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This paper addresses novel applications to practical modelling of the newly developed theory of necessary optimality conditions in controlled sweeping/Moreau processes with free time and pointwise control and state constraints. Problems of this type appear, in particular, in dynamical models dealing with unmanned surface vehicles (USVs) and nanoparticles. We formulate optimal control problems for a general class of such dynamical systems and show that the developed necessary optimality conditions for constrained free-time controlled sweeping processes lead us to designing efficient procedures to solve practical models of this class. Moreover, the paper contains numerical calculations of optimal solutions to marine USVs and nanoparticle models in specific situations. Overall, this study contributes to the advancement of optimal control theory for constrained sweeping processes and its practical applications in the fields of marine USVs and nanoparticle modelling. 

Anomaly analysis is an important component of any surveillance system. In recent years, it has drawn the attention of the computer vision and machine learning communities. In this article, our overarching goal is thus to provide a coherent and systematic review of state-of-the-art techniques and a comprehensive review of the research works in anomaly analysis. We will provide a broad vision of computational models, datasets, metrics, extensive experiments, and what anomaly analysis can do in images and videos. Intensively covering nearly 200 publications, we review (i) anomaly related surveys, (ii) taxonomy for anomaly problems, (iii) the computational models, (iv) the benchmark datasets for studying abnormalities in images and videos, and (v) the performance of state-of-the-art methods in this research problem. In addition, we provide insightful discussions and pave the way for future work. 

We present the first threefold differential measurement for neutral-pion multiplicity ratios produced in semi-inclusive deep-inelastic electron scattering on carbon, iron, and lead nuclei normalized to deuterium from CLAS at Jefferson Lab. We found that the neutral-pion multiplicity ratio is maximally suppressed for the leading hadrons (energy fraction $z\to$1), suppression varying from 25% in carbon up to 75% in lead. An enhancement of the multiplicity ratio at low $z$and high $p_T^2$is observed, suggesting an interconnection between these two variables. This behavior is qualitatively similar to the previous twofold differential measurement of charged pions by the HERMES Collaboration and, recently, by CLAS Collaboration. The largest enhancement was observed at high $p_T^2$for heavier nuclei, namely, iron and lead, while the smallest enhancement was observed for the lightest nucleus, carbon. This behavior suggests a competition between partonic multiple scattering, which causes enhancement, and hadronic inelastic scattering, which causes suppression. 

NKX3.1’s downregulation is strongly associated with prostate cancer (PCa) initiation, progression, and CRPC development. Nevertheless, a clear disagreement exists between NKX3.1 protein and mRNA levels in PCa tissues, indicating that its regulation at a post-translational level plays a vital role. This study identified a strong negative relationship between NKX3.1 and LIMK2, which is critical in CRPC pathogenesis. We identified that NKX3.1 degradation by direct phosphorylation by LIMK2 is crucial for promoting oncogenicity in CRPC cells and in vivo. LIMK2 also downregulates NKX3.1 mRNA levels. In return, NKX3.1 promotes LIMK2’s ubiquitylation. Thus, the negative crosstalk between LIMK2-NKX3.1 regulates AR, ARv7, and AKT signaling, promoting aggressive phenotypes. We also provide a new link between NKX3.1 and PTEN, both of which are downregulated by LIMK2. PTEN loss is strongly linked with NKX3.1 downregulation. As NKX3.1 is a prostate-specific tumor suppressor, preserving its levels by LIMK2 inhibition provides a tremendous opportunity for developing targeted therapy in CRPC. Further, as NKX3.1 downregulates AR transcription and inhibits AKT signaling, restoring its levels by inhibiting LIMK2 is expected to be especially beneficial by co-targeting two driver pathways in tandem, a highly desirable requisite for developing effective PCa therapeutics. 

In recent years, the need to exploit digitized document data has been increasing. In this paper, we address the problem of parsing digitized Vietnamese paper documents. The digitized Vietnamese documents are mainly in the form of scanned images with diverse layouts and special characters introducing many challenges. To this end, we first collect the UIT-DODV dataset, a novel Vietnamese document image dataset that includes scientific papers in Vietnamese derived from different scientific conferences. We compile both images that were converted from PDF and scanned by a smartphone in addition a physical scanner that poses many new challenges. Additionally, we further leverage the state-of-the-art object detector along with the fused loss function to efficiently parse the Vietnamese paper documents. Extensive experiments conducted on the UIT-DODV dataset provide a comprehensive evaluation and insightful analysis.