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Understanding travel behavior is crucial to transportation decarbonization. OpenPATH is an open-source mobility platform which collects and analyzes human travel behavior at the individual level. The mobile application passively senses trips and prompts users to label them. However, users find the labeling process burdensome; less than half the trips are typically labeled, making much of the data unusable in aggregate analyses of mobility patterns. Prior work has addressed the response fatigue challenge through automated mode inference using sensor data, but sensors cannot capture all aspects of travel behavior. We explore an alternative approach in which we leverage prior user input to predict travel choices in novel trips. We first explore trip clustering methods and develop a novel two-step pipeline using DBSCAN and SVMs to extract realistic geospatial clusters. We then propose two strategies to predict trip labels: (i) clustering trips and extrapolating labels for similar trips, and (ii) random forest classification. The random forest approach is able to achieve - $70-80% accuracy (purpose: 72%, mode: 79%, replaced mode: 81%). These novel approaches to trip classification allow us to increase the rate of user labeling by suggesting predicted labels to be verified by the user. Unlabeled trips can also contribute to aggregate analyses, using label predictions and their associated confidences as a substitute. While there exist other travel survey apps with the ability to infer travel choices, to our knowledge, this is the first paper to describe such a supervised system and rigorously evaluate it.
Face recognition technology has advanced significantly in recent years due largely to the availability of large and increasingly complex training datasets for use in deep learning models. These datasets, however, typically comprise images scraped from news sites or social media plat-forms and, therefore, have limited utility in more advanced security, forensics, and military applications. These applications require lower resolution, longer ranges, and ele-vated viewpoints. To meet these critical needs, we collected and curated the first and second subsets of a large multi-modal biometric dataset designed for use in the research and development (R&D) of biometric recognition technolo-gies under extremely challenging conditions. Thus far, the dataset includes more than 350,000 still images and over 1,300 hours of video footage of approximately 1,000 sub-jects. To collect this data, we used Nikon DSLR cameras, a variety of commercial surveillance cameras, specialized long-rage R&D cameras, and Group 1 and Group 2 UAV platforms. The goal is to support the development of algorithms capable of accurately recognizing people at ranges up to 1,000 m and from high angles of elevation. These ad-vances will include improvements to the state of the art in face recognition and will support new research in the area of whole-body recognition using methods based on gait and anthropometry. This paper describes methods used to col-lect and curate the dataset, and the dataset's characteristics at the current stage.
A method for providing task load-optimized computer-generated training experiences to a user of a training system that includes: a display, a training simulator, a prediction program (ML1), and a training optimization program (ML2). In response to receiving a predicted optimal task load, ML2 provides a first training experience recommendation related to the training content and/or training conditions that, if utilized in providing a training experience to the user, is predicted to result in the predicted actual task load of the user equaling the predicted optimal task load. In response to receiving biometric information or performance metric information, ML1 determines the predicted actual task load. If the predicted actual task load does not match the predicted optimal task load, ML2 provides a second training experience recommendation and a second training experience is provided where at least one of the training content or the training conditions is changed.
Many casualties of the Hiroshima and Nagasaki atomic bombs, and many of the firefighters who first responded to the Chernobyl nuclear power plant accident, became ill with acute radiation syndrome (ARS). Most of the people who do not recover from ARS will die within a few weeks to a few months after exposure, with the primary cause of death being the destruction of the body's bone marrow (BM). This is exemplified by the Chernobyl firefighters, the majority of whom received whole body doses between 0.8 and 10 Gy, and the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) final report on the disaster concluded that the underlying cause of death of all 28 firefighters who succumbed to ARS was from bone marrow failure. BM is comprised of hematopoietic stem cells (HSCs) which are responsible for the constant renewal of blood cells. Due to their high rate of proliferation, HSCs are especially vulnerable to ionizing radiation, but are endowed with remarkable regenerative potential. Owing to their central role in blood production, lethal irradiation of HSCs leads to death from severe anemia, infection and internal bleeding. This relationship between high doses of radiation and HSC apoptosis has led to the use of HSC transplantation as a life-saving intervention in cases of acute exposure. This is demonstrable in medical practice, where thousands of individuals have undergone supra-lethal Total Body Irradiation (TBI) for purposes of cancer therapy, and were rescued by well-matched BM transplantation. Indeed, life-threatening damage may be reversed by BM transplantation in individuals receiving doses of radiation of up to 10 Gy. At doses > 10 Gy, damage to gastrointestinal (GI) tissue may become a limiting factor in survival. Remarkably, in the common procedure of BM transplantation, the number of HSCs extracted from a single active BM site containing less than 5% of the donor's BM tissue is sufficient to support the complete reconstitution of the HSC compartment in a lethally irradiated recipient. This capacity of BM to expand and replenish is due to the high regenerative potential of the HSCs it harbors. In contrast to mature blood cells, which are dispersed throughout the body, HSCs are confined to the bones, allowing for effective targeted shielding. This has been confirmed in several animal models, where sparing the HSC-rich area of a subject receiving otherwise full-body irradiation is sufficient to support hematopoietic functions and allow survival. Approximately 48% of the human body's active BM is contained within the lumbar vertebrae and the pelvic region. This high concentration of BM makes the pelvic region an ideal area to shield for preventing the serious hematopoietic effects of radiation exposure. Stem-cell rich tissues like active BM are also more sensitive to the stochastic effects (i.e. cancer) of radiation exposure. The high amount of BM in the pelvic region, combined with the presence of the sensitive gastrointestinal system and female gonads in this same area of the body allows for the possibility of significantly reducing stochastic effects of radiation by limiting radiation exposure to this vital area. Thus, shielding this region holds great promise for both acute and protracted exposures. Thus, a specialized radiation shielding device for the protection of active BM concentrations is presented here. This belt-like selective shielding device focuses on the protection of BM that is present in the pelvis and hip bones, protecting the medullary volume from which BM is commonly extracted for transplantation (i.e. the iliac bones) while allowing relatively unhindered movement of the wearer. In order to optimize the use of shielding materials towards the protection of active BM, the shielding uniquely brings into account the natural shielding properties of human tissue, with thickness being inversely related to the thickness and radiation attenuation of the underlying tissue at each point surrounding the area being protected. The findings resulting from both experimental and simulation testing of this selective shielding device are presented here.
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A textile includes: (1) a matrix; and (2) particulate fillers dispersed within the matrix. The textile has a transmittance of infrared radiation at a wavelength of 9.5 μm of at least about 40%, and the textile has a weighted average reflectivity of radiation over a wavelength range of 0.3 μm to 2 μm of at least about 40%.
Urinary haloacetic acids (HAAs), such as dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA), have been suggested as potential biomarkers of exposure to drinking water disinfection byproducts (DBPs). However, variable exposure to and the short elimination half-lives of these biomarkers can result in considerable variability in urinary measurements, leading to exposure misclassification. Here we examined the variability of DCAA and TCAA levels in the urine among eleven men who provided urine samples on 8 days over 3 months. The urinary concentrations of DCAA and TCAA were measured by gas chromatography coupled with electron capture detection. We calculated the intraclass correlation coefficients (ICCs) to characterize the within-person and between-person variances and computed the sensitivity and specificity to assess how well single or multiple urine collections accurately determined personal 3-month average DCAA and TCAA levels. The within-person variance was much higher than the between-person variance for all three sample types (spot, first morning, and 24-h urine samples) for DCAA (ICC=0.08–0.37) and TCAA (ICC=0.09–0.23), regardless of the sampling interval. A single-spot urinary sample predicted high (top 33%) 3-month average DCAA and TCAA levels with high specificity (0.79 and 0.78, respectively) but relatively low sensitivity (0.47 and 0.50, respectively). Collecting two or three urine samples from each participant improved the classification. The poor reproducibility of the measured urinary DCAA and TCAA concentrations indicate that a single measurement may not accurately reflect individual long-term exposure. Collection of multiple urine samples from one person is an option for reducing exposure classification errors in studies exploring the effects of DBP exposure on reproductive health. - Highlights: • We evaluated the variability of DCAA and TCAA levels in the urine among men. • Urinary DCAA and TCAA levels varied greatly over a 3-month period. • Single measurement may not accurately reflect personal long-term exposure levels. • Collecting multiple samples from one person improved the exposure classification.
The Document Concurrence System is a combination of software modules for routing users' expressions of concurrence with documents. This system enables determination of the current status of concurrences and eliminates the need for the prior practice of manually delivering paper documents to all persons whose approvals were required. This system runs on a server, and participants gain access via personal computers equipped with Web-browser and electronic-mail software. A user can begin a concurrence routing process by logging onto an administration module, naming the approvers and stating the sequence for routing among them, and attaching documents. The server then sends a message to the first person on the list. Upon concurrence by the first person, the system sends a message to the second person, and so forth. A person on the list indicates approval, places the documents on hold, or indicates disapproval, via a Web-based module. When the last person on the list had concurred, a message is sent to the initiator, who can then finalize the process through the administration module. A background process running on the server identifies concurrence processes that are overdue and sends reminders to the appropriate persons.
The Document Concurrence System is a combination of software modules for routing users' expressions of concurrence with documents. This system enables determination of the current status of concurrences and eliminates the need for the prior practice of manually delivering paper documents to all persons whose approvals were required. This system runs on a server, and participants gain access via personal computers equipped with Web-browser and electronic-mail software. A user can begin a concurrence routing process by logging onto an administration module, naming the approvers and stating the sequence for routing among them, and attaching documents. The server then sends a message to the first person on the list. Upon concurrence by the first person, the system sends a message to the second person, and so forth. A person on the list indicates approval, places the documents on hold, or indicates disapproval, via a Web-based module. When the last person on the list has concurred, a message is sent to the initiator, who can then finalize the process through the administration module. A background process running on the server identifies concurrence processes that are overdue and sends reminders to the appropriate persons.