Toward A Realization Of Psycholinguistic Principles In The Esl Reading Class 1

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98335/1/j.1467-1770.1977.tb00297.x.pd

"Mysteries" of Modern Physics and the Fundamental Constants c, h, and G

We review how the kinematic structures of special relativity and quantum mechanics both stem from the relativity principle, i.e., "no preferred reference frame" (NPRF). Essentially, NPRF applied to the measurement of the speed of light c gives the light postulate and leads to the geometry of Minkowski space, while NPRF applied to the measurement of Planck's constant h gives "average-only" projection and leads to the denumerable-dimensional Hilbert space of quantum mechanics. These kinematic structures contain the counterintuitive aspects ("mysteries") of time dilation, length contraction, and quantum entanglement. In this essay, we extend the application of NPRF to the gravitational constant G and show that it leads to the "mystery" of the contextuality of mass in general relativity. Thus, we see an underlying coherence and integrity in modern physics via its "mysteries" and the fundamental constants c, h, and G. It is well known that Minkowski and Einstein were greatly influenced by David Hilbert in their development of special relativity and general relativity, respectively, but relating those theories to quantum mechanics via its non-Boolean Hilbert space kinematics is perhaps surprising.Quanta 2022; 11: 5–14

Inferno: Side-channel Attacks for Mobile Web Browsers

We demonstrate power consumption as a side-channel on mobile devices. While web pages may look aesthetically similar, the web browser exercises different behaviors while rendering the underlying code. The variance between the browser’s behavior and power consumption implies that different webpages consume different amounts of power. Thus, webpages can be uniquely identified from one another by analyzing power traces collected during a page load. While power channel attacks and defenses have been analyzed for fixed function units such as secure cryptoprocessors, this side- channel has not been studied for general-purpose systems such as mobile devices. In our evaluation, we use this side-channel to reveal a mobile user’s browsing activity from the hardware level with 80% accuracy. In addition, we attempt to develop countermeasures to combat this type of attack. We use two approaches to decrease information leakage: normalizing the computational workload to make a signal indistinguishable or increasing the amount of computational noise to make a signal incomparable. To do this, we altered DVFS (Dynamic Voltage and Frequency Scaling) to alter CPU frequency. We noticed that holding CPU frequency constant improved the accuracy of our machine learning classification. Thus, we developed a CPU governor that would change the frequency randomly. This defense managed to reduce the accuracy of the attack to 26%.Electrical and Computer Engineerin

GPUfs: The Case for Operating System Services on GPUs

Due to their impressive price/performance and performance/watt curves, GPUs have become the processor of choice for many types of intensively parallel computations from data mining to molecular dynamics simulations Unfortunately, GPU programming models are still almost entirely lacking core system abstractions, such as files and sockets, that CPU programmers have taken for granted for decades. Today's GPU is capable of amazing computational feats when fed with the right data and managed by application code on the host CPU, but it is incapable of initiating basic system interactions for itself, such as reading an input file from a disk. Because core system abstractions are unavailable to GPU code, GPU programmers today face many of the same challenges CPU application developers did a half-century ago-particularly the constant reimplementation of system abstractions such as data movement and management operations. We feel the time has come to provide GPU programs with the useful system services that CPU code already enjoys. This goal emerges from a broader trend to integrate GPUs more cleanly with operating systems (OS), as exemplified by recent work to support pipeline composition of GPU tasks Two key GPU characteristics make developing OS abstractions for GPUs challenging: data parallelism, and independent memory system. GPUs are optimized for Single Program Multiple Data (SPMD) parallelism, where the same program is used to concurrently process many different parts of the input data. GPU programs typically use tens of thousands of lightweight threads running similar or identical code with little control-flow variation. Conventional OS services, such as the POSIX file system API, were not built with such an execution environment in mind. In GPUfs, we had to adapt both the API semantics and its implementation to support such massive parallelism, allowing thousands of threads to efficiently invoke open, close, read, or write calls simultaneously. To feed their voracious appetites for data, high-end GPUs usually have their own DRAM storage. A massively parallel memory interface to this DRAM offers high bandwidth for local access by GPU code, but GPU access to the CPU's system memory is an order of magnitude slower, because it requires communication over bandwidth-constrained, higher latency PCI Express bus. In the increasingly common case of systems with multiple discrete GPUs- http://doi.acm.org/10.1145/2656206 standard in Apple's new Mac Pro, for example-each GPU has its own local memory, and accessing a GPU's own memory can be an order of magnitude more efficient than accessing a sibling GPU's memory. GPUs thus exhibit a particularly extreme non-uniform memory access (NUMA) property, making it performance-critical for the OS to optimize for access locality in data placement and reuse across CPU and GPU memories. GPUfs, for example, distributes its buffer cache across all CPU and GPU memories to enable idioms like process pipelines that read and write files from the same or different processors. To highlight the benefits of bringing core OS abstractions such as files to GPUs, we show the use of GPUfs in a self-contained GPU application for string search on NVIDIA GPUs. This application illustrates how GPUfs can efficiently support irregular workloads, in which parallel threads open and access dynamically-selected files of varying size and composition, and the output size might be arbitrarily large and determined at runtime. Our version is about seven times faster than a parallel 8-core CPU run on a full Linux kernel source stored in about 33,000 small files. While currently our prototype benchmarks represent only a few simple application data points for a single OS abstraction, they suggest that OS services for GPU code are not only hypothetically desirable, but are feasible and efficient in practice

GPUfs: Integrating a File System with GPUs

As GPU hardware becomes increasingly general-purpose, it is quickly outgrowing the traditional, constrained GPU-as-coprocessor programming model. To make GPUs easier to program and improve their integration with operating systems, we propose making the host’s file system directly accessible to GPU code. GPUfs provides a POSIX-like API for GPU programs, exploits GPU parallelism for efficiency, and optimizes GPU file access by extending the host CPU’s buffer cache into GPU memory. Our experiments, based on a set of real benchmarks adapted to use our file system, demonstrate the feasibility and benefits of the GPUfs approach. For example, a self-contained GPU program that searches for a set of strings throughout the Linux kernel source tree runs over seven times faster than on an eight-core CPU

Occipital nerve stimulation for the treatment of intractable chronic migraine headache: ONSTIM feasibility study

Background: Medically intractable chronic migraine (CM) is a disabling illness characterized by headache ≥15 days per month

Evaluation of an epigenetic assay for predicting repeat prostate biopsy outcome in African American men

OBJECTIVE: To evaluate an epigenetic assay performed on tissue from negative prostate biopsies in a group of African American (AA) men undergoing repeat biopsy, and to compare accuracy for predicting repeat biopsy outcome to prior studies conducted in predominantly Caucasian populations. MATERIALS AND METHODS: The study population consisted of 211 AA men from 7 urology centers across the United States; all of whom were undergoing 12-core transrectal ultrasound-guided repeat biopsy within 30 months from a negative index biopsy. All biopsy cores from the negative index biopsy were profiled for the epigenetic biomarkers GSTP1, APC, and RASSF1 using ConfirmMDx for Prostate Cancer (MDxHealth, Irvine, CA). RESULTS: Upon repeat biopsy, 130 of 211 subjects (62%) had no prostate cancer (PCa) detected and 81 of 211 (38%) were diagnosed with PCa. Of the subjects with PCa, 54 (67%) were diagnosed with Gleason score (GS) = 7 disease. For detection of PCa at repeat biopsy, ConfirmMDx sensitivity was 74.1% and specificity was 60.0%, equivalent to prior studies (P = .235 and .697, respectively). For detection of GS >= 7 PCa, sensitivity was 78% and specificity was 53%. The negative predictive values for detection of all PCa and GS >= 7 PCa were 78.8% and 94.2%, respectively. CONCLUSION: In this group of AA men, we successfully validated an epigenetic assay to assess the need for repeat biopsy. Results were consistent with previous studies from predominantly Caucasian populations. Therefore, the ConfirmMDx assay is a useful tool for risk stratification of AA men who had an initial negative biopsy