In a significant leap forward for vehicle navigation, researchers have developed an advanced system that integrates Global Navigation Satellite Systems (GNSS), Inertial Measurement Units (IMU), and Light Detection and Ranging (LiDAR) Odometry (LO).

Uncle Ren’s life took an unexpected turn when a routine fecal DNA methylation test detected early-stage colorectal cancer, prompting urgent surgery. Thanks to the screening initiative by Xihu District’s Health Bureau and BGI Genomics, he avoided chemotherapy and now only requires regular follow-ups. Grateful for his narrow escape, Uncle Ren encourages others to get screened, knowing early detection saved his life.

A latest study introduces a surfactant-based method for the selective recovery of fine active materials from high-temperature water electrolyzers. By employing cetyltrimethylammonium bromide (CTAB) and sodium dodecyl sulfate (SDS), researchers modified the surface characteristics of materials such as NiO, YSZ, and ZrO₂, enabling the efficient separation of these components. The findings demonstrate that NiO can be selectively recovered in the organic phase, while the other particles remain in the aqueous phase. In contrast to traditional, energy-intensive metallurgical methods, this approach minimizes chemical consumption and promotes a more sustainable circular economy. The study also suggests potential optimizations, such as increasing the number of phase separation stages for enhanced recovery. Additionally, magnetic separation techniques are proposed for materials like perovskite LSM. This work was published in Industrial Chemistry & Materials on 9th July 2024.

The strict requirement for a coherent spectrum in coherent diffractive imaging (CDI) limits efficient photon use across the full spectrum. To date, broadband CDI (BCDI) has depended on precise spectroscopic measurements, as broad spectra are incompatible with conventional CDI systems. Scientists in China have introduced an advanced approach that extends CDI to ultra-broadband CDI (UDI) with unknown probe spectra, effectively overcoming key challenges faced by current state-of-the-art BCDI frameworks.

Maxwell’s equations in vacuum present self-duality symmetry, but in materials this symmetry is broken, leading to polarization-dependent phenomena. This work presents an approach to restore effective self-duality in dielectric metamaterials, while simultaneously extending the Brewster effect across all incident angles and polarizations. Consequently, self-dual and vacuum-like dielectric metamaterials have been realized, showcasing polarization-independent impedance matching and birefringence-free refraction despite anisotropy, like "stretched free space" in transformation optics. This finding has many potential applications like radomes.

A recent study highlights the hepatotoxicity of tire-wear particle (TWP) leachates in aquatic environments, impacting gut-liver axis and inducing oxidative damage. The findings suggest potential health risks for aquatic organisms.

Microendoscopes based on multicore fibers allow for minimally invasive 3D imaging of tissues in hard-to-reach locations in medical diagnostics and brain research. Unfortunately, they suffer from low light collection efficiency. Scientists from Poland and Germany invented a way to increase the light collection leading to even three times higher contrast in transmitted image. Their research is an important step in progress of fiber-based microendoscopy and its transfer to applications in brain cancer diagnostics.

Researchers have developed a virtual vibration test rig (VTR) capable of simulating the fatigue life of dozer push arms with unprecedented accuracy.

Electric vehicles (EVs) have emerged as a promising trend for future development. Serving as the core energy source for EVs, lithium-ion batteries offer advantages. Accurate SoC estimation is vital when you have to take care of battery management. A recent breakthrough study presented by researchers from the Chang'an University and RWTH Aachen University introduces an improved model combining machine learning and Kalman filtering architecture for state of charge estimation of lithium-ion batteries. This advanced method not only achieves accurate online SOC estimation and improves the safety of Lithium-ion batteries.