cssi/SciSciGPT-SciSciNet huggingface dataset:
Ultra Lightweight Multiple-time Digital Signature for the Internet of Things Devices

Digital signatures are basic cryptographic tools to provide authentication and integrity in the emerging ubiquitous systems in which resource-constrained devices are expected to operate securely and efficiently. However, existing digital signatures might not be fully practical for such resource-constrained devices (e.g., medical implants) that have energy limitations. Some other computationally efficient alternatives (e.g., one-time/multiple-time signatures) may introduce high memory and/or communication overhead due to large private key and signature sizes. In this paper, our contributions are two-fold: First, we develop a new lightweight multiple-time digital signature scheme called Signer Efficient Multiple-time Elliptic Curve Signature (SEMECS), which is suitable for resource-constrained embedded devices. SEMECS achieves optimal signature and private key sizes for an EC-based signature without requiring any EC operation (e.g., EC scalar multiplication or addition) at the signer. We prove SEMECS is secure (in random oracle model) with a tight security reduction. Second, we fully implemented SEMECS on 8-bit AVR microprocessor with a comprehensive energy consumption analysis and comparison. Our experiments confirm up to 19x less battery-consumption for SEMECS as compared to its fastest (full-time) counterpart, SchnorrQ, while offering significant performance advantages over its multiple-time counterparts in various fronts. We open-source our implementation for public testing and adoption.
Random hypersurfaces and embedding curves in surfaces over finite fields

Abstract We use Poonen's closed point sieve to prove two independent results. First, we show that the obvious obstruction to embedding a curve in an unspecified smooth surface is the only obstruction over a perfect field, by proving the finite field analogue of a Bertini-type result of Altman and Kleiman. Second, we prove a conjecture of Vakil and Wood on the asymptotic probability of hypersurface sections having a prescribed number of singularities.
Heterogeneity adjustment with applications to graphical model inference.

Heterogeneity is an unwanted variation when analyzing aggregated datasets from multiple sources. Though different methods have been proposed for heterogeneity adjustment, no systematic theory exists to justify these methods. In this work, we propose a generic framework named ALPHA (short for Adaptive Low-rank Principal Heterogeneity Adjustment) to model, estimate, and adjust heterogeneity from the original data. Once the heterogeneity is adjusted, we are able to remove the batch effects and to enhance the inferential power by aggregating the homogeneous residuals from multiple sources. Under a pervasive assumption that the latent heterogeneity factors simultaneously affect a fraction of observed variables, we provide a rigorous theory to justify the proposed framework. Our framework also allows the incorporation of informative covariates and appeals to the ‘Bless of Dimensionality’. As an illustrative application of this generic framework, we consider a problem of estimating high-dimensional precision matrix for graphical model inference based on multiple datasets. We also provide thorough numerical studies on both synthetic datasets and a brain imaging dataset to demonstrate the efficacy of the developed theory and methods.
Intelligent Parameter Tuning in Optimization-Based Iterative CT Reconstruction via Deep Reinforcement Learning

A number of image-processing problems can be formulated as optimization problems. The objective function typically contains several terms specifically designed for different purposes. Parameters in front of these terms are used to control the relative importance among them. It is of critical importance to adjust these parameters, as quality of the solution depends on their values. Tuning parameters are a relatively straight forward task for a human, as one can intuitively determine the direction of parameter adjustment based on the solution quality. Yet manual parameter tuning is not only tedious in many cases, but also becomes impractical when a number of parameters exist in a problem. Aiming at solving this problem, this paper proposes an approach that employs deep reinforcement learning to train a system that can automatically adjust parameters in a human-like manner. We demonstrate our idea in an example problem of optimization-based iterative computed tomography (CT) reconstruction with a pixel-wise total-variation regularization term. We set up a parameter-tuning policy network (PTPN), which maps a CT image patch to an output that specifies the direction and amplitude by which the parameter at the patch center is adjusted. We train the PTPN via an end-to-end reinforcement learning procedure. We demonstrate that under the guidance of the trained PTPN, reconstructed CT images attain quality similar or better than those reconstructed with manually tuned parameters.
Stein Variational Adaptive Importance Sampling.

We propose a novel adaptive importance sampling algorithm which incorporates Stein variational gradient decent algorithm (SVGD) with importance sampling (IS). Our algorithm leverages the nonparametric transforms in SVGD to iteratively decrease the KL divergence between our importance proposal and the target distribution. The advantages of this algorithm are twofold: first, our algorithm turns SVGD into a standard IS algorithm, allowing us to use standard diagnostic and analytic tools of IS to evaluate and interpret the results; second, we do not restrict the choice of our importance proposal to predefined distribution families like traditional (adaptive) IS methods. Empirical experiments demonstrate that our algorithm performs well on evaluating partition functions of restricted Boltzmann machines and testing likelihood of variational auto-encoders.
Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics

In this essay I discuss potential outcome and graphical approaches to causality, and their relevance for empirical work in economics. I review some of the work on directed acyclic graphs, including the recent The Book of Why (Pearl and Mackenzie 2018). I also discuss the potential outcome framework developed by Rubin and coauthors (e.g., Rubin 2006), building on work by Neyman (1990 [1923]). I then discuss the relative merits of these approaches for empirical work in economics, focusing on the questions each framework answers well, and why much of the the work in economics is closer in spirit to the potential outcome perspective.
Phase transition in the spiked random tensor with rademacher prior

We consider the problem of detecting a deformation from a symmetric Gaussian random $p$-tensor $(p\geq3)$ with a rank-one spike sampled from the Rademacher prior. Recently, in Lesieur et al. (Barbier, Krzakala, Macris, Miolane and Zdeborova (2017)), it was proved that there exists a critical threshold $\beta_{p}$ so that when the signal-to-noise ratio exceeds $\beta_{p}$, one can distinguish the spiked and unspiked tensors and weakly recover the prior via the minimal mean-square-error method. On the other side, Perry, Wein and Bandeira (Perry, Wein and Bandeira (2017)) proved that there exists a $\beta_{p}'<\beta_{p}$ such that any statistical hypothesis test cannot distinguish these two tensors, in the sense that their total variation distance asymptotically vanishes, when the signa-to-noise ratio is less than $\beta_{p}'$. In this work, we show that $\beta_{p}$ is indeed the critical threshold that strictly separates the distinguishability and indistinguishability between the two tensors under the total variation distance. Our approach is based on a subtle analysis of the high temperature behavior of the pure $p$-spin model with Ising spin, arising initially from the field of spin glasses. In particular, we identify the signal-to-noise criticality $\beta_{p}$ as the critical temperature, distinguishing the high and low temperature behavior, of the Ising pure $p$-spin mean-field spin glass model.
Bandits with Feedback Graphs and Switching Costs

We study the adversarial multi-armed bandit problem where the learner is supplied with partial observations modeled by a \emph{feedback graph} and where shifting to a new action incurs a fixed \emph{switching cost}. We give two new algorithms for this problem in the informed setting. Our best algorithm achieves a pseudo-regret of $\tilde O(\gamma(G)^{\frac{1}{3}}T^{\frac{2}{3}})$, where $\gamma(G)$ is the domination number of the feedback graph. This significantly improves upon the previous best result for the same problem, which was based on the independence number of $G$. We also present matching lower bounds for our result that we describe in detail. Finally, we give a new algorithm with improved policy regret bounds when partial counterfactual feedback is available.
The Geometry of Deep Networks: Power Diagram Subdivision

We study the geometry of deep (neural) networks (DNs) with piecewise affine and convex nonlinearities. The layers of such DNs have been shown to be max-affine spline operators (MASOs) that partition their input space and apply a region-dependent affine mapping to their input to produce their output. We demonstrate that each MASO layer's input space partitioning corresponds to a power diagram (an extension of the classical Voronoi tiling) with a number of regions that grows exponentially with respect to the number of units (neurons). We further show that a composition of MASO layers (e.g., the entire DN) produces a progressively subdivided power diagram and provide its analytical form. The subdivision process constrains the affine maps on the potentially exponentially many power diagram regions with respect to the number of neurons to greatly reduce their complexity. For classification problems, we obtain a formula for a MASO DN's decision boundary in the input space plus a measure of its curvature that depends on the DN's nonlinearities, weights, and architecture. Numerous numerical experiments support and extend our theoretical results.
Clinical Concept Extraction for Document-Level Coding.

The text of clinical notes can be a valuable source of patient information and clinical assessments. Historically, the primary approach for exploiting clinical notes has been information extraction: linking spans of text to concepts in a detailed domain ontology. However, recent work has demonstrated the potential of supervised machine learning to extract document-level codes directly from the raw text of clinical notes. We propose to bridge the gap between the two approaches with two novel syntheses: (1) treating extracted concepts as features, which are used to supplement or replace the text of the note; (2) treating extracted concepts as labels, which are used to learn a better representation of the text. Unfortunately, the resulting concepts do not yield performance gains on the document-level clinical coding task. We explore possible explanations and future research directions.
Homologous Recombination-Based Genome Editing by Clade F AAVs Is Inefficient in the Absence of a Targeted DNA Break

Adeno-associated virus (AAV) vectors are frequently used as donor templates for genome editing by homologous recombination. Although modification rates are typically under 1%, they are greatly enhanced by targeted double-stranded DNA breaks (DSBs). A recent report described clade F AAVs mediating high-efficiency homologous recombination-based editing in the absence of DSBs. The clade F vectors included AAV9 and a series isolated from human hematopoietic stem and progenitor cells (HSPCs). We evaluated these vectors by packaging homology donors into AAV9 and an AAVHSC capsid and examining their ability to insert GFP at the CCR5 and AAVS1 loci in human HSPCs and cell lines. As a control, we used AAV6, which effectively edits HSPCs but only when combined with a targeted DSB. Each AAV vector promoted GFP insertion in the presence of matched CCR5 or AAVS1 zinc-finger nucleases (ZFNs), but none supported detectable editing in the absence of the nucleases. Rates of editing with ZFNs correlated with transduction efficiencies for each vector, implying no differences in the ability of donor sequences delivered by the different vectors to direct genome editing. Our results, therefore, do not support that clade F AAVs can perform high-efficiency genome editing in the absence of a DSB.
Effect of forename string on author name disambiguation

In author name disambiguation, author forenames are used to decide which name instances are disambiguated together and how much they are likely to refer to the same author. Despite such a crucial role of forenames, their effect on the performance of heuristic (string matching) and algorithmic disambiguation is not well understood. This study assesses the contributions of forenames in author name disambiguation using multiple labeled data sets under varying ratios and lengths of full forenames, reflecting real‐world scenarios in which an author is represented by forename variants (synonym) and some authors share the same forenames (homonym). The results show that increasing the ratios of full forenames substantially improves both heuristic and machine‐learning‐based disambiguation. Performance gains by algorithmic disambiguation are pronounced when many forenames are initialized or homonyms are prevalent. As the ratios of full forenames increase, however, they become marginal compared to those by string matching. Using a small portion of forename strings does not reduce much the performances of both heuristic and algorithmic disambiguation methods compared to using full‐length strings. These findings provide practical suggestions, such as restoring initialized forenames into a full‐string format via record linkage for improved disambiguation performances.
Platform Mispricing and Lender Learning in Peer-to-Peer Lending

We document how online lenders exploit a flawed, new pricing mechanism in a peer-to-peer lending platform: Prosper.com. Switching from auctions to a posted-price mechanism in December 2010, Prosper assigned loan listings with different estimated loss rates into seven distinctive rating grades and adopted a single price for all listings with the same rating grade. We show that lenders adjusted their investment portfolios towards listings at the low end of the risk spectrum of each Prosper rating grade. We find heterogeneity in the speed of adjustment by lender experience, investment size, and diversification strategies. It took about 16–17 months for an average lender to take full advantage of the “cherry-picking” opportunity under the single-price regime, which is roughly when Prosper switched to a more flexible pricing mechanism.
The International Law Commission’s Soft Law Influence

Since the 1990s, the International Law Commission has increasingly produced soft law, such as principles and draft conclusions, in addition to hard law like draft treaty articles This essay explores the implications of the International Law Commission’s transition toward a greater emphasis on soft law. Soft law is an effective vehicle for the International Law Commission’s mission of codification and progressive development of international law; the International Law Commission’s involvement increases the clarity and accessibility of international law norms and promotes a dynamic, synergistic relationship between hard law and soft law that contributes to the effective evolution of international law. Likewise, the International Law Commission is well-structured to produce soft law by virtue of its expertise, work processes, and robust engagement with states in the Sixth Committee of the United Nations General Assembly. Furthermore, the International Law Commission’s soft law has in fact been influential on an audience of diverse global legal actors, including the International Court of Justice and other international courts and tribunals, treaty bodies, states, and scholars. In order to build on its existing soft law influence, the International Law Commission should acknowledge its vast global audience and tailor its processes and practices to better reach these communities.
Comment on confirmation of the sigma meson

A Comment on the Letter by Nils A. T{umlt o}rnqvist and Matts Roos, Phys. Rev. Lett. {bold 76}, 1575 (1996). The authors of the Letter offer a Reply. {copyright} {ital 1996 The American Physical Society.}
A Dynamic Routing Framework for Shared Mobility Services

Travel time in urban centers is a significant contributor to the quality of living of its citizens. Mobility on Demand (MoD) services such as Uber and Lyft have revolutionized the transportation infrastructure, enabling new solutions for passengers. Shared MoD services have shown that a continuum of solutions can be provided between the traditional private transport for an individual and the public mass transit-based transport, by making use of the underlying cyber-physical substrate that provides advanced, distributed, and networked computational and communicational support. In this article, we propose a novel shared mobility service using a dynamic framework. This framework generates a dynamic route for multi-passenger transport, optimized to reduce time costs for both the shuttle and the passengers and is designed using a new concept of a space window. This concept introduces a degree of freedom that helps reduce the cost of the system involved in designing the optimal route. A specific algorithm based on the Alternating Minimization approach is proposed. Its analytical properties are characterized. Detailed computational experiments are carried out to demonstrate the advantages of the proposed approach and are shown to result in an order of magnitude improvement in the computational efficiency with minimal optimality gap when compared to a standard Mixed Integer Quadratically Constrained Programming-based algorithm.
Counterexamples to the Tilting and $(p,r)$-Filtration Conjectures

In this paper the authors produce a projective indecomposable module for the Frobenius kernel of a simple algebraic group in characteristic $p$ that is not the restriction of an indecomposable tilting module. This yields a counterexample to Donkin's longstanding Tilting Module Conjecture. The authors also produce a Weyl module that does not admit a $p$-Weyl filtration. This answers an old question of Jantzen, and also provides a counterexample to the $(p,r)$-Filtration Conjecture.
One-Sided Cross-Validation for Nonsmooth Density Functions

One-sided cross-validation (OSCV) is a bandwidth selection method initially introduced by Hart and Yi (J Am Stat Assoc 93(442):620–631, 1998) in the context of smooth regression functions. Martinez-Miranda et al. (in Gregoriou (ed) Operational risk towards basel III: best practices and issues in modeling, management and regulation, Wiley, Hoboken, 2009) developed a version of OSCV for smooth density functions. This article extends the method for nonsmooth densities. It also introduces the fully robust OSCV modification that produces consistent OSCV bandwidths for both smooth and nonsmooth cases. Practical implementations of the OSCV method for smooth and nonsmooth densities are discussed. One of the considered cross-validation kernels has potential for improving the OSCV method’s performance in the regression context.
Hotspot swells and the lifespan of volcanic ocean islands.

Volcanic ocean islands generally form on swells—seafloor that is shallower than expected for its age over areas hundreds to more than a thousand kilometers wide—and ultimately subside to form atolls and guyots (flat-topped seamounts). The mechanisms of island drowning remain enigmatic, however, and the subaerial lifespan of volcanic islands varies widely. We examine swell bathymetry and island drowning at 14 hotspots and find a correspondence between island lifespan and residence time atop swell bathymetry, implying that islands drown as tectonic plate motion transports them past mantle sources of swell uplift. This correspondence argues strongly for dynamic uplift of the lithosphere at ocean hotspots. Our results also explain global variations in island lifespan, which influence island topography, biodiversity, and climate.
Synthesizing enterprise data to strategically align performance: The intentionality of strategy surrogation

Abstract Strategic performance measurement systems (SPMS) are employed by senior management as a means of translating strategy into performance measures. Recent research suggests that this translation can lead managers to focus on personal performance measures as opposed to overall organizational strategy—a phenomenon referred to as strategy surrogation. Emerging technologies are increasingly used to operationalize SPMS via smart phone/tablet/laptop formats that inherently promote the use of small subsets of performance measures and have the potential to exacerbate strategy surrogation effects. This study explores executive managers' motivations in deploying dashboards and the resulting effect on operational managers' focus on associated performance measures. An exploratory cross-sectional field study is conducted with 27 executive to mid-level managers to establish a theoretical model explaining how and why organizations deploy dashboards and why managers use dashboards to facilitate their activities and decisions. Despite concerns over the propensity of managers to focus on performance measures and lose sight of strategic objectives (i.e. strategy surrogation), the interview data indicate that executive management intentionally designs dashboards to achieve strategy surrogation. The impact of this intentional surrogation appears to arise through operational managers' beliefs that dashboard measures align with organizational strategy and lead to improved managerial and organizational performance. However, this relationship between perceived alignment of performance measures and managerial and organizational performance is mediated by dashboard quality and information quality. These findings have important implications as the effects of SPMS on strategy surrogation are further explored by researchers, and as system designers consider the side effects of emerging technologies on effective strategic performance measurement.
Rapid Head Movements in Common Marmoset Monkeys.

Summary Gaze shifts, the directing of the eyes to an approaching predator, preferred food source, or potential mate, have universal biological significance for the survival of a species. Our knowledge of gaze behavior is based primarily on visually triggered responses, whereas head orientation triggered by auditory stimuli remains poorly characterized. Common marmoset (Callithrix jacchus) is a diurnal, small-bodied (∼350 g), New World monkey species, known for its rich behavioral repertoires during social interactions. We used a lightweight head tracking system to measure marmosets' reflexive head orientations toward a natural stimulus presented from behind. We found that marmoset could rotate its head at angular velocities above 1,000°/s and maintained target accuracy for a wide range of rotation amplitudes (up to 250°). This unusual, saccadic head orienting behavior offers opportunities for understanding the many biological factors that have shaped the evolution of sensorimotor controls of gaze orientation by the primate brain.
Tort’s Indifference: Conformity, Compliance, and Civil Recourse

Leading accounts of tort law split cleanly into two seams. Some trace its foundations to a deontic form of morality; others to an instrumental, policy-oriented system of efficient loss allocation. An increasingly prominent alternative to both seams, Civil Recourse Theory (CRT) resists this binary by arguing that tort comprises a basic legal category, and that its directives constitute reasons for action with robust normative force. Using the familiar question whether tort’s directives are guidance rules or liability rules as a lens, or prism, this essay shows how considerations of practical reasoning undermine one of CRT’s core commitments. If tort directives exert robust normative force, we must account for its grounds—for where it comes from, and why it obtains. CRT tries to do so by co-opting H.L.A. Hart’s notion of the internal point of view, but this leveraging strategy cannot succeed: while the internal point of view sees legal directives as guides to action, tort law merely demands conformity. To be guided by a directive is to comply with it, not conform to it, so tort’s structure blocks the shortcut to normativity CRT attempts to navigate. Given the fine-grained distinctions the theory makes, and with the connection between its claims and tort’s requirements thus severed, CRT faces a dilemma: it’s either unresponsive to tort’s normative grounds, or it’s inattentive to tort’s extensional structure.
Effects of Delayed Video-Based Feedback and Observing Feedback on Paraprofessional Implementation of Evidence-Based Practices for Students With Severe Disabilities:

Coaching with live observation and immediate performance feedback is an effective means to train paraprofessionals, but might not always be feasible. We used a multiple baseline across participants...
Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems

Many modern nonlinear control methods aim to endow systems with guaranteed properties, such as stability or safety, and have been successfully applied to the domain of robotics. However, model uncertainty remains a persistent challenge, weakening theoretical guarantees and causing implementation failures on physical systems. This paper develops a machine learning framework centered around Control Lyapunov Functions (CLFs) to adapt to parametric uncertainty and unmodeled dynamics in general robotic systems. Our proposed method proceeds by iteratively updating estimates of Lyapunov function derivatives and improving controllers, ultimately yielding a stabilizing quadratic program model-based controller. We validate our approach on a planar Segway simulation, demonstrating substantial performance improvements by iteratively refining on a base model-free controller.
A formal Riemannian structure on conformal classes and the inverse Gauss curvature flow

We define a formal Riemannian metric on a given conformal class of metrics on a closed Riemann surface. We show interesting formal properties for this metric, in particular the curvature is nonpositive and the Liouville energy is geodesically convex. The geodesic equation for this metric corresponds to a degenerate elliptic fully nonlinear PDE, and we prove that any two points are connected by a $C^{1,1}$ geodesic. Using this we can define a length space structure on the given conformal class. We present a different approach to the uniformization theorem by studying the negative gradient flow of the normalized Liouville energy, a new geometric flow whose principal term is the inverse of the Gauss curvature. We prove long time existence of solutions with arbitrary initial data and weak convergence to constant scalar curvature metrics. This is all a special case of a more general construction on even dimensional manifolds related to the $\sigma_{\frac{n}{2}}$-Yamabe problem, which will appear in a forthcoming article.
Pitfalls of data-driven peaks-over-threshold analysis: Perspectives from extreme ship motions

Abstract A popular peaks-over-threshold (PoT) method of Extreme Value Theory to quantify the probabilities of rare events is examined here on data generated from a nonlinear random oscillator model, describing a qualitative behavior of rolling of a ship in irregular seas. The restoring force in the oscillator model has a softening shape associated with the ship rolling application, and the response is also made bounded, so as to eliminate the possibility of “capsizing.” As a result, the tail of the resulting probability density function of the response undergoes three regimes: the Gaussian core, the heavy tail and the short bounded tail. By considering several scenarios where data are available in one but not another regime, it is shown that the PoT method can produce unsatisfactory results. Some refined methods from Extreme Value Theory, for example, those based on mixture models, are also examined, but without much success. It is thus argued that a data-driven application of the PoT method may fail, if the physical aspects of the system under study are not taken into account.
Optimal WDM Power Allocation via Deep Learning for Radio on Free Space Optics Systems

Radio on Free Space Optics (RoFSO), as a universal platform for heterogeneous wireless services, is able to transmit multiple radio frequency signals at high rates in free space optical networks. This paper investigates the optimal design of power allocation for Wavelength Division Multiplexing (WDM) transmission in RoFSO systems. The proposed problem is a weighted total capacity maximization problem with two constraints of total power limitation and eye safety concern. The model-based Stochastic Dual Gradient algorithm is presented first, which solves the problem exactly by exploiting the null duality gap. The model-free Primal-Dual Deep Learning algorithm is then developed to learn and optimize the power allocation policy with Deep Neural Network (DNN) parametrization, which can be utilized without any knowledge of system models. Numerical simulations are performed to exhibit significant performance of our algorithms compared to the average equal power allocation.
Nanosecond pulsed laser processing turns engineering metal alloys antireflective and superwicking

Abstract In this work, superwicking and antireflective properties are achieved on engineering metal surfaces by creating a surface pattern using a high energy nanosecond pulsed laser followed by a chemical immersion treatment. The high-energy nanosecond pulse laser scans the metal surface in air. Subsequently, the laser-textured surface is further treated by immersion in a 3-cyanopropyltricholosilane reagent. As a result of these two processes, microgrooves with micro- and nano-scale surface features are generated on the metal surface. Due to the created surface structure and favorable surface chemistry, water sprints uphill defying the gravity. The fast self-propelling movement of water is due to the supercapillary effect of the surface microchannel and the superhydrophilic surface nitrile group. The wicking effect on the processed surface follows the classical square root of time dependence. The processed surface shows good antireflective properties in the visible and infrared spectrum. Surface features, surface chemistry, wettability, surface reflectivity and wicking behavior are measured on AA6061 and Ti-6Al-4V specimens through Scanning Electron Microscopy (SEM), X-ray Photoelectron Spectroscopy (XPS), contact angle goniometer, UV-VIS-NIR spectrometer and high-speed camera, respectively.
Characterizing the interplay between information and strength in Blotto games

In this paper, we investigate informational asymmetries in the Colonel Blotto game, a game-theoretic model of competitive resource allocation between two players over a set of battlefields. The battlefield valuations are subject to randomness. One of the two players knows the valuations with certainty. The other knows only a distribution on the battlefield realizations. However, the informed player has fewer resources to allocate. We characterize unique equilibrium payoffs in a two battlefield setup of the Colonel Blotto game. We then focus on a three battlefield setup in the General Lotto game, a popular variant of the Colonel Blotto game. We characterize unique equilibrium payoffs and quantify the value of information - the difference in equilibrium payoff between the asymmetric information game and complete information game. Though information can never give a weaker player the competitive advantage when there are only two battlefields, three battlefields offers sufficient complexity such that it is possible.
Children’s Capacities and Paternalism

Paternalism is widely viewed as presumptively justifiable for children but morally problematic for adults. The standard explanation for this distinction is that children lack capacities relevant to the justifiability of paternalism. I argue that this explanation is more difficult to defend than typically assumed. If paternalism is often justified when needed to keep children safe from the negative consequences of their poor choices, then when adults make choices leading to the same negative consequences, what makes paternalism less justified? It seems true that ordinary adults have capacities enabling them to promote their interests in ways most children lack. This can explain why paternalism is more often justified towards children than adults. What is not explained, however, is why paternalism would be justifiable for children, but not adults, when neither possess the relevant interest-promoting capacities—exactly the cases when paternalism towards adults might be considered. I argue that this dilemma undercuts capacities-based explanations for the belief that childhood is distinctively relevant for the permissibility of paternalism. I then address defenses of both consequentialist and deontological versions of the capacities-based explanation. Absent this capacities-based explanation, I argue that the intuition that less demanding justificatory standards apply to paternalism when directed at children than when directed towards adults presents unresolved problems for egalitarians.
A Re-Solving Heuristic with Uniformly Bounded Loss for Network Revenue Management

We consider a canonical quantity-based network revenue management problem where a firm accepts or rejects incoming customer requests irrevocably in order to maximize expected revenue given limited ...
Conformal Dirac Structures

The Courant bracket defined originally on the sections of a vector bundle TM⊕T * M→M is extended to the direct sum of the 1-jet vector bundle and its dual. The extended bracket allows one to interpret many structures encountered in differential geometry, in terms of Dirac structures. We give here a new approach to conformal Jacobi structures.
Performance evaluation of packet data services over cellular voice networks

In this paper we develop a Markov chain modeling framework for throughput/delay analysis of data services over cellular voice networks, using the dynamic channel stealing method. Effective approximation techniques are also proposed and verified for simplification of modeling analysis. Our study identifies the average voice call holding time as the dominant factor to affect data delay performance. Especially in heavy load conditions, namely when the number of free voice channels becomes momentarily less, the data users will experience large network access delay in the range of several minutes or longer on average. The study also reveals that the data delay performance deteriorates as the number of voice channels increases at a fixed voice call blocking probability, due to increased voice trunking efficiency. We also examine the data performance improvement by using the priority data access scheme and speech silence detection technique.
Long monochromatic paths and cycles in 2-colored bipartite graphs

Abstract Gyarfas and Lehel and independently Faudree and Schelp proved that in any 2-coloring of the edges of K n , n there exists a monochromatic path on at least 2 ⌈ n ∕ 2 ⌉ vertices, and this is tight. We prove a stability version of this result which holds even if the host graph is not complete; that is, for every γ ≫ η > 0 and n ≥ n 0 ( γ ) , if G is a balanced bipartite graph on 2 n vertices with minimum degree at least ( 3 ∕ 4 + γ ) n , then in every 2-coloring of the edges of G , either there exists a monochromatic cycle on at least ( 1 + η ) n vertices, or the coloring of G is close to an extremal coloring — in which case G has a monochromatic path on at least 2 ⌈ n ∕ 2 ⌉ vertices and a monochromatic cycle on at least 2 ⌊ n ∕ 2 ⌋ vertices. Furthermore, we determine an asymptotically tight bound on the length of a longest monochromatic cycle in a 2-colored balanced bipartite graph on 2 n vertices with minimum degree δ n for all 0 ≤ δ ≤ 1 .
Entropy based analysis of vertebrate sperm protamines sequences: evidence of potential dityrosine and cysteine-tyrosine cross-linking in sperm protamines.

Spermatogenesis is the process by which germ cells develop into spermatozoa in the testis. Sperm protamines are small, arginine-rich nuclear proteins which replace somatic histones during spermatogenesis, allowing a hypercondensed DNA state that leads to a smaller nucleus and facilitating sperm head formation. In eutherian mammals, the protamine-DNA complex is achieved through a combination of intra- and intermolecular cysteine cross-linking and possibly histidine-cysteine zinc ion binding. Most metatherian sperm protamines lack cysteine but perform the same function. This lack of dicysteine cross-linking has made the mechanism behind metatherian protamines folding unclear. Protamine sequences from UniProt’s databases were pulled down and sorted into homologous groups. Multiple sequence alignments were then generated and a gap weighted relative entropy score calculated for each position. For the eutherian alignments, the cysteine containing positions were the most highly conserved. For the metatherian alignment, the tyrosine containing positions were the most highly conserved and corresponded to the cysteine positions in the eutherian alignment. High conservation indicates likely functionally/structurally important residues at these positions in the metatherian protamines and the correspondence with cysteine positions within the eutherian alignment implies a similarity in function. One possible explanation is that the metatherian protamine structure relies upon dityrosine cross-linking between these highly conserved tyrosines. Also, the human protamine P1 sequence has a tyrosine substitution in a position expecting eutherian dicysteine cross-linking. Similarly, some members of the metatherian Planigales genus contain cysteine substitutions in positions expecting plausible metatherian dityrosine cross-linking. Rare cysteine-tyrosine cross-linking could explain both observations.
Chapter 11 – Larderello Dry-Steam Power Plants, Tuscany, Italy

The case studies section of this book begins at the birthplace of geothermal energy as a source of electricity—Larderello, Italy. It was here in this Tuscan village in 1904 that Prince Piero Ginori Conti fashioned the first electromechanical device that converted the energy of the indigenous steam, issuing from the earth for centuries, into electricity—enough to illuminate five light bulbs in his boric acid factory.
Constructing two-qubit gates with minimal couplings

Couplings between quantum systems are frequently less robust and harder to implement than controls on individual systems; thus, constructing quantum gates with minimal interactions is an important problem in quantum computation. In this paper we study the optimal synthesis of two-qubit quantum gates for the tunable coupling scheme of coupled superconducting qubits and compute the minimal interaction time of generating any two-qubit quantum gate.
Does Ethnicity Pay? Evidence from Overseas Chinese FDI in China

Most of the economic analyses of the overseas Chinese network focus on trade and investment flows at the country level. In this paper, we analyze the effects of the ethnic Chinese network at the firm level. Contrary to the conventional wisdom, we find that ethnic Chinese FDI firms in China in fact underperform nonethnic Chinese FDI firms. We also find that the performance of ethnic Chinese firms deteriorates over time. We present evidence consistent with the hypothesis that ethnic Chinese firms underinvest in those firm attributes that may contribute to long-term performance, such as human capital and technology. Our findings raise both empirical and normative implications of ethnic ties.
Multiagent learning in large anonymous games

In large systems, it is important for agents to learn to act effectively, but sophisticated multi-agent learning algorithms generally do not scale. An alternative approach is to find restricted classes of games where simple, efficient algorithms converge. It is shown that stage learning efficiently converges to Nash equilibria in large anonymous games if bestreply dynamics converge. Two features are identified that improve convergence. First, rather than making learning more difficult, more agents are actually beneficial in many settings. Second, providing agents with statistical information about the behavior of others can significantly reduce the number of observations needed.
Chapter 17 – Frogs

Frogs and toads (Anura) are unmistakable with their unique short, tailless bodies; broad, flat heads with big mouths; and long, muscular hindlimbs. Frogs and toads occur worldwide on all continents except Antarctica and on most continental islands. They are a diverse group with over 6200 species distributed in 49 families. Taxonomic status of frogs is under continual revision as more species are described and technology and analytical methods improve. Frogs and toads live in most aquatic and terrestrial habitats from lowlands to mountaintops. Conservation status of frogs is summarized. An up-to-date phylogeny details approximate time periods during which divergences occurred during the evolutionary history of frogs and shows evolutionary relationships among the families as we now know them. Taxonomic accounts provide information on generic content, distribution, characteristics, and biology of each family.
2 – Parabolic Equations

Publisher Summary This chapter discusses the properties of parabolic equations. Problems considered are usually assumed to be properly posed from the outset. Existence and uniqueness are usually ensured under physically reasonable assumptions such as those of piecewise differentiability of coefficients and initial data. Parabolic partial differential equations arising in scientific and engineering problems are often of the form u1 = L, where L is a second-order elliptic partial differential operator that may be linear or nonlinear. Diffusion in an isotropic medium, heat conduction in an isotropic medium, fluid flow through porous media, boundary layer flow over a flat plate, persistence of solar prominences, and the wake growth behind a submerged object have been modeled by the parabolic equation. An explicit formula provides for a noniterative marching process for obtaining the solution at each present point in terms of known preceding and boundary values. As parabolic equations characteristically have open integration domains, explicit methods are applicable to these problems.
Chapter 7 – Distributions of Sampling Statistics

We introduce the concept of sampling from a population distribution. The sample mean and sample variance are studied, and their expectations and variances are given. The central limit theorem is presented and applied to show that the distribution of the sample mean is approximately normal.
2 – The Fungi

Publisher Summary Fungi decompose dead plants and animals and recycle essential minerals back into the soil for reuse by other growing plants. Fungi are important industrially in the production of antibiotics, cheeses, wines, and a large number of other products. Fungi are also the most commonly encountered group of plant pathogens. The species of fungi that can attack woody plants are the major concern for those working with the shade trees. This chapter discusses the methods of identification of fungi that cause tree diseases. The identification of fungi is a complex process that requires the microscopic examination and an extensive knowledge of the taxonomy of the fungi. It is the duty of the shade tree specialist to know when to submit the samples, what tree tissues are needed in the samples for the particular case, and how to collect and ship the samples of diseased plant materials to the plant disease diagnostician for identification. Trees respond to the attacks of fungi and other infectious pathogens by placing barriers in front of the invading microorganisms, thus attempting to limit the amount of infected tissue.
The condition number of a function relative to a set

The condition number of a differentiable convex function, namely the ratio of its smoothness to strong convexity constants, is closely tied to fundamental properties of the function. In particular, the condition number of a quadratic convex function is the square of the aspect ratio of a canonical ellipsoid associated to the function. Furthermore, the condition number of a function bounds the linear rate of convergence of the gradient descent algorithm for unconstrained convex minimization. We propose a condition number of a differentiable convex function relative to a reference convex set and distance function pair. This relative condition number is defined as the ratio of relative smoothness to relative strong convexity constants. We show that the relative condition number extends the main properties of the traditional condition number both in terms of its geometric insight and in terms of its role in characterizing the linear convergence of first-order methods for constrained convex minimization. When the reference set X is a convex cone or a polyhedron and the function f is of the form $$f = g\circ A$$ , we provide characterizations of and bounds on the condition number of f relative to X in terms of the usual condition number of g and a suitable condition number of the pair (A, X).
16 – Biological effects of radiation

Publisher Summary This chapter describes the biological effect of radiation on cells, tissues, organs, and individuals. The units of measurement of radiation and its effect are identified, and the philosophy and practice of setting limits on exposure are reviewed. When radiation interacts with biological tissue, energy is deposited and ionization takes place that causes damage to cells. The most important point from the biological standpoint is that the bombarding particles have energy, which can be transferred to atoms and molecules of living cells that cause disruptive effect on their normal function. Since an organism is composed of very many cells, tissues, and organs, a disturbance of one atom is likely to be imperceptible, but exposure to many particles or rays can alter the function of a group of cells and thus affect the whole system. It is usually assumed that damage is cumulative, even though some accommodation and repair takes place. The effect on organisms is somatic, related to body health, and genetic, related to inherited characteristics. Radiation dose equivalent as a biologically effective energy deposition per gram is usually expressed in rems, with natural background giving about 0.36 rem/y. Exposure limits are set by use of data on radiation effects at high dosages with a conservative linear hypothesis applied to predict effects at low dose rates.
Studying cytoskeletal dynamics in living cells using green fluorescent protein.

Microfilaments, intermediate filaments, and microtubules are three major cytoskeletal systems providing cells with stability to maintain proper shape. Although the word “cytoskeleton” implicates rigidity, it is quite dynamic exhibiting constant changes within cells. In addition to providing cell stability, it participates in a variety of essential and dynamic cellular processes including cell migration, cell division, intracellular transport, vesicular trafficking, and organelle morphogenesis. During the past eight years since the green fluorescent protein (GFP) was first used as a marker for the exogenous gene expression, it has been an especially booming era for live cell observations of intracellular movement of many proteins. Because of the dynamic behavior of the cytoskeleton in the cell, GFP has naturally been a vital part of the studies of the cytoskeleton and its associated proteins. In this article, we will describe the advantage of using GFP and how it has been used to study cytoskeletal proteins.