Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-level laser therapy in the prevention and treatment of chemotherapy-induced oral mucositis in young patients.

OBJECTIVE A pilot clinical study was conducted to evaluate the efficacy and feasibility of low-level laser therapy (LLLT) in the prevention and treatment of chemotherapy (CT)-induced oral mucositis (OM) in young patients. BACKGROUND DATA Besides compromising the patient's nutrition and well-being, oral mucositis represents a portal of entry into the body for microorganisms present in the mouth, which may lead to sepsis if there is hematological involvement. Oncologic treatment tolerance decreases and systemic complications may arise that interfere with the success of cancer treatment. LLLT appears to be an interesting alternative to other approaches to treating OM, due to its trophic, anti-inflammatory, and analgesic properties. MATERIALS AND METHODS Patients undergoing chemotherapy (22 cycles) without mucositis were randomized into a group receiving prophylactic laser-irradiation (group 1), and a group receiving placebo light treatment (group 2). Patients who had already presented with mucositis were placed in a group receiving irradiation for therapeutic purposes (group 3, with 10 cycles of CT). Serum granulocyte levels were taken and compared to the progression of mucositis. RESULTS In group 1, most patients (73%) presented with mucositis of grade 0 (p = 0.03 when compared with the placebo group), and 18% presented with grade 1. In group 2, 27% had no OM and did not require therapy. In group 3, the patients had marked pain relief (as assessed by a visual analogue scale), and a decrease in the severity of OM, even when they had severe granulocytopenia. CONCLUSION The ease of use of LLLT, high patient acceptance, and the positive results achieved, make this therapy feasible for the prevention and treatment of OM in young patients.
A comprehensive study of sparse codes on abnormality detection

Sparse representation has been applied successfully in abnormal event detection, in which the baseline is to learn a dictionary accompanied by sparse codes. While much emphasis is put on discriminative dictionary construction, there are no comparative studies of sparse codes regarding abnormality detection. We comprehensively study two types of sparse codes solutions - greedy algorithms and convex L1-norm solutions - and their impact on abnormality detection performance. We also propose our framework of combining sparse codes with different detection methods. Our comparative experiments are carried out from various angles to better understand the applicability of sparse codes, including computation time, reconstruction error, sparsity, detection accuracy, and their performance combining various detection methods. Experiments show that combining OMP codes with maximum coordinate detection could achieve state-of-the-art performance on the UCSD dataset [14].
Popular theater for social change in Latin America : essays in Spanish and English

Vingt-six communications sur le theâtre populaire en Amerique Latine groupees en six chapitres: 1. Theorie et methode| 2. Panorama des nations (Cuba, Porto Rico, Mexique, Uruguay, Paraguay, Colombie, Chili, Argentine)| 3. Theâtre populaire et theâtre pour enfants| 4. Festivals| 5. Groupes et experiences (Bresil, Argentine, Perou, Colombie)| 6. Bibliographie selective.
Proteomic Characterization and Comparison of Malaysian Tropidolaemus wagleri and Cryptelytrops purpureomaculatus Venom Using Shotgun-Proteomics

Tropidolaemus wagleri and Cryptelytrops purpureomaculatus are venomous pit viper species commonly found in Malaysia. Tandem mass spectrometry analysis of the crude venoms has detected different proteins in T. wagleri and C. purpureomaculatus. They were classified into 13 venom protein families consisting of enzymatic and nonenzymatic proteins. Enzymatic families detected in T. wagleri and C. purpureomaculatus venom were snake venom metalloproteinase, phospholipase A2, l-amino acid oxidase, serine proteases, 5′-nucleotidase, phosphodiesterase, and phospholipase B. In addition, glutaminyl cyclotransferase was detected in C. purpureomaculatus. C-type lectin-like proteins were common nonenzymatic components in both species. Waglerin was present and unique to T. wagleri—it was not in C. purpureomaculatus venom. In contrast, cysteine-rich secretory protein, bradykinin-potentiating peptide, and C-type natriuretic peptide were present in C. purpureomaculatus venom. Composition of the venom proteome of T. wagleri and C. purpureomaculatus provides useful information to guide production of effective antivenom and identification of proteins with potential therapeutic applications.
Essays on fiscal policy and political economy

This thesis consists of three essays concerned with endogenous scal policy and its interaction with political economy constraints. The rst essay presented in Chapter 2 examines the cyclical behavior of endogenous government consumption over the business cycle absent a commitment mechanism in a neoclassical economy with Total Factor Productivity (TFP) shocks and investment shocks. Tax rates that nance public consumption are chosen in a time consistent way in a dynamic game between the government and a representative agent that values public goods in his utility. It is found that government consumption set without commitment behaves procyclical in response to the mentioned shocks. The government-consumption-output ratio is mildly procyclical or countercyclical depending on the selected calibration. Particularly, the elasticity of substitution between private and public goods plays an important role. The second essay showed in Chapter 3 extends the model studied in Chapter 2 adding agent heterogeneity in wealth and labor productivity. The aim of this study is to identify how policy outcomes are a¤ected by inequality of households, particularly the median voters choice of tax rates that nance public goods. For a standard RBC calibration to the U.S. economy the result is a strong procyclical comovement of public consumption with output, and a relatively weak procyclical comovement of the output share of public consumption with output, that becomes stronger with rising inequality. The politico-economic channel induces causality from output to lagged tax rates, therefore after a Hicks neutral productivity shock the median voter tries to delay the increase in the tax rate, such that the increment will take place just after the accumulation of more capital. In the case of equal agents the response is to decrease the tax rate in the rst year after the shock. Additionally, the model predicts that the size of government consumption decreases with inequality. The last essay in Chapter 4 presents a stylized model of external sovereign debt that incorporates corruption in the form of rent-seeking groups by which the choice to cooperate or non-cooperate in providing public goods, in extracting rents and in issuing debt, is endogenized. More than one rent-seeking group originates a "tragedy of the commons" over scal resources that make the borrower economy to show collective scal impatience. External creditors envision that impatience and require higher interest rates for buying bonds, exacerbating the problem of high debt. The high level of interest rates decreases the wealth of the country and endangers its ability to repay the debt. We show that bailout plans, de ned as temporary loans with lower than market level interest rates, are not e¤ective in such economies.
SYSTEM: INTEGRATION OF ONTOLOGY AND CBR

This paper discusses the development o f a web-based student enquiry system using techniques in case-based reasoning combined with advances in ontology. The system functions as an online enquiry front-desk to allow prospective students to fin d out i f they are eligible fo r admission to a post-graduate course in an Australian University. Ontology is applied in the system to ensure explicit specifications o f concept and definition o f terminology can be achieved in the web-based system. The system applies case-based reasoning technique to handle the query.
A Complete Comparison on Pure and Cued Recall-Based Graphical User Authentication Algorithms

Nowadays, user authentication is one of the important topics in information security. Strong text-based password schemes could provide with certain degree of security. However, the fact that strong passwords are difficult to memorize often leads their owners to write them down on papers or even save them in a computer file. Graphical authentication has been proposed as a possible alternative solution to text-based authentication, motivated particularly by the fact that humans can remember images better than text. In recent years, many networks, computer systems and Internet-based environments try used graphical authentication technique for their user’s authentication. All of graphical passwords have two different aspects which are usability and security. Unfortunately none of these algorithms were being able to cover both of these aspects at the same time. During our research, we could find eleven Recall-Based authentication algorithms which we tried to explain their lacks and attacks. Then in the last section, in order to cover usability and security features at the same time, we try to make three different comparison tables.
Designing of Index-Guiding Photonic Crystal Fibre by Finite Element Method Simulation

Different structures of Index-guiding Photonic crystal fibre are designed. The attractive vectorial Finite Element Method simulation technique is used to analyse such PCFs by taking suitable fibre parameter i.e. air hole diameter (d), pitch (Λ) and air core diameter (d´). Few important properties such as variation of refractive index with wavelength and nice confinement modal field pattern were studied. Index-guided photonic crystal fibre having inner core of radius 0. 2µm, pitch 2. 4µm and identical air hole of diameter d=1. 38µm is suggested for which leakage of signal is almost zero at wavelength 1. 55µm.
Sudden stop regimes and output: a Markov switching analysis

Sudden stops in capital inflows were a main characteristic of the emerging market crisis during the 1990’s. Concerns about them have recurred in the light of recently increased global stability risk and the quantitative easing that led to substantial capital inflows in emerging economies. We add to the empirical literature that relies on a univariate approach by using a multivariate framework to assess the effect of sudden stops on economic growth and by the identification of sudden stop shocks using a Markov switching VAR and sign restrictions. The Markov switching VAR approach dates sudden stop periods comparable to the existing literature. It reveals a significant negative influence of the regime switch on economic growth that is robust across different estimation methods. Moreover, the Markov switching VAR also indicates that the reaction of macroeconomic variables to the identified shock based on sign restrictions is regime dependent.
A novel Voting Algorithm of multi-class SVM for web page classification

The increasing numbers of web pages on the cyber world result to the less effectiveness of document retrieval that matches the need of users. The classification of web pages is one of the solutions to solve this problem. This paper proposes VAMSVM_WPC model which is a novel voting algorithm for classifying the web pages, which uses a multi-class SVM method. First, feature is generated from text and title, and then reduces the number of features by two feature selection techniques. Use these two types of features to give input to multi-class SVM. Finally, on the output of SVM, a voting algorithm is used to determine the category of the web pages. Results on CMU benchmark dataset show that using text and title feature with 1vsAll_Voting Algorithm gives the highest F-measure value.
The Development of Swedish Tourism Public Policy 1930-2010

In this article, the development and changes in Swedish public policy relating to tourism from the 1930s to 2010 is described and interpreted from a political economy perspective. A case study, compiled from mainly secondary sources, is analyzed from a theoretical framework based on regulation theory. The purpose with this study is to increase the understanding of how the macro political economy context has influenced the policy-making in tourism in Sweden, but also to make a contribution to an area which seems to be quite neglected when it comes to research. The changes are analyzed according to the three periods denoted as pre-Fordism (mid-19th century-1930s), Fordism (1930s-1970s) and post-Fordism (1970s to present). It is observed how the general changes between these periods regarding aspects such as regulation and deregulation, and the degree of state involvement, have affected tourism policy making. The tourism policy making has changed from being insignificant, to a high degree of state involvement including planning, control and supervision, to a situation where the market rather than government regulation is considered as state of the art.
Parallelization Methods for Edge Extraction Applied to Chip Multiprocessor Clusters

As the parallel computing technologies become mature, many computationally intensive and/or data intensive algorithms could be improved with parallelization methods. In this paper, we improve the performance of the edge extraction algorithmic program by parallelizing the sequential algorithm. We altogether propose three parallelization methods based on chip multiprocessor (CMP) clusters. The OpenMP-based method is investigated for the shared memory model and thus it is applied to single CMP node, while the three MPI-based methods are investigated for the message passing model and thus they are applied to CMP-clusters. Massive experiments verify that the parallelization methods proposed in this paper are all effective and efficient.
Data for snowmelt model development, calibration, and verification at an Alpine Site, Colorado Front Range

Logistical constraints have caused data collection in seasonally snow covered areas to generally be on a campaign basis with limited instrumentation. The problems of winter access, cold air temperatures, and blowing snow cause both equipment malfunctions and problems with consistent and timely maintenance. At the Long‐Term Ecological Research program network site in an alpine area of Colorado we have been operating a meteorological station and subnivean (below snow) laboratory at 3517 m since the spring of 1994 to collect information that will allow us to better understand snow‐surface energy exchanges and the mass flux of water during snowmelt. This unique and high‐quality data set was designed to measure the meteorologic and hydrologic parameters necessary to compute the surface energy and snowpack mass balances at a point. All meteorological parameters are directly measured. Turbulent fluxes are calculated using the aerodynamic profile method. The timing and magnitude of snowmelt is measured with 18 snow lysimeters. Meteorologic parameters and energy fluxes are available at 10‐min, hourly, and daily time steps. Complementary information includes a high‐resolution digital elevation model, snowpack parameters, and stream discharge.
Discovery of a dense molecular cloud towards a young massive embedded star in 30 Doradus

Context. The 30 Doradus region in the Large Magellanic Cloud is one of the most outstanding star-forming regions of the Local Group and a primary target for studying star formation in an environment of low metallicity. Aims. To obtain a more complete picture of the cool gas that has not yet been consumed or dispersed, we searched for line emission from molecular clouds that could be associated with molecular hydrogen emission detected in the region. Methods. We obtained a high sensitivity 12 CO $J = 2$–1 map with the 15-m SEST telescope, complemented by pointed observations of 13 CO $J = 2$–1 and CS $J=2$–1. Results. We report the discovery of a dense molecular cloud towards an embedded young massive star at ~20” (~5 pc, at the distance of 50 kpc) northwest of R136, the compact massive central stellar cluster powering 30 Doradus in the LMC, which could be triggering star formation in the surrounding molecular clouds. We derived a molecular mass of ≲ 10 4 $M_\odot$, a linear radius of 3 pc, as an upper limit, and a mean density of ≳ 10 3 cm -3 for the cloud. The detection of the CS $J = 2$–1 emission line indicates higher densities, ~10 6 cm -3 . The dense molecular cloud is associated with molecular 2.12 μ m H 2 emission. We suggest that the observed molecular gas could be the remains of dense molecular material surviving the action of strong UV fields and winds in which the young massive star has formed.
The West and Islam : western liberal democracy versus the system of shura

Introduction Part 1: Historical background 1. The evolution of democracy 2. The eclectic nature of shura 3. Shura in the contemporary period: the case of Sudan Part 2: Comparison of Western liberal democracies and al-Turabi's shura system 4. The foundations of Western liberal democracy and al-Turabi's shura system 5. Political system divisions 6. Political legalisation Conclusion
Frankencode: Creating Diverse Programs Using Code Clones

In this paper, we present an approach to detecting novel cyber attacks though a form of program diversification, similar to the use of n-version programming for fault tolerant systems. Building on extensive previous and ongoing work by others on the use of code clones in a wide variety of areas, our Functionally Equivalent Variants using Information Synchronization (FEVIS) system automatically generates program variants to berun in parallel, seeking to detect attacks through divergence in behavior. Unlike approaches to diversification that only change program memory layout and behavior, FEVIS can detect attacks exploiting vulnerabilities in execution timing, string processing, and other logic errors. We are in the early stages of research and development for this approach, but have made sufficient progress to provide a proof of concept and some lessons learned. In this paper we describe FEVIS and its application to diversifying an open-source webserver, with results on several different example classes of attack which FEVIS will detect.
A new spin-image based 3D Map registration algorithm using low-dimensional feature space

Spin image is a good feature descriptor of the 3D surface, thus it has been extensively used in many applications such as SLAM of mobile robot and cooperation of heterogeneous robots. However, due to the huge computational burden, it is difficult to be used in real time applications. Thus, in order to improve the efficiency and accuracy of spin image based point clouds registration algorithm, a fast registration algorithm is proposed in this paper based on low-dimensional feature space composed of curvature, the Tsallis entropy of the spin image and laser reflection intensity. The main contribution of this paper is that through constructing the low dimensional feature space, the correspondence searching procedure can be divided into two steps: firstly, select similar key points in the proposed low dimensional feature space using k-d tree; then spin image feature is used to search for correspondences among a very limited amount of point candidates. Finally, experiments with respect to a man made surroundings are conducted and the results show the feasibility and validity of the new proposed algorithm. Index Terms - Point cloud map registration, spin image, k-d tree, features description.
Transducers, logic and algebra for functions of finite words

The robust theory of regular languages is based on three important pillars: computation (automata), logic, and algebra. In this paper, we survey old and recent results on extensions of these pillars to functions from words to words. We consider two important classes of word functions, the rational and regular functions, respectively defined by one-way and two-way automata with output words, called transducers.
An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.
Efficient Selective Feedback Design for Multicell Cooperative Networks

Multicell cooperative processing (MCP) has been recognized as a promising technique for increasing the spectral efficiency of future wireless systems. Unfortunately, the provided benefits of MCP come at the cost of increased radio feedback and backhaul overhead; for downlink transmission in frequency-division duplexing (FDD) systems, users need to feed back their channel-state information (CSI) to the MCP scheduler, and user data need to be exchanged between all cooperating base stations (BSs) through the backhaul network. In the context of conventional noncooperative networks, it has been suggested that radio feedback load could be reduced by preventing users with low-quality channels from feeding back their CSI (concept of selective feedback), at the cost of a small fraction of the multiuser diversity gain. In this paper, we investigate the translation of this selective feedback concept to MCP systems. According to this technique, users with weak interference links are prevented from feeding back their full CSI to the MCP scheduler. Although efficient, this technique alone cannot mitigate the backhaul overhead related to routing user data possibly to several BSs. To overcome this condition, we propose two schemes: one scheme based on Media Access Control (MAC)-layer scheduling and the other scheme based on physical-layer precoding. These schemes, combined with feedback load reduction, allow for a substantial mitigation of the MCP overheads related to feedback and backhaul load. We analyze the improvements in terms of both user-to-BS feedback reduction and backhaul load reduction, and we show that this framework results in a good tradeoff between performance and overhead for multicell cooperative networks.
Estimating the Number of Mouse Genes and the Duplicated Regions within the Mouse Genome

To elucidate the evolution of mammalian genomes, it is crucial to estimate the number of genes in thegenome and to measure the degree of redundancy in the genome in various species. The number ofhuman protein-coding genes was recently estimated as 35,000-40,000, though it is still controversial.Also, traces of ancient duplications of extensive chromosomal regions were being discovered withinthe human genome. In this study, we estimated the number of mouse genes using expressed sequencetags of full-length cDNA library and a set of genes obtained by clustering mRNA sequences fromDDBJ/EMBL/GenBank. We also estimated the duplicated chromosomal regions within the mousegenome using the map information derived from the Mouse Genome Database and the numeroushomologous gene pairs from DDBJ/EMBL/GenBank.