Miracle-dz/UniFAR-FTUs huggingface dataset:
Lifestyle factors and cognitive ageing in the Lothian Birth Cohort 1936: exploring the role of confounding by prior cognitive ability

With an increase in life expectancy, the number of older people affected by cognitive decline and dementia is rising, causing major, global public health concerns. However, there is substantial variation in the rate and magnitude of cognitive decline experienced among ageing individuals. Evidence suggests that many age-associated changes in cognitive functioning can be explained by modifiable lifestyle factors such as smoking, physical activity and diet choices. The weight of the evidence supports the promotion of a healthy lifestyle as an effective strategy for healthy cognitive ageing. Many epidemiological studies have drawn causal conclusions with regard to the positive and direct benefits of lifestyle, yet few have considered the possible confounding role of prior cognitive ability in explaining the lifestyle and cognition relationship in older age. Given the potential for reverse causation, whereby better prior cognitive functioning leads to a greater uptake of healthy behaviours rather than vice versa, it is a mechanism which should be studied, but rarely is. The present thesis focuses on the possible confounding effect of prior cognitive ability on the cross-sectional relationships between lifestyle factors and cognitive ability domains in later-life. The core of the thesis is a series of independent, peer-reviewed (six first-author and one co-author) journal articles in the public domain. Data were derived from the Lothian Birth Cohort 1936 study (n = 1091), a sample of relatively healthy, community-dwelling men and women aged 70 years from Edinburgh, Scotland, for whom childhood (age 11) mental test scores are available. The lifestyle factors investigated were caffeine consumption, alcohol consumption, dietary patterns, body mass index, smoking, serum cholesterol, and physical activity. Cognitive function was assessed across five major ageing-related domains: age 70 IQ (based on the same test that was taken in childhood), general cognitive ability (g), processing speed, memory, and verbal ability. General linear models (ANCOVA) were adjusted for the following covariates: age; sex; childhood cognitive ability; and socioeconomic status (SES). Other potential covariates were additionally adjusted for as necessary. Overall, the positive and significant associations observed between ‘healthy’ lifestyle factors and better cognitive functions at age 70 were consistent with previous research; their effect size was around 1% of the variance in cognitive tests scores. However, these relationships were markedly attenuated (by on average 80%) by a higher childhood
Polarization of resonance X-ray lines from clusters of galaxies

It is known that resonant scattering can distort the surface brightness profiles of clusters of galaxies in X-ray lines. We demonstrate that the scattered line emission should be polarized and possibly detectable with future X-ray polarimeters. Spectrally resolved mapping of a galaxy cluster in polarized X-rays could provide valuable independent information on the physical conditions, in particular element abundances and the characteristic velocity of small-scale turbulent motions, in the intracluster gas. The expected degree of polarization is of the order of 10 per cent for the richest regular clusters (e.g. Coma) and clusters whose X-ray emission is dominated by a central cooling flow (such as Perseus and M87/Virgo).
Self-adaptive clustering data stream algorithm based on SSMC-tree

Due to the data stream is real-time, fast, unlimited, one-pass, clustering data stream requires algorithms which are capable to process the data stream in the limited time and memory. In this paper, we propose a clustering algorithm based on the improved similarity search tree (SSMC-Tree), and introduce buffer, hitchhike processing and local aggregation strategy, it can adapt to different speed data stream. We adopt an outlier processing mechanism by introducing potential core-micro-cluster buffer and outlier micro-cluster buffer to process noise in the data stream. Experimental results show that our algorithm can adapt to the high-speed data stream with noise.
Surface Phonon Polariton in InAlGaN Quaternary Alloys

— III-nitride quaternary In x Al y Ga 1-x - y N alloys have experienced considerable interest as potential materials for optoelectronic applications. Despite these interesting applications and the extensive efforts to understand their fundamental properties, research on its fundamental surface property, i.e., surface phonon polariton (SPP) has not yet been reported. In fact, the SPP properties have been shown to provide application for some photonic devices. Hence, there is an absolute need for thorough studies on the SPP properties of this material. In this work, theoretical study on the SPP modes in InAlGaN quaternary alloys are reported. Attention is focus on the wurtzite ( α -) structure In x Al y Ga 1-x - y N semi-crystal with different In composition, x ranging from 0 to 0.10 and constant Al composition, y = 0.06. The SPP modes are obtained through the theoretical simulation by means of anisotropy model. The characteristics of SP dispersion curves are discussed. Accessible results in terms of the experimental point of view are also given. Finally, the results revealed that the SPP mode of α -In x Al y Ga 1-x - y N semiconductors exhibits two-mode behavior.
Human neutrophil adherence to laminin in vitro. Evidence for a distinct neutrophil integrin receptor for laminin

We used mAbs against polymorphonuclear leukocyte (PMN) surface proteins to investigate the mechanisms by which stimulated human neutrophils (PMNs) adhere in vitro to laminin, the major glycoprotein of mammalian basement membrane. mAb IB4, which is directed against the common beta 2 chain of the CD11/CD18, only partially inhibited the adherence of PMA- stimulated PMNs to both laminin and to subendothelial matrices. In contrast, IB4 completely inhibited PMA-stimulated PMN adherence to gelatin, fibronectin, collagen IV, and endothelial cell monolayers. PMA- stimulated PMNs from a patient with severe congenital CD11/CD18 deficiency also adhered to laminin, but not to gelatin or endothelial cell monolayers. Therefore, PMA-stimulated PMNs adhere to laminin by both CD11/CD18-dependent and CD11/CD18-independent mechanisms. Expression of CD11/CD18-independent adherence to laminin was agonist dependent, occurring after stimulation with the calcium ionophore A23187 and recombinant TNF-alpha, but not with the chemotactic factors FMLP, platelet activating factor, or recombinant human C5a. Expression of CD11/CD18-independent adherence was also divalent cation dependent, occurring in the presence of Mg2+ but not Ca2+ as the sole added divalent cation. The mAbs AIIB2 and 13, which are directed against the beta 1 subunit of the VLA integrins, significantly inhibited the CD11/CD18-independent adherence of normal PMNs to laminin, and completely abolished the adherence of CD11/CD18-deficient PMNs to laminin. Both anti-beta 1 mAbs bound to PMNs, as demonstrated by flow cytometry, and immunoprecipitated a membrane molecule of Mr 130,000 daltons from 125I-labeled, detergent-solubilized PMNs. These data suggest that human PMNs possess beta 1 and beta 2 classes of integrins, and that both mediate PMN adherence.
Fish Consumption Measured during Pregnancy and Risk of Cardiovascular Diseases Later in Life: An Observational Prospective Study

Previous studies have indicated a protective effect of long chain n-3 PUFAs against cardiovascular disease; however, the overall evidence remains uncertain, and there is a general lack of knowledge in the field of cardiovascular epidemiology in women. Therefore, the objective of this study was to explore the association between fish intake and cardiovascular disease among 7429 women from a prospective pregnancy cohort in Aarhus, Denmark, who were followed for 12–17 years. Exposure information derived from a questionnaire sent to the women in gestation week 16, and daily fish consumption was quantified based on assumptions of standard portion sizes and food tables. Information on admissions to hospital was obtained from the Danish National Patient Registry and diagnoses of hypertensive, cerebrovascular and ischaemic heart disease were used to define the outcome: cardiovascular disease. During the follow-up period 263 events of cardiovascular disease were identified. Overall, there was no association between cardiovascular disease and fish intake, confidence intervals for effect estimates in the different fish intake groups were wide, overlapped and for all but one they encompassed unity. Restricting the analysis to women who had reported the same fish intake in a questionnaire in gestation week 30 did not alter these findings. In conclusion, our data from a prospective cohort of relatively young and initially healthy women from Aarhus linked with information from registries could not substantiate a protective effect of fish intake against cardiovascular disease.
Polynomial Methods for Separable Convex Optimization in Unimodular Linear Spaces with Applications

We consider the problem of minimizing a separable convex objective function over the linear space given by a system Mx=0 with M a totally unimodular matrix. In particular, this generalizes the usual minimum linear cost circulation and cocirculation problems in a network and the problems of determining the Euclidean distance from a point to the perfect bipartite matching polytope and the feasible flows polyhedron. We first show that the idea of minimum mean cycle canceling originally worked out for linear cost circulations by Goldberg and Tarjan [J. Assoc. Comput. Mach. , 36 (1989), pp. 873--886. ] and extended to some other problems [T. R. Ervolina and S. T. McCormick, Discrete Appl. Math., 46 (1993), pp. 133--165], [A. Frank and A. V. Karzanov, Technical Report RR 895-M, Laboratoire ARTEMIS IMAG, Universite Joseph Fourier, Grenoble, France, 1992], [T. Ibaraki, A. V. Karzanov, and H. Nagamochi, private communication, 1993], [M. Hadjiat, Technical Report, Groupe Intelligence Artificielle, Faculte des Sciences de Luminy, Marseille, France, 1994] can be generalized to give a combinatorial method with geometric convergence for our problem. We also generalize the computationally more efficient cancel-and-tighten method. We then consider objective functions that are piecewise linear, pure and piecewise quadratic, or piecewise mixed linear and quadratic, and we show how both methods can be implemented to find exact solutions in polynomial time (strongly polynomial in the piecewise linear case). These implementations are then further specialized for finding circulations and cocirculations in a network. We finish by showing how to extend our methods to find optimal integer solutions, to linear spaces of larger fractionality, and to the case when the objective functions are given by approximate oracles.
Experimental verification of TCAD simulation for high-performance SiGe HBTs

The ability of state-of-the-art TCAD simulation to predict the performance of SiGe HBTs with advanced vertical doping profiles is evaluated by a comparison of simulation and experiment. Doping profiles of HBTs with fT > 400GHz were derived from a combination of various experimental techniques and used as input for two-dimensional device simulation with the hydrodynamic transport model. While the present simulations agree with measured DC characteristics, they underestimate measured peak fT values by 11 %.
Automatic Corpus Expansion for Chinese Word Segmentation by Exploiting the Redundancy of Web Information

Currently most of state-of-the-art methods for Chinese word segmentation (CWS) are based on supervised learning, which depend on large scale annotated corpus. However, these supervised methods do not work well when we deal with a new different domain without enough annotated corpus. In this paper, we propose a method to automatically expand the training corpus for the out-of-domain texts by exploiting the redundant information on Web. We break up a complex and uncertain segmentation by resorting to Web for an ample supply of relevant easy-to-segment sentences. Then we can pick out some reliable segmented sentences and add them to corpus. With the augmented corpus, we can re-train a better segmenter to resolve the original complex segmentation. The experimental results show that our approach can more effectively and stably improve the performance of CWS. Our method also provides a new viewpoint to enhance the performance of CWS by automatically expanding corpus rather than developing complicated algorithms or features.
A Finite Gamma Mixture Model-Based Discriminative Learning Frameworks

It is well-known that classification tasks can be approached using either generative models or discriminative ones. While the goal of generative approaches is to learn class-conditional densities, the main goal of discriminative techniques is to learn decision boundaries directly without taking into account class-conditional densities. In classic supervised learning, we would usually represent a given object (an image, for instance) by a vector of D real-valued features and then select a given generative or discriminative approach to perform classification. In many applications, however, the object can be represented by a set (or) bag of vectors. Recent developments in machine learning, along with powerful computational tools, have enabled researchers to develop more sophisticated models to handle such applications using the so-called hybrid generative discriminative models. The main idea is based on exploiting the advantages of both families of models. Thus, the success of such an approach depends on the choice of an appropriate discriminative technique and a suitable generative one. The goal of this paper is to develop a hybrid generative discriminative framework based on support vector machine and Gamma mixture. In particular, we focus on the generation of kernels when examples (images, for instance) are structured data (i.e. described by sets of vectors) modeled by Gamma mixtures. Experimental results on real-world challenging applications, namely 3D shape class recognition, object categorization, and video event analysis, show the effectiveness of the proposed framework.
A Multidimensional Software Engineering Course

Software engineering (SE) is a multidimensional field that involves activities in various areas and disciplines, such as computer science, project management, and system engineering. Though modern SE curricula include designated courses that address these various subjects, an advanced summary course that synthesizes them is still missing. Such a course would enable young practitioners to get a comprehensive description of SE, to experience a genuine software development process, and to appreciate the relations and tradeoffs between the various domains of SE. This paper proposes a multidimensional SE course framework aimed at giving SE students just such comprehensive, cross-paradigm, practical, and theoretical experience and background. The course is organized along four axes: a) fundamentals of SE; b) practices and tools; c) productization; and d) technology evolution. Each of these axes, in themselves multifaceted, enables an examination of SE on various scales and from different perspectives; together they create a holistic multidimensional description of SE. The course is evaluated according to accepted criteria highlighting the course scope, pedagogic decisions, and relevance. The authors also describe their experience of teaching the course three times in the Tel Aviv University and the academic college of Tel-Aviv-Yaffo, Israel.
Learning a multi-size patch-based hybrid kernel machine ensemble for abnormal region detection in colonoscopic images

When detecting abnormalities in colonoscopic images, the location, shape and size of the abnormal regions in the image are unknown and vary across images. It is difficult to determine the appropriate patch-size for patch-based approach. So multi-size patches are used simultaneously to represent the image regions and an ensemble is constructed in which each classifier handles one patch size. The combination of classifiers trained using multiple-size patches can recognize abnormal regions more effectively than only using single-size patches. The classification of the image patches can be performed using a discriminative binary support vector machine (SVM) or a recognition-based one-class SVM. Integration of the two types of SVMs is expected to further improve abnormal region detection. Experimental results show the good performance of our proposed ensemble.
Advances in Group-Based Trajectory Modeling and an SAS Procedure for Estimating Them

This article is a follow-up to Jones, Nagin, and Roeder (2001), which described an SAS procedure for estimating group-based trajectory models. Group-based trajectory is a specialized application of finite mixture modeling and is designed to identify clusters of individuals following similar progressions of some behavior or outcome over age or time. This article has two purposes. One is to summarize extensions of the methodology and of the SAS procedure that have been developed since Jones et al. The other is to illustrate how group-based trajectory modeling lends itself to presentation of findings in the form of easily understood graphical and tabular data summaries.
Ill-Conditioned Convex Processes and Linear Inequalities

We prove the smallest possible norm of a linear perturbation making a closed convex process nonsurjective is the inverse of the norm of the inverse process. This generalizes the fundamental property of the condition number of a linear map. We then apply this result to strengthen a theorem of Renegar measuring the size of perturbation necessary to make an inequality system inconsistent.
Domain knowledge acquisition and plan recognition by probabilistic reasoning

In this paper, a probabilistic framework for acquiring domain knowledge from heterogeneous corpora is introduced. The acquired information is used for intelligent human-computer interaction through the web. The application selected for the framework experimentation was education on issues of chemotherapy of nosocomial and community acquired pneumonia. Contrasting to existing educational dialogue engines which use handcrafted knowledge of the application domain, our approach utilizes automatic encoding of the semantic model of the application, based on learning Bayesian networks from past user questions. The structure of the networks as well as the conditional probability distributions are computed automatically from dialogue corpora, thus eliminating the tedious process of manual insertion of domain knowledge. Furthermore, we attempt to overcome the significant issue of limited vocabulary by incorporating a methodology which estimates semantic similarities of words not found within the system’s vocabulary and probabilistically associates them with those who appear.
Improving Data Dissemination in MANET

Choosing appropriate data dissemination strategies are crucial in mobile ad hoc networks (MANET) due to the frequent topology changes. There are two main factors which infect the data dissemination in MANETs. One is the dynamics and the other is the resource constrains. In this paper, we analyze the features of epidemic routing, give out the performance inflexion according to the nodes density. We show that, if don' t consider the memory, energy and bandwidth constrain of the nodes, disseminating only report is the most energy spare scheme and could leads smaller system delay when the size of query and report are same. We also introduce some ranking based dissemination strategy which could take a globe control of the system.
Title: Discussion Stutterer-nonstutterer Comparisons

The relationship between communication attitude, anxiety, and depression in stutterers and non-stutterers. Abstract: Examined self-perceptions of general state and trait anxiety, depression, and communication attitude in matched groups of 52 stutterers and 52 nonstutterers (aged 16– 68 yrs). Measures included the Beck Depression Inventory and the State-Trait Anxiety Inventory. Anxiety and depression were not related to self-ratings of stuttering severity. Communication attitude was negative and became increasingly negative as self-ratings of stuttering became more severe. Stutterers grouped by severity rating differed in the strength of the relation between measures of communication attitude, anxiety, and depression. Findings suggest that the anxiety of stutterers is restricted to their attitude toward communication situations and is a rational response to negative communication experiences. People who stutter are frequently viewed as more anxious than nonstutterers and as being depressed. Further, a strong and pervasive stereotype is held by nonstutterers that people who stutter are guarded, nervous, and tense. This study examined self-perceptions of general state and trait anxiety, depression, and communication attitude in matched groups of stutterers and nonstutterers. Results refute the assertion that people who stutter are more anxious or depressed than those who do not. Anxiety and depression are not related to self-ratings of stuttering severity. Communication attitude is negative for this group of people who stutter and becomes increasingly negative as self-ratings of stuttering become more severe. People who stutter, grouped by severity rating, differed in the strength of the relation between measures of communication attitude, anxiety, and depression. Findings suggest that the anxiety of people who stutter is restricted to their attitude towards communication situations and that it is a rational response to negative communication experiences. Anxiety plays a central role in many theories of stuttering (Bloodstein, 1987). Anxiety is included in theories of the etiology of the stuttering disorder, is related causally to the moment of stuttering, and is often described as a reaction to stuttering behaviors that can maintain these behaviors. Johnson's (1942) diagnosogenic theory proposes that children begin to stutter as a reaction to parental anxiety, pressure, and criticism directed toward normal childhood nonfluencies. Parental concern about the child's speech increases the child's anxiety about speech. As a consequence, the child's speech becomes dysfluent. Classical conditioning theories propose that a person who stutters learns to associate speech with negative emotional states such as anxiety, fear, and stress (Negative emotions become classically conditioned so that anxiety and/or fear become …
Towards Incremental Grounding in Tuffy

Markov Logic Networks (MLN) have become a powerful framework in logical and statistical modeling. However, most of the current MLN implementations are in-memory, and cannot scale up to large data sets. Only recently, Tuffy addresses the scalability issue by using a pure RDB-based implementation. Inference in Tuffy could be divided into two stages: grounding and search. The grounding stage substitutes evidence into MLN rules to obtain a set of ground clauses, which is used in the search stage to find the most likely world of the MLN. However, the ground clauses will change if underlying evidence is updated, and redoing grounding from scratch to obtain the new set of ground clauses is costly. In this paper, we study the problem of incremental grounding in Tuffy. We propose a 2-phase update algorithm, which divides the update procedure into two stages. The first stage tries to find clauses that are unchanged after updating evidence, and can be done completely in memory, while the second stage tries to find remaining new clauses. We prove the correctness of the algorithm, and our experimental evaluation demonstrates its efficiency.