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In this article, we study three pricing policies for a monopoly platform, such as Uber or Gett, who offers vertically differentiated services to customers via multiple types of self-scheduling providers. Ideally, the platform can employ a "dynamic pricing" policy, which pays providers wages and charges customers prices for the transactions of different services that both adjust based on prevailing demand conditions, to maximize its profit. However, since it is challenging for the platform to implement and for providers to understand this policy, the other two pricing policies are commonly adopted in practice, that is, "surge pricing" policy (adopted by Uber) which pays providers a fixed commission of its dynamic prices, and "static pricing" policy (applied by Gett) which pays providers a fixed commission of its fixed prices. By observing these phenomena, we propose to study and discuss the platform's profit performance of these three pricing strategies. We show that the surge pricing policy does not always perform well, which can explain why some on-demand platforms would implement the static pricing policy in practice. Also, although the dynamic pricing policy will significantly improve the platform's profit, we find that the profitability of the static (surge) pricing policy would approach that of the dynamic pricing policy if the platform can balance the number of different types of providers and/or reduce the commission rate. [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO2) plays a key role in environmental protection and human health. Recently, molybdenum disulfide (MoS2) representative of novel 2D materials has been utilized to detect NO2 gas, still hindered by the weak response, high operation temperature, as well as poor recovery characteristics. Herein, we report a UV light-assisted, room-temperature, recoverable, sensitive and selective NO2 gas sensing based on few-layer MoS2 nanosheet-Au nanoparticle composites serving as the sensing layer. In the dark condition, the as-prepared MoS2-Au sensor showed a response of 10% toward 2.5 ppm NO2 more than two times larger than MoS2 one, arising from more reaction sites (spillover effect and produced interfaces) and smaller baseline resistance after Au incorporation. Undesirably, all sensors exhibited an incomplete recovery. When MoS2-Au sensors were exposed to NO2 gas under UV illumination, better performance in terms of three-time enhanced response, full recovery and favorable repeatability was achieved in comparison with that in the dark case. Two aspects were responsible for these phenomena. On one hand, additional photoinduced charge carriers ensured sufficient gas-solid interactions between sensing layer and target molecules, thereby resulting in a larger response. The other aspect lay in effective separation of these charge carriers at MoS2/Au interfaces, contributing to recoverable and repeatable reactions. MoS2-Au composites were adopted for NO2 detection under UV illumination and exhibited a promising capacity of UV photodetector as well as an inspiring room-temperature gas detection, which provided an alternative strategy to design a single optoelectronic device with multi-functions. [ABSTRACT FROM AUTHOR]

In this paper we introduce the notions of topological pressure and measure-theoretic entropy for a free semigroup action. Suppose that a free semigroup acts on a compact metric space by continuous self-maps. To this action we assign a skew-product transformation whose fiber topological pressure is taken to be the topological pressure of the initial action. Some properties of these two notions are given, followed by two main results. One is the relationship between the topological pressure of the skew-product transformation and the topological pressure of the free semigroup action, the other is the partial variational principle about the topological pressure. Moreover, we apply this partial variational principle to study the measure-theoretic entropy and the topological entropy of finite affine transformations on a metrizable group. [ABSTRACT FROM PUBLISHER]

Bisphenol A (BPA) is an endocrine disruptor that may lead to reproductive disorder, heart disease, and diabetes. Infants and young children are likely to be vulnerable to the effects of BPA. At present, the detection methods of BPA are complicated to operate and require expensive instruments. Therefore, it is quite vital to develop a simple, rapid, and highly sensitive method to detect BPA in different samples. In this study, we have designed a rapid and highly sensitive biosensor based on an effective self-assembled monolayer (SAM) and alternating current (AC) electrokinetics capacitive sensing method, which successfully detected BPA at nanomolar levels with only one minute. The developed biosensor demonstrates a detection of BPA ranging from 0.028 μg/mL to 280 μg/mL with a limit of detection (LOD) down to 0.028 μg/mL in the samples. The developed biosensor exhibited great potential as a portable BPA biosensor, and further development of this biosensor may also be useful in the detection of other small biochemical molecules. [ABSTRACT FROM AUTHOR]

This study introduces an innovative method for identifying high-efficiency perovskite materials using an asymmetric convolution block (ACB). Our approach involves preprocessing extensive data on perovskite oxide materials and developing a precise predictive model. This system is designed to accurately predict key properties such as band gap and stability, thereby eliminating the reliance on traditional feature importance filtering. It exhibited outstanding performance, achieving an accuracy of 96.8% and a recall of 0.998 in classification tasks, and a coefficient of determination (R2) value of 0.993 with a mean squared error (MSE) of 0.004 in regression tasks. Notably, DyCoO3 and YVO3 were identified as promising candidates for photovoltaic applications due to their optimal band gaps. This efficient and precise method significantly advances the development of advanced materials for solar cells, providing a robust framework for rapid material screening. [ABSTRACT FROM AUTHOR]

Multimodal Federated Learning (MMFL) is a novel machine learning technique that enhances the capabilities of traditional Federated Learning (FL) to support collaborative training of local models using data available in various modalities. With the generation and storage of a vast amount of multimodal data from the internet, sensors, and mobile devices, as well as the rapid iteration of artificial intelligence models, the demand for multimodal models is growing rapidly. While FL has been widely studied in the past few years, most of the existing research was based in unimodal settings. With the hope of inspiring more applications and research within the MMFL paradigm, we conduct a comprehensive review of the progress and challenges in various aspects of state-of-the-art MMFL. Specifically, we analyze the research motivation for MMFL, propose a new classification method of existing research, discuss the available datasets and application scenarios, and put forward perspectives on the opportunities and challenges faced by MMFL. [ABSTRACT FROM AUTHOR]

Acrylamide (AA), an odorless and colorless organic small-molecule compound found generally in thermally processed foods, possesses potential carcinogenic, neurotoxic, reproductive, and developmental toxicity. Compared with conventional methods for AA detection, bio/chemical sensors have attracted much interest in recent years owing to their reliability, sensitivity, selectivity, convenience, and low cost. This paper provides a comprehensive review of bio/chemical sensors utilized for the detection of AA over the past decade. Specifically, the content is concluded and systematically organized from the perspective of the sensing mechanism, state of selectivity, linear range, detection limits, and robustness. Subsequently, an analysis of the strengths and limitations of diverse analytical technologies ensues, contributing to a thorough discussion about the potential developments in point-of-care (POC) for AA detection in thermally processed foods at the conclusion of this review. [ABSTRACT FROM AUTHOR]