Additive manufacturing (AM), also known as 3D printing, has emerged as a transformative technology across various manufacturing sectors. It enables the fabrication of complex geometries, high-volume customization, significant material savings through layer-by-layer manufacturing methods, and the potential for the use of Eco-friendly materials. This technology offers significant freedom in the design and fabrication of complex geometric parts, with the potential to reduce costs in both prototyping and final product manufacturing, as well as reduce waste through the recycling of materials lost during manufacturing processes. Although its adoption in the ceramics industry has lagged that of polymers and metals, its unique capabilities in fabricating complex geometries of high-performance ceramics are receiving significant attention. This review provides a comprehensive overview of the current landscape of AM technologies specifically designed for ceramic materials. It explores the underlying principles of various ceramic 3D printing processes, highlighting their advantages and disadvantages in producing high-density, defect-free components with customized properties. Furthermore, this paper examines the transformative impact of AM on ceramics in various structural and functional industrial applications, including aerospace, biomedicine, electronics, energy, and more. By bringing together the latest developments and addressing the inherent challenges associated with ceramic processing via additive manufacturing, this review highlights the tremendous potential of this technology to revolutionize conventional ceramic manufacturing and enable the production of advanced ceramic components with enhanced performance and functionality.

This study explores the feasibility of producing biodiesel from dehulled orange seed oil, a non-edible agro-industrial byproduct with significant potential as a renewable energy feedstock. The research aims to enhance biodiesel yield through the optimization of transesterification process parameters using Response Surface Methodology (RSM). Dehulled orange seeds were processed to extract oil, after which transesterification was carried out using methanol. Five key process factors—reaction temperature, reaction time, catalyst concentration, methanol-to-oil molar ratio, and agitation speed—were systematically varied based on a central composite design to assess their individual and interactive effects on biodiesel yield. Statistical analysis indicated that all variables influenced conversion efficiency, with methanol ratio and catalyst concentration exerting particularly strong effects. The quadratic model developed showed high predictive accuracy and statistical significance, confirming its suitability for optimization. The optimal reaction conditions were identified as a temperature of 75 °C, reaction time of 150 minutes, catalyst concentration of 5 wt%, methanol-to-oil molar ratio of 12:1, and agitation speed of 350 rpm. Under these conditions, the biodiesel yield reached 95.23%, demonstrating efficient conversion and validating the optimization strategy. The physico-chemical characteristics of the produced biodiesel further complied with standard fuel specifications, underscoring its suitability as a renewable fuel. Overall, the results affirm that dehulled orange seed oil is a viable and sustainable feedstock for biodiesel production. The optimized process not only achieves high yields but also adds value to agricultural waste streams, contributing to cleaner energy alternatives and supporting circular bioeconomy initiatives. This study highlights the importance of exploring non-edible oils for biodiesel production to reduce competition with food resources and promote environmental sustainability.

Gas turbines (GTs) operating in offshore environments are highly vulnerable to performance degradation from airborne contaminants such as salt aerosols, mist, hydrocarbons, and particulate matter. This study develops and validates a computational fluid dynamics (CFD) model to optimize a multistage inlet-air filtration system for offshore GT applications, complementing prior experimental investigations. A three-dimensional CAD model of a wind tunnel housing six ASHRAE filter classes (F7, H12, E11, E10, G5, F9) was created in ANSYS Design Modeler, and simulations were performed under steady-state and transient conditions using Navier–Stokes, turbulence, and particle transport models. Contaminant mass loadings from 20–100% were evaluated at inlet velocities of 5 m/s and 10 m/s to characterize airflow distribution, static and total pressures, and filtration efficiency. Results revealed peak inlet velocities up to nine times the free-stream value, with mass flow concentration opposite the vertical inflow reaching 8.4 kg/s. Static and total pressures decreased progressively downstream, with the highest pressure drops occurring at 80% contaminant loading, indicating increased flow resistance. Transient analyses showed filtration efficiency degradation over time due to fouling. Model predictions for total pressure drop and volumetric flow rate deviated by ≤10% from experimental data, confirming robustness and accuracy. This work offers validated CFD insights into the complex aero–particle dynamics in offshore GT inlet filtration, providing a predictive framework for optimizing filter design, selection, and maintenance to enhance long-term turbine reliability and efficiency.

In this article, I discuss the ways in which technology has been used to build, implement, and maintain an automated report for the purpose of reporting swap transactions that are covered by the European Market Infrastructure Regulation (EMIR) and Dodd-Frank Act (DFA) Rule 12b-2. The automated report will use advances in technology, including but not limited to Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP), to enhance the regulatory reporting process, exception management, and compliance with EMIR, DFA and across all regions of the globe. All automated reports will be designed so that companies can minimize their need to perform manual processing and maximize the quality, accuracy, and transparency of their reports by converting them to a single format and standardizing the way they collect and submit data to regulators. By utilizing the advanced analytics capabilities in combination with a real-time monitoring, companies will benefit from more timely swap reporting and will ultimately enhance the efficiency of markets for all types of securities. The automated reporting of swaps improves the environment for regulatory reporting in regard to the marketplace, provides a new baseline for the financial services industry's compliance with regulation, eliminates or reduces the possibility of violating regulatory requirements within the financial services sector, decreases the cost of regulatory penalties associated with non-compliance, and improves the reputation of the organization overall.

1099 Provider Tax Application, providing healthcare organizations with an automated 1099 Provider Tax Reporting solution for the full end-to-end process of provider income reporting by enabling automatic electronic reporting to IRS via an approved format, enables healthcare organizations to automate their income reporting processes from the initial provider billing through to IRS electronic filing. 1099 Provider Tax Application utilizes a unique combination of statistical data analysis techniques to identify provider income that is based on the claims payment data and the electronic systems that provide the claims data. Data regarding provider income from all these electronic sources is effectively collated and stored in an S3 data engine environment for future retrieval and aggregation. In addition, because of AWS's Serverless architecture, the 1099 Provider Tax Application can create, and securely deliver to providers, IRS-compliant 1099s on an annual basis. The cloud-native architecture of the platform enhances both the speed and accuracy of tax document filing and ensures compliance with HIPAA and IRS regulations, which greatly reduces the likelihood of human error in the reconciliation and filing of tax documents. Moreover, the flexible nature of the platform would allow for the addition of other types of tax forms and multi-state/country reporting, along with the capability for integration with organizational data lakes and self-service portals for providers. As such, the cloud-native 1099 Provider Tax Application represents an opportunity to develop a reusable template for reporting systems in the regulated financial and healthcare sectors.