A Comparison of the Achievement of Selected Students in High School Social Studies Taught by the Team Teaching Method and the Traditional Method

It was the purpose of this study to compare learning outcomes of students taught by traditional methods with that of students instructed by certain selected arrangements of resources commonly associated with the teaching team approach

The NACA's High Speed Flight Research Station and the Development of Reaction Control Systems

This presentation and companion text describe the history of the development of Reaction Control Systems

A multi-method approach to delineate and validate migratory corridors

Context: Managers are faced with numerous methods for delineating wildlife movement corridors, and often must make decisions with limited data. Delineated corridors should be robust to different data and models. Objectives: We present a multi-method approach for delineating and validating wildlife corridors using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania. Methods: We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and Maxent), to generate resource selection functions (RSFs) and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type. Results: Both data types produced similar RSFs. Wildebeest consistently selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with highest probability of use. Conclusions: The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information

The wandering spleen: an unusual case of thrombocytopenia

Thrombocytopenia is a common laboratory finding in current medical practices. The workup of thrombocytopenia can be challenging with numerous causes that can be included in the differential diagnosis. Thrombocytopenia can be due to bone marrow hypoproliferation, peripheral destruction, or sequestration. This paper presents a case of isolated thrombocytopenia in a young female and discusses the causes of thrombocytopenia

UR-350 Quantum Game Theory

Quantum computing is a computing paradigm that utilizes the properties of quantum mechanics such as superposition, interface and entanglement for data processing and other tasks. Quantum computing can be used to work on the same problems existing supercomputers do but in a much more efficient manner. Classical game theory is a process of modeling that is widely used in AI applications. The extension of this theory to the quantum field is known as quantum game theory. It can be a promising tool for overcoming critical problems in quantum communication and the implementation of quantum artificial intelligence. Quantum game theory allows the player(s) to formulate strategies differing from the conventional way of playing a game. We review the performance of classical and quantum strategies on five classical games by analyzing the logic and outcomes of each approach

Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains

Multi-modal foundation models are typically trained on millions of pairs of natural images and text captions, frequently obtained through web-crawling approaches. Although such models depict excellent generative capabilities, they do not typically generalize well to specific domains such as medical images that have fundamentally shifted distributions compared to natural images. Building generative models for medical images that faithfully depict clinical context may help alleviate the paucity of healthcare datasets. Thus, in this study, we seek to research and expand the representational capabilities of large pretrained foundation models to medical concepts, specifically for leveraging the Stable Diffusion model to generate domain specific images found in medical imaging. We explore the sub-components of the Stable Diffusion pipeline (the variational autoencoder, the U-Net and the text-encoder) to fine-tune the model to generate medical images. We benchmark the efficacy of these efforts using quantitative image quality metrics and qualitative radiologist-driven evaluations that accurately represent the clinical content of conditional text prompts. Our best-performing model improves upon the stable diffusion baseline and can be conditioned to insert a realistic-looking abnormality on a synthetic radiology image, while maintaining a 95% accuracy on a classifier trained to detect the abnormality.Comment: 17 pages, 8 figure

Device-Independent Quantum Key Distribution with Generalized Two-Mode Schrödinger Cat States

We show how weak nonlinearities can be used in a device-independent quantum key distribution (QKD) protocol using generalized two-mode Schrödinger cat states. The QKD protocol is therefore shown to be secure against collective attacks and for some coherent attacks. We derive analytical formulas for the optimal values of the Bell parameter, the quantum bit error rate, and the device-independent secret key rate in the noiseless lossy bosonic channel. Additionally, we give the filters and measurements which achieve these optimal values. We find that, over any distance in this channel, the quantum bit error rate is identically zero, in principle, and the states in the protocol are always able to violate a Bell inequality. The protocol is found to be superior in some regimes to a device-independent QKD protocol based on polarization entangled states in a depolarizing channel. Finally, we propose an implementation for the optimal filters and measurements