Determination of beam incidence conditions based on the analysis of laser interference patterns

Beam incidence conditions in the formation of two-, three- and four-beam laser interference patterns are presented and studied in this paper. In a laser interference lithography (LIL) process, it is of importance to determine and control beam incidence conditions based on the analysis of laser interference patterns for system calibration as any slight change of incident angles or intensities of beams will introduce significant variations of periods and contrasts of interference patterns. In this work, interference patterns were captured by a He-Ne laser interference system under different incidence conditions, the pattern period measurement was achieved by cross-correlation with, and the pattern contrast was calculated by image processing. Subsequently, the incident angles and intensities of beams were determined based on the analysis of spatial distributions of interfering beams. As a consequence, the relationship between the beam incidence conditions and interference patterns is revealed. The proposed method is useful for the calibration of LIL processes and for reverse engineering applications

Heavy fermion fluid in high magnetic fields: an infrared study of CeRu4_4Sb12_{12}

We report a comprehensive infrared magneto-spectroscopy study of CeRu$_4$Sb$_{12}$ compound revealing quasiparticles with heavy effective mass m$^*$, with a detailed analysis of optical constants in fields up to 17 T. We find that the applied magnetic field strongly affects the low energy excitations in the system. In particular, the magnitude of m$^*$ $\simeq$ 70 m$_b$ (m$_b$ is the quasiparticle band mass) at 10 K is suppressed by as much as 25 % at 17 T. This effect is in quantitative agreement with the mean-field solution of the periodic Anderson model augmented with a Zeeman term

Flowering time: from physiology, through genetics to mechanism.

Plant species have evolved different requirements for environmental/endogenous cues to induce flowering. Originally, these varying requirements were thought to reflect the action of different molecular mechanisms. Thinking changed when genetic and molecular analysis in Arabidopsis thaliana revealed that a network of environmental and endogenous signalling input pathways converge to regulate a common set of 'floral pathway integrators'. Variation in the predominance of the different input pathways within a network can generate the diversity of requirements observed in different species. Many genes identified by flowering time mutants were found to encode general developmental and gene regulators, with their targets having a specific flowering function. Studies of natural variation in flowering were more successful at identifying genes acting as nodes in the network central to adaptation and domestication. Attention has now turned to mechanistic dissection of flowering time gene function and how that has changed during adaptation. This will inform breeding strategies for climate-proof crops and help define which genes act as critical flowering nodes in many other species. [Abstract copyright: © The Author(s) 2024. Published by Oxford University Press on behalf of American Society of Plant Biologists.

Developing offloading-enabled application development frameworks for android mobile devices

Mobile devices, such as smartphones, offer people great convenience in accessing information and computation resources. However, mobile devices remain relatively limited in terms of computing, memory and energy capacity when compared with desktop machines. A promising solution to mitigate these limitations is to enhance the services mobile devices can provide by utilizing powerful cloud platforms through offloading mechanisms, i.e., offloading the heavy information processing tasks from mobile devices to the Cloud. This paper addresses this issue by developing two offloading-enabled application development frameworks by adapting certain Android OS interfaces. The applications developed using these frameworks will be equipped with offloading capability. In the first framework, each application is selfish and makes offloading decisions independently, whereas in the second, a central offloading manager resides in the mobile device and is responsible for making the offloading decisions for all applications. The two frameworks are designed in a way that application developers only need to make minimal changes to their programming behavior. Experiments have been conducted that verify the feasibility and effectiveness of the offloading mechanisms that are proposed

Ce doping in T-La2CuO4 films: Broken electron-hole symmetry for high-Tc superconductivity

We attempted Ce doping in La2CuO4 with the K2NiF4 (T) structure by molecular beam epitaxy. At low growth temperature and with an appropriate substrate choice, we found that Ce can be incorporated into the K2NiF4 lattice up to x ~ 0.06, which had not yet been realized in bulk synthesis. The doping of Ce makes T-La2-xCexCuO4 more insulating, which is in sharp contrast to Ce doping in La2CuO4 with the Nd2CuO4 structure, which makes the compounds superconducting. The observed smooth increase in resistivity from hole-doped side (T-La2-xSrxCuO4) to electron-doped side (T-La2-xCexCuO4) indicates that electron-hole symmetry is broken in the T-phase materials.Comment: proceedings of ISS 200

Nature of the spin resonance mode in CeCoIn5_5

Spin-fluctuation-mediated unconventional superconductivity can emerge at the border of magnetism, featuring a superconducting order parameter that changes sign in momentum space. Detection of such a sign-change is experimentally challenging, since most probes are not phase-sensitive. The observation of a spin resonance mode (SRM) from inelastic neutron scattering is often seen as strong phase-sensitive evidence for a sign-changing superconducting order parameter, by assuming the SRM is a spin-excitonic bound state. Here, we show that for the heavy fermion superconductor CeCoIn$_5$, its SRM defies expectations for a spin-excitonic bound state, and is not a manifestation of sign-changing superconductivity. Instead, the SRM in CeCoIn$_5$ likely arises from a reduction of damping to a magnon-like mode in the superconducting state, due to its proximity to magnetic quantum criticality. Our findings emphasize the need for more stringent tests of whether SRMs are spin-excitonic, when using their presence to evidence sign-changing superconductivity.Comment: accepted for publication in Communications Physic

Generic phase diagram of "electron-doped" T' cuprates

We investigated the generic phase diagram of the electron doped superconductor, Nd2-xCexCuO4, using films prepared by metal organic decomposition. After careful oxygen reduction treatment to remove interstitial Oap atoms, we found that the Tc increases monotonically from 24 K to 29 K with decreasing x from 0.15 to 0.00, demonstrating a quite different phase diagram from the previous bulk one. The implication of our results is discussed on the basis of tremendous influence of Oap "impurities" on superconductivity and also magnetism in T' cuprates. Then we conclude that our result represents the generic phase diagram for oxygen-stoichiometric Nd2-xCexCuO4.Comment: 12 pages, 4 figures; International Symposium on Superconductivity (ISS) 200

Optical Signatures of Dirac Nodal-lines in NbAs2_2

Using polarized optical and magneto-optical spectroscopy, we have demonstrated universal aspects of electrodynamics associated with Dirac nodal-lines. We investigated anisotropic electrodynamics of NbAs$_2$ where the spin-orbit interaction triggers energy gaps along the nodal-lines, which manifest as sharp steps in the optical conductivity spectra. We show experimentally and theoretically that shifted 2D Dirac nodal-lines feature linear scaling $\sigma_1 (\omega)\sim\omega$, similar to 3D nodal-points. Massive Dirac nature of the nodal-lines are confirmed by magneto-optical data, which may also be indicative of theoretically predicted surface states. Optical data also offer a natural explanation for the giant magneto-resistance in NbAs$_2$

The AI Revolution: Opportunities and Challenges for the Finance Sector

This report examines Artificial Intelligence (AI) in the financial sector, outlining its potential to revolutionise the industry and identify its challenges. It underscores the criticality of a well-rounded understanding of AI, its capabilities, and its implications to effectively leverage its potential while mitigating associated risks. The potential of AI potential extends from augmenting existing operations to paving the way for novel applications in the finance sector. The application of AI in the financial sector is transforming the industry. Its use spans areas from customer service enhancements, fraud detection, and risk management to credit assessments and high-frequency trading. However, along with these benefits, AI also presents several challenges. These include issues related to transparency, interpretability, fairness, accountability, and trustworthiness. The use of AI in the financial sector further raises critical questions about data privacy and security. A further issue identified in this report is the systemic risk that AI can introduce to the financial sector. Being prone to errors, AI can exacerbate existing systemic risks, potentially leading to financial crises. Regulation is crucial to harnessing the benefits of AI while mitigating its potential risks. Despite the global recognition of this need, there remains a lack of clear guidelines or legislation for AI use in finance. This report discusses key principles that could guide the formation of effective AI regulation in the financial sector, including the need for a risk-based approach, the inclusion of ethical considerations, and the importance of maintaining a balance between innovation and consumer protection. The report provides recommendations for academia, the finance industry, and regulators