cssi/SciSciGPT-SciSciNet huggingface dataset:
Subscription-enhanced content delivery

In existing content delivery systems user accesses are popularly used for predicting the request pattern of contents. In novel web applications such as publish/subscribe services, users explicitly provide statements of interest in the form of subscriptions. These subscriptions provide another source of user information in addition to access patterns. This paper addresses the content delivery problem when user-stated interest is available. Each request by a user is either based on a notification about the availability of content that matches the user's subscriptions, or general browsing that is not based on the publish/subscribe service. We propose two approaches to content delivery that exploit both proactive push-time placement and passive access-time replacement based on the subscription information, the access pattern of subscribers, and that of non-subscribers. In our simulation-based evaluation, the two approaches are compared to an access-based caching only algorithm and to three approaches that were proposed for pure notification-driven accesses in our earlier study [5]. The results demonstrate that incorporating subscription information judiciously can substantially reduce the response time, even when only a small portion of accesses is driven by notifications and the subscription information does not reflect subscribers' accesses perfectly. To our knowledge, this work is the first effort to investigate general content delivery and caching enhanced by using subscription information.
Microarray Data Mining

Based on the concept of simultaneously studying the expression of a large number of genes, a DNA microarray is a chip on which numerous probes are placed for hybridization with a tissue sample. Biological complexity encoded by a deluge of microarray data is being translated into all sorts of computational, statistical or mathematical problems bearing on biological issues ranging from genetic control to signal transduction to metabolism. Microarray data mining is aimed to identify biologically significant genes and find patterns that reveal molecular network dynamics for reconstruction of genetic regulatory networks and pertinent metabolic pathways.
Does high school homework increase academic achievement

ABSTRACTAlthough previous research has shown that homework improves students’ academic achievement, the majority of these studies use data on students’ homework time from retrospective questionnaires, which may be less accurate than time-diary data. We use data from the combined Child Development Supplement (CDS) and the Transition to Adulthood Survey (TA) of the Panel Study of Income Dynamics to explore the effects of time spent on homework while attending high school on two measures of academic achievement: high school grade point averages and college attendance by age 20. We find that homework time has positive effects on academic achievement for boys.
Health and Economic Growth

Abstract This chapter examines the relationship between health and economic growth. Across countries, income per capita is highly correlated with health, as measured by life expectancy or a number of other indicators. Within countries, there is also a correlation between people’s health and income. Finally, over time, the historical evolution of cross-country health differences has largely paralleled the evolution of income differences, with the exception that in the last half century the convergence of health has been much faster than the convergence of income. How are health and income related? Theoretically, there is good reason to believe that causality runs in both directions. Healthier individuals are more productive, learn more in school, and, because they live longer, face enhanced incentives to accumulate human capital. Similarly, higher income for individuals or countries improves health in a variety of ways, ranging from better nutrition to construction of public health infrastructure. Empirically, there is evidence for both of these causal channels being operative, but the magnitude of the effects is limited, at least as they apply to cross-sectional differences among countries or individuals. Apparently, other factors that simultaneously raise income and improve health outcomes, such as institutional quality (for countries) and human capital (for individuals), are responsible for a good deal of the observed health–income correlation. The final section of the chapter discusses measures of aggregate welfare that combine consumption and life expectancy.
Four-Body Trajectory Optimization

The two methods which are suitable for use in a 4-body trajectory optimization program are both multiconic methods. They include an approach due to Wilson (1970) and to Byrnes and Hooper (1970) and a procedure developed by Stumpff and Weiss (1968). The various steps in a trajectory optimization program are discussed, giving attention to variable step integration, the correction of errors by quadrature formulas, questions of two-impulse transfer, three-impulse transfer, and two examples which illustrate the implementation of the computational approaches.
A Provable-Security Analysis of Intel’s Secure Key RNG

We provide the first provable-security analysis of the Intel Secure Key hardware RNG (ISK-RNG), versions of which have appeared in Intel processors since late 2011. To model the ISK-RNG, we generalize the PRNG-with-inputs primitive, introduced by Dodis et al. at CCS’13 for their /dev/[u]random analysis. The concrete security bounds we uncover tell a mixed story. We find that ISK-RNG lacks backward-security altogether, and that the forward-security bound for the “truly random” bits fetched by the \(\mathtt {RDSEED}\) instruction is potentially worrisome. On the other hand, we are able to prove stronger forward-security bounds for the pseudorandom bits fetched by the \(\mathtt {RDRAND}\) instruction. En route to these results, our main technical efforts focus on the way in which ISK-RNG employs CBCMAC as an entropy extractor.
Microcomputer programming skills

One of the most overwhelming aspects of the microcomputer revolution has been the speed with which hardware costs have plummeted. The software versus hardware costs ratio which prompted much of the interest in software engineering in recent years has grown dramatically as the parallel development of the microprocessors pushed down the cost of computer systems and their proliferation fueled software demand. This is increasing the need for skilled programmers for microsystems, part of which will be met by programmers currently working on big systems. In this paper we will examine some of the differences in skills and techniques that one can expect to encounter in the transition from programmer to microprogrammer. (The terms microprogram, microprogrammer , and microprogramming are frequently used in reference to the firmware or microcode of large machines. We will be using such terms only with reference to microprocessors.)
Assessment of blurring and facial expression effects on facial image recognition

In this paper we present methods for assessing the quality of facial images, degraded by blurring and facial expressions, for recognition. To assess the blurring effect, we measure the level of blurriness in the facial images by statistical analysis in the Fourier domain. Based on this analysis, a function is proposed to predict the performance of face recognition on blurred images. To assess facial images with expressions, we use Gaussian Mixture Models (GMMs) to represent images that can be recognized with the Eigenface method, we refer to these images as “Good Quality”, and images that cannot be recognized, we refer to these images as “Poor Quality”. During testing, we classify a given image into one of the two classes. We use the FERET and Cohn-Kanade facial image databases to evaluate our algorithms for image quality assessment. The experimental results demonstrate that the prediction function for assessing the quality of blurred facial images is successful. In addition, our experiments show that our approach for assessing facial images with expressions is successful in predicting whether an image has a good quality or poor quality for recognition. Although the experiments in this paper are based on the Eigenface technique, the assessment methods can be extended to other face recognition algorithms.
Analysis of interval-based global state detection

The problem of global state observation is fundamental to distributed systems. All interactions in distributed systems can be analyzed in terms of the building block formed by the pairwise interactions of intervals between two processes. Considering causality-based pairwise interactions by which two intervals at different processes may interact with each other, there are 40 possible orthogonal interactions. This paper examines the problem: “If a global state of interest to an application is specified in terms of the pairwise interaction types between each pair of processes, how can such a global state be detected?” A solution identifies a global state in which the relation specified for each process pair is satisfied. This paper formulates the specific conditions on the exact communication structures to determine which of the intervals being examined at any time may never satisfy the stipulated relation for that pair of processes, and therefore that interval must be deleted.
PAC Analogues of Perceptron and Winnow Via Boosting the Margin

We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit sample complexity bounds remarkably similar to those of known online algorithms such as Perceptron and Winnow, thus suggesting that these well-studied online algorithms in some sense correspond to instances of boosting. We show that the new algorithms can be viewed as natural PAC analogues of the online p-norm algorithms which have recently been studied by Grove, Littlestone, and Schuurmans (1997, Proceedings of the Tenth Annual Conference on Computational Learning Theory (pp. 171–183) and Gentile and Littlestone (1999, Proceedings of the Twelfth Annual Conference on Computational Learning Theory (pp. 1–11). As special cases of the algorithm, by taking p e 2 and p e ∞ we obtain natural boosting-based PAC analogues of Perceptron and Winnow respectively. The p e ∞ case of our algorithm can also be viewed as a generalization (with an improved sample complexity bound) of Jackson and Craven's PAC-model boosting-based algorithm for learning “sparse perceptrons” (Jackson & Craven, 1996, Advances in neural information processing systems 8, MIT Press). The analysis of the generalization error of the new algorithms relies on techniques from the theory of large margin classification.
An Improved Private Mechanism for Small Databases

We study the problem of answering a workload of linear queries \(\mathcal {Q}\), on a database of size at most \(n = o(|\mathcal {Q}|)\) drawn from a universe \(\mathcal {U}\) under the constraint of (approximate) differential privacy. Nikolov, Talwar, and Zhang [NTZ13] proposed an efficient mechanism that, for any given \(\mathcal {Q}\) and \(n\), answers the queries with average error that is at most a factor polynomial in \(\log |\mathcal {Q}|\) and \(\log |\mathcal {U}|\) worse than the best possible. Here we improve on this guarantee and give a mechanism whose competitiveness ratio is at most polynomial in \(\log n\) and \(\log |\mathcal {U}|\), and has no dependence on \(|\mathcal {Q}|\). Our mechanism is based on the projection mechanism of [NTZ13], but in place of an ad-hoc noise distribution, we use a distribution which is in a sense optimal for the projection mechanism, and analyze it using convex duality and the restricted invertibility principle.
Trade Liberalization and the Skill Premium: A Local Labor Markets Approach †

Trade economists have long studied the effects of globalization on wage differences between workers with different levels of skill or education. 1 This literature has generally sought to link globalization to changes in the economy-wide skill premium. Attanasio, Goldberg, and Pavcnik (2004) and Gonzaga, Menezes Filho, and Terra (2006) are salient examples that investigate whether changes in sector-specific prices or tariffs, changes in skill composition within and across sectors, and movements in the skill premium are consistent with the predictions of workhorse trade models, such as the HeckscherOhlin model. However, there is little evidence directly establishing a causal effect of globalization on the skill premium. 2 More recently, a growing body of research has focused on trade’s differential effects across local markets within a country. 3 In this paper, we combine these two strands of literature by developing a theoretically consistent approach to studying the causal
Behavioral Modeling for Churn Prediction: Early Indicators and Accurate Predictors of Custom Defection and Loyalty

Churn prediction, or the task of identifying customers who are likely to discontinue use of a service, is an important and lucrative concern of firms in many different industries. As these firms collect an increasing amount of large-scale, heterogeneous data on the characteristics and behaviors of customers, new methods become possible for predicting churn. In this paper, we present a unified analytic framework for detecting the early warning signs of churn, and assigning a "Churn Score" to each customer that indicates the likelihood that the particular individual will churn within a predefined amount of time. This framework employs a brute force approach to feature engineering, then winnows the set of relevant attributes via feature selection, before feeding the final feature-set into a suite of supervised learning algorithms. Using several terabytes of data from a large mobile phone network, our method identifies several intuitive - and a few surprising - early warning signs of churn, and our best model predicts whether a subscriber will churn with 89.4% accuracy.
Patience-Aware Scheduling for Cloud Services: Freeing Users from the Chains of Boredom

Scheduling of service requests in Cloud computing has traditionally focused on the reduction of pre-service wait, generally termed as waiting time. Under certain conditions such as peak load, however, it is not always possible to give reasonable response times to all users. This work explores the fact that different users may have their own levels of tolerance or patience with response delays. We introduce scheduling strategies that produce better assignment plans by prioritising requests from users who expect to receive results earlier and by postponing servicing jobs from those who are more tolerant to response delays. Our analytical results show that the behaviour of users' patience plays a key role in the evaluation of scheduling techniques, and our computational evaluation demonstrates that, under peak load, the new algorithms typically provide better user experience than the traditional FIFO strategy.
The Global Demography of Aging: Facts, Explanations, Future

Abstract Population aging is the 21st century's dominant demographic phenomenon. Declining fertility, increasing longevity, and the progression of large-sized cohorts to the older ages are causing elder shares to rise throughout the world. The phenomenon of population aging, which is unprecedented in human history, brings with it sweeping changes in population needs and capacities, with potentially significant implications for employment, savings, consumption, economic growth, asset values, and fiscal balance. This chapter provides a broad overview of the global demography of aging. It reviews patterns, trends, and projections involving various indicators of population aging and their demographic antecedents and sequelae. The chapter also reviews theories economists use to explain the behavioral changes driving the most prominent demographic shifts. Finally, it discusses the changing nature of aging, the future of longevity, and associated policy implications, highlighting some key research issues that require further examination.
Policy iteration for relational MDPs

Relational Markov Decision Processes are a useful abstraction for complex reinforcement learning problems and stochastic planning problems. Recent work developed representation schemes and algorithms for planning in such problems using the value iteration algorithm. However, exact versions of more complex algorithms, including policy iteration, have not been developed or analyzed. The paper investigates this potential and makes several contributions. First we observe two anomalies for relational representations showing that the value of some policies is not well defined or cannot be calculated for restricted representation schemes used in the literature. On the other hand, we develop a variant of policy iteration that can get around these anomalies. The algorithm includes an aspect of policy improvement in the process of policy evaluation and thus differs from the original algorithm. We show that despite this difference the algorithm converges to the optimal policy.
Anthocyanin-rich Black Elderberry Extract Improves Markers of HDL Function and Reduces Aortic Cholesterol in Hyperlipidemic Mice

Serum high-density lipoprotein-cholesterol (HDL-C) is a risk factor considered to be protective of atherosclerosis. However, atherosclerosis is an inflammatory disease and contributes to impairment in high-density lipoprotein (HDL) function, including reductions in HDL-C, HDL antioxidant and anti-inflammatory activities. Anthocyanins are polyphenols that have demonstrated antioxidant and anti-inflammatory properties. The objective of this study was to determine whether an anthocyanin-rich black elderberry extract (Sambucus nigra) (BEE) (13% anthocyanins) would protect against inflammation-related impairments in HDL function and atherosclerosis in apoE(-/-) mice, a mouse model of hyperlipidemia and HDL dysfunction. We fed an AIN-93M diet supplemented with 1.25% (w/w) BEE or control diet to 10 week old male apoE(-/-) mice for 6 weeks. The BEE fed to mice was rich in cyanidin 3-sambubioside (∼ 9.8% w/w) and cyanidin 3-glucoside (∼ 3.8% w/w). After 6 weeks, serum lipids did not differ significantly between groups, while aspartate transaminase (AST) and fasting glucose were reduced in BEE-fed mice. Hepatic and intestinal mRNA changes with BEE-feeding were consistent with an improvement in HDL function (Apoa1, Pon1, Saa1, Lcat, Clu) and a reduction in hepatic cholesterol levels (increased Ldlr and Hmgcr, reduced Cyp7a1). In BEE-fed mice, serum paraoxonase-1 (PON1) arylesterase activity was significantly higher. In addition, mice fed BEE had significantly lower serum chemokine (C-C motif) ligand 2 (CCL2) compared to control-fed mice. Notably, we observed significant reductions in total cholesterol content of the aorta of BEE-fed mice, indicating less atherosclerosis progression. This study suggests that black elderberry may have the potential to influence HDL dysfunction associated with chronic inflammation by impacting hepatic gene expression.
Terawatt lasers: probing unique material properties with novel diagnostic source

Short pulse and high intensity lasers can produce bright ultrashort-pulse-duration X-rays, electrons and ions. They also make highly nonequilibrium plasmas that can be used to deposit thin films with unique material properties. We present new experimental results on all of these topics. We first report results on the characterization, control, and applications of ultrashort X-rays emitted from laser plasmas. It is demonstrated experimentally that the pulse duration may be controlled by adjusting the incident ultrashort-pulse laser flux.
Do trace cache, value prediction and prefetching improve SMT throughput?

While trace cache, value prediction, and prefetching have been shown to be effective in the single-threaded superscalar, there has been no analysis of these techniques in a Simultaneously Multi threaded (SMT) processor. SMT brings new factors both for and against these techniques, and it is not known how these techniques would fare in SMT. We evaluate these techniques in an SMT to pro vide recommendations for future SMT designs. Our key contribu tions are: (1) we identify a fundamental interaction between the techniques and SMT's sharing of resources among multiple threads, and (2) we quantify the impact of this interaction on SMT through put. SMT's sharing of the instruction storage (i.e., trace cache or i-cache), physical registers, and issue queue impacts the effectiveness of trace cache, value prediction, and prefetching, respectively.
Cell geometry designs for efficient plasma display panels

Summary form only given, as follows. We use a two-dimensional self-consistent simulation model to study the effect of the geometric parameters on the operating voltages and the efficiency of a coplanar-electrode plasma display panel cell. For the standard coplanar-electrode geometry it is found that there is a trade-off between high efficiency and low operating voltages as the electrode gap, or other parameters of the upper dielectric are varied, while variation of the sustain electrode width has no significant effect on either the operating voltages or efficiency. We also investigate the performance of several non-standard cell geometry designs involving two-dimensional variations of the coplanar-electrode PDP cell. A PDP cell with modified shape of sustain electrodes is found to have /spl sim/20% larger luminous efficiency without substantial increase of the operating voltages. Similar performance improvement is achieved by designs with different shapes of the upper dielectric, or by those involving two different dielectric layers. The dependence of PDP performance on the design parameters of these structures is also investigated.
Expected utility networks

We introduce a new class of graphical representations, expected utility networks (EUNs), and discuss some of its properties and potential applications to artificial intelligence and economic theory. In EUNs not only probabilities, but also utilities enjoy a modular representation. EUNs are undirected graphs with two types of arc, representing probability and utility dependencies respectively. The representation of utilities is based on a novel notion of conditional utility independence, which we introduce and discuss in the context of other existing proposals. Just as probabilistic inference involves the computation of conditional probabilities, strategic inference involves the computation of conditional expected utilities for alternative plans of action. We define a new notion of conditional expected utility (EU) independence, and show that in EUNs node separation with respect to the probability and utility subgraphs implies conditional EU independence.
Exact Solution of Some Linear Matrix Equations Using Algebraic Methods

A study is done of solution methods for Linear Matrix Equations including Lyapunov's equation, using methods of modern algebra. The emphasis is on the use of finite algebraic procedures which are easily implemented on a digital computer and which lead to an explicit solution to the problem. The action f sub BA is introduced a Basic Lemma is proven. The equation PA + BP = -C as well as the Lyapunov equation are analyzed. Algorithms are given for the solution of the Lyapunov and comment is given on its arithmetic complexity. The equation P - A'PA = Q is studied and numerical examples are given.
On Two Pseudo-Paradoxes in Bayesian Analysis

This note discusses two problems that might be considered weaknesses of Bayesian analysis. The rst was noted in a recent paper of Cozman (2000), and concerns the notion of \relevance" when complete probabilistic model is not available. The second, stimulated by an example due to Philippe Smets, concerns the interpretation of evidential reports that are cast as betting odds. I will describe the two problems, o er their resolution, and then argue that Bayesian analysis should retain its status as a powerful model of human reasoning.
Random multipliers numerically stabilize Gaussian and block Gaussian elimination: Proofs and an extension to low-rank approximation ☆

Abstract We study two applications of standard Gaussian random multipliers. At first we prove that with a probability close to 1 such a multiplier is expected to numerically stabilize Gaussian elimination with no pivoting as well as block Gaussian elimination. Then, by extending our analysis, we prove that such a multiplier is also expected to support low-rank approximation of a matrix without customary oversampling. Our test results are in good accordance with this formal study. The results remain similar when we replace Gaussian multipliers with random circulant or Toeplitz multipliers, which involve fewer random parameters and enable faster multiplication. We formally support the observed efficiency of random structured multipliers applied to approximation, but we still continue our research in the case of elimination. We specify a narrow class of unitary inputs for which Gaussian elimination with no pivoting is numerically unstable and then prove that, with a probability close to 1, a Gaussian random circulant multiplier does not fix numerical stability problems for such inputs. We also prove that the power of the random circulant preprocessing increases if we also include random permutations.
Proceedings of the 3rd ACM workshop on Security of ad hoc and sensor networks

It is our great pleasure to welcome you to the 3rd ACM Workshop on Security of Ad Hoc and Sensor Networks (SASN'05), held in conjunction with the 12th ACM Conference on Computer and Communications Security (CCS'05), November 7, 2005, in Alexandria, Virginia.This year we received a total of 39 submissions on various aspects of ad-hoc and sensor network security. The program committee selected 6 as regular papers that cover a variety of topics, including trust establishment in Mobile Ad-Hoc Networks (MANETs), security of vehicular ad-hoc networks, secure group communication, key pre-distribution for sensor networks, jamming attacks against sensor network MAC protocols, and defense against Denial-of-Service (DoS) attacks. This year we continue the tradition of SASN'03 and SASN'04 to encourage the presentation and discussion of work-in-progress on ad-hoc and sensor network security. Among the 39 submissions, the program committee selected 7 papers to present in work-in-progress sessions, covering topics on anonymous routing for MANETs, key distribution for inter-group multicast in ad-hoc networks, improved topology assumptions for threshold cryptography in MANETs, RFID security, tracing in mobile wireless sensor networks, time synchronization attacks in sensor networks, and coordinated deployment for improving secure communications and sensing coverage in wireless sensor networks. In addition, the program includes a panel on Advances in Sensor and Ad-hoc Network Security and an invited keynote talk by Radha Poovandran (University of Washington) on Information Assurance in MANETs and Wireless Sensor Networks. We hope that these proceedings will serve as a valuable reference for security researchers and developers.
Technology Adoption in Poorly Specified Environments

This article extends the characteristics-based choice framework of technology adoption to account for decisions taken by boundedly-rational individuals in environments where traits are not fully observed. It is applied to an agricultural setting and introduces the concept of ambiguity in the agricultural technology adoption literature by relaxing strict informational and cognition related assumptions that are implied by traditional Bayesian analysis. The main results confirm that ambiguity increases as local conditions become less homogeneous and as computational ability, own experience and nearby adoption rates decrease. Measurement biases associated with full rationality assumptions are found to increase when decision makers have low computational ability, low experience and when their farming conditions differ widely from average adopter ones. A complementary empirical paper (Useche 2006) finds that models assuming low confidence in observed data, ambiguity and pessimistic expectations about traits predict sample shares better than models which assume that farmers do not face ambiguity or are optimistic about the traits of new varieties.
Board Independence, Ownership Structure and Performance: Evidence from Real Estate Investment Trusts

For Real Estate Investment Trusts (REITs), mandatory distribution of income limits free cash flow. But, restrictions on source of income and asset structure result in widely dispersed stock ownership, which makes external monitoring through the takeover market less likely. As such, alternative monitoring mechanisms, including external directors, must be in place to discourage deviant managerial behavior. Using a simultaneous equation system, we conclude that while independent directors enhance REIT performance, the effect is weak. Higher CEO stock ownership and control through tenure and chairmanship of the board reduce the representation by outside directors, and adversely affect REIT performance. Institutional ownership or blockownership fails to serve as alternate disciplining mechanism to (inadequate) monitoring by outside board members, although their presence seems to enhance performance.
New Lithium-Containing Pnictides with 1-D Infinite Chains of Supertetrahedral Clusters: Synthesis, Crystal and Electronic Structure of Ba4Li2Cd3Pn6 (Pn = P, As and Sb)

The novel complex pnictides Ba4Li2Cd3Pn6 (Pn = P, As and Sb) have been synthesized by direct combination of the respective elements at high temperature, and structurally characterized by single-crystal X-ray diffraction. The three isostructural compounds crystallize with their own structure type in the centrosymmetric orthorhombic space group Cmcm (Pearson code oC60). The crystal structure is based on one-dimensional infinite chains of supertetrahedral clusters, [Cd4Pn10], running parallel the a-axis. These chains are connected through Pn2-type dumbbells. Tight-binding electronic structure calculations show that the electronic stability of these compounds requires strong covalent Pn–Pn and Cd–Pn bonds. The interactions within the polyanionic sub-structure are complimented by weaker Ba–Pn and Li–Pn bonds, which also show a substantial degree of covalency, and the strength of all interactions correlates very well with the corresponding interatomic distances. The precise satisfaction of the valence rules and the Zintl–Klemm concept is not essential though as structural vacancies on Cd and Li sites bring about an interplay between ionicity and covalency among the electronegative components. Electronic structure calculations show that Ba4Li2Cd3P6 is expected to be a semiconductor with a band gap of ca. 0.5 eV, while the gap decreases and vanishes altogether for the As- and Sb-analogs, respectively. Solid solutions between arsenides and antimonides appear possible, which could be an effective way to fine-tune transport properties. Since the latter two compounds can be considered as moderately-to-heavily doped intrinsic semiconductors, these materials might be suitable candidates for thermoelectric applications.
Conformal Fitness and Uniformization of Holomorphically Moving Disks

Let $\{U_t \}_{t \in {\mathbb D}}$ be a family of topological disks on the Riemann sphere containing the origin 0 whose boundaries undergo a holomorphic motion over the unit disk $\mathbb D$. We study the question of when there exists a family of Riemann maps $g_t:({\mathbb D},0) \to (U_t,0)$ which depends holomorphically on the parameter $t$. We give five equivalent conditions which provide analytic, dynamical and measure-theoretic characterizations for the existence of the family $\{g_t \}_{t \in {\mathbb D}}$, and explore the consequences.
Comparative statics of monopoly pricing

Summary. When consumers' willingness-to-pay increases by a uniform amount, the change in the resulting monopoly price is generally indeterminate. Our analy sis identifies sufficient conditions on the underlying demand curve which predict both the sign and the magnitude of the resulting price change.
Hiding satisfying assignments: two are better than one

The evaluation of incomplete satisfiability solvers depends critically on the availability of hard satisfiable instances. A plausible source of such instances consists of random k- SAT formulas whose clauses are chosen uniformly from among all clauses satisfying some randomly chosen truth assignment A. Unfortunately, instances generated in this manner tend to be relatively easy and can be solved efficiently by practical heuristics. Roughly speaking, for a number of different algorithms, A acts as a stronger and stronger attractor as the formula's density increases. Motivated by recent results on the geometry of the space of satisfying truth assignments of random k-SAT and NAE-k-SAT formulas, we introduce a simple twist on this basic model, which appears to dramatically increase its hardness. Namely, in addition to forbidding the clauses violated by the hidden assignment A, we also forbid the clauses violated by its complement, so that both A and A are satisfying. It appears that under this "symmetrization" the effects of the two attractors largely cancel out, making it much harder for algorithms to find any truth assignment. We give theoretical and experimental evidence supporting this assertion.
Geometric implications of the naive Bayes assumption

A Naive (or Idiot) Bayes network is a network with a single hypothesis node and several observations that are conditionally independent given the hypothesis. We recently surveyed a number of members of the UAI community and discovered a general lack of understanding of the implications of the Naive Bayes assumption on the kinds of problems that can be solved by these networks. It has long been recognized [Minsky 61] that if observations are binary, the decision surfaces in these networks are hyperptanes. We extend this result (hyperplane separability) to Naive Bayes networks with m-ary observations. In addition, we illustrate the effect of observation-observation dependencies on decision surfaces. Finally, we discuss the implications of these results on knowledge acquisition and research in learning.
An improved upper bound on covering radius

A simple upper bound on covering radius yields new information on various codes. It leads us to show that the nonlinear codes of Sloane and Whitehead [18] are quasi-perfect. We get some new bounds for the Berlekamp-Gale switching problem [7]. It gives the exact covering radius for some codes of length up to 31 and is within 1 or 2 of the exact value for the even quadratic-residue codes of lengths 41 and 47.
Collision-free communication in sensor networks

In this paper, we provide a stabilizing solution for collision-free diffusion in sensor networks. Such diffusions are often necessary in sensor networks when information from one sensor needs to be communicated to other sensors that satisfy certain geographic properties. Our solution deals with several difficulties, e.g., unidirectional links, unreliable links, long links, failed sensors, and sensors that are sleeping in order to save energy, that occur in sensor networks. It also ensures that there are no collisions during the diffusion and that the time required for the diffusion is O(D) where D is the diameter of the network. Moreover, while the solution can be applied to an arbitrary topology, it is more suitable for a commonly occurring topology, a two-dimensional grid. We show how our solution for collision-free diffusion can be used for time-division multiplexing (TDM) in sensor networks. TDM ensures that the message communication (other than the messages sent by diffusion) among sensors is also collision-free. While collision-free diffusion and time-division multiplexing are interdependent, we show how both these properties can be achieved simultaneously. Our algorithms are stabilizing fault-tolerant, i.e., collision-free diffusion and time-division multiplexing are restored even if the system reaches an arbitrary state where the sensors are corrupted or improperly initialized.
An analytical solution for slug tracer tests in fractured reservoirs

The transport of chemicals or heat in fractured reservoirs is strongly affected by the fracture-matrix interfacial area. In a vapor-dominated geothermal reservoir, this area can be estimated by inert gas tracer tests, where gas diffusion between the fracture and matrix causes the tracer breakthrough curve (BTC) to have a long tail determined by the interfacial area. For water-saturated conditions, recent studies suggest that sorbing solute tracers can also generate strong tails in BTCs that may allow a determination of the fracture-matrix interfacial area. To theoretically explore such a useful phenomenon, this paper develops an analytical solution for BTCs in slug-tracer tests in a water-saturated fractured reservoir. The solution shows that increased sorption should have the same effect on BTCs as an increase of the diffusion coefficient. The solution is useful for understanding transport mechanisms, verifying numerical codes, and for identifying appropriate chemicals as tracers for the characterization of fractured reservoirs.
Vision-based control of robot motion

Visual servo control is now a mature method for controlling robots using real-time vision feedback. It can be considered as the fusion of computer vision, robotics and control, and it has been a distinct field since the 1990's, though the earliest work dates back to the 1980's. Over this period several major, and well understood, approaches have evolved and have been demonstrated in many laboratories around the world. Many visual servo schemes can be classified as either position-based or image-based, depending on whether camera pose or image features are used in the control law. This lecture will review both position-based and image-based methods for visual servo control, presenting the basic derivations and concepts, and describing a few of the performance problems faced by each. Following this, a few recent and more advanced methods will be described. These approaches essentially partition the control system either along spatial or temporal dimensions. The former are commonly referred to as hybrid or partitioned control systems, while the latter are typically referred to as switched systems.
CO (2-1) Observations of Maffei 2

Maffei 2 is a highly obscured galaxy, probably of type Sbc, at a distance of 5 Mpc (Allen and Raimond 1972; Spinrad et al. 1973). Since it lies close to the Galactic plane, there is considerable confusion in infrared and 21-cm HI observations due to Galactic emission, but investigations of its structure can be carried out at millimeter wavelengths where the Galaxy contribution is confined to a limited velocity range. The high resolution (30″) of our CO J=2−l observations permits both a detailed examination of Maffei 2 and a study of the nature of the gas in its nucleus, through comparison with the CO J=l−0 observations.
Charged Particle Distribution in the Nearest Vicinity of Ionospheric Satellites-Comparison of the Main Results from the Ariel I, Explorer 31 and Gemini-Agena 10 Spacecraft

Electron and ion measurements performed by probes mounted on the Ariel I, the Explorer 31 and the Gemini-Agena 10 spacecraft which reflect on some aspects of the interaction between a spacecraft and its ionospheric plasma are compared. A partial picture of charged particle distributions around surfaces in space is thereby obtained. Results from the above satellites are compared among themselves and the degree of agreement/disagreement is demonstrated. Comparisons of results with some wake models are included, and the degree of agreement is discussed.
Modeling the radiation belt electrons with radial diffusion driven by the solar wind

[1] On the basis of the correlation between the solar wind and radiation belt electron fluxes, we develop a model to simulate the MeV electron phase space density variations from L = 3 to L = 8 by extending the Li et al. (2001) radial diffusion model for geosynchronous electrons. We add L dependence to the Li et al. model and allow for comparison with measurements at more than one L shell while retaining a similar form of their diffusion coefficient. The extended model achieves a prediction efficiency (PE) of 0.61 at L = 4 and 0.52 at L = 6 when the phase space density is converted to differential flux and compared with orbit-averaged Polar 2 MeV measurements at L = 4 and daily averaged LANL 0.7–1.8 MeV geosynchronous measurements for the year 1998. These results indicate that radial diffusion plays a strong role in the enhancement of radiation belt electrons yet leaves a significant portion of the variance unaccounted for. We have also tuned parameters to model the electron fluxes during four individual geomagnetic storms during 1998 and found that the parameter values must differ from those of the long term and from each other to achieve the best PE. This suggests that the different solar wind drivers have varying degrees of influence on the MeV electron variations during different magnetic storms. This model can be used to forecast the MeV electron variations inside geosynchronous orbit with a reasonably good PE on the basis of real-time solar wind measurements only.
The dimensions of individual strings and sequences

A constructive version of Hausdorff dimension is developed using constructive supergales, which are betting strategies that generalize the constructive supermartingales used in the theory of individual random sequences. This constructive dimension is used to assign every individual (infinite, binary) sequence S a dimension, which is a real number dim(S) in the interval [0, 1]. Sequences that are random (in the sense of Martin-Lof) have dimension 1, while sequences that are decidable, Σ10, or Π10, have dimension 0. It is shown that for every Δ20-computable real number α in [0, 1] there is a Δ20 sequence S such that dim(S) = α. A discrete version of constructive dimension is also developed using termgales, which are supergale-like functions that bet on the terminations of (finite, binary) strings as well as on their successive bits. This discrete dimension is used to assign each individual string w a dimension, which is a nonnegative real number dim(w). The dimension of a sequence is shown to be the limit inferior of the dimensions of its prefixes. The Kolmogorov complexity of a string is proven to be the product of its length and its dimension. This gives a new characterization of algorithmic information and a new proof of Mayordomo's recent theorem stating that the dimension of a sequence is the limit inferior of the average Kolmogorov complexity of its first n bits. Every sequence that is random relative to any computable sequence of coin-toss biases that converge to a real number β in (0, 1) is shown to have dimension H(β), the binary entropy of β.
Mitigation of Cretinism by Breast-Feeding

An athyrotic infant had hypothyroidism at 1 year of age. He had grown at an above-average velocity until age 10 months when breast-feeding was discontinued, yet his bone age remained that of a newborn. These observations suggested that breast-feeding had attenuated hypothyroidism by providing significant quantities of thyroid hormones in the milk. To test this hypothesis, thyroxine (T4), 3,5,39- triiodothyronine (T3, and 3,39,59-triiodothyronine (reverse T3) were measured in breast milk samples collected serially from three months before to four months after delivery. Mean breast milk T4 content fell from 1.4 to 0.7 µg/dl within 48 hours after delivery, while T3 content rose from 136 to 286 ng/dl. Reverse T3 content remained unchanged. The shift in the T4/T3 ratio after delivery was observed in samples of all five donors; the highest postpartum T4 level was 1.1µg/dl and the highest postpartum T3 level was 405 ng/dl. It is concluded that breast-feeding may deliver sufficient thyroid hormones to the athyrotic infant to mitigate severe hypothyroidism and to prevent impaired neurological development.
Monte carlo calculations of nuclei

Nuclear many-body calculations have the complication of strong spin-and isospin-dependent potentials. In these lectures I discuss the variational and Green’s function Monte Carlo techniques that have been developed to address this complication, and present a few results.
Untangling the braid: finding outliers in a set of streams

Monitoring the performance of large shared computing systems such as the cloud computing infrastructure raises many challenging algorithmic problems. One common problem is to track users with the largest deviation from the norm (outliers), for some measure of performance. Taking a streamcomputing perspective, we can think of each user's performance profile as a stream of numbers (such as response times), and the aggregate performance profile of the shared infrastructure as a "braid" of these intermixed streams. The monitoring system's goal then is to untangle this braid sufficiently to track the top k outliers. This paper investigates the space complexity of one-pass algorithms for approximating outliers of this kind, proves lower bounds using multi-party communication complexity, and proposes small-memory heuristic algorithms. On one hand, stream outliers are easily tracked for simple measures, such as max or min, but our theoretical results rule out even good approximations for most of the natural measures such as average, median, or the quantiles. On the other hand, we show through simulation that our proposed heuristics perform quite well for a variety of synthetic data.
The mechanisms of information technology's contribution to economic growth

The first book in this important new series, under the general editorship of Nobel Laureate Robert Solow, Institutions, Innovation and Growth assembles a stellar cast of international contributors. Leading economists join the debate on innovation and economic growth, focussing on a broad spectrum of issues ranging from labour markets to corporate governance. Growth paths within the OECD are also assessed, with particular emphasis on contrasts between US and European models. The book seeks to identify those institutional factors, taking into account different national trajectories, which might serve to promote economic growth in Europe.
The Fueling and Evolution of AGN: Internal and External Triggers

In this chapter, I review the fueling and evolution of active galactic nuclei (AGN) under the influence of internal and external triggers, namely intrinsic properties of host galaxies (morphological or Hubble type, color, presence of bars and other non-axisymmetric features, etc) and external factors such as environment and interactions. The most daunting challenge in fueling AGN is arguably the angular momentum problem as even matter located at a radius of a few hundred pc must lose more than 99.99 % of its specific angular momentum before it is fit for consumption by a BH. I review mass accretion rates, angular momentum requirements, the effectiveness of different fueling mechanisms, and the growth and mass density of black BHs at different epochs. I discuss connections between the nuclear and larger-scale properties of AGN, both locally and at intermediate redshifts, outlining some recent results from the GEMS and GOODS HST surveys.
THE LOSS AVERSION / NARROW FRAMING APPROACH TO THE EQUITY PREMIUM PUZZLE

Abstract We review a recent approach to understanding the equity premium puzzle. The key elements of this approach are loss aversion and narrow framing, two well-known features of decision-making under risk in experimental settings. In equilibrium, models that incorporate these ideas can generate a large equity premium and a low and stable risk-free rate, even when consumption growth is smooth and only weakly correlated with the stock market. Moreover, they can do so for parameter values that correspond to sensible attitudes to independent monetary gambles. We conclude by suggesting some possible directions for future research.