cssi/SciSciGPT-SciSciNet huggingface dataset:
Self-Serving Attribution Bias, Overconfidence, and the Issuance of Management Forecasts: overconfidence and forecast issuance

Prior studies document that managers consider a variety of costs and benefits when deciding whether to issue earnings forecasts. Using an abstract experiment and a survey of experienced financial managers, we provide evidence that managerial overconfidence may also contribute to this decision. Our experiment shows that participants engage in self-serving attribution, giving greater weight to internal than external factors as explanations for good performance. This increases confidence in improved future performance, which increases their willingness to issue forecasts. Two facets of the stable individual trait overconfidence, dispositional optimism and miscalibration, also contribute to confidence in improved future performance and willingness to issue forecasts. Consistent with these results, experienced financial manager survey participants believe other managers are likely to overestimate the extent to which they contribute to positive firm performance, and both overoptimism about firm performance and overconfidence in their ability to predict future firm performance contribute to issuance of earnings forecasts.
New definitions and separations for circular security

Traditional definitions of encryption security guarantee secrecy for any plaintext that can be computed by an outside adversary. In some settings, such as anonymous credential or disk encryption systems, this is not enough, because these applications encrypt messages that depend on the secret key. A natural question to ask is do standard definitions capture these scenarios? One area of interest is n-circular security where the ciphertexts $E(pk_1,sk_2),\allowbreak E(pk_2,sk_3)$, …$,\allowbreak E(pk_{n-1},sk_n), E(pk_n, sk_1)$ must be indistinguishable from encryptions of zero. Acar et al. (Eurocrypt 2010) provided a CPA-secure public key cryptosystem that is not 2-circular secure due to a distinguishing attack. In this work, we consider a natural relaxation of this definition. Informally, a cryptosystem is n-weak circular secure if an adversary given the cycle $E(pk_1,sk_2),\allowbreak E(pk_2,sk_3), \dots,\allowbreak E(pk_{n-1},sk_n), E(pk_n, sk_1)$ has no significant advantage in the regular security game, (e.g., CPA or CCA) where ciphertexts of chosen messages must be distinguished from ciphertexts of zero. Since this definition is sufficient for some practical applications and the Acar et al. counterexample no longer applies, the hope is that it would be easier to realize, or perhaps even implied by standard definitions. We show that this is unfortunately not the case: even this weaker notion is not implied by standard definitions. Specifically, we show:For symmetric encryption, under the minimal assumption that one-way functions exist, n -weak circular (CPA) security is not implied by CCA security, for any n . In fact, it is not even implied by authenticated encryption security, where ciphertext integrity is guaranteed. For public-key encryption, under a number-theoretic assumption, 2-weak circular security is not implied by CCA security. In both of these results, which also apply to the stronger circular security definition, we actually show for the first time an attack in which the adversary can recover the secret key of an otherwise-secure encryption scheme after an encrypted key cycle is published. These negative results are an important step in answering deep questions about which attacks are prevented by commonly-used definitions and systems of encryption. They say to practitioners: if key cycles may arise in your system, then even if you use CCA-secure encryption, your system may break catastrophically; that is, a passive adversary might be able to recover your secret keys.
Hormones and memory.

Abstract This article examines the roles of hormones in regulating two aspects of memory. The first aspect is hormonal control of memory formation, with evidence that hormonal responses to an experience up-regulate the brain processes responsible for storing new information. The second aspect is hormonal control of the strategies used to solve a problem, with a basis in differential activation of neural systems responsible for storing different attributes of memory. These issues are illustrated using epinephrine, corticosterone, and estrogens as the principle examples of hormonal effects on memory. Included in the article are descriptions of several mechanisms by which the hormones act on memory.
The Economic Consequences of Sharing Security Information

Information technology (IT) security has emerged as an important issue in the last decade. To promote the disclosure and sharing of cyber-security information amongst firms, the US federal government has encouraged the establishment of many industry based Information Sharing & Analysis Centers(ISACs) under Presidential Decision Directive-63. We develop an analytical framework to investigate the competitive implications of sharing information about security breaches and investments in technologies which promote security. Using a game-theoretic model, we point out how firm and industry characteristics affect the incentives for information sharing amongst competing firms and their impact on firms’ profits. We find that security technologies and information sharing act as “strategic complements in equilibrium”. Our paper points out that by joining such alliances, firms can benefit from a “direct effect” which increases demand and a “strategic effect ” which alleviates price competition. Our results suggest that information sharing is more valuable when product substitutability is higher, suggesting that information is of greater value in more competitive industries. We also highlight that sharing security information is more valuable for larger firms and in larger industries. Finally we show that “demand-side spillover” effects boosts sharing levels and lead to higher prices. Conversely, “cost-based spillovers” might lead to lower sharing and lower technology investments.
An alternative approach for image-plane control of robots

The article distinguishes between camera-space manipulation and visual servoing; it identifies application categories which particularly favor the former. Using a 2-dimensional, 2-degree-of-freedom example, a point of convergence between the two methods is identified. This is based upon an extension of visual servoing wherewith a Kalman Filter is used to estimate the ongoing visual-error signal from discrete-time, noisy, delayed and possibly intermittent visual input combined with continuous joint-rotation input. A working, nonholonomic, vision-based control system which applies a similar estimation strategy is introduced in order to illustrate and make plausible this extension, and to clarify the comparison. The comparison is discussed in terms of advantages/disadvantages accrued in the restoration of the two methods to their usual forms from their respective extensions or modifications as required to produce convergence.
Two-Orbit Convex Polytopes and Tilings

We classify the convex polytopes whose symmetry groups have two orbits on the flags. These exist only in two or three dimensions, and the only ones whose combinatorial automorphism group is also two-orbit are the cuboctahedron, the icosidodecahedron, and their duals. The combinatorially regular two-orbit convex polytopes are certain 2n-gons for each $$n \ge 2$$n?2. We also classify the face-to-face tilings of Euclidean space by convex polytopes whose symmetry groups have two flag orbits. There are finitely many families, tiling one, two, or three dimensions. The only such tilings which are also combinatorially two-orbit are the trihexagonal plane tiling, the rhombille plane tiling, the tetrahedral---octahedral honeycomb, and the rhombic dodecahedral honeycomb.
3-Carboxamido analogues of morphine and naltrexone: synthesis and opioid receptor binding properties

In response to the unexpectedly high affinity for opioid receptors observed in a novel series of cyclazocine analogues where the prototypic 8-OH was replaced by a carboxamido group, we have prepared the corresponding 3-CONH(2) analogues of morphine and naltrexone. High affinity (K(i)=34 and 1.7nM) for mu opioid receptors was seen, however, the new targets were 39- and 11-fold less potent than morphine and naltrexone, respectively.
On-Line Monitoring for Temporal Logic Robustness

In this paper, we provide a Dynamic Programming algorithm for on-line monitoring of the state robustness of Metric Temporal Logic specifications with past time operators. We compute the robustness of MTL with unbounded past and bounded future temporal operators (MTL\(^{<+\infty}_{+pt}\)) over sampled traces of Cyber-Physical Systems. We implemented our tool in Matlab as a Simulink block that can be used in any Simulink model. We experimentally demonstrate that the overhead of the MTL\(^{<+\infty}_{+pt}\) robustness monitoring is acceptable for certain classes of practical specifications.
Toxicity Testing, Reproductive

Abstract Reproductive toxicity evaluations encompass embryo/fetal development in utero, secondary and tertiary sex characteristics, sexual behavior and performance in both sexes, and pregnancy, parturition, lactation, and other maternal behaviors in females. Reproductive toxicants are categorized by type of agent and/or by function or mechanism. Governmental regulation of agents began in 1966 after the worldwide thalidomide disaster, with the U.S. Food and Drug Administration establishing guidelines for Reproductive Studies for Safety Evaluation of Drugs for Human Use. The U.S. Environmental Protection Agency promulgated endocrine disruptor screening assays and definitive tests to detect natural and man-made endocrine disruptors in mammals, amphibians, fish, and invertebrates.
Small-time asymptotics for Gaussian self-similar stochastic volatility models

We consider the class of Gaussian self-similar stochastic volatility models, and characterize the small-time (near-maturity) asymptotic behavior of the corresponding asset price density, the call and put pricing functions, and the implied volatility. Away from the money, we express the asymptotics explicitly using the volatility process’ self-similarity parameter H, and its Karhunen–Loeve characteristics. Several model-free estimators for H result. At the money, a separate study is required: the asymptotics for small time depend instead on the integrated variance’s moments of orders $$\frac{1}{2}$$ and $$ \frac{3}{2}$$ , and the estimator for H sees an affine adjustment, while remaining model-free.
A Tale of Two Countries: Sovereign Default, Exchange Rate, and Trade

This paper explores the impacts of sovereign defaults on trade and income through a real exchange rate channel, in a DSGE model of two risk-averse open economies, with production. In the model, once the borrower country defaults due to an adverse productivity shock, foreign firms reduce their imports of intermediate goods from the defaulting country, whose income consequently declines. This causes the defaulting country to adjust its consumption portfolio of domestic goods and imports according to its home bias preference, triggers a collapse in its real exchange rate, and leads to a further endogenous plummet in national income. This paper makes three main contributions. First, along business cycles, the model generates countercyclical trade balances, procyclical trade flows, and countercyclical bond spreads with a data-consistent average. Second, following a sovereign default, the model endogenously delivers sharp real exchange rate deterioration, output drops, trade balance improvements, and bilateral trade flow declines. This paper thus also studies a real exchange rate channel, through which default risks and occurrences, income, and trade interact with each other. Lastly, this model predicts lasting welfare gains for the creditor country through the real exchange rate channel, but relatively short-lived welfare losses for the borrower country and the world during and after a sovereign default.
Predicting fracture energies and crack-tip fields of soft tough materials

Abstract Soft materials including elastomers and gels are pervasive in biological systems and technological applications. Whereas it is known that intrinsic fracture energies of soft materials are relatively low, how the intrinsic fracture energy cooperates with mechanical dissipation in process zone to give high fracture toughness of soft materials is not well understood. In addition, it is still challenging to predict fracture energies and crack-tip strain fields of soft tough materials. Here, we report a scaling theory that accounts for synergistic effects of intrinsic fracture energies and dissipation on the toughening of soft materials. We then develop a coupled cohesive-zone and Mullins-effect model capable of quantitatively predicting fracture energies of soft tough materials and strain fields around crack tips in soft materials under large deformation. The theory and model are quantitatively validated by experiments on fracture of soft tough materials under large deformations. We further provide a general toughening diagram that can guide the design of new soft tough materials.
Adjuvant molecularly targeted therapy—epidermal growth factor tyrosine kinase inhibition and beyond

In stage IV non-small cell lung cancer (NSCLC), DNA molecular testing for mutations in epidermal growth factor receptor ( EGFR ) and gene rearrangements of anaplastic lymphoma kinase ( ALK ) has become the new standard of care. This is based on the unprecedented efficacy of small molecule EGFR tyrosine kinase inhibitors (TKIs) such as gefitinib and erlotinib against EGFR mutant NSCLC (1,2), and the ALK TKI crizotinib against ALK positive NSCLC (3). While these highly active drugs should conceptually be effective as a component of the curative treatment of earlier stage NSCLC, the presently available evidence is minimal as pivotal studies are either underway or still in development. This article reviews current evidence about the use of adjuvant therapy for molecular targets in NSCLC, in particular regarding the use of EGFR TKIs in the treatment of early stage NSCLC harboring EGFR mutations.
Economics, Equality, and Responsibility: A Review Essay

John Roemer’s recent book, Theories of Distributive Justice, is a major contribution to the debate over egalitarian theories of justice. In this review essay I confine myself to two of the central issues in this debate: his criticism of the current varieties of egalitarianism and his discussion of the critical role of responsibility in contemporary egalitarian theory.
Is There a Positive Intertemporal Tradeoff Between Risk and Return After All

This paper develops an extended version of Turner, Startz, and Nelson's (1989) Markov-switching model of stock returns. The model is motivated as an alternative version of Campbell and Hentschel's (1992) volatility feedback model, with news about future dividends subject to a two-state Markov-switching variance. We are able to identify an endogenous volatility feedback effect by assuming that economic agents acquire information about market volatility that is not directly available to econometricians. Using this model, we find strong evidence for a positive tradeoff between volatility and the equity risk premium, especially for post-War stock returns.
Fundamental kinetics and mechanistic pathways for oxidation reactions in supercritical water

Oxidation of the products of human metabolism in supercritical water has been shown to be an efficient way to accomplish the on-board water/waste recycling in future long-term space flights. Studies of the oxidation kinetics of methane to carbon dioxide in supercritical water are presented in this paper in order to enhance the fundamental understanding of the oxidation of human waste compounds in supercritical water. It is concluded that, although the elementary reaction models remain the best hope for simulating oxidation in supercritical water, several modifications to existing mechanisms need to be made to account for the role of water in the reaction mechanism.
Ethanol plant investment using net present value and real options analyses

Abstract A real options analysis of entry–exit decisions for dry-grind corn ethanol plants is conducted to incorporate the impact of rising volatility in market prices. For a large plant, the estimated gross margins (ethanol price less corn price), in current dollars, that induce entry and exit were 0.35 US$ dm−3 and 0.03 US$ dm−3, respectively; nearly 207% (63%) above (below) their respective net present value estimates. Under baseline conditions, a large operating plant would become mothballed at 0.05 US$ dm−3 and reactivate if margins rebounded to 0.17 US$ dm−3. Growth in the variability of ethanol margins will lead to delays in new plant investments, as well as exits of currently operating facilities. To the extent that alternative renewable fuel technologies become viable, the model can be easily adapted to estimate and compare the results across alternative bioenergy investments.
Lower Bounds for Approximate LDCs

We study an approximate version of q-query LDCs (Locally Decodable Codes) over the real numbers and prove lower bounds on the encoding length of such codes. A q-query (α,δ)-approximate LDC is a set V of n points in ℝ d so that, for each i ∈ [d] there are Ω(δn) disjoint q-tuples (u 1,…,u q ) in V so that span(u 1,…,u q ) contains a unit vector whose i’th coordinate is at least α. We prove exponential lower bounds of the form \(n \geq 2^{\Omega(\alpha \delta \sqrt{d})}\) for the case q = 2 and, in some cases, stronger bounds (exponential in d).
Path-planning strategies for a point mobile automaton moving amidst unknown obstacles of arbitrary shape

The problem of path planning for an automaton moving in a two-dimensional scene filled with unknown obstacles is considered. The automaton is presented as a point; obstacles can be of an arbitrary shape, with continuous boundaries and of finite size; no restriction on the size of the scene is imposed. The information available to the automaton is limited to its own current coordinates and those of the target position. Also, when the automaton hits an obstacle, this fact is detected by the automaton’s “tactile sensor.” This information is shown to be sufficient for reaching the target or concluding in finite time that the target cannot be reached. A worst-case lower bound on the length of paths generated by any algorithm operating within the framework of the accepted model is developed; the bound is expressed in terms of the perimeters of the obstacles met by the automaton in the scene. Algorithms that guarantee reaching the target (if the target is reachable), and tests for target reachability are presented. The efficiency of the algorithms is studied, and worst-case upper bounds on the length of generated paths are produced.
Quantified constraint satisfaction and 2-semilattice polymorphisms

The quantified constraint satisfaction problem (QCSP) is a natural and useful generalization of the constraint satisfaction problem (CSP) in which both universal and existential quantification of variables is permitted. Because the CSP and QCSP are in general intractable, much effort has been directed towards identifying restricted cases of these problems that are tractable in polynomial time. In this paper, we investigate restricted cases of the QCSP having 2-semilattice polymorphisms. We prove a complete classification of 2-semilattice polymorphisms, demonstrating that each gives rise to a case of the QCSP that is either tractable in polynomial time, or coNP-hard.
Herbaceous biomass feedstock production: the economic potential and impacts on US agriculture.

Abstract This paper addresses the economic feasibility and impacts on US agriculture of establishing a biomass crop industry capable of producing 8.4 million GJ of methanol or 9.9 million GJ of ethanol by the year 2030 from grasses grown as biomass feedstocks. The results suggest that such an industry could become commercially viable and that the agricultural economy would benefit. Producers of traditional and biomass crops would benefit most. Consumers and livestock producers would lose from higher crop prices, but these losses would be offset by gains to society from reduced government payments to crop producers.
Parameter networks: towards a theory of low-level vision

One of the most fundamental problems in vision is segmentation; the way in which parts of an image are perceived as a meaningful whole. Recent work has shown how to calculate images of physical parameters from raw intensity data. Such images are known as intrinsic images, and examples are images of velocity (optical flow), surface orientation, occluding contour, and disparity. While intrinsic images are not segmented, they are distinctly easier to segment than the original intensity image. Segments can be detected by a general Hough transform technique. Networks of feature parameters are appended to the intrinsic image organization. Then the intrinsic image points are mapped into these networks. This mapping will be many-to-one onto parameter values that represent segments. This basic method is extended into a general representation and control technique with the addition of three main ideas: abstraction levels; sequential search; and tight counting These ideas are a nucleus of a connectionist theory of low 'eve and m'ermediate-level vision. This theory explains segmentation in terms of massively parallel cooperative computation among intrinsic images and a set of parameter spaces at different levels of abstraction.
Accommodating Labor and Antitrust

One of the joys of the academic life is being paid a good salary to read important and provocative articles, such as Michael LeRoy’s latest contribution to the debate about the extent to which antitrust law should constrain owners in monopoly sports leagues from limiting competition among themselves for the services of players. This particular article reminded me of a prior job as an attorney for the Senate Judiciary Committee. My first assignment was to participate in negotiations on amendments to shipping laws that granted antitrust exemptions for agreements in that industry. An attorney for the Senate Commerce Committee kept referring to the Shipping Act as “our law” and, sneering at me and my Judiciary Committee colleagues, referring to the Sherman Act as “your law.” Professor LeRoy, a distinguished scholar of labor law and empirical research on the effect of labor law on labor relations, clearly prefers that “his law” should govern sports league labor disputes, and that “my law” should stay out. Although his empirical work is a useful contribution to the literature that will serve as a valuable reference for other scholars, the evidence about what is —that federal courts often grant antitrust remedies in sports labor disputes—tells us nothing about what should be . Namely, in Professor LeRoy’s words, whether “federal jurisdiction properly extends to antitrust lawsuits filed by union-represented athletes who challenge labor market restrictions imposed by their league.”
Money in the Utility Function: An Empirical Implementation

This paper studies household asset demands by allowing certain assets to contribute directly to utility. It estimates the parameters of an aggregate utility function which includes both consumption and liquidity services.These liquidity services depend on the level of various asset stocks. We apply these estimates to investigate the long- and short-run interest elasticities of demand for money, time deposits, and Treasury bills. We also examine the impact of open market operations on interest rates, and present new estimates of the welfare cost of inflation.
On Generating Independent Random Strings

It is shown that from two strings that are partially random and independent (in the sense of Kolmogorov complexity) it is possible to effectively construct polynomially many strings that are random and pairwise independent. If the two initial strings are random, then the above task can be performed in polynomial time. It is also possible to construct in polynomial time a random string, from two strings that have constant randomness rate.
An Anatomy Of Credit Booms: Evidence From Macro Aggregates And Micro Data

This paper proposes a methodology for measuring credit booms and uses it to identify credit booms in emerging and industrial economies over the past four decades. In addition, we use event study methods to identify the key empirical regularities of credit booms in macroeconomic aggregates and micro-level data. Macro data show a systematic relationship between credit booms and economic expansions, rising asset prices, real appreciations, widening external deficits and managed exchange rates. Micro data show a strong association between credit booms and firm-level measures of leverage, firm values, and external financing, and bank-level indicators of banking fragility. Credit booms in industrial and emerging economies show three major differences: (1) credit booms and the macro and micro fluctuations associated with them are larger in emerging economies, particularly in the nontradables sector; (2) not all credit booms end in financial crises, but most emerging markets crises were associated with credit booms; and (3) credit booms in emerging economies are often preceded by large capital inflows but not by financial reforms or productivity gains.
Exploring the dark side of the web: collection and analysis of u.s. extremist online forums

Contents in extremist online forums are invaluable data sources for extremism reseach. In this study, we propose a systematic Web mining approach to collecting and monitoring extremist forums. Our proposed approach identifies extremist forums from various resources, addresses practical issues faced by researchers and experts in the extremist forum collection process. Such collection provides a foundation for quantitative forum analysis. Using the proposed approach, we created a collection of 110 U.S. domestic extremist forums containing more than 640,000 documents. The collection building results demonstrate the effectiveness and feasibility of our approach. Furthermore, the extremist forum collection we created could serve as an invaluable data source to enable a better understanding of the extremism movements.
Coalitional Manipulation on Communication Network

In an abstract model of division problems, we study division rules that are not manipulable through a reallocation of individual characteristic vectors within a coalition (e.g. reallocation of claims in bankruptcy problems). A coalition can be formed if members of the coalition are connected on a communication network, or a graph. We offer a characterization of non-manipulable division rules without any assumption on the structure of communication network. As corollaries, we obtain a number of earlier characterization results established with the assumption of complete network (complete graph) in various specialized settings. Moreover, our characterization, as we show, can be quite different from the earlier results depending on the network structure: for example, when the network is a tree, much larger family of rules are shown to be non-manipulable. The abstract model we consider can have various special examples such as bankruptcy problems, surplus sharing problems, cost sharing problems, social choice with transferable utility, etc
Robust and MaxMin Optimization under Matroid and Knapsack Uncertainty Sets

Consider the following problem: given a set system (U, Ω) and an edge-weighted graph G = (U, E) on the same universe U, find the set A ∈ Ω such that the Steiner tree cost with terminals A is as large as possible—“which set in Ω is the most difficult to connect up?” This is an example of a max-min problem: find the set A ∈ Ω such that the value of some minimization (covering) problem is as large as possible.In this article, we show that for certain covering problems that admit good deterministic online algorithms, we can give good algorithms for max-min optimization when the set system Ω is given by a p-system or knapsack constraints or both. This result is similar to results for constrained maximization of submodular functions. Although many natural covering problems are not even approximately submodular, we show that one can use properties of the online algorithm as a surrogate for submodularity.Moreover, we give stronger connections between max-min optimization and two-stage robust optimization, and hence give improved algorithms for robust versions of various covering problems, for cases where the uncertainty sets are given by p-systems and knapsack constraints.
Post Walrasian Macro Policy and the Economics of Muddling Through

(2003). Post Walrasian Macro Policy and the Economics of Muddling Through. International Journal of Political Economy: Vol. 33, No. 2, pp. 17-35.
Automated Debugging Using Path-Based Weakest Preconditions

Software debugging is the activity of locating and correcting erroneous statements in programs. Automated tools to locate and correct the erroneous statements in a program can significantly reduce the cost of software development. In this paper, we present a new approach to locate and correct an erroneous statement in a function. We assume the correct specification of the erroneous function is available in the form of preconditions and postconditions of the function. Our approach combines ideas from software testing and weakest preconditions used in correctness proof methods to locate a likely erroneous statement. We have implemented our approach and conducted experiments with several small programs. In our experiments, our approach was able to locate the erroneous statements in a large number of cases. Our preliminary experimental results show that our approach has potential for development of an automated bug location and correction tool.
Taking stock of risk management techniques for sovereigns

The author reviews the current state of affairs and thinking on external risk management for developing countries. He tries to identify the reasons behind the limited risk management by sovereigns. Perverse incentives arising from a too generous international safety net, limited access to international financial markets by developing countries arising from low creditworthiness, a limited supply of financial risk management tools suited to developing countries, and a poor supply of skills have inhibited risk management. Another constraint has been the limited attention given to the strategic objectives for risk management. Going forward, the author identifies actions by international financial markets, countries, and international financial institutions that can help improve risk management. These actions include GDP-indexed loans and efforts to develop price and weather indexes.
Combining test and proof in MBAT: An aerospace case study

In the aerospace industry, it has become possible to use formal analysis results as certification evidence thanks to the new version of the standard DO-178C and its formal methods supplement DO-333. Furthermore, formal proof has a high potential of cost reduction. On the other hand, it is not possible to replace testing completely by formal analysis, because the latter only considers more or less abstract models of the system under analysis, and can fail due to a too high complexity. But since certain verification tasks can be carried out by formal analysis with an advantage compared to testing, the question arises how both techniques, i.e. proof and test, can be combined in the best way. The European project MBAT gives answers to this question, and in this article we show how the combined approach has been applied to a relevant use case from Rockwell Collins.
Secure Name Service: A Framework for Protecting Critical Internet Resources

We propose a novel Secure Name Service (SNS) framework for protecting critical Internet resources from unauthorized accesses, denial of service (DoS) and other attacks. The key idea is to enforce packet-origin authentication through resource virtualization and utilize dynamic name binding for protecting servers under attacks and improving service availability. Different from static network-level security schemes such as IPsec and VPN, SNS is able to dynamically bind the names of critical resources at the service level, which allows us to actively protect the service resources through a distributed filtering mechanism built on authenticated packet forwarding paths. Our prototype implementation of authenticated packet forwarding components on Pentium 4 Linux machines demonstrates that regular Linux platforms are sufficient to support SNS authenticated packet forwarding on 100Mbps or lGbps LANs.
Density boosting for Gaussian mixtures

Ensemble method is one of the most important recent developments in supervised learning domain. Performance advantage has been demonstrated on problems from a wide variety of applications. By contrast, efforts to apply ensemble method to unsupervised domain have been relatively limited. This paper addresses the problem of applying ensemble method to unsupervised learning, specifically, the task of density estimation. We extend the work by Rosset and Segal [3] and apply the boosting method, which has its root as a gradient descent algorithm, to the estimation of densities modeled by Gaussian mixtures. The algorithm is tested on both artificial and real world datasets, and is found to be superior to non-ensemble approaches. The method is also shown to outperform the alternative bagging algorithm.
GTAP-M: A GTAP Model and Data Base that Incorporates Domestic Margins

Transportation, wholesaling, and retailing activities are a significant segment of economic activity in many economies. The magnitude of these activities can vary greatly between products, users, and regions. However, in most applied general equilibrium (AGE) analyses, these marketing activities are not tied to specific commodities. This paper develops a model framework and database that incorporates domestic marketing margins on domestic and imported goods going to final demand or used as intermediate inputs, and margins on exports, into the standard GTAP Model. The effects of incorporating domestic marketing activities into an AGE model are illustrated by comparing the results of the standard GTAP Model to the new GTAP-M Model for several different technological change scenarios. The comparison yields two main results. First, tying the domestic marketing activities to specific commodities changes the degree of price transmission from producers to users, compared to a model that does not include margin activities explicitly. The second main result is that the magnitude of the elasticity of substitution between commodities and the composite marketing activity is very important. Allowing variable margins creates a new source of demand-responsiveness for commodities which can significantly alter the results of policy simulations.
Synthesis of 1,2,4-thiadiazoles by oxidative dimerization of carbothioamides by using oxone

1,2,4-Thiadiazoles were efficiently synthesized in good yields through the oxidative dimerization of carbothioamides by using Oxone as a readily available, inexpensive, and environmentally safe oxidant. A similar reaction of phenylselenoamide led to the corresponding 1,2,4-phenylselenadiazole in high yield.
Aberrant Myeloid Marker Expression in Precursor B-Cell and T-Cell Leukemias

The World Health Organization (WHO) characterization of the immunophenotype of precursor B-cell acute lymphoblastic leukemia (pre-B ALL) includes the possible expression of myeloid cluster of differentiation (CD) markers CD13 and CD33. In precursor T-cell acute lymphoblastic leukemia (pre-T ALL), myeloid markers CD13 and CD33 are frequent while CD117 is rare. In the present investigation, 71 cases of confirmed pre-B ALL were evaluated for the presence of CD13 and CD33. Of the 19 (27%) cases that positively expressed myeloid markers, 10 (53%) expressed CD13, 17 (89%) expressed CD33, and 1 (5%) expressed CD117. Eight (42%) expressed both CD13 and CD33, and 1 (5%) expressed CD13, CD33, and CD117. Twenty-one cases of confirmed pre-T ALL were analyzed for myeloid markers CD13, CD33, CD117, and MPO. Of the 6 (29%) expressing myeloid markers, 4 (67%) were positive for CD13, 4 (67%) for CD33, 3 50(%) for CD117, and 1 (17%) for MPO. One (17%) was positive for both CD13 and CD117; one (17%) for CD13 and CD33; one (17%) for CD13, CD33 and CD117; and one (17%) for CD13, CD33 and MPO. These markers portend a poor prognosis compared to ALL cases without myeloid antigens, and a poor response to drug therapies targeting conventional ALL. Future studies will be directed to correlation of these markers with prognosis and therapeutic response, as well as whether drug therapies targeting myeloid antigens could be of use in treatment.
Organic-functionalized molecular sieves as shape-selective catalysts

Zeolites and related crystalline molecular sieves can possess catalytically active acid sites, as well as uniformly sized and shaped pores and voids, that allow for their industrial use as shape-selective catalysts1. Some catalytic reactions that are not mediated by acids (such as oxidation) have also been shown to occur in zeolites in a shape-selective manner2, but the diversity in active sites in these materials remains restricted. For mesoporous materials3, the diversity in catalytic activity has been broadened by grafting organosilanes that contain organic functional groups onto the internal pore surfaces4,5,6 or by incorporating them into the structure during the synthesis process7,8,9,10,11,12. The former approach has not proven straightforward for microporous zeolites because a large fraction of the grafted functional groups become attached instead to the exterior surfaces of the crystal, where there is no shape selectivity13. The synthesis of zeolites and molecular sieves using organosilanes as structure-directing agents has been accomplished14,15, but the subsequent creation of porosity requires the complete loss of the organic functional groups. Here we report a new methodology that overcomes these problems and allows the production of microporous molecular sieves containing organic functionalities within their pores. During the initial synthesis phase, phenethyl groups covalently tethered to silicon atoms are incorporated into the framework. The external surface-bound functionalities and the structure-directing agents residing within the intracrystalline spaces are then removed to create a microporous material. Subsequent sulphonation of the phenyl rings produces intrapore sulphonic acid sites that perform shape-selective catalysis. Different active-site types can be created by attaching other functional groups to the framework silicon, and we therefore expect that our method will lead to the formation of a wide range of shape-selective catalysts.
Effect of Test Temperature, Oxygen Attack, Thermal Transients, and Protective Coatings on Tensile Strength of Silicon Carbide Matrix Composites

Tensile strength and elongation are reported for SiC/SiC and SiC/C composites from RT to 1200 C in air. Both composites show reduced fracture resistance at temperatures in excess of 600 C. The SiC/SiC composite is resistant to environmental attack during isothermal and cyclic exposures to 1000 C. However, the SiC/C composite is severely attacked and the C fibers may fully oxidize leading to very low fracture resistance. Protective coatings have no significant effect on SiC/SiC but provide substantial protection for SiC/C. There are indications that the latter system may crack readily as a result of thermal expansion mismatch because even the coated samples degrade on thermal cycling. No correlations were discerned between degree of fiber pullout and fracture resistance. 4 refs.
Enumeration of totally real number fields of bounded root discriminant

We enumerate all totally real number fields F with rootdiscriminant δF ≤ 14. There are 1229 such fields, each with degree[F : Q] ≤ 9.
Estimation in High Dimensions: A Geometric Perspective

This tutorial provides an exposition of a flexible geometric framework for high-dimensional estimation problems with constraints. The tutorial develops geometric intuition about high-dimensional sets, justifies it with some results of asymptotic convex geometry, and demonstrates connections between geometric results and estimation problems. The theory is illustrated with applications to sparse recovery, matrix completion, quantization, linear and logistic regression, and generalized linear models.
Software verification with liquid types

Traditional software verification algorithms work by using a combination of Floyd-Hoare Logics, Model Checking and Abstract Interpretation, to check and infer suitable program invariants. However, these techniques are problematic in the presence of complex but ubiquitous constructs like generic data structures, first-class functions. We observe that modern type systems are capable of the kind of analysis needed to analyze the above constructs, and we use this observation to develop Liquid Types, a new static verification technique which combines the complementary strengths of Floyd-Hoare logics, Model Checking, and Types. As a result, we demonstrate how liquid types can be used to statically verify properties ranging from memory safety to data structure correctness, in higher-order languages like ML. This presentation is based on joint work with Patrick Rondon and Ming Kawaguchi.
Dynamical systems trees

We propose dynamical systems trees (DSTs) as a flexible class of models for describing multiple process that interact via a hierarchy of aggregating parent chains. DSTs extend Kalman filters, hidden Markov models and nonlinear dynamical systems to an interactive group scenario. Various individual processes interact as communities and sub-communities in a tree structure that is unrolled in time. To accommodate nonlinear temporal activity, each individual leaf process is modeled as a dynamical system containing discrete and/or continuous hidden states with discrete and/or Gaussian emissions. Subsequent higher level parent processes act like hidden Markov models and mediate the interaction between leaf processes or between other parent processes in the hierarchy. Aggregator chains are parents of child processes that they combine and mediate, yielding a compact overall parameterization. We provide tractable inference and learning algorithms for arbitrary DST topologies via an efficient structured mean-field algorithm. The diverse applicability of DSTs is demonstrated by experiments on gene expression data and by modeling group behavior in the setting of an American football game.
Non-Abelian gauge theory on q-Quantum spaces

Gauge theories on q-deformed spaces are constructed using covariant derivatives. For this purpose a ''vielbein'' is introduced, which transforms under gauge transformations. The non-Abelian case is treated by establishing a connection to gauge theories on commutative spaces, i.e. by a Seiberg-Witten map. As an example we consider the Manin plane. Remarks are made concerning the relation between covariant coordinates and covariant derivatives.
Conformal N=0 d=4 gauge theories from AdS/CFT superstring duality?

Abstract Non-supersymmetric d =4 gauge theories which arise from superstring duality on a manifold AdS 5 × S 5 / Z p are cataloged for a range 2≤ p ≤41. A number have vanishing two-loop gauge β −function, a necessary but not sufficient condition to be a conformal field theory.
The spectral structure of correlator matrices

In lattice QCD spectrum calculations, it is desirable to obtain multiple excited state energies in each symmetry channel. Typically, one constructs several interpolating operators for the symmetry channel of interest, forms the ‘correlator matrix’ of all possible two-point functions, and uses the variational method to obtain as many energy levels as possible. We present a detailed look at this last step, starting from a discussion of the symmetry properties and spectral structure of the correlator matrix. We continue by motivating and describing the variational method, before discussing some conceptual and practical challenges concerning the light baryon sector. We conclude by mentioning some alternate spectrum extraction methods currently under study. Throughout, we attempt to quantify all approximations and assumptions, and we illustrate our points using a nucleon correlator matrix estimated on dynamical two-flavor lattice data.
Towards Sustainable Water Supply: Schematic Development of Big Data Collection Using Internet of Things (IoT)

Abstract Water supply systems in the United States connect raw water sources to hundreds of millions of water consumers through humongous infrastructure that include approximately one million miles of buried water mains and service connections and thousands of treatment facilities and appurtenances. This enormous set-up is currently operated by more than 170,000 public water systems. Sustainability of the water supply system faces several imminent challenges such as: 1) increasing water main breaks, 2) decreasing fresh water resources, 3) untraceable non-revenue water use, and 4) increasing water demands. However, current water supply management practices are not capable of providing fundamental solutions to the issues identified above. Big Data is a new technical concept to collect massive amounts of relevant data from sensors installed to monitor structural condition, usage, and system performance. This Big Data concept can be realized by deploying Internet of Things (IoT) technology throughout the water supply infrastructure and consumers’ usage. This paper presents a schematic development of IoT application for Big Data collection through a myriad of water clients. The scheme consists of downstream and upstream data collection using Wireless Sensor Network (WSN) technologies connecting to IoT. Downstream data shall provide water usage and performance data to clients and upstream data is similar to traditional SCADA and Automated Meter Reading (AMR) systems. Ultimately, all data will be converged to build a Big Data collection system where data mining identifies 1) local and system performances including pressure and flow, 2) non-revenue and illegitimate water consumption, and 3) locations and quantity of water breaks and water losses. The goal of this development is to enable both utilities and consumers to proactively manage their water usage and achieve higher levels of sustainability in water supply.
On the relation between the A-polynomial and the Jones polynomial

This paper shows that the noncommutative generalization of the A-polynomial of a knot, defined using Kauffman bracket skein modules, together with finitely many colored Jones polynomials, determines the remaining colored Jones polynomials of the knot. It also shows that under certain conditions, satisfied for example by the unknot and the trefoil knot, the noncommutative generalization of the A-polynomial determines all colored Jones polynomials of the knot.
Lattice Distortions and Charge Carriers in Cuprates

A phenomenological model with itinerant bands and local states trapped by thelattice on the Cu-sites, is discussed to describe global features ofcuprates. Relative energy positions of localized and itinerant states beingtuned (thermodynamically or by doping), the system must undergo first-orderMott metal-insulator transition. Decreasing the local level (from themetallic end of a stoichiometric compound), charge separation instabilityoccurs first before the Mott transition. Crossing and hybridization betweenlocal (flat) and itinerant bands introduce a structure in density of stateswhich may account for “pseudogap” features in cuprates. Modelresults in polaronic lattice effects and is rich enough to serve as aphenomenology of cuprates.