Preparation, characterization, and antiproliferative activities of biotin-decorated docetaxel-loaded bovine serum albumin nanoparticles

The aim of the present study was to characterize biotin-decorated docetaxel-loaded bovine serum albumin nanoparticles (DTX-BIO-BSA-NPs) and evaluate their antiproliferative activity in vitro. The particle size of prepared DTX-BIO-BSA-NPs was found to be always lower than 200 nm, with sizes of 166.9, 160.3, 159.0, 176.1 and 184.8 nm and the zeta potential was -29.51, -28.54, -36.54, -36.08 and -27.56 mV after redissolution with water for 0, 1, 2, 4 and 8 hours, respectively. The polydispersity index (PDI) was stable in the range of 0.170 - 0.178. In the in vitro drug-release study, the DTX-BIO-BSA-NPs targeted a human breast cancer cell line MCF-7 effectively. The x-ray diffraction spectrum and DSC curve of DTX-BIO-BSA-NPs suggested that docetaxel was in an amorphous or disordered crystalline phase in DTX-BIO-BSA-NPs. In vitro cytotoxicity results showed that DTX-BIO-BSA-NPs inhibits proliferation of MCF-7, SGC7901, LS-174T and A549 cells in a concentration-dependent manner after exposure to DTX-BIO-BSA-NPs for 48 hours. Taken together, these results indicate that DTX-BIO-BSA-NPs may have potential as an alternative delivery system for parenteral administration of docetaxel

A heuristic explicit model predictive control framework for Eco-trajectory planning: Theoretical analysis and case study

The trajectory planning problem (TPP) has become increasingly crucial in the research of next-generation transportation systems, but it presents challenges due to the non-linearity of its constraints. One specific case within TPP, namely the Eco-trajectory Planning Problem (EPP), poses even greater computational difficulties due to its nonlinear, high-order, and non-convex objective function. This paper proposes a heuristic explicit predictive model control (heMPC) framework to address the eco-trajectory planning problem in scenarios without lane-changing behavior. The heMPC framework consists of an offline module and an online module. In the offline module, we build an optimal eco-trajectory batch by optimizing a series of simplified EPPs considering different system initial states and terminal states, which is equivalent to the lookup table in the general eMPC framework. The core idea of the offline module is to finish all potential optimization and computing in advance to avoid any form of online optimization in the online module. In the online module, we provide static and dynamic trajectory planning algorithms. Both algorithms greatly improve the computational efficiency of planning and only suffer from a limited extent of optimality losses through a batch-based selection process because any optimization and calculation are pre-computed in the offline module. The latter algorithm is also able to face possible emergencies and prediction errors. Both theoretical analysis and numerical are shown and discussed to test the computational quality and efficiency of the heMPC framework under a mixed-traffic flow environment that incorporates human-driving vehicles (HDV) and connected and automated vehicles (CAV) with different market penetration rates (MPR)

Truth Forest: Toward Multi-Scale Truthfulness in Large Language Models through Intervention without Tuning

Despite the great success of large language models (LLMs) in various tasks, they suffer from generating hallucinations. We introduce Truth Forest, a method that enhances truthfulness in LLMs by uncovering hidden truth representations using multi-dimensional orthogonal probes. Specifically, it creates multiple orthogonal bases for modeling truth by incorporating orthogonal constraints into the probes. Moreover, we introduce Random Peek, a systematic technique considering an extended range of positions within the sequence, reducing the gap between discerning and generating truth features in LLMs. By employing this approach, we improved the truthfulness of Llama-2-7B from 40.8\% to 74.5\% on TruthfulQA. Likewise, significant improvements are observed in fine-tuned models. We conducted a thorough analysis of truth features using probes. Our visualization results show that orthogonal probes capture complementary truth-related features, forming well-defined clusters that reveal the inherent structure of the dataset.Comment: Accepted as AAAI 202

Optical neural network architecture for deep learning with the temporal synthetic dimension

The physical concept of synthetic dimensions has recently been introduced into optics. The fundamental physics and applications are not yet fully understood, and this report explores an approach to optical neural networks using synthetic dimension in time domain, by theoretically proposing to utilize a single resonator network, where the arrival times of optical pulses are interconnected to construct a temporal synthetic dimension. The set of pulses in each roundtrip therefore provides the sites in each layer in the optical neural network, and can be linearly transformed with splitters and delay lines, including the phase modulators, when pulses circulate inside the network. Such linear transformation can be arbitrarily controlled by applied modulation phases, which serve as the building block of the neural network together with a nonlinear component for pulses. We validate the functionality of the proposed optical neural network for the deep learning purpose with examples handwritten digit recognition and optical pulse train distribution classification problems. This proof of principle computational work explores the new concept of developing a photonics-based machine learning in a single ring network using synthetic dimensions, which allows flexibility and easiness of reconfiguration with complex functionality in achieving desired optical tasks

Stress test measurements of lattice-matched InAlN/AlN/GaN HFET structures

InAlN/GaN heterostructures offer some benefits over existing AlGaN/GaN heterostructures for HFET device applications. In addition to having a larger bandgap than typical AlGaN compounds used in HFET devices (with Al < 30%), which leads to better confinement and subsequent larger power carrying capacity, InAlN can be grown lattice-matched to GaN, resulting in strain-free heterostructures. As such, lattice-matched InAlN provides a unique system wherein the reliability of the devices may exceed that of the strained AlGaN/GaN devices as a result of being able to decouple the hot electron/hot phonon effects on the reliability from the strain related issues. In this work, we subjected lattice-matched InAlN-based HFETs to electrical stress and observed the corresponding degradation in maximum drain current. We found that the degradation rates are lower only for a narrow range of moderate gate biases, corresponding to low field average 2-dimensional electron gas (2DEG) densities of 9–10 × 10 12  cm −2 . We propose that the degradation is attributable to the buildup of hot phonons since the degradation rates as a function of electron density generally follow the hot phonon lifetime versus electron density. This provides evidence that hot phonons have a significant role in device degradation and there exists an optimal 2DEG density to minimize hot phonon related degradation. We did not observe any correlation between the degradation rate and the gate leakage.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77433/1/1345_ftp.pd

An AT-hook gene is required for palea formation and floral organ number control in rice

AbstractGrasses have highly specialized flowers and their outer floral organ identity remains unclear. In this study, we identified and characterized rice mutants that specifically disrupted the development of palea, one of the outer whorl floral organs. The depressed palea1 (dp1) mutants show a primary defect in the main structure of palea, implying that palea is a fusion between the main structure and marginal tissues on both sides. The sterile lemma at the palea side is occasionally elongated in dp1 mutants. In addition, we found a floral organ number increase in dp1 mutants at low penetration. Both the sterile lemma elongation and the floral organ number increase phenotype are enhanced by the mutation of an independent gene SMALL DEGENERATIVE PALEA1 (SDP1), whose single mutation causes reduced palea size. E function and presumable A function floral homeotic genes were found suppressed in the dp1–2 mutant. We identified the DP1 gene by map-based cloning and found it encodes a nuclear-localized AT-hook DNA binding protein, suggesting a grass-specific role of chromatin architecture modification in flower development. The DP1 enhancer SDP1 was also positional cloned, and was found identical to the recently reported RETARDED PALEA1 (REP1) gene encoding a TCP family transcription factor. We further found that SDP1/REP1 is downstreamly regulated by DP1