Estimating Watermarking Capacity in Gray Scale Images Based on Image Complexity

Capacity is one of the most important parameters in image watermarking. Different works have been done on this subject with different assumptions on image and communication channel. However, there is not a global agreement to estimate watermarking capacity. In this paper, we suggest a method to find the capacity of images based on their complexities. We propose a new method to estimate image complexity based on the concept of Region Of Interest (ROI). Our experiments on 2000 images showed that the proposed measure has the best adoption with watermarking capacity in comparison with other complexity measures. In addition, we propose a new method to calculate capacity using proposed image complexity measure. Our proposed capacity estimation method shows better robustness and image quality in comparison with recent works in this field

An integrating study of genetic diversity and ecological niche modelling in Salvia aristata (Lamiaceae)

Applying both molecular data and ecological niche modelling is essential to infer the speciation mechanism and species delimitation in organisms. Salvia aristata Auch. ex Benth is an endemic species restricted to western, northwestern and centre of Iran and eastern parts of Turkey with variations in morphological character along its distributions. In this study, we applied SRAP marker and ecological niche modelling using climatic and geographic data to detect and examine the genetic structure and niche differentiation in S. aristata accessions. SRAP marker’s results showed 242 bands highly polymorph. Genetic distance analysis provided two main clusters. The STRUCTURE analysis provided two distinct ecotypes (K = 2). Our ecological niche model produced good results with high performance based on area under curve (AUC > 0.9) for both ecotypes. Altitude was the most important variable contributing in niche model of both ecotypes. The niche space of both ecotypes is different based on niche identity test and background test as well. Based on genetic and ecological evidence, it is concluded that S. aristata gene pool underwent a parapatric speciation process caused by niche divergence and reproductive isolations as a consequence of divergent selection on floral traits

Total Flavonoids Contents and Anti Bacterial Activity of the Extracts of two Labiateae Species: Nepeta menthoides and Thymus trautvetteri

Total flavonoids contents and antibacterial activity of the extracts from the aerial parts of two Labiateae species, Nepeta menthoides Boiss. & Buhse and Thymus trautvetteri Klokov & Desj.-Shost. were determined. Quantitative determination of flavonoid contents was calculated in terms of quercetin equivalent in various extracts (50% methanol, chloroform and distilled water) by AlCl3 colorimetric method. It was found that total flavonoids contents of N. menthoides extracts in different solvents were (2.308%, 0.884% and 0.710%) mg/g and (2.076%, 1.468% and 1.412%) mg/g for T. trautvetteri  respectively.Antibacterial activity of the extracts was also determined against 6 gr (+/-) bacteria by disc diffusion method. The results showed that 50% methanol extracts of two species displayed better inhibitor activity against the tested bacteria. The bacteria Stapylococcus epidermidis, Staphylococcus saprophyticus and Staphylococcus aureus  were sensitive against 50% methanol extract of N. menthoides even more than the standard antibiotics (10μg). Therefore a good correlation between total flavonoids contents and antibacterial activity of the studied extracts is demonstrated

Self-Supervised Learning with Limited Labeled Data for Prostate Cancer Detection in High Frequency Ultrasound

Deep learning-based analysis of high-frequency, high-resolution micro-ultrasound data shows great promise for prostate cancer detection. Previous approaches to analysis of ultrasound data largely follow a supervised learning paradigm. Ground truth labels for ultrasound images used for training deep networks often include coarse annotations generated from the histopathological analysis of tissue samples obtained via biopsy. This creates inherent limitations on the availability and quality of labeled data, posing major challenges to the success of supervised learning methods. On the other hand, unlabeled prostate ultrasound data are more abundant. In this work, we successfully apply self-supervised representation learning to micro-ultrasound data. Using ultrasound data from 1028 biopsy cores of 391 subjects obtained in two clinical centres, we demonstrate that feature representations learnt with this method can be used to classify cancer from non-cancer tissue, obtaining an AUROC score of 91% on an independent test set. To the best of our knowledge, this is the first successful end-to-end self-supervised learning approach for prostate cancer detection using ultrasound data. Our method outperforms baseline supervised learning approaches, generalizes well between different data centers, and scale well in performance as more unlabeled data are added, making it a promising approach for future research using large volumes of unlabeled data

A revision of chestnut-leaved oak (Quercus castaneifolia C. A. Mey.; Fagaceae) in Hyrcanian Forests of Iran

Chestnut-leaved oak (Quercus castaneifolia C. A. Mey) is one of the most important native oaks of Iran distributed in the Hyrcanian Forests. The pure and mixed stands of it cover about 6.5% of these forests. The species represents morphological variations which have resulted in the description of several infraspecific taxa by different authors. Eight taxa were recognized as subspecies and varieties of Q. castaneifolia. In this survey, a set of quantitative and qualitative micro-morphological characteristics such as type of trichome, number and length of trichome rays, type of epicuticular waxes, type and shape of stomata, shape and sculptural features of pollen exine were studied using light microscopy and scanning electron microscopy. These characters were analyzed by the discriminant analysis method and combined with the macromorphological characters to designate the variation within the species and to evaluate the existing infraspecific taxa. Based on our results, the studied taxa are defined into four infraspecific taxa as follows: Q. castaneifolia subsp. castaneifolia var. castaneifolia, Q. castaneifolia subsp. castaneifolia var. minuta, Q. castaneifolia subsp. aitchisoniana, Q. castaneifolia subsp. undulate. The studied characteristics showed to be diagnostic for identification of the infraspecific taxa

Towards controlling the crystallisation behaviour of fenofibrate melt: triggers of crystallisation and polymorphic transformation

Fenofibrate (FEN) is a dyslipidemia treatment agent which is poorly soluble in water. FEN has tendency to form polymorphs and its crystallisation behaviour is difficult to predict. The nucleation process can be initiated by mechanical disruption such as ball milling or surface scratching which may result in different crystallisation behaviour to that observed in the unperturbed system. This study has obtained insights into the controllability of FEN crystallisation by means of regulating the exposed surface and growth temperatures during its crystallisation. The availability of an open top surface (OTS) during the crystallisation of the FEN melt resulted in a mixture containing FEN form I and IIa (I ≫ IIa) at room temperature, and in the range 40 to 70 °C. Covering the surface led to significant increases in the yield of form IIa at room temperature and at 40 and 50 °C. These temperatures also yielded the highest amount of form IIa in the OTS samples whilst crystallisation at 70 °C led to only FEN form I crystals regardless of the availability of the free surface. The metastable FEN form IIa transforms to the stable form I under the influence of a mechanical stress. Additionally, the introduction of OTS before the completion of crystallisation of form IIa led to a ‘switch’ of from IIa growth to form I. This study demonstrates that the polymorph selection of FEN can be obtained by the manipulation of the crystallisation conditions

Dizaj i statistička optimizacija liposfera s glipizidom pomoću metodologije odgovora površine

A 32 factorial design was employed to produce glipizide lipospheres by the emulsification phase separation technique using paraffin wax and stearic acid as retardants. The effect of critical formulation variables, namely levels of paraffin wax (X1) and proportion of stearic acid in the wax (X2) on geometric mean diameter (dg), percent encapsulation efficiency (% EE), release at the end of 12 h (rel12) and time taken for 50% of drug release (t50), were evaluated using the F-test. Mathematical models containing only the significant terms were generated for each response parameter using the multiple linear regression analysis (MLRA) and analysis of variance (ANOVA). Both formulation variables studied exerted a significant influence (p < 0.05) on the response parameters. Numerical optimization using the desirability approach was employed to develop an optimized formulation by setting constraints on the dependent and independent variables. The experimental values of dg, % EE, rel12 and t50 values for the optimized formulation were found to be 57.54 ± 1.38 µm, 86.28 ± 1.32 %, 77.23 ± 2.78 % and 5.60 ± 0.32 h, respectively, which were in close agreement with those predicted by the mathematical models. The drug release from lipospheres followed first-order kinetics and was characterized by the Higuchi diffusion model. The optimized liposphere formulation developed was found to produce sustained anti-diabetic activity following oral administration in rats.32 faktorijalni dizajn primijenjen je za pripravu liposfera s glipizidom metodom separacije pomoću emulzija koristeći parafinski vosak i starinsku kiselinu kao tvari za usporavanje. Pomoću F-testa praćen je učinak kritičnih varijabli tijekom formuliranja, tj. količina parafinskog voska (X1) i udio stearinske kiseline (X2) na srednji promjer liposfera (dg), postotak inkapsulirane ljekovite tvari (% EE), oslobađanje ljekovite tvari nakon 12 h (rel12) te vrijeme potrebno za oslobađanje 50% ljekovite tvari (t50). Pomoću multiple linearne regresijske analize (MLRA) i analize varijabli (ANOVA) za svaki su parametar načinjeni matematički modeli koji sadrže samo značajne varijable. Proučavanje varijabli na oba načina ukazalo je na njihov značajan utjecaj (p < 0,05) na parametre liposfera. Postavljanjem ograničenja na zavisne i nezavisne varijable provedena je numerička optimizacija na principu poželjnosti. Eksperimentalne vrijednosti dg, % EE, rel12 i t50 optimiziranih formulacija bile su 57,54 ± 1,38 µm, 86,28 ± 1,32%, 77,23 ± 2,78% i 5,60 ± 0,32 h. Dobivene eksperimentalne vrijednosti iznosile su vrlo slične vrijednostima predviđenim matematičkim modelima. Oslobađanje glipizida iz liposfera slijedio je kinetiku prvog reda i okarakterizirano je Higuchijevim difuzijskim modelom. Optimizirane liposfere su nakon peroralne primjene na štakorima pokazale produljeni antidijabetički učinak

Shift of the western boundary of the distribution area of Micromeria cristata (Hampe) Griseb. and Steptorhamphus tuberosus (Jacq.) Grossh.

During field investigations of Mt Rumija, two new taxa for the flora of Montenegro were recorded: Micromeria cristata (Hampe) Griseb. and Steptorhamphus tuberosus (Jacq.) Grossh. From the phytogeographic point of view these data indicate a change in the distribution area of both taxa, which have shifted to the west. Ashort overview of the taxonomic treatment of both genera is given