Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing Leaky Waveguide Modes by Pseudospectral Modal Method

Leaky modes are important when optical waveguides fail to confine light completely. Computing waveguide modes to high accuracy is challenging if the waveguide has high index-contrast and sharp corners. The propagation constant of a leaky mode is complex, its imaginary part is an important physical quantity (the decay rate along the waveguide axis). To find complex propagation constants with a small imaginary part, high-accuracy numerical solutions are necessary. The pseudospectral modal method (PSMM), originally developed for diffraction gratings, has recently been reformulated as a full-vectorial waveguide mode solver. In this letter, the PSMM is extended to analyze two challenging waveguide benchmark problems involving leaky modes.
Community structure of soil oribatida (acari) two years after windthrow in the high tatra mountains

In November 2004 a catastrophic windstorm destroyed a large part of the spruce forest in the Tatra National Park (Slovakia). The majority of the windthrown area was cleared; only a small part was left uncleared, thereby allowing regeneration by natural succession. The aim of the present study was to assess the impact of the different forestry practices on soil Oribatida. Three different stands were selected for the study, where sampling took place in June and October 2006: control forest stands (REF), windthrown stands left for natural development (NEX) and clear-cut windthrown stands (EXT). The mean abundance of Oribatida recorded in REF and NEX stands was significantly higher than in EXT stands. Kruskal-Wallis test of mean abundance of adults as well as juveniles confirmed significant influence of treatment and date. The highest abundance of adults was found in control forest stands (REF). Post hoc multiple comparison proved significantly lower abundance of adults in clear-cut stands (EXT) compared with REF. The mean abundance of adults and juveniles was several times higher in stands left for natural development (NEX) than in EXT stands. The highest species richness was observed in REF, followed by NEX and EXT stands. Ordination method showed differences in species composition between studied treatments. Furthermore, a much lower abundance of Hermannia gibba, a dweller of leaf litter and upper soil layers, was recorded in cleared stands compared to the other stands. Indeed, windthrown stands had an obvious lower species richness than control stands. The ordination method used demonstrated a significant influence of both treatment and sampling date on the abundance and species richness of Oribatida. The present study showed that clear-cutting of wind-damaged spruce forest markedly decreases the abundance of soil Oribatida compared with windthrown forest stands left to natural succession.
Ubiquitin Fold Modifier 1 (UFM1) and Its Target UFBP1 Protect Pancreatic Beta Cells from ER Stress-Induced Apoptosis

UFM1 is a member of the ubiquitin like protein family. While the enzymatic cascade of UFM1 conjugation has been elucidated in recent years, the biological function remains largely unknown. In this report we demonstrate that the recently identified C20orf116 [1], which we name UFM1-binding protein 1 containing a PCI domain (UFBP1), andCDK5RAP3 interact with UFM1. Components of the UFM1 conjugation pathway (UFM1, UFBP1, UFL1 and CDK5RAP3) are highly expressed in pancreatic islets of Langerhans and some other secretory tissues. Co-localization of UFM1 with UFBP1 in the endoplasmic reticulum (ER)depends on UFBP1. We demonstrate that ER stress, which is common in secretory cells, induces expression of Ufm1, Ufbp1 and Ufl1 in the beta-cell line INS-1E.siRNA-mediated Ufm1 or Ufbp1knockdown enhances apoptosis upon ER stress.Silencing the E3 enzyme UFL1, results in similar outcomes, suggesting that UFM1-UFBP1 conjugation is required to prevent ER stress-induced apoptosis. Together, our data suggest that UFM1-UFBP1participate in preventing ER stress-induced apoptosis in protein secretory cells.
The Size and Power of Bootstrap Tests

We show that, in many circumstances, the size distortion of a bootstrap P value for a test will be one whole order of magnitude smaller than that of the corresponding asymptotic P value. We also show that, at least in the parametric case, the magnitude of the distorsion will depend on the shape of what we call the P value function. As regards the power of bootstrap tests, we show that the size-corrected power of a bootstrap test differs from that of the corresponding asymptotic test only by an amount of the same order magnitude as the size distortion, and of arbitrary sign.
Standard versus Abdominal Lifting and Compression CPR

Background. This study compared outcomes of abdominal lifting and compression cardiopulmonary resuscitation (ALP-CPR) with standard CPR (STD-CPR). Materials and Methods. Patients with cardiac arrest seen from April to December 2014 were randomized to receive standard CPR or ALP-CPR performed with a novel abdominal lifting/compression device. The primary outcome was return of spontaneous circulation (ROSC). Results. Patients were randomized to receive ALP-CPR (n = 40) and STD-CPR (n = 43), and the groups had similar baseline characteristics. After CPR, 9 (22.5%) and 7 (16.3%) patients in the ALP-CPR and STD-CPR groups, respectively, obtained ROSC. At 60 minutes after ROSC, 7 (77.8%) and 2 (28.6%) patients, respectively, in the ALP-CPR and STD-CPR groups survived (P = 0.049). Patients in the ALP-CPR group had a significantly higher heart rate and lower mean arterial pressure (MAP) than those in the STD-CPR group (heart rate: 106.8 versus 79.0, P < 0.001; MAP: 60.0 versus 67.3 mm Hg, P = 0.003). The posttreatment PCO2 was significantly lower in ALP-CPR group than in STD-CPR group (52.33 versus 58.81, P = 0.009). PO2 was significantly increased after ALP-CPR (45.15 to 60.68, P < 0.001), but it was not changed after STD-CPR. PO2 after CPR was significantly higher in the ALP-CPR group (60.68 versus 44.47, P < 0.001). There were no differences between genders and for patients who are > 65 or ≤ 65 years of age. Conclusions. The abdominal lifting and compression cardiopulmonary resuscitation device used in this study is associated with a higher survival rate after ROSC than standard CPR.
Institutions and Economic Growth: Europe After World War II

European economic growth in the quarter of a century that ended in 1973 outstripped growth in any period of comparable length before or since. The elements of Europe's growth miracle -- wage moderation, high investment and rapid export growth -- were delivered by a tailor-made set of domestic and international arrangements -- on the domestic side the social market economy, on the external side international agreements and supranational institutions -- that solved problems of commitment and cooperation that would have otherwise hindered the resumption of growth.
Idiomatic Constructions in HPSG

A new and distinct peach variety possessing a relatively low chilling requirement is provided. The fruit of the new variety is early maturing and unlike most low chilling varieties has a higher level of red skin coloration, and excellent commercial qualities such as firmness and the ability to withstand handling and shipping. The new variety originated as an open pollinated seedling with the Ruby Gold nectarine variety (U.S. Plant Pat. No. 3,101) serving as the seed parent. Various peach varieties having low chilling requirements were growing the area and likely served as the pollen source. The new variety of the present invention is particularly suited for growing in the United States in zone 9 and the upper part of zone 10.
Facial event classification with task oriented dynamic Bayesian network

Facial events include all activities of face and facial features in spatial or temporal space, such as facial expressions, face gesture, gaze and furrow happening, etc. Developing an automated system for facial event classification is always a challenging task due to the richness, ambiguity and dynamic nature of facial expressions. This paper presents an efficient approach to real-world facial event classification. By integrating dynamic Bayesian network (DBN) with a general-purpose facial behavior description language, a task-oriented stochastic and temporal framework is constructed to systematically represent and classify facial events of interest. Based on the task oriented DBN, we can spatially and temporally incorporate results from previous times and prior knowledge of the application domain. With the top-down inference, the system can make active selection among multiple visual channels to identify the most effective sensory channels to use. With the bottom-up inference from observed evidences, the current facial event can be classified with a desired confident level via the belief propagation. We applied the task-oriented DBN framework to monitoring driver vigilance. Experimental results demonstrate the feasibility and efficiency of our approach.
The Ecological Fallacy Revisited: Aggregate- versus Individual-level Findings on Economics and Elections, and Sociotropic Voting

Several aggregate-level studies have found a relationship between macroeconomic conditions and election outcomes, operating in intuitively plausible directions. More recent survey-based studies, however, have been unable to detect any comparable relationship operating at the individual-voter level. This persistent discrepancy is puzzling. One recently proposed explanation for it is that voters actually behave in an altruistic or “sociotropic” fashion, responding to economic events only as they affect the general welfare, rather than in terms of self-interested “pocketbook” considerations. It is argued here that the discrepancies between the macro- and microlevel studies are a statistical artifact, arising from the fact that observable changes in individual welfare actually consist of two unobservable components, a government-induced (and politically relevant) component, and an exogenous component caused by life-cycle and other politically irrelevant factors. Because of this, individual level cross-sectional estimates of the effects of welfare changes on voting are badly biased and are essentially unrelated to the true values of the behavioral parameters of interest: they will generally be considerable underestimates and may even be of the wrong sign. An aggregate-level time-series analysis, on the other hand, will often yield reasonably good (if somewhat attenuated) estimates of the underlying individual-level effects of interest. Therefore, in this case, individual behavior is best investigated with aggregate- rather than individual-level data. It is also shown that the evidence for sociotropic voting is artifactual, in the sense that the various findings and evidence which ostensibly show sociotropic behavior are all perfectly compatible with the null hypothesis of self-interested, pocketbook voting.
Departures from Tree Structures in Discourse: Shared Arguments in the Penn Discourse TreeBank

The term discourse structure is used to denote any structure of a text above that of the sentence. Trees have often been posited as a good abstraction when discourse is taken to have a hierarchical structure (Mann and Thompson 1987; Webber et al. 2003; Marcu 2000; Egg and Redeker 2008). Nevertheless, periodically researchers have commented on the need to depart from the strict singleparent hierarchy of trees to structures which have shared daughters, a move which incorporates multiple inheritance and is therefore an issue for tree representations. This study follows up on the observation in (Lee et al. 2006) about the relative ubiquity of shared structures in the Penn Discourse Treebank or PDTB (Prasad et al. 2008; PDTB-Group 2008)), a recently released corpus which annotates discourse relations and their arguments. We limit our investigation here to cases where the shared discourse structure is a syntactically subordinate clause introduced by a subordinating conjunction (e.g. because, although, when, etc.). We examine annotations in the PDTB where the subordinate clause has been taken to be an argument of both the relation associated with the subordinating conjunction and another relation expressed in the immediately subsequent discourse. We ask what such annotations imply about the link between syntactic subordination and discourse subordination. Our argument is that while syntactic subordination may often correlate with discourse subordination, there are interesting exceptions that might better be captured as discourse coordination. We provide some systematic characterization of these exceptions by appealing to well-motivated discourse factors, and discuss their implications for tree structures.
Relative Movement to Support Stock Forecasting of the Thai Market using the Neural Network

Nowadays, stock analysis is a challenging task in stock prediction. Stock analysis methods including fundamental analysis and technical analysis are commonly used among financial professionals to help them on investment decisions. In recent days, AI-based system becomes a common tool to predict stock price. Among AI-based models for stock forecasting, Artificial Neural Network (ANN) is the most popular and accurate model. This research proposes data preprocessing using relative movement to improve performance of ANN-based stock forecasting. Both fundamental and technical indicators are chosen as input to the system. The common preprocessing including Principal Component Analysis (PCA) and Z-Scaling is also applied. The evaluation metrics include Root Mean Squared Error (RMSE), hit ratio, and total return. The k-fold cross validation is used to utilize the dataset of stocks in banking sector. The significance of those three metrics is determined through t-test over cross validation. The experiments show that the proposed model outperforms a traditional model, random walk model, and buy & hold strategy for all evaluation metrics.
NUS-I2R: Learning a Combined System for Entity Linking

In this paper, we report the joint participation of NUS and I2R team in Knowledge Base Population at Text analysis conference 2010. For Entity Linking, we analyze IR approaches and SVM classification in the disambiguation stage and develop a supervised learner for combining these approaches. The combined system performs better than the individual components and achieves results much better than the median. Furthermore, according to our error analysis, quite some errors are caused due to the different Wikipedia version is used, which hinder our system to show significant better performance.
Telemedicine and terminology: different needs of context information

Traditionally, communication between healthcare providers, including the provision of physicians with information and knowledge, works quite well because there are implicitly common conventions and assumptions in the collaboration of all involved actors. The basic prerequisite of the communication process between humans is a mutual agreement on syntax and semantics of oral and written language, i.e., of the medical sublanguage. With telemedicine, i.e., the use of telecommunication and informatics in medicine, this prerequisite is no longer sufficient. First, various professionals from different clinical communities, characterized by specialty, nationality, school, etc., share the management of the patient's health. Second, electronically communicated information is more and more intended for processing by computer applications rather than for direct interpretation by human users. Third, the interconnection of distributed heterogeneous software systems in medicine raises the issue of semantic interoperability, especially the problem of data integration. A faithful communication in such a scenario must be based on explicit assumptions behind a message. Interpreting an usually highly context-dependent utterance demands for mechanisms on a pragmatic level in natural language processing. The need for additional processing and integration of the transferred data by the receiving system demands for standardization and mediation, taking into consideration contextual knowledge that cannot entirely be explained and processed with linguistic and terminological approaches. This paper describes different categories of contexts and also different needs of applications concerning context awareness.
Organization of behavioral knowledge from extraction of temporal-spatial features of human whole body motions

This paper describes an approach to structuring behavioral knowledge based on classification of human whole body motions and extraction of the behavioral transitions. The motion patterns are learned by Hidden Markov Models (HMMs), which can be used for classification of the motion patterns. The HMMs are called “motion symbol” since They abstract their corresponding motion patterns. The motion patterns are organized into a hierarchical tree structure (“motion symbol tree”) representing the property of similarity among the motion patterns. The motion patterns are classified based on the motion symbol tree. Concatenated sequences of motion patterns are stochastically represented as transitions between the abstracted motion patterns by using an N-gram Model (“motion symbol graph”), and the transitional relationships of the human behaviors are extracted. The integration of the motion symbol tree and the motion symbol graph makes it possible to recognize motion patterns fast and predict human behavior during observation. The experiments on a large motion dataset validate the proposed framework.
MFTZ-1 reduces constitutive and inducible HIF-1α accumulation and VEGF secretion independent of its topoisomerase II inhibition

The macrolide compound MFTZ‐1 has been identified as a novel topoisomerase II (Top2) inhibitor with potent in vitro and in vivo anti‐tumour activities. In this study, we further examined the effects of MFTZ‐1 on hypoxia‐inducible factor‐1α (HIF‐1α) accumulation, vascular endothelial growth factor (VEGF) secretion and angiogenesis. MFTZ‐1 reduced HIF‐1α accumulation driven by hypoxia or growth factors in human cancer cells. Mechanistic studies revealed that MFTZ‐1 did not affect the degradation of HIF‐1α protein or the level of HIF‐1α mRNA. By contrast, MFTZ‐1 apparently inhibited constitutive and inducible activation of both phosphatidylinositol‐3‐kinase (PI3K)‐Akt and p42/p44 mitogen‐activated protein kinase (MAPK) pathways. Further studies revealed that MFTZ‐1 abrogated the HIF‐1α‐driven increase in VEGF mRNA and protein secretion. MFTZ‐1 also lowered the basal level of VEGF secretion. The results reveal an important feature that MFTZ‐1 can reduce constitutive, HIF‐1α‐independent VEGF secretion and concurrently antagonize inducible, HIF‐1α‐dependent VEGF secretion. Moreover, MFTZ‐1 disrupted tube formation of human umbilical vein endothelial cells (HUVECs) stimulated by hypoxia with low‐concentration serum or by serum at normoxia, and inhibited HUVECs migration at normoxia. MFTZ‐1 also prevented microvessel outgrowth from rat aortic ring. These data reflect the potent anti‐angiogenesis of MFTZ‐1 under different conditions. Furthermore, using specific small interfering RNA targeting Top2α or Top2‐defective HL60/MX2 cells, we showed that MFTZ‐1 affected HIF‐1α accumulation and HUVECs tube formation irrelevant to its Top2 inhibition. Taken together, our data collectively reveal that MFTZ‐1 reduces constitutive and inducible HIF‐1α accumulation and VEGF secretion possibly via PI3K‐Akt and MAPK pathways, eliciting anti‐angiogenesis independently of its Top2 inhibition.
A Kleene Algebra of Tagged System Actors for Reasoning about Heterogeneous Embedded Systems

The tagged signal model (TSM) is a formal framework for modeling heterogeneous embedded systems. In the present work, we provide a representation of tagged systems using the semantics of Kleene algebra. We further illustrate mechanisms for both behavioral transformational verification through equivalence checking and property verification of heterogeneous embedded systems based on this algebraic representation.
American black bear habitat selection in northern Lower Peninsula, Michigan, USA, using discrete-choice modeling

Abstract Since 1990, increases in American black bear (Ursus americanus) population and distribution in the Lower Peninsula of Michigan, USA, have led to positive trends in black bear harvests, sightings, and nuisance reports. Policy makers and wildlife managers can prepare for the difficult task of managing future bear–human interactions by using resource selection models to assess bear habitat selection and predict future bear range expansion. We modeled habitat selection by black bears in the northern Lower Peninsula of Michigan using 6 environmental variables based on radiotelemetry locations from 1991–2000 for 20 males and 35 females. We developed Bayesian random effects discrete-choice models for males and females separately to estimate probability of bear selection of grid cells at 3 spatial resolutions (1 km2, 4 km2, 9 km2). These models weight individual bears and their relocations, allowing inference about both individual and population-level selection characteristics. We assessed goodness-of-fit of individual models using a Bayesian P value that estimated deviance between a simulated dataset and the observed dataset. Models for males at the 9-km2 resolution and for females at 4-km2 resolution fit our data better than others; both indicated that locations of bears were negatively associated with water, small and medium roads, mean patch size, patch size coefficient of variation, edge density, developed land-use, and non-forested wetlands, and positively associated with Shannon's diversity index, aspen (Populus spp.), and forested wetlands. Furthermore, the variability in selection by individual female bears for non-forested wetland and individual male bears for agriculture was large relative to the variability in selection of other land-use or land-cover types. Male bears had more heterogeneity with respect to selection of land-use or land-cover types than female bears. There were significant correlations between male bear age and their respective selection parameter estimates for small roads, medium roads, and developed land-use. Running Bayesian random effects discrete-choice models at multiple resolutions accounted for variability due to unequal sample sizes and bear behavior, and demonstrate the utility of the Bayesian framework for bear management purposes.
The relationship between social fragmentation and sleep among adolescents living in Boston, Massachusetts.

BACKGROUND Sufficient sleep is needed for the healthy development of youth. However, only a small minority of adolescents obtain adequate amounts of sleep. Although individual-level correlates of sleep have been identified, studies investigating the influence of the environment on sleep are warranted. METHODS By using cross-sectional data collected from 1878 urban adolescents living in 38 neighborhoods participating in the 2008 Boston Youth Survey (BYS), we determined the association between neighborhood social fragmentation and sleep. Social fragmentation of each participant's residential neighborhood was composed using 2010 US Census data. Multilevel regression models were used to determine the association between social fragmentation and meeting the recommended hours of sleep (>8.5 h) and sleep duration while controlling for individual-level sex, race, age and nativity. RESULTS Moderate (OR = 0.51, 95% CI = 0.27, 0.97) and high (OR = 0.33, 95% CI = 0.18, 0.61) social fragmentation within the residential neighborhood was associated with a decreased likelihood of obtaining adequate sleep. Those in moderate (β = -23.9, 95% CI = -43.1, -4.8) and high (β = -22.1, 95% CI = -43.3, -0.9) socially fragmented neighborhoods obtained fewer minutes of sleep per night. CONCLUSIONS Social fragmentation may be an important determinant of sleep among youth living in urban settings.