This paper is concerned with linear quadratic control problems of stochastic differential equations (SDEs, in short) and stochastic Volterra integral equations (SVIEs, in short). Notice that for ...stochastic systems, the control weight in the cost functional is allowed to be indefinite. This feature is demonstrated here only by open-loop optimal controls but not limited to closed-loop optimal controls in the literature. As to linear quadratic problem of SDEs, some examples are given to point out the issues left by existing papers, and new characterizations of optimal controls are obtained in different manners. For the study of SVIEs with deterministic coefficients, a class of stochastic Fredholm−Volterra integral equations is introduced to replace conventional forward-backward SVIEs. Eventually, instead of using convex variation, we use spike variation to obtain some additional optimality conditions of linear quadratic problems for SVIEs.
This article is addressed to giving a solution to a unsolved problem,
i.e.
, to establish the necessary optimality conditions of Pontraygin’s type for controlled stochastic Volterra integral ...equations (SVIEs) when the control region is non-convex and the control variable enters into the diffusion. This problem has been open since J. Yong,
Stochastic Process Appl.
116
(2006) 779–795 obtained the analogue result for the case of convex control region. The key is to introduce
a pair of
suitable second-order adjoint processes (SOAPs). It is found that the usual way of using
only one
SOAP in the maximum condition for the classical setting of controlled stochastic differential equations does not work here.
With more than a billion people lacking accessible drinking water, there is a critical need to convert nonpotable sources such as seawater to water suitable for human use. However, energy ...requirements of desalination plants account for half their operating costs, so alternative, lower energy approaches are equally critical. Membrane distillation (MD) has shown potential due to its low operating temperature and pressure requirements, but the requirement of heating the input water makes it energy intensive. Here, we demonstrate nanophotonics-enabled solar membrane distillation (NESMD), where highly localized photothermal heating induced by solar illumination alone drives the distillation process, entirely eliminating the requirement of heating the input water. Unlike MD, NESMD can be scaled to larger systems and shows increased efficiencies with decreased input flow velocities. Along with its increased efficiency at higher ambient temperatures, these properties all point to NESMD as a promising solution for household- or community-scale desalination.
For some backward stochastic Volterra integral equations (BSVIEs) in multi-dimensional Euclidean spaces, comparison theorems are established in a systematic way for the adapted solutions and adapted ...M-solutions. For completeness, comparison theorems for (forward) stochastic differential equations, backward stochastic differential equations, and (forward) stochastic Volterra integral equations (FSVIEs) are also presented. Duality principles are used in some relevant proofs. Also, it is found that certain kinds of monotonicity conditions play crucial roles to guarantee the comparison theorems for FSVIEs and BSVIEs to be true. Various counterexamples show that the assumed conditions are almost necessary in some sense.
Anaplastic thyroid carcinoma (ATC) is a highly malignant tumor with invasive nature. Most patients present with locally advanced and/or distant metastatic diseases that are difficult to treat. We ...report a case of a previously inoperable patient with v-Raf murine sarcoma viral oncogene homolog B (BRAF) mutated ATC. After a trial of neoadjuvant Dabrafenib/Trametinib with immunotherapy, the tumor became operable, and surgical pathology indicated a pathologic complete response (pCR). We also reviewed cases from the literature that utilized neoadjuvant BRAF-directed therapy in ATCs. These cases emphasize that BRAF-and immune-directed therapy is a feasible option in patients with inoperable ATC and may lead to improved outcomes.
The way that artificial intelligence technology is being developed is causing a progressive evolution in college and university teaching methods and systems. This paper presents the design of the ...English teaching mode in colleges and universities based on artificial intelligence technology. Research on strategies for English teaching reform in colleges and universities supported by artificial intelligence technology. A weighted inference model was used to design an AI expert system, based on which an intelligent assisted learning system based on a neural network was constructed using the law of knowledge forgetting. Based on information acquisition, the random Linsen method was selected as the assessment methodology for the impact of English instruction in colleges and universities. The assessment model’s performance and errors are examined through comparison tests of the teaching evaluation model. In this article, the educational effect evaluation model has an accuracy rate of 91% and a mean square error of less than 0.002. The impact of AI-assisted English instruction on teaching is evaluated based on this. Results from studies conducted both before and following the experimental group show that the overall score increases by 12.33 points and the P-value of the four dimensions’ teaching effect is less than 0.01. The experimental group using artificial intelligence technology for English instruction received an average comprehensive score of 95 points in the actual English assessment, which is 8 points higher than the control group receiving traditional English instruction. This paper’s artificial intelligence teaching mode is believed to have a significant impact on students’ English, which is confirmed by its effectiveness and rationality. It is beneficial for teaching reform and guides enhancing and advancing English instruction in colleges and institutions.
With the development of electric vehicles, more attention has been paid to the role of the driving cycle in vehicle performance testing. At present, the K-means algorithm is often used in the ...development of driving cycles. However, it is sensitive to the outlier points and also difficult to determine the K value. To solve this problem, the hierarchical cluster method is applied in this study. First, the real-world driving data are collected and denoised through wavelet domain denoising. Then, the data are divided into micro-trips and the characteristic parameters are extracted. The hierarchical cluster method is adopted to classify the micro-trips into different categories. An appropriate number of micro-trips are selected from each group in proportion to each category to assemble the driving cycle. Finally, both the economic simulation and the statistical analysis prove the accuracy of the generated driving cycle and the feasibility of the development method proposed in this paper.
In this technical note, we formulate and investigate a class of mean-field linear-quadratic-Gaussian (LQG) games for stochastic integral systems. Unlike other literature on mean-field games where the ...individual states follow the controlled stochastic differential equations (SDEs), the individual states in our large-population system are characterized by a class of stochastic Volterra-type integral equations. We obtain the Nash certainty equivalence (NCE) equation and hence derive the set of associated decentralized strategies. The ∈-Nash equilibrium properties are also verified. Due to the intrinsic integral structure, the techniques and estimates applied here are significantly different from those existing results in mean-field LQG games for stochastic differential systems. For example, some Fredholm equation in the meanfield setup is introduced for the first time. As for applications, two types of stochastic delayed systems are formulated as the special cases of our stochastic integral system, and relevant mean-field LQG games are discussed.
The present work aims to evaluate the significance of sleep disturbance and electroencephalogram (EEG) alteration in the early stage of Alzheimer's disease (AD).
Sleep disturbance is common in ...patients with AD. It is not known if it can occur at the early stage of AD and if EEG recording may help identify the early sign of the disease.
Sleep disturbance in AD has generally been considered as late consequence of the neurodegenerative process. A growing body of evidence has suggested that the sleep disturbance may occur at the early stage of AD.
Based on the previous epidemiologic studies and our recent findings, we propose that sleep disturbance may play an important role in the development of AD. Sleep EEG changes may serve as a valuable early sign for AD in the prepathological stage.
Our data suggested that AβPPswe/PS1ΔE9 transgenic AD mice at preplaque stage (3 and 4 months of age) exhibited different profile of sleep architecture and sleep EEG, which preceded the cognitive deficit and AD neuropathology.
Future experiments should focus on sleep EEG changes in patients with mild cognitive impairment and early stage of AD. Follow-up studies in high-risk population of the elderly are equally important. In addition, the exact molecular mechanism underlying the sleep disturbance should be thoroughly investigated.
Studies on human participants with early stage of AD, especially the follow-up studies on the presymptomatic elderly in a large population, are difficult and time-consuming.
Our hypothesis may link previous theories to establish a bidirectional relationship between sleep disorders and AD, which may finally form a new schematic mechanism to understand the disease pathogenesis and disease progression.
Elevated adenosine generated by CD73 (ecto‐5′‐nucleotidase; NT5E) could boost immunosuppressive responses and promote immune evasion in the tumor microenvironment. However, despite the immune ...response, CD73 could also promote tumor progression in a variety of cancers, and the nonimmunologic role and corresponding molecular mechanism of CD73 involved in head and neck squamous cell carcinoma (HNSCC) progression are not well characterized. Here, we demonstrated that CD73/NT5E is overexpressed in HNSCC tissues and predicts poor prognosis. Suppression of CD73 inhibited the proliferation, migration, and invasion of HNSCC cell lines (CAL27 and HN4) in vitro and in vivo. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) predicted that CD73 may be involved in invadopodia formation and MAPK signaling activation. As expected, knockdown of CD73 inhibited the MAPK signaling pathway, and the suppressive effect of CD73 knockdown on proliferation, migration, invasion, and invadopodia formation was reversed by a MAPK signaling activator. Our results suggest that CD73 could promote the proliferation, migration, invasion, and invadopodia formation of HNSCC via the MAPK signaling pathway and provide new mechanistic insights into the nonimmunological role of CD73 in HNSCC.
Despite immunomodulating role, corresponding molecular mechanism of CD73 involved in HNSCC progression are not well characterized. In this work, We found that CD73 was up‐regulated in HNSCC tissues and could serve as independent prognostic factor. Based on the result of GSEA and GSVA, we found that CD73 take part in the invadopodia formation of HNSCC and activation of MAPK signaling pathway may account for the tumor promoting role of CD73.
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