A comparative study of efficacy of tadalafil and alfuzosin regimens in patients of benign prostate hyperplasia

Background: Aim of the study was to compare efficacy of Tadalafil and Alfuzosin regimens in patients of Benign Prostate Hyperplasia.Methods: It was a comparative, prospective, observational, non-invasive, parallel and randomised study conducted at the Outpatient Department of Urology, Rajindra Hospital, Patiala. 60 patients diagnosed with Benign Prostate Hyperplasia along with Lower Urinary Tract Symptoms, out which, 30 patients, consuming Tadalafil and 30 patients consuming Alfuzosin were considered. History regarding the concerned disease and the compliance of treatment was taken. Symptom scores were assessed with the help of International Prostate Symptom Score, Quality of Lifestyle Score and Erectile Dysfunction Score. Physical examination consisting of Focused Neurological Examination along with Digital Rectal Examination were conducted. Parameters like Renal Function Test, Urine analysis, Ultrasound of Prostate and uroflowmetry were also considered.Results: The mean age selected for study was 64 years for Tadalafil and Alfuzosin group. The mean level of IPS Score, Qol Score and ED Score at the first day of inclusion of patients were 23.96±4.49, 4±0.78, and 25.33±4.02 respectively for Tadalafil group and regarding Alfuzosin group they were 25.23±4.84, 3.56±0.81, and 26.1±4.04 respectively. Follow ups were conducted at 15 days, 1 month and 3 months for both the groups which were found to be statistically significant after 3 months and Alfuzosin showed a favourable result.Conclusions: Alfuzosin 10mg given at daily dose was found to have higher efficacy than Tadalafil (5mg)

Robust and Automatic Data Clustering: Dirichlet Process meets Median-of-Means

Clustering stands as one of the most prominent challenges within the realm of unsupervised machine learning. Among the array of centroid-based clustering algorithms, the classic $k$-means algorithm, rooted in Lloyd's heuristic, takes center stage as one of the extensively employed techniques in the literature. Nonetheless, both $k$-means and its variants grapple with noteworthy limitations. These encompass a heavy reliance on initial cluster centroids, susceptibility to converging into local minima of the objective function, and sensitivity to outliers and noise in the data. When confronted with data containing noisy or outlier-laden observations, the Median-of-Means (MoM) estimator emerges as a stabilizing force for any centroid-based clustering framework. On a different note, a prevalent constraint among existing clustering methodologies resides in the prerequisite knowledge of the number of clusters prior to analysis. Utilizing model-based methodologies, such as Bayesian nonparametric models, offers the advantage of infinite mixture models, thereby circumventing the need for such requirements. Motivated by these facts, in this article, we present an efficient and automatic clustering technique by integrating the principles of model-based and centroid-based methodologies that mitigates the effect of noise on the quality of clustering while ensuring that the number of clusters need not be specified in advance. Statistical guarantees on the upper bound of clustering error, and rigorous assessment through simulated and real datasets suggest the advantages of our proposed method over existing state-of-the-art clustering algorithms

On Petri Nets with Hierarchical Special Arcs

We investigate the decidability of termination, reachability, coverability and deadlock-freeness of Petri nets endowed with a hierarchy of places, and with inhibitor arcs, reset arcs and transfer arcs that respect this hierarchy. We also investigate what happens when we have a mix of these special arcs, some of which respect the hierarchy, while others do not. We settle the decidability status of the above four problems for all combinations of hierarchy, inhibitor, reset and transfer arcs, except the termination problem for two combinations. For both these combinations, we show that deciding termination is as hard as deciding the positivity problem on linear recurrence sequences -- a long-standing open problem

A comparative study of efficacy of febuxostat and allopurinol regimens in patients of hyperuricemia

Background: Gout, resulting from the precipitation of urate crystals in the tissues and the subsequent inflammatory response, causes an exquisitely painful distal monoarthritis alongwith joint destruction, subcutaneous deposits (tophi), renal calculi. The main culprit is uric Acid, which is a waste product formed due to purine metabolism. Gout Patients either produce excess Uric acid or are unable to excrete Uric acid produced in normal conditions. Uric acid lowering therapy (ULT) has become popular regarding management of gout. Nowadays. 2 drugs which are responsible for decreasing synthesis of Uric acid are Febuxostat and Allopurinol. The purpose of this study is to determine efficacy of Febuxostat and Allopurinol experienced by patients during course of therapy.Methods: It was an open, prospective, observational, non-invasive, parallel and randomised study, conducted at the Outpatient Department of Urology, Rajindra Hospital, Patiala. It had 60 patients of gout, out which, 30 patients were administered Febuxostat and 30 patients were administered Allopurinol. For each patient, history regarding drug intake was taken, along with analysis of Serum Uric acid profile before prescription and during follow up.Results: The mean age selected for study was 47 years for Febuxostat group and 43 years for Allopurinol group. Mean Urate (mg%) in pre-treatment stage of patients of Febuxostat group is about 8.28 whereas for Allopurinol group its about 8.61. Mean urate levels after 4 follow ups (10 days each) were conducted. The mean Urate level at 10, 20, 30, 40 days were conducted at each group which were found to be statistically significant and the results of Febuxostat group was found to be favourable.Conclusions: Febuxostat, (40mg) given at daily dose was found to have higher efficacy than allopurinol, at a dose of 100mg (zyloric) which is the most commonly prescribed dose in order to lower the serum urate level

Data acquisition system for muon tracking in a muon scattering tomography setup

We report here the development of a multi-channel DAQ system for muon tracking in a muon scattering tomography setup. The salient features of the proposed DAQ system are direct acquisition and processing of LVDS signals, 500 MHz sampling frequency and scalability. It consists of front-end electronics stage built around NINO ASIC. The back-end electronics is configured with Intel/Altera MAX-10 FPGA development board which transmits data to the storage following UART protocol. The proposed DAQ system has been tested for its performance using a position sensitive glass RPC detector with two-dimensional 8X8 readout strip configuration

Determination of charge spread, position resolution, energy resolution and gain uniformity of Gas Electron Multipliers (GEM)

Gas electron multipliers (GEM) detectors are gaseous detectors widely used for tracking and imaging applications due to their good position resolution, high efficiency at high irradiation rates, among other factors. In the present work, position resolution, charge spread, energy resolution and gain uniformity have been investigated experimentally for single and double GEM geometries using an Fe-55 source. The position resolution measurements have been performed by a novel method, using a high precision instrument for source movement and is found to be highly successful. The result shows that the double GEM can resolve positions with sigma values up to 36.8 micron and 54.6 micron in x and y directions, respectively. To validate the experimental results, a Garfield simulation work has been carried out on charge spread

Generalized particle dynamics in anti de Sitter spaces: A source for dark energy

We consider the generalized particle dynamics, proposed by us, in brane world formalisms for an asymptotically anti de Sitter background. The present framework results in a new model that accounts for the late acceleration of the universe. An effective Dark Energy equation of state, exhibiting a phantom like behaviour, is generated. The model is derived by embedding the physical FRW universe in a $(4+1)$-dimensional effective space-time, induced by the generalized particle dynamics. We corroborate our results with present day observed cosmological parameters.Comment: 18 pages, 6 figures. Final version to appear in IJMP

Brane inflation in background supergravity

We propose a model of inflation in the framework of brane cosmology driven by background supergravity. Starting from bulk supergravity we construct the inflaton potential on the brane and employ it to investigate for the consequences to inflationary paradigm. To this end, we derive the expressions for the important parameters in brane inflation, which are somewhat different from their counterparts in standard cosmology, using the one loop radiative corrected potential. We further estimate the observable parameters and find them to fit well with recent observational data by confronting with WMAP7 using CAMB. We also analyze the typical energy scale of brane inflation with our model, which resonates well with present estimates from cosmology and standard model of particle physics.Comment: 14 pages, 7 figures, 1 table, some minor corrections in the text, Abstract slightly modified, Accepted for publication in Physical Review

VI Jornades IET "Bretxa salarial i desigualtats de gènere en el mercat de treball"

Quantitative structure–property relationship (QSPR) models used for prediction of property of untested chemicals can be utilized for prioritization plan of synthesis and experimental testing of new compounds. Validation of QSPR models plays a crucial role for judgment of the reliability of predictions of such models. In the QSPR literature, serious attention is now given to external validation for checking reliability of QSPR models, and predictive quality is in the most cases judged based on the quality of predictions of property of a single test set as reflected in one or more external validation metrics. Here, we have shown that a single QSPR model may show a variable degree of prediction quality as reflected in some variants of external validation metrics like <i>Q</i>²_F1, <i>Q</i>²_F2, <i>Q</i>²_F3, CCC, and <i>r_m</i>² (all of which are differently modified forms of predicted variance, which theoretically may attain a maximum value of 1), depending on the test set composition and test set size. Thus, this report questions the appropriateness of the common practice of the “classic” approach of external validation based on a single test set and thereby derives a conclusion about predictive quality of a model on the basis of a particular validation metric. The present work further demonstrates that among the considered external validation metrics, <i>r_m</i>² shows statistically significantly different numerical values from others among which CCC is the most optimistic or less stringent. Furthermore, at a given level of threshold value of acceptance for external validation metrics, <i>r_m</i>² provides the most stringent criterion (especially with Δ<i>r</i>_<i>m</i>² at highest tolerated value of 0.2) of external validation, which may be adopted in the case of regulatory decision support processes