Spray deposited copper zinc tin sulphide (Cu<inf>2</inf>ZnSnS<inf>4</inf>) film as a counter electrode in dye sensitized solar cells

Stoichiometric thin films of Cu2ZnSnS4 (CZTS) were deposited by the spray technique on a FTO coated glass substrate, with post-annealing in a H2S environment to improve the film properties. CZTS films were used as a counter electrode (CE) in Dye-Sensitized Solar Cells (DSCs) with N719 dye and an iodine electrolyte. The DSC of 0.25 cm2 area using a CE of CZTS film annealed in a H2S environment under AM 1.5G illumination (100 mW cm-2) exhibited a short circuit current density (JSC) = 18.63 mA cm-2, an open circuit voltage (VOC) = 0.65 V and a fill factor (FF) = 0.53, resulting in an overall power conversion efficiency (PCE) = 6.4%. While the DSC using as deposited CZTS film as a CE showed the PCE = 3.7% with JSC = 13.38 mA cm-2, VOC = 0.57 V and FF = 0.48. Thus, the spray deposited CZTS films can play an important role as a CE in the large area DSC fabrication. © the Partner Organisations 2014

Accelerated Predictive Healthcare Analytics with Pumas, a High Performance Pharmaceutical Modeling and Simulation Platform

Pharmacometric modeling establishes causal quantitative relationship between administered dose, tissue exposures, desired and undesired effects and patient’s risk factors. These models are employed to de-risk drug development and guide precision medicine decisions. Recent technological advances rendered collecting real-time and detailed data easy. However, the pharmacometric tools have not been designed to handle heterogeneous, big data and complex models. The estimation methods are outdated to solve modern healthcare challenges. We set out to design a platform that facilitates domain specific modeling and its integration with modern analytics to foster innovation and readiness to data deluge in healthcare. New specialized estimation methodologies have been developed that allow dramatic performance advances in areas that have not seen major improvements in decades. New ODE solver algorithms, such as coefficient-optimized higher order integrators and new automatic stiffness detecting algorithms which are robust to frequent discontinuities, give rise to up to 4x performance improvements across a wide range of stiff and non-stiff systems seen in pharmacometric applications. These methods combine with JIT compiler techniques and further specialize the solution process on the individual systems, allowing statically-sized optimizations and discrete sensitivity analysis via forward-mode automatic differentiation, to further enhance the accuracy and performance of the solving and parameter estimation process. We demonstrate that when all of these techniques are combined with a validated clinical trial dosing mechanism and non-compartmental analysis (NCA) suite, real applications like NLME parameter estimation see run times halved while retaining the same accuracy. Meanwhile in areas with less prior optimization of software, like optimal experimental design, we see orders of magnitude performance enhancements. Together we show a fast and modern domain specific modeling framework which lays a platform for innovation via upcoming integrations with modern analytics

Accelerated Predictive Healthcare Analytics with Pumas, a High Performance Pharmaceutical Modeling and Simulation Platform

Pharmacometric modeling establishes causal quantitative relationship between administered dose, tissue exposures, desired and undesired effects and patient’s risk factors. These models are employed to de-risk drug development and guide precision medicine decisions. Recent technological advances rendered collecting real-time and detailed data easy. However, the pharmacometric tools have not been designed to handle heterogeneous, big data and complex models. The estimation methods are outdated to solve modern healthcare challenges. We set out to design a platform that facilitates domain specific modeling and its integration with modern analytics to foster innovation and readiness to data deluge in healthcare. New specialized estimation methodologies have been developed that allow dramatic performance advances in areas that have not seen major improvements in decades. New ODE solver algorithms, such as coefficient-optimized higher order integrators and new automatic stiffness detecting algorithms which are robust to frequent discontinuities, give rise to up to 4x performance improvements across a wide range of stiff and non-stiff systems seen in pharmacometric applications. These methods combine with JIT compiler techniques and further specialize the solution process on the individual systems, allowing statically-sized optimizations and discrete sensitivity analysis via forward-mode automatic differentiation, to further enhance the accuracy and performance of the solving and parameter estimation process. We demonstrate that when all of these techniques are combined with a validated clinical trial dosing mechanism and non-compartmental analysis (NCA) suite, real applications like NLME parameter estimation see run times halved while retaining the same accuracy. Meanwhile in areas with less prior optimization of software, like optimal experimental design, we see orders of magnitude performance enhancements. Together we show a fast and modern domain specific modeling framework which lays a platform for innovation via upcoming integrations with modern analytics

Spray deposited copper zinc tin sulphide (Cu2ZnSnS4) film as a counter electrode in dye sensitized solar cells.

PublishedThis is the author accepted manuscript. The final version is available from the Royal Society of Chemistry via the DOI in this record.Stoichiometric thin films of Cu2ZnSnS4 (CZTS) were deposited by the spray technique on a FTO coated glass substrate, with post-annealing in a H2S environment to improve the film properties. CZTS films were used as a counter electrode (CE) in Dye-Sensitized Solar Cells (DSCs) with N719 dye and an iodine electrolyte. The DSC of 0.25 cm(2) area using a CE of CZTS film annealed in a H2S environment under AM 1.5G illumination (100 mW cm(-2)) exhibited a short circuit current density (JSC) = 18.63 mA cm(-2), an open circuit voltage (VOC) = 0.65 V and a fill factor (FF) = 0.53, resulting in an overall power conversion efficiency (PCE) = 6.4%. While the DSC using as deposited CZTS film as a CE showed the PCE = 3.7% with JSC = 13.38 mA cm(-2), VOC = 0.57 V and FF = 0.48. Thus, the spray deposited CZTS films can play an important role as a CE in the large area DSC fabrication.The work presented in this paper was done under the Department of Science and Technology (DST)–Research Council UK (RCUK) project “Advancing the efficiency and production potential of excitonic solar cells”. Sanjay Kumar Swami acknowledges Ministry of National Renewable Energy (MNRE), New Delhi, India for providing the financial assistantship. Mr. Firoz Alam is also thanks for helping in initial impedance measurements

Echoes of time. The mobility of Brazilian researchers and students in Portugal

A investigação que apresentamos, de caráter exploratório, recaiu sobre histórias biográficas de brasileiros que escolhem Portugal para prosseguir formação e ou investigação. Procura-se encontrar na sua experiência elos de ligação explicativos sobre as motivações e os processos que os trazem para Portugal, assim como as expetativas e os projetos que comportam para os seus futuros e que incluem, ou não, este país. Temos em conta, especialmente, a forma como essa narrativa transporta sentidos identitários decorrentes das formas de relacionamento intercultural e político entre Portugal e Brasil e formas de cooperação implícitas, assim como mapas representacionais acerca dos lugares de eleição para desenvolvimento de carreiras científicas e académicas. A nossa pesquisa incide sobre as informações recolhidas através de um inquérito por questionário e entrevistas realizadas junto de estudantes e bolseiros brasileiros em Portugal.We present an exploratory study that investigated biographical stories of Brazilians who choose to continue their education or develop research in Portugal. We sought to find in their experiences explanatory links connecting the motivations and processes that bring them to Portugal, as well as the expectations and projects that they hold for the future, which may include, or not, this country. We take into account, particularly, the way this narrative carries senses of identity arising from the forms of intercultural and political relationship between Portugal and Brazil, as well as implicit forms of cooperation and representations about the places chosen for the development of scientific and academic careers. Our research draws on information collected through a survey based on questionnaires and interviews with Brazilian students and scholarship holders in Portugal.(undefined

Vegetarian diets

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Evaluating the Role of Middle Ear Risk Indices in Assessing Postoperative Outcome following Tympanoplasty Procedure

Introduction Tympanoplasty is the treatment of choice for patients suffering with Chronic Otitis Media (COM). Outcome of tympanoplasty depends on various factors like size and location of tympanic membrane perforation, ear ossicles, degree of otorrhea, cholesteatoma, smoking history, granulation tissue etc. Prediction of outcome of tympanoplasty procedure prior to surgery with respect to graft uptake and hearing improvement can serve as a crucial factor in decision making in resource limited nations. Hence, a study was conducted to evaluate the role of Middle Ear Risk Indices (MERI) in predicting the outcome among patients undergoing tympanoplasty procedure. Materials and Methods A prospective study at a tertiary care centre was conducted for a duration of 2 years among 60 patients with COM who underwent tympanoplasty. Results The mean age of patients was 25.32 ± 8.43 years with a male to female ratio of 3:2. Majority (78.46%) of the patients had Mild MERI score; 18.46% patients had moderate MERI score and 3.08% patients had severe MERI risk score. The difference in mean Air –Bone (AB) gap in the mild and moderate MERI groups’ pre and post operatively was found to be statistically highly significant (p<0.001). Conclusion Lower MERI scores prior to surgery showed significantly better outcomes with respect to graft uptake, degree of AB gap closure and hearing improvement

Development and Validation of a Stability-Indicating RP-HPLC Method for the Simultaneous Estimation of Guaifenesin and Dextromethorphan Impurities in Pharmaceutical Formulations

A sensitive, stability-indicating gradient RP-HPLC method has been developed for the simultaneous estimation of impurities of Guaifenesin and Dextromethorphan in pharmaceutical formulations. Efficient chromatographic separation was achieved on a Sunfire C18, 250 × 4.6 mm, 5 µm column with mobile phase containing a gradient mixture of solvents A and B. The flow rate of the mobile phase was 0.8 mL min−1 with column temperature of 50°C and detection wavelength at 224 nm. Regression analysis showed an r value (correlation coefficient) greater than 0.999 for Guaifenesin, Dextromethorphan, and their impurities. Guaifenesin and Dextromethorphan formulation sample was subjected to the stress conditions of oxidative, acid, base, hydrolytic, thermal, and photolytic degradation. Guaifenesin was found stable and Dextromethorphan was found to degrade significantly in peroxide stress condition. The degradation products were well resolved from Guaifenesin, Dextromethorphan, and their impurities. The peak purity test results confirmed that the Guaifenesin and Dextromethorphan peak was homogenous and pure in all stress samples and the mass balance was found to be more than 98%, thus proving the stability-indicating power of the method. The developed method was validated according to ICH guidelines with respect to specificity, linearity, limits of detection and quantification, accuracy, precision, and robustness