Miracle-dz/UniFAR-FTUs huggingface dataset:
Prolonged network life-time in self-organizing peer-to-peer networks with E-RSSI clustering

Clustering is an essential tool to facilitate the function of self-organizing peer-to-peer and sensor networks. The LEACH (Low-Energy Adaptive Clustering Hierarchy) algorithm for forming clusters in ad-hoc networks represents a probabilistic way of choosing cluster-heads which shows a large variation over the average link distances of clusters and leads to uneven energy consumption during the transmission phase. However LEACH has the advantage that the energy load of being cluster-head is distributed among all the nodes resulting in a longer network life-time. On the other hand, the RSSI (Received Signal Strength Indicator)-based algorithms try to reduce the variation over the average link distances of clusters by means of choosing cluster-heads in the areas of higher node density in order to have an even energy consumption during transmission phase. But it distributes the energy load of being the cluster-head between some specific nodes which leads to a shorter network life-time. Here, we propose a new clustering scheme E-RSSI (Enhanced RSSI), which has the main advantages of the RSSI based schemes as well as LEACH. The average link distance of E-RSSI is almost the same as the average link distance of RSSI. And E-RSSI, like RSSI, has a significantly smaller variation over the average link distances in comparison with LEACH and at the same time shows significant improvement in network life-time. E-RSSI produces a low energy cost per node like RSSI and a more evenly distributed energy cost per node like LEACH therefore a prolonged network life-time.
Nested Subtree Hash Kernels for Large-Scale Graph Classification over Streams

Most studies on graph classification focus on designing fast and effective kernels. Several fast subtree kernels have achieved a linear time-complexity w.r. t. the number of edges under the condition that a common feature space (e.g., a subtree pattern list) is needed to represent all graphs. This will be infeasible when graphs are presented in a stream with rapidly emerging subtree patterns. In this case, computing a kernel matrix for graphs over the entire stream is difficult since the graphs in the expired chunks cannot be projected onto the unlimitedly expanding feature space again. This leads to a big trouble for graph classification over streams - Different portions of graphs have different feature spaces. In this paper, we aim to enable large-scale graph classification over streams using the classical ensemble learning framework, which requires the data in different chunks to be in the same feature space. To this end, we propose a Nested Subtree Hashing (NSH) algorithm to recursively project the multi-resolution subtree patterns of different chunks onto a set of common low-dimensional feature spaces. We theoretically analyze the derived NSH kernel and obtain a number of favorable properties: 1) The NSH kernel is an unbiased and highly concentrated estimator of the fast subtree kernel. 2) The bound of convergence rate tends to be tighter as the NSH algorithm steps into a higher resolution. 3) The NSH kernel is robust in tolerating concept drift between chunks over a stream. We also empirically test the NSH kernel on both a large-scale synthetic graph data set and a real-world chemical compounds data set for anticancer activity prediction. The experimental results validate that the NSH kernel is indeed efficient and robust for graph classification over streams.
Tupaia Belangeri as an Experimental Animal Model for Viral Infection

Tupaias, or tree shrews, are small mammals that are similar in appearance to squirrels. The morphological and behavioral characteristics of the group have been extensively characterized, and despite previously being classified as primates, recent studies have placed the group in its own family, the Tupaiidae. Genomic analysis has revealed that the genus Tupaia is closer to humans than it is to rodents. In addition, tupaias are susceptible to hepatitis B virus and hepatitis C virus. The only other experimental animal that has been demonstrated to be sensitive to both of these viruses is the chimpanzee, but restrictions on animal testing have meant that experiments using chimpanzees have become almost impossible. Consequently, the development of the tupaia for use as an animal infection model could become a powerful tool for hepatitis virus research and in preclinical studies on drug development.
Efficient Approach for Knowledge Management Using Deep Web Information Retrieval System

Along with the development of network technology, web information are rapidly growing, and the way of information storage is gradually changed from the html to the database, thus web information can be divided into the surface web and deep web. Deep web is a concept corresponding to the surface web. It means from ordinary search engine that is difficult to discover the information content of a web page. The traditional crawler only crawl the content on the surface of a web, which makes the current traditional search engine, did not retrieve deep web data. Deep web compared with surface web has the advantage of large volume, high quality, theme single-minded, good structured. In view of several advantages, the establishment of deep web data integration system is becoming a research hotspot. The deep web query interface is the only entrance of the background database, so how to determine which web form is the query interface is important to the deep web information access. However, because the page proportion on the internet which contains querying interface is very small, using the traditional breadth-first strategy and keyword filtering method to crawl, it will download a lot of unrelated pages, spend a lot of resources, we need a way to efficiently find and collect the query interfaces through deep web crawling strategy. We proposed novel query planning approach, for executing different types of complex attribute through queries over multiple inter-dependent deep web data sources. increase accelerate query searching based on attribute selection, execution and propose optimization techniques, including query plan merging and grouping optimization. Keywords: Novel query planning approach, Deep web, Semantic Deep Web, Ontologies, attribute.
A spectral-Galerkin turbulent channel flow solver for large-scale simulations

A fully (pseudo-)spectral solver for direct numerical simulations of large-scale turbulent channel flows is described. The solver utilizes the Chebyshev base functions suggested by J. Shen [SIAM J. Sci. Comput. , 16, 1, 1995], that lead to stable and robust numerical schemes, even at very large scale. New and fast algorithms for the direct solution of the linear systems are devised, and algorithms and matrices for all required scalar products and transforms are provided. We validate the solver for very high Reynolds numbers. Specifically, the solver is shown to reproduce the first order statistics of Hoyas and Jim\'{e}nez [Phys. Fluids, 18(1), 2006], for a channel flow at $Re_{\tau}=2000$. The solver is available through the open source project spectralDNS [this https URL].
Constructing masculinity on a social networking site

Social networking website (SNS) Rate is the most popular online environment for young Estonians, which has more than 290000 active users. The study aims to examine visual self-presentations of young men (N = 108) in Rate. Quantitative content analysis methodology was used to analyze 599 profile images of young men belonging to a community ‘Damn I’m Beautiful! ’. The results indicate that media representations of men are often taken as role-models while constructing one’s visual identities online. In particular, young men mostly pose alone in order to emphasize their looks and appear as willing sexual or romantic objects. They appear mostly in the public sphere, however, without being engaged in any purposeful activities. All in all, SNS profile images function on many levels in order to portray different versions of masculinity. The findings highlight the importance of photos as additional impression management tools and confirm their conscious use for identity ‘performances’ on SNS.
Reducing Peritonitis Rates in a Peritoneal Dialysis Program of Indigent Ethnic Minorities

tion and a decrease in lean body mass. JAm Soc Nephrol 2000; 11:1303–9. 11. Don BR, Rosales LM, Levine NW, Mitch W, Kaysen GA. Leptin is a negative acute phase protein in chronic hemodialysis patients. Kidney Int 2001; 59:1114–20. 12. Chung SH, Lindholm B, Lee HB. Influence of initial nutritional status on continuous ambulatory peritoneal dialysis patient survival. Perit Dial Int 2000; 20:19–26. 13. Avram MM, Sreedhara R, Fein P, Oo KK, Chattopadhyay J, Mittman N. Survival on hemodialysis and peritoneal dialysis over 12years with emphasis on nutritional parameters. Am J Kidney Dis 2001; 37(Suppl 2):S77–80. 14. Fernström A, Hylander B, Moritz A, Jacobsson H, Rossner S. Increase of intra-abdominal fat in patients treated with continuous ambulatory peritoneal dialysis. Perit Dial Int 1998; 18:166–71. 15. Heimbürger O, Lonnqvist F, Danielsson A, Nordenstrom J, Stenvinkel P. Serum immunoreactive leptin concentration and its relation to the body fat content in chronic renal failure. JAm Soc Nephrol 1997; 8:1423–30. 16. Fleischmann E, Teal N, Dudley J, May W, Bower JD, Salahudeen AK. Influence of excess weight on mortality and hospital stay in 1346hemodialysis patients . Kidney Int 1999; 55:1560–7. 17. Johnson DW, Herzig KA, Purdie DM, Chang W, Brown AM, Rigby RJ, etal . Is obesity a favorable prognostic factor in peritoneal dialysis patients? Perit Dial Int 2000; 20:715–21. 18. Aslam N, Bernardini J, Fried L, Piraino B. Large body mass index does not predict short-term survival in peritoneal dialysis patients. Perit Dial Int 2002; 22: 191–6. 19. Kaizu Y, Tsunega Y, Yoneyama T, Sakao T, Hibi I, Miyaji K, etal . Overweight as another nutritional risk factor for the long-term survival of non-diabetic hemodialysis patients. Clin Nephrol 1998; 50:44–50.
Detection of a Red Supergiant Progenitor Star of a Type II-Plateau Supernova

We present the discovery of a red supergiant star that exploded as supernova 2003gd in the nearby spiral galaxy M74. The Hubble Space Telescope (HST) and the Gemini Telescope imaged this galaxy 6 to 9 months before the supernova explosion, and subsequent HST images confirm the positional coincidence of the supernova with a single resolved star that is a red supergiant of \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(8_{-2}^{+4}\) \end{document} solar masses. This confirms both stellar evolution models and supernova theories predicting that cool red supergiants are the immediate progenitor stars of type II–plateau supernovae.
Barrett's Esophagus Commonly Diagnosed in Elderly Men with Limited Life Expectancy

2015;49:135–143. 5. Jhamb M, Liang K, Yabes J et al. Prevalence and correlates of fatigue in chronic kidney disease and end-stage renal disease: Are sleep disorders a key to understanding fatigue? Am J Nephrol 2013;38:489–495. 6. Meuwese CL, Stenvinkel P, Dekker FW et al. Monitoring of inflammation in patients on dialysis: Forewarned is forearmed. Nat Rev Nephrol 2011;7:166–176. 7. De Lorenzo F, Xiao H, Mukherjee M et al. Chronic fatigue syndrome: Physical and cardiovascular deconditioning. QJM 1998;91:475–481. 8. Mart ınez-Alonso M, Dusso A, Ariza G et al. Vitamin D deficiency and its association with fatigue and quality of life in advanced cancer patients under palliative care: A cross-sectional study. Palliat Med 2016;30:89–96. 9. Albaaj F, Sivalingham M, Haynes P et al. Prevalence of hypogonadism in male patients with renal failure. Postgrad Med J 2006;82:693–696. 10. Johansen KL, Mulligan K, Schambelan M. Anabolic effects of nandrolone decanoate in patients receiving dialysis: A randomized controlled trial. JAMA 1999;281:1275–1281.
Optimization of Graph Query on Relational Database

Graph data structures are being increasingly employed to model dynamic information such as online social networks, transporation networks and protein structures. They are widely used due to the fact that they can represent real world knowledge through an intuitive and flexible scheme. These data structures allow intuitive interconnection between different nodes or components through edges. There can be more than one edge between a pair of nodes and each edge have a label which defines the relationship between connected nodes. Furthermore, graphs can easily capture real world dynamics through addition or removal of edges. With the increase in popularity of graphs, various specialised graph database have arised such as Neo4j and Trinity. These NoSQL databases are designed so that they can be easily scaled and have high availability. However, the legacy Relational Database Management Systems (RDBMS) have key advantages. They have been employed by various industries for long time and its features have evolved through extensive research that has been carried out on the relational model. It includes features such as transaction consistency, normalization and declarative query language. Furthermore, there are various RDBMS off-the-shelf products available which can be quickly deployed. Due to various desirable properties, the RDBMS continue to be used for different applications. However, the relational database are not efficient on querying graphs as it involves JOIN operation between tuples which is slow and has limitations. This project aims to address this issue by applying efficient pre-fetching techniques to optimize graph query. A graph processing layer called Crackle was also built which achieves local caching at the application level. A set of experiements are conducted to evaluate the performance gain through Hierarchical blocking technique. There was significant improvement in Small World by upto 8x followed by Random and Scale free graphs. The comparison tests between relational and graph database showed decrease in the performance gap between them. In some cases, the relational database outperformed the graph database by 18% by using Hierarchical blocking. Clearly, this shows how Hierarchical blocking can achieve implicit pre-fetching through efficient graph layout. This algorithm can be further extended by applying more targeted heurisitic based on the topology of underlying graph. However, that would make the blocking algorithm more graph-specific as opposed to being domain-indpendent which is what this project aims to explore.
Multicenter Retrospective Study of Adjuvant Therapy for Patients with Pathologically Lymph Node-Positive Oral Squamous Cell Carcinoma : Analysis of Covariance Using Propensity Score

Background. The presence of pathologically positive lymph nodes (pN? ) is a well-known prognostic factor in oral squamous cell carcinoma (OSCC). The aims of this retrospective multicenter study were to assess the prognosis of OSCC patients with pN? disease; to compare the prognosis of patients with pN? disease who underwent surgery plus radiotherapy (RT) or concurrent chemoradiotherapy (CCRT) with that of patients who underwent surgery only; and to account for biases associated with treatment selection of adjuvant RT or CCRT. Methods. The records of 313 OSCC patients with pN? disease were retrospectively reviewed. The main outcome measures were 5-year disease-specific survival (DSS) and overall survival (OS) rates. To reduce selection biases associated with retrospective data, the treatment groups were evaluated by Cox proportional hazard analysis with propensity score as a covariate. Results. The 5-year OS and DSS survival rates for the entire patient cohort were 51.8 and 59.2 %, respectively. T3–4 stage, closed (\5 mm) margin distance, C4 involved nodes, and extracapsular spread were significant poor prognostic factors for OS and DSS. In the propensity score analysis, postoperative RT/CCRT significantly improved OS and DSS compared to surgery only. However, OS and DSS were not significantly different between patients who received postoperative RT and CCRT. Conclusion. The addition of cytotoxic chemotherapy to RT does not provide additional survival benefit in OSCC patients with pN? disease. Alternative strategies, such as molecular targeted therapies, are needed to further improve the survival of high-risk OSCC patients with pN? disease. Oral squamous cell carcinoma (OSCC) accounts for 2– 3 % of all cancers and is the sixth most common cancer worldwide. OSCC continues to show a poor prognosis and remains a lethal disease in[50 % of cases diagnosed annually. Trends in the treatment of high-risk OSCC cases have been directed toward surgery plus postoperative RT with or without concurrent chemotherapy. The presence of pathologically positive lymph nodes (pN? ) is a wellknown prognostic factor in OSCC. Extracapsular spread (ECS) of lymph node metastasis and the presence of Society of Surgical Oncology 2015 First Received: 6 June 2015; Published Online: 20 August 2015 S. Yanamoto, DDS, PhD e-mail: syana@nagasaki-u.ac. jp Ann Surg Oncol (2015) 22:S992–S999 DOI 10.1245/s10434-015-4824-5
A single number can't hedge against economic catastrophes

July 2, 1999 Holger Rootz en Claudia Kl uppelberg Department of Mathematical Statistics Center for Mathematical Sciences Chalmers University of Technology Munich University of Technology S-41396 Gothenburg D-80290 Munich email: rootzen@math.chalmers.se email: cklu@ma.tum.de www.math.chalmers.se/ rootzen/ www.ma.tum.de/stat/ Abstract Mathematics and statistics have transformed the day-to-day trading in the world's nancial markets. This has lead to new ways to reduce (or "hedge") risks which provides an important service to society, but also a temptation to very big gambles, with a potential for extreme losses. This paper discusses some of the ways statistics and mathematics can be used to understand and protect against very large, "catastrophic" nancial risks. We argue that means don't mean anything for catastrophic risk, that separate large nancial risks often are better handled by separate companies, and that the mathematical aspects of risk can't be summarized into one number. We also believe that there is a large potential for improved risk management in nancial institutions, where extreme value theory, a speciality of the present authors, may be a useful tool. Improvements, however will not come for free but require long and hard work, where mathematics is only one part of the total e ort.
A sustainability framework for the beneficial reuse of alumina refinery residue

When bauxite is processed to manufacture alumina, a solid waste by-product is created. For every one tonne of bauxite digested by the refining process about 400 kg of alumina and 600 kg of waste residue are produced. As a consequence, each year up to 120 million tonnes of solid waste residue are generated by about 100 alumina refineries in Australia, China, Brazil, India and elsewhere, and in excess of three billion tonnes of waste residue are reportedly stockpiled in impoundments throughout the world, making alumina refinery residue the world’s single largest industrial waste product by volume. The physical and chemical properties of alumina refinery residue have long been the subject of scientific investigation because the residue contains iron, aluminium, silica, titanium, sodium and other elements and compounds of potential value. In the last ten years, this investigation has centred on not only the recovery of valuable components of the waste but also on the various beneficial reuse possibilities associated with this type of residue, both as a way of reducing the amount of waste being stockpiled as well harnessing the inherent valuable components in it. The alumina industry has therefore developed a series of “technology roadmaps” to address the growing inventories of alumina refinery waste, including how to better dewater and store it safely. However, while commendable, these roadmaps have mostly focused on process improvement and productivity dividends and failed to address certain fundamental truths related to sustainable and beneficial reuse, including lifecycle analyses, how the residue can be incorporated into wider regional plans for sustainable development, and the inescapable fact that alumina refinery residue is a classified hazardous waste in most jurisdictions with potentially detrimental human and environmental health effects when applied incorrectly or inappropriately. By considering not only the obvious industrial, commercial and chemical imperatives which drive residue reuse and inform current technology roadmaps, but also by including the regulatory, environmental, investment, research and social licensing dimensions (among other factors) of a complete and holistic future, this paper presents a new framework for the beneficial reuse of alumina refinery residue. The paper argues that only through a comprehensive understanding and consideration of all aspects of alumina refinery residue beneficial reuse and a meaningful engagement with the broadest possible range of stakeholders can a truly sustainable future for this type of waste be realized by society and industry.
Algorithms and optimization for quality of experience aware routing in wireless networks : from centralized solutions. (Algorithmes centralisés et distribués pour le routage basé sur la qualité d'expérience dans les réseaux sans-fil)

Wireless and mobile networks have become an important part in our modern society. Thanks to ubiquitous wireless connectivity, people can connect to the Internet anytime and anywhere. Video streaming is one of the most popular services on the Internet and it covers from 70% to 82% of all Internet traffic. Modern infrastructure networks, such as Long-Term Evolution (LTE), are prospective solutions for video streaming because of their high data rates. Nevertheless, the high implementation cost and the lack of compatibility of users’ equipment prevent them from practical deployment. Moreover, infrastructure networks may not be available in some cases such as after disasters or in a rural area. In these scenarios, wireless mesh networks (WMNs) become a promising alternative because of its easy deployment, low cost, and recovery ability. The decisive component of WMNs is the routing algorithm in which the end-to-end routes are determined. Most of existing routing algorithms are based on single or combination of network-oriented metrics. Consequently, routing decisions may not correlate with user experience or Quality of Experience (QoE). This thesis addresses the QoE-aware routing of video streaming over WMNs and proposes centralized and decentralized routing algorithms that take user-oriented metrics into account. The results confirm the advantages of using QoE concept in routing algorithms.
A Search-Theoretic Model of the Term Premium

A consistent empirical feature of bond yields is that term premia are, on average, positive. That is, investors in long term bonds receive higher returns than investors in similar (i.e.\ same default risk) shorter maturity bonds over the same holding period. The majority of theoretical explanations for this observation have viewed the term premia through the lens of the consumption based capital asset pricing model. In contrast, we harken to an older empirical literature which attributes the term premium to the idea that short maturity bonds are inherently more liquid. The goal of this paper is to provide a theoretical justification of this concept. To that end, we employ a model in the tradition of modern monetary theory extended to include assets of different maturities. Short term assets always mature in time to take advantage of random consumption opportunities. Long term assets do not, but agents may liquidate them in a secondary asset market, characterized by search-and-bargaining frictions a la Duffie, Garleanu, and Pedersen (2005). In equilibrium, long term assets have higher rates of return to compensate agents for their relative lack of liquidity. Consistent with empirical findings, our model predicts a steeper yield curve for assets that trade in less liquid secondary markets.