Enabling Disabled Persons to Gain Access to Digital Media

A report describes the first phase in an effort to enhance the NaviGaze software to enable profoundly disabled persons to operate computers. (Running on a Windows-based computer equipped with a video camera aimed at the user s head, the original NaviGaze software processes the user's head movements and eye blinks into cursor movements and mouse clicks to enable hands-free control of the computer.) To accommodate large variations in movement capabilities among disabled individuals, one of the enhancements was the addition of a graphical user interface for selection of parameters that affect the way the software interacts with the computer and tracks the user s movements. Tracking algorithms were improved to reduce sensitivity to rotations and reduce the likelihood of tracking the wrong features. Visual feedback to the user was improved to provide an indication of the state of the computer system. It was found that users can quickly learn to use the enhanced software, performing single clicks, double clicks, and drags within minutes of first use. Available programs that could increase the usability of NaviGaze were identified. One of these enables entry of text by using NaviGaze as a mouse to select keys on a virtual keyboard

Gesture-Controlled Interfaces for Self-Service Machines

Gesture-controlled interfaces are software- driven systems that facilitate device control by translating visual hand and body signals into commands. Such interfaces could be especially attractive for controlling self-service machines (SSMs) for example, public information kiosks, ticket dispensers, gasoline pumps, and automated teller machines (see figure). A gesture-controlled interface would include a vision subsystem comprising one or more charge-coupled-device video cameras (at least two would be needed to acquire three-dimensional images of gestures). The output of the vision system would be processed by a pure software gesture-recognition subsystem. Then a translator subsystem would convert a sequence of recognized gestures into commands for the SSM to be controlled; these could include, for example, a command to display requested information, change control settings, or actuate a ticket- or cash-dispensing mechanism. Depending on the design and operational requirements of the SSM to be controlled, the gesture-controlled interface could be designed to respond to specific static gestures, dynamic gestures, or both. Static and dynamic gestures can include stationary or moving hand signals, arm poses or motions, and/or whole-body postures or motions. Static gestures would be recognized on the basis of their shapes; dynamic gestures would be recognized on the basis of both their shapes and their motions. Because dynamic gestures include temporal as well as spatial content, this gesture- controlled interface can extract more information from dynamic than it can from static gestures

Kinetic Alfvén mode and kinetic magnetosonic mode from a fluid description

The dispersion relations for the classical electromagnetic modes in a uniform, magnetized, monoenergetic plasma, are reconstructed from a fluid approach. Under study are the Alfvén waves (parallel propagation) and the magnetosonic waves (perpendicular propagation). This fluid theory accounts for finite Larmor radius effects to all order, and is shown to yield identical results from the Vlasov formulation. © 1995 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70334/2/PHPAEN-2-5-1367-1.pd

Gesture-controlled interfaces for self-service machines and other applications

A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines

Interpreting Gene Expression Effects of Disease-Associated Variants: A Lesson from SNCA rs356168

The SNCA intronic single nucleotide polymorphism (SNP), rs356168, has been associated with Parkinson’s disease (PD) in large genome wide association studies (GWAS). Recently, the PD-risk allele, rs356168-G was shown to increase SNCA-mRNA expression using genome edited human induced pluripotent stem cells (iPSC)-derived neurons. In this study, as means of validation, we tested the effect of rs356168 on total SNCA-mRNA levels using brain tissues, temporal and frontal cortex, from healthy control donors. Carriers of the rs356168-G allele demonstrated a borderline significant decrease of SNCA-mRNA levels in temporal brain tissues (p = 0.02) compared to individuals homozygous for the ‘A’ allele. Similar trend, but weak, was observed in the analysis of frontal cortex samples, however, this analysis did not reach statistical significance. These results conflict with the recently reported effect of SNCA SNP rs356168 described above. Our study conveys the need to carefully interpret the precise molecular mechanism by which rs356168, or another tightly linked variant, affects the regulation of SNCA expression. The regulatory mechanisms that contribute to the observed associations between PD and the SNCA-3′ linkage disequilibrium region warrant further investigations

Peripuberty stress leads to abnormal aggression, altered amygdala and orbitofrontal reactivity and increased prefrontal MAOA gene expression.

Although adverse early life experiences have been found to increase lifetime risk to develop violent behaviors, the neurobiological mechanisms underlying these long-term effects remain unclear. We present a novel animal model for pathological aggression induced by peripubertal exposure to stress with face, construct and predictive validity. We show that male rats submitted to fear-induction experiences during the peripubertal period exhibit high and sustained rates of increased aggression at adulthood, even against unthreatening individuals, and increased testosterone/corticosterone ratio. They also exhibit hyperactivity in the amygdala under both basal conditions (evaluated by 2-deoxy-glucose autoradiography) and after a resident-intruder (RI) test (evaluated by c-Fos immunohistochemistry), and hypoactivation of the medial orbitofrontal (MO) cortex after the social challenge. Alterations in the connectivity between the orbitofrontal cortex and the amygdala were linked to the aggressive phenotype. Increased and sustained expression levels of the monoamine oxidase A (MAOA) gene were found in the prefrontal cortex but not in the amygdala of peripubertally stressed animals. They were accompanied by increased activatory acetylation of histone H3, but not H4, at the promoter of the MAOA gene. Treatment with an MAOA inhibitor during adulthood reversed the peripuberty stress-induced antisocial behaviors. Beyond the characterization and validation of the model, we present novel data highlighting changes in the serotonergic system in the prefrontal cortex-and pointing at epigenetic control of the MAOA gene-in the establishment of the link between peripubertal stress and later pathological aggression. Our data emphasize the impact of biological factors triggered by peripubertal adverse experiences on the emergence of violent behaviors

Genome-wide structural variant analysis identifies risk loci for non-Alzheimer’s dementias

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer’s dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia