AI-driven optimization of ethanol-powered internal combustion engines in alignment with multiple SDGs: A sustainable energy transition

With the escalating requirement for global sustainable energy solutions and the complexities linked with the complete transition to new technologies, internal combustion engines (ICEs) powered with biofuels like ethanol are gaining significance over time. However, problems linked to the performance and emissions of such ICEs necessitate accurate prediction and optimization. The study employed the integration of artificial neural networks (ANN) and multi-level historical design of response surface methodology (RSM) to address these challenges in alignment with the Sustainable Development Goals (SDGs). A single-cylinder spark ignition (SI) engine powered with ethanol-gasoline blends at different loads and speeds was used to gather data. Among six initially trained ANN models, the most efficient model with a regression coefficient (R2) of 0.9952 (training), 0.98579 (validation), 0.98847 (testing), and 0.99307 (overall) was employed to predict outputs such as brake power, brake specific fuel consumption (BSFC), brake thermal energy (BTE), concentration of carbon dioxide (CO2), carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen NOx. Predicted outputs were optimized by incorporating RSM. On implementing optimized conditions, it was observed that BP and BTE increased by 19.9%, and 29.8%, respectively. Additionally, CO, and HC emissions experienced substantial reductions of 28.1%, and 40.6%, respectively. This research can help engine producers and researchers make refined decisions and achieve improved performance and emissions. The study directly supports SDG 7, SDG 9, SDG 12, SDG 13, and SGD 17, which call for achieving affordable, clean energy, sustainable industrialization, responsible consumption, and production, taking action on climate change, and partnership to advance the SDGs as a whole respectively

Tailoring surface properties, biocompatibility and corrosion behavior of stainless steel by laser induced periodic surface treatment towards developing biomimetic stents

Laser-Induced Periodic Surface Structures (LIPSS) holds great potential for regenerative biomedicine. Creating highly precise LIPSS enables to generate biomimetic implant surfaces with improved properties. The present study focuses on the fabrication and investigation of laser-treated stainless steel samples with applied linear LIPSS patterns with grooves made by means of a picosecond laser system using wavelengths of 1064 nm and 532 nm. To investigate properties of the laser-treated surfaces and to understand the basics of cell-surface interactions between the LIPSS and human Umbilical Cord Mesenchymal Stem Cells (UCMSC), flat stainless steel samples with various applied nanopatterns were used. Such LIPSSs demonstrated higher surface roughness, good biocompatibility, lower wettability and higher corrosion resistance compared to the untreated (polished) spec-imens. The surface roughness of laser-treated samples was in microscale that enabled adhesion and migration of endothelial cells, thus increasing the likelihood for endothelialisation. This thereby could reduce the chances for the development of Late Stent Thrombosis (LST) and In-Stent Restenosis (ISR). Furthermore, laser textured surfaces demonstrated an environment supportive for cell attachment, proliferation and alignment with the nanogroves. Therefore, application of the biomimetic nanopatterns could help to overcome frequent post-surgery complications after the stent implantation

Symmetric mhd channel flow of nonlocal fractional model of btf containing hybrid nanoparticles

A nonlocal fractional model of Brinkman type fluid (BTF) containing a hybrid nanostructure was examined. The magnetohydrodynamic (MHD) flow of the hybrid nanofluid was studied using the fractional calculus approach. Hybridized silver (Ag) and Titanium dioxide (TiO2) nanoparticles were dissolved in base fluid water (H2O) to form a hybrid nanofluid. The MHD free convection flow of the nanofluid (Ag-TiO2-H2O) was considered in a microchannel (flow with a bounded domain). The BTF model was generalized using a nonlocal Caputo-Fabrizio fractional operator (CFFO) without a singular kernel of order α with effective thermophysical properties. The governing equations of the model were subjected to physical initial and boundary conditions. The exact solutions for the nonlocal fractional model without a singular kernel were developed via the fractional Laplace transform technique. The fractional solutions were reduced to local solutions by limiting α→1 . To understand the rheological behavior of the fluid, the obtained solutions were numerically computed and plotted on various graphs. Finally, the influence of pertinent parameters was physically studied. It was found that the solutions were general, reliable, realistic and fixable. For the fractional parameter, the velocity and temperature profiles showed a decreasing trend for a constant time. By setting the values of the fractional parameter, excellent agreement between the theoretical and experimental results could be attained

Caputo fractional MHD casson fluid flow over an oscillating plate with thermal radiation

The effect of the thermal radiation on the MHD Casson fluid along with the fractional derivative in an oscillating vertical plate is elucidated. More exactly, the Caputo fractional model is utilized in developing the governing equations. Besides, the influence of the buoyancy force due to the temperature gradient has also been considered. The derived fractional partial differential equations are converted into ordinary differential equations by using the Laplace transform technique and then are solved for analytical solutions via the characteristic method. The inversion of the Laplace transformation is obtained through the numerical approach of Zakian. The effects of various physical parameters on the velocity and temperature profiles, Nusselt number, and skin friction have been analyzed and depicted in graphs and tables. The distribution of the velocity and temperature either in viscous or Casson fluid do enhance by the fractional parameter

Computational Validation of Injection Molding Tooling by Additive Layer Manufacture to Produce EPDM Exterior Automotive Seals

During the design and development of ethylene propylene diene monomer (EPDM) exterior automotive seals, prototype components can only manufactured through production tooling platforms by either injection molding or extrusion. Consequently, tooling is expensive and has long lead times. This paper investigates whether additive layer manufacture is a viable method for producing tooling used in injection molding of exterior automotive seals in EPDM. Specifically, a novel rapid tooling is a method that combines additive layer manufacture (ALM) with epoxy reinforcement. Computational validation is performed whereby the mechanical properties of the tool are evaluated. The research has concluded that the novel tooling configuration would be suitable for prototyping purposes which would drastically reduce both costly and environmentally detrimental pre-manufacturing processes. This work has laid the foundations to implement rapid tooling technology to the injection molding of prototype EPDM parts

Diagnostic of Cystic Fibrosis in Lung Computer Tomographic Images using Image Annotation and Improved PSPNet Modelling

The research deals with the development of an algorithm for detecting pathological formation in cystic fibrosis using the PSPNet model with focal loss. The model allows data sets to be entered in accordance to their similarities based on their pathological diagnostic signs. The simple and effective algorithm structure groups annotated images, processes them in a multiscale CNN, and localizes areas of cystic fibrosis in the lungs with high accuracy

Cell-selective labeling using amino acid precursors for proteomic studies of multicellular environments.

We report a technique to selectively and continuously label the proteomes of individual cell types in coculture, named cell type-specific labeling using amino acid precursors (CTAP). Through transgenic expression of exogenous amino acid biosynthesis enzymes, vertebrate cells overcome their dependence on supplemented essential amino acids and can be selectively labeled through metabolic incorporation of amino acids produced from heavy isotope-labeled precursors. When testing CTAP in several human and mouse cell lines, we could differentially label the proteomes of distinct cell populations in coculture and determine the relative expression of proteins by quantitative mass spectrometry. In addition, using CTAP we identified the cell of origin of extracellular proteins secreted from cells in coculture. We believe that this method, which allows linking of proteins to their cell source, will be useful in studies of cell-cell communication and potentially for discovery of biomarkers

Experimental Aspects of Synthesis

We discuss the problem of experimentally evaluating linear-time temporal logic (LTL) synthesis tools for reactive systems. We first survey previous such work for the currently publicly available synthesis tools, and then draw conclusions by deriving useful schemes for future such evaluations. In particular, we explain why previous tools have incompatible scopes and semantics and provide a framework that reduces the impact of this problem for future experimental comparisons of such tools. Furthermore, we discuss which difficulties the complex workflows that begin to appear in modern synthesis tools induce on experimental evaluations and give answers to the question how convincing such evaluations can still be performed in such a setting.Comment: In Proceedings iWIGP 2011, arXiv:1102.374

Delay in diagnosis of tuberculosis in Rawalpindi, Pakistan

<p>Abstract</p> <p>Background</p> <p>Delay in diagnosis and treatment of tuberculosis (TB) may enhance the chances of morbidity and mortality and play a key role in continuous transmission of the bacilli. The objective of this study was to describe health care seeking behavior of suspected TB patients and initial diagnostic work up prior to consultation and diagnosis at National TB Center (NTC).</p> <p>Findings</p> <p>Interviews of 252 sputum smear positive patients were taken from NTC, Rawalpindi. The duration between on-set of symptoms and start of treatment was considered as the total delay and correlated with general characteristics of TB patients. The proportion of males and females were 49.6% and 50.4% with median age of 25 and 24 years respectively. A median delay of 56 days (8 weeks) was observed which was significantly associated with age, cough and fever. More than 50% of the current patients had a history of contact with previously diagnosed TB patients. The majority of patients (63%) visited health care providers within three weeks of appearance of symptoms but only thirty five percent were investigated for TB diagnosis.</p> <p>Conclusion</p> <p>Cough and fever are being ignored as likely symptoms of TB by patients as well as health care providers resulting in delay. Engaging private practitioners through public private mix (PPM) approach for expansion of TB diagnosis and increasing public awareness could be more beneficial to reduce delay.</p