Aggregation induced photodynamic therapy enhancement based on linear and nonlinear excited FRET of fluorescent organic nanoparticles

A binary molecule can self-assemble to form fluorescent organic nanoparticles (FONs) based on the Aggregation-Induced Emission Enhancement (AIEE) property and subsequently, presents an efficient fluorescence resonance energy transfer (FRET) to generate singlet oxygen under linear and nonlinear light sources. Biologically, this FON-photosensitizer is much more phototoxic to cancer cells than to normal cells without significant dark toxicity. Eventually, a new approach, called FON FRET-PDT or AIEE FRET-PDT, to promote the PDT effect is expected

FinTech Governance Challenges and Solutions: A Critical Review and Research Agenda

Background: The rise of financial technology (FinTech) has opened avenues for non-financial companies to innovate and provide personalized financial services. Despite the benefits of FinTech innovations, ensuring quality governance remains a significant challenge for the entire FinTech ecosystem. Existing literature primarily addresses general challenges at the enterprise level, with limited focus on the multi-faceted governance of FinTech. This study aims to present a taxonomical classification by synthesizing relevant issues and proposing theoretically feasible solutions for the governance of the entire FinTech ecosystem. Method: This study conducts a comprehensive literature review of 38 published articles on FinTech challenges and governance over the past two decades. Employing a theoretical review approach, the collected articles are initially analyzed and synthesized into 105 concepts with the assistance of ChatGPT-3.5 and then manually categorized into challenges and their corresponding solutions. Results: A total of 29 issues from the pool of literature are classified into 7 categories along with 53 corresponding solutions. This study confirms that FinTech governance should be undertaken collaboratively by all actors across the ecosystem. Conclusion: Through reviewing and analyzing the existing literature, this study provides an overview of the present knowledge base of FinTech governance and formulates a taxonomy for the challenges and solutions of FinTech governance. The identified issues and potential solutions may serve as a valuable reference for stakeholders in the FinTech ecosystem, offering practical insights for improving governance practices. In theory, this study contributes to the literature by expanding the understanding of FinTech governance beyond individual enterprises to encompass the entire ecosystem, thus highlighting the interconnected nature of governance challenges and solutions

On the Distribution of Neutral Tone in Southern Min: LCC and Beyond

The aim of this paper is to address an often-overlooked topic in Southern Min tonology: neutral tone. We show that the tone sandhi domain in Southern Min is not always isomorphic with an XP in syntax or a phonological phrase. In fact, this domain may be smaller than what has been predicted, as evidenced in the phrase-final functional morphemes as well as in the rhythmic effect. We propose that the tone sandhi domain in Southern Min is defined by a constituent Tone Sandhi Domain (TSD, τ) between the p-phrase and the p-word. A TSD is required to bear a final prominence, and only a p-word, mapped from a contentive or focused element in syntax, can be a “prominence-bearing unit.

Influence of nonuniform recharge on groundwater flow in heterogeneous aquifers

The composition of soils in aquifers is typically not homogeneous, and soil layers may be cracked or displaced due to geological activities. This heterogeneity in soil distribution within aquifers affects groundwater flow and water level variations. In the present study, we established a two-dimensional (2D) mathematical model that considers the influence of surface recharge on groundwater flow in heterogeneous sloping aquifers. By considering temporal variations in surface recharge, slope angle and aquifer heterogeneity, the simulated results are expected to better reflect real conditions in natural aquifers. The effects of aquifer heterogeneity on groundwater flow and water levels are particularly significant in sloping aquifers. The study's findings indicate that even when the soil composition remains constant, variations in groundwater level and flow may be considerable, depending on factors such as soil alignment, slope angle of the aquifer's base layer and the direction of water flow

THE EFFECT OF FOOT POSITION ON KINETICS OF LOWER LIMBS DURING SQUAT

The purposes of this study were to evaluate the effects of the foot position on the joint forces and moments of lower limbs during squat. Eleven male weightlifters were recruited in this study to perform squat with different foot position (forward position and toe-out 20 degrees). The VICON motion analysis system and two KISTLER force platforms were used to record the kinematical and kinetic data during squat. The results showed that the ankle joint maximal shear force, maximal adduction moment, external rotation moment and knee external rotation moment during squat with foot forward position were significantly greater than the results in toe-out position. Squat with foot forward position could be suggested to improve the ankle stability in rehabilitative training

A Methodology for Evaluating Data and Output Misfits in Commercial Off-The-Shelf ERP Systems

This paper presents a methodology based on the task-technology fit theory to identify data and output misfits in the ex-ante evaluation of an off-the shelf enterprise resources planning (ERP) package. The proposed methodology consists of two stages: output misfit analysis and data misfit analysis. The purpose of the first stage is to identify corresponding field (output misfits) and data glossary for data misfit analysis. The latter stage identifies data misfits for every corresponding activity in the business process sequence. The proposed methodology provides a systematic approach to alleviate the difficulty and complexity in identifying data and output misfits. The identification results identify where the misfits are and provide a degree of mismatch, thus providing a practical basis for ERP tool selection to reduce the risk of failure in its implementation

Self-Progressing Robust Training

Enhancing model robustness under new and even adversarial environments is a crucial milestone toward building trustworthy machine learning systems. Current robust training methods such as adversarial training explicitly uses an "attack" (e.g., $\ell_{\infty}$-norm bounded perturbation) to generate adversarial examples during model training for improving adversarial robustness. In this paper, we take a different perspective and propose a new framework called SPROUT, self-progressing robust training. During model training, SPROUT progressively adjusts training label distribution via our proposed parametrized label smoothing technique, making training free of attack generation and more scalable. We also motivate SPROUT using a general formulation based on vicinity risk minimization, which includes many robust training methods as special cases. Compared with state-of-the-art adversarial training methods (PGD-l_inf and TRADES) under l_inf-norm bounded attacks and various invariance tests, SPROUT consistently attains superior performance and is more scalable to large neural networks. Our results shed new light on scalable, effective and attack-independent robust training methods.Comment: Accepted in AAAI202