Miracle-dz/UniFAR-FTUs huggingface dataset:
An online learning approach to dynamic pricing for demand response

In this paper, the problem of optimal dynamic pricing for retail electricity with an unknown demand model is considered. Under the day-ahead dynamic pricing (a.k.a. real time pricing) mechanism, a retailer obtains electricity in a twosettlement wholesale market and serves its customers in real time. Without knowledge on the aggregated demand function of its customers, the retailer aims to maximize its retail surplus by sequentially adjusting its price based on the behavior of its customers in the past. An online learning algorithm, referred to as piecewise linear stochastic approximation (PWLSA), is proposed. It is shown that PWLSA achieves the optimal rate of learning defined by the growth rate of cumulative regret. In particular, the regret of PWLSA is shown to grow logarithmically with respect to the learning horizon, and no other on-line learning algorithm can have the growth rate slower than that of PWLSA. Simulation studies are presented using traces of actual day-ahead prices, and PWLSA compares favorably under both static and dynamically changing parameters.
What Keeps Chinese Students Motivated in Doing Math Homework? An Empirical Investigation

Background As many students face the enduring challenge of maintaining their motivation to complete homework assignments, there is a critical need to pay close attention to homework motivation management (i.e., students’ efforts to sustain or enhance their motivation in order to complete homework assignments that might be boring or difficult). Yet, in spite of research showing that homework motivation has a powerful influence on homework performance and academic achievement, there have been few attempts to systematically investigate models of factors that influence homework motivation management. Purpose The current investigation examines empirical models of motivation management for Chinese students in the context of math homework, with models informed by key motivation theories, including self-regulation of motivation, expectancy-value, and volitional control. Research Design The study reported here used cross sectional survey data. Participants The participants were 1,799 high school students from 46 classes in China. Results Results from multilevel analyses indicated that, at the class level, motivation management was positively associated with homework interest, but was negatively associated with teacher feedback. At the student level, motivation management was positively related to managing emotion, managing time, students’ interest in homework, cognitive reappraisal, expectancy belief, and time on sports. Meanwhile, motivation management was negatively associated with value belief and time on TV. Conclusion The current investigation found that some results were in line with key motivation theories and related findings with U.S. students (e.g., managing time, and homework interest at the student level). In addition, it suggests that other results may be influenced by cultural and societal differences (e.g., gender, value belief, and teacher feedback). Consequently, it would be informative to pursue this line of research in cross-cultural settings. With respect to promoting student motivation in the homework process, it would be beneficial to pay more close attention to the role of homework interest, expectancy belief, and student initiatives (e.g., managing time, managing emotion, and cognitive reappraisal).
Nova: A Robustness-oriented Byzantine Fault Tolerance Protocol

With the increased complexity, malicious faults have become an important reasons that affect the reliability of the distributed system, especially the web-scale infrastructures, i.e. Amazon S3, Google AppEngine etc. Most such systems assume benign fault model which can’t depict the malicious actions. The goal of Byzantine Fault Tolerance protocol (BFT for short) is to mask the malicious behaviors and it has been proved that some new proposed BFTs are suitable to support practical applications. But these BFTs still lack in robustness, a simple fault injection may cause significantly decrease in throughput or run in low throughput without violating the BFT safety property. We propose a new robustness-oriented BFT named Nova. Experiments show Nova has comparable throughput as PBFT in normal case and behave stably under the malicious attack. Compared with other BFTs, Nova can support practical applications more effectively.
Fully distributed algorithms for blind rendezvous in cognitive radio networks

Rendezvous process is the cornerstone to construct Cognitive Radio Networks (CRNs), through which a secondary user can establish a link for communication with its neighbor on a common channel. Although many blind rendezvous algorithms have been proposed which do not rely on a central controller or a common control channel, all of these works still rely on the global parameters such as the number of licensed channels N and the number of users. This paper aims to design fully distributed blind rendezvous algorithms only based on each user's local information. We first give the Synchronous Check & Hop (SCH) algorithm for two synchronous users where they start the rendezvous process at the same time. The SCH algorithm guarantees rendezvous in O(min{ka,kb} N) time slots where ka,kb are the corresponding number of sensed channels of these two users. Our main contribution is a fully distributed algorithm called Conversion Based Hopping (CBH), where each user only uses its identifier (ID) and its number of sensed channels. CBH guarantees rendezvous between two asynchronous users in O((max{ka,kb})2) time slots. To our knowledge, this is the first result with rendezvous time independent of the global parameter N. We also derive a lower bound of rendezvous time between two users as Ω((ka-kg)(kb-kg)) where k_g is the number of their common channels. All of our results also apply to a more general blind rendezvous problem which we call Oblivious Blind Rendezvous where each user is free to assign their local labels to the sensed channels. Extensive simulation results compared with the state-of-the-art rendezvous algorithms corroborate our theoretical analyses.
Perceptually augmented simulator design through decomposition

We approach the problem of determining a general method for augmenting haptic simulators to amplify the perceptually salient aspects of the interaction that induce effective skill transfer. Using such a method, we seek to simplify the design of haptic simulators that can improve training effectiveness without requiring expensive improvements in the capability of the rendering hardware. We present a decomposition approach to the automated design of perceptually augmented simulations, and we describe a user-study of the training effectiveness of a search-task simulator designed using our approach vs. an un-augmented simulator. The results indicate that our decomposition approach allows existing psychophysical findings to be leveraged in the design of haptic simulators that effectively impart skill by targeting perceptually significant aspects of the interaction.
First polarimetric observations and modeling of the FeH F^4 Delta-X^4 Delta system

Lines of diatomic molecules are more temperature and pressure sensitive than atomic lines, which makes them ideal tools for studying cool stellar atmospheres an internal structure of sunspots and starspots. The FeH F^4 Delta-X^4 Delta system represents such an example that exhibits in addition a large magnetic field sensitivity. The current theoretical descriptions of these transitions including the molecular constants involved are only based on intensity measurements because polarimetric observations have not been available so far, which limits their diagnostic value. We present for the first time spectropolarimetric observations of the FeH F^4 Delta-X^4 Delta system measured in sunspots to investigate their diagnostic capabilities for probing solar and stellar magnetic fields. We investigate whether the current theoretical model of FeH can reproduce the observed Stokes profiles including their magnetic properties. The polarimetric observations are compared with synthetic Stokes profiles modeled with radiative transfer calculations. This allows us to infer the temperature and the magnetic field strength of the observed sunspots. We find that the current theory successfully reproduces the magnetic properties of a large number of lines in the FeH F^4 Delta-X^4 Delta system. In a few cases the observations indicate a larger Zeeman splitting than predicted by the theory. There, our observations have provided additional constraints, which allowed us to determine empirical molecular constants. The FeH F^4 Delta-X^4 Delta system is found to be a very sensitive magnetic diagnostic tool. Polarimetric data of these lines provide us with more direct information to study the coolest parts of astrophysical objects.
Not Just a Complication , But a Basic Variation

A literature review on sex differences and women's issues in HIV Women's bodies differ in essential ways from men's. That difference is locked into the genes from the moment of conception. Growth and development unfold the sexual dimorphism so that it exists on every level of biological organization, from the cell to the whole organism. The result is a male-female variation in relationship with the outside world that goes far beyond reproduction to mental outlook, food metabolism and immune responses. Sexual reproduction is important because it weeds out noxious mutations; sexual dimorphism extends the breadth of human abilities, making the species more responsive to a wide range of environments, including the technological culture we have so recently adopted. It is part of the essential biologic pattern, then, that there is a divergence in the male and female response to invasion by HIV. The female mode of response, long dismissed as a trivial biological complication, is better viewed as a central variation on a theme. Studying the way women's bodies differ from men's when confronting HIV is not to be avoided as a superfluous expense. It is vital to learning how HIV causes disease and how to more appropriately treat it. From bench science to postmarketing trials, lack of research on AIDS in women hobbles our efforts to halt the HIV epidemic. Whereas activists once saw such studies as way to achieve early access to experimental treatments when those were our only hope, now we can see this research as a matter of profound scientific equity. This paper reviews the latest findings on female sex as a major determinant in the human relationship with HIV. A revolution in molecular biology is bringing ever greater understanding as to how sexual biology affects the body. It is amazing how little of that seeped into the field of HIV and AIDS.
State-Space Modeling of Wind Turbine Generators for Power System Studies

Mathematical modeling of synchronous and induction generators for wind turbines using state-space representations is presented. Emphasis is given to those models suitable for control schemes of variable-speed wind turbines and their application for different power system studies. The state-space representations provide a convenient way to assess different configurations of fixed and variable-speed wind turbines based on synchronous and induction generators. The modeling approach here presented allows both transient and small-signal stability analysis. As a case study, the performance of fixed and variable-speed wind turbines under faults and voltage sags is assessed. The state-space models are used to investigate the capability of different wind turbine technologies to satisfy Grid Code requirements. An eigenanalysis is included to show the flexibility of the models.
Lower Methane Emissions from Yak Compared with Cattle in Rusitec Fermenters

Globally methane (CH4) emissions from ruminant livestock account for 29% of total CH4 emissions. Inherited variation about CH4 emissions of different animal species might provide new opportunity for manipulating CH4 production. Six rumen-simulating fermenters (Rusitec) were set up for this study lasting for 16 d. The diet consisted of forage to concentrate ratio of 50:50 with barley straw as the forage. Treated vessels were supplied with rumen fluid from yak or cattle (3 vessels per animal species). Microbial growth was measured using 15N as a marker. The microbial community structure from liquid- and solid-fraction of each vessel was determined based on the 16S rRNA genes targeting both bacteria and archaea with MiSeq platform. CH4 yield was lower when the inoculum used from yak than that from cattle (0.26 and 0.33 mmol CH4/g dry matter intake, respectively). Lower H2 production was observed in Rusitec fermenters with rumen fluid from yak compare with that from cattle (0.28 and 0.86 mmol/d, respectively). The apparent digestibility of neutral detergent fiber, the isovalerate percentage with respect to the total amount of volatile fatty acids, the hydrogen recovery, and the proportion of liquid-associated microbial nitrogen derived from ammonia-nitrogen were higher in Rusitec fermenters incubated with rumen fluid from cattle than that from yak. The relative abundances of methanogens were no difference between two animal species. We hypothesize that more H2 production contributes to the higher methane emissions in cattle compare with yak.
Pathophysiological Mechanisms and Diagnostic Markers in Alzheimer’s Disease

Alzheimer’s disease (AD), the most common cause of dementia, is a growing concern. As the life expectancy increases across the globe, the number of affected people is estimated to reach 100 million by 2050. Efforts to develop effective treatments for humans have mostly been based on the assumption that a faulty homeostasis of beta amyloid (Aβ) is the triggering or the driving factor behind this condition. So far these efforts have failed, making a better understanding of other pathophysiological mechanisms behind this disease necessary in order to find new therapeutic approaches. The aim for this thesis was to explore such mechanisms. Besides changes typical of AD, these patients often show signs of vascular disease. In order to explore how white matter changes (WMLs) affects the course of disease, we analyzed CSF levels of phosphorylated tau (P-tau) and assessed WMLs on brain scans in healthy controls and patients with mild cognitive impairment. We found that a pathological level of P-tau and WMLs in the parietal lobes independently increased the risk of developing AD dementia, but that the risk was considerably higher for patients that had both. Next, we analyzed the CSF/plasma ratio of albumin, as a proxy for blood-brain barrier integrity, and found it to be increased in AD and other common dementias. This ratio was not associated with the APOE genotype, as had previously been suggested, or markers of Aβ load. Instead, we found it to be associated with diabetes mellitus and markers of microvascular damage in the brain. We then moved on from vascular factors to other mechanisms suggested in AD.The insulin-like growth factor (IGF) related system is implicated in regulating life-span and in growth-promotion and neuroprotection in the human nervous system. There are reports of changes to the IGF-related system in cognitive disorders. When we analyzed components of this system in healthy controls and patients with AD we found differences in CSF and blood plasma levels of IGF-II and some of its associated binding proteins, possibly reflecting an activated general response to neuronal damage. Lastly, we analyzed CSF biomarkers of synaptic degeneration (neurogranin) and microglial activation (YKL-40) in healthy controls, patients with mild cognitive impairment and patients with common dementias. We found the former to be selectively increased in AD dementia, whereas the latter was increased in both AD and frontotemporal dementia. However, these biomarkers did not improve the diagnostic accuracy of either prodromal AD or AD dementia when compared to established CSF biomarkers of AD. Nevertheless, we think they are useful, since they reflect other processes in AD than Aβ deposition and axonal damage. We hope that the results from this thesis has provided new insights into the pathophysiological mechanisms in AD and that they might suggest novel routes for exploring this complex condition.
HogMap: Using SDNs to Incentivize Collaborative Security Monitoring

Cyber Threat Intelligence (CTI) sharing facilitates a comprehensive understanding of adversary activity and enables enterprise networks to prioritize their cyber defense technologies. To that end, we introduce HogMap, a novel software-defined infrastructure that simplifies and incentivizes collaborative measurement and monitoring of cyber-threat activity. HogMap proposes to transform the cyber-threat monitoring landscape by integrating several novel SDN-enabled capabilities: (i) intelligent in-place filtering of malicious traffic, (ii) dynamic migration of interesting and extraordinary traffic and (iii) a software-defined marketplace where various parties can opportunistically subscribe to and publish cyber-threat intelligence services in a flexible manner. We present the architectural vision and summarize our preliminary experience in developing and operating an SDN-based HoneyGrid, which spans three enterprises and implements several of the enabling capabilities (e.g., traffic filtering, traffic forwarding and connection migration). We find that SDN technologies greatly simplify the design and deployment of such globally distributed and elastic HoneyGrids.
The Discretely-Discontinuous Galerkin Coarse Grid for Domain Decomposition

We present an algebraic method for constructing a highly effective coarse grid correction to accelerate domain decomposition. The coarse problem is constructed from the original matrix and a small set of input vectors that span a low-degree polynomial space, but no further knowledge of meshes or continuous functionals is used. We construct a coarse basis by partitioning the problem into subdomains and using the restriction of each input vector to each subdomain as its own basis function. This basis resembles a Discontinuous Galerkin basis on subdomain-sized elements. Constructing the coarse problem by Galerkin projection, we prove a highorder convergent error bound for the coarse solutions. Used in a twolevel symmetric multiplicative overlapping Schwarz preconditioner, the resulting conjugate gradient solver shows optimal scaling. Convergence requires a constant number of iterations, independent of fine problem size, on a range of scalar and vector-valued second-order and fourth-order PDEs.
Using Semantic Analysis to Classify Search Engine Spam

Search engines have tried many techniques to filter out these spam pages before they can appear on the query results page. In Section 2 we present a collection of current methods that are being used to combat spam. We introduce a new approach to spam detection in Section 3 that uses semantic analysis of textual content as a means of detecting spam. This new approach uses a series of content analyzers combined with a decision tree classifier to determine if a given webpage is spam. Section 4 discusses the implementation of our approach. Our architecture is augments the search engine Lucene by adding a Java-based spam classifier. The spam classifier makes use of the Wordnet word database and the machine learning library Weka to classify web documents as either spam or not spam. We describe the results of our work in Section 5 and finally present our conclusions and future work in Section 6.
Statement of Research Visual Event Perception

People can describe what they see. If you were to see me pick up a pen, you could describe that observation by saying Jee picked up the pen. In doing so, you describe both objects, like people and pens, as well as events, like pickings up. Most machine vision research has focussed on object recognition. In contrast, much of my work for the past six years has focussed on event recognition. A portion of my PhD thesis proposed a theory for event recognition. This theory is summarized in Siskind (1995a). This theory makes three central claims. First, it claims that the notions of support, contact, and attachment play a key role in event perception. Many simple spatial-motion events are characterized by the changing support, contact, and attachment relations between the participant objects. For example, picking up a pen oo a table involves several state changes: the hand comes into contact with and grasps the pen, and the pen ceases to be supported by table and comes to be supported by the hand. Second, it claims that support, contact, and attachment relations are only implicit in the observations; they must be derived from explicit information, such as the positions and orientations of objects, by way of counterfactual simulation embodied in an imagination capacity. For example, one determines that A is supported by imagining the short-term future and not seeing it fall. Furthermore, one determines that A supports B by determining that B is supported but ceases to be supported if A were to be removed. Finally, it claims that such an imagination capacity embodies a naive physical theory rather than a more accurate theory such as classical mechanics. The aforementioned theory was implemented in a computer program called Abigail. Abigail receives animated line drawings as input, performs counterfactual simulation on each frame using a naive physical theory to recover the changing support, contact, and attachment relations between objects represented as collections of line segments, and classiies characteristic sequences of such changing relations as occurrences of various event types. This work was expanded upon in Siskind (1996b). This paper proposes two algorithms that facilitate the perception of events within the aforementioned theory. First, it shows how support, contact, and attachment relations can be inferred from line drawings without counterfactual simulation by an eecient reduction of a theory of kinematics to linear programming. Second, it presents an eecient algorithm for detecting the occurrences …
The catalytic activity of Src is dispensable for translocation to focal adhesions but controls the turnover of these structures during cell motility

The Src family of protein tyrosine kinases is involved in transducing signals at sites of cellular adhesion. In particular, the v‐Src oncoprotein resides in cellular focal adhesions, where it induces tyrosine phosphorylation of pp125FAK and focal adhesion loss during transformation. v‐Src is translocated to cellular focal adhesions by an actin‐dependent process. Here we have used mutant v‐Src proteins that are temperature‐dependent for translocation, but with secondary mutations that render them constitutively kinase‐inactive or myristylation‐defective, to show that neither v‐Src kinase activity nor a myristyl group are required to induce association of v‐Src with actin stress fibres and redistribution to sites of focal adhesions at the stress fibre termini. Moreover, switching the constitutively kinase‐inactive or myristylation‐defective temperature‐sensitive v‐Src proteins to the permissive temperature resulted in concomitant association with tyrosine‐phosphorylated focal adhesion kinase (pp125FAK) and redistribution of both to focal adhesions. However, both catalytic activity and myristylation‐mediated membrane association are required to induce dissociation of pp125FAK from v‐Src, later degradation of pp125FAK and focal adhesion turnover during transformation and cell motility. These observations provide strong evidence that the role of the tyrosine kinase activity of the Src family at sites of cellular focal adhesions is to regulate the turnover of these structures during cell motility.