Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving measurement methods for behavior change interventions: opportunities for innovation.

Theoretically based behavioral interventions havedemonstrated effectiveness in stopping smoking,increasing physical activity and improving nutritionin order to prevent major chronic diseases such ascardiovascular disease, cancer and diabetes [1–7]. Despite the development of effective behaviorchange programs, the magnitude of change in thesebehaviors has been relatively modest [8, 9]. Therising rates of diabetes and obesity, for example,indicate there is still much to learn about the mech-anisms of behavior change and how to maintainnewly acquired behavioral skills. One problemthat has slowed behavioral intervention research isthat the validity and reliability of our measures hassometimes lagged other innovations such as thedevelopment of effective tailored interventions [10,11] or analytical techniques for assessing moder-ators and mediators of behavior change, hencemaking it difﬁcult to understand the mechanismsof behavior change and making it difﬁcult toimprove our interventions [12–15]. This special issue of Health Education Researchprovides an opportunity to consider an importantadvancement in our behavioral measurement meth-ods, speciﬁcally, how we can apply item responsemodels to improve our psychometric methods inhealth education and health behavior research andpractice.Althoughitemresponsemodeling(IRM)hasbeen used in educational testing over the last threedecades [16], it is an emerging method in healtheducation and health behavior research [17]. As, forexample, in health research, IRM is being widelyadopted to improve and revise quality of life ques-tionnaires [18–20]. There are many other innovativeapplicationsofIRMandastheninepapersinthisissueshowus,theseapplicationscanaidourunderstandingof the psychometric properties of scales beyondmaking questionnaires shorter and beyond whatmostofuslearnedinoursurveydevelopmentcoursesbased on classical test theory (CTT). In this briefafterword, we highlight current and future applica-tions of IRM and discuss how these methods mighthelp us improve the efﬁciency of our research. Webelieve these methods could lead to considerableimprovements in intervention methods, understand-ing the mechanisms of behavior change and de-veloping and reﬁning theoretical models to makethemmore parsimonious aswell asprovide a founda-tion for considering the feasibility of computerizedadaptivetestingformeasuresofbehavioralconstructs.For those who are not familiar with IRM methods,the two papers by Wilson colleagues [21, 22] pro-vide an excellent tutorial by presenting an exampleusing the Rasch one-parameter model to examinea measure of self-efﬁcacy using both dichotomousand polytomous models and then comparing IRMand CTT methods. In the ﬁrst paper, readers learnthe basics of IRM, including the relationship ofindividual items as well as the role of item difﬁcultyresponse patterns. In other words, item responsemodels estimate a result of the underlying construct
Why Writing Your Own Search Engine Is Hard

There must be 4,000 programmers typing away in their basements trying to build the next “world’s most scalable” search engine. It has been done only a few times. It has never been done by a big group; always one to four people did the core work, and the big team came on to build the elaborations and the production infrastructure. Why is it so hard? We are going to delve a bit into the various issues to consider when writing a search engine. This article is aimed at those individuals or small groups that are considering this endeavor for their Web site or intranet. It is fun, but a word of caution: not only is it difficult, but you need two commodities in short supply: time and patience.
Welfare impacts of the 1996 United States - Canada Softwood Lumber (trade) Agreement

This paper investigates welfare impacts of the 1996 United States - Canada Softwood Lumber (trade) Agree- ment (SLA), which set up a tariff-regulated quota system to restrict softwood lumber export from Canada to the United States. An aggregate price model is used to estimate the price impact of the SLA, and the implied quantity and welfare effects are examined. The results show that while the anticipated change in lumber price is about $59 in 1997 U.S. dollars or 16%, on average, for the first 4 years under the SLA, the gains to U.S. producers of softwood lumber are large and the losses to U.S. consumers are much larger. In addition, Canadian producers have benefitted from the SLA in the U.S. market, and the Canadian government has collected a small amount of additional export fees. As the overall efficiency costs of the SLA are modest, the SLA can be seen as an effective means of welfare transfer from U.S. consum- ers to the U.S. and Canadian producers. These results should provide a framework for ongoing trade policy debate. Resume : Cette etude examine les impacts sociaux de l'accord commercial sur le bois d'œuvre resineux entre le Ca- nada et les Etats-Unis signe en 1996. Cet accord etablit un systeme de tarifs base sur des quotas dans le but de res - treindre l'exportation de bois d'œuvre resineux du Canada vers les Etats-Unis. Un modele de prix global est utilise pour evaluer l'impact de l'accord sur le prix. La quantite impliquee et les effets sociaux sont egalement etudies. Les resultats montrent que, tandis que le changement anticipe dans le prix du bois d'œuvre est d'environ 59$ en dollars americains de 1997 ou 16% en moyenne pour les quatre premieres annees de l'accord, les gains pour les producteurs americains de bois d'œuvre resineux sont importants et les pertes pour les consommateurs americains sont beaucoup plus importantes. De plus, les producteurs canadiens ont beneficie de l'accord et le gouvernement canadien a preleve un faible montant supplementaire de taxes a l'exportation. Etant donne que les couts globaux d'efficacite de l'accord sont faibles, cet accord peut etre considere comme un moyen efficace de transfert de richesse des consommateurs ame- ricains vers les producteurs americains et canadiens. Ces resultats devraient constituer un cadre de reference dans le de- bat en cours sur la politique commerciale. (Traduit par la Redaction) Zhang 1967
Object Recognition Based On Indexing In 2D Environment

Model-based object recognition has attracted considerable attention in the vision paper presents a model-based two dimensional object recognition system using feature indexing under a linear transformation through geometric hashing. The objects are represented by their dominant invariant features under a linear transformation in the normalised orthogonal coordinate frame. The goal of this paper is to solve the 2D recognition in'the industrial environment in an efficient way and reduce the net computational overhead. The proposed algorithm is also able to identify a partially occluded object in cluttered environment. The paper shows how the symmetry of the object can be exploited to reduce the model data storage and to speed up the matching process. The matching is done through its feature set tuples. The feature set includes both the local and global features of the objects, which helps to recognise the object more accurately.
Adaptive Enterprise Architecture Modelling

Agile or adaptive enterprise architecture driven software development approach requires a modelling standard to describe the existing and to-be developed artifacts both at the high enterprise level and low, detailed level. However, a single modelling standard may not be used off-the-shelf to fully support the modelling needs of an adaptive enterprise architecture driven software development needs. The modelling standards need to be systematically analyzed and integrated for a particular modelling context. This paper reviews two well-known modeling standards ArchiMate and BPMN by using the interoperability research framework. Based on the syntax, semantics and structural analysis of these two modelling standards' metamodels, it proposes a hybrid adaptive enterprise architecture modelling approach for describing and analysing the artifacts both at the high enterprise level and low, detailed level for a particular context. This paper has both theoretical and practical implications for researchers and practitioners pursuing to integrate various modelling standards.
Facility Location with Client Latencies: LP-Based Techniques for Minimum-Latency Problems

We introduce a problem that is a common generalization of the uncapacitated facility location (UFL) and minimum latency (ML) problems, where facilities not only need to be opened to serve clients, but also need to be sequentially activated before they can provide service. This abstracts a setting where inventory demanded by customers needs to be stocked or replenished at facilities from a depot or warehouse.Formally, we are given a set ℱ of n facilities with facility-opening costs, a set (D-script) of m clients, and connection costs c ( i , j ) specifying the cost of assigning a client j to a facility i , a root node r denoting the depot, and a time metric d () on ℱ ∪ { r }. Our goal is to open a subset of facilities, find a path P starting at r and spanning the open facilities to activate them, and connecting each client j to an open facility so as to minimize the total facility opening cost, the total client connection cost, and the total time of arrivals at each facility along P . We call this the minimum latency uncapacitated facility location (MLUFL) problem.Our main result is an O (log n max(log n , log m ))-approximation for MLUFL. Via a reduction to the group Steiner tree (GST) problem, we show this result is tight in the sense that any improvement in the approximation guarantee for MLUFL, implies an improvement in the (currently known) approximation factor for GST. We obtain significantly improved constant approximation guarantees for two natural special cases of the problem: (a) Related MLUFL, where the connection costs form a metric that is a scalar multiple of the time metric; (b) Metric uniform MLUFL, where we have metric connection costs and the time-metric is uniform.Our LP-based methods are fairly versatile and are easily adapted with minor changes to yield approximation guarantees for MLUFL (and ML) in various more general settings, such as (i) the setting where the latency-cost of a client is a function (of bounded growth) of the delay faced by the facility to which it is connected; and (ii) the k -route version, where we can dispatch k vehicles in parallel to activate the open facilities.Our LP-based understanding of MLUFL also offers some LP-based insights into ML. We obtain two natural LP-relaxations for ML with constant integrality gap, which we believe shed new light upon the problem and offer a promising direction for obtaining improvements for ML.
Improving dissolution and oral bioavailability of pranlukast hemihydrate by particle surface modification with surfactants and homogenization

The present study was carried out to develop an oral formulation of pranlukast hemihydrate with improved dissolution and oral bioavailability using a surface-modified microparticle. Based on solubility measurements, surface-modified pranlukast hemihydrate microparticles were manufactured using the spray-drying method with hydroxypropylmethyl cellulose, sucrose laurate, and water and without the use of an organic solvent. The hydrophilicity of the surface-modified pranlukast hemihydrate microparticle increased, leading to enhanced dissolution and oral bioavailability of pranlukast hemihydrate without a change in crystallinity. The surface-modified microparticles with an hydroxypropylmethyl cellulose/sucrose laurate ratio of 1:2 showed rapid dissolution of up to 85% within 30 minutes in dissolution medium (pH 6.8) and oral bioavailability higher than that of the commercial product, with approximately 2.5-fold and 3.9-fold increases in area under the curve (AUC0→12 h) and peak plasma concentration, respectively. Therefore, the surface-modified microparticle is an effective oral drug delivery system for the poorly water-soluble therapeutic pranlukast hemihydrate.
The Internet and an Informed Citizenry

A new communications environment, driven largely by the Internet and World Wide Web, is rapidly changing the economic, social, and political landscape. According to recent surveys, nearly seven in ten Americans (68 percent) now use computers at least "occasionally," six in ten (59 percent) have computers in their homes, and more than half (55 percent) have access to the Internet, 43 percent of these from home. Of the 55 percent of Americans who are "wired," more than one-third (36 percent), or 20 percent of the general public, now go online five or more hours per week. These numbers are up significantly from just a few years ago. For example, the number of Americans who say they go online at least occasionally has increased from 21 percent in 1996 to 54 percent in 2000. Comments NOTE: At the time of publication, the author Michael X. Delli Carpini was affiliated with Columbia University. Currently January 2008, he is a faculty member of the Annenberg School for Communication at the University of Pennsylvania. This book chapter is available at ScholarlyCommons: http://repository.upenn. edu/asc_papers/2 The Internet and an Informed Citizenry MICHAEL X. DELLI CARPINI AND SCOTT KEETER 9 AiNEW COMMUNICATIONS environment, driven largely by the Internet and World Wide Web, is rapidly changing the ecoomic, social, and political landscape. According to recent surveys, nearly seven in ten Americans (68 percent) now use computers at least "occasionally," six in ten (59 percent) have computers in their homes, and more than half (55 percent) have access to the Internet, 43 percent of these from home. Of the 55 percent ofAmericans who are "wired," more than one-third (36 percent), or 20 percent of the general public, now go online five or more hours per week. These numbers are up significantly from just a few years ago. For example, the number ofAmericans who say they go online at least occasionally has increased from 21 percent in 1996 to 54 percent in 2000.1 Although much of this increased Internet traffic is devoted to work, entertainment, and/or personal consumption, the Web has also become an increasingly important source ofnews (see table 9.1). Onethird of Americans (33 percent) report going online for news at least one day per week, nearly one-fourth (23 percent) at least three days per week, and 15 percent every day. Although the Internet is not yet a predominant news source for campaigns-in February 2000, only 7 percent ofcitizens reported that the Internet was one of their top two sources for campaign news (up from 2 percent in 1996)-nearly onefourth (24 percent) said they "regularly" or "sometimes" learned something about the presidential campaign or candidates from the Internet.2 The civic potential of the Internet is especially strong among younger Americans. For example, one recent survey found that 70 percent of18to 25-year-olds believe the Internet is a "useful" source of political and issue information (compared to 48 percent of those
The Subsurface Stress Field Created by Three-Dimensionally Rough Bodies in Contact with Traction

A numerical simulation technique for calculating the complete subsurface stress field for three-dimensionally rough bodies in sliding contact is described. The stresses are calculated using real digitized three-dimensional surface profiles. The effects of the surface roughness and the sliding friction are presented. Using an existing contact simulation code, the digitized surfaces are mathematically pressed together and the real areas of contact and the asperity pressures are calculated. The surfaces are assumed to remain elastic throughout the contact simulation process. The shear forces at the asperity contact interfaces are assumed to be proportional to their calculated normal pressures. The subsurface stresses are then determined with these known normal and tangential forces at the surface. Presented at the 48th Annual Meeting in Calgary, Alberta, Canada May 17–20, 1993
Continental-scale distributions of dust-associated bacteria and fungi

Significance We inhale thousands of microbial cells when we breathe in outdoor air, and some of these airborne microbes can serve as pathogens or triggers of allergic disorders. Using settled dust samples from ∼1,200 locations, we generated the first atlas, to our knowledge, of airborne bacterial and fungal distributions across the continental United States. We found that airborne microbial communities, such as terrestrial plants and animals, exhibit nonrandom geographic patterns, and we identified the factors that shape the continental-scale distributions of microbial taxa. Furthermore, we found that the airborne microbes found in urban and more rural areas are not distinct in composition, but the dust-associated communities found in more urbanized areas are more homogeneous across the United States. It has been known for centuries that microorganisms are ubiquitous in the atmosphere, where they are capable of long-distance dispersal. Likewise, it is well-established that these airborne bacteria and fungi can have myriad effects on human health, as well as the health of plants and livestock. However, we have a limited understanding of how these airborne communities vary across different geographic regions or the factors that structure the geographic patterns of near-surface microbes across large spatial scales. We collected dust samples from the external surfaces of ∼1,200 households located across the United States to understand the continental-scale distributions of bacteria and fungi in the near-surface atmosphere. The microbial communities were highly variable in composition across the United States, but the geographic patterns could be explained by climatic and soil variables, with coastal regions of the United States sharing similar airborne microbial communities. Although people living in more urbanized areas were not found to be exposed to distinct outdoor air microbial communities compared with those living in more rural areas, our results do suggest that urbanization leads to homogenization of the airborne microbiota, with more urban communities exhibiting less continental-scale geographic variability than more rural areas. These results provide our first insight into the continental-scale distributions of airborne microbes, which is information that could be used to identify likely associations between microbial exposures in outdoor air and incidences of disease in crops, livestock, and humans.
Dopamine neurons projecting to the posterior striatum form an anatomically distinct subclass

Combining rabies-virus tracing, optical clearing (CLARITY), and whole-brain light-sheet imaging, we mapped the monosynaptic inputs to midbrain dopamine neurons projecting to different targets (different parts of the striatum, cortex, amygdala, etc) in mice. We found that most populations of dopamine neurons receive a similar set of inputs rather than forming strong reciprocal connections with their target areas. A common feature among most populations of dopamine neurons was the existence of dense ‘clusters’ of inputs within the ventral striatum. However, we found that dopamine neurons projecting to the posterior striatum were outliers, receiving relatively few inputs from the ventral striatum and instead receiving more inputs from the globus pallidus, subthalamic nucleus, and zona incerta. These results lay a foundation for understanding the input/output structure of the midbrain dopamine circuit and demonstrate that dopamine neurons projecting to the posterior striatum constitute a unique class of dopamine neurons regulated by different inputs. DOI: http://dx.doi. org/10.7554/eLife.10032. 001
Big-Data Visualization

Almost all fields of study and practice sooner or later will confront the big-data problem. Visualization has proven effective for not only presenting essential information in vast amounts of data but also driving complex analyses. Big-data analytics and discovery present new research opportunities to the computer graphics and visualization community. This special issue highlights the latest advancements in solving the big-data problem through visual means, with four articles on new techniques, systems, or applications.
Optimal Sample Selection for Batch-mode Reinforcement Learning

We introduce the Optimal Sample Selection(OSS) meta-algorithm for solving discrete-time Optimal Control problems. This meta-algorithm maps the problem of finding a near-optimal closed-loop policy to the identification of a small set of one-step system transitions, leading to high-quality policies when used as input of a batch-mode Reinforcement Learning (RL) algorithm. We detail a particular instance of this OSS meta-algorithm that uses tree-based Fitted Q-Iteration as a batch-mode RL algorithm and Cross Entropy search as a method for navigating efficiently in the space of sample sets. The results show that this particular instance of OSS algorithms is able to identify rapidly small sample sets leading to high-quality policies.
The reduction of serum aminotransferase levels is proportional to the decline of the glomerular filtration rate in patients with chronic kidney disease

OBJECTIVE: This study sought to determine the serum aminotransferase levels of patients with predialysis chronic kidney disease and establish their relationships with serum creatinine levels and glomerular filtration rate. METHODS: Patients with chronic kidney disease were evaluated between September 2011 and May 2012. Aminotransferase and creatinine serum levels were measured using an automated kinetic method, and glomerular filtration rates were estimated using the Cockroft-Gault and Modification of Diet in Renal Disease formulas to classify patients into chronic kidney disease stages. RESULTS: Exactly 142 patients were evaluated (mean age: 64±16 years). The mean creatinine serum level and glomerular filtration rate were 3.3±1.2 mg/dL and 29.1±13 mL/min/1.73 m2, respectively. Patients were distributed according to their chronic kidney disease stages as follows: 3 (2.1%) patients were Stage 2; 54 (38%) were Stage 3; 70 (49.3%) were Stage 4; and 15 (10.5%) were Stage 5. The mean aspartate aminotransferase and alanine aminotransferase serum levels showed a reduction in proportion to the increase in creatinine levels (p=0.001 and p=0.05, respectively) and the decrease in glomerular filtration rate (p=0.007 and p=0.028, respectively). Alanine aminotransferase and aspartate aminotransferase serum levels tended to be higher among patients classified as stage 2 or 3 compared with those classified as stage 4 or 5 (p=0.08 and p=0.06, respectively). CONCLUSIONS: The aspartate aminotransferase and alanine aminotransferase serum levels of patients with predialysis chronic kidney disease decreased in proportion to the progression of the disease; they were negatively correlated with creatinine levels and directly correlated with glomerular filtration rate.