Miracle-dz/UniFAR-FTUs huggingface dataset:
Mass quantization of the Schwarzschild black hole

We examine the Wheeler-DeWitt equation for a static, eternal Schwarzschild black hole in Kucha{hacek r}-Brown variables and obtain its energy eigenstates. Consistent solutions vanish in the exterior of the Kruskal manifold and are nonvanishing only in the interior. The system is reminiscent of a particle in a box. States of definite parity avoid the singular geometry by vanishing at the origin. These definite parity states admit a discrete energy spectrum, depending on one quantum number which determines the Arnowitt-Deser-Misner mass of the black hole according to a relation conjectured long ago by Bekenstein M{approximately}{radical} (n) M{sub p}. If attention is restricted only to these quantized energy states, a black hole is described not only by its mass but also by its parity. States of indefinite parity do not admit a quantized mass spectrum. {copyright} {ital 1999} {ital The American Physical Society}
A novel ensemble vision based deep web data extraction technique for web mining applications

Web Content extraction is the task of extracting structured information from unstructured and semi-structured machine-readable documents. In most of the cases this activity concerns processing human language texts by means of natural language processing (NLP). Recent activities in multimedia document processing like automatic annotation and content extraction out of images and audio, video could be seen as information extraction. Similarly, information retrieval is the process which is based on user's query. The retrieved information is to be extracted using the web content extraction concept. The Challenges for this type of web page content extraction is increasing now-a-days. In this work, we study the problem of automatically extracting the contents from the web pages. Many more researches have been done to address this problem. The existing approaches have some limitations such as that, it has no sufficient power to deal with the large number of web pages and also that they are web-page-programming- language(HTML) dependent. Our proposed work is to overcome the limitations of the existing system. This work deals with information retrieval process in which the Vision based approach is applied, which helps to extract both images and text from the web pages. In fact most of researches show that when a page is presented to the user, the spatial and visual features play a very important role because they help the user to unconsciously divide the webpage into several semantic parts. Hence, proposed work focus on the primary visual features of a web page. The extraction is carried out on the basis of these features. This approach can gain a better performance when compared with other traditional methods.
Testing for Temporal Asymmetry in the Price-Volume Relationship

This paper presents some evidence for the presence of temporal asymmetry in the price-volume relationship in the crude oil futures market. By using threshold models we show that there is bidirectional causality between volume and prices, whereas the conventional model that assumes symmetry can only detect unidirectional causality. The results also show that the price-volume relationship is asymmetric, in the sense that negative price and volume changes have stronger effects (on each other) than positive changes. Some explanations for asymmetry in the price-volume relationship are suggested.
Identifying Common Substructure for Incremental Methods

In this paper we solve the problem of identifying a “matching” between two logic circuits or “networks”. A matching is a functions that maps each gate or “node” in the new circuit into one in the old circuit (if a matching does not exist it maps it to null). We present both an exact and a heuristic way to solve the maximal matching problem. The matching problem does not require any input correspondences; the purpose is to identify structurally identical regions in the networks. We apply this solution to the problem of incremental design. Logic design is usually an iterative process where errors are corrected and optimizations performed repeatedly. A designer rectifies, re-optimizes, and rechecks a design many times. In practice, it is common for small, incremental changes to be made to the design, rather than changing the entirety of the design. Currently, each time the system is modified, the entire set of computations (synthesis,verification) are repeated from the beginning. This results in unnecessary re-computation of information, which can be avoided by re-using results of a previous iteration and information about changes to the system. Synthesis and verification tools that recognize these sequences of slightlydiffering inputs may be able to outperform their counterparts that discard all previous work. This work is concerned with detecting what information has changed in a design, and what information may be re-utilized.
Interpretation of Regressions with Multiple Proxies

Multiple proxy variables are typically available for an unobserved explanatory variable in a regression. We provide a procedure by which the coefficient of interest can be estimated from a regression in which all the proxies are included simultaneously. This estimator is superior in large samples to the common practice of creating a summary measure of the proxy variables. We examine the relationship between parents' income and children's reading test scores in the United States, and between parents' assets and children's school enrollment in India, and demonstrate that the reduction in attenuation bias from a better use of proxy variables can be significant.
New Strategies in Estrogen Receptor–Positive Breast Cancer

Endocrine therapy has led to a significant improvement in outcomes for women with estrogen receptor–positive (ER+) breast cancer. Current questions in the adjuvant setting include the optimal duration of endocrine therapy, and the accurate molecular prediction of endocrine responsiveness using gene array–based assays compared with ER expression itself. In advanced disease, novel selective estrogen receptor antagonists (SERM) have failed to make an impact, although the pure ER antagonist fulvestrant may have a role, albeit optimal dose and sequence remain unclear. Overcoming de novo or acquired endocrine resistance remains critical to enhancing further the benefit of existing endocrine therapies. Recent progress has been made in understanding the molecular biology associated with acquired endocrine resistance, including adaptive “cross-talk” between ER and peptide growth factor receptor pathways such as epidermal growth factor receptor (EGFR)/human epidermal growth factor receptor 2 (HER2). Future strategies that are being evaluated include combining endocrine therapy with inhibitors of growth factor receptors or downstream signaling pathways, to treat or prevent critical resistance pathways that become operative in ER+ tumors. Preclinical experiments have provided great promise for this approach, although clinical data remain mixed. Enriching trial recruitment by molecular profiling of different ER+ subtypes will become increasingly important to maximize additional benefit that new agents may bring to current endocrine therapies for breast cancer. Clin Cancer Res; 16(7); 1979–87. ©2010 AACR.
A Preliminary Investigation into Predictive Models for Adverse Drug Events

Adverse drug events are a leading cause of danger and cost in health care. We could reduce both the danger and the cost if we had accurate models to predict, at prescription time for each drug, which patients are most at risk for known adverse reactions to that drug, such as myocardial infarction (MI, or “heart attack”) if given a Cox2 inhibitor, angioedema if given an ACE inhibitor, or bleeding if given an anticoagulant such as Warfarin. We address this task for the specific case of Cox2 inhibitors, a type of non-steroidal anti-inflammatory drug (NSAID) or pain reliever that is easier on the gastrointestinal system than most NSAIDS. Because of the MI adverse drug reaction, some but not all very effective Cox2 inhibitors were removed from the market. Specifically, we use machine learning to predict which patients on a Cox2 inhibitor would suffer an MI. An important issue for machine learning is that we do not know which of these patients might have suffered an MI even without the drug. To begin to make some headway on this important problem, we compare our predictive model for MI for patients on Cox2 inhibitors against a more general model for predicting MI among a broader population not on Cox2 inhibitors.
Cluster categories for algebras of global dimension 2 and quivers with potential

Soient k un corps et A une k-algebre de dimension finie et de dimension globale ≤ 2. On construit une categorie triangulee C A associee a A, qui est triangle-equivalente a la categorie amassee C A si A est hereditaire. Lorsque C A est Hom-finie, on prouve qu'elle est 2-Calabi-Yau et munie d'un objet amas-basculant canonique. Cette nouvelle classe de categories contient certaines sous-categories stables de modules sur une algebre preprojective introduite par Geiss-Leclerc-Schroer et par Buan-Iyama-Reiten-Scott. Ces resultats s'appliquent aussi aux carquois a potentiel. Plus precisement, on introduit une categorie amassee C(Q,W) associee a un carquois a potentiel (Q,W). Quand il est Jacobi-fini, on prouve que cette categorie est munie d'un objet amas-basculant dont l'algebre d'endomorphismes est isomorphe a l'algebre jacobienne.
Inequalities for the minimum eigenvalue of M-matrices

Let A be a nonsingular M-matrix, and τ(A) denote its minimum eigenvalue. Shivakumar et al. [SIAM J. Matrix Anal. Appl. , 17(2):298-312, 1996] presented some bounds of τ(A) when A is a weakly chained diagonally dominant M-matrix. The present paper establishes some new bounds of τ(A) for a general nonsingular M-matrix A. Numerical examples show that the results obtained are an improvement over some known results in certain cases.
A Multi-objective Optimization Strategy for Content Delivery from Multihomed Stub IP / MPLS Networks

how to simultaneously optimize several objectives, such as: i) minimizing the operative costs; ii) guaranteeing a set of end-to-end traffic constraints; while iii) optimizing the consumption of resources along their networks. When the target is to consider all the objectives together, the optimal accomplishment of each and all of the individual objectives is typically unachiev-able, since some of the objectives are actually contenders. Therefore, most CPs focus on decision making algorithms that suitably balance the inherent trade-offs between the different objectives. Offline multi-objective optimization and evolutionary algorithms offer the natural tool to formulate and deal with this kind of problem. In this paper, we formulate a multi-objective optimization problem, with focus on the establishment of a Pareto optimal set of MPLS Label Switched Paths (LSPs) from a multihomed stub CP. This establishment of LSPs offers a suitable offline mechanism to accommodate aggregate traffic flows with given constraints towards the set of major content consumers.
Search the web x.0: mining and recommending web-mediated processes

Nowadays, people have been increasingly interested in exploiting Web Search Engines (WSEs) not only for having access to simple Web pages, but mainly for accomplishing even complex activities, namely Web-mediated processes (or taskflows). Thus, users' information needs will become more complex, and Web search and recommender systems should change accordingly for dealing with this shift. We claim that such taskflows and their composing tasks are implicitly present in users' minds when they interact with a WSE to access the Web. Our first research challenge is thus to evaluate this belief by analyzing a very large, long-term log of queries submitted to a WSE, and associating meaningful semantic labels with the extracted tasks (i.e., clusters of related queries) and taskflows. This large knowledge base constitutes a good starting point for building a model of users' behaviors. The second research challenge is to devise a novel recommender system that goes beyond the simple query suggestion of modern WSEs. Our system has to exploit the knowledge base of Web-mediated processes and the learned model of users' behaviors, to generate complex insights and task-based suggestions to incoming users while they interact with a WSE.
"Sheldon speaking, Bonjour!": Leveraging Multilingual Tracks for (Weakly) Supervised Speaker Identification

We address the problem of speaker identification in multimedia data, and TV series in particular. While speaker identification is traditionally a supervised machine-learning task, our first contribution is to significantly reduce the need for costly preliminary manual annotations through the use of automatically aligned (and potentially noisy) fan-generated transcripts and subtitles. We show that both speech activity detection and speech turn identification modules trained in this weakly supervised manner achieve similar performance as their fully supervised counterparts (i.e. relying on fine manual speech/non-speech/speaker annotation). Our second contribution relates to the use of multilingual audio tracks usually available with this kind of content to significantly improve the overall speaker identification performance. Reproducible experiments (including dataset, manual annotations and source code) performed on the first six episodes of The Big Bang Theory TV series show that combining the French audio track (containing dubbed actor voices) with the English one (with the original actor voices) improves the overall English speaker identification performance by 5% absolute and up to 70% relative on the five main characters.
MIMO Broadcast Channel Rate Region with Linear Filtering at High SNR: Full Multiplexing

In this paper, the rate region of the two user MIMO broadcast channel (BC) under linear filtering at high signal-to-noise ratio (SNR) is investigated when time sharing is not available and the transmitter has more antennas than the sum of the receiving antennas. To reach the rate region's boundary, the sum rate is maximized subject to a given ratio between the users rates. The sum rate is first considered asymptotically when the SNR tends to infinity and taken as an affine function of the logarithm of the SNR, with the multiplicative and the additive parameters called the multiplexing gain (MG) and the rate offset (RO), respectively. The maximal MG and the maximal RO are obtained for every rate ratio constraint. Additionally, the asymptotic optimal stream allocations that achieve those values are also derived. Analytical inner and outer bounds, which offer a rough approximation of the boundary but are extremely easy to evaluate even in fading channels, are then developed. The maximization of the rate subject to a rate ratio constraint is then studied at finite SNR. Algorithmic inner and outer bounds for the rate region boundary are derived and shown to be very close to each other and accurate even at intermediate SNR.
Environmental dissemination of antibiotic resistance genes and correlation to anthropogenic contamination with antibiotics

Antibiotic resistance is a growing problem which threatens modern healthcare globally. Resistance has traditionally been viewed as a clinical problem, but recently non-clinical environments have been highlighted as an important factor in the dissemination of antibiotic resistance genes (ARGs). Horizontal gene transfer (HGT) events are likely to be common in aquatic environments; integrons in particular are well suited for mediating environmental dissemination of ARGs. A growing body of evidence suggests that ARGs are ubiquitous in natural environments. Particularly, elevated levels of ARGs and integrons in aquatic environments are correlated to proximity to anthropogenic activities. The source of this increase is likely to be routine discharge of antibiotics and resistance genes, for example, via wastewater or run-off from livestock facilities and agriculture. While very high levels of antibiotic contamination are likely to select for resistant bacteria directly, the role of sub-inhibitory concentrations of antibiotics in environmental antibiotic resistance dissemination remains unclear. In vitro studies have shown that low levels of antibiotics can select for resistant mutants and also facilitate HGT, indicating the need for caution. Overall, it is becoming increasingly clear that the environment plays an important role in dissemination of antibiotic resistance; further studies are needed to elucidate key aspects of this process. Importantly, the levels of environmental antibiotic contamination at which resistant bacteria are selected for and HGT is facilitated at should be determined. This would enable better risk analyses and facilitate measures for preventing dissemination and development of antibiotic resistance in the environment.
Lessons from the lighthouse: collaboration in a shared mixed reality system

Museums attract increasing numbers of online visitors along with their conventional physical visitors. This paper presents a study of a mixed reality system that allows web, virtual reality and physical visitors to share a museum visit together in real time. Our system allows visitors to share their location and orientation, communicate over a voice channel, and jointly navigate around a shared information space. Results from a study of 34 users of the system show that visiting with the system was highly interactive and retained many of the attractions of a traditional shared exhibition visit. Specifically, users could navigate together, collaborate around objects and discuss exhibits. These findings have implications for non-museum settings, in particular how location awareness is a powerful resource for collaboration, and how 'hybrid objects' can support collaboration at-a-distance.
Negotiating with gatekeepers to get interviews with politicians: qualitative research recruitment in a digital media environment

This article tackles the puzzle of the best practices to acquire an interview with a politician. It seeks to assist researchers who must persuade gatekeepers in busy political offices to present an elected representative with an interview request. Our research is based on a copious review of the literature and is punctuated by fresh insights collected via interviews with 32 academics, journalists and political staff in six countries. We argue that researchers must tailor their approach when placing interview requests to elected officials and make careful use of email, websites, social media and online reputation management. For ease of reference three summary tables are presented. This synopsis about securing interviews with election candidates and legislators can inform qualitative research recruitment with other types of political elites in a rapidly evolving digital environment.
Salmonella abortus equi endotoxin does not affect leptin plasma levels in healthy humans.

Figure 1. Host responses to intravenous injection in 5 healthy subjects of 0.4 ng/kg body weight (Ⅺ) or 0.8 ng/kg body weight (Ⅵ) S. abortus equi endotoxin. For all variables, mean differences between endotoxin and placebo conditions at every time point are depicted. of mean. For description of results and for statistics, see Bars ϭ SE text. To the Editor—We read with interest the recent paper of Born-stein et al. [1], who report that 4 ng/kg body weight Escherichia coli endotoxin injected intravenously into healthy volunteers fails to increase circulating leptin levels, despite a clear-cut activation of the hypothalmo-pituitary-adrenal system and an increase in rectal temperature. This finding is surprising, because endotoxin has been shown to stimulate leptin production in animals [2] and because the administration of pivotal mediators of endotoxin's effects on host defense, such as tumor necrosis factor-a (TNF-a) [3] and glucocorticoids [4], has been shown to increase leptin levels in humans. We report here on the effects of another endotoxin preparation on rectal temperature, and on the plasma levels of interleukin-6 (IL-6), TNF-a, and cor-tisol in healthy volunteers. The study comprised 10 male subjects (age: years). 26 ‫ע‬ 4 Five subjects received 0.4 ng/kg body weight and 5 received 0.8 ng/kg body weight Salmonella abortus equi endotoxin (for details about the endotoxin preparation see [5]) intravenously in a single-blind placebo-controlled design. On two experimental occasions separated by 2 weeks, they fasted, starting at 7 p.m. Endotoxin or 0.9% saline solution was injected at 11 p.m. , when temperature and cortisol responses are much more pronounced than in the morning [6]. After the injection, the subjects were kept awake throughout the experiment. They participated in a larger study of the interactions between host responses to en-dotoxin and sleep-wake behavior (the respective results will be presented elsewhere). Rectal temperature was monitored continuously, and blood samples were taken through an intravenous catheter. Plasma was frozen to Ϫ20ЊC. IL-6 and TNF-a levels were determined by ELISAs (Medgenix Diagnostics, Brussels); RIAs were used to measure cortisol (ICN Biomedicals, Carson, CA) and leptin (DRG Instruments, Marburg, Germany) levels. The effects of endotoxin (expressed as the difference between values obtained
Do Cinnamon Supplements Cause Acute Hepatitis?

Patient: Female, 73 Final Diagnosis: Drug induced acute hepatitis Symptoms: Abdominal pain • diarrhea • vomiting Medication: — Clinical Procedure: — Specialty: Gastroenterology and Hepatology Objective: Unusual or unexpected effect of treatment Background: The use of herbal medications to treat various diseases is on the rise. Cinnamon has been reported to improve glycolated hemoglobin and serum glucose levels. When patients consider the benefit of such substances, they are often not aware of potential adverse effects and drug interactions. Cinnamon, via coumarin, can cause liver toxicity. Therefore, its concomitant use with hepatotoxic drugs should be avoided. Case Report: A 73-year-old woman was seen in the Emergency Department complaining of abdominal pain associated with vomiting and diarrhea after she started taking cinnamon supplements for about 1 week. The patient had been taking statin for coronary artery disease for many months. The laboratory workup and imaging studies confirmed the diagnosis of hepatitis. The detail workup did not reveal any specific cause. Cinnamon and statin were held. A few weeks after discharge, the statin was resumed without any further complications. This led to a diagnosis of cinnamon-statin combination-induced hepatitis. Conclusions: A combination of cinnamon supplement and statin can cause hepatitis, and it should be discouraged.
Budgetary and Management control Process in a Manufacturing

Date : June, 2008. Level : Master Thesis EF0705, 10 points (15credits) Authors : Amalokwu Obiajulum John (820821) Lawrence Njilefack Ngoasong (770901) Title : Budgetary and Management control Proce .
Combined Method for Effective Clustering based on Parallel SOM and Spectral Clustering

The paper is oriented to the problem of clustering for large datasets with high-dimensions. We propose a two-phase combined method with regard to high dimensions and exploiting the standard clustering algorithm. The first step of the method is based on the learn- ing phase using artificial neural network, especially Self organizing map, which we find as a suitable method for the reduction of the problem complexity. Due to the fact, that the learning phase of artificial neural networks can be time-consuming operation (especially for large high- dimensional datasets), we decided to accelerate this phase using paral- lelization to improve the computational eciency. The second phase of the proposed method is oriented to clustering. Because the visualization provided by Self organizing maps is depending on the map dimension, and is not as clear and comprehensible in the cases of clustering applica- tions, we decided to use spectral clustering algorithm to obtain sucient clusters. According to our results, the proposed combined method is suciently rapid and quite accurate.