Mechanism Design of Fashion Virtual Enterprise under Monitoring Strategy

published_or_final_versio

Mode-Based Classifier: A Robust and Flexible Discriminant Analysis for High-Dimensional Data

This file available on this institutional repository is a preprint. It has not been certified by peer review. It is freely available at http://www3.stat.sinica.edu.tw/ss_newpaper/SS-2023-0014_na.pdf.Supplementary Materials: In the supplementary materials, we present additional results for simulation examples and real data analysis, and provide the technical results of Theorems 1-3.High-dimensional classification is both challenging and of interest in numerous applications. Componentwise distance-based classifiers, which utilize partial information with known categories, such as mean, median and quantiles, provide a convenient way. However, when the input features are heavy-tailed or contain outliers, performance of the centroid classifier can be poor. Beyond that, it frequently occurs that a population consists of two or more subpopulations, the mean, median and quantiles in this scenario fail to capture such a structure that can be instead preserved by mode, which is an appealing measure of considerable significance but might be neglected. This paper thus introduces and investigates componentwise mode-based classifiers that can reveal important structures missed by existing distance-based classifiers. We explore several strategies for defining the family of mode-based classifiers, including the unimodal classifiers, the multimodal classifier and the quantilemode classifier. The unimodal classifiers are proposed based on componentwise unimodal distance and kernel mode estimation, and the multimodal classifier is constructed by identifying all the local modes of a distribution according to a novel introduced algorithm. We establish the asymptotic properties of these methods and demonstrate through simulation studies and three real datasets that the mode-based classifiers compare favorably to the current state-of-art methods.The research of W. Xiong was supported in part by NSFC grants 12001101 and the Fundamental Research Funds for the Central Universities in UIBE CXTD14-05

Space-Variant Gabor Decomposition for Filtering 3D Medical Images

This is an experimental paper in which we introduce the possibility to analyze and to synthesize 3D medical images by using multivariate Gabor frames with Gaussian windows. Our purpose is to apply a space-variant filter-like operation in the space-frequency domain to correct medical images corrupted by different types of acquisitions errors. The Gabor frames are constructed with Gaussian windows sampled on non-separable lattices for a better packing of the space-frequency plane. An implementable solution for 3D-Gabor frames with non-separable lattice is given and numerical tests on simulated data are presented.Austrian Science Fund (FWF) P2751

Common-path interferometric label-free protein sensing with resonant dielectric nanostructures

Research toward photonic biosensors for point-of-care applications and personalized medicine is driven by the need for high-sensitivity, low-cost, and reliable technology. Among the most sensitive modalities, interferometry offers particularly high performance, but typically lacks the required operational simplicity and robustness. Here, we introduce a common-path interferometric sensor based on guided-mode resonances to combine high performance with inherent stability. The sensor exploits the simultaneous excitation of two orthogonally polarized modes, and detects the relative phase change caused by biomolecular binding on the sensor surface. The wide dynamic range of the sensor, which is essential for fabrication and angle tolerance, as well as versatility, is controlled by integrating multiple, tuned structures in the field of view. This approach circumvents the trade-off between sensitivity and dynamic range, typical of other phase-sensitive modalities, without increasing complexity. Our sensor enables the challenging label-free detection of procalcitonin, a small protein (13 kDa) and biomarker for infection, at the clinically relevant concentration of 1 pg mL−1, with a signal-to-noise ratio of 35. This result indicates the utility for an exemplary application in antibiotic guidance, and opens possibilities for detecting further clinically or environmentally relevant small molecules with an intrinsically simple and robust sensing modality

Spectroscopic investigation of quantum confinement effects in ion implanted silicon-on-sapphire films

Crystalline Silicon-on-Sapphire (SOS) films were implanted with boron (B$^+$) and phosphorous (P$^+$) ions. Different samples, prepared by varying the ion dose in the range $10^{14}$ to 5 x $10^{15}$ and ion energy in the range 150-350 keV, were investigated by the Raman spectroscopy, photoluminescence (PL) spectroscopy and glancing angle x-ray diffraction (GAXRD). The Raman results from dose dependent B$^+$ implanted samples show red-shifted and asymmetrically broadened Raman line-shape for B$^+$ dose greater than $10^{14}$ ions cm$^{-2}$. The asymmetry and red shift in the Raman line-shape is explained in terms of quantum confinement of phonons in silicon nanostructures formed as a result of ion implantation. PL spectra shows size dependent visible luminescence at $\sim$ 1.9 eV at room temperature, which confirms the presence of silicon nanostructures. Raman studies on P$^+$ implanted samples were also done as a function of ion energy. The Raman results show an amorphous top SOS surface for sample implanted with 150 keV P$^+$ ions of dose 5 x $10^{15}$ ions cm$^{-2}$. The nanostructures are formed when the P$^+$ energy is increased to 350 keV by keeping the ion dose fixed. The GAXRD results show consistency with the Raman results.Comment: 9 Pages, 6 Figures and 1 Table, \LaTex format To appear in SILICON(SPRINGER

On staying grounded and avoiding Quixotic dead ends

The 15 articles in this special issue on The Representation of Concepts illustrate the rich variety of theoretical positions and supporting research that characterize the area. Although much agreement exists among contributors, much disagreement exists as well, especially about the roles of grounding and abstraction in conceptual processing. I first review theoretical approaches raised in these articles that I believe are Quixotic dead ends, namely, approaches that are principled and inspired but likely to fail. In the process, I review various theories of amodal symbols, their distortions of grounded theories, and fallacies in the evidence used to support them. Incorporating further contributions across articles, I then sketch a theoretical approach that I believe is likely to be successful, which includes grounding, abstraction, flexibility, explaining classic conceptual phenomena, and making contact with real-world situations. This account further proposes that (1) a key element of grounding is neural reuse, (2) abstraction takes the forms of multimodal compression, distilled abstraction, and distributed linguistic representation (but not amodal symbols), and (3) flexible context-dependent representations are a hallmark of conceptual processing

Experimental investigation of classical and quantum correlations under decoherence

It is well known that many operations in quantum information processing depend largely on a special kind of quantum correlation, that is, entanglement. However, there are also quantum tasks that display the quantum advantage without entanglement. Distinguishing classical and quantum correlations in quantum systems is therefore of both fundamental and practical importance. In consideration of the unavoidable interaction between correlated systems and the environment, understanding the dynamics of correlations would stimulate great interest. In this study, we investigate the dynamics of different kinds of bipartite correlations in an all-optical experimental setup. The sudden change in behaviour in the decay rates of correlations and their immunity against certain decoherences are shown. Moreover, quantum correlation is observed to be larger than classical correlation, which disproves the early conjecture that classical correlation is always greater than quantum correlation. Our observations may be important for quantum information processing.Comment: 7 pages, 4 figures, to appear in Nature Communication

Serotonin tranporter methylation and response to cognitive behaviour therapy in children with anxiety disorders

Anxiety disorders that are the most commonly occurring psychiatric disorders in childhood, are associated with a range of social and educational impairments and often continue into adulthood. Cognitive behaviour therapy (CBT) is an effective treatment option for the majority of cases, although up to 35-45% of children do not achieve remission. Recent research suggests that some genetic variants may be associated with a more beneficial response to psychological therapy. Epigenetic mechanisms such as DNA methylation work at the interface between genetic and environmental influences. Furthermore, epigenetic alterations at the serotonin transporter (SERT) promoter region have been associated with environmental influences such as stressful life experiences. In this study, we measured DNA methylation upstream of SERT in 116 children with an anxiety disorder, before and after receiving CBT. Change during treatment in percentage DNA methylation was significantly different in treatment responders vs nonresponders. This effect was driven by one CpG site in particular, at which responders increased in methylation, whereas nonresponders showed a decrease in DNA methylation. This is the first study to demonstrate differences in SERT methylation change in association with response to a purely psychological therapy. These findings confirm that biological changes occur alongside changes in symptomatology following a psychological therapy such as CBT

Hybrid Mechanical Systems

We discuss hybrid systems in which a mechanical oscillator is coupled to another (microscopic) quantum system, such as trapped atoms or ions, solid-state spin qubits, or superconducting devices. We summarize and compare different coupling schemes and describe first experimental implementations. Hybrid mechanical systems enable new approaches to quantum control of mechanical objects, precision sensing, and quantum information processing.Comment: To cite this review, please refer to the published book chapter (see Journal-ref and DOI). This v2 corresponds to the published versio

Time Varying Quantile Lasso

In the present paper we study the dynamics of penalization parameter λ of the least absolute shrinkage and selection operator (Lasso) method proposed by Tibshirani (1996) and extended into quantile regression context by Li and Zhu (2008). The dynamic behaviour of the parameter λ can be observed when the model is assumed to vary over time and therefore the fitting is performed with the use of moving windows. The proposal of investigating time series of λ and its dependency on model characteristics was brought into focus by Hardle et al. (2016), which was a foundation of FinancialRiskMeter (http://frm.wiwi.hu-berlin.de). Following the ideas behind the two aforementioned projects, we use the derivation of the formula for the penalization parameter λ as a result of the optimization problem. This reveals three possible effects driving λ; variance of the error term, correlation structure of the covariates and number of nonzero coefficients of the model. Our aim is to disentangle these three effect and investigate their relationship with the tuning parameter λ, which is conducted by a simulation study. After dealing with the theoretical impact of the three model characteristics on λ, empirical application is performed and the idea of implementing the parameter λ into a systemic risk measure is presented. The codes used to obtain the results included in this work are available on http://quantlet.de/d3/ia/