Knowledge of primary paediatric care providers regarding attention deficit hyperactivity disorder and learning disorder: a study from Pakistan

Introduction: Attention deficit hyperactivity disorder (ADHD) and learning disorder (LD) remain prevalent globally and are also speculated to have a high occurrence in Pakistan. An early diagnosis and intervention in these disabilities is imperative for achieving good clinical and functional outcomes. This can be ensured by an effective screening at the level of primary paediatric care in the developing countries. We aimed to explore the ability of general practitioners (GPs) and paediatricians in Pakistan to screen for ADHD and LD based on their awareness regarding the risk factors and symptomatology of ADHD and LD. Methods: A total of 96 paediatricians and 98 GPs practising in Karachi, Pakistan were included in the study. Data was collected employing a self-administered questionnaire. Results: Only 13.7 percent of the GPs and 21.6 percent of the paediatricians were shown to have knowledge sufficient to effectively screen for / diagnose ADHD. Alarmingly, not a single GP was adequately familiar with the established risk factors and clinical symptoms of LD. The level of knowledge was not influenced by age, gender, and clinical practice attributes of the physicians. Doctors who regularly read medical journals and attend medical education seminars showed slightly better trends. Conclusion : We hypothesise that this demonstrated lack of knowledge at the level of primary care in Pakistan prevents an early screening of ADHD and LD. A multipronged strategy targeted at the provision of objective screening tools for primary paediatric care providers, regular continuing medical education seminars and an emphasis on paediatric mental health in undergraduate and postgraduate curricula may ensure an early detection of ADHD and LD in Pakistan

Exploring the Exhaust Emission and Efficiency of Algal Biodiesel Powered Compression Ignition Engine: Application of Box–Behnken and Desirability Based Multi-Objective Response Surface Methodology

Sustainable Development Goals were established by the United Nations General Assembly to ensure that everyone has access to clean, affordable, and sustainable energy. Third-generation biodiesel derived from algae sources can be a feasible option in tackling climate change caused by fossil fuels as it has no impact on the human food supply chain. In this paper, the combustion and emission characteristics of Azolla Pinnata oil biodiesel-diesel blends are investigated. The multi-objective response surface methodology (MORSM) with Box–Behnken design is employed to decrease the number of trials to conserve finite resources in terms of human labor, time, and cost. MORSM was used in this study to investigate the interaction, model prediction, and optimization of the operating parameters of algae biodiesel-powered diesel engines to obtain the best performance with the least emission. For engine output prediction, a prognostic model is developed. Engine operating parameters are optimized using the desirability technique, with the best efficiency and lowest emission as the criteria. The results show Theil’s uncertainty for the model’s predictive capability (Theil’s U2) to be between 0.0449 and 0.1804. The Nash–Sutcliffe efficiency is validated to be excellent between 0.965 and 0.9988, whilst the mean absolute percentage deviation is less than 4.4%. The optimized engine operating conditions achieved are 81.2% of engine load, 17.5 of compression ratio, and 10% of biodiesel blending ratio. The proposed MORSM-based technique’s dependability and robustness validate the experimental methods

Search Bias Quantification: Investigating Political Bias in Social Media and Web Search

Users frequently use search systems on the Web as well as online social media to learn about ongoing events and public opinion on personalities. Prior studies have shown that the top-ranked results returned by these search engines can shape user opinion about the topic (e.g., event or person) being searched. In case of polarizing topics like politics, where multiple competing perspectives exist, the political bias in the top search results can play a significant role in shaping public opinion towards (or away from) certain perspectives. Given the considerable impact that search bias can have on the user, we propose a generalizable search bias quantification framework that not only measures the political bias in ranked list output by the search system but also decouples the bias introduced by the different sources—input data and ranking system. We apply our framework to study the political bias in searches related to 2016 US Presidential primaries in Twitter social media search and find that both input data and ranking system matter in determining the final search output bias seen by the users. And finally, we use the framework to compare the relative bias for two popular search systems—Twitter social media search and Google web search—for queries related to politicians and political events. We end by discussing some potential solutions to signal the bias in the search results to make the users more aware of them.publishe

With No Deliberate Speed: The Segregation of Roma Children in Europe

In this study, by taking the advantage of both inorganic ZnO nanoparticles and the organic material chitosan as a composite seed layer, we have fabricated well-aligned ZnO nanorods on a gold-coated glass substrate using the hydrothermal growth method. The ZnO nanoparticles were characterized by the Raman spectroscopic techniques, which showed the nanocrystalline phase of the ZnO nanoparticles. Different composites of ZnO nanoparticles and chitosan were prepared and used as a seed layer for the fabrication of well-aligned ZnO nanorods. Field emission scanning electron microscopy, energy dispersive X-ray, high-resolution transmission electron microscopy, X-ray diffraction, and infrared reflection absorption spectroscopic techniques were utilized for the structural characterization of the ZnO nanoparticles/chitosan seed layer-coated ZnO nanorods on a gold-coated glass substrate. This study has shown that the ZnO nanorods are well-aligned, uniform, and dense, exhibit the wurtzite hexagonal structure, and are perpendicularly oriented to the substrate. Moreover, the ZnO nanorods are only composed of Zn and O atoms. An optical study was also carried out for the ZnO nanoparticles/chitosan seed layer-coated ZnO nanorods, and the obtained results have shown that the fabricated ZnO nanorods exhibit good crystal quality. This study has provided a cheap fabrication method for the controlled morphology and good alignment of ZnO nanorods, which is of high demand for enhancing the working performance of optoelectronic devices

Analysis of temperature variations in fixed-bed columns using non-isothermal and non-equilibrium transport model

A non-isothermal and non-equilibrium two-component lumped kinetic model of fixed-bed column liquid chromatography is formulated with the linearized isotherm and solved analytically to study the influence of temperature variations on the process. The model equations constitute a system of convection-diffusion PDE for mass and energy balances in the bulk phase coupled with differential equations for mass and energy balances in the stationary phase. The analytical solutions are derived for Dirichlet boundary conditions by implementing the Laplace transformation, Tschirnhaus-Vieta approach, the linear decomposition technique and an elementary solution technique of ODE. An efficient and accurate numerical Laplace inversion technique is applied to bring back the solution in the actual time domain. In order to validate the derived analytical solutions for concentration and temperature fronts, the high resolution upwind finite volume scheme is applied to approximate the model equations numerically. Various case studies are carried out assuming realistic model parameters. The results obtained will be beneficial for interpreting mass and energy profiles in non-equilibrium and non-isothermal liquid chromatographic columns and provide deeper insight into the sensitivity of the separation process without performing costly and time-consuming laboratory experiments

Mycotoxic effect of Medicinal Plants Against Helminthosporium sativum and Aspergillus niger

hirty-nine extracts from 10 medicinal plants were tested against Helminthosporium sativum and Aspergillus niger for their fungitoxicity in vitro. Methanol leaves extracts of Lawsonia inermis, Withania somnifera, Datura metel, Datura stramonium and stem bark extract of Bauhinia racemosa significantly inhibited mycelia growth of both target fungi. Some extracts exhibited greater fungitoxicity than that of synthetic fungicide Dithane M-45