Antimicrobial drug use and risk factors associated with treatment incidence and mortality in Swiss veal calves reared under improved welfare conditions

Ninety-one Swiss veal farms producing under a label with improved welfare standards were visited between August and December 2014 to investigate risk factors related to antimicrobial drug use and mortality. All herds consisted of own and purchased calves, with a median of 77.4% of purchased calves. The calves' mean age was 29±15days at purchasing and the fattening period lasted at average 120±28 days. The mean carcass weight was 125±12kg. A mean of 58±33 calves were fattened per farm and year, and purchased calves were bought from a mean of 20±17 farms of origin. Antimicrobial drug treatment incidence was calculated with the defined daily dose methodology. The mean treatment incidence (TIADD) was 21±15 daily doses per calf and year. The mean mortality risk was 4.1%, calves died at a mean age of 94±50 days, and the main causes of death were bovine respiratory disease (BRD, 50%) and gastro-intestinal disease (33%). Two multivariable models were constructed, for antimicrobial drug treatment incidence (53 farms) and mortality (91 farms). No quarantine, shared air space for several groups of calves, and no clinical examination upon arrival at the farm were associated with increased antimicrobial treatment incidence. Maximum group size and weight differences >100kg within a group were associated with increased mortality risk, while vaccination and beef breed were associated with decreased mortality risk. The majority of antimicrobial treatments (84.6%) were given as group treatments with oral powder fed through an automatic milk feeding system. Combination products containing chlortetracycline with tylosin and sulfadimidine or with spiramycin were used for 54.9%, and amoxicillin for 43.7% of the oral group treatments. The main indication for individual treatment was BRD (73%). The mean age at the time of treatment was 51 days, corresponding to an estimated weight of 80-100kg. Individual treatments were mainly applied through injections (88.5%), and included administration of fluoroquinolones in 38.3%, penicillines (amoxicillin or benzylpenicillin) in 25.6%, macrolides in 13.1%, tetracyclines in 12.0%, 3th and 4th generation cephalosporines in 4.7%, and florfenicol in 3.9% of the cases. The present study allowed for identifying risk factors for increased antimicrobial drug treatment and mortality. This is an important basis for future studies aiming at reducing treatment incidence and mortality in veal farms. Our results indicate that improvement is needed in the selection of drugs for the treatment of veal calves according to the principles of prudent use of antibiotics.

Non-metastatic castrate-resistant prostate cancer: a call for improved guidance on clinical management.

BACKGROUND Guidelines on the clinical management of non-metastatic castrate-resistant prostate cancer (nmCRPC) generally focus on the need to continue androgen deprivation therapy and enrol patients into clinical trials of investigational agents. This guidance reflects the lack of clinical trial data with established agents in the nmCRPC patient population and the need for trials of new agents. AIM To review the evidence base and consider ways of improving the management of nmCRPC. CONCLUSION Upon the development of castrate resistance, it is essential to rule out the presence of metastases or micrometastases by optimising the use of bone scans and possibly newer procedures and techniques. When nmCRPC is established, management decisions should be individualised according to risk, but risk stratification in this diverse population is poorly defined. Currently, prostate-specific antigen (PSA) levels and PSA doubling time remain the best method of assessing the risk of progression and response to treatment in nmCRPC. However, optimising imaging protocols can also help assess the changing metastatic burden in patients with CRPC. Clinical trials of novel agents in nmCRPC are limited and have problems with enrolment, and therefore, improved risk stratification and imaging may be crucial to the improved management. The statements presented in this paper, reflecting the views of the authors, provide a discussion of the most recent evidence in nmCRPC and provide some advice on how to ensure these patients receive the best management available. However, there is an urgent need for more data on the management of nmCRPC.

Assessing the improved discriminatory power of a new biomarker in prognostic models

Although the area under the receiver operating characteristic (AUC) is the most popular measure of the performance of prediction models, it has limitations, especially when it is used to evaluate the added discrimination of a new biomarker in the model. Pencina et al. (2008) proposed two indices, the net reclassification improvement (NRI) and integrated discrimination improvement (IDI), to supplement the improvement in the AUC (IAUC). Their NRI and IDI are based on binary outcomes in case-control settings, which do not involve time-to-event outcome. However, many disease outcomes are time-dependent and the onset time can be censored. Measuring discrimination potential of a prognostic marker without considering time to event can lead to biased estimates. In this dissertation, we have extended the NRI and IDI to survival analysis settings and derived the corresponding sample estimators and asymptotic tests. Simulation studies were conducted to compare the performance of the time-dependent NRI and IDI with Pencina’s NRI and IDI. For illustration, we have applied the proposed method to a breast cancer study.^ Key words: Prognostic model, Discrimination, Time-dependent NRI and IDI ^

Improved Techniques for Acquisition and Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Detecting Vascular Permeability in the Central Nervous System

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive technique for quantitative assessment of the integrity of blood-brain barrier and blood-spinal cord barrier (BSCB) in the presence of central nervous system pathologies. However, the results of DCE-MRI show substantial variability. The high variability can be caused by a number of factors including inaccurate T1 estimation, insufficient temporal resolution and poor contrast-to-noise ratio. My thesis work is to develop improved methods to reduce the variability of DCE-MRI results. To obtain fast and accurate T1 map, the Look-Locker acquisition technique was implemented with a novel and truly centric k-space segmentation scheme. In addition, an original multi-step curve fitting procedure was developed to increase the accuracy of T1 estimation. A view sharing acquisition method was implemented to increase temporal resolution, and a novel normalization method was introduced to reduce image artifacts. Finally, a new clustering algorithm was developed to reduce apparent noise in the DCE-MRI data. The performance of these proposed methods was verified by simulations and phantom studies. As part of this work, the proposed techniques were applied to an in vivo DCE-MRI study of experimental spinal cord injury (SCI). These methods have shown robust results and allow quantitative assessment of regions with very low vascular permeability. In conclusion, applications of the improved DCE-MRI acquisition and analysis methods developed in this thesis work can improve the accuracy of the DCE-MRI results.

Improved digital elevation model (DEM) for Lake Eyre, Australia

Here we demonstrate the applicability of using altimetry data and Landsat imagery to provide the most accurate digital elevation model (DEM) of Australia's largest playa lake - Lake Eyre. We demonstrate through the use of geospatial techniques a robust assessment of lake area and volume of recent lake-filling episodes whilst also providing the most accurate estimates of area and volume for larger lake filling episodes that occurred throughout the last glacial cycle. We highlight that at a depth of 25 m Lake Mega-Eyre would merge with the adjacent Lake Mega-Frome to form an immense waterbody with a combined area of almost 35,000 km**2 and a combined volume of ~520 km**3. This would represent a vast water body in what is now the arid interior of the Australian continent. The improved DEM is more reliable from a geomorphological and hydrological perspective and allows a more accurate assessment of water balance under the modern hydrological regime. The results presented using GLAS/ICESat data suggest that earlier historical soundings were correct and the actual lowest topographic point in Australia is -15.6 m below sea level. The results also contrast nicely the different basin characteristics of two adjacent lake systems; Lake Eyre and Lake Frome.

Improved geoid solution for the Weddell Sea region

We present a geoid solution for the Weddell Sea and adjacent continental Antarctic regions. There, a refined geoid is of interest, especially for oceanographic and glaciological applications. For example, to investigate the Weddell Gyre as a part of the Antarctic Circumpolar Current and, thus, of the global ocean circulation, the mean dynamic topography (MDT) is needed. These days, the marine gravity field can be inferred with high and homogeneous resolution from altimetric height profiles of the mean sea surface. However, in areas permanently covered by sea ice as well as in coastal regions, satellite altimetry features deficiencies. Focussing on the Weddell Sea, these aspects are investigated in detail. In these areas, ground-based data that have not been used for geoid computation so far provide additional information in comparison with the existing high-resolution global gravity field models such as EGM2008. The geoid computation is based on the remove-compute-restore approach making use of least-squares collocation. The residual geoid with respect to a release 4 GOCE model adds up to two meters and more in the near-coastal and continental areas of the Weddell Sea region, also in comparison with EGM2008. Consequently, the thus refined geoid serves to compute new estimates of the regional MDT and geostrophic currents.

Improved ore processing assessed by digital image análisis of the ores: a key to the sustainable development of the Iberian Pyrite Belt

Mining in the Iberian Pyrite Belt (IPB), the biggest VMS metallogenetic province known in the world to date, has to face a deep crisis in spite of the huge reserves still known after ≈5 000 years of production. This is due to several factors, as the difficult processing of complex Cu-Pb-Zn-Ag- Au ores, the exhaustion of the oxidation zone orebodies (the richest for gold, in gossan), the scarce demand for sulphuric acid in the world market, and harder environmental regulations. Of these factors, only the first and the last mentioned can be addressed by local ore geologists. A reactivation of mining can therefore only be achieved by an improved and more efficient ore processing, under the constraint of strict environmental controls. Digital image analysis of the ores, coupled to reflected light microscopy, provides a quantified and reliable mineralogical and textural characterization of the ores. The automation of the procedure for the first time furnishes the process engineers with real-time information, to improve the process and to preclude or control pollution; it can be applied to metallurgical tailings as well. This is shown by some examples of the IPB.

An improved way for evaluating competences: A different approach to project management learning .;

This paper presents a formal initiative for monitoring the competence acquisition by a team of students with different backgrounds facing the experience of being working by projects and in a project. These students are inexperienced in the project management field and they play this game on a time-shared manner along with other activities. The goal of this experience is to make some improvements in determining the competence levels acquired by means of how the work is being done. The use of this information, which is out of the scope of this particular work, could make possible to bring additional information to the students involved in terms of their individual competencies and the identification of new opportunities of personal improvement.

An improved bit parallel exact maximum clique algorithm

This paper describes new improvements for BB-MaxClique (San Segundo et al. in Comput Oper Resour 38(2):571–581, 2011 ), a leading maximum clique algorithm which uses bit strings to efficiently compute basic operations during search by bit masking. Improvements include a recently described recoloring strategy in Tomita et al. (Proceedings of the 4th International Workshop on Algorithms and Computation. Lecture Notes in Computer Science, vol 5942. Springer, Berlin, pp 191–203, 2010 ), which is now integrated in the bit string framework, as well as different optimization strategies for fast bit scanning. Reported results over DIMACS and random graphs show that the new variants improve over previous BB-MaxClique for a vast majority of cases. It is also established that recoloring is mainly useful for graphs with high densities.

Improved design of an overhead rail current conductor for application in underground lines

Overhead rail current collector systems for railway traction offer certain features, such as low installation height and reduced maintenance, which make them predominantly suitable for use in underground train infrastructures. Due to the increased demands of modern catenary systems and higher running speeds of new vehicles, a more capable design of the conductor rail is needed. A new overhead conductor rail has been developed and its design has been patented [13]. Modern simulation and modelling techniques were used in the development approach. The new conductor rail profile has a dynamic behaviour superior to that of the system currently in use. Its innovative design permits either an increase of catenary support spacing or a higher vehicle running speed. Both options ensure savings in installation or operating costs. The simulation model used to optimise the existing conductor rail profile included both a finite element model of the catenary and a three-dimensional multi-body system model of the pantograph. The contact force that appears between pantograph and catenary was obtained in simulation. A sensitivity analysis of the key parameters that influence in catenary dynamics was carried out, finally leading to the improved design.

Improved Animal Tracking Algorithm using Distributed Kalman Filter-based Algortihms

Animal tracking has been addressed by different initiatives over the last two decades. Most of them rely on satellite connectivity on every single node and lack of energy-saving strategies. This paper presents several new contributions on the tracking of dynamic heterogeneous asynchronous networks (primary nodes with GPS and secondary nodes with a kinetic generator) motivated by the animal tracking paradigm with random transmissions. A simple approach based on connectivity and coverage intersection is compared with more sophisticated algorithms based on ad-hoc implementations of distributed Kalman-based filters that integrate measurement information using Consensus principles in order to provide enhanced accuracy. Several simulations varying the coverage range, the random behavior of the kinetic generator (modeled as a Poisson Process) and the periodic activation of GPS are included. In addition, this study is enhanced with HW developments and implementations on commercial off-the-shelf equipment which show the feasibility for performing these proposals on real hardware.

New inorganic nanotube polymer nanocomposites: Improved thermal, mechanical and tribological properties in isotactic polypropylene incorporating INT-MoS2.

Environmentally friendly molybdenum disulfide (INT-MoS2) inorganic nanotubes were introduced into an isotactic polypropylene (iPP) polymer matrix to generate novel nanocomposite materials through an advantageous melt-processing route. The effects of INT-MoS2 content on the thermal, mechanical and tribological properties were investigated. The incorporation of INT-MoS2 generates notable performance enhancements through reinforcement effects, highly efficient nucleation activity and excellent lubricating ability in comparison with other nanoparticle fillers such as nanoclays, carbon nanotubes, silicon nitrides and halloysite nanotubes. It was shown that these INT-MoS2 nanocomposites can provide an effective balance between performance, cost effectiveness and processability, and should be of some interest in the area of multifunctional polymer nanocomposite materials.

Improved GaN-based HEMT performance by nanocrystalline diamond capping

As a wide-bandgap semiconductor, gallium nitride (GaN) is an attractive material for next-generation power devices. To date, the capabilities of GaN-based high electron mobility transistors (HEMTs) have been limited by self-heating effects (drain current decreases due to phonon scattering-induced carrier velocity reductions at high drain fields). Despite awareness of this, attempts to mitigate thermal impairment have been limited due to the difficulties involved with placing high thermal conductivity materials close to heat sources in the device. Heat spreading schemes have involved growth of AIGaN/GaN on single crystal or CVD diamond, or capping of fullyprocessed HEMTs using nanocrystalline diamond (NCD). All approaches have suffered from reduced HEMT performance or limited substrate size. Recently, a "gate after diamond" approach has been successfully demonstrated to improve the thermal budget of the process by depositing NCD before the thermally sensitive Schottky gate and also to enable large-area diamond implementation.

Improved estimation of Weibull Parameters considering unreliability uncertainties

We propose a linear regression method for estimating Weibull parameters from life tests. The method uses stochastic models of the unreliability at each failure instant. As a result, a heteroscedastic regression problem arises that is solved by weighted least squares minimization. The main feature of our method is an innovative s-normalization of the failure data models, to obtain analytic expressions of centers and weights for the regression. The method has been Monte Carlo contrasted with Benard?s approximation, and Maximum Likelihood Estimation; and it has the highest global scores for its robustness, and performance.