Miracle-dz/UniFAR-FTUs huggingface dataset:
Glioblastoma-associated microglia and macrophages: targets for therapies to improve prognosis

Glioblastoma is the most common and most malignant primary adult human brain tumour. Diagnosis of glioblastoma carries a dismal prognosis. Treatment resistance and tumour recurrence are the result of both cancer cell proliferation and their interaction with the tumour microenvironment. A large proportion of the tumour microenvironment consists of an inflammatory infiltrate predominated by microglia and macrophages, which are thought to be subverted by glioblastoma cells for tumour growth. Thus, glioblastoma-associated microglia and macrophages are logical therapeutic targets. Their emerging roles in glioblastoma progression are reflected in the burgeoning research into therapeutics directed at their modification or elimination. Here, we review the biology of glioblastoma-associated microglia and macrophages, and model systems used to study these cells in vitro and in vivo. We discuss translation of results using these model systems and review recent advances in immunotherapies targeting microglia and macrophages in glioblastoma. Significant challenges remain but medications that affect glioblastoma-associated microglia and macrophages hold considerable promise to improve the prognosis for patients with this disease.
On the Size of Reactive Plans

One of the most widespread approaches to reactive planning is Schoppers' universal plans. We propose a stricter definition of universal plans which guarantees a weak notion of soundness not present in the original definition. Furthermore, we isolate three different types of completeness which capture different behaviours exhibited by universal plans. We show that universal plans which run in polynomial time and are of polynomial size cannot satisfy even the weakest type of completeness unless the polynomial hierarchy collapses. However, by relaxing either the polynomial time or the polynomial space requirement, the construction of universal plans satisfying the strongest type of completeness becomes trivial.
Physiological Adjustments to Arid and Mesic Environments in Larks (Alaudidae)

Because deserts are characterized by low food availability, high ambient temperature extremes, and absence of drinking water, one might expect that birds that live in these conditions exhibit a lower basal metabolic rate (BMR), reduced total evaporative water loss (TEWL), and greater ability to cope with high air temperatures than their mesic counterparts. To minimize confounding effects of phylogeny, we compared the physiological performance of four species of larks at ambient temperatures (Ta's) ranging from 0° to 50°C: hoopoe larks (Alaemon alaudipes) and Dunn’s larks (Eremalauda dunni) live in hot and dry deserts, whereas skylarks (Alauda arvensis) and woodlarks (Lullula arborea) occur in temperate mesic areas. Mass‐adjusted BMR and TEWL were indistinguishable between hoopoe lark and Dunn’s lark and between skylark and woodlark. When grouping the data of the two desert larks in one set and the data of the two mesic larks in another, desert larks are shown to have 43% lower BMR levels and 27% lower TEWL values than the mesic species. Their body temperatures (Tb's) were 1.1°C lower, and the minimal dry heat transfer coefficients (h) were 26% below values for the mesic larks. When Ta exceeded Tb, the h of hoopoe larks and Dunn’s larks was high and indistinguishable from h at 40°C, in contrast to the prediction that h should be decreased to minimize heat gain through conductance, convection, or radiation from the environment when Ta exceeds Tb.
Efficient Lifting of MAP LP Relaxations Using k-Locality

Inference in large scale graphical models is an important task in many domains, and in particular for probabilistic relational models (e.g,. Markov logic networks). Such models often exhibit considerable symmetry, and it is a challenge to devise algorithms that exploit this symmetry to speed up inference. Here we address this task in the context of the MAP inference problem and its linear programming relaxations. We show that symmetry in these problems can be discovered using an elegant algorithm known as the kdimensional Weisfeiler-Lehman (k-WL) algorithm. We run k-WL on the original graphical model, and not on the far larger graph of the linear program (LP) as proposed in earlier work in the eld. Furthermore, the algorithm is polynomial and thus far more practical than other previous approaches which rely on orbit partitions that are GI complete to nd. The fact that k-WL can be used in this manner follows from the recently introduced notion of k-local LPs and their relation to Sherali Adams relaxations of graph automorphisms. Finally, for relational models such as Markov logic networks, the benets of our approach are even more dramatic, as we can discover symmetries in the original domain graph, as opposed to running lifting on the much larger grounded model.
Ceteris Paribus Preference Elicitation with Predictive Guarantees

CP-networks have been proposed as a simple and intuitive graphical tool for representing conditional ceteris paribus preference statements over the values of a set of variables. While the problem of reasoning with CP-networks has been receiving some attention, there are very few works that address the problem of learning CP-networks. In this work we investigate the task of learning CP-networks, given access to a set of pairwise comparisons. We first prove that the learning problem is intractable, even under several simplifying assumptions. We then present an algorithm that, under certain assumptions about the observed pairwise comparisons, identifies a CP-network that entails these comparisons. We finally show that the proposed algorithm is a PAC-learner, and, thus, that the CP-networks it induces accurately predict the user's preferences on previously unseen situations.
[Auditory processing maturation in children with and without learning difficulties].

BACKGROUND Auditory processing maturation in school children with and without learning difficulties. AIM To verify response improvement with the increase in age of the auditory processing skills in school children with ages ranging from eight to ten years, with and without learning difficulties and to perform a comparative study. METHOD Eighty-nine children without learning complaints (Group 1) and 60 children with learning difficulties (Group II) were assessed. The used auditory processing tests were: Pediatric Speech Intelligibility (PSI), Speech in Noise, Dichotic Non-Verbal (DNV) and Staggered Spondaic Word (SSW). RESULTS A better performance was observed for Group I between the ages of eight and ten in all of the used tests. However, the observed differences were statistically significant only for PSI and SSW. For Group II, a better performance was also observed with the increase in age, with statistically significant differences for all of the used tests. Comparing the results between Groups I and II, a better performance was verified for children with no learning difficulties, in the three age groups, in PSI, DNV and SSW. CONCLUSION A statistically significant improvement was verified in the responses of the auditory processing with the increase in age, for the ages between eight and ten years, in children with and without learning difficulties. In the comparative study, it was verified that children with learning difficulties presented a lower performance in all of the used tests in the three age groups. This suggests, for this group, a delay in the maturation of the auditory processing skills.
Understanding How Learning Affects Agreement Process in Social Networks

In this article, we study how learning affects the dynamics of opinion formation in a population of agents modeled through the so-called naming game. This agent-based model captures the essential features of the agreement dynamics by means of a memory-driven negotiation process. We analyze the impact of learning in such social agreement model through a control parameter describing the resistance toward learning. We show that there exists a critical above which the consensus time diverges. In particular, we embed this model on various interaction topologies and real-world face-to-face interaction data and, thereby, point out the important differences in the agreement dynamics that take place in a real time-varying social settings vis-a-vis different static social settings. Remarkably, in all types of topology, we observe that beyond the critical value of, the number of unique words increase manifold in the system and hence the time to consensus diverges possibly pointing to an universal aspect of language learning. In order to support the simulation results, we further develop a web-based online game - the `tagging game' - which is a close correlate of the naming game and observe the game dynamics when human subjects are exposed to play the game. Remarkably, similar characteristic properties as that of the modified naming game is observed here even while different people from different geographical location play the game. This shows that synthetic modeling has nowadays reached the maturity to answer certain long-standing questions in cognitive science reasonably well.
Author's Personal Copy Understanding the relationship between obesity and positive and negative affect: The role of psychosocial mechanisms §

We examined the relationship between body mass index (BMI) and positive and negative affect, and evaluated whether this relationship is mediated (or suppressed) by physical health, intrusiveness of weight on physical functioning, and distressing interpersonal interactions. Analyses were based on a national sample of more than 3,000 adults ages 25 to 74. Class II (BMI 35– 39.9) and Class III (BMI 40) obesity were associated with more frequent negative affect and less frequent positive affect, even after demographic and socioeconomic status characteristics were controlled. After the purported pathway variables were controlled, however, obese I persons reported significantly more frequent positive affect, while overweight, obese I, and obese II persons reported significantly less frequent negative affect, compared to normal weight persons. These patterns did not differ significantly by race or gender. Our findings suggest that excessive body weight is not necessarily distressing, yet the physical and interpersonal strains associated with obesity may impair one’s mood. We discuss the implications for policy and practice. # 2007 Elsevier Ltd. All rights reserved.
The hidden face of job insecurity

Drawing on nationally representative data for British employees, the article argues for a more comprehensive concept of job insecurity, including not only job tenure insecurity but also job status insecurity, relating to anxiety about changes to valued features of the job. It shows that job status insecurity is highly prevalent in the workforce and is associated with different individual, employment and labour market characteristics than those that affect insecurity about job loss. It is also related to different organizational contexts. However, the article also shows that the existence of effective mechanisms of employee participation can reduce both types of job insecurity.
Gender, sex hormones and pulmonary hypertension

Most subtypes of pulmonary arterial hypertension (PAH) are characterized by a greater susceptibility to disease among females, although females with PAH appear to live longer after diagnosis. While this “estrogen paradox” of enhanced female survival despite increased female susceptibility remains a mystery, recent progress has begun to shed light upon the interplay of sex hormones, the pathogenesis of pulmonary hypertension, and the right ventricular response to stress. For example, emerging data in humans and experimental models suggest that estrogens or differential sex hormone metabolism may modify disease risk among susceptible subjects, and that estrogens may interact with additional local factors such as serotonin to enhance the potentially damaging chronic effects of estrogens on the pulmonary vasculature. Regardless, it remains unclear why not all estrogenic compounds behave equally, nor why estrogens appear to be protective in certain settings but detrimental in others. The contribution of androgens and other compounds, such as dehydroepiandrosterone, to pathogenesis and possibly treatment must be considered as well. In this review, we will discuss the recent understandings on how estrogens, estrogen metabolism, dehydroepiandrosterone, and additional susceptibility factors may all contribute to the pathogenesis or potentially to the treatment of pulmonary hypertension, by evaluating current human, cell-based, and experimental model data.
Geometric Spanner Networks Master Thesis

The topic of this thesis is geometric spanner networks. Geometric spanners are networks defined by a set of points P and a set of straight line segments E, called edges, that connect the points in P . The aim of spanners is to balance the total number of edges in the network against the largest detour one has to make when taking the shortest path of edges from an arbitrary point in P to any other. This largest detour defines the spanning ratio of the spanner. In this thesis we restrict our attention to the case where the points in P are located in the 2-dimensional plane. Within the area of geometric spanners we address two subtopics. First we propose a new type of spanner and prove that it has spanning ratio 1.998, and consists of at most 8n − 6 edges. We furthermore show it has the desirable property that the shortest path between any two vertices consists of at most 53.2 log n edges. This spanner is based on the Delaunay triangulation, and is constructed by means of the hierarchical data structure introduced by Kirkpatrick [18]. Using the same construction method, we show that it is possible to build a spanner with similar properties using any θk-graph as a base. In particular, this spanner has spanning ratio 1 1−2 sin(π/k) , consists of kn edges, and has a short path between any two vertices of O(log n) edges. The second part of this thesis focuses on a specific spanner called the θ5-graph. A special version of the θ5-graph is the one where we introduce a set S of line segments, called constraints. These constraints prevent us from drawing edges crossing them. Though (constrained) θk-graphs have been studied extensively, and the spanning ratio of most of these graphs have been (tightly) proved, the spanning ratio of the constrained θ5-graph remains undetermined so far. In this thesis we make an attempt to bound it by generalizing the approach Bose et al. [7] used to bound the spanning ratio of the θ5-graph in the unconstrained setting. Unfortunately it turns out that their approach cannot be generalized easily to the constrained setting. We nonetheless present the proof to the point where it breaks down, and discuss alternative strategies that were considered. Geometric Spanner Networks iii
Content of quality-of-life instruments is affected by item-generation methods.

BACKGROUND Methods used to generate items for complex measurement scales are heterogeneous and probably produce heterogeneous data, yet nothing is known about the advantages of one method over another. OBJECTIVE We aimed to compare methods of generating items for tools designed to measure quality-of-life for patients. METHODS We used five methods to develop a quality-of-life instrument for patients with lower-limb osteoarthritis: individual interviews with patients involving two different techniques (semi-structured and cognitive), individual interviews with health professionals, and focus groups of patients and health professionals. The process generated 80 items, of which 37 were excluded after content and psychometric analysis. With the final 43-item scale used as a 'reference standard', we estimated the contribution of each method. RESULTS For health professionals, the focus group and individual interviews produced 35 and 81% of the items, respectively. For patients, the focus groups produced 74% of the items and both interview techniques 100% of the items. Health professionals provided a narrower picture of the effects of the disease on quality-of-life. Focus groups contributed less to social domains than did individual interviews. The two patient interview techniques highlighted different themes. CONCLUSION In developing a complex measurement scale for patients, we found individual interviews with patients the best method for formulating items; other methods such as physician interviews and focus groups contributed no additional information. Reports of instrument generation should include details of the item-generation step, the methods used to develop items and the number of people involved.
Refactoring Java generics by inferring wildcards, in practice

Wildcard annotations can improve the generality of Java generic libraries, but require heavy manual effort. We present an algorithm for refactoring and inferring more general type instantiations of Java generics using wildcards. Compared to past approaches, our work is practical and immediately applicable: we assume no changes to the Java type system, while taking into account all its intricacies. Our system allows users to select declarations (variables, method parameters, return types, etc.) to generalize and considers declarations not declared in available source code. It then performs an inter-procedural flow analysis and a method body analysis, in order to generalize type signatures. We evaluate our technique on six Java generic libraries. We find that 34% of available declarations of variant type signatures can be generalized - i.e., relaxed with more general wildcard types. On average, 146 other declarations need to be updated when a declaration is generalized, showing that this refactoring would be too tedious and error-prone to perform manually.
Signal Transient and Crosstalk Model of Capacitively and Inductively Coupled VLSI Interconnect Lines

Analytical compact form models for the signal transients and crosstalk noise of inductive- effect-prominent multi-coupled RLC lines are developed. Capacitive and inductive coupling effects are investigated and formulated in terms of the equivalent transmission line model and transmission line parameters for fundamental modes. The signal transients and crosstalk noise expressions of two coupled lines are derived by using a waveform approximation technique. It is shown that the models have excellent agreement with SPICE simulation.
Automatic Lyrics-based Music Genre Classification in a Multilingual Setting

A large amount of research has been undertaken with regard to the classification of lyrics into genres, but most of this work has featured solely English lyrics. This study investigates the implications of classifying a multilingual database and the effectiveness of a number of techniques and algorithms for doing so. Part of this involves the creation of a high-quality dataset for use in this research. This paper finds that there are significant challenges in preprocessing multilingual text, and that traditional techniques like stemming and stop words may actually do more harm than good in such circumstances. It also finds that classes with strong language bias may be more likely to perform better than those with multiple languages.
Enlarged FAMSBASE: protein 3D structure models of genome sequences for 41 species

Enlarged FAMSBASE is a relational database of comparative protein structure models for the whole genome of 41 species, presented in the GTOP database. The models are calculated by Full Automatic Modeling System (FAMS). Enlarged FAMSBASE provides a wide range of query keys, such as name of ORF (open reading frame), ORF keywords, Protein Data Bank (PDB) ID, PDB heterogen atoms and sequence similarity. Heterogen atoms in PDB include cofactors, ligands and other factors that interact with proteins, and are a good starting point for analyzing interactions between proteins and other molecules. The data may also work as a template for drug design. The present number of ORFs with protein 3D models in FAMSBASE is 183 805, and the database includes an average of three models for each ORF. FAMSBASE is available at http://famsbase.bio. nagoya-u.ac. jp/famsbase/.
A Software Architecture for Provision of Context-Aware Web-based m-Commerce Applications

Mobile commerce is gaining significant importance in the recent years as an alternative option of e-commerce for the moving user. The mobile applications through which m-commerce takes place operate in highly dynamic environments with diverse characteristics and under varying conditions. The characteristics and conditions of these environments -- called context -- should be exploited in order to provide adaptive services, services that offer a suitable user experience and deliver innovative and enhanced capabilities that will facilitate user interaction, attract new customers and maintain existing ones. The goal of adaptivity is realized through the adaptation of user interface, functionality and content of applications using the context information. Therefore, context-awareness constitutes an essential aspect -- almost a requirement -- of mobile services. In order to realize context-aware services, there is a necessity to capture the context information from its sources, process and distribute it to the software components that will use it. In this paper, we propose a software architecture for context information management suitable for m-commerce applications. We describe the functionality and characteristics of its components, as well as the interaction among these different components.
Optimal adaptive algorithms for finding the nearest and farthest point on a parametric black-box curve

We consider a general model for representing and manipulating parametric curves, in which a curve is specified by a black box mapping a parameter value between 0 and 1 to a point in Euclidean <i>d</i>-space. In this model, we consider the nearest-point-on-curve and farthest-point-on-curve problems: given a curve <i>C</i> and a point <i>p</i>, find a point on <i>C</i> nearest to <i>p</i> or farthest from <i>p</i>. In the general black-box model, no algorithm can solve these problems. Assuming a known bound on the speed of the curve (a Lipschitz condition),the answer can be estimated up to an additive error of <i>ε</i> using <i>O</i>(1/<i>ε</i>) samples, and this bound is tight in theworst case. However, many instances can be solved with substantially fewer samples, and we give algorithms that adapt to the inherent difficulty of the particular instance, up to a logarithmic factor. More precisely, if OPT(<i>C,p,ε</i>)is the minimum number of samples of <i>C</i> that every correct algorithm must perform to achieve tolerance <i>ε</i>, then our algorithm performs <i>O</i>(OPT(<i>C,p,ε</i>)log(<i>ε</i><sup>-1</sup>/OPT(<i>C,p,ε</i>))) samples. Furthermore, any algorithm requires Ω(<i>k</i>log(<i>ε</i><sup>-1</sup>/<i>k</i>))samples for some instance <i>C'</i> with OPT(<i>C',p,ε</i>) = <i>k</i>; except that, for the nearest-point-on-curve problem when the distance between <i>C</i> and <i>p</i> is less than <i>ε</i>, OPT is 1 but the upper and lower bounds on the number of samples are both Θ(1/<i>ε</i>). When bounds on relative error are desired, we give algorithms that perform <i>O</i>(OPT log(2+(1+<i>ε</i><sup>-1</sup>)) m<sup>-1</sup>/OPT))samples (where <i>m</i> is the exact minimum or maximum distance from <i>p</i> to <i>C</i>) and prove that Ω(OPT log(1/<i>ε</i>)) samples are necessary on some problem instances.
Scaling Phrase-Based Statistical Machine Translation to Larger Corpora and Longer Phrases

In this paper we describe a novel data structure for phrase-based statistical machine translation which allows for the retrieval of arbitrarily long phrases while simultaneously using less memory than is required by current decoder implementations. We detail the computational complexity and average retrieval times for looking up phrase translations in our suffix array-based data structure. We show how sampling can be used to reduce the retrieval time by orders of magnitude with no loss in translation quality.