Promises, Promises

As host of the Olympic Games, China seeks to increase national economic and socialdevelopment and "display to the world a new image of China", and presents the Games as an opportunity to foster democracy, improve human rights and integrate China with the rest of the world. In its Olympic Action Plan promulgated in 2002, China outlined the phases of construction in the run up to the 2008 Games, and the standards to which it would hold itself in the governance and construction of venues, impact on Beijing's environment, increasing social and economic development and providing China's citizenry with greater access to information and technology.The goals and specific commitments that the government has adopted not only have implications for the smooth and successfuloperation of the Olympic Games, but also have the potential to impact on a number of China's international obligations, including its human rights obligations.Despite human rights-related commitments as diverse as transparency and accountability, access to information and freedom of the press, poverty alleviation, an improved standard of living for all people, and compensation for evictions and health issues, the record to date raises serious compliance issues

Probing the Superfluid to Mott Insulator Transition at the Single Atom Level

Quantum gases in optical lattices offer an opportunity to experimentally realize and explore condensed matter models in a clean, tunable system. We investigate the Bose-Hubbard model on a microscopic level using single atom-single lattice site imaging; our technique enables space- and time-resolved characterization of the number statistics across the superfluid-Mott insulator quantum phase transition. Site-resolved probing of fluctuations provides us with a sensitive local thermometer, allows us to identify microscopic heterostructures of low entropy Mott domains, and enables us to measure local quantum dynamics, revealing surprisingly fast transition timescales. Our results may serve as a benchmark for theoretical studies of quantum dynamics, and may guide the engineering of low entropy phases in a lattice

Personality as a Predictor of Student Success in Programming Principles

Large numbers of college students continue to fail to successfully complete programming principles courses. However, little research has addressed potential reasons for student failure. Many educators simply assume that high failure rates are acceptable – that computer programming is difficult and some students simply “don’t get it.” Some researchers (i.e., Bishop-Clark & Wheeler, 1994; Carland & Carland, 1990) have studied personality as a predictor of success in computer programming courses. However, with the exception of Woszczynski & Guthrie (2003), few studies have attempted to gather cognitive profiles (Krause, 2000) and match performance to profile type exhibited. Krause’s work shows that students with identified profiles can apply certain study skills to improve the probability of success in the classroom, and Woszczynski & Guthrie (2003) extended this research to the programming classroom, identifying underperforming cognitive profile groups. This study identified the primary cognitive profile of 236 students in a programming principles course at a southeastern university and matched profile to final average in programming principles I. Overall, intuitive thinkers (NT) tended to perform better in programming principles I than sensor feelers (SF). We found no other differences in performance between other paired profiles. We recommend a number of interventions to reach underperforming groups

NutritionVerse: Empirical Study of Various Dietary Intake Estimation Approaches

Accurate dietary intake estimation is critical for informing policies and programs to support healthy eating, as malnutrition has been directly linked to decreased quality of life. However self-reporting methods such as food diaries suffer from substantial bias. Other conventional dietary assessment techniques and emerging alternative approaches such as mobile applications incur high time costs and may necessitate trained personnel. Recent work has focused on using computer vision and machine learning to automatically estimate dietary intake from food images, but the lack of comprehensive datasets with diverse viewpoints, modalities and food annotations hinders the accuracy and realism of such methods. To address this limitation, we introduce NutritionVerse-Synth, the first large-scale dataset of 84,984 photorealistic synthetic 2D food images with associated dietary information and multimodal annotations (including depth images, instance masks, and semantic masks). Additionally, we collect a real image dataset, NutritionVerse-Real, containing 889 images of 251 dishes to evaluate realism. Leveraging these novel datasets, we develop and benchmark NutritionVerse, an empirical study of various dietary intake estimation approaches, including indirect segmentation-based and direct prediction networks. We further fine-tune models pretrained on synthetic data with real images to provide insights into the fusion of synthetic and real data. Finally, we release both datasets (NutritionVerse-Synth, NutritionVerse-Real) on https://www.kaggle.com/nutritionverse/datasets as part of an open initiative to accelerate machine learning for dietary sensing

Prioritizing MCDC test cases by spectral analysis of Boolean functions

Test case prioritization aims at scheduling test cases in an order that improves some performance goal. One performance goal is a measure of how quickly faults are detected. Such prioritization can be performed by exploiting the Fault Exposing Potential (FEP) parameters associated to the test cases. FEP is usually approximated by mutation analysis under certain fault assumptions. Although this technique is effective, it could be relatively expensive compared to the other prioritization techniques. This study proposes a cost-effective FEP approximation for prioritizing Modified Condition Decision Coverage (MCDC) test cases. A strict negative correlation between the FEP of a MCDC test case and the influence value of the associated input condition allows to order the test cases easily without the need of an extensive mutation analysis. The method is entirely based on mathematics and it provides useful insight into how spectral analysis of Boolean functions can benefit software testing

Androgen ablation mitigates tolerance to a prostate/prostate cancer-restricted antigen

SummaryTo understand the T cell response to prostate cancer, we created transgenic mice that express a model antigen in a prostate-restricted pattern and crossed these animals to TRAMP mice that develop spontaneous prostate cancer. Adoptive transfer of prostate-specific CD4 T cells shows that, in the absence of prostate cancer, the prostate gland is mostly ignored. Tumorigenesis allows T cell recognition of the prostate gland—but this recognition is tolerogenic, resulting in abortive proliferation and ultimately in hyporesponsiveness at the systemic level. Androgen ablation (the most common treatment for metastatic prostate cancer) was able to mitigate this tolerance—allowing prostate-specific T cells to expand and develop effector function after vaccination. These results suggest that immunotherapy for prostate cancer may be most efficacious when administered after androgen ablation