Gait Verification using Knee Acceleration Signals

A novel gait recognition method for biometric applications is proposed. The approach has the following distinct features. First, gait patterns are determined via knee acceleration signals, circumventing difficulties associated with conventional vision-based gait recognition methods. Second, an automatic procedure to extract gait features from acceleration signals is developed that employs a multiple-template classification method. Consequently, the proposed approach can adjust the sensitivity and specificity of the gait recognition system with great flexibility. Experimental results from 35 subjects demonstrate the potential of the approach for successful recognition. By setting sensitivity to be 0.95 and 0.90, the resulting specificity ranges from 1 to 0.783 and 1.00 to 0.945, respectively

Humidity contribution to C_n^2 over a 600m pathlength in a tropical marine environment

We present new optical turbulence structure parameter measurements, C_n^2, over sea water between La Parguera and Magueyes Island (17.6N 67W) on the southwest coast of Puerto Rico. The 600 meter horizontal paths were located approximately 1.5 m and 10 m above sea level. No data of this type has ever been made available in the literature. Based on the data, we show that the C_n^2 measurements are about 7 times less compared to equivalent land data. This strong evidence reinforces our previous argument that humidity must be accounted for to better ascertain the near surface atmospheric turbulence effects, which current visible / near infrared C_n^2 bulk models fail to do. We also explore the generalised fractal dimension of this littoral data and compare it to our reference land data. We find cases that exhibit monofractal characteristics, that is to say, the effect of rising temperatures during the daylight hours upon turbulence are counterbalanced by humidity, leading to a single characteristic scale for the measurements. In other words, significant moisture changes in the measurement volume cancels optical turbulence increases due to temperature rises. Figures available as JPG only.Comment: 7 pages, 4 figures, 1 table, SPIE Photonics West 2007, paper 6457B-2

Applying the Hilbert--Huang Decomposition to Horizontal Light Propagation C_n^2 data

The Hilbert Huang Transform is a new technique for the analysis of non--stationary signals. It comprises two distinct parts: Empirical Mode Decomposition (EMD) and the Hilbert Transform of each of the modes found from the first step to produce a Hilbert Spectrum. The EMD is an adaptive decomposition of the data, which results in the extraction of Intrinsic Mode Functions (IMFs). We discuss the application of the EMD to the calibration of two optical scintillometers that have been used to measure C_n^2 over horizontal paths on a building rooftop, and discuss the advantage of using the Marginal Hilbert Spectrum over the traditional Fourier Power Spectrum.Comment: 9 pages, 11 figures, proc. SPIE 626

Self-monitoring Practices, Attitudes, and Needs of Individuals with Bipolar Disorder: Implications for the Design of Technologies to Manage Mental Health

Objective To understand self-monitoring strategies used independently of clinical treatment by individuals with bipolar disorder (BD), in order to recommend technology design principles to support mental health management. Materials and Methods Participants with BD (N = 552) were recruited through the Depression and Bipolar Support Alliance, the International Bipolar Foundation, and WeSearchTogether.org to complete a survey of closed- and open-ended questions. In this study, we focus on descriptive results and qualitative analyses. Results Individuals reported primarily self-monitoring items related to their bipolar disorder (mood, sleep, finances, exercise, and social interactions), with an increasing trend towards the use of digital tracking methods observed. Most participants reported having positive experiences with technology-based tracking because it enables self-reflection and agency regarding health management and also enhances lines of communication with treatment teams. Reported challenges stem from poor usability or difficulty interpreting self-tracked data. Discussion Two major implications for technology-based self-monitoring emerged from our results. First, technologies can be designed to be more condition-oriented, intuitive, and proactive. Second, more automated forms of digital symptom tracking and intervention are desired, and our results suggest the feasibility of detecting and predicting emotional states from patterns of technology usage. However, we also uncovered tension points, namely that technology designed to support mental health can also be a disruptor. Conclusion This study provides increased understanding of self-monitoring practices, attitudes, and needs of individuals with bipolar disorder. This knowledge bears implications for clinical researchers and practitioners seeking insight into how individuals independently self-manage their condition as well as for researchers designing monitoring technologies to support mental health management

Gender Determination using Fingerprint Features

Several previous studies have investigated the gender difference of the fingerprint features. However, regarding to the statistical significance of such differences, inconsistent results have been obtained. To resolve this problem and to develop a method for gender determination, this work proposes and tests three fingertip features for gender determination. Fingerprints were obtained from 115 normal healthy adults comprised of 57 male and 58 female volunteers. All persons were born in Taiwan and were of Han nationality. The age range was18-35 years. The features of this study are ridge count, ridge density, and finger size, all three of which can easily be determined by counting and calculation. Experimental results show that the tested ridge density features alone are not very effective for gender determination. However, the proposed ridge count and finger size features of left little fingers are useful, achieving a classification accuracy of 75% (P-valu

Meridional Transport in the Stratosphere of Jupiter

The Cassini measurements of C$_2$H$_2$ and C$_2$H$_6$ at $\sim$5 mbar provide a constraint on meridional transport in the stratosphere of Jupiter. We performed a two-dimensional photochemical calculation coupled with mass transport due to vertical and meridional mixing. The modeled profile of C$_2$H$_2$ at latitudes less than 70$^\circ$ follows the latitude dependence of the solar insolation, while that of C$_2$H$_6$ shows little latitude dependence, consistent with the measurements. In general, our model study suggests that the meridional transport timescale above 5-10 mbar altitude level is $\gtrsim$1000 years and the time could be as short as 10 years below 10 mbar level, in order to fit the Cassini measurements. The derived meridional transport timescale above the 5 mbar level is a hundred times longer than that obtained from the spreading of gas-phase molecules deposited after the impact of Shoemaker-Levy 9 comet. There is no explanation at this time for this discrepancy.Comment: 11 pages, 3 figures, 1 table. ApJL in pres

Impaired natural killer cell phenotype and function in idiopathic and heritable pulmonary arterial hypertension

BACKGROUND: Beyond their role as innate immune effectors, natural killer (NK) cells are emerging as important regulators of angiogenesis and vascular remodeling. Pulmonary arterial hypertension (PAH) is characterized by severe pulmonary vascular remodeling and has long been associated with immune dysfunction. Despite this association, a role for NK cells in disease pathology has not yet been described. METHODS AND RESULTS: Analysis of whole blood lymphocytes and isolated NK cells from PAH patients revealed an expansion of the functionally defective CD56(-)/CD16(+) NK subset that was not observed in patients with chronic thromboembolic pulmonary hypertension. NK cells from PAH patients also displayed decreased levels of the activating receptor NKp46 and the killer immunoglobulin-like receptors 2DL1/S1 and 3DL1, reduced secretion of the cytokine macrophage inflammatory protein-1β, and a significant impairment in cytolytic function associated with decreased killer immunoglobulin-like receptor 3DL1 expression. Genotyping patients (n=222) and controls (n=191) for killer immunoglobulin-like receptor gene polymorphisms did not explain these observations. Rather, we show that NK cells from PAH patients exhibit increased responsiveness to transforming growth factor-β, which specifically downregulates disease-associated killer immunoglobulin-like receptors. NK cell number and cytotoxicity were similarly decreased in the monocrotaline rat and chronic hypoxia mouse models of PAH, accompanied by reduced production of interferon-γ in NK cells from hypoxic mice. NK cells from PAH patients also produced elevated quantities of matrix metalloproteinase 9, consistent with a capacity to influence vascular remodeling. CONCLUSIONS: Our work is the first to identify an impairment of NK cells in PAH and suggests a novel and substantive role for innate immunity in the pathobiology of this disease

Classification of Infant Sleep/Wake States: Cross-Attention among Large Scale Pretrained Transformer Networks using Audio, ECG, and IMU Data

Infant sleep is critical to brain and behavioral development. Prior studies on infant sleep/wake classification have been largely limited to reliance on expensive and burdensome polysomnography (PSG) tests in the laboratory or wearable devices that collect single-modality data. To facilitate data collection and accuracy of detection, we aimed to advance this field of study by using a multi-modal wearable device, LittleBeats (LB), to collect audio, electrocardiogram (ECG), and inertial measurement unit (IMU) data among a cohort of 28 infants. We employed a 3-branch (audio/ECG/IMU) large scale transformer-based neural network (NN) to demonstrate the potential of such multi-modal data. We pretrained each branch independently with its respective modality, then finetuned the model by fusing the pretrained transformer layers with cross-attention. We show that multi-modal data significantly improves sleep/wake classification (accuracy = 0.880), compared with use of a single modality (accuracy = 0.732). Our approach to multi-modal mid-level fusion may be adaptable to a diverse range of architectures and tasks, expanding future directions of infant behavioral research.Comment: Preprint for APSIPA202

Negative differential resistance in molecular junctions: The effect of the electrodes electronic structure

We have carried out calculations of electron transport through a metal-molecule-metal junction with metal nanoclusters taking the part of electrodes. We show that negative differential resistance peaks could appear in the current-voltage curves. The peaks arise due to narrow features in the electron density of states of the metal clusters. The proposed analysis is based on the ab initio computations of the relevant wave functions and energies within the framework of the density functional theory using NRLMOL software package.Comment: 4 pages, 2 figures, added text