Smart Healthcare Using Data-Driven Prediction of Immunization Defaulters in Expanded Program on Immunization (EPI)

Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases, child mortality and morbidity. Expanded Program on Immunization (EPI) is a nation-wide program in Pakistan to implement immunization activities, however the coverage is quite low despite the accessibility of free vaccination. This study proposes a defaulter prediction model for accurate identification of defaulters. Our proposed framework classifies defaulters at five different stages: defaulter, partially high, partially medium, partially low, and unvaccinated to reinforce targeted interventions by accurately predicting children at high risk of defaulting from the immunization schedule. Different machine learning algorithms are applied on Pakistan Demographic and Health Survey (2017–18) dataset. Multilayer Perceptron yielded 98.5% accuracy for correctly identifying children who are likely to default from immunization series at different risk stages of being defaulter. In this paper, the proposed defaulters’ prediction framework is a step forward towards a data-driven approach and provides a set of machine learning techniques to take advantage of predictive analytics. Hence, predictive analytics can reinforce immunization programs by expediting targeted action to reduce dropouts. Specially, the accurate predictions support targeted messages sent to at-risk parents’ and caretakers’ consumer devices (e.g., smartphones) to maximize healthcare outcomes.     

Responses of bimetallic Ag/ZnO alloy nanoparticles and urea on morphological and physiological attributes of wheat

Wheat (Triticum aestivum L.) is the most important staple food crop globally. According to economic survey 2018‐19, agriculture sector of Pakistan grew by 0.85%, with wheat accounting for 8.9% of agriculture and 1.6% of GDP, and its production fell short of the target by 4.9%. Wheat requires beneficial ties to improve its efficiency with the help of modern technology. Nanotechnology modifies conventional agricultural practices as these are stimulating agents for plant growth. Green bimetallic Ag/ZnO alloy nanoparticles (NPs) synthesised from salts reduced by Moringa oleifera and characterised by UV‐visible spectroscopy, scanning electron microscopy, and energy‐dispersive X‐ray spectroscopy are studied herein. Different concentrations of urea and Ag/ZnO alloy NPs were applied exogenously to wheat plants (Pakistan‐13 and Galaxy13). A significant effect of 100 mg/L urea and 75 ppm Ag/ZnO alloy NPs was observed on the morphology of wheat, with a maximum increase of 58% plant length, 85% leaf area, 89% plant fresh weight and 76% plant dried weight. In physiological parameters, relative water content and membrane stability index have shown maximum increases of 39% and 77%, while chlorophyll a, b, and total chlorophyll content (TCC) showed maximum increases of 92%, 71%, and 84% respectively. Evidence of the morpho‐physiological responses of urea and green synthesised alloy NPs on wheat varieties are reported on.     

A comparative neutronic study of the standard HEU core and various potential LEU alternatives for a typical MNSR system

A comparative study has been performed for neutronic analysis of highly enriched in uranium (HEU) and potential low enriched in uranium (LEU) cores for the Pakistan Research Reactor-2 (PARR-2) taken as a typical miniature neutron source reactor (MNSR) system. The group constant generation has been carried out using transport theory code WIMS-D4 and a detailed five-group RZ-model has been used in the CITATION code for multigroup diffusion theory analysis. The neutronic analysis of the 90% HEU reference and potential LEU alternative: UO₂, U₃Si₂ and U9Mo, cores has been carried out yielding 11%, 20.7% and 14.25% enrichments with corresponding values of excess reactivity: 4.33, 4.30 and 4.07 mk. These results have been found in good agreement with recently reported Monte Carlo-based transport theory calculations. The diffusion theory-based calculated values of thermal flux profiles for axial as well as for radial directions have been found to agree well with the corresponding experimental measurements. The UO₂-based LEU core has been found having flux spectrum closest to the reference core while U9Mo core has significantly harder flux spectrum at irradiation site.     

Fabrication of cadmium titanate nanofibers via electrospinning technique

Here we present an electrospinning technique for the fabrication of cadmium titanate/polyvinyl-pyrrolidone composite nanofibers. The composite nanofibers are then annealed at 600 °C to obtain ilmenite rhombohedral phase cadmium titanate nanofibers. The structure, composition, thermal stability and optical properties of as synthesized and annealed cadmium titanate nanofibers are characterized by X-ray diffraction, energy dispersive X-ray spectroscopy, scanning electron microscopy, transmission electron microscopy, thermogravimetric analysis, Fourier transform infrared spectroscopy and ultraviolet–visible spectroscopy. The average diameter and length of the nanofibers are found to be ～150–200 nm and ～100 μm, respectively.     

Mechanisms Underlying the Anti-Aging and Anti-Tumor Effects of Lithocholic Bile Acid

Bile acids are cholesterol-derived bioactive lipids that play essential roles in the maintenance of a heathy lifespan. These amphipathic molecules with detergent-like properties display numerous beneficial effects on various longevity- and healthspan-promoting processes in evolutionarily distant organisms. Recent studies revealed that lithocholic bile acid not only causes a considerable lifespan extension in yeast, but also exhibits a substantial cytotoxic effect in cultured cancer cells derived from different tissues and organisms. The molecular and cellular mechanisms underlying the robust anti-aging and anti-tumor effects of lithocholic acid have emerged. This review summarizes the current knowledge of these mechanisms, outlines the most important unanswered questions and suggests directions for future research.     

Enhanced Magnetic Properties in Cu0.5Tl0.5Ba2Ca2Cu3O10−δ Superconductor Doped with Carbon Nanotubes

Fluctuation-induced conductivity (FIC) analysis in the critical fluctuation region (cr), three-dimensional (3D), two-dimensional (2D), and zero-dimensional (0D) regions is reported for undoped and carbon nanotubes (CNT)-doped Cu_0.5Tl_0.5Ba₂Ca₂Cu₃O_10?δ (CuTl-1223) superconductors. Samples were synthesized by well-known solid-state reaction method by adding CNT up to 7 wt %. The X-ray diffraction data confirms the single-phase orthorhombic structures following PMMM space group for all the samples. The scanning electron microscope (SEM) images reveal that the carbon nanotubes are present in the spaces between the grains and connect the grains electrically to help the intergranular current flow. From FIC analysis, it was found that the width of critical and 3D regimes are shrunken with the increased CNT doping in the final compound. Also, the coherence length (ξ_c(0)), the Fermi velocity (V _F), and the coupling constant (J) are suppressed with increased CNT doping except for the 0.25 wt % doped sample. The decrease in important superconductivity parameters most likely arises due to low CNT doping which indeed functions as columnar defects that are produced by heavy ion irradiation. In this analysis, we also found that the critical magnetic fields (B _c(0), B _c1(0)) and critical current density (J _c(0)) were found to increase with increased CNT concentration. These observations suggest that addition of CNT (efficient pinning centers) to CuTl-1223 compounds improve the electrical connection between the superconducting grains to result in the improvement of magnetic properties of the final compound.