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Phototherapy is the main treatment of neonatal hyperbilirubinemia to prevent encephalopathy. It is generally believed to be safe; however, some studies have shown it might be associated with cancer development. In this systematic review and meta-analysis, we aimed to assess the effect of neonatal phototherapy on future cancer risk. A systematic search in 13 databases was conducted in December 2018 and updated in August 2022 to identify studies that report cancer development after exposure to phototherapy. Throughout the study period, regular manual searches were also conducted to include new studies. A meta-analysis using R programming language was done in which the odds ratios (ORs) with 95% confidence intervals (CIs) were estimated and pooled using the reported adjusted and unadjusted data. Fifteen studies were included. A statistically significant association was detected between neonatal phototherapy and any type of cancer (OR 1.24; 95% CI 1.1, 1.4), any hematopoietic cancer (OR 1.49; 95% CI 1.17, 1.91), any leukemia (OR 1.35; 95% CI 1.08, 1.67), and myeloid leukemia (OR 2.86; 95% CI 1.4, 5.84). The other investigated cancers (lymphoid leukemia, Hodgkin's lymphoma, kidney cancer, nervous system cancer, and skin cancer) were not associated with phototherapy. Conclusions: Phototherapy may carry a possible risk of future cancers. Future research is needed to quantify the magnitude of the cancer risk. These future studies should consider predictors of preterm birth or exclude premature babies from their analysis. What is Known • There were various reports about the possible association between phototherapy in neonates and the increased risk of cancer in the future. What is New • A statistically significant association between phototherapy and various hematopoietic cancers (especially myeloid leukemia) was recorded. • The effect of the duration of phototherapy on the increased risk of hematopoietic cancers is yet unclear.

— A quadcopter is a form of unmanned aerial vehicle with several rotors. Surveillance, military operations, fire detection, agriculture, spyware, and a variety of other applications are all new to it. Because of their dependability, cost effectiveness, and multi-functionality, they are frequently used in many locations. This article details the design process, including component selection and manufacturing of X-shape quadcopter.

Micro-porous hydrophilic membranes were successfully fabricated using polystyrene waste by phase inversion casting. Four concentrations (20, 25, 30, and 35 wt%) of recycled high-impact polystyrene (HIPS-R) in N, N-dimethyl formamide (DMF) solution were employed to prepare the membranes. The effect of polystyrene concentration on the characteristics of the different membranes was thoroughly studied. Based on the Fourier transform infrared spectroscopy (FTIR) results, the chemical composition of HIPS-R was analogous to that of pure high-impact polystyrene HIPS raw material of the previous studies. Also, field-emission scanning electron microscopy (FESEM) was employed to study the morphology and porosity of the prepared membranes. The membranes cross-section showed a sponge structure with longitudinal macro voids. The solid walls around these voids have a sponge-like structure, especially for high concentration polystyrene membranes. Furthermore, the number of pores into the membrane surface decreased with the increase of polystyrene concentration. The membranes surface pores size was ranged from 150 nm to 550 nm with the different used concentrations. Water contact angle (CA) of the prepared membrane's surface were measured. All the measured CA of the prepared membranes, except the 35 wt% showed CA of 91o, showed a hydrophilic behavior. Thus, the results suggest effective membranes could be obtained using recycled polystyrene. And then, solve the polymer waste accumulation problem in parallel with help in drinking water crisis solution.

In our previous work, microfiltration membranes were successfully manufactured by non-solvent induced phase separation (NIPS) method using two concentrations (30 and 35 wt%) of recycled high impact polystyrene (HIPS-R). N, Ndimethyl formamide (DMF) was used as solvent and water as a coagulation bath. These membranes were characterized in terms of chemical composition, surface hydrophilicity, surface crosssection morphology, porosity, and pores size distribution. Accordingly, the membrane's surfaces showed a semihydrophilic behavior with contact angles of 81o and 91o for 30 wt% and 35 wt% membranes respectively. In the current study, The prepared membranes were examined for the removal of Humic acid (HA) and Rhodamine B (RhB) dye in a microfiltration process. Filtration experiment showed that pure water flux of 30 wt% membrane was higher than of 35 wt% membrane, also 30 wt% membrane has a higher humic acid and Dye removal efficiency than of 35 wt% membrane. Thus, the results suggest active membranes could be obtained using recycled high-impact polystyrene. And then, solve the polymer waste accumulation problem in parallel with help in drinking water crisis solution.

Teams of Artificially Intelligent agents can more effectively achieve their goals by learning to cooperate. Methods for learning cooperation can be centralised or decentralised but the trade-offs of applying these methods are not well understood. This thesis conducts an in-depth analysis of different learning methods. It introduces a new multi-agent task that facilitates the study of complex cooperation and implements it as part of a reusable experimental platform. It uses the platform to conduct a systematic comparison of centralised and decentralised learning, providing new insights into their trade-offs, and presents a theoretical model that generalises the findings to new contexts.

Additive manufacturing (AM) is a process of joining materials to make parts from 3D model data by successive layer by layer material addition. AM has triggered a paradigm shift towards parts and assemblies design methodologies, materials development and utilization, and additional part functionalization. The workflow to produce an additively manufactured part consists of three steps: preprocessing, build cycle, and post-processing. Design for additive manufacturing (DfAM) or preprocessing is crucial in additive manufacturing and significantly impacts the process outcomes like part's strength, geometry, and manufacturing time which translates to cost. DfAM consists of different sub-steps: part design, process parameters optimization, and path planning. The promised advantages of AM will not get realized, and the results can be significantly costly unless the rules for DfAM are implemented. Additionally, new design strategies should be developed to overcome the inherent limitations of each AM process.Functional additively manufactured parts are evaluated based on three main criteria; mechanical performance, geometrical accuracy, Physical efficiency (thermal, fluid, and weight), and cost. Part design, process parameters, and path planning required to produce cost-effective and successful functional parts must be carefully designed and optimized to overcome the inherent tradeoffs of the selected process. The ultimate goal of DfAM is to produce parts with "as-built" geometrical measurements and mechanical performance that match the "as designed" CAD part design specifications. The challenges facing design for polymer additive manufacturing process outcomes are coupled, process parameters are interdependent, commercially promised resolution is different from manufacturing resolution, and lack of simulation, modelling and optimization tools.The thesis's primary research question is "Can the DfAM tools and optimized process parameters produce a feasible as-built part comparable to the as-designed CAD par specifications?". The research domain of this thesis includes two subdomains. The first subdomain is the process parameter optimization, and the second domain is part design optimization to improve mechanical properties, geometrical accuracy and minimize cost and weight. This thesis studies two polymer AM processes to apply and investigate the different challenges, namely Projection stereolithography (PSLA) and fused deposition modelling (FDM).For the first subdomain, the thesis investigates the effect of the PSLA process parameters on the mechanical properties, geometric accuracy, and surface roughness of the manufactured part in light of a novel introduced curing model to estimate the accumulated exposure energy per each layer. Developed analytical and empirical models are integrated to predict the final part’s geometrical distortion, material properties, and surface roughness. Newly introduced terminologies like irradiance affected zone and critical energy for mechanical properties are used to develop curing schemes to improve geometrical accuracy while maintaining the mechanical properties to ensure the part integrity during manufacturing. Then mechanical properties can be enhanced during post-curing. A novel high-resolution fluorescence induced irradiance measurement methodology is introduced to measure and capture the irradiance profile projected from one micromirror and quantify the effect of building plat irradiance map non-uniformity on geometrical accuracy. The effect of part location on the geometrical accuracy and the effect of grayscale pixels on minimizing that effect is experimentally explored. A novel 3D geometry prediction algorithm is developed to simulate the geometrical distortion in different features and surface roughness. A three-stage integrated optimization algorithm with a newly introduced cross-layers optimization method and irradiance compensation algorithm is presented.For the second subdomain, the thesis investigates the effect of part 2D design parameters on the mechanical properties and cost of manufactured parts by the FDM process. A cost-based methodology is used while considering the part design parameters to manufacture parts optimized for strength and cost. A novel algorithm called the reverse CAD algorithm is introduced, which converts the machine input G-code file back to a CAD model. The Reverse CAD provides an accurate assessment of the geometric and mechanical behaviour of the printed part as it also incorporates the effect of slicing parameters. Finally, a novel framework to grade both the size and relative density of standard and custom unit cells simultaneously within a lattice structure as a function of the cell spatial coordinates. It was found that dual grading enhances compressive strength, modulus of elasticity, absorbed energy, and fracture behaviour of the lattice structure at the same part weight.