The increasing global demand for sustainable energy alternatives has positioned biodiesel as a promising renewable fuel source. This study presents a comprehensive modelling and optimization approach for biodiesel production from jatropha oil using advanced process simulation and statistical optimization techniques. The research employed Aspen Plus® V11 for process modelling, incorporating transesterification, methanol recovery, water washing, and purification stages. Response Surface Methodology (RSM) with a Central Composite Design was utilized to optimize three critical process parameters: transesterification temperature (40-80°C), water washing flow rate (40-60 kg/hr), and reflux ratio (0.7-1.3). The Peng–Robinson–Boston–Mathias thermodynamic model was selected to accurately represent the multi-component hydrocarbon system behaviour. The optimized process achieved a biodiesel yield of 83.09% under optimal conditions of 63°C transesterification temperature, 44 kg/hr water flow rate, and 1.1 reflux ratio. The simulation demonstrated that temperature significantly influences yield until an optimal point of 68°C is reached, beyond which methanol evaporation reduces conversion efficiency. Economic analysis revealed a minimum fuel selling price (MFSP) of $0.62/kg. Life cycle assessment using OpenLCA 2.0 and the ReCiPe 2016 methodology indicated positive environmental benefits. This integrated approach successfully demonstrates the technical and economic viability of jatropha-based biodiesel production. The optimized process parameters provide practical guidelines for industrial-scale implementation, while the comprehensive economic evaluation confirms biodiesel's competitiveness with fossil fuels. This study contributes to sustainable energy development by offering a systematic methodology for biodiesel process optimization that balances yield maximization with economic feasibility.

This study aims to investigate the aerodynamic properties of fabrics used in winter sportswear, with a specific focus on the effect of seam placement on air resistance. To achieve this, wind tunnel experiments were conducted using two different models: a cylindrical model and an airfoil-shaped model. The experiments were designed to simulate real-world conditions encountered in high-speed winter sports and to analyze how changes in seam position affect aerodynamic performance.

For the cylindrical model, the seam was tested at various angular positions. The results showed that placing the seam at a 30-degree angle from the front-facing direction yielded the lowest drag coefficient (Cd = 0.63) at a wind speed of 100 km/h. This represents a 25% reduction in air resistance compared to a seam positioned at the very front (0 degrees, Cd = 0.84). This suggests that seam placement away from the stagnation point can significantly reduce drag in cylindrical shapes.

In contrast, the airfoil-shaped model exhibited the lowest drag when the seam was located directly at 0 degrees, indicating that aligning the seam with the airflow direction is most effective for this geometry.

These findings demonstrate that seam location plays a crucial role in the aerodynamic efficiency of winter sports apparel. Depending on the shape of the body or equipment, optimal seam positioning can vary. Understanding these dynamics allows for better design strategies aimed at minimizing drag and improving athlete performance in high-speed winter sports environments.

Manila, the capital of the Philippines, is among the most densely populated cities globally and is highly susceptible to flooding due to its low-lying terrain, rapid urban development, inadequate drainage infrastructure, and geographic proximity to the Pasig River and Manila Bay. The city regularly experiences pluvial, fluvial, and tidal flooding, exacerbated by climate variability and sea-level rise. This study presents a spatiotemporal analysis of urban flood vulnerability in Manila under three distinct rainfall scenarios: light, moderate, and heavy intensity. Flood hazard maps were generated for each scenario using hydrodynamic simulations and integrated with socio-demographic data at the Barangay level to evaluate population exposure and sensitivity. Spatial correlation and spatial autocorrelation techniques, including Moran’s I and Local Indicators of Spatial Association (LISA), were applied to identify statistically significant clusters of flood vulnerability. Vulnerability was assessed as a function of flood intensity, population density, poverty incidence, age distribution, and access to basic services and infrastructure. In addition to mapping high-risk areas, the study identified flood-resilient “safe zones”, geographic locations that consistently remained outside flood extents across all modeled scenarios. These areas were evaluated for their suitability as evacuation centers and emergency response sites based on proximity to vulnerable populations and existing infrastructure. Findings highlight a clear spatial overlap between flood-prone zones and socioeconomically disadvantaged communities, indicating the need for targeted disaster risk reduction and urban planning strategies. The results provide evidence-based recommendations for policy development aimed at enhancing flood resilience and adaptive capacity in Manila’s urban landscape.

Understanding the dynamics of gas bubbles in viscoelastic media is crucial for applications involving stable cavitation under ultrasound, such as drug delivery, materials processing, and biomedical imaging. The Rayleigh–Plesset equation formulated in terms of bubble volume variation, incorporating viscoelastic effects via the linear Kelvin–Voigt model, is extended here to a fourth-order approximation. This extension should allow a more accurate description of nonlinear bubble dynamics at finite acoustic amplitudes.

The resulting equation is solved numerically under various acoustic conditions, with particular emphasis on driving frequencies near the bubble’s resonance. The fourth-order model represents a more accurate and detailed version of the equation describing bubble oscillations. This increased precision allows for a better understanding of how the medium’s shear elasticity and viscosity influence bubble behavior, especially under high amplitude oscillations or near-resonance driving frequencies. Comparisons with lower-order models will be carried out to show whether this fourth-order approximation significantly enhances the description of nonlinear oscillations. In particular, it may reveal dynamic features that traditional second-order formulations fail to capture.

This work provides a robust framework for analyzing how viscoelastic properties affect bubble dynamics, contributing to improved prediction and control of stable cavitation phenomena in complex media. These findings highlight the importance of using the fourth-order model to fully account for viscoelastic behavior when modeling bubble volume variations under ultrasound excitation.

The Navier–Stokes equations, which describe the motion of viscous fluids, form a cornerstone of classical physics and engineering. A central unresolved issue, designated as a Millennium Prize Problem, concerns the global existence and smoothness of their solutions in three dimensions—a quest for global predictability in fluid dynamics. While a complete mathematical proof of regularity remains elusive, the physical reality of non-singular fluid flow is empirically undisputed. This paper addresses this dichotomy by proposing a definitive physical solution, asserting that such singularities are inherently precluded by the very nature of physical fluids. We develop a rigorous analytical framework founded upon eight fundamental principles of physics, including Continuum Emergence, the Second Law of Thermodynamics, and the existence of a Natural Cutoff scale. This framework synthesizes concepts from statistical mechanics, quantum mechanics, and causality to construct a logically closed argument. We demonstrate that these principles, when taken in concert, act as intrinsic regulators that inherently constrain the dynamics of a classical fluid to exclude the formation of finite-time singularities. The analysis shows that phenomena such as infinite velocity gradients or pressure spikes are not merely mathematically challenging but are, in fact, physically impossible within the domain of applicability of the Navier–Stokes equations. This paper concludes that the regularity of solutions is a necessary consequence of the fundamental laws governing physical systems, thereby resolving the problem from a physical, rather than a purely mathematical, standpoint, and identifying the remaining analytical hurdle for mathematics.

Developing an advanced simulation to control a swarm of 20 PocketQube nanosatellites using a Linear Quadratic Regulator (LQR) involves several crucial steps that go beyond the initial scheme. A comprehensive approach requires a deep understanding of orbital mechanics and in particular the challenges presented by the nanosatellite platform. The inherent limitations of nanosatellite power, propulsion, and communications systems require careful orbital selection and maneuver planning to achieve mission objectives efficiently and reliably. This includes optimizing launch windows, understanding atmospheric drag effects in low Earth orbits (LEO), and designing robust attitude control systems to maintain the desired pointing for scientific instruments or communications links. Our article focuses on simulating the attitude control of PocketQube nanosatellites in a swarm using the Matlab/Simulink environment. First, we provided a mathematical model for the relative coordinates of a nanosatellite swarm. Second, we developed a mathematical model of the Linear Quadratic Regulator implementation in the relative navigation. Third, we simulated the attitude control of 20 PocketQube nanosatellites using the Matlab/Simulink environment. Finally, we provided the swarm scenario and attitude control system data. Simulation of an attitude control system for 20 PocketQube nanosatellites using an LQR controller in swarm successfully demonstrated the stabilization capabilities essential for swarm operations in the space environment. A link to the video of the simulation is provided in the Results section.

1. Introduction

Passive optofluidic sorting offers a precise and label-free approach for directing and stabilizing nanoparticles of various sizes along controlled trajectories by leveraging the interplay between optical and hydrodynamic forces. In this work, we analyze a device designed to separate nanoparticles, aiming to reach the exosomal size range (typically 150-200 nm), a challenging task when using passive techniques.

2. Methods and results

The system consists of three silicon waveguides embedded in a CYTOP layer and arranged in a three-step directional coupler (power splitting ratio of 4:1) configuration, integrated with a microchannel through which water flows as the carrier fluid, transporting the suspended nanoparticles. Simulations were performed using the three-dimensional Finite Element Method approach, incorporating optical forces, creeping flow dynamics, and particle tracing analysis. Starting from the optical forces acting on nanoparticles of different sizes, we designed the microfluidic channel such that the drag forces counterbalance the optical ones, stabilizing particle positions. By integrating both effects and tracking the particle dynamics within the microchannel, we demonstrate controlled particle deflection and size-selective trajectory steering. Nanospheres with diameters of 500 nm, 600 nm, and 700 nm are effectively separated due to the action of transverse trapping force of 46.46 pN/W, 52,76 pN/W, and 58.26 pN/W, respectively, with input power of 20 mW.

3. Conclusions

This configuration optimizes the photonic and microfluidic integration to enhance particle discrimination resolution, showing great potential for biomedical use, especially in early cancer diagnostics, where sorting exosome-sized particles is crucial.

In the construction industry, waste cement or shelf-life-expired (SLE) cement shows potential sustainability challenges. In geotechnical applications, grout materials are crucial for filling voids, improving load-bearing capacity, and minimising the differential settlement of the ground. Within the scope of this work, an investigation is conducted into the potential use of SLE cement as a binder in cementitious grout for geotechnical applications that require moderate intensity. The mechanical properties were confirmed through the ASTM standard for flexural and compressive strength. Simultaneously, the fresh properties were evaluated using fresh density and fluidity tests, as per ASTM and European standards. Whereas M2-type grout achieved 4.43 MPa (max.) flexural and 23.54 MPa (max.) compressive strength, M1 grout indicated better results with 5.68 MPa (max.) and 33.51 MPa (max.) at 28 days. Fluidity remained within a considerable limit for the injectable grout. This grout can be used in geotechnical applications such as void filling, settlement control in compressible soils, permeation grouting (seepage cut-off), stabilising the subgrade of light pavements, shallow slope stabilisation, temporary groundwater sealing, and soft soil improvement, where volume stability or permeability reduction is more critical than strength. Through effective resource construction and valorisation, this study reduces cement waste and the consumption of manufactured raw materials, thereby supporting the SDGs on Sustainable Cities and Communities (SDG 11) and Responsible Consumption and Production (SDG 12).

Silicon photonic microring resonators offer an ultra‑compact, label‑free platform for translating minute refractive‑index perturbations into easily tracked resonance shifts. This invited lecture surveys the fundamental physics of all‑pass and add‑drop configurations, with emphasis on confinement, group index engineering, quality factor management, and the coupled trade‑offs that ultimately define sensitivity and detection limits. Within this framework I will contextualise my doctoral contributions, beginning with a systematic comparison of multiple waveguide geometries in SOI technology, including strip, slot, PANDA and S‑junction designs, working at 1550 nm. Finite‑element modelling and experimental validation identified the slot ring as the most effective refractometric transducer, owing to its enhanced evanescent‑field overlap and favourable balance between propagation loss and optical confinement.

Building on these insights, the research migrated to a silicon nitride platform at 1310 nm, leveraging reduced material absorption to achieve substantially higher quality factors and correspondingly lower intrinsic detection limits under microfluidic operation. Surface functionalization with oriented monoclonal antibodies then converted optimized slot cavities from generic refractometers into robust biosensors. Assays targeting spike and fusion proteins from clinically relevant respiratory viruses demonstrated selective, real‑time monitoring of binding kinetics, while preserving specificity in the presence of complex sample matrices.

Finally, the methodology was validated using unprocessed nasopharyngeal swab extracts, achieving diagnostic concordance with reference molecular techniques and highlighting the robustness of the photonic interface. The talk concludes by outlining routes toward large‑scale multiplexing, integrated fluidic handling and fibre‑to‑chip packaging, positioning microring resonators as a scalable foundation for near‑patient infection surveillance and broader lab‑on‑a‑chip applications.

Abstract:
Extreme rainfall events in coastal cities such as Alexandria, Egypt, are challenging to forecast due to the combined influences of local convection, sea surface conditions, and aerosol interactions. The convective storm of 31 May 2025 caused intense rainfall over Alexandria, which was poorly predicted by most operational weather models.

In this study, the WRF-Chem model was configured to investigate this event, focusing on the role of aerosols and dust in modifying cloud microphysics and precipitation. The model setup included the MOSAIC 4-bin aerosol scheme (chem_opt=300), dust emissions (dust_opt=1), and the Morrison two-moment microphysics scheme (mp_physics=10). A sea surface temperature (SST) update was applied to better represent the evolving surface conditions over the Mediterranean. Sensitivity experiments were performed to assess the effects of aerosol–cloud interactions and aerosol–radiation feedback on convective development.

The results indicate that WRF-Chem successfully reproduced the timing, location, and intensity of the observed rainfall, outperforming typical operational forecasts. Aerosols and desert dust increased cloud condensation nuclei (CCN), which enhanced cloud water content, delayed precipitation onset, and intensified convection. The SST update was also found to play a critical role in triggering and sustaining the convective cells over coastal regions.

This study demonstrates that coupling aerosol chemistry with advanced microphysics and SST updates can significantly improve the predictability of extreme weather events in complex coastal environments.