In this manuscript, the authors investigate the growth of indium zinc oxide, indium zinc oxide (InZnO, IZO) as a channel material for thin-film transistors. IZO is grown at atmospheric pressure and a high deposition rate using spatial atomic layer deposition (S-ALD). By varying the ratio of diethylzinc and trimethylindium vapor, the In/(In þ Zn) ratio of the film can be accurately tuned in the entire range from zinc oxide to indium oxide. Thin film transistors with an In to Zn ratio of 2:1 show high field-effect mobility—exceeding 30 cm2/V s—and excellent stability. The authors demonstrate large scale integration in the form of 19-stage ring oscillators operating at 110 kHz. These electrical characteristics, in combination with the intrinsic advantages of atomic layer deposition, demonstrate the great potential of S-ALD for future display production.

The usage of Artificial Neural Networks (ANNs) for genome-enabled classifications and establishing genome-phenotype correlations have been investigated more extensively over the past few years. The reason for this is that ANNs are good approximates of complex functions, so classification can be performed without the need for explicitly defined input-output model. This engineering tool can be applied for optimization of existing methods for disease/syndrome classification. Cytogenetic and molecular analyses are the most frequent tests used in prenatal diagnostic for the early detection of Turner, Klinefelter, Patau, Edwards and Down syndrome. These procedures can be lengthy, repetitive; and often employ invasive techniques so a robust automated method for classifying and reporting prenatal diagnostics would greatly help the clinicians with their routine work. The database consisted of data collected from 2500 pregnant woman that came to the Institute of Gynecology, Infertility and Perinatology “Mehmedbasic” for routine antenatal care between January 2000 and December 2016. During first trimester all women were subject to screening test where values of maternal serum pregnancy-associated plasma protein A (PAPP-A) and free beta human chorionic gonadotropin (β-hCG) were measured. Also, fetal nuchal translucency thickness and the presence or absence of the nasal bone was observed using ultrasound. The architectures of linear feedforward and feedback neural networks were investigated for various training data distributions and number of neurons in hidden layer. Feedback neural network architecture out performed feedforward neural network architecture in predictive ability for all five aneuploidy prenatal syndrome classes. Feedforward neural network with 15 neurons in hidden layer achieved classification sensitivity of 92.00%. Classification sensitivity of feedback (Elman’s) neural network was 99.00%. Average accuracy of feedforward neural network was 89.6% and for feedback was 98.8%. The results presented in this paper prove that an expert diagnostic system based on neural networks can be efficiently used for classification of five aneuploidy syndromes, covered with this study, based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics. Developed Expert System proved to be simple, robust, and powerful in properly classifying prenatal aneuploidy syndromes.

The purpose of this work was to examine the influence of non-coherent polarized light upon the growth of Escherichia coli. Experiments were designed to test the main hypothesis that this kind of polychromatic light can produce decimal reductions in numbers of E. coli bacteria. Two strains of E. coli - isolated from ground pork and commercial culture E. coli ATCC 25922, were both exposed to light for 20, 30, 40 and 60 minutes. The source of non-coherent polarized light was a Bioptron-1 lamp (Zepter, Swiss) with the following technical char - acteristics: wavelength 400-2000 nm, polarization > 95%, and constant radiation dose 2.4 J/cm 2 per minute. The result for both strains showed a slight increase in bacterial count in response to an irradiation time of 20 min and decreases in bacterial counts for irradiation times of 30, 40 and 60 min without characteristics of a decimal reduction. Bacterial counts after treatments displayed a linear relationship with the total count of bacteria before treatments as well as the percentage surviving bacteria and irradiation time. Data analysis (ANOVA two factors with replication) showed that the survival of bacteria was influenced significantly by duration time ( P < 0.01), bacterial culture (p<0.05), and interaction between duration time and bacterial culture ( P < 0.01). Neither E. coli ATCC 25922 nor E. coli isolated from ground pork showed a decimal reduction after irradiation with non-coherent polychromatic polarized light.

The post-eradication incidence of bovine tuberculosis in seven Central European Countries (Bosnia and Herzegovina, Croatia, Czech Republic, Hungary, Poland, Slovakia and Slovenia) was studied between 1990 and 1999. The majority of cattle to the age of 24 months were screened by tuberculin skin test on annual basis. Tuberculous lesions observed during meat inspection at abattoirs were further laboratory examined by direct microscopy, cultivation and histol- ogy for the presence of mycobacteria. Data describing the incidence of the disease in animals for the whole period were obtained from all countries except Bosnia and Herzegovina, where data were obtained after the year 1995. Between the years 1990 and 1999, bovine tuberculosis was diagnosed in a total of 1 084 cattle herds. Nine hundred and seventy five (89.9%) outbreaks of the disease were reported in small herds (≤10 cows) and 109 (10.1%) outbreaks in large cattle herds (>10 cows). The last outbreak of bovine tuberculosis in cattle was diagnosed in Slovakia, Slovenia, the Czech Republic, Croatia and Bosnia and Herzegovina in 1993, 1993, 1995, 1999 and 1999, respectively. Bovine tuberculosis was diagnosed under proper quarantine in Slovenia in 37 fattening bulls imported from two European countries before animals were introduced to the targeting farms.