LLukas22/scidocs huggingface dataset:
Designing for the Safety of Pedestrians , Cyclists , and Motorists in Urban Environments

Problem: While design solutions aimed at enhancing the safety of pedestrians are viewed as being incompatible with those intended to improve the safety of motorists, there has been little meaningful evaluation of the issue. Instead, this disagreement is based largely on the theoretical assertion that traffic crashes are the result of random driver error, and that the only certain means for addressing safety is to design roadways to be forgiving of these errors when they occur. This perspective overlooks the possibility that crashes may instead be the product of systematic patterns of behavior associated with the characteristics of the built environment. Purpose: This study sought to discover whether urban crash incidence is the product of random error, or whether it may be influenced by characteristics of the built environment. Methods: We used negative binomial regression models to examine the relationship between several aspects of the built environment and the incidence of crashes involving motorists, pedestrians, and cyclists. We further subdivided motorist crashes into multiple-vehicle, fixed-object, and parked-car crashes to determine if these crash types had unique characteristics. Results and conclusions: We used vehicle miles of travel as a proxy for random error and found it to be positively, but weakly, associated with crashes involving motorists and pedestrians. We found stronger associations between crashes and characteristics of the built environment. We found miles of arterial roadways and numbers of four-leg intersections, strip commercial uses, Designing for the Safety of Pedestrians, Cyclists, and Motorists in Urban Environments
MACE prediction of acute coronary syndrome via boosted resampling classification using electronic medical records

OBJECTIVES
Major adverse cardiac events (MACE) of acute coronary syndrome (ACS) often occur suddenly resulting in high mortality and morbidity. Recently, the rapid development of electronic medical records (EMR) provides the opportunity to utilize the potential of EMR to improve the performance of MACE prediction. In this study, we present a novel data-mining based approach specialized for MACE prediction from a large volume of EMR data.


METHODS
The proposed approach presents a new classification algorithm by applying both over-sampling and under-sampling on minority-class and majority-class samples, respectively, and integrating the resampling strategy into a boosting framework so that it can effectively handle imbalance of MACE of ACS patients analogous to domain practice. The method learns a new and stronger MACE prediction model each iteration from a more difficult subset of EMR data with wrongly predicted MACEs of ACS patients by a previous weak model.


RESULTS
We verify the effectiveness of the proposed approach on a clinical dataset containing 2930 ACS patient samples with 268 feature types. While the imbalanced ratio does not seem extreme (25.7%), MACE prediction targets pose great challenge to traditional methods. As these methods degenerate dramatically with increasing imbalanced ratios, the performance of our approach for predicting MACE remains robust and reaches 0.672 in terms of AUC. On average, the proposed approach improves the performance of MACE prediction by 4.8%, 4.5%, 8.6% and 4.8% over the standard SVM, Adaboost, SMOTE, and the conventional GRACE risk scoring system for MACE prediction, respectively.


CONCLUSIONS
We consider that the proposed iterative boosting approach has demonstrated great potential to meet the challenge of MACE prediction for ACS patients using a large volume of EMR.
Modeling Gaze Behavior as a Function of Discourse Structure

This paper addresses the problem of designing conversational agents that exhibit appropriate gaze behavior during dialogues with human users. Previous research on gaze behavior has concentrated on its relationship to turn-taking phenomena [3,4,5]. Recent work has incorporated some of these findings into the design of autonomous human-like conversational agents and interactive communicative humanoids [1,13]. However, none of this research has examined the relationship between information structure and gaze behavior. In this paper we discuss why turn-taking is not an adequate explanation for gaze behavior in conversation and why information structure should be integrated with turn-taking as an explanation for this behavior. We then examine the relationship of gaze behavior to information structure and turn-taking through an empirical analysis of discourse transcripts for several dyadic conversations. A simple algorithm for assigning gaze behavior is proposed on the basis of the findings of this empirical analysis. We describe work in progress on implementing this algorithm in an existent communicative humanoid agent [14] with the goal of producing more natural gaze behavior related to propositional content in human-computer conversations.
Olfactory influences on mood and autonomic, endocrine, and immune function

Despite aromatherapy's popularity, efficacy data are scant, and potential mechanisms are controversial. This randomized controlled trial examined the psychological, autonomic, endocrine, and immune consequences of one purported relaxant odor (lavender), one stimulant odor (lemon), and a no-odor control (water), before and after a stressor (cold pressor); 56 healthy men and women were exposed to each of the odors during three separate visits. To assess the effects of expectancies, participants randomized to the "blind" condition were given no information about the odors they would smell; "primed" individuals were told what odors they would smell during the session, and what changes to expect. Experimenters were blind. Self-report and unobtrusive mood measures provided robust evidence that lemon oil reliably enhances positive mood compared to water and lavender regardless of expectancies or previous use of aromatherapy. Moreover, norepinephrine levels following the cold pressor remained elevated when subjects smelled lemon, compared to water or lavender. DTH responses to Candida were larger following inhalation of water than lemon or lavender. Odors did not reliably alter IL-6 and IL-10 production, salivary cortisol, heart rate or blood pressure, skin barrier repair following tape stripping, or pain ratings following the cold pressor.
Flame Wars : Automatic Insult Detection

Toxic comments are increasingly drowning out constructive ones, and websites are reacting by shutting down comment sections. Human moderation is slow and expensive, so an algorithmic solution is preferable. In this project, we explore the problem, existing literature, and recurrent models that have not been applied to this task.
Modern information technology in an old workforce: Toward a strategic research agenda

As the workforce ages rapidly in industrialized countries, a phenomenon known as the graying of the workforce, new challenges arise for firms as they have to juggle this dramatic demographical change (Trend 1) in conjunction with the proliferation of increasingly modern information and communication technologies (ICTs) (Trend 2). Although these two important workplace trends are pervasive, their interdependencies have remained largely unexplored. While Information Systems (IS) research has established the pertinence of age to IS phenomena from an empirical perspective, it has tended to model the concept merely as a control variable with limited understanding of its conceptual nature. In fact, even the few IS studies that used the concept of age as a substantive variable have mostly relied on stereotypical accounts alone to justify their age-related hypotheses. Further, most of these studies have examined the role of age in the same phenomenon (i.e., initial adoption of ICTs), implying a marked lack of diversity with respect to the phenomena under investigation. Overall, IS research has yielded only limited insight into the role of age in phenomena involving ICTs. In this essay, we argue for the importance of studying agerelated impacts more carefully and across various IS phenomena, and we enable such research by providing a research agenda that IS scholars can use. In doing so, we hope that future research will further both our empirical and conceptual understanding of the managerial challenges arising from the interplay of a graying workforce and rapidly evolving ICTs. 2014 Elsevier B.V. All rights reserved.
Space Syntax and Spatial Cognition: Proceedings of the Workshop held in Bremen, 24th September 2006

What can we learn of the human mind by examining its products? Here it is argued that a great deal can be learned, and that the study of human minds through its creations in the real world could be a promising field of study within the cognitive sciences. The city is a case in point. Since the beginning of cities human ideas about them have been dominated by geometric ideas, and the real history of cities has always oscillated between the geometric and the ‘organic’. Set in the context of the suggestion from cognitive neuroscience that we impose more geometric order on the world that it actually possesses, an intriguing question arises: what is the role of geometric intuition in how we understand cities and how we create them? Here we argue that all cities, the organic as well as the geometric, are pervasively ordered by geometric intuition, so that neither the forms of the cities nor their functioning can be understood without insight into their distinctive and pervasive emergent geometrical forms. The city is, as it is often said to be, the creation of economic and social processes, but, it is argued, these processes operate within an envelope of geometric possibility defined by human minds in its interaction with spatial laws that govern the relations between objects and spaces in the ambient world. Note: I have included only selected images here. All the examples will be shown fully in the presentation. Introduction: the Ideal and the Organic The most basic distinction we make about the form of cities is between the ideal and the organic. The ideal are geometric, the organic are not — or seem not to be. The geometric we define in terms of straight lines and 90 or 45 degree angles, the organic in terms of the lack of either (Fig. 1). The ideal seem to be top-down impositions of the human mind, the outcome of reason, often in association with power. We easily grasp their patterns when seen ‘all at once’. The organic we take to be the outcome of unplanned bottom up processes reflecting the
What contributes to good patient outcomes in the home treatment of the severely mentally ill: study protocol of a multi-centre analysis

BACKGROUND
While evidence is available that home treatment could be effective for treating severe mental illness, there is a lack of evidence on what exactly makes home treatment effective. The study presented here aims to develop recommendations for structures and processes in home treatment that are necessary for its effectiveness.


METHODS/DESIGN
14 provider networks of home treatment for severe mental illness will be analyzed and compared according to their structures, processes and patient-related outcomes. Data will be drawn from health care claims data, routine assessments of psychosocial functioning, and from questionnaires on structures and processes. The primary outcome will be psychosocial functioning; secondary outcomes, quality of life and days spent in hospital. The relation between structures and processes on one hand side and outcomes on the other side will be identified by multilevel analysis. In addition, focus groups with patients, relatives and network staff will be held to add further insight into relevant processes. All networks will receive individual quality reports, providing them with feedback on the results of this research and benchmarking them against the average. Based on this research, recommendations for processes and structures of home treatment will be developed.


DISCUSSION
The research will use longitudinal data on outcomes routinely assessed since 2009 and claims data. Routine data is also used for the assessment of structures and processes. By way of additional questionnaires developed in discussion with providers, further relevant factors can be included. The approach of this study becomes more comprehensive by conducting focus groups with patients, relatives and providers and by having the chance to evaluate the results with the networks by providing feedback of results. Several factors such as outcomes related to regional availability of hospital beds or size of networks might limit this study.
Semigroups and automata on infinite words

This paper is an introduction to the algebraic theory of infinite words. Infinite words are widely used in computer science, in particular to model the behaviour of programs or circuits. From a mathematical point of view, they have a rich structure, at the cross-roads of logic, topology and algebra. This paper emphasizes the combinatorial and algebraic aspects of this theory but the interested reader is referred to the survey articles [34, 44] or to the report [30] for more information on the other aspects. In particular, the important topic of the complexity of the algorithms on infinite words is not treated in this paper. The paper is written with the perspective of generalizing the results on recognizable sets of finite words to infinite words. This does not exactly follow the historical development of the theory, but it gives a good idea of the type of problems that occur in this field. Some of these problems are still open, or have been solved quite recently so that the definitions and results presented below may not be as yet finalized. The first result to be generalized is the equivalence between finite automata, finite deterministic automata and rational expressions. If one adds infinite iteration (“omega” operation) to the standard rational operations, union, product and star, one gets a natural definition of the ω-rational sets of infinite words that extends the definition of rational sets of finite words. Buchi [5] was the first to propose a definition of finite automata acting on infinite words. This definition suffices to extend Kleene’s theorem to infinite words: the sets of infinite words recognized by finite Buchi automata are exactly the ω-rational sets. This result is now known as Buchi’s theorem. However, Buchi’s definition is not totally satisfying since deterministic Buchi automata are not equivalent to non deterministic ones. The con-
Age, education and occupation as determinants of trends in body mass index in Finland from 1982 to 1997

OBJECTIVE: To investigate trends in body mass index (BMI) and prevalence of obesity among adults in Finland from 1982 to 1997, and to identify population groups with increasing obesity.SUBJECTS: Random samples from the national population register including men and women aged 25–64 y (n=24604, total).DESIGN: Four cross-sectional surveys carried out in three areas in Finland every fifth year since 1982.MEASUREMENTS: Weight and height were measured, and data on occupation and education level were collected by a self-administered questionnaire.RESULTS: The mean BMI increased in both genders. In men, the upward trend was greatest (the increase of 1.3 kg/m2 in 15 y) in the oldest age group (55–64 y), and was found also (the increase of 0.6 kg/m2) in the youngest age group (25–34 y), whereas in women, the upward trend was most prominent (the increase of 0.9 kg/m2) in the youngest age group. BMI increased in all educational groups in men, but in women the upward trend seemed to be greatest in the lowest educational group. The upward trends were most prominent among retired and unemployed men, while in women changes in BMI were similar in all occupational groups.CONCLUSION: The strongest upward trend in BMI was found in the oldest men, in the youngest age group in both genders and, in particular, among men who were outside the labor force. Education is still a strong determinant of obesity, especially in women, although the social gradient in BMI has not widened in the 1990s.
An Empirical Study of Investigating Mobile Applications Development Challenges

Context: mobile application development is rapidly evolving with substantial economic and scientific interest. One of the primary reasons for mobile application development failure is the increasing number of mobile platforms; some organizations endorse mobile application development before understanding the associated development challenges of each target platform. Objective: the objective of this paper is to identify the challenges of native, web, and hybrid mobile applications, which can undermine the successful development of such applications. Method: we adopted a two-phase research approach: at first, the challenges were identified via a systematic literature review (SLR); and then, the identified challenges were validated through conducting interviews with practitioners. Results: through both research approaches, we identified nine challenges vital to the success of mobile application development and four additional challenges from interviews not reported in the literature. A comparison of the challenges (native, web, and hybrid) identified in SLR indicates that there are slightly more differences than similarities between the challenges. On the other hand, the challenges (native, web, and hybrid) identified in interviews indicates that there are more similarities than differences between the challenges. Our results show a weak negative correlation between the ranks obtained from the SLR and the interviews (<inline-formula> <tex-math notation="LaTeX">$[rs(9) = -.034]$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$p = 0.932$ </tex-math></inline-formula>). The results obtained from our t-test (i.e., <inline-formula> <tex-math notation="LaTeX">$t = 0.868, p = 0.402 > 0.05$ </tex-math></inline-formula>) depicts that there is no significant difference between the findings of SLR and interviews. Conclusions: mobile application development organizations should try to address the identified challenges when developing mobile applications (native, web, or hybrid) to increase the probability of mobile application success.
Vitamin D3 and calcium to prevent hip fractures in elderly women.

BACKGROUND
Hypovitaminosis D and a low calcium intake contribute to increased parathyroid function in elderly persons. Calcium and vitamin D supplements reduce this secondary hyperparathyroidism, but whether such supplements reduce the risk of hip fractures among elderly people is not known.


METHODS
We studied the effects of supplementation with vitamin D3 (cholecalciferol) and calcium on the frequency of hip fractures and other nonvertebral fractures, identified radiologically, in 3270 healthy ambulatory women (mean [+/- SD] age, 84 +/- 6 years). Each day for 18 months, 1634 women received tricalcium phosphate (containing 1.2 g of elemental calcium) and 20 micrograms (800 IU) of vitamin D3, and 1636 women received a double placebo. We measured serial serum parathyroid hormone and 25-hydroxyvitamin D (25(OH)D) concentrations in 142 women and determined the femoral bone mineral density at base line and after 18 months in 56 women.


RESULTS
Among the women who completed the 18-month study, the number of hip fractures was 43 percent lower (P = 0.043) and the total number of nonvertebral fractures was 32 percent lower (P = 0.015) among the women treated with vitamin D3 and calcium than among those who received placebo. The results of analyses according to active treatment and according to intention to treat were similar. In the vitamin D3-calcium group, the mean serum parathyroid hormone concentration had decreased by 44 percent from the base-line value at 18 months (P < 0.001) and the serum 25(OH)D concentration had increased by 162 percent over the base-line value (P < 0.001). The bone density of the proximal femur increased 2.7 percent in the vitamin D3-calcium group and decreased 4.6 percent in the placebo group (P < 0.001).


CONCLUSIONS
Supplementation with vitamin D3 and calcium reduces the risk of hip fractures and other nonvertebral fractures among elderly women.
Where's the Bear? - Automating Wildlife Image Processing Using IoT and Edge Cloud Systems

We investigate the design and implementation of Where's The Bear (WTB), an end-to-end, distributed, IoT system for wildlife monitoring. WTB implements a multi-tier (cloud, edge, sensing) system that integrates recent advances in machine learning based image processing to automatically classify animals in images from remote, motion-triggered camera traps. We use non-local, resource-rich, public/private cloud systems to train the machine learning models, and "in-the-field," resource-constrained edge systems to perform classification near the IoT sensing devices (cameras).
 We deploy WTB at the UCSB Sedgwick Reserve, a 6000 acre site for environmental research and use it to aggregate, manage, and analyze over 1.12M images. WTB integrates Google TensorFlow and OpenCV applications to perform automatic image classification and tagging. To avoid transferring large numbers of training images for TensorFlow over the low-bandwidth network linking Sedgwick to public clouds, we devise a technique that uses stock Google Images to construct a synthetic training set using only a small number of empty, background images from Sedgwick. Our system is able to accurately identify bears, deer, coyotes, and emtpy images and significantly reduces the time and bandwidth requirements for image transfer, as well as end-user analysis time, since WTB automatically filters the images on-site.
Budget feasible mechanism design

In this letter we sketch a brief introduction to budget feasible mechanism design. This framework captures scenarios where the goal is to buy items or services from strategic agents under budget. The setting introduces interesting challenges that arise from the tension between incentive compatibility and the budget constraint, and leaves many interesting open questions. We will discuss several application domains that include crowdsourcing, information dissemination in social networks, and privacy-preserving recommendation systems.
Holistic Scene Understanding for 3D Object Detection with RGBD Cameras

In this paper, we tackle the problem of indoor scene understanding using RGBD data. Towards this goal, we propose a holistic approach that exploits 2D segmentation, 3D geometry, as well as contextual relations between scenes and objects. Specifically, we extend the CPMC [3] framework to 3D in order to generate candidate cuboids, and develop a conditional random field to integrate information from different sources to classify the cuboids. With this formulation, scene classification and 3D object recognition are coupled and can be jointly solved through probabilistic inference. We test the effectiveness of our approach on the challenging NYU v2 dataset. The experimental results demonstrate that through effective evidence integration and holistic reasoning, our approach achieves substantial improvement over the state-of-the-art.
Wide bandwidth and small size LPDA antenna

In this paper, a wideband log periodic dipole antenna (LPDA) with small size is proposed. The arms of the dipole are in the shape of a second order fractal, which makes each dipole element to resonate in more than one frequency. This results in a LPDA antenna whose size can be greatly reduced. The proposed antenna has a substrate size of 90 × 60 mm2 and operates over 2-8 GHz bandwidth with VSWR<; 2. The antenna has stable pattern over the frequency range.
A texture-based method for modeling the background and detecting moving objects

This paper presents a novel and efficient texture-based method for modeling the background and detecting moving objects from a video sequence. Each pixel is modeled as a group of adaptive local binary pattern histograms that are calculated over a circular region around the pixel. The approach provides us with many advantages compared to the state-of-the-art. Experimental results clearly justify our model.