KMT-2021-BLG-1547Lb: Giant microlensing planet detected through a signal deformed by source binarity

We investigate the previous microlensing data collected by the KMTNet survey in search of anomalous events for which no precise interpretations of the anomalies have been suggested. From this investigation, we find that the anomaly in the lensing light curve of the event KMT-2021-BLG-1547 is approximately described by a binary-lens (2L1S) model with a lens possessing a giant planet, but the model leaves unexplained residuals. We investigate the origin of the residuals by testing more sophisticated models that include either an extra lens component (3L1S model) or an extra source star (2L2S model) to the 2L1S configuration of the lens system. From these analyses, we find that the residuals from the 2L1S model originate from the existence of a faint companion to the source. The 2L2S solution substantially reduces the residuals and improves the model fit by $\Delta\chi^2=67.1$ with respect to the 2L1S solution. The 3L1S solution also improves the fit, but its fit is worse than that of the 2L2S solution by $\Delta\chi^2=24.7$. According to the 2L2S solution, the lens of the event is a planetary system with planet and host masses $(M_{\rm p}/M_{\rm J}, M_{\rm h}/M_\odot)=\left( 1.47^{+0.64}_{-0.77}, 0.72^{+0.32}_{-0.38}\right)$ lying at a distance \D_{\rm L} =5.07^{+0.98}_{-1.50}~kpc, and the source is a binary composed of a subgiant primary of a late G or an early K spectral type and a main-sequence companion of a K spectral type. The event demonstrates the need of sophisticated modeling for unexplained anomalies for the construction of a complete microlensing planet sample.Comment: 9 pages, 4 tables, 7 figure

KMT-2022-BLG-0440Lb: A New q<10−4q < 10^{-4} Microlensing Planet with the Central-Resonant Caustic Degeneracy Broken

We present the observations and analysis of a high-magnification microlensing planetary event, KMT-2022-BLG-0440, for which the weak and short-lived planetary signal was covered by both the KMTNet survey and follow-up observations. The binary-lens models with a central caustic provide the best fits, with a planet/host mass ratio, $q = 0.75$--$1.00 \times 10^{-4}$ at $1\sigma$. The binary-lens models with a resonant caustic and a brown-dwarf mass ratio are both excluded by $\Delta\chi^2 > 70$. The binary-source model can fit the anomaly well but is rejected by the ``color argument'' on the second source. From Bayesian analyses, it is estimated that the host star is likely a K or M dwarf located in the Galactic disk, the planet probably has a Neptune-mass, and the projected planet-host separation is $1.9^{+0.6}_{-0.7}$ or $4.6^{+1.4}_{-1.7}$ au, subject to the close/wide degeneracy. This is the third $q < 10^{-4}$ planet from a high-magnification planetary signal ($A \gtrsim 65$). Together with another such planet, KMT-2021-BLG-0171Lb, the ongoing follow-up program for the KMTNet high-magnification events has demonstrated its ability in detecting high-magnification planetary signals for $q < 10^{-4}$ planets, which are challenging for the current microlensing surveys.Comment: MNRAS accepte

Fast Bidirectional Motion Planning for Self-Driving General N-Trailers Vehicle Maneuvering in Narrow Space

Self-driving General N-trailers (GNT) vehicles are one of the future solutions to build intelligent factory due to its flexibility and large load. Maneuvering of GNT vehicle to its destination requires accurate and robust motion planning. But the narrow operating environment causes nonlinear nonconvex constraints which are challenging. Furthermore, the nonholonomic constraints in GNT kinematics elevate the complexity in state space. Therefore, motion planning of GNT vehicle maneuvering in narrow space within a reasonable time and high success rate is a critical problem. This paper proposes a fast bidirectional motion planning algorithm to generate trajectories for GNT vehicles to maneuver in a narrow space. A coarse-to-fine motion planning paradigm has been proposed to balance the robustness and time. In the coarse step, an initial guess is generated through a bidirectional-sampled closed-loop Rapidly-exploring Random Tree, and a spatial-temporal safety corridor has been constructed to convert nonlinear nonconvex constraints to linear convex constraints. In the fine step, an optimal control problem is defined accordingly and solved to obtain feasible trajectory. Four different scenarios have been conducted with forward and reverse GNT vehicle maneuvering in a narrow environment. The results show that the proposed method outperforms state-of-the-art sampling-based and optimization-based motion planning methods

Metal nanoparticles for cancer therapy: Precision targeting of DNA damage

Cancer, a complex and heterogeneous disease, arises from genomic instability. Currently, DNA damage-based cancer treatments, including radiotherapy and chemotherapy, are employed in clinical practice. However, the efficacy and safety of these therapies are constrained by various factors, limiting their ability to meet current clinical demands. Metal nanoparticles present promising avenues for enhancing each critical aspect of DNA damage-based cancer therapy. Their customizable physicochemical properties enable the development of targeted and personalized treatment platforms. In this review, we delve into the design principles and optimization strategies of metal nanoparticles. We shed light on the limitations of DNA damage-based therapy while highlighting the diverse strategies made possible by metal nanoparticles. These encompass targeted drug delivery, inhibition of DNA repair mechanisms, induction of cell death, and the cascading immune response. Moreover, we explore the pivotal role of physicochemical factors such as nanoparticle size, stimuli-responsiveness, and surface modification in shaping metal nanoparticle platforms. Finally, we present insights into the challenges and future directions of metal nanoparticles in advancing DNA damage-based cancer therapy, paving the way for novel treatment paradigms