cssi/SciSciGPT-SciSciNet huggingface dataset:
Electromagnetic properties of multiphase composites containing barium strontium titanate and nickel zinc ferrite inclusions from 1-4 GHz

Abstract The growing importance of nonlinear transmission lines for pulsed power and high power microwave devices in defense and industrial applications motivates material development for system optimization. This study investigates composites manufactured with various volume loadings of both nonlinear magnetic (nickel zinc ferrite) and dielectric (barium strontium titanate) inclusions in a silicone matrix. Increasing the volume fraction of barium strontium titanate (BST) and nickel zinc ferrite (NZF) increased the permittivity with a stronger dependence on BST volume fraction. Increasing NZF volume fraction increased the magnetic permeability, while changing BST volume fraction had no effect. The DC dielectric breakdown voltage decreased exponentially with increased NZF volume fraction. Adding as little as 5% BST to an NZF composite more than doubled the breakdown threshold compared to a composite containing NZF alone. For example, adding 10% BST to a 15% NZF composite increased the breakdown strength by over 800%. The combination of tunability of permittivity and permeability by managing BST and NZF volume fractions with the increased dielectric breakdown strength by introducing BST make this a promising approach for designing high power nonlinear transmission lines with input pulses of hundreds of kilovolts.
The Geological Unconscious: German Literature and the Mineral Imaginary, by Jason Groves, New York, Fordham University Press, 2020, 208 pp., ISBN 978-0823288106

The Geological Unconscious: German Literature and the Mineral Imaginary grapples with the problem of representing various lithic materials in distinct moments of time from the mines of nineteenth-c...
Mild cognitive impairment, dementia and risk of mortality in essential tremor: A longitudinal prospective study of elders.

Abstract Background There is evidence that the risk of mortality is increased in patients with essential tremor (ET), however, there are few longitudinal, prospective data on the predictors of mortality in ET. There is also evidence that ET is associated with cognitive impairment; yet, it is unknown whether this is associated with elevated risk of mortality. Methods In a longitudinal, prospective study of 194 elders with ET, an extensive neuropsychological test battery was performed at three time points: baseline, 18 months, and 36 months, and cognitive diagnoses (normal, mild cognitive impairment [MCI], and dementia) were assigned during consensus conferences. We used Cox proportional hazards models to estimate hazard ratios (HR) for death. Results The mean baseline age was 79.1 ± 9.7 years. During follow-up, 52 (26.8%) died. In initial univariate models, a variety of baseline factors were associated with increased risk of mortality, including demographic variables (i.e., older age), cognitive variables and gait and balance variables. In the final multivariate Cox model, baseline dementia (HR = 2.66, p = 0.006), older baseline age (HR = 1.18, p Conclusions In this longitudinal, prospective study, baseline dementia resulted in a 2- to 3-times increase in risk of mortality in ET, further highlighting the clinical significance of cognitive impairment, specifically dementia, in this population.
Principles for the 2020 Surface Transportation Reauthorization

America’s surface transportation infrastructure needs significant improvements and rehabilitation, yet Congress is uncertain about how to do this. Some want to significantly increase federal spending on infrastructure. Others want to end deficit financing of transportation and end federal restrictions that reduce the efficiency and effectiveness of the funds that are spent. To resolve this conundrum, this paper presents three principles that Congress should apply to a new surface transportation funding bill. These principles are pay-as-you-go, user fees, and subsidiarity. Pay-as-you-go. The Congressional Budget Office estimates that limiting transportation expenditures to actual transportation revenues, rather than relying heavily on borrowing, will reduce deficit spending by at least $116 billion over the next decade. Putting transportation on a pay-as-you-go basis will also make transportation agencies more responsive to the needs of transportation users. User fees. Congress should rely on and encourage state and local governments to rely more on user fees for transportation. This can be done by eliminating restrictions on road tolling and incorporating user fees into the formulas for distributing funds to the states. Subsidiarity. Congress should give state and local transportation agencies greater latitude in deciding how to spend their shares of federal funds. This should promote the efficient use of those funds by reallocating decisionmaking closer to voters and taxpayers. Subsidiarity includes distributing funds using formulas that divide the funds between jurisdictions, not competitive grants that often reward inefficient proposals, and using as few funds as possible — preferably two, one for highways and one for transit — rather than the two dozen funds used today. Together, these principles will increase the efficiency and effectiveness of federal transportation spending.
Failure sentinels: ubiquitous just-in-time intermittent computation via low-cost hardware support for voltage monitoring

Energy harvesting systems support the deployment of low-power microcontrollers untethered by constant power sources or batteries, enabling long-lived deployments in a variety of applications previously limited by power or size constraints. However, the limitations of harvested energy mean that even the lowest-power microcontrollers operate intermittently---waiting for the harvester to slowly charge a buffer capacitor and rapidly discharging the capacitor to support a brief burst of computation. The challenges of the intermittent operation brought on by harvested energy drive a variety of hardware and software techniques that first enabled long-running computation, then focused on improving performance. Many of the most promising systems demand dynamic updates of available energy to inform checkpointing and mode decisions. Unfortunately, existing energy monitoring solutions based on analog circuits (e.g., analog-to-digital converters) are ill-matched for the task because their signal processing focus sacrifices power efficiency for increased performance---performance not required by current or future intermittent computation systems. This results in existing solutions consuming as much energy as the microcontroller, stealing energy from useful computation. To create a low-power energy monitoring solution that provides just enough performance for intermittent computation use cases, we design and implement Failure Sentinels, an on-chip, fully-digital energy monitor. Failure Sentinels leverages the predictable propagation delay response of digital logic gates to supply voltage fluctuations to measure available energy. Our design space exploration shows that Failure Sentinels provides 30--50mV of resolution at sample rates up to 10kHz, while consuming less than 2μA of current. Experiments show that Failure Sentinels increases the energy available for software computation by up to 77%, compared to current solutions. We also implement a RISC-V-based FPGA prototype that validates our design space exploration and shows the overheads of incorporating Failure Sentinels into a system-on-chip.
Three-loop soft anomalous dimensions in QCD

I present results for soft anomalous dimensions through three loops for many QCD processes. In particular, I give detailed expressions for soft anomalous dimensions in various processes with electroweak and Higgs bosons as well as single top quarks and top-antitop pairs.
Riverscape-Scale Modeling of Fundamentally Suitable Habitat for Mussel Assemblages in an Ozark River System, Missouri

Identifying the physical habitat characteristics associated with riverine freshwater mussel assemblages is challenging but crucial for understanding the causes of mussel declines. The occurrence of mussels in multispecies beds suggests that common physical factors influence or limit their occurrence. Fine-scale geomorphic and hydraulic factors (e.g., scour, bed stability) are predictive of mussel-bed occurrence, but they are computationally challenging to represent at intermediate or riverscape scales. We used maximum entropy (MaxEnt) modeling to evaluate associations between riverscape-scale hydrogeomorphic variables and mussel-bed presence along 530 river km of the Meramec River basin, USA, to identify river reaches that are fundamentally suitable for mussels as well as those that are not. We obtained the locations of mussel beds from an existing, multiyear dataset, and we derived river variables from high-resolution, open-source datasets of aerial imagery and topography. Mussel beds occurred almost exclusively in reaches identified by our model as suitable; these were characterized by laterally stable channels, absence of adjacent bluffs, proximity to gravel bars, higher stream power, and larger areas of contiguous water (a proxy for drought vulnerability). We validated our model findings based on model sensitivity using a set of mussel-bed locations not used in model development. These findings can inform how resource managers allocate survey, monitoring, and conservation efforts.
Monitoring tools and numerical models for evaluation of monitored natural attenuation of explosives at selected sites

As part of the natural attenuation study and long- term monitoring of explosives, new types of direct push technologies (DPT) that allow direct detection of contamination, without bringing soil or water samples to the surface for analysis, have been developed in recent years. The DPT has been used to provide data to a multi-objective project conducted at two contaminated sites. The DPT also provided samples for microbiological studies and stratigraphic analysis of lithologies for the numerical modeling effort. The main objective of the modeling work was to assist field monitoring and data collection for a better demonstration and graphic representation of natural attenuation of explosives. The study has shown that the DPT is an effective tool for sampling both soil and water in varying geologic environments of deposition. DPT technology provided a cost-effective means of providing real-time data concerning the stratigraphy, resistivity and ground water contamination of the sites. The ground water modeling system (GMS) was used to simulate flow and mass transport of contaminants of concern (TNT, RDX) at the sites. Modeling runs for LAAP indicated that the TNT and RDX plumes are static and possibly slowly diminishing
Bayesian nonparametric inverse reinforcement learning

Inverse reinforcement learning (IRL) is the task of learning the reward function of a Markov Decision Process (MDP) given the transition function and a set of observed demonstrations in the form of state-action pairs. Current IRL algorithms attempt to find a single reward function which explains the entire observation set. In practice, this leads to a computationally-costly search over a large (typically infinite) space of complex reward functions. This paper proposes the notion that if the observations can be partitioned into smaller groups, a class of much simpler reward functions can be used to explain each group. The proposed method uses a Bayesian nonparametric mixture model to automatically partition the data and find a set of simple reward functions corresponding to each partition. The simple rewards are interpreted intuitively as subgoals, which can be used to predict actions or analyze which states are important to the demonstrator. Experimental results are given for simple examples showing comparable performance to other IRL algorithms in nominal situations. Moreover, the proposed method handles cyclic tasks (where the agent begins and ends in the same state) that would break existing algorithms without modification. Finally, the new algorithm has a fundamentally different structure than previous methods, making it more computationally efficient in a real-world learning scenario where the state space is large but the demonstration set is small.
Olfactory Nerve (Cranial Nerve I)

All animals from simple single cell organisms through to complex vertebrates detect and react to chemicals/odors in their external environment, some at concentrations of only a few parts per million. These environmental odors are generally complex mixtures of individual chemicals/odorants; coffee, for example, may contain as many as 1000 separate chemicals/odorants. The olfactory system, therefore, must be capable of detecting and identifying diverse odorant mixtures. Only the immune system surpasses the olfactory system in ability to recognize such a diverse array of molecules. Olfaction in higher animals is used for detection of food, identification of predators, kinship recognition, and mate selection. Indeed, some mammals experience severe reproductive disadvantage if their olfactory system is compromised. In recent years there have been considerable advances in our understanding of the molecular, anatomical, and neurophysiological mechanisms underlying function in the olfactory system.
A Decade of Economic Reforms in India: The Unfinished Agenda:

This paper aims to assess the economic reforms in India undertaken during the 1990s. India has gone through the first decade of her reform process. Hence, an assessment of what has been achieved so...
An Evaluation of the Invariance Properties of a Biologically-Inspired System for Unconstrained Face Recognition

A key challenge in building face recognition systems — biologically-inspired or otherwise — is evaluating performance. While much of face recognition research has traditionally used posed photographs for evaluation, recent efforts have emerged to build more naturalistic, unconstrained test sets by collecting large numbers of face images from the internet (e.g. the “Labeled Faces in the Wild”(LFW) test set [1]). While such efforts represent a large step forward in the direction of realism, the nature of posed photographs from the internet arguably represents an incomplete sampling of the range of variation in view, lighting, etc. found in the real world. Here, we evaluate a family of large-scale biologically-inspired vision algorithms that has previously proven to perform well on a variety of object and face recognition test sets [2], and show that members of this family perform at a level of performance that is comparable with current state-of-the-art approaches on the LFW challenge. As a counterpoint to internet-photo based approaches, we use synthetic (rendered) face images where the amount of view variation is controllable and known by design. We show that while there is gross agreement between the LFW benchmark and synthetic benchmarks, the synthetic benchmarks reveal a substantially greater degree of tolerance to view variation than is apparent from the LFW benchmark in models containing deeper hierarchies. Furthermore, such an approach yields important insights into which axes of variation are most challenging. These results suggest that parametric synthetic benchmarks can play an important role in guiding the progress of biologically-inspired vision systems.
Nematic-Substrate Interaction and the Boundary Layer Phase Transition

Substrate alignment of liquid crystals is an essential element in the functioning of a liquid crystal display device. While the primary role of the treated substrate is to anchor the nematic director at the solid-liquid crystal interface in some pre-designed manner, it has been pointed out in an earlier work1 that if a similar anchoring effect exists for the orientational order parameter S, then the substrate would also induce a boundary layer, extending about 1000 A from the substrate, within which the orientational order can be significantly different from that of the bulk. In particular, this would mean that the liquid crystal molecules in the vicinity of the substrate can possess a finite degree of orientational ordering even when the bulk is isotropic -- a property whose experimental utilization led eventually to the observation of this surface-induced effect.2
Characterization of the viscous behavior of compacted ceramic particles under shear and pressure loads

Ceramic armors are known to provide excellent ballistic resistance, but the precise mechanisms of projectile defeat in these systems are not fully understood. A critical stage in the penetration process is the flow of the pulverized ceramic past the projectile. To further understand this phenomenon, we are investigating the flow and energy dissipation of granular beds, specifically under conditions of high pressure. Two different viscometer systems are designed and fabricated to characterize the behavior of ceramic particles under shear stress and high pressures. The first system is a Couette flow device with ability to exert pressure on the particles during its rotation and measure the torque and angular velocity of the system. These data are used to extract viscosity and energy dissipation due to friction between particles as a function of the shear rate. The second system focuses on the movement of a cylinder through a bed of compacted ceramic particles. By measuring the force required to move the cylinder through the compacted bed, we can evaluate the effective resistance of the particle bed under various compaction pressures. By characterizing the friction coefficient, we obtain the apparent viscosity of the compacted granules under different pressure loads for low strain rates. This characterization should prove useful in understanding the shearing and dissipation mechanisms between granular particles under high pressures.© 2003 ASME
Mandates and the Incentive for Environmental Innovation

Mandates, which establish minimum use quotas for certain goods, are becoming increasingly popular policy tools to promote renewable energy use. In addition to mitigating the pollution externality of conventional energy, clean energy mandates have the goal of promoting research and development (R&D) investments in renewable energy technology. But how well do mandates perform as innovation incentives? To address this question, we develop a partial equilibrium model to examine the R&D incentives induced by a mandate, and compare this policy to two benchmark situations: laissez faire and a carbon tax. Innovation is stochastic and the model permits an endogenous number of multiple innovators. We present both analytical results and conclusions based on numerical simulations. We find that the optimal mandate is larger than it would be without the prospect of innovation, that neglecting the outlook for innovation significantly reduces welfare, and that the optimal mandate is more sensitive to assumptions about the innovation process than an optimal carbon tax. Furthermore, we find that mandates create relatively strong incentives for R&D investment in low-quality innovations, but relatively weak incentives to invest in high-quality innovations. We also rank policies by expected welfare. An optimal carbon tax has higher expected welfare than an optimal mandate, and both have higher expected welfare than laissez faire. Moreover, in our endogenous innovation setting, a stronger result obtains: a simple carbon tax equal to the damage from pollution (unadjusted for the prospect of innovation) has higher expected welfare than an optimal mandate.
Computerized physician order entry and communication: reciprocal impacts.

Participant observation, focus group and oral history techniques were used to collect data from four distinctly different sites across the U.S. Data were examined initially to identify success factors for computerized physician order entry (CPOE) implementation. These data, reexamined for communication issues, revealed significant impacts on communication channels and relationships unanticipated by the implementers. Effects on physician-nurse interactions, pharmacy roles, and patient communications that vary by time and location were noted. The importance of robust bi-directional information channels between administration and staff was demonstrated to be potentially "mission-critical." The recommendation for implementers is "Plan to be surprised." Careful planning and pre-work are important but, no matter how much an institution prepares for the upheaval of CPOE, unforeseen consequences are inevitable. The presence of a prepared and capable implementation support group is essential.
Estimating Cotton Harvest Cost per Acre When Harvest Days are Stochastic

The cotton harvesting industry is in the beginnings of its next technological advance, cotton harvesters that form cotton modules inside the machine then deposit them off the rows. These new machines eliminate the need for extra labor and equipment, but are more expensive than conventional pickers. Increased field efficiency is also a benefit of the on-board module builders. The problem facing producers is determining the optimal number of acres to plan for harvest when trying to decide which harvester to purchase. This paper examines two objectives. First, determine the cost per acre of both conventional and on-board module harvester systems for different acreage levels assuming harvest hours per year are fixed. Second, make the harvest hours per season stochastic to determine the cost per acre under different farm sizes for each type of cotton picker. The results show that the maximum benefits of the new machines are realized with larger farms when a larger number of acres need to be harvested in the harvest period. Results should help farmers plan both their cotton acre estimates as well as their purchase decisions for new cotton pickers.
The Changing Economic Model of Scholarly Publishing: Uncertainty, Complexity and Multi-media Serials.

Scholarly publishing is undergoing a transformation that affects every participant in the information chain. Serials used to be a relatively uncomplicated activity, driven by the need of scholars and researchers to publish (see Fig 1). Until the 1980s, libraries found it possible to maintain coherent collections of the journals required to serve the teaching and research needs of their individual institutions, albeit at the expense of their monograph collections. Since that time, both journal price inflation and the growth in the number of journals and the numbers of papers published have outstripped the ability of even the most lavishly funded library to purchase what faculty and students demand. At the same time, modern technology has, in the last few years, offered us the opportunity to develop new media of distribution for scholarly literature: media that offer the researcher
Iterative Proportional Fitting

Iterative proportional fitting, also known as iterative proportional scaling, is an algorithm for constructing tables of numbers satisfying certain constraints. In its simplest form, the algorithm enables one to construct two-way tables with specified row and column margins and prescribed association, measured by a family of cross-ratios. The algorithm can be used to obtain maximum likelihood estimates of table entries under hierarchical loglinear models, and it can be used to adjust counts in survey sampling, where it is known as raking. Natural extensions exist to three and higher-way tables, and to more general exponential families. Keywords: cross-ratio; hierarchical loglinear model; marginals; interactions; I-divergence
Fiscal and Generational Imbalances: An Update

This paper provides an update of the U.S. fiscal and generational imbalances that we originally calculated in Gokhale and Smetters (2003) and presents the calculations in several alternative ways. We find that a lot has changed in just a few years. In particular, the nation's fiscal imbalance has grown from around $44 trillion as of fiscal year-end 2002 to about $63 trillion, mostly due to the recent adoption of the prescription drug bill (Medicare, Part D). The imbalance also grows by more than $1.5 trillion (in inflation adjusted terms) each year that action is not taken to reduce it. This imbalance now equals about 8 percent of all future gross domestic product (GDP) and it could, in theory, be eliminated by more than doubling the employer-employee payroll tax from 15.3 percent of wages to over 32 percent immediately and forever--assuming, quite critically, no reduction in labor supply or national saving and capital formation. Massive cuts in government spending would also be required to achieve fiscal...
The Economic Impact of Fruit and Vegetable Production in Southwest Iowa Considering Local and Nearby Metropolitan Markets

Rural producers are interested in developing income enhancing opportunities. Increased, in-season production of fresh fruits and vegetables fro local or regional consumption is one farm-level opportunity. This study looks at a 12 county region and evaluates the production-driven income gains that could be anticipated from increased local fruit and vegetable production of local consumption, as well as increased production to satisfy the demand of two major metropolitan markets that exist outside of the primary production region.
Lord's Paradox

Frederic Lord presents a statistical paradox regarding the analysis of pre-post data often used in program evaluation. His paradox cast doubt on the value of certain uses of the analysis of covariance. The resolution of the paradox requires careful attention to the ambiguity of the implicit causal questions that underlie it. Keywords: control group; treatment; gain scores; Neyman–Rubin model; regression; analysis of covariance
Evaluating marketing channel options for small-scale fruit and vegetable producers.

An analytical framework and ranking system is developed to summarize the primary factors affecting marketing channel performance and to prioritize those channels with the greatest opportunity for success. An application of the model is conducted using case-study evidence from four small-scale diversified vegetable crop producers in Central New York. The relative costs and benefits of alternative wholesale and direct marketing channels are investigated, including how the factors of risk, owner and paid labor, profits, lifestyle preferences and sales volume interact to impact optimal market channel selection. Given the highly perishable nature of the crops grown, along with the risks and potential sales volume of particular channels, a combination of different marketing channels is needed to maximize overall firm performance.
Music, New Aesthetic and Complexity

This paper illustrates an algorithm to generate a complex acoustic stimulus whose statistical properties are as close as possible to the non-stationary dynamics revealed by the current analysis of the electro-encephalogram activity of the human brain. Thus, the composition is driven by crucial events, namely renewal non-Poisson events with an inter-time distribution density ψ(τ), which is an inverse power law with index μ, fitting the condition 1 ≤ μ ≤ 2. We find that the music composition is more attractive when we fill the time region between two consecutive crucial events so as to enhance the leading role of μ. In all cases the spectra markedly depart from the ideal 1/f condition, thereby suggesting a shift from the 1/f noise perspective of the pioneer work of Voss and Clark to the Zipf’s law perspective advocated by more recent work on music composition.
Subgame Perfect Correlated Equilibria in Repeated Games

This paper investigates discounted in…nitely repeated games with observable actions extended with an extensive form correlation device. Such games model situations of repeated interaction of many players who choose their individual actions conditional on both public and private information. A number of characterizations of the set of sub
Intra-amniotic infusion of bicarbonate in the treatment of human fetal acidosis.

Abstract At the time of cesarean section with the use of spinal anesthesia, 40 to 100 mEq. of sodium bicarbonate was infused into the amniotic cavities of 11 near-term pregnant women, the majority of whom had special complications. Eleven other near-term pregnant women served as controls. Five patients in the treated group developed post-spinal-block hypotension, as did 5 patients in the untreated group. All hypotensive episodes were treated by acute hydration. An equilibration period of 15 to 20 minutes was allowed between sodium bicarbonate infusion and delivery. Mean umbilical arterial base excess of the treated group was significantly greater than that of the untreated group (−7.0 vs. −10.9 mEq. per liter, p
Learning for semantic interpretation: scaling up without dumbing down

Most recent researchin learning approaches to natural language have studied fairly "low-level" tasks such as morphology, part-ofspeechtagging, and syntactic parsing. However, I believe that logical approaches may have the most relevance and impact at the level of semantic interpretation, where a logical representation of sentence meaning is important and useful. We have explored the use of inductive logic programming for learning parsers that map natural-language database queries into executable logical form. This work goes against the growing trend in computational linguistics of focusing on shallow but broad-coverage natural language tasks ("scaling up by dumbing down") and instead concerns using logic-based learning to develop narrower, domain-specific systems that perform relatively deep processing. I first present a historical view of the shifting emphasis of research on various tasks in natural language processing and then briefly review our own work on learning for semantic interpretation. I will then attempt to encourage others to study such problems and explain why I believe logical approaches have the most to offer at the level of producing semantic interpretations of complete sentences.
The Need for Fast Communication in Hardware-Based Speculative Chip Multiprocessors

Chip-multiprocessor (CMP) architectures are a promising design alternative to exploit the ever-increasing number of transistors that can be put on a die. To deliver high performance on applications that cannot be easily parallelized, CMPs can use additional support for speculatively executing the possibly data-dependent threads of an application. For cross-thread dependences that must be handled dynamically, the threads can be made to synchronize and communicate either at the register level or at the memory level. In the past, it has been unclear whether the higher hardware cost of register-level communication is cost-effective. In this paper, we show that the wide-issue dynamic processors that will soon populate CMPs, make fast communication a requirement for high performance. Consequently, we propose an effective hardware mechanism to support communication and synchronization of registers between on-chip processors. Our scheme adds enough support to enable register-level communication without specializing the architecture toward speculation much. Finally, our scheme allows the system to achieve near ideal performance.
The Economic Impact of Milk Production on the Wisconsin Economy

The intent of this study is to introduce and report a new method for assessing the economic impact of milk production on the Wisconsin economy. Previous agricultural impact studies have used methods with inherent lags in the timing of the relevant data. In addition, previous studies treated dairy farms as a single entity and did not separate out milk production. Dairy farms are multi-product firms producing milk, cull cows for meat as well as crops. This study focuses on just milk production. By using current annual data from the Wisconsin Agricultural Statistics a more timely analysis is provided. In addition an annual moving average of production levels is used to minimize the role of yearly fluctuate.
Efficient cryptographic protocols realizing e-markets with price discrimination

Perfect (or “first degree”) Price Discrimination is a standard economic practice that is used to increase the pricing effectiveness over a diverse population of prospective buyers. It is done by selling to different buyers at different prices based on their respective willingness to pay. While the strategy achieves Pareto efficiency, there are a number of problems in realizing and giving incentive to buyers to participate (and stay) in a market with price discrimination. This is especially true in an open process (like Internet commerce), where parties may learn about their price's individual standing (within the group of buyers) and may withdraw due to being relatively “over-charged” or may “resell” due to getting the goods at a relatively low price. We investigate the difficulties of realizing perfect price discrimination markets when full information is available to the participants even under the assumption of using standard cryptographic techniques. We then propose a “fair solution” for price discrimination in e-markets: using efficient cryptographic protocols (much more efficient than secure function evaluation protocols) we give incentives to users to stay in a market that utilizes price discrimination. Our protocols assure that the seller obtains the total revenue it expects and no buyer learns the price of other buyers. In addition, each buyer gets a “fair” discount off the surplus (the accumulated suggested payments by buyers minus the seller's expected revenue) when applicable and the seller may get part of the surplus as well. Further, the seller gets to learn the market “willingness to pay” (for potential future use), while this knowledge does not affect the pricing of the current e-market instance. Along the way we investigate the cryptographic primitive of “robust distributed summation” that may be of independent interest as a protocol construction.
Causal inference in the presence of latent variables and selection bias

We show that there is a general, informative and reliable procedure for discovering causal relations when, for all the investigator knows, both latent variables and selection bias may be at work. Given information about conditional independence and dependence relations between measured variables, even when latent variables and selection bias may be present, there are sufficient conditions for reliably concluding that there is a causal path from one variable to another, and sufficient conditions for reliably concluding when no such causal path exists.
Process, structure and modularity in reasoning with uncertainty

Abstract Computational mechanisms for uncertainty management must support interactive and incremental problem formulation, inference, hypothesis testing, and decision making. however, most current uncertainty inference systems concentrate primarily on inference, and provide no support for the larger issues. We present a computational approach to uncertainty management which provides direct support for the dynamic, incremental aspect of this task, while at the same time permitting direct representation of the structure of evidential relationships. At the same time, we show that this approach responds to the modularity concerns of Heckerman and Horvitz [Heck87]. This paper emphasizes examples of the capabilities of this approach. Another paper [D'Am89] details the representations and algorithms involved.
Energy-economy interactions in Mexico: A multiperiod general equilibrium model

Abstract A multisector, multiperiod linear programming model is constructed to analyze the interactions of energy and economic policy issues in Mexico. Using piece-wise linear approximations, the model embodies non-linear substitution possibilities between alternative technologies within sectors, between foreign borrowing in successive time periods, between the rate of oil extraction and reserve depletion and in consumption and trade patterns. Complete intertemporal efficiency is achieved as compared to the temporally myopic feature of conventional computable general equilibrium models. Alternative solutions suggest that production restraint to help stabilize oil prices may have had significant costs to Mexico and that imposition of a debt ceiling could create infeasible conditions, without significant changes in behavioural relations.
Matching reforms to institutional realities : a framework for assessing social service delivery reform strategies in developing countries

The paper is based on the premise that effective institutional reforms for service delivery require a carefully-considered institutional "fitting" process as opposed to transplantation of "international best practices." The paper asks how the specific institutional contexts of a given country limit options for service delivery reforms, and therefore how a feasible set of reform options may vary systematically across countries.
IS NEW YORK CITY STILL PROPELLING GROWTH IN ITS SUBURBS?: A STUDY OF ECONOMIC SPILLOVER EFFECTS THROUGH SPATIAL CONTIGUITY *

In this paper I investigate from a strict efficiency perspective whether or not New York City’s suburbs should be helping the city in its economic development efforts. By analyzing metropolitan New York City, I am able to take advantage of the area’s spatial size and the ready availability of a pool of economic data below the metropolitan level (counties). In particular I disaggregate New York City’s economy into three sectors and the suburban geography into three rings and four radial subregions. In the case of the employment equation, national city-based industry variables tended to have expected effects on suburban economic growth when they were significant at all. Greater articulation of the geography of analysis through the inclusion of fixed effects does change the nature of these findings slightly, however. More surprising was a swing in the direction of the influence on suburban economic growth of the City’s nonfinancial nonmanufacturing sector when the analysis was performed using earnings data. This differential effect is rationalized by the City’s ability to retain high-wage service workers who reside in the suburbs.
Localization and register sharing for predicate abstraction

In the domain of software verification, predicate abstraction has emerged to be a powerful and popular technique for extracting finite-state models from often complex source code. In this paper, we report on the application of three techniques for improving the performance of the predicate abstraction refinement loop. The first technique allows faster computation of the abstraction. Instead of maintaining a global set of predicates, we find predicates relevant to various basic blocks of the program by weakest pre-condition propagation along spurious program traces. The second technique enables faster model checking of the abstraction by reducing the number of state variables in the abstraction. This is done by re-using Boolean variables to represent different predicates in the abstraction. However, some predicates are useful at many program locations and discovering them lazily in various parts of the program leads to a large number of abstraction refinement iterations. The third technique attempts to identify such predicates early in the abstraction refinement loop and handles them separately by introducing dedicated state variables for such predicates. We have incorporated these techniques into NEC's software verification tool F-Soft, and present promising experimental results for various case studies using these techniques.
The Role of Infrastructure Capital in China’s Regional Economic Growth

This paper investigates the role of infrastructure capital in China’s regional economic development during 1990 to 2009 in a neoclassical economic growth model. Four types of infrastructure capital are discussed; electricity, road, rail, and land-line telephone. The results support a positive role of infrastructure in improving economic wellbeing in China. It shows that infrastructure has contributed to the convergence among China’s provinces. However, declining growth momentum from rapid increase of road infrastructure, in particular for the Western region, suggests that road development in the region has been growing too fast. The results counter the conventional wisdom of “road leads to prosperity” widely accepted among national and local governments in China. Thus, the seemingly productive infrastructure capital, when invested beyond a proper level or speed, will become unproductive. The results resonate with the theoretical literature on the inverse U shaped growth impact of infrastructure capital and the dominant “crowding out” of private capital if there is too much infrastructure. They also address the puzzle in the current literature debates as to the direction and magnitude of the growth impact of infrastructure capital.
Information measures in detecting and recognizing symmetries

This paper presents a method to detect and recognize symmetries in Boolean functions. The idea is to use information theoretic measures of Boolean functions to detect sub-space of possible symmetric variables. Coupled with the new techniques of efficient estimations of information measures on Binary Decision Diagrams (BDDs) we obtain promised results in symmetries detection for large-scale functions.
Population matters when modeling hurricane fatalities.

Jung et al. (1) find gender bias leads to misperception of hurricane risk in both experimental and historical evidence. We affirm the rich literature on gender bias. However, we argue that Jung et al.’s empirical analysis suffers from endogeneity. Once addressed, we find the previous results to be of questionable robustness. Although gender bias may exist in limited-information experiments, historical evidence does not indicate gender bias in hurricane fatalities.
The Use of Markets To Increase Private Investment in Environmental Stewardship

U.S. farmers and ranchers produce a wide variety of commodities for food, fuel, and fiber in response to market signals. Farms also contain significant amounts of natural resources that can provide a host of environmental services, including cleaner air and water, flood control, and improved wildlife habitat. Environmental services are often valued by society, but because they are a public good - that is, people can obtain them without paying for them - farmers and ranchers may not benefit financially from producing them. As a result, farmers and ranchers underprovide these services. This report explores the use of market mechanisms, such as emissions trading and eco-labels, to increase private investment in environmental stewardship. Such investments could complement or even replace public investments in traditional conservation programs. The report also defines roles for government in the creation and function of markets for environmental services.
Hysteresis in Unemployment: Evidence from Latin America

This paper tests the hysteresis hypothesis in unemployment for 13 Latin American countries covering the period 1980-2005. The tests exploit the time series and the cross sectional variation of the series, and allows for cross section dependence and a different number of endogenously determined structural breakpoints. The findings give support to the hysteric dynamic hypothesis for the majority of the countries analyzed. The implications of the results have ramifications regarding macro-stabilization, structural reform, and the design of social safety protection.
Cognitive Moral Development and Real Estate Practitioners

In recent years, researchers in many organizational disciplines have begun to approach the study of ethics from a cognitive theoretical framework. This study has investigated the ethical reasoning of real estate practitioners using Kohlberg's cognitive moral development (CMD) approach, a potent theoretical concept with a considerable research literature. Using standardized measures of CMD on groups of Realtors® and controlling for level of education, the results of this study show that real estate practitioners compare favorably with other professional and societal groups. Further, when entered independently CMD was a significant indicator, along with education and experience, of success in real estate.
Exploring Terabyte Archives in Astronomy

Astronomy is about to undergo a major paradigm shift, with data sets becoming larger, and more homogeneous, for the first time designed in the top-down fashion. In a few years it may be much easier to “dial-up” a part of the sky, when we need a rapid observation than wait for several months to access a (sometimes quite small) telescope. With several projects in multiple wavelengths under way, like the SDSS, 2MASS, GSC-2, POSS2, ROSAT, FIRST and DENIS projects, each surveying a large fraction of the sky, the concept of having a ”Digital Sky”, with multiple, TB size databases interoperating in a seamless fashion is no longer an outlandish idea. More and more catalogues will be added and linked to the existing ones, query engines will become more sophisticated, and astronomers will have to be just as familiar with mining data as with observing on telescopes.
Quick Prototying of Multifacete Interface for Healthcare Wireless Sensor Network

This paper presents a quick prototyping of a mobile wireless sensor network (WSN) in healthcare applications that provides multiple interfaces with various access rights to different personnel involved in medical systems such as patients, healthcare providers, and system administrators. The prototype demonstrates a seamless access from constantly sensing patients’ vital signs to long term medical records stored in central database. A quick prototyping approach facilitates communications and understanding of the system requirements among the stakeholders and is a cost-effective way to build a functioning massive ubiquitous healthcare infrastructure.
IMPROVING VERTICAL AND LATERAL RESOLUTION BY STRETCH-FREE, HORIZON-ORIENTED IMAGING

The pre-stack Kirchhoff migration is implemented for delivering wavelet stretch-free imaged data, if the migration is (ideally) limited to the wavelet corresponding to a target horizon. Avoiding wavelet stretch provides long-offset imaged data, far beyond what is reached in conventional migration and results in images from the target with improved vertical and lateral resolution and angular illumination. Increasing the range of imaged offsets also increases the sensitivity to event-crossing, velocity errors and anisotropy. These issues must be addressed to fully achieve the greatest potential of this technique. These ideas are further illustrated with a land survey seismic data application in Texas, U.S.
How do adolescents spell time use

Adolescence is an important stage in a child’s deve lopment. Yet, research on adolescents has concentrated either on developmental outcomes or on risky behaviors, largely overlooking the day-to-day activities of teenagers that give rise t o these outcomes. We investigate teens’ time use using event-history methods and time-diary info rmation for nearly 2,300 15-18 year olds from the 2003-2005 American Time Use Survey and find evidence that disadvantaged teens spend time differently than do other teens. Living in a single-parent household and being behind grade-level in school both reduce time spent in sch ooling-related activities while weak labor market opportunities reduce the time teens spend in market work. The effects of household earnings and the number of adult workers in the hou sehold are found to have more complex effects.
How access to urban potable water and sewerage connections affects child mortality

Using a city-level database of global Urban Indicators, the author finds that: 1) Improved access to urban potable water and sewerage connections is consistently associated with low child mortality. 2) Government involvement in providing water services, especially locally, significantly reduces child mortality. 3) Private or parastatal participation in providing sewerage connections is associated with low child mortality. $) Rapid urban growth and high levels of poverty within the city are correlated with high child mortality.