The Electroweak Phase Transition in Ultra Minimal Technicolor

We unveil the temperature-dependent electroweak phase transition in new extensions of the Standard Model in which the electroweak symmetry is spontaneously broken via strongly coupled, nearly-conformal dynamics achieved by the means of multiple matter representations. In particular, we focus on the low energy effective theory introduced to describe Ultra Minimal Walking Technicolor at the phase transition. Using the one-loop effective potential with ring improvement, we identify regions of parameter space which yield a strong first order transition. A striking feature of the model is the existence of a second phase transition associated to the electroweak-singlet sector. The interplay between these two transitions leads to an extremely rich phase diagram.Comment: 38 RevTeX pages, 9 figure

Renal Tumor Invasion Depth and Diameter are the Two Most Accurate Anatomical Features Regarding the Choice of Radical Versus Partial Nephrectomy

Background and Aims: To evaluate simple tumor characteristics (renal tumor diameter and parenchymal invasion depth) compared with more complex classifications, that is, Renal Tumor Invasion Index (RTII) and Preoperative Aspects and Dimensions Used for an Anatomical classification, in predicting the type of nephrectomy (radical vs partial) performed. Material and Methods: A total of 915 patients who had undergone either partial nephrectomy (n=388, 42%) or radical nephrectomy (n=527, 58%) were identified from the Helsinki University Hospital kidney tumor database between 1 January 2006 and 31 December 2014. Tumor maximum diameter and depth of invasion into the parenchyma were estimated from computed tomography or magnetic resonance imaging images and compared with Preoperative Aspects and Dimensions Used for an Anatomical and Renal Tumor Invasion Index. Logistic regression and receiver operating curves were used to compare the parameters at predicting the type of nephrectomy. Results and conclusion: All the anatomical variables of receiver operating curve/area under the curve analyses were significant predictors for the type of nephrectomy. Parenchymal invasion (area under the curve 0.91; 95% confidence interval, 0.89-0.93), RTII (area under the curve 0.91; 95% confidence interval, 0.89-0.93), and diameter (area under the curve 0.91; 95% confidence interval, 0.89-0.93) performed significantly better than Preoperative Aspects and Dimensions Used for an Anatomical classification (area under the curve 0.88; 95% confidence interval, 0.85-0.89). In multivariable analysis, invasion depth was the best predictor of nephrectomy type (percentage correct, 85.6%). Addition of one anatomic parameter into the model of non-anatomical cofactors improved the accuracy of the model significantly, but the addition of more parameters did not. Parenchymal invasion depth and tumor diameter are the most accurate anatomical features for predicting the nephrectomy type. All potential anatomical classification systems should be tested against these two simple characteristics.Peer reviewe

Doppler images and the underlying dynamo. The case of AF Leporis

The (Zeeman-)Doppler imaging studies of solar-type stars very often reveal large high-latitude spots. This also includes F stars that possess relatively shallow convection zones, indicating that the dynamo operating in these stars differs from the solar dynamo. We aim to determine whether mean-field dynamo models of late-F type dwarf stars can reproduce the surface features recovered in Doppler maps. In particular, we wish to test whether the models can reproduce the high-latitude spots observed on some F dwarfs. The photometric inversions and the surface temperature maps of AF Lep were obtained using the Occamian-approach inversion technique. Low signal-to-noise spectroscopic data were improved by applying the least-squares deconvolution method. The locations of strong magnetic flux in the stellar tachocline as well as the surface fields obtained from mean-field dynamo solutions were compared with the observed surface temperature maps. The photometric record of AF Lep reveals both long- and short-term variability. However, the current data set is too short for cycle-length estimates. From the photometry, we have determined the rotation period of the star to be 0.9660+-0.0023 days. The surface temperature maps show a dominant, but evolving, high-latitude (around +65 degrees) spot. Detailed study of the photometry reveals that sometimes the spot coverage varies only marginally over a long time, and at other times it varies rapidly. Of a suite of dynamo models, the model with a radiative interior rotating as fast as the convection zone at the equator delivered the highest compatibility with the obtained Doppler images.Comment: accepted for publication in Astronomy & Astrophysic

Serum tumour associated trypsin inhibitor, as a biomarker for survival in renal cell carcinoma : Scandinavian Journal of Urology

Abstract Objective Tumour associated trypsin inhibitor (TATI) is a peptide that is a marker for several tumours. TATI may also behave as an acute phase reactant in severe inflammatory disease. Overexpression of TATI predicts an unfavourable outcome for many cancers. This study aimed to evaluate the prognostic value of pre- and postoperative concentration of TATI in serum (S-TATI) of patients with renal cell carcinoma (RCC). Materials and methods S-TATI was determined by time resolved immunofluorometric assay in preoperative and postoperative samples that were collected from 132 RCC patients, who underwent partial or complete nephrectomy in Helsinki University Hospital from May 2005 to July 2010. Results Preoperative S-TATI was significantly associated with tumour stage, lymph-node involvement, metastatic stage, Chronic Kidney Disease Stage (CKD grade), and preoperative C-reactive protein level (p?Peer reviewe

Necessary conditions for algorithmic tuning of weather prediction models using OpenIFS as an example

Algorithmic model tuning is a promising approach to yield the best possible forecast performance of multi-scale multi-phase atmospheric models once the model structure is fixed. The problem is to what degree we can trust algorithmic model tuning. We approach the problem by studying the convergence of this process in a semi-realistic case. Let M (x, theta) denote the time evolution model, where x and theta are the initial state and the default model parameter vectors, respectively. A necessary condition for an algorithmic tuning process to converge is that theta is recovered when the tuning process is initialised with perturbed model parameters theta' and the default model forecasts are used as pseudo-observations. The aim here is to gauge which conditions are sufficient in a semi-realistic test setting to obtain reliable results and thus build confidence on the tuning in fully realistic cases. A large set of convergence tests is carried in semi-realistic cases by applying two different ensemble-based parameter estimation methods and the atmospheric forecast model of the Integrated Forecasting System (OpenIFS) model. The results are interpreted as general guidance for algorithmic model tuning, which we successfully tested in a more demanding case of simultaneous estimation of eight OpenIFS model parameters.Peer reviewe

An example of a method to wirelessly transfer measurement data from cows in a free stall barn

Here we describe a wireless data measurement and transfer system that operates within a free stall barn. We report also the reliability of the system. This system was designed and built in Very Intelligent Cow Barn project in 2006-2007

Continuous data assimilation for global numerical weather prediction

A new configuration of the European Centre for Medium-Range Weather Forecasts (ECMWF) incremental 4D-Var data assimilation (DA) system is introduced which builds upon the quasi-continuous DA concept proposed in the mid-1990s. Rather than working with a fixed set of observations, the new 4D-Var configuration exploits the near-continuous stream of incoming observations by introducing recently arrived observations at each outer loop iteration of the assimilation. This allows the analysis to benefit from more recent observations. Additionally, by decoupling the start time of the DA calculations from the observational data cut-off time, real-time forecasting applications can benefit from more expensive analysis configurations that previously could not have been considered. In this work we present results of a systematic comparison of the performance of a Continuous DA system against that of two more traditional baseline 4D-Var configurations. We show that the quality of the analysis produced by the new, more continuous configuration is comparable to that of a conventional baseline that has access to all of the observations in each of the outer loops, which is a configuration not feasible in real-time operational numerical weather prediction. For real-time forecasting applications, the Continuous DA framework allows configurations which clearly outperform the best available affordable non-continuous configuration. Continuous DA became operational at ECMWF in June 2019 and led to significant 2 to 3% reductions in medium-range forecast root mean square errors, which is roughly equivalent to 2-3 hr of additional predictive skill.Peer reviewe