Mechanical controller for a smartphone

This disclosure describes a mechanically operated controller for a mobile device. The controller includes a grid of black and white squares whose pattern can be mechanically changed. Particular patterns are read by a mobile device, e.g., via its camera, and interpreted as different commands. The mechanical controller can be used as an interface between a mechanical device, e.g., a musical instrument, and the mobile device

Erweiterungen zur Methode der Kernel Dependency Estimation und deren Anwendungen in der Robotik

Diese Dissertation behandelt algorithmische Erweiterungen der Kernel Depency Estimation (KDE) und deren Anwendungen auf das Problem des Imitationslernens. KDE ist eine neues Lernverfahren, mit dem sich Abbildungen zwischen Mengen lernen lassen. Hierbei werden, im Gegensatz zu existierenden Lernverfahren, keinerlei Annahmen über den Typ der Mengenelemente gemacht. Die Unabhängigkeit vom jeweiligen Datentyp wird durch den Einsatz von Kernfuntionen erreicht, mit denen sich aufgabenspezifische Informationen Datentypen kapseln lassen. Das originale Lernproblem kann dann in einem Merkmalsraum als hochdimensionales multivariates lineares Regressionsproblem gelöst werden.This dissertation contributes several algorithmic extensions to the method of Kernel Dependency Estimation and explores its applications in robotic imitation learning. Kernel Dependency Estimation is a novel learning algorithm that can learn between sets. In contrast to existing algorithms there are no assumptions on the nature of the input and output set elements due to the use of kernel functions. The original learning problem is then solved by KDE via a high dimensional multivariate regression problem

Building sparse large margin classifiers

This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The added constraint explicitly controls the sparseness of the classifier and an approach is provided to solve the formulated problem. When considering the dual of this problem, it can be seen that building an SLMC is equivalent to constructing an SVM with a modified kernel function. Further analysis of this kernel function indicates that the proposed approach essentially finds a discriminating subspace that can be spanned by a small number of vectors, and in this subspace different classes of data are linearly well separated. Experimental results over several classification benchmarks show that in most cases the proposed approach outperforms the state-of-art sparse learning algorithms. 1

Influence of noise on the inference of dynamic Bayesian networks from short time series

Abstract — In this paper we investigate the influence of external noise on the inference of network structures. The purpose of our simulations is to gain insights in the experimental design of microarray experiments to infer, e.g., transcription regulatory networks from microarray experiments. Here external noise means, that the dynamics of the system under investigation, e.g., temporal changes of mRNA concentration, is affected by measurement errors. Additionally to external noise another problem occurs in the context of microarray experiments. Practically, it is not possible to monitor the mRNA concentration over an arbitrary long time period as demanded by the statistical methods used to learn the underlying network structure. For this reason, we use only short time series to make our simulations more biologically plausible

Cloning, expression and characterization of endo-β-1,4-mannanase from aspergillus fumigatus in aspergillus sojae and pichia pastoris

To be utilized in biomass conversion, including ethanol production and galactosylated oligosaccharide synthesis, namely prebiotics, the gene of extracellular endo-β-1,4-mannanase (EC 32.1.78) of Aspergillus fumigatus IMI 385708 (formerly known as Thermomyces lanuginosus IMI 158749) was expressed first in Aspergillus sojae and then in Pichia pastoris under the control of the glyceraldehyde triphosphate dehydrogenase (gpdA) and the alcohol oxidase (AOX1) promoters, respectively. The highest production of mannanase (352 U mL -1)in A. sojae was observed after 6 days of cultivation. In P. pastoris, the highest mannanase production was observed 10 h after induction with methanol (61 U mL-1). The fold increase in mannanase production was estimated as ∼12-fold and ∼2-fold in A. sojae and P. pastoris, respectively, when compared with A. fumigatus. Both recombinant enzymes showed molecular mass of about 60 kDa and similar specific activities (∼350 U mg-1 protein). Temperature optima were at 60°C and 45°C, and maximum activity was at pH 4.5 and 5.2 for A. sojae and P. pastoris, respectively. The enzyme from P. pastoris was more stable retaining most of the activity up to 50°C, whereas the enzyme from A. sojae rapidly lost activity above 40°C

The role of T2-weighted images in assessing the grade of extraprostatic extension of the prostate carcinoma

Purpose Extraprostatic extension (EPE) is an unfavorable prognostic factor and the grade of EPE is also shown to be correlated with the prognosis of prostate cancer. The current study assessed the value of prostate magnetic resonance imaging (MRI) in measuring the radial distance (RD) of EPE and the role of T2 WI signs in predicting the grade of EPE. Materials and methods A total of 110 patients who underwent prostate MRI before radical prostatectomy are enrolled in this retrospective study. Eighty-four patients have organ confined disease and the remaining twenty-six patients have EPE all verified by histopathology. Prostate MRI examinations were conducted with 3T MRI scanner and phased array coil with the following sequences: T2 WI, T1 WI, DCE, DWI with ADC mapping, and high b-value at b = 1500 s/mm(2). The likelihood of EPE with 5-point Likert scale was assigned, several MRI features were extracted for each dominant tumor identified by using T2 WI. Tumors with Likert scales 4-5 were evaluated further to obtain MRI-based RD. The relationship between pathological and MRI-determined RD was tested. Univariate and multivariate logistic regression models were developed to detect the grade of pathological EPE. The inputs were among the 2 clinical parameters and 4 MRI features. Results There is a moderate correlation between pathological RD and MRI-determined RD (rho = 0.45, P < 0.01). In univariate and multivariate models, MRI features and clinical parameters possess varying significance levels (univariate models; P = 0.048-0.788, multivariate models; P = 0.173-0.769). Multivariate models perform better than the univariate models by offering fair to good performances (AUC = 0.69-0.85). The multivariate model that employs the MRI features offers better performance than the model employs clinical parameters (AUC = 0.81 versus 0.69). Conclusion Co-existence of T2 WI signs provide higher diagnostic value even than clinical parameters in predicting the grade of EPE. Combined use of clinical parameters and MRI features deliver slightly superior performance than MRI features alone

Pneumococcal Meningitis in 18 Year-Old Young Pregnant Woman

Community acquired bacterial meningitis is associated with high morbidity and mortality, and the most common bacterial pathogen is Streptococcus pneumoniae. Few case reports and two small case series of pneumococcal meningitis during pregnancy have been reported in the literature. This is the first case report of pneumococcal meningitis in an 18 year-old pregnant woman from Turkey. She was admitted to our emergency department at 33rd week of gestation with the complaints of fever, nausea, vomiting and sudden onset of confusion. The diagnosis of acute bacterial meningitis was made according to the findings of lumbar puncture. Empirical treatment with ceftriaxone (2 x 2 g/day) and vancomycin (4 x 500 mg/day) were started immediately. Caesarean section was performed on the sixth day of hospitalization (34th week of gestation) because of the premature rupture of membrane. Both mother and the infant survived without any sequela. Successful results for both mother and infant can be achieved with early diagnosis and appropriate treatment in cases of pneumococcal meningitis during pregnancy

Antimicrobial Susceptibility and Frequency of Extended Spectrum Beta-Lactamase (ESBL) of Escherichia coli Strains Isolated from Community Acquired and Nosocomial Infections

Introduction: Escherichia coli is one of the most important causes of nosocomial and community acquired infections. Beta-lactam antibiotics constitute one of the major therapeutic options to treat infections caused by these microorganism. Resistance to beta-lactams antibiotics is mainly caused by extended-spectrum beta-lactamases (ESBLs). The aim of this study was to determine the production rates of ESBL of E. coli isolates causing nosocomial and community acquired infections as well as to determine their antimicrobial susceptibility patterns. Materials and Methods: Between June 2006-December 2010, 555 E. coli strains isolated from clinical specimens (256 wound, 213 urine, 42 blood, 28 respiratory truct, 16 others) of inpatients, and 3052 E. coli strains isolated from urines of outpatients admitted to Cumhuriyet University Research and Training Hospital, were included to the study. Identification of the isolates and antibiotic susceptibility testings were performed by an automatic system (BD, Phoenix, USA). The production of ESBL was done by the broth microdilution method according to Clinical and Laboratory Standards Institute guidelines. Results: The rate of ESBL producers in the nosocomial isolates was approximately three times higher than the community acquired isolates (47.7% vs. 15.8%). Ciprofloxacin and piperacillin-tazobactam resistance rate were significantly different between the nosocomial and community acquired ESBL producing E. coli isolates. Ciprofloxacin resistance was higher in community acquired strains (84.3% vs. 77.7%, p= 0.026) and piperacillin-tazobactam resistance was higher in nosocomial strains (44.5% vs. 37.1%, p= 0.046). Nitrofurantoin and fosfomycine resistance in the community acquired ESBL positive E. coli strains was quite low (4.0% vs. 0.5%), and the nosocomial isolates were not studied. All nosocomial and community acquired E. coli isolates were sensitive to carbapenems. Conclusion: These results show that ESBL production is high in nosocomial E. coli isolates, and some differences can be seen in antibiotics susceptibility of nosocomial and community acquired ESBL producing E. coli strains