Age and growth of four-spotted megrim (Lepidorhombus boscii Risso, 1810) from Saros Bay (Northern Aegean Sea, Turkey)

In this study, the growth parameters of the four-spotted megrim, (Lepidorhombus boscii Risso, 1810), were studied in Saros Bay, which had been closed to bottom trawl fishery since 2000. The sex ratio of females to males was 1:0.42. Length-weight relationships were W=0.0032L3.31 and W=0.0069L3.04 for females and males, respectively. Growth parameters of the populations were L∞=49.8 cm, k=0.09 year-1, t0=-2.15 year for females; L∞=39.1 cm, k=0.11 year-1, t0=-2.59 year for males. The growth performance index (Φ’) was found to be 2.35 and 2.23 for females and males, respectively

Enhancing gas sepration across a membrane with pulsating flow

Paper presented to the 10th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Florida, 14-16 July 2014.Gas-gas separation is a critical process in natural gas purification. Removing acidic gasses from natural gas is particularly important to protect the pipeline from corrosion. Using a membrane to purify natural gas is receiving a lot of attention recently. Membrane performance can be enhanced by either improving the permeability or the selectivity of the membrane or by enhancing the momentum mixing in the bulk flow. Our work will focus on improving membrane performance by enhancing momentum mixing in the bulk flow for gas-gas separation to purify natural gas. Pulsating flow in a channel with turbulators will be considered. Computational fluid dynamics simulation will be conducted for turbulent flow of multicomponent fluid including mass transfer of each species. RANS -Reynolds-Averaged Navier-Stokes equation along with mass transport equation will be employed to simulate 2-D transient turbulent flows of bulk fluid. The membrane will be modeled as a functional surface where the flux of each component will be determined based on the local partial pressure of each species, composition, and permeability and selectivity of the membrane. The performance of the system will be measured by maximum mass separation with minimal frictional losses.cf201

Elastic instability in stratified core annular flow

We study experimentally the interfacial instability between a layer of dilute polymer solution and water flowing in a thin capillary. The use of microfluidic devices allows us to observe and quantify in great detail the features of the flow. At low velocities, the flow takes the form of a straight jet, while at high velocities, steady or advected wavy jets are produced. We demonstrate that the transition between these flow regimes is purely elastic -- it is caused by viscoelasticity of the polymer solution only. The linear stability analysis of the flow in the short-wave approximation captures quantitatively the flow diagram. Surprisingly, unstable flows are observed for strong velocities, whereas convected flows are observed for low velocities. We demonstrate that this instability can be used to measure rheological properties of dilute polymer solutions that are difficult to assess otherwise.Comment: 4 pages, 4 figure

Interaction between ABA and cytokinins in salinized tomato plants

Abscisic acid (ABA) and cytokinins (CKs) are phytohormones that mediate plant responses to abiotic stress and are mainly considered to be produced in roots. These two plant hormones have long been considered antagonists, but the role of this antagonism in mediating abiotic stress resistance remains unknown. In this study we have used reciprocal grafting of transgenic lines with altered hormone synthesis (ABA or CK synthesis) with the aim of assessing the importance of ABA and CK interaction in mediating plant salinity responses in tomato. Preliminary results have shown a negative effect in ABA and CK on tomato plant biomass under salinity. Results have also indicated that jasmonic acid (JA) might be involved in the negative impact on tomato growth caused by ABA and CK interaction under salt conditions.The authors thank Andrew J. Thompson, from Cranfield Univertity (UK), and Ann C. Smigocki from Molecular Plant Pathology Laboratory (EEUU) the NCED and IPT seeds sets respectively. This work was supported by CICYT AGL2011‐27996 and ROOTOPOWER (REF: 289365. FP7‐KBBE‐2011‐5 European Union)

MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study.

Background: Diffuse intrinsic pontine gliomas (DIPGs) are lethal pediatric brain tumors. Presently, MRI is the mainstay of disease diagnosis and surveillance. We identify clinically significant computational features from MRI and create a prognostic machine learning model. Methods: We isolated tumor volumes of T1-post-contrast (T1) and T2-weighted (T2) MRIs from 177 treatment-naïve DIPG patients from an international cohort for model training and testing. The Quantitative Image Feature Pipeline and PyRadiomics was used for feature extraction. Ten-fold cross-validation of least absolute shrinkage and selection operator Cox regression selected optimal features to predict overall survival in the training dataset and tested in the independent testing dataset. We analyzed model performance using clinical variables (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variables. Results: All selected features were intensity and texture-based on the wavelet-filtered images (3 T1 gray-level co-occurrence matrix (GLCM) texture features, T2 GLCM texture feature, and T2 first-order mean). This multivariable Cox model demonstrated a concordance of 0.68 (95% CI: 0.61-0.74) in the training dataset, significantly outperforming the clinical-only model (C = 0.57 [95% CI: 0.49-0.64]). Adding clinical features to radiomics slightly improved performance (C = 0.70 [95% CI: 0.64-0.77]). The combined radiomics and clinical model was validated in the independent testing dataset (C = 0.59 [95% CI: 0.51-0.67], Noether's test P = .02). Conclusions: In this international study, we demonstrate the use of radiomic signatures to create a machine learning model for DIPG prognostication. Standardized, quantitative approaches that objectively measure DIPG changes, including computational MRI evaluation, could offer new approaches to assessing tumor phenotype and serve a future role for optimizing clinical trial eligibility and tumor surveillance

Radiomic signatures of posterior fossa ependymoma: Molecular subgroups and risk profiles

BACKGROUND: The risk profile for posterior fossa ependymoma (EP) depends on surgical and molecular status [Group A (PFA) versus Group B (PFB)]. While subtotal tumor resection is known to confer worse prognosis, MRI-based EP risk-profiling is unexplored. We aimed to apply machine learning strategies to link MRI-based biomarkers of high-risk EP and also to distinguish PFA from PFB. METHODS: We extracted 1800 quantitative features from presurgical T2-weighted (T2-MRI) and gadolinium-enhanced T1-weighted (T1-MRI) imaging of 157 EP patients. We implemented nested cross-validation to identify features for risk score calculations and apply a Cox model for survival analysis. We conducted additional feature selection for PFA versus PFB and examined performance across three candidate classifiers. RESULTS: For all EP patients with GTR, we identified four T2-MRI-based features and stratified patients into high- and low-risk groups, with 5-year overall survival rates of 62% and 100%, respectively (p < 0.0001). Among presumed PFA patients with GTR, four T1-MRI and five T2-MRI features predicted divergence of high- and low-risk groups, with 5-year overall survival rates of 62.7% and 96.7%, respectively (p = 0.002). T1-MRI-based features showed the best performance distinguishing PFA from PFB with an AUC of 0.86. CONCLUSIONS: We present machine learning strategies to identify MRI phenotypes that distinguish PFA from PFB, as well as high- and low-risk PFA. We also describe quantitative image predictors of aggressive EP tumors that might assist risk-profiling after surgery. Future studies could examine translating radiomics as an adjunct to EP risk assessment when considering therapy strategies or trial candidacy

Firms cash management, adjustment cost and its impact on firms’ speed of adjustment-A cross country analysis

We investigate the firms’ specific attributes that determine the difference in speed of adjustment (SOA) towards the cash holdings target in the Scandinavian countries: Denmark, Norway and Sweden. We examine whether Scandinavian firms maintain an optimal level of cash holdings and determine if the active cash holdings management is associated with the firms’ higher SOA and lower adjustment costs. Our findings substantiate that a higher level of off-target cost induces professional managers to rebalance their cash level towards the optimal balance of cash holdings. Our results reveal that Scandinavian firms accelerate SOA towards cash targets primarily for the precautionary motive. Moreover, our results show that SOA is heterogeneous across Scandinavian firms based on adjustment cost and deviate cash holdings towards the target mainly with the support of internal financing. Furthermore, our empirical findings show that the SOA of Norwegian firms is significantly higher than the Danish and Swedish firms

Space technology capacity building in support of SDG 2030 through CubeSat SharjahSat-l

The SHARJAH-SAT-1 would be the first CubeSat mission to be developed by the Sharjah Academy for Astronomy, Space Sciences, and Technology (SAASST)students and researchers, with the aim of not only designing, fabricating, testing & launching the CubeSat itself, but also building the capacities and expertise for future SAASST CubeSat missions as well. For the project, SAASST is working in close collaboration with an experienced international partner, the Istanbul Technical University, Space Systems Design and Test Laboratory which has already developed and launched 5 CubeSats into low earth orbit. Overall, the project, puts the human capacity development in its center, in support of UN SDG 2030 for an equal world