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Actual and Perceived Effects of Anabolic Steroid Use on Maximal Strength Performance: A Brief Review
No full textAnabolic steroids (AS) have been repeatedly identified as an effective way to increase muscle size, strength, and plasma free-testosterone levels with or without exercise. Improving these variables can give athletes a performance advantage in competitive sports. Steroid use is generally a taboo subject around athletes, and as such, it represents a powerful psychological tool as much as it acts physiologically. The expectancy effect of AS is so powerful that even administration of a “steroid placebo” can significantly increase one repetition maximum (1RM) in advanced powerlifters and varsity athletes over a short intervention. The motivational and self-efficacy components of believed AS usage can improve strength at a significantly faster rate than high intensity resistance training alone. Not only do AS work physiologically to increase muscle size and strength, but AS administration may alter intensity perception, resulting in notable strength improvements
The Napkin Sketch Pilot Study: A minute-paper reflection in pictorial form
Get PDFThis paper presents an evidence-based practice pilot study of the potential cognitive benefits of requiring students to create sketches that summarize course material in ways different than presented in class. This exercise is termed a “napkin sketch” to articulate to students the benefits of simple sketches to communicate ideas – as is often done by engineers in practice. The purpose of the study was to investigate how this napkin sketch activity addresses three concerns of engineering educators: creativity, visualization and communication, and knowledge retention. Specific objectives of the study were to generate conclusions regarding the activity’s ability to (1) provide an outlet for, and a means of encouraging creativity, (2) provide an opportunity for students to visualize and communicate what they have learned through drawings rather than equations or writing, and (3) encourage knowledge retention by providing a mechanism for students to think about and describe concepts learned in the classroom differently than for other requirements. The scope of this paper includes the generation, implementation, and analysis of the napkin sketch activity in three civil engineering courses across eight different class sections in the spring and fall of 2019 at the U.S. Military Academy, a small, public, undergraduate-only four-year college in the northeast United States. The motivation for the study stems from evidence-based practices of re-representation from educational psychology, minute papers from educational research, the growing shift to computer-aided design and away from hand drawing, and recent research suggesting our engineering programs may be degrading student creativity. A between-subjects quasi-experimental setup examined four activity implementations and 249 sketches were collected. Sketch creativity was assessed by three instructors using a creativity rubric adapted from literature. The sketch creativity scores, along with individual student academic and course performance data, were analyzed using standard least squares regression and machine learning techniques to investigate the effect of sketching on creativity and understanding of course material. An anonymous and optional survey was also provided to a total of 56 students, with 21 students responding (37.5%). The following key conclusions can be drawn from the study: (1) the activity does encourage students to think about the material differently, and provides a means for creative students to express lesson content creatively; however, assessment bias, selection bias, and the inherent difficulty in assessing creativity does not allow us to draw conclusions about the creativity of engineering students in any absolute sense from the collected data; (2) incorporating an emphasis on freehand sketching into the engineering curriculum could have positive effects toward developing creativity and pictorial communication skills; (3) there was evidence in the data suggesting that the sample populations examined in the study are experiencing degradation in creativity between sophomore and senior level coursework, which was an idea expressed in the literature; (4) the sketch creativity scores are higher when it is conducted after blocks of material and performed outside of class
Implementing Abbreviated Personas into Engineering Education
Get PDFPersonas are fictional archetypal consumers that aid designers and engineers in more effectively creating products with a human interface. As more products shift from strict utilitarian function to meeting additional physical and psychological needs, designers and engineers must implement emotional design in more domains. Learning to employ personas to explore elements of emotional design is beneficial in an academic course and capstone project as these personas allow students to consider engineering requirements from the perspective of Donald Norman’s three aspects of emotional design: visceral, behavioral, and reflective. In this paper, we present an approach to evaluate the efficacy of using abbreviated personas, which are truncated personas containing typical user biographic information, goals, habits, or experiences. In our first experiment at Stanford University the students focused on the use of and outcome from the abbreviated personas and not the persona generation itself. The lessons learned from this experiment were then applied in a capstone course at the US Military Academy to better understand the full extent of implementation into engineering education. The automotive design capstone originated in a mechanical engineering course focused on engineering engagement through story-telling and included three distinct presentation methods for abbreviated personas at a public exhibition. Over 250 participants interacted with the abbreviated personas and manipulated an analog display based on their understanding of each persona. From these participants, 82 provided written feedback and completed exit surveys on the presentation methods for the abbreviated personas. The data indicate that despite some differences between the presentation methods, all the abbreviated personas contained enough information for making design decisions based on user emotion and requirements. The second application of abbreviated personas builds on this notion and unifies the presentation method to focus on the inputs of the abbreviated personas throughout the design/build process in the capstone. Team member interviews and surveys will capture the data from this iteration
Cooperative Aerial Search and Localization Using Lissajous Patterns
Get PDFThis paper presents a cooperative aerial search-and-localization framework for applications where knowledge about the target of concern is minimal. The proposed framework leverages the sweeping oscillatory properties of Lissajous curves to improve an agent\u27s chances of encountering a target. To accurately estimate the states of cooperative search drones, a discrete-time linear Lissajous motion model approximation is presented in such a way that uncertainty in physical model parameters can be accounted for. These uncertainties are propagated through estimation formulas to improve both agent and target localization relative to a static base station. Numerous experiments conducted in a physics-driven simulation environment show that Lissajous search patterns are a logical and effective substitute for many existing search pattern standards. Furthermore, parametric Monte Carlo simulation studies validate the proposed estimation framework as a more accurate target localizer than other traditional methods which do not account for inaccuracy in the motion model. These techniques hold promise for both static and dynamic target search-and-localization scenarios, allowing for robust estimation by eliminating the need for knowledge of low-level control input to search agents
A Generalized Bayesian Approach for Localizing Static Natural Obstacles on Unpaved Roads
Get PDFThis paper presents an approach that implements sensor fusion and recursive Bayesian estimation (RBE) to improve a vehicle\u27s ability to perform obstacle detection and localization in unpaved road environments. The proposed approach utilizes RADAR, LiDAR and stereovision fully for sensor fusion to detect and localize static natural obstacles. Each sensor is characterized by a probabilistic sensor model which quantifies level of confidence (LOC) and probability of detection (POD) associatively. Deploying these sensor models enables the fusion of heterogeneous sensors without extensive formulations and with the incorporation of each sensor\u27s strengths. An Extended Kalman filter (EKF) is formulated and implemented for robust and computationally efficient RBE of obstacles\u27 locations while a sensor-equipped vehicle moves and observes them. Results with a test vehicle show the successful detection and localization of a static natural object on an unpaved road has demonstrated the effectiveness of the proposed approach
Analysis and Design of One-Way Steel-Plate Composite Walls for Far-Field Blast Effects
No full textThis paper presents the development of normalized total force-total impulse (P-I) diagrams for analyzing and designing steel-plate composite (SC) walls to resist far-field blast loads. The P-I diagrams depict contours of constant damage states created using a single-degree-of-freedom (SDOF) model for one-way SC wall panels subjected to uniform pressure loading resulting from far-field blasts. The resistance function for uniform pressure loading was developed using a novel (hybrid experimental-numerical) approach that eliminated the need for specialized testing and loading equipment. The hybrid approach consisted of (1) conducting four-point bending tests, (2) developing and benchmarking three-dimensional (3D) finite-element (FE) models for the tests, (3) using the benchmarked FE models to conduct numerical simulations for uniform pressure loading, and (4) idealizing the resistance function for uniform pressure using a bilinear relationship. The SDOF model and idealized resistance functions were further benchmarked using results from shock-tube tests conducted on SC wall panels. The benchmarked SDOF model was used to conduct parametric analyses leading to the development of ductility-dependent total pressure-total impulse (P-I) diagrams. These P-I diagrams were validated using the experimental results from blast tests and additional results generated using the benchmarked FE models. The P-I diagrams, along with the ductility-dependent damage states, are recommended for the design of SC wall panels subjected to far-field blast loading
Dean\u27s Significant Activities Report 01-31-2020
Get PDFThe Dean’s Weekly Significant Activities Report lists all activities conducted within the Departments, Centers & Staff. The Report is provided to the Dean and Directorate personnel for situational awareness.https://digitalcommons.usmalibrary.org/sigact/1028/thumbnail.jp
Physiological versus Self-Report Measures of Arousal During Tactical Training Involving a Synthetic Topographic Environment
No full textThis research examines the relationship between the electrodermal activity (EDA) of 43 West Point Cadets while viewing military tactics displays and compares that to results from the Self-Assessment Manikin (SAM; Bradley & Lang, 1994). First there is a need to understand how EDA varies between two different types of presentation formats. Second it was expected that the EDA data would negatively correlate to self-report data based on previous research (Boyce, Reyes, et al., 2016), and third was that EDA and self-report data would be able to predict performance. Results did not indicate significant differences based on display type, however the results did support the negative correlation between EDA and SAM. Finally there was a trend toward predicting performance but it did not reach statistically significant levels, warranting the need for further investigation
Advancing the Research and Development of Assured Artificial Intelligence and Machine Learning Capabilities
No full textArtificial intelligence (AI) and machine learning (ML) have become increasingly vital in the development of novel defense and intelligence capabilities across all domains of warfare. An adversarial AI (A2I) and adversarial ML (AML) attack seeks to deceive and manipulate AI/ML models. It is imperative that AI/ML models can defend against these attacks. A2I/AML defenses will help provide the necessary assurance of these advanced capabilities that use AI/ML models. The A2I Working Group (A2IWG) seeks to advance the research and development of assured AI/ML capabilities via new A2I/AML defenses by fostering a collaborative environment across the U.S. Department of Defense and U.S. Intelligence Community. The A2IWG aims to identify specific challenges that it can help solve or address more directly, with initial focus on three topics: AI Trusted Robustness, AI System Security, and AI/ML Architecture Vulnerabilities
Finding globally optimal macrostructure in multiple relation, mixed-mode social networks
No full textFrom the outset, computational sociologists have stressed leveraging multiple relations when blockmodeling social networks. Despite this emphasis, the majority of published research over the past 40 years has focused on solving blockmodels for a single relation. When multiple relations exist, a reductionist approach is often employed, where the relations are stacked or aggregated into a single matrix, allowing the researcher to apply single relation, often heuristic, blockmodeling techniques. Accordingly, in this article, we develop an exact procedure for the exploratory blockmodeling of multiple relation, mixed-mode networks. In particular, given (a) N1 role= presentation style= display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative; \u3eN1N1 actors, (b) N2 role= presentation style= display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative; \u3eN2N2 events, (c) an (N1×N1) role= presentation style= display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative; \u3e(N1×N1)(N1×N1) binary one-mode network depicting the ties between actors, and (d) an (N1×N2) role= presentation style= display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative; \u3e(N1×N2)(N1×N2) binary two-mode network representing the ties between actors and events, we use integer programming to find globally optimal (P1×P1|P1×P2) role= presentation style= display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative; \u3e(P1×P1|P1×P2)(P1×P1|P1×P2) image matrices and partitions, where P1 role= presentation style= display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative; \u3eP1P1 and P2 role= presentation style= display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative; \u3eP2P2 represent the number of actor and event positions, respectively. Given the problem’s computational complexity, we also develop an algorithm to generate a minimal set of non-isomorphic image matrices, as well as a complementary, easily accessible heuristic using the network analysis software Pajek. We illustrate these concepts using a simple, hypothetical example, and we apply our techniques to a terrorist network