Monitoring strip mining and reclamation with LANDSAT data in Belmont County, Ohio

The utility of LANDSAT digital data for mapping and monitoring surface mines in Belmont County, Ohio was investigated. Two data sets from 1976 and 1979 were processed to classify level 1 land covers and three strip mine categories in order to examine change over time and assess reclamation efforts. The two classifications were compared with aerial photographs. Results of the accuracy assessment show that both classifications are approximately 86 per cent correct, and that surface mine change detection (date-to-date comparison) is facilitated by the digital format of LANDSAT data

An Inventory of Ohio's Land Use/Land Cover as Seen by Landsat

LANDSAT 2 (Land Satellite) was launched at Vandenburg, AFB, California on January 22, 1975. The satellite orbits the earth at an altitude of about 920 km (570 miles) and scans the earth's surface in a continuous track 185 km (115 miles) wide. LANDSAT 2 passes over the same spot every 18 days transmitting scanned data to receiving stations scattered around the globe. LANDSAT's continuously-scanning sensors provide useful information about the earth, one of the most important categories being land use. The statistics contained in the appendices of this report represent acreage and percentage of seven types of land cover in Ohio as seen by LANDSAT. The inventory represents a trial effort at determining the Sate's land cover by a method which is inexpensive, reliable, accurate and rapid. Given a successful method, the inventory and periodic updates could provide information to land use decision-makers and, over a period of time, would reveal patterns of land use change. Technical aspects of the project (process, methodology, and verification) are discussed in Schaal (1977) and Schmidt (1976)

Multi-National Topics Maps for Parliamentary Debate Analysis

In recent years, automated political text processing became an indispensable requirement for providing automatic access to political debate. During the Covid-19 worldwide pandemic, this need became visible not only in social sciences but also in public opinion. We provide a path to operationalize this need in a multi-lingual topic-oriented manner. Using a publicly available data set consisting of parliamentary speeches, we create a novel process pipeline to identify a good reference model and to link national topics to the cross-national topics. We use design science research to create this process pipeline as an artifact

Cardiorespiratory Responses to Underwater Treadmill Running Versus Land-Based Treadmill Running

Underwater (UW) running provides a low load-bearing form of supplementary training that can be used for recovery and rehabilitation while maintaining cardiovascular fitness. Whether it elicits a cardiorespiratory training stimulus comparable to that of land-based (LB) running is seemingly unclear. The purpose of this study was to compare cardiorespiratory responses between underwater treadmill running and land-based running. Fourteen male triathletes completed trials at maximal and submaximal workloads for each of three conditions: running on an underwater treadmill with AQx® water running shoes, running on an underwater treadmill barefoot, and running on a land-based treadmill. No differences between groups were found for measures of oxygen consumption (VO2), rating of perceived exertion (RPE), or respiratory exchange rate (RER) across modalities for maximal trials; however heart rate (HR) was greater during land-based running than underwater treadmill running. No group differences were found for HR, RPE, and RER across modalities for submaximal trials; however, VO2 was significantly greater during land-based running than underwater treadmill running. We concluded that the cardiorespiratory training stimulus during underwater treadmill running was comparable to that of land-based running at maximal exertion levels, with the exception of HR, and therefore could be an effective form of supplemental training during rehabilitation. At submaximal levels, underwater treadmill running elicited a less rigorous training stimulus than land-based running in terms of VO2 and therefore is a less effective form of supplemental training

CHRI sis at the NICU: The Medley with Midazolam

Approximately 1.5 million neonates undergo anesthesia for surgical procedures in the United States every year1. Midazolam is a commonly used anesthetic agent used in the Neonatal Intensive Care Unit (NICU). It is used to sedate neonates and facilitates complex procedures such as mechanical ventilation.2 The extensive use of midazolam has raised questions about whether it affects the cognitive development of infants. In 2014, the International Anesthesia Research Society released a statement saying, “Surgeries and procedures requiring anesthetic and sedative drugs that could reasonably be delayed should possibly be postponed because of the potential risk to the developing brain of infants, toddlers, and preschool children”. 3 Although some evidence shows that midazolam exposure could harm an infant’s cognitive development, little is known about what parts of the developing brain are directly affected by midazolam. Additionally, research has yet to uncover whether the effects of midazolam persist into adulthood. In order to examine the consequences of midazolam exposure, a holistic system biology approach should be implemented. Experimental data from four different levels ─ the molecular level, the physical trait level, the behavioral level, and “omics” level would help address these issues. Our objective is to investigate how prolonged exposure to midazolam affects cellular as well as behavioral functions. A rodent model was implemented to study the effects at infanthood, adolescence, and adulthood. Our molecular results revealed that midazolam could potentially cause disturbances in key brain protein levels. Additionally, midazolam could potentially contribute to social deficits as evidenced by behavioral results. Overall, the results all point to midazolam\u27s potential to delay proper neurodevelopment.https://digitalcommons.unmc.edu/surp2021/1028/thumbnail.jp

Preconscious control of stereotype activation through chronic egalitarian goals

This research shows stereotype activation is controlled by chronic egalitarian goals. In the first 2 studies it was found that the stereotype of women is equally available to individuals with and without chronic goals, and the discriminant validity of the concept of egalitarian goals was established. In the next 2 experiments, differences in stereotype activation as a function of this individual difference were found. In Study 3, participants read attributes following stereotypical primes. Facilitated response times to stereotypical attributes were found for nonchronics but not for chronics. This lack of facilitation occurred at stimulus onset asynchronies (SOAs) where effortful correction processes could not operate, demonstrating preconscious control of stereotype activation due to chronic goals. In Study 4, inhibition of the stereotype was found at an SOA where effortful processes of stereotype suppression could not operate. The data reveal that goals are activated and used preconsciously to prevent stereotype activation, demonstrating both the controllability of stereotype activation and the implicit role of goals in cognitive control. The current research addresses an important question for understanding both the nature of stereotyping and the nature of cognitive control: Can one's commitment to a goal lead to control over th

Documentation technique : équipement et réparation des livres

For robots of increasing complexity such as humanoid robots, conventional identification of rigid body dynamics models based on CAD data and actuator models becomes difficult and inaccurate due to the large number of additional nonlinear effects in these systems, e.g., stemming from stiff wires, hydraulic hoses, protective shells, skin, etc. Data driven parameter estimation offers an alternative model identification method, but it is often burdened by various other problems, such as significant noise in all measured or inferred variables of the robot. The danger of physically inconsistent results also exists due to unmodeled nonlinearities or insufficiently rich data. In this paper, we address all these problems by developing a Bayesian parameter identification method that can automatically detect noise in both input and output data for the regression algorithm that performs system identification. A post-processing step ensures physically consistent rigid body parameters by nonlinearly projecting the result of the Bayesian estimation onto constraints given by positive definite inertia matrices and the parallel axis theorem. We demonstrate on synthetic and actual robot data that our technique performs parameter identification with 10 to 30% higher accuracy than traditional methods. Due to the resulting physically consistent parameters, our algorithm enables us to apply advanced control methods that algebraically require physical consistency on robotic platforms

Dynamics of commitment and contribution quality in collaborative communities

It is well-known that commitment is an important ingredient for contributions of high quality. With the internet heading towards being an actionable social space, rather than a collection of web-sites, the issue of quality becomes crucial for sharing knowledge and action in collaborative scenarios. We propose a case study for the investigation of the influence of time, user feedback and interface complexity on contribution quality. We plan to exploit different online user groups across two different temporal phases for the evaluation