Miracle-dz/UniFAR-FTUs huggingface dataset:
Budget Institutions and Fiscal Policy in the U.S. States

This paper summarizes state balanced budget requirements, and the available empirical evidence on the effect of these rules on state fiscal policies. Existing state rules differ from many current proposals at the federal level. They are typically restricted to part of the state budget, they frequently permit short term borrowing, and they lack formal enforcement mechanisms. The paper also surveys previous research on how anti-deficit provisions affect state fiscal policy. The available evidence indicates that stringent anti-deficit provisions lead to more rapid adjustment of state taxes and expenditures when fiscal deficits emerge. This suggests that changing the federal budget process has the potential to affect federal fiscal policy.
SODA: Sensitivity Based Optimization of Disk Architecture

Storage plays a pivotal role in the performance of many applications. Optimizing disk architectures is a design-time as well as a run-time issue and requires balancing between performance, power and capacity. The design space is large and there are many "knobs" that can be used to optimize disk drive behavior. Here we present a sensitivity-based optimization for disk architectures (SODA) which leverages results from digital circuit design. Using detailed models of the electro-mechanical behavior of disk drives and a suite of realistic workloads, we show how SODA can aid in design and runtime optimization.
A Semi-Automatic Approach for Confounding-Aware Subgroup Discovery

This paper presents a semi-automatic approach for confounding-aware subgroup discovery: Confounding essentially disturbs the measured effect of an association between variables due to the influence of other parameters that were not considered. The proposed method is embedded into a general subgroup discovery approach, and provides the means for detecting potentially confounded subgroup patterns, other unconfounded relations, and/or patterns that are affected by effect-modification. Since there is no purely automatic test for confounding, the discovered relations are presented to the user in a semi-automatic approach. Furthermore, we utilize (causal) domain knowledge for improving the results of the algorithm, since confounding is itself a causal concept. The applicability and benefit of the presented technique is illustrated by real-world examples from a case-study in the medical domain.
Multi-robot decentralized belief space planning in unknown environments via efficient re-evaluation of impacted paths

In this paper we develop a new approach for decentralized multi-robot belief space planning in high-dimensional state spaces while operating in unknown environments. State of the art approaches often address related problems within a sampling based motion planning paradigm, where robots generate candidate paths and are to choose the best paths according to a given objective function. As exhaustive evaluation of all candidate path combinations from different robots is computationally intractable, a commonly used (sub-optimal) framework is for each robot, at each time epoch, to evaluate its own candidate paths while only considering the best paths announced by other robots. Yet, even this approach can become computationally expensive, especially for high-dimensional state spaces and for numerous candidate paths that need to be evaluated. In particular, upon an update in the announced path from one of the robots, state of the art approaches re-evaluate belief evolution for all candidate paths and do so from scratch. In this work we develop a framework to identify and efficiently update only those paths that are actually impacted as a result of an update in the announced path. Our approach is based on appropriately propagating belief evolution along impacted paths while employing insights from factor graph and incremental smoothing for efficient inference that is required for evaluating the utility of each impacted path. We demonstrate our approach in a synthetic simulation.
Starting Points: Divergent Trajectories of Labor Market Integration among U.S. Lawful Permanent Residents

Abstract:Legal status is a growing dimension of inequality among immigrants in the U.S. Scholars have suggested that the legal status with which immigrants enter the country stratifies their short- and long-term opportunities for labor market integration. However, much quantitative immigration scholarship modeling the relationship between legal status and labor market integration treats legal status as static. In reality, immigrants change statuses dynamically throughout their lives. This article uses a dynamic conceptualization of legal status, as well as nationally representative data and regression and propensity score weighting techniques, to examine whether five initial legal statuses are associated with divergent labor market trajectories even after those statuses change. I find that initial legal statuses—which I refer to as starting points—are associated with ordered differences in immigrants' occupational positions immediately after immigrants change status to lawful permanent residence. These differences persist over time. Five years after all immigrants share lawful permanent residence, employment visa holders maintain more prestigious jobs; immigrants with family reunification and diversity status are in the middle; and immigrants with refugee status and undocumented experience have less prestigious jobs. This article demonstrates aggregate, longitudinal patterns of stratification among a nationally representative sample of permanent residents. The findings suggest the importance of modeling legal status as a dynamic rather than static category to reflect the continued influence of legal status starting points on immigrants' labor market integration.
Graph matching using spectral embedding and alignment

This paper describes how graph-spectral methods can be used to transform the node correspondence problem into one of point-set alignment. We commence by using the ISOMAP algorithm to embed the nodes of a graph in a low-dimensional Euclidean space. With the nodes in the graph transformed to points in a metric space, we can recast the problem of graph matching into that of aligning the points. Here, we use a variant of the Scott and Longuet-Higgins algorithm to find point correspondences. We experiment with the resulting algorithm on a number of real-world problems.
Novel modulatory effects of neurosteroids and benzodiazepines on excitatory and inhibitory neurons excitability: a multi-electrode array recording study

The balance between glutamate- and GABA-mediated neurotransmission in the brain is fundamental in the nervous system, but it is regulated by the “tonic” release of a variety of endogenous factors. One such important group of molecules are the neurosteroids (NSs) which, similarly to benzodiazepines (BDZs), enhance GABAergic neurotransmission. The purpose of our work was to investigate, at in vivo physiologically relevant concentrations, the effects of NSs and BDZs as GABA modulators on dissociated neocortical neuron networks grown in long-term culture. We used a multi-electrode array (MEA) recording technique and a novel analysis that was able to both identify the action potentials of engaged excitatory and inhibitory neurons and to detect drug-induced network up-states (burst). We found that the NSs tetrahydrodeoxycorticosterone (THDOC) and allopregnanolone (ALLO) applied at low nanomolar concentrations, produced different modulatory effects on the two neuronal clusters. Conversely, at high concentrations (1 μM), both NSs, decreased excitatory and inhibitory neuron cluster excitability; however, even several hours after wash-out, the excitability of inhibitory neurons continued to be depressed, leading to a network long-term depression (LTD). The BDZs clonazepam (CLZ) and midazolam (MDZ) also decreased the network excitability, but only MDZ caused LTD of inhibitory neuron cluster. To investigate the origin of the LTD after MDZ application, we tested finasteride (FIN), an inhibitor of endogenous NSs synthesis. FIN did not prevent the LTD induced by MDZ, but surprisingly induced it after application of CLZ. The significance and possible mechanisms underlying these LTD effects of NSs and BDZs are discussed. Taken together, our results not only demonstrate that ex vivo networks show a sensitivity to NSs and BDZs comparable to that expressed in vivo, but also provide a new global in vitro description that can help in understanding their activity in more complex systems.
The Diffusion of Organic Food Products: Toward a Theory of Adoption

This study explores drivers influencing food processors' decisions to adopt organic practices and the constraints which may limit the availability of food products using the National Organic Program (NOP) organic seal as a marketing tool. A constrained diffusion model is applied to assess seal qualified adoption across food categories. A second model explores market forces that influence variations in the diffusion process. Results suggest that external factors, including new regulation, impact diffusion rates. Future adoption of organic practices will require enhanced informational and physical access for potential adopters. © 2008 Wiley Periodicals, Inc.
Clustering Segregation with Ultraviolet Luminosity in Lyman Break Galaxies at z~3 and Its Implications

We report on the clustering properties of Lyman break galaxies (LBGs) at z ~ 3. The correlation length of flux-limited samples of LBGs depends on their rest-frame ultraviolet (UV) luminosity at λ ~ 1700 Å, with fainter galaxies being less strongly clustered in space. We have used three samples with progressively fainter flux limits: two extracted from our ground-based survey and one from the Hubble Deep Fields (both North and South). The correlation length decreases by a factor of ≈3 over the range of limiting magnitudes that we have probed, namely, 25 ≲ ℛ ≲ 27, suggesting that samples with a fainter UV luminosity limit include galaxies with smaller mass. We have compared the observed scaling properties of the clustering strength with those predicted for cold dark matter (CDM) halos and found that (1) the clustering strength of LBGs follows, within the errors, the same scaling law with the volume density as the halos; and (2) the scaling law predicted for the galaxies using the halo mass spectrum and a number of models for the relationship that maps the halos' mass into the galaxies' UV luminosity depends only on how tightly mass and UV luminosity correlate but is otherwise insensitive to the details of the models. We interpret these results as additional evidence that the strong spatial clustering of LBGs is due to galaxy biasing, supporting the theory of biased galaxy formation and gravitational instability as the primary physical mechanism for the formation of structure. We have also fitted models of the mass-UV luminosity relationship to the data to reproduce simultaneously from the CDM halo mass spectrum the dependence of the correlation length with the UV luminosity and the luminosity function. We have found that (1) a scale invariant relationship between mass and UV luminosity (e.g., a power law) is not supported by the observations, suggesting that the properties of star formation of galaxies change along the mass spectrum of the observed LBGs; (2) the scatter of the UV luminosity of LBGs of given mass must be relatively small for massive LBGs, suggesting that the mass is an important parameter in regulating the activity of star formation in these systems; and (3) the fraction of massive halos at z ~ 3 that are not observed in UV-selected surveys is not large. From the fits, for a given choice of the cosmology, one can assign a scale of mass to the LBGs. For example, if Ω = 0.3 and ΩΛ = 0.7, the average mass of galaxies with luminosity ℛ = 23, 25.5, and 27.0 is = 2.5, 0.9, and 0.4 × 1012 M☉, respectively. The numbers are ≈2 times larger and ≈10 times smaller in an open universe with Ω = 0.2 and ΩΛ = 0 and in the Einstein-de Sitter cosmologies, respectively.
Ancestry informative marker sets for determining continental origin and admixture proportions in common populations in America

To provide a resource for assessing continental ancestry in a wide variety of genetic studies, we identified, validated, and characterized a set of 128 ancestry informative markers (AIMs). The markers were chosen for informativeness, genome‐wide distribution, and genotype reproducibility on two platforms (TaqMan® assays and Illumina arrays). We analyzed genotyping data from 825 subjects with diverse ancestry, including European, East Asian, Amerindian, African, South Asian, Mexican, and Puerto Rican. A comprehensive set of 128 AIMs and subsets as small as 24 AIMs are shown to be useful tools for ascertaining the origin of subjects from particular continents, and to correct for population stratification in admixed population sample sets. Our findings provide general guidelines for the application of specific AIM subsets as a resource for wide application. We conclude that investigators can use TaqMan assays for the selected AIMs as a simple and cost efficient tool to control for differences in continental ancestry when conducting association studies in ethnically diverse populations. Hum Mutat 0,1–10, 2008. © 2008 Wiley‐Liss, Inc.
Sensors in the wild: Exploring electrodermal activity in child-robot interaction

Recent advances in biosensor technology enabled the appearance of commercial wireless sensors that can measure electrodermal activity (EDA) in user's everyday settings. In this paper, we investigate the potential benefits of measuring EDA to better understand children-robot interaction in two distinct directions: to characterize and evaluate the interaction, and to dynamically recognize user's affective states. To do so, we present a study in which 38 children interacted with an iCat robot while wearing a wireless sensor that measured their electrodermal activity. We found that different patterns of electrodermal variation emerge for different supportive behaviours elicited by the robot and for different affective states of the children. The results also yield significant correlations between statistical features extracted from the signal and surveyed parameters regarding how children perceived the interaction and their affective state.
Advanced Authentication Scheme Using a Predefined Keystroke Structure

This paper presents an advanced keystroke authentication model improving users’ validation strength. The proposed system is based on defining a keystroke structure for each authorized user, to be used in the user login attempts. This structure is composed based on two components; the user’s typing time deviation thresholds; and a unique user secret code which is distributed between password's characters based on time distances. The strength of the proposed method depends primarily on the amount of information distributed among typing time, and on reducing the deviation of these times. During the preliminary evaluation, it was confirmed that the proposed system has achieved an improved authentication level, and the system model was highly accepted between participating users.
A visualization of medical therapy plans compared to Gantt and PERT charts

Medical therapy planning shares a number of properties of project management. It is, however, different in a few very important aspects-most notably the more complex notion of time it requires. Asbru is a language that can represent medical therapy plans in terms of time-oriented, skeletal plans, but due to its formal nature, it cannot be used directly by physicians. Therefore, we developed a visualization and user interface to deal with plans defined in Asbru, which can deal with most of its complexity. We present this interface (called Asbru View), and discuss its features and advantages over the two representations typically used in project management: Gantt and PERT charts.
D ec 2 00 2 Critical behavior of the piezoresistive response in RuO 2-glass composites

We re-analyse earlier measurements of resistance R and piezoresistance K in RuO 2-based thick-film resistors. The percolating nature of transport in these systems is well accounted by values of the transport exponent t larger than its universal value t ≃ 2.0. Furthermore, we show that the RuO 2 volume fraction dependence of the piezoresistance data fit well with a logarithmically divergence at the percolation thresold. We argue that the universality breakdown and divergent piezoresistive response could be understood in the framework of a tunneling-percolating model proposed a few years ago to apply in carbon-black–polymer composites. We propose a new tunneling-percolating theory based on the segregated microstructure common to many thick-film resistors, and show that this model can in principle describe the observed universality breakdown and the divergent piezoresistance.
Learning Composable Signals for a Cognitive Substrate

According to the cognitive substrate hypothesis, human int elligence arises from the integration of specialist parts tha t are mostly shared with other mammals. In order for such specialists to cooperate in novel situations, however, they must ag ree on a system of signals that can describe aspects of the new sit uation using relations between familiar elements. This pos es a problem because many signals can only be learned from experience, yet different specialists may experience the wor ld in very different ways. This paper demonstrates that distribu ted learning of such signals is possible, and also that the appar ent problem is actually a benefit, using a vision specialist and a hearing specialist that together observe a simulated fourway intersection. Using a heuristic method based on Allen’s tim e relations, these two specialists agree on a set of composabl e signals, and some dynamics of the simulation are captured in the differences in how the two specialists interpret signal s.
Indexing uncertain spatio-temporal data

The advances in sensing and telecommunication technologies allow the collection and management of vast amounts of spatio-temporal data combining location and time information.Due to physical and resource limitations of data collection devices (e.g., RFID readers, GPS receivers and other sensors) data are typically collected only at discrete points of time. In-between these discrete time instances, the positions of tracked moving objects are uncertain. In this work, we propose novel approximation techniques in order to probabilistically bound the uncertain movement of objects; these techniques allow for efficient and effective filtering during query evaluation using an hierarchical index structure.To the best of our knowledge, this is the first approach that supports query evaluation on very large uncertain spatio-temporal databases, adhering to possible worlds semantics. We experimentally show that it accelerates the existing, scan-based approach by orders of magnitude.
A 1 MHz eGaN FET based 4-switch buck-boost converter for automotive applications

This paper presents the development of a 1 MHz enhancement mode GaN (eGaN) FET based 4-switch buck-boost converter with bootstrap driver for automotive applications. Conventionally, with Si MOSFETs, it is difficult to optimize the efficiency of a 4-switch buck-boost converter since the high side switches need to switch at high frequency or completely conduct the output/input current in either buck or boost operation mode. GaN FET with much lower Figure of Merit provides the possibility to achieve high efficiency of 4-switch buck-boost converter at MHz switching frequency. This paper investigates the challenges of using bootstrap driver in MHz 4-switch buck-boost converter, and presents associated solutions. A 6-45Vin, 10V/7A, 1 MHz eGaN FET based 4-switch buck-boost converter is built and measured high conversion efficiency confirms the superior performance with GaN FET.
Introductory Chapter: Bio-Psychosocial Model of Health

Health psychology explores different ways in the pursuit of getting people to embrace health promotion, illness prevention and health maintenance. As a speciality, health psychology examines how biological, psychological and social factors influence people’s behaviour about their health status. The aim of this chapter is to examine possible contributory connections between bio-psychosocial factors and health at the population level. The book explores bio-psychosocial model which can help individuals to develop and maintain healthy lifestyles so as to promote good health and prevent illness. Friedman and Adler [1] noted that the original bio-psychosocial model shaped not only research and theory on health but also the development of health psychology.
A Clustering Tool Using Particle Swarm Optimization for DNA Chip Data

Abstract DNA chips are becoming increasingly popular as a con-venient way to perform vast amounts of experiments re-lated to genes on a single chip. And the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties such as cancer. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy charac-teristic. The Particle Swarm Optimization algorithm which was recently proposed is a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed is efficient in terms of execution time for clustering DNA chip data, and thus be used to extract valuable in-formation such as cancer related genes from DNA chip data with high cluster accuracy and in a timely manner.Availability: The codes for the developed algorithm may be obtained from the author under consent to in-tellectual property agreements. The code is a demo ver-sion and thus some configuration methods are done through editing configuration files. The results are shown in a text window which will be improved in the future. Contact mlee@ewha.ac. kr if you are interested in the demo version of the codes for possible collaboration.Keywords: clustering, DNA chip data
Promoting the Integration and Use of an Industry IOIS: an Action-Oriented Perspective

The main reason for the failure of an industry inter-organizational information system (IOIS) is the low rate of adoption and use of the IOIS. Literature on IOIS has proposed primarily factor-based models to explain the adoption decision or the extent of use. In this paper we argue that a processual view is lacking for IOIS literature. We conduct a case study of an industry IOIS at the Seaport of Barcelona, which supports the message exchanges among the port agents operating in the Seaport. Using grounded theory research approach, we conceptualize the strategies adopted by managers of the IOIS in order to promote the integration of port agents’ systems with the IOIS and its further use. We then use action-oriented diagrams to structure and report on those strategies. Finally, drawing on mutual adaptation literature, we regard those strategies as adaptations to conform to three types of misalignments: technical, delivery system and value.