Miracle-dz/UniFAR-FTUs huggingface dataset:
Brachytherapy boost and cancer-specific mortality in favorable high-risk versus other high-risk prostate cancer

Purpose Recent retrospective data suggest that brachytherapy (BT) boost may confer a cancer-specific survival benefit in radiation-managed high-risk prostate cancer. We sought to determine whether this survival benefit would extend to the recently defined favorable high-risk subgroup of prostate cancer patients (T1c, Gleason 4 + 4 = 8, PSA < 10 ng/ml or T1c, Gleason 6, PSA > 20 ng/ml). Material and methods We identified 45,078 patients in the Surveillance, Epidemiology, and End Results database with cT1c-T3aN0M0 intermediate- to high-risk prostate cancer diagnosed 2004-2011 treated with external beam radiation therapy (EBRT) only or EBRT plus BT. We used multivariable competing risks regression to determine differences in the rate of prostate cancer-specific mortality (PCSM) after EBRT + BT or EBRT alone in patients with intermediate-risk, favorable high-risk, or other high-risk disease after adjusting for demographic and clinical factors. Results EBRT + BT was not associated with an improvement in 5-year PCSM compared to EBRT alone among patients with favorable high-risk disease (1.6% vs. 1.8%; adjusted hazard ratio [AHR]: 0.56; 95% confidence interval [CI]: 0.21-1.52, p = 0.258), and intermediate-risk disease (0.8% vs. 1.0%, AHR: 0.83, 95% CI: 0.59-1.16, p = 0.270). Others with high-risk disease had significantly lower 5-year PCSM when treated with EBRT + BT compared with EBRT alone (3.9% vs. 5.3%; AHR: 0.73; 95% CI: 0.55-0.95; p = 0.022). Conclusions Brachytherapy boost is associated with a decreased rate of PCSM in some men with high-risk prostate cancer but not among patients with favorable high-risk disease. Our results suggest that the recently-defined “favorable high-risk” category may be used to personalize therapy for men with high-risk disease.
Biorthogonal Polynomials and Numerical Integration Formulas for Infinite Intervals

In this work, we consider a class of numerical quadrature formulas for the infinite-range integrals ∫ ∞ 0 w(x)f(x)dx, where w(x) = x α e -x and w(x) = x α E p (x), E p (x) being the Exponential Integral. These formulas are obtained by applying the Levin C and Sidi S transformations, two effective convergence acceleration methods, to the asymptotic expansions of ∫ ∞ 0 w(x)/(z - x)dx as z → ∞, and they turn out to be interpolatory. In addition, their abscissas turn out to have some interesting properties: For example, if X ni , i = 1,. ,n, are the abscissas of the appropriate n-point formula, then the polynomial Π n i=1 (z - z ni ) is orthogonal to some set of n real exponential functions, e-σnkx, k = 1,. , n, where σ -1 nk are the zeros of some known polynomials. We provide some tables and numerical examples that show the effectiveness of our numerical quadrature formulas.
Bad-smell prediction from software design model using machine learning techniques

Bad-smell prediction significantly impacts on software quality. It is beneficial if bad-smell prediction can be performed as early as possible in the development life cycle. We present methodology for predicting bad-smells from software design model. We collect 7 data sets from the previous literatures which offer 27 design model metrics and 7 bad-smells. They are learnt and tested to predict bad-smells using seven machine learning algorithms. We use cross-validation for assessing the performance and for preventing over-fitting. Statistical significance tests are used to evaluate and compare the prediction performance. We conclude that our methodology have proximity to actual values.
Identification of consensus patterns in unaligned DNA sequences known to be functionally related

We have developed a method for identifying consensus patterns in a set of unaligned DNA sequences known to bind a common protein or to have some other common biochemical function. The method is based on a matrix representation of binding site patterns. Each row of the matrix represents one of the four possible bases, each column represents one of the positions of the binding site and each element is determined by the frequency the indicated base occurs at the indicated position. The goal of the method is to find the most significant matrix--i.e. the one with the lowest probability of occurring by chance--out of all the matrices that can be formed from the set of related sequences. The reliability of the method improves with the number of sequences, while the time required increases only linearly with the number of sequences. To test this method, we analysed 11 DNA sequences containing promoters regulated by the Escherichia coli LexA protein. The matrices we found were consistent with the known consensus sequence, and could distinguish the generally accepted LexA binding sites from other DNA sequences.
Routing and processing multiple aggregate queries in sensor networks

We present a novel approach to processing continuous aggregate queries in sensor networks, which lifts the assumption of tree-based routing. Given a query workload and a special-purpose gateway node where results are expected, the query optimizer exploits query correlations in order to generate an energy-efficient distributed evaluation plan. The proposed algorithms, named STG and STS, identify common query sub-aggregates, and propose common routing structures to share the sub-aggregates at an early stage. Moreover, they avoid routing sub-aggregates of the same query through long-disjoint paths, thus further reducing the communication cost of result propagation. In this poster, we provide examples to illustrate the functionality and the communication savings of STG and STS compared to the existing tree-based approach.
SearchPanel: A Browser Extension for Managing Search Activity

People often use more than one query when searching for information; they also revisit search results to re-nd information. These tasks are not well-supported by search interfaces and web browsers. We designed and built a Chrome browser extension that helps people manage their ongoing information seeking. The extension combines document and process metadata into an interactive representation of the retrieved documents that can be used for sense-making, for navigation, and for re-nding documents.
Geometry Diagnostics of a Stellar Flare from Fluorescent X-Rays

We present evidence of Fe fluorescent emission in the Chandra HETGS spectrum of the single G-type giant HR 9024 during a large flare. In analogy to solar X-ray observations, we interpret the observed Fe Kα line as being produced by illumination of the photosphere by ionizing coronal X-rays, in which case, for a given Fe photospheric abundance, its intensity depends on the height of the X-ray source. The HETGS observations, together with three-dimensional Monte Carlo calculations to model the fluorescence emission, are used to obtain a direct geometric constraint on the scale height of the flaring coronal plasma. We compute the Fe fluorescent emission induced by the emission of a single flaring coronal loop that well reproduces the observed X-ray temporal and spectral properties according to a detailed hydrodynamic modeling. The predicted Fe fluorescent emission is in good agreement with the observed value within observational uncertainties, pointing to a scale height ≲ 0.3R*. Comparison of the HR 9024 flare with that recently observed on II Peg by Swift indicates the latter is consistent with excitation by X-ray photoionization.
A self-learning fuzzy control method based on RBF neural networks

This paper proposes an self-learning fuzzy control method based on an improved radial basis function neural networks (RBFNN). The architecture of the proposed approach is comprised of a fuzzy controller and an RBFNN. For such an architecture, firstly, an analytical formula is employed to design fuzzy controller. Then, RBFNN based on an efficient locally regularized forward recursive (LRFR) algorithm is described and employed to learn the model of the plant. Finally, the parameters of fuzzy controller are tuned online by self-learning algorithm based on RBFNN. The simulation studies for a heating, ventilation and air-conditioning (HVAC) system demonstrates the validity and performance of the proposed learning algorithm.
Reward, a driver to creativity: mediating role of appraisals of reward between self efficacy and creative performance

The purpose of this dyadic study was to explore the insight that trigger the creative performance. For such purpose self-efficacy and rewards in shape of challenge and threat appraisal were used. A Survey was conducted to collect the data from the public and private sector organizations related to technical education in Punjab. Sample was the faculty member working on positions of instructors, senior instructor and lectures. A total of 302 respondents were analyzed. The results of the analysis show that there is significant relationship among self-efficacy and creative performance. The mediation analysis also shows that challenge appraisal of rewards for creativity and threat appraisal of reward also worked as mediator. Consequently, we reached at the point that having high level of self-efficacy, individuals in technical education organizations appraises the reward as a challenge and perform creatively. And on the other side having low level of self-efficacy, but appraising the Reward as a threat, tends to impact negatively on creative performance.
X-TREPAN : AN EXTENDED TREPAN FOR COMPREHENSIBILITY AND CLASSIFICATION ACCURACY IN ARTIFICIAL NEURAL NETWORKS

In this work, the TREPAN algorithm is enhanced and extended for extracting decision trees from neural networks. We empirically evaluated the performance of the algorithm on a set of databases from real world events. This benchmark enhancement was achieved by adapting Single-test TREPAN and C4.5 decision tree induction algorithms to analyze the datasets. The models are then compared with X-TREPAN for comprehensibility and classification accuracy. Furthermore, we validate the experimentations by applying statistical methods. Finally, the modified algorithm is extended to work with multi-class regression problems and the ability to comprehend generalized feed forward networks is achieved.
Cost-effectiveness of tuberculosis control strategies among immigrants and refugees

Today, in Western Europe, Canada and the USA, more than half of all new active tuberculosis (TB) cases occur among foreign-born migrants. This article examines the impact of migration from high TB-incidence to low TB-incidence countries, and compares the cost-effectiveness of different TB control strategies. A Medline search was conducted to identify relevant English language publications prior to December 2003. Additional articles were identified from the reference lists from these publications. Despite the high proportion of active cases in low-incidence countries attributable to foreign-born residents, the public health impact is relatively low. Current chest radiograph screening programmes have little impact and are not cost-effective. Screening with sputum culture would improve cost-effectiveness marginally. Treatment of latent infection detected through screening with tuberculin skin testing or chest radiographs may require coercive measures to maximise impact and cost-effectiveness. In contrast, contact tracing, particularly within ethnic communities, appears to be more cost-efficient and less intrusive. In low-incidence countries, screening of migrants at entry has little overall impact and is not a very cost-effective tuberculosis control strategy. More effective alternatives include contact tracing delivered through primary care and increased investment in global tuberculosis control.
Approximate Belief Propagation by Hierarchical Averaging of Outgoing Messages

This paper presents an approximate belief propagation algorithm that replaces outgoing messages from a node with the averaged outgoing message and propagates messages from a low resolution graph to the original graph hierarchically. The proposed method reduces the computational time by half or two-thirds and reduces the required amount of memory by 60% compared with the standard belief propagation algorithm when applied to an image. The proposed method was implemented on CPU and GPU, and was evaluated against Middlebury stereo benchmark dataset in comparison with the standard belief propagation algorithm. It is shown that the proposed method outperforms the other in terms of both the computational time and the required amount of memory with minor loss of accuracy.
Odds Prediction of Drought Category Using Loglinear Models Based on SPI in the Northeast of Thailand

The prediction of drought category is performed through Loglinear modeling for three dimensional contingency tables. The frequencies of drought categories are evaluated from a 12-month time scale by means of Standardized Precipitation Index (SPI), using the raw data obtained from 19 rain gauge stations in 19 provinces in the Northeast of Thailand. SPI monthly values were computed in a 12 month time scale for the period from January 1962 to December 2009, within 48 years or 576 months in each of 19 rainfall stations. The results show that the selected quasi-association loglinear model is an adequate model and appropriate tool to fit the data from 19 stations (P-value = 0.927). The values of various drought class transitions are estimated in three consecutive months. The predicted odds ratios and the corresponding confidence intervals are evaluated to predict the drought classes’ transitions. Even if, most of the results display for more normal drought classes than those of moderate or severity drought classes; however, there are still some areas of investigation that drought could be developed. Therefore, future monitoring of drought watch system is needed to be set the pace in these areas to keep up with them. Furthermore, an appropriate statistical model to predict drought phenomenon in each area is necessary and is probably able to provide more effectiveness in the administrative management of hazard from drought. Key Words: Odds ratio; Drought class transitions; Three-dimensional loglinear models
An Engineering Toolbox to Build Situation Aware Ambient Assisted Living Systems

Due to increasing anticipated average life and health expenditure ambient assisted living (AAL) systems attract the attention of researchers. To successfully build and deploy AAL systems knowledge from different fields of computer science is needed: pervasive computing to gain the raw data, machine learning and pattern recognition to interpret these data and HCI knowledge to allow implicit interaction with the system.In this paper we propose a reference architecture for building AAL systems. Based on this reference architecture we introduce a toolbox that simplifies the development of AAL systems. The toolbox consists of a meta-model for pipeline systems, a low-level context model, high-level context ontologies, customizable components and tool support.
Simple robust bearing-range source's localization with curved wavefronts

In array processing, the far-field assumption of planar wavefronts is widely used by direction of arrival (DOA) estimators but not always satisfied. In this letter, we introduce a new method for bearing-range estimation, which extends classical subspace-based bearing estimators to a curved wavefront context. The bearing estimation is provided by a one-dimensional procedure, and ranges are simply analytically deduced from the bearing estimates. The proposed approach is illustrated by the introduction of the music curved wavefront (MCW) algorithm.
EMC ’ 09 / Kyoto SAR Calculation Using Numerical Human Model Exposed to EM Wave from Commercial Wireless Terminal at 150 MHz

The commercial wireless terminal is usually hold in the vicinity of a human body, it is needed an attention for the specific absorption rate (SAR) in an abdomen. In addition, the electromagnetic (EM) waves from the wireless terminal penetrate a deep region of body, because the wavelength of the EM waves of the wireless terminal operating in VHF band is longer than those of a cellular phone operating in the GHz band. In this paper, to evaluate the SARs of a male and a female when they are wearing a wireless terminal on their abdomens, we calculated the SAR in the abdomen using the numerical human model exposed to EM waves from several positions of a normal mode helical antenna (NHA) with a metallic case.
Q band multi-beam antenna based on MEMS and Substrate Integrated Waveguide technology

A Micro-Electro-Mechanical System (MEMS) based Q band Substrate Integrated Waveguide (SIW) multi-beam antenna was designed, fabricated and measured. Fed by a 4×4 SIW Butler matrix, the prototype antenna can generate 4 beams simultaneously with respect to its 4 ports. The radiators of the proposed antenna are SIW transverse slots. At 45GHz, the measured 4 beam angles with respect to normal direction are -15°, -40°, 15° and 40°.
Development of Decision Support System for Jute Grading

-It is well known that jute plays an important role in our daily life. Jute ranks next to cotton as the most important natural fibre. Corchorus capsularis is popularly known as White jute or 'tita' pat and Corchorus olitorius known as Tossa jute or 'mitha' pat. Basically jute is regarded as cash crop. The role of jute in eastern part of India is important from economic point of view. India earns 1450 crores foreign exchange out of jute and its products. Approximately 40 lakh farmer families are depend it on jute cultivation. Apart from that more or less 20 lakh people are involved directly or indirectly in this trade. Jute has an important position in the packaging world for many years due to its cheapness, hardwearing properties and biodegradability. The fibre, which spins into the fine yarn, is considered to be of very good quality. The process of classification of the fibre quality on the basis of the physical properties of unsorted jute fibre is called Jute Grading. It is a process of establishment of certain standards based on the intrinsic physical properties of the fibre with a view to subdivide it into several grades or classes. Quality of jute determines its end uses. For diversification of jute products supply of superior and fine quality of fibre has to be ensured. Thus improvement of quality of jute fibre has assumed much importance in the recent times. The ICT technique aimed at enabling the user to make faster and logical decisions. Keywords-Jute grading, database, Decision support system, ICT
Synthesis of Low Power NOC Topologies under Bandwidth Constraints

We propose an efficient design flow for the automatic synthesis of Networkon-Chip (NOC) topologies. The specification of the problem is given as a netlist of IP cores and their communication requirements. Each IP is characterized by its area. A communication constraint is denoted by its source and destination IP and a minimum bandwidth requirement. Together with the specification, the users provides a percentage of the chip area that they want to allocate for the communication network. Then, given the clock period of the network (that we assume to be synchronous), and a target technology, the proposed design flow explores the entire topology space and returns an optimal NOC where each router has a position and a routing table assigned. We consider two optimality criteria: power consumption and power delay product. Our design flow, which is based on an approximation algorithm, is efficient and highlights the delicate trade-off balance between cost of communication and cost of switching.
Success and satisfaction of members of selected adult male bowling teams registered with the Greater Greensboro Bowling Association and their task and affiliation motivation

It was the purpose of this study, conducted at the University of North Carolina at Greensboro during the Spring of 1974, to investigate success and satisfaction of adult male bowlers and their task and affiliation motivation. It was hypothesized that high task and high affiliation motivated adult male bowlers are more successful and satisfied than low task and low affiliation motivated adult male bowlers. The subjects were one hundred six adult male bowlers. All of them lived in Greensboro, North Carolina or within twenty miles of the corporate limits of the city. Each subject was a member of the Metro 850 or Century League, sanctioned by the American Bowling Congress and registered with the Greater Greensboro Bowling Association. All of the subjects bowled in the Brunswick Friendly Lanes establishment.
Development of a Novel, Single-Cycle Replicable Rift Valley Fever Vaccine

Rift Valley fever virus (RVFV) (genus Phlebovirus, family Bunyaviridae) is an arbovirus that causes severe disease in humans and livestock in sub-Saharan African countries. Although the MP-12 strain of RVFV is a live attenuated vaccine candidate, neuroinvasiveness and neurovirulence of MP-12 in mice may be a concern when vaccinating certain individuals, especially those that are immunocompromised. We have developed a novel, single-cycle replicable MP-12 (scMP-12), which carries an L RNA, M RNA mutant encoding a mutant envelope protein lacking an endoplasmic reticulum retrieval signal and defective for membrane fusion function, and S RNA encoding N protein and green fluorescent protein. The scMP-12 underwent efficient amplification, then formed plaques and retained the introduced mutation after serial passages in a cell line stably expressing viral envelope proteins. However, inoculation of the scMP-12 into naïve cells resulted in a single round of viral replication, and production of low levels of noninfectious virus-like particles. Intracranial inoculation of scMP-12 into suckling mice did not cause clinical signs or death, a finding which demonstrated that the scMP-12 lacked neurovirulence. Mice immunized with a single dose of scMP-12 produced neutralizing antibodies, whose titers were higher than in mice immunized with replicon particles carrying L RNA and S RNA encoding N protein and green fluorescent protein. Moreover, 90% of the scMP-12-immunized mice were protected from wild-type RVFV challenge by efficiently suppressing viremia and replication of the challenge virus in the liver and the spleen. These data demonstrated that scMP-12 is a safe and immunogenic RVFV vaccine candidate.
Band 3 Profile as a Marker of Erythrocyte Changes in Chronic Kidney Disease Patients

Our aim was to study changes in red blood cell (RBC) membrane band 3 profile, as a cumulative marker of RBC changes, in chronic kidney disease (CKD) patients under haemodialysis and recombinant human erythropoietin (rhEPO) therapy and its linkage with resistance to this therapy. We studied 63 CKD patients, 32 responders and 31 non-responders to rhEPO therapy, and 26 healthy individuals. We evaluated the band 3 profile (% of band 3 monomer, high molecular weight aggregates (HMWAg), and proteolytic frag- ments (Pfrag)), membrane-bound haemoglobin (MBH), haematological data, total serum bilirubin, glutathione peroxidase (GPx) and superoxide dismutase activities, total antioxidant status (TAS) and plasma lipid peroxidation (TBA). Compared to controls, band 3 profile presented by CKD patients showed statistically significant lower HMWAg and Pfrag values and a significant higher value in band 3 monomer. GPx, TBA and TAS activities, and TBA/TAS ratio were also signifi- cantly higher in CKD patients. Comparing responders to non-responders CKD patients, significantly lower value in Pfrag and a trend for a higher value in MBH were found in non-responders. Our data suggest that CKD patients present younger RBC population, which could be related to the rhEPO therapy. The adverse plasma environment associated to CKD patients under hemodialysis imposes changes in band 3 profile, particu- larly in non-responders, suggesting that resistance to rhEPO therapy in CKD patients seems to be associated to an increase in RBC damage.