Quasi-convexity in mixtures for generalized rank-dependent functions

Quasi-convexity in probabilistic mixtures is a common and useful property in decision analysis. We study a general class of non-monotone mappings, called the generalized rank-dependent functions, which include the preference models of expected utilities, dual utilities, and rank-dependent utilities as special cases, as well as signed Choquet integrals used in risk management. As one of our main results, quasi-convex (in mixtures) signed Choquet integrals precisely include two parts: those that are convex (in mixtures) and the class of scaled quantile-spread mixtures, and this result leads to a full characterization of quasi-convexity for generalized rank-dependent functions. Seven equivalent conditions for quasi-convexity in mixtures are obtained for dual utilities and signed Choquet integrals. We also illustrate a conflict between convexity in mixtures and convexity in risk pooling among constant-additive mappings

The research on the evolution of long-term intercompany supply chain collaboration and its influence factors based on the life cycle theory

In today’s increasingly fierce competitive marketing environment, supply chain collaboration is employed by more and more companies as core competitiveness to obtain competitive advantage. Supply chain collaboration is considered to be dynamic. The dissertation researches on the evolution of long-term intercompany supply chain collaboration and its influence factors by taking long-term intercompany collaborative relationships as the unit of analysis. The life cycle theory is introduced to study supply chain collaboration. The dissertation mainly explores the evolution of supply chain collaboration from the life cycle perspective and investigates the way in which influence factors affect the maintenance of supply chain collaboration. Two real cases of supply chain collaboration illustrate the analysis and findings of the dissertation. The life cycle model of long-term intercompany supply chain collaboration is built. The study points out that long-term intercompany supply chain collaboration would experience four stages that are introduction, adjustment, development and maturity. Characteristics of each stage are affected by strategies and management that companies applied. Influence factors would affect the level of collaboration and the re-willingness of collaboration of collaborators, and then impact the maintenance of supply chain collaboration. The dissertation also puts forward the viewpoint that the relative importance of influence factors is different at various stages

Risk Aversion and Insurance Propensity

We provide a new foundation of risk aversion by showing that the propension to exploit insurance opportunities fully describes this attitude. Our foundation, which applies to any probabilistically sophisticated preference, well accords with the commonly held prudential interpretation of risk aversion that dates back to the seminal works of Arrow (1963) and Pratt (1964). In our main results, we first characterize the Arrow-Pratt risk aversion in terms of propension to full insurance and the stronger notion of risk aversion of Rothschild and Stiglitz (1970) in terms of propension to partial insurance. We then extend the analysis to comparative risk aversion by showing that the notion of Yaari (1969) corresponds to comparative propension to full insurance, while the stronger notion of Ross (1981) corresponds to comparative propension to partial insurance

Learning A Coarse-to-Fine Diffusion Transformer for Image Restoration

Recent years have witnessed the remarkable performance of diffusion models in various vision tasks. However, for image restoration that aims to recover clear images with sharper details from given degraded observations, diffusion-based methods may fail to recover promising results due to inaccurate noise estimation. Moreover, simple constraining noises cannot effectively learn complex degradation information, which subsequently hinders the model capacity. To solve the above problems, we propose a coarse-to-fine diffusion Transformer (C2F-DFT) for image restoration. Specifically, our C2F-DFT contains diffusion self-attention (DFSA) and diffusion feed-forward network (DFN) within a new coarse-to-fine training scheme. The DFSA and DFN respectively capture the long-range diffusion dependencies and learn hierarchy diffusion representation to facilitate better restoration. In the coarse training stage, our C2F-DFT estimates noises and then generates the final clean image by a sampling algorithm. To further improve the restoration quality, we propose a simple yet effective fine training scheme. It first exploits the coarse-trained diffusion model with fixed steps to generate restoration results, which then would be constrained with corresponding ground-truth ones to optimize the models to remedy the unsatisfactory results affected by inaccurate noise estimation. Extensive experiments show that C2F-DFT significantly outperforms diffusion-based restoration method IR-SDE and achieves competitive performance compared with Transformer-based state-of-the-art methods on $3$ tasks, including deraining, deblurring, and real denoising.Comment: 9 pages, 8 figure

3ET: Efficient Event-based Eye Tracking using a Change-Based ConvLSTM Network

This paper presents a sparse Change-Based Convolutional Long Short-Term Memory (CB-ConvLSTM) model for event-based eye tracking, key for next-generation wearable healthcare technology such as AR/VR headsets. We leverage the benefits of retina-inspired event cameras, namely their low-latency response and sparse output event stream, over traditional frame-based cameras. Our CB-ConvLSTM architecture efficiently extracts spatio-temporal features for pupil tracking from the event stream, outperforming conventional CNN structures. Utilizing a delta-encoded recurrent path enhancing activation sparsity, CB-ConvLSTM reduces arithmetic operations by approximately 4.7× without losing accuracy when tested on a v2e-generated event dataset of labeled pupils. This increase in efficiency makes it ideal for real-time eye tracking in resource-constrained devices. The project code and dataset are openly available at https://github.com/qinche106/cb-convlstm-eyetracking

Global repair bandwidth cost optimization of generalized regenerating codes in clustered distributed storage systems

In clustered distributed storage systems (CDSSs), one of the main design goals is minimizing the transmission cost during the failed storage nodes repairing. Generalized regenerating codes (GRCs) are proposed to balance the intra-cluster repair bandwidth and the inter-cluster repair bandwidth for guaranteeing data availability. The trade-off performance of GRCs illustrates that, it can reduce storage overhead and inter-cluster repair bandwidths simultaneously. However, in practical big data storage scenarios, GRCs cannot give an effective solution to handle the heterogeneity of bandwidth costs among different clusters for node failures recovery. This paper proposes an asymmetric bandwidth allocation strategy (ABAS) of GRCs for the inter-cluster repair in heterogeneous CDSSs. Furthermore, an upper bound of the achievable capacity of ABAS is derived based on the information flow graph (IFG), and the constraints of storage capacity and intra-cluster repair bandwidth are also elaborated. Then, a metric termed global repair bandwidth cost (GRBC), which can be minimized regarding of the inter-cluster repair bandwidths by solving a linear programming problem, is defined. The numerical results demonstrate that, maintaining the same data availability and storage overhead, the proposed ABAS of GRCs can effectively reduce the GRBC compared to the traditional symmetric bandwidth allocation schemes

Three-dimensional scattering from uniaxial objects with a smooth boundary using a multiple infinitesimal dipole method

The formulations for three-dimensional (3D) scattering from uniaxial objects with a smooth boundary using a multiple infinitesimal dipole method (MIDM) are introduced. The proposed technique uses two sets of infinitesimal dipole triplets (IDTs), including three co-located orthogonally polarized electric infinitesimal dipoles, distributed inside and outside of a scatterer to construct simulated fields. The dyadic Green’s functions of uniaxial materials are deployed in the MIDM so as to obtain the simulated fields. The singularity issues in using the uniaxial dyadic Green’s functions, which cannot be solved analytically so far for a general uniaxial medium, can be easily eliminated by using the proposed MIDM. In comparison to the traditional single-layered distribution scheme of IDTs, the proposed multiple-layered distribution scheme can handle the scattering from uniaxial objects accurately and efficiently. Several numerical examples are presented to study bistatic radar cross section (RCS) responses under different scenarios. Excellent agreement is achieved by comparing numerical results with those obtained from commercial software packages, while the simulation performance including CPU time and required memory is drastically improved by using the MIDM when computing a general uniaxial material or a relatively larger object. The proposed technique has its merits on simplicity, conciseness and fast computation in comparison to existing numerical methods

Seasonal and intra-seasonal thermocline variability in the central South China Sea

Geophysical Research Letters, American Geophysical UnionSeasonal and intraseasonal variability of thermocline and relative surface height in the central South China Sea (SCS) are investigated using time series data of temperature from three buoys and sea surface height anomaly data from TOPEX/POSEIDON and ERS-1/ERS-2 satellites( T/P-ERS) from Feb. 1998 through Mar. 1999. We found that the thermocline becomesde eper and thinner in winter, owing to a great loss of the heat on the sea surface. Thisf eature is more evident in the northern than the southern part of the central SCS. The intraseasonal variation of the thermocline ismain ly controlled by the geostrophic vorticity and is out-of-phase with sea surface height (SSH). Furthermore, we find a double-thermocline phenomenon occurs in the SCS: In spring, owing to maximum net downward heat flux at the surface, with the new thermocline appearing above 80 m and the old thermocline keeping under 80 m deep

Pair-barcode high-throughput sequencing for large-scale multiplexed sample analysis

<p>Abstract</p> <p>Background</p> <p>The multiplexing becomes the major limitation of the next-generation sequencing (NGS) in application to low complexity samples. Physical space segregation allows limited multiplexing, while the existing barcode approach only permits simultaneously analysis of up to several dozen samples.</p> <p>Results</p> <p>Here we introduce pair-barcode sequencing (PBS), an economic and flexible barcoding technique that permits parallel analysis of large-scale multiplexed samples. In two pilot runs using SOLiD sequencer (Applied Biosystems Inc.), 32 independent pair-barcoded miRNA libraries were simultaneously discovered by the combination of 4 unique forward barcodes and 8 unique reverse barcodes. Over 174,000,000 reads were generated and about 64% of them are assigned to both of the barcodes. After mapping all reads to pre-miRNAs in miRBase, different miRNA expression patterns are captured from the two clinical groups. The strong correlation using different barcode pairs and the high consistency of miRNA expression in two independent runs demonstrates that PBS approach is valid.</p> <p>Conclusions</p> <p>By employing PBS approach in NGS, large-scale multiplexed pooled samples could be practically analyzed in parallel so that high-throughput sequencing economically meets the requirements of samples which are low sequencing throughput demand.</p