S190 interpretation techniques development and application to New York State water resources

There are no author-identified significant results in this report

S190 interpretation techniques development and application to New York State water resources

There are no author-identified significant results in this report

S190 interpretation techniques development and application to New York State water resources

The author has identified the following significant results. The program has demonstrated that Skylab imagery can be utilized to regularly monitor eutrophication indices of lakes, such as chlorophyll concentration and photic zone depth. The relationship between the blue to green reflectance ratio and chlorophyll concentration was shown, along with changes in lake properties caused by chlorophyll, lignin, and humic acid using reflectance ratios and changes. A data processing technique was developed for detecting atmospheric fluctuations occurring over a large lake

Dynamic Key-Value Memory Networks for Knowledge Tracing

Knowledge Tracing (KT) is a task of tracing evolving knowledge state of students with respect to one or more concepts as they engage in a sequence of learning activities. One important purpose of KT is to personalize the practice sequence to help students learn knowledge concepts efficiently. However, existing methods such as Bayesian Knowledge Tracing and Deep Knowledge Tracing either model knowledge state for each predefined concept separately or fail to pinpoint exactly which concepts a student is good at or unfamiliar with. To solve these problems, this work introduces a new model called Dynamic Key-Value Memory Networks (DKVMN) that can exploit the relationships between underlying concepts and directly output a student's mastery level of each concept. Unlike standard memory-augmented neural networks that facilitate a single memory matrix or two static memory matrices, our model has one static matrix called key, which stores the knowledge concepts and the other dynamic matrix called value, which stores and updates the mastery levels of corresponding concepts. Experiments show that our model consistently outperforms the state-of-the-art model in a range of KT datasets. Moreover, the DKVMN model can automatically discover underlying concepts of exercises typically performed by human annotations and depict the changing knowledge state of a student.Comment: To appear in 26th International Conference on World Wide Web (WWW), 201

Foreign Direct Investments in Business Services: Transforming the Visegrád Four Region into a Knowledge-based Economy?

Foreign direct investments (FDIs) in the service sector are widely attributed an important role in bringing more skill-intensive activities into the Visegrad Four (V4). This region—comprising Poland, the Czech Republic, Hungary and Slovakia—relied heavily on FDIs in manufacturing, which was often found to generate activities with limited skill content. This contribution deconstructs the chaotic concept of “business services” by analysing the actual nature of service sector activities outsourced and offshored to the V4. Using the knowledge-based economy (KBE) as a benchmark, the paper assesses the potential of service sector outsourcing in contributing to regional competitiveness by increasing the innovative capacity. It also discusses the role of state policies towards service sector FDI (SFDI). The analysis combines data obtained from case studies undertaken in service sector outsourcing projects in V4 countries. Moreover, it draws on interviews with senior employees of investment promotion agencies and publicly available data and statistics on activities within the service sector in the region. It argues that the recent inward investments in business services in the V4 mainly utilize existing local human capital resources, and their contribution to the development of the KBE is limited to employment creation and demand for skilled labour

Effective forces in colloidal mixtures: from depletion attraction to accumulation repulsion

Computer simulations and theory are used to systematically investigate how the effective force between two big colloidal spheres in a sea of small spheres depends on the basic (big-small and small-small) interactions. The latter are modeled as hard-core pair potentials with a Yukawa tail which can be both repulsive or attractive. For a repulsive small-small interaction, the effective force follows the trends as predicted by a mapping onto an effective non-additive hard-core mixture: both a depletion attraction and an accumulation repulsion caused by small spheres adsorbing onto the big ones can be obtained depending on the sign of the big-small interaction. For repulsive big-small interactions, the effect of adding a small-small attraction also follows the trends predicted by the mapping. But a more subtle ``repulsion through attraction'' effect arises when both big-small and small-small attractions occur: upon increasing the strength of the small-small interaction, the effective potential becomes more repulsive. We have further tested several theoretical methods against our computer simulations: The superposition approximation works best for an added big-small repulsion, and breaks down for a strong big-small attraction, while density functional theory is very accurate for any big-small interaction when the small particles are pure hard-spheres. The theoretical methods perform most poorly for small-small attractions.Comment: submitted to PRE; New version includes an important quantitative correction to several of the simulations. The main conclusions remain unchanged thoug

Solving the conundrum of intra-specific variation in metabolic rate: A multidisciplinary conceptual and methodological toolkit

Researchers from diverse disciplines, including organismal and cellular physiology, sports science, human nutrition, evolution and ecology, have sought to understand the causes and consequences of the surprising variation in metabolic rate found among and within individual animals of the same species. Research in this area has been hampered by differences in approach, terminology and methodology, and the context in which measurements are made. Recent advances provide important opportunities to identify and address the key questions in the field. By bringing together researchers from different areas of biology and biomedicine, we describe and evaluate these developments and the insights they could yield, highlighting the need for more standardisation across disciplines. We conclude with a list of important questions that can now be addressed by developing a common conceptual and methodological toolkit for studies on metabolic variation in animals

Brain Potentials Highlight Stronger Implicit Food Memory for Taste than Health and Context Associations

Increasingly consumption of healthy foods is advised to improve population health. Reasons people give for choosing one food over another suggest that non-sensory features like health aspects are appreciated as of lower importance than taste. However, many food choices are made in the absence of the actual perception of a food's sensory properties, and therefore highly rely on previous experiences of similar consumptions stored in memory. In this study we assessed the differential strength of food associations implicitly stored in memory, using an associative priming paradigm. Participants (N = 30) were exposed to a forced-choice picture-categorization task, in which the food or non-food target images were primed with either non-sensory or sensory related words. We observed a smaller N400 amplitude at the parietal electrodes when categorizing food as compared to non-food images. While this effect was enhanced by the presentation of a food-related word prime during food trials, the primes had no effect in the non-food trials. More specifically, we found that sensory associations are stronger implicitly represented in memory as compared to non-sensory associations. Thus, this study highlights the neuronal mechanisms underlying previous observations that sensory associations are important features of food memory, and therefore a primary motive in food choice.</p

Hypoxia Due to Cardiac Arrest Induces a Time-Dependent Increase in Serum Amyloid β Levels in Humans

Amyloid β (Aβ) peptides are proteolytic products from amyloid precursor protein (APP) and are thought to play a role in Alzheimer disease (AD) pathogenesis. While much is known about molecular mechanisms underlying cerebral Aβ accumulation in familial AD, less is known about the cause(s) of brain amyloidosis in sporadic disease. Animal and postmortem studies suggest that Aβ secretion can be up-regulated in response to hypoxia. We employed a new technology (Single Molecule Arrays, SiMoA) capable of ultrasensitive protein measurements and developed a novel assay to look for changes in serum Aβ42 concentration in 25 resuscitated patients with severe hypoxia due to cardiac arrest. After a lag period of 10 or more hours, very clear serum Aβ42 elevations were observed in all patients. Elevations ranged from approximately 80% to over 70-fold, with most elevations in the range of 3–10-fold (average approximately 7-fold). The magnitude of the increase correlated with clinical outcome. These data provide the first direct evidence in living humans that ischemia acutely increases Aβ levels in blood. The results point to the possibility that hypoxia may play a role in the amyloidogenic process of AD