Grabowski, 2004) and establish a habitat for breeding grounds that outweighs the importance of harvestable oyster production (Luckenbach et al., 2005). Statistical models to investigate factorial multicolinearities between water quality and oyster restoration activities were developed in this research to evaluate productivity levels of oyster restoration on multiple substrates, as well as the physical, chemical, hydrological and biological site characteristics, so that the greatest contributing factors were systematically identified. Findings from the factorial models were then further utilized to propose and develop a number of in situ water quality improvement design in forms of Total Maximum Daily Loads (TMDLs) and Best Management Practices (BMPs). A factorial model evaluates the relationship among the dependent variable, oyster biomass, and treatment levels of temperature (which includes seasonal variability), as well as salinity, TSS (total suspended solids),Escherichia coli/Enterococcus bacterial counts, depth, dissolved oxygen levels (DO) and nutrients such as nitrogen, phosphorus and chlorophyll a, and the block levels designated for the model such as alternative substrates (oyster shells versus riprap, granite, cement, cinder blocks, limestone marl or combinations). The different scenarios are analyzed utilizing the Factorial Model along with a Multiple Means Comparison (MMC) to compare the production rates and evaluate which combination of variables produces the highest biomass of oysters. Once the variables of greatest impact are identified, BMPs and TMDLs will be identified to aid in lowering the existing levels and develop future plans for maintaining them. In summary, this model is being developed for maximizing the likelihood of successful oyster reef restoration in an effort to establish a healthier ecosystem and to improve overall estuarine water quality in the Chesapeake Bay estuaries

An EEG Source-Space Analysis of the Neural Correlates Underlying Self-Regulation

Self-regulation is the cognitive process of controlling our thoughts and behaviors to be aligned with our goals. This process is used in many different contexts and has been associated with contributions from several brain regions. This research aimed to investigate differences in four prefrontal areas of the brain while participants applied four different self-regulation strategies. We recorded EEG while participants (N = 132) performed three tasks which engaged each of the four self-regulation strategies: the AX-CPT task engaged proactive and reactive control, the Go/Nogo task engaged inhibitory control, and the hybrid Flanker Global/Local task engaged the resolution of response conflict. This study used the N2 event-related potential (ERP) to capture the neural activity related to each self-regulation strategy and then source-space analyses (eLORETA) were conducted to estimate the activity in four regions of interest (ROIs): dorsolateral (DL) PFC, ventrolateral (VL) PFC, ventromedial (VM) PFC, and dorsal ACC. The dorsal ACC was most activated for proactive control, indicative of performance monitoring. The right VLPFC was indicative of conflict adaptation in reactive control and response conflict, and indicative of motor inhibition in inhibitory control. DLPFC was most active for goal maintenance during proactive and reactive control. The left VLPFC was most active during reactive control, indicating its importance in memory of goal information. These results are in line with much of the previous literature. VMPFC did not show any differences across the strategies likely due to the lack of emotional context. This study builds on the extant literature by directly comparing neural processes across four different self-regulation strategies within one large sample, highlighting the fact that various self-regulation strategies recruit unique patterns of activation and thus future research should not collapse across these strategies

Absorbed dose thresholds and absorbed dose rate limitations for studies of electron radiation effects on polyetherimides

The threshold values of total absorbed dose for causing changes in tensile properties of a polyetherimide film and the limitations of the absorbed dose rate for accelerated-exposure evaluation of the effects of electron radiation in geosynchronous orbit were studied. Total absorbed doses from 1 kGy to 100 MGy and absorbed dose rates from 0.01 MGy/hr to 100 MGy/hr were investigated, where 1 Gy equals 100 rads. Total doses less than 2.5 MGy did not significantly change the tensile properties of the film whereas doses higher than 2.5 MGy significantly reduced elongation-to-failure. There was no measurable effect of the dose rate on the tensile properties for accelerated electron exposures

Long-term trends of changes in pine and oak foliar nitrogen metabolism in response to chronic nitrogen amendments at Harvard Forest, MA

We evaluated the long-term (1995–2008) trends in foliar and sapwood metabolism, soil solution chemistry and tree mortality rates in response to chronic nitrogen (N) additions to pine and hardwood stands at the Harvard Forest Long Term Ecological Research (LTER) site. Common stress-related metabolites like polyamines (PAs), free amino acids (AAs) and inorganic elements were analyzed for control, low N (LN, 50 kg NH4NO3 ha−1 year−1) and high N (HN, 150 kg NH4NO3 ha−1 year−1) treatments. In the pine stands, partitioning of excess N into foliar PAs and AAs increased with both N treatments until 2002. By 2005, several of these effects on N metabolites disappeared for HN, and by 2008 they were mostly observed for LN plot. A significant decline in foliar Ca and P was observed mostly with HN for a few years until 2005. However, sapwood data actually showed an increase in Ca, Mg and Mn and no change in PAs in the HN plot for 2008, while AAs data revealed trends that were generally similar to foliage for 2008. Concomitant with these changes, mortality data revealed a large number of dead trees in HN pine plots by 2002; the mortality rate started to decline by 2005. Oak trees in the hardwood plot did not exhibit any major changes in PAs, AAs, nutrients and mortality rate with LN treatment, indicating that oak trees were able to tolerate the yearly doses of 50 kg NH4NO3 ha−1 year−1. However, HN trees suffered from physiological and nutritional stress along with increased mortality in 2008. In this case also, foliar data were supported by the sapwood data. Overall, both low and high N applications resulted in greater physiological stress to the pine trees than the oaks. In general, the time course of changes in metabolic data are in agreement with the published reports on changes in soil chemistry and microbial community structure, rates of soil carbon sequestration and production of woody biomass for this chronic N study. This correspondence of selected metabolites with other measures of forest functions suggests that the metabolite analyses are useful for long-term monitoring of the health of forest trees

Security Analysis of the Masimo MightySat: Data Leakage to a Nosy Neighbor

Embedded technology known as the Internet of Things (IoT) has been integrated into everyday life, from the home, to the farm, industry, enterprise, the battlefield, and even for medical devices. With the increased use of networked devices comes an increased attack surface for malicious actors to gather and inject data, putting the privacy of users at risk. This research considers the Masimo MightySat fingertip pulse oximeter and the companion Masimo Professional Health app from a security standpoint, analyzing the Bluetooth Low Energy (BLE) communication from the device to the application and the data leakage between the two. It is found that with some analysis of a personally owned Masimo MightySat Rx through the use of an Ubertooth BLE traffic sniffer, static analysis of the HCI\_snoop.log and application data, and dynamic analysis of the app, data could be reasonably captured for another MightySat and interpret it to learn user health data

An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem

In this paper, the current variant technique of the stochastic gradient descent (SGD) approach, namely, the adaptive moment estimation (Adam) approach, is improved by adding the standard error in the updating rule. ,e aim is to fasten the convergence rate of the Adam algorithm. ,is improvement is termed as Adam with standard error (AdamSE) algorithm. On the other hand, the mean-variance portfolio optimization model is formulated from the historical data of the rate of return of the S&P 500 stock, 10-year Treasury bond, and money market. ,e application of SGD, Adam, adaptive moment estimation with maximum (AdaMax), Nesterov-accelerated adaptive moment estimation (Nadam), AMSGrad, and AdamSE algorithms to solve the meanvariance portfolio optimization problem is further investigated. During the calculation procedure, the iterative solution converges to the optimal portfolio solution. It is noticed that the AdamSE algorithm has the smallest iteration number. ,e results show that the rate of convergence of the Adam algorithm is significantly enhanced by using the AdamSE algorithm. In conclusion, the efficiency of the improved Adam algorithm using the standard error has been expressed. Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated