Detection of SUSY Signals in Stau Neutralino Co-annihilation Region at the LHC

We study the prospects of detecting the signal in the stau neutralino co-annihilation region at the LHC using tau leptons. The co-annihilation signal is characterized by the stau and neutralino mass difference (dM) to be 5-15 GeV to be consistent with the WMAP measurement of the cold dark matter relic density as well as all other experimental bounds within the minimal supergravity model. Focusing on tau's from neutralino_2 --> tau stau --> tau tau neutralino_1 decays in gluino and squark production, we consider inclusive MET+jet+3tau production, with two tau's above a high E_T threshold and a third tau above a lower threshold. Two observables, the number of opposite-signed tau pairs minus the number of like-signed tau pairs and the peak position of the di-tau invariant mass distribution, allow for the simultaneous determination of dM and M_gluino. For dM = 9 GeV and M_gluino = 850 GeV with 30 fb^-1 of data, we can measure dM to 15% and M_gluino to 6%.Comment: 4 pages LaTex, 3 figures. To appear in Proceedings of SUSY06, the 14th International Conference on Supersymmetry and the Unification of Fundamental Interactions, UC Irvine, California, 12-17 June 2006. A typo in a reference is correcte

Color dynamics of cooked sausages after nitrite reduction and incorporation of biologically active substances

In most cases, the color of meat products is the factor influencing consumer choice. It’s formation and preservation is the highest priority. Sodium nitrite is used for fixation of the pleasant pink-red color, but also has a negative image from the consumers oriented towards clean label products. The valorization of rose oil-industry by-products by their incorporation in foods as natural additives is growing research area. The formulated cooked sausage recipes, contain blend of three biologically active substances (BAS) and different level of sodium nitrite reductions: AN100, AN75, AN50, AN25, AN0 and control - C. Color attributes CIE L*, a*, b* were assessed during 14 days of chilled storage (0-4 °C) and their changes in dynamics were evaluated every 10 min for an hour at air exposure. The incorporation of the inhibit the oxidation of meat pigments during the chilled storage and slowed down the fading of the pinkred color of the cross-cut surface during the 60 min of air exposure. The sausages produced with up to 50 % nitrite reduction and the blend of three BAS have lower lightness (L*), higher intensity of the red color (a*) and lower yellowness (b*) of the cross-cut surface in comparison to the control

Parallel Unsmoothed Aggregation Algebraic Multigrid Algorithms on GPUs

We design and implement a parallel algebraic multigrid method for isotropic graph Laplacian problems on multicore Graphical Processing Units (GPUs). The proposed AMG method is based on the aggregation framework. The setup phase of the algorithm uses a parallel maximal independent set algorithm in forming aggregates and the resulting coarse level hierarchy is then used in a K-cycle iteration solve phase with a $\ell^1$-Jacobi smoother. Numerical tests of a parallel implementation of the method for graphics processors are presented to demonstrate its effectiveness.Comment: 18 pages, 3 figure

Early perioperative res ults in 53 cases of locally rec urrent colorectal cancer

Purpose: The objective of this study was to analyze retrospectively the early perioperative results in a cohort of 53 patients with localy reccurent colorectal cancer (CRC).Material and methods: The study covered 53 patients with CRC 21 males and 32 females at a mean age of 62 years treated in the Clinic of Liver, Biliary, Pancreatic and General Surgery, Tokuda Hospital of Sofia, during the period from January 2007 to March 2013. Any necessary diagnostic and surgical methods were applied.Results: The locally recurrent CRC is a challenge for the surgeon because of the fact that in most cases it engages adjacent anatomical structures and organs, on the one hand, and it is accompanied by complications, on the other hand.Conclusion: Achievement of good late results in patients with recurrent CRC is due to radicality of the interventions. Most often, they should be multivisceral resections. The presence of intestinal obstruction of varying degree and of synchronous peritoneal and liver metastases commonly limit the possibilities for surgical interference with the disease. Particular attention should be paid to possible neoadjuvant treatment capable of reducing the stage of diasease and improving the perioperative outcomes. Therapeutic behaviour should be strictly individual and consider any possible options. The experience of the surgical team is extremely important, too

Locally advanced adenocarcinoma of the supramesocolic part of the colon . Feat ures of surgical treatment and challenges

Purpose: The objective of the present study was to analyze the early results from the surgical treatment of locally advanced carcinoma of the colon in its transverse section and the two flexures.Material and methods: The study covered 36 patients with locally advanced colonic carcinoma, 19 males and 17 females at a mean age of 65,6 years, treated in the Clinic of Liver, Biliary, Pancreatic and General Surgery, Tokuda Hospital of Sofia during the period from January 2007 to March 2013. Any necessary diagnostic and surgical methods were applied.Results: Multivisceral resections were commonly performed in order to achieve a radical surgery in cases of locally advanced disease. Great surgeon`s experience in liver, biliary and pancreatic interventions is obligatorily required. In this paper we share our experience in the treatment of this disease for a period of 6 years.Conclusion: Our application of the multivisceral resections results in surgical radicality along with acceptable levels of perioperative morbidity and mortality rates when compared to other studies in in the foreign literature available

Multivisceral ‘en-bloc` resections of colorectal tumours - milestones in the surgical techniques

Purpose: Colorectal tumours (CRT) consisting mainly of colorectal cancer (CRC) are diagnosed sometimes at an advanced T4 stage, i. e. local involvement of neighbouring organ/organs and anatomical structure/ structures. Aggressive surgical approach preceded and/or followed by neo-adjuvant/adjuvant therapy is advocated because of proven benefit for the patient. The aim of this study was to carry out a literature survey, on the one hand, and to analyze the cases from the authors` institutional experience, on the other hand, in an attempt to submit for consideration the milestones of the multivisceral en-block resections in cases of locally advanced CRTs, i.e. to describe the specific surgical approaches depending on different tumour location and peritumoural involvement of adjacent structures and organs.Material and methods: A retrospective analysis of 154 cases of CRT was performed, all of them operated in the Clinic of Liver, Biliary, Pancreatic and General Surgery, Tokuda Hospital of Sofia, from January 1, 2007 to March 31, 2013. All the patients were diagnosed in an advanced T4-stage and received multivisceral en-bloc resections. Three main groups of methods that had been used were analyzed: 1) preoperative diagnosis, giving a hint of multivisceral en-bloc resection; 2) intraoperative assessment - gross tumour appearance, frozen sections (?), final histological examinations, and 3) surgical methods.Results: Early morbidity and mortality rates were 22,6% and 5,8%, respectively, without any significant difference when compared with ‘simple` colon and rectum resections and with literature data available.Conclusion: Multivisceral en-bloc resection for CRCs has been performed in more than 10% of the cases. It benefits the long-term prognosis. Tumour location and number of resected organs are essential characteristics of these procedures and they are independently associated with the quantity of intraoperative blood loss, higher early morbidity rates and more frequent local recurrence

High Dielectric Permittivity in AFe1/2_{1 / 2}B1/2_{1 / 2}O3_{3} Nonferroelectric Perovskite Ceramics (A - Ba, Sr, Ca; B - Nb, Ta, Sb)

AFe$_{1 / 2}$B$_{1 / 2}$O$_{3}$(A- Ba, Sr, Ca; B-Nb, Ta, Sb) ceramics were synthesized and temperature dependencies of the dielectric permittivity were measured at different frequencies. The experimental data obtained show very high values of the dielectric permittivity in a wide temperature interval that is inherent to so-called high-k materials. The analyses of these data establish a Maxwell-Wagner mechanism as a main source for the phenomenon observed.Comment: 6 pages, 7 figure

Outlier detection algorithms over fuzzy data with weighted least squares

In the classical leave-one-out procedure for outlier detection in regression analysis, we exclude an observation and then construct a model on the remaining data. If the difference between predicted and observed value is high we declare this value an outlier. As a rule, those procedures utilize single comparison testing. The problem becomes much harder when the observations can be associated with a given degree of membership to an underlying population, and the outlier detection should be generalized to operate over fuzzy data. We present a new approach for outlier detection that operates over fuzzy data using two inter-related algorithms. Due to the way outliers enter the observation sample, they may be of various order of magnitude. To account for this, we divided the outlier detection procedure into cycles. Furthermore, each cycle consists of two phases. In Phase 1, we apply a leave-one-out procedure for each non-outlier in the dataset. In Phase 2, all previously declared outliers are subjected to Benjamini–Hochberg step-up multiple testing procedure controlling the false-discovery rate, and the non-confirmed outliers can return to the dataset. Finally, we construct a regression model over the resulting set of non-outliers. In that way, we ensure that a reliable and high-quality regression model is obtained in Phase 1 because the leave-one-out procedure comparatively easily purges the dubious observations due to the single comparison testing. In the same time, the confirmation of the outlier status in relation to the newly obtained high-quality regression model is much harder due to the multiple testing procedure applied hence only the true outliers remain outside the data sample. The two phases in each cycle are a good trade-off between the desire to construct a high-quality model (i.e., over informative data points) and the desire to use as much data points as possible (thus leaving as much observations as possible in the data sample). The number of cycles is user defined, but the procedures can finalize the analysis in case a cycle with no new outliers is detected. We offer one illustrative example and two other practical case studies (from real-life thrombosis studies) that demonstrate the application and strengths of our algorithms. In the concluding section, we discuss several limitations of our approach and also offer directions for future research

Outlier detection algorithms over fuzzy data with weighted least squares

In the classical leave-one-out procedure for outlier detection in regression analysis, we exclude an observation and then construct a model on the remaining data. If the difference between predicted and observed value is high we declare this value an outlier. As a rule, those procedures utilize single comparison testing. The problem becomes much harder when the observations can be associated with a given degree of membership to an underlying population, and the outlier detection should be generalized to operate over fuzzy data. We present a new approach for outlier detection that operates over fuzzy data using two inter-related algorithms. Due to the way outliers enter the observation sample, they may be of various order of magnitude. To account for this, we divided the outlier detection procedure into cycles. Furthermore, each cycle consists of two phases. In Phase 1, we apply a leave-one-out procedure for each non-outlier in the dataset. In Phase 2, all previously declared outliers are subjected to Benjamini–Hochberg step-up multiple testing procedure controlling the false-discovery rate, and the non-confirmed outliers can return to the dataset. Finally, we construct a regression model over the resulting set of non-outliers. In that way, we ensure that a reliable and high-quality regression model is obtained in Phase 1 because the leave-one-out procedure comparatively easily purges the dubious observations due to the single comparison testing. In the same time, the confirmation of the outlier status in relation to the newly obtained high-quality regression model is much harder due to the multiple testing procedure applied hence only the true outliers remain outside the data sample. The two phases in each cycle are a good trade-off between the desire to construct a high-quality model (i.e., over informative data points) and the desire to use as much data points as possible (thus leaving as much observations as possible in the data sample). The number of cycles is user defined, but the procedures can finalize the analysis in case a cycle with no new outliers is detected. We offer one illustrative example and two other practical case studies (from real-life thrombosis studies) that demonstrate the application and strengths of our algorithms. In the concluding section, we discuss several limitations of our approach and also offer directions for future research