A Monetary Theory with Non-Degenerate Distributions

Dispersion of money balances among individuals is the basis for a range of policies but it has been abstracted from in monetary theory for tractability reasons. In this paper, we fill in this gap by constructing a tractable search model of money with a non-degenerate distribution of money holdings. We assume search to be directed in the sense that buyers know the terms of trade before visiting particular sellers. Directed search makes the monetary steady state block recursive in the sense that individuals' policy functions, value functions and the market tightness function are all independent of the distribution of individuals over money balances, although the distribution affects the aggregate activity by itself. Block recursivity enables us to characterize the equilibrium analytically. By adapting lattice-theoretic techniques, we characterize individuals' policy and value functions, and show that these functions satisfy the standard conditions of optimization. We prove that a unique monetary steady state exists. Moreover, we provide conditions under which the steady-state distribution of buyers over money balances is non-degenerate and analyze the properties of this distribution.Money; Distribution; Search; Lattice-Theoretic

A Monetary Theory with Non-Degenerate Distributions

Dispersion of money balances among individuals is the basis for a range of policies but it has been abstracted from in monetary theory for tractability reasons. In this paper, we fill in this gap by constructing a tractable search model of money with a non-degenerate distribution of money holdings. We assume search to be directed in the sense that buyers know the terms of trade before visiting particular sellers. Directed search makes the monetary steady state block recursive in the sense that individuals’ policy functions, value functions and the market tightness function are all independent of the distribution of individuals over money balances, although the distribution affects the aggregate activity by itself. Block recursivity enables us to characterize the equilibrium analytically. By adapting lattice-theoretic techniques, we characterize individuals’ policy and value functions, and show that these functions satisfy the standard conditions of optimization. We prove that a unique monetary steady state exists. Moreover, we provide conditions under which the steady-state distribution of buyers over money balances is non-degenerate and analyze the properties of this distribution.Money; Distribution; Search; Lattice-Theoretic

A Monetary Theory with Non-Degenerate Distributions

Dispersion of money balances among individuals is the basis for a range of policies but it has been abstracted from in monetary theory for tractability reasons. In this paper, we fill in this gap by constructing a tractable search model of money with a non-degenerate distribution of money holdings. We assume search to be directed in the sense that buyers know the terms of trade before visiting particular sellers. Directed search makes the monetary steady state block recursive in the sense that individuals' policy functions, value functions and the market tightness function are all independent of the distribution of individuals over money balances, although the distribution affects the aggregate activity by itself. Block recursivity enables us to characterize the equilibrium analytically. By adapting lattice-theoretic techniques, we characterize individuals' policy and value functions, and show that these functions satisfy the standard conditions of optimization. We prove that a unique monetary steady state exists. Moreover, we provide conditions under which the steady-state distribution of buyers over money balances is non-degenerate and analyze the properties of this distribution.Search, Distribution, Money, Lattice-Theoretic

A Transformer-Based Substitute Recommendation Model Incorporating Weakly Supervised Customer Behavior Data

The substitute-based recommendation is widely used in E-commerce to provide better alternatives to customers. However, existing research typically uses the customer behavior signals like co-view and view-but-purchase-another to capture the substitute relationship. Despite its intuitive soundness, we find that such an approach might ignore the functionality and characteristics of products. In this paper, we adapt substitute recommendation into language matching problem by taking product title description as model input to consider product functionality. We design a new transformation method to de-noise the signals derived from production data. In addition, we consider multilingual support from the engineering point of view. Our proposed end-to-end transformer-based model achieves both successes from offline and online experiments. The proposed model has been deployed in a large-scale E-commerce website for 11 marketplaces in 6 languages. Our proposed model is demonstrated to increase revenue by 19% based on an online A/B experiment.Comment: 6 pages, 3 figures, 5 tables, accepted in 21st IEEE International Conference on Machine Learning and Application

Development of an indirect enzyme-linked immunosorbent assay (ELISA) assay based on a recombinant truncated VP2 (tVP2) protein for the detection of canine parvovirus antibodies

By removing the N-terminal hydrophobic sequence, truncated VP2 (tVP2) genes were cloned into the pET-32a (+) plasmid and subsequently expressed as His fusion proteins. The purified recombinant tVP2 proteins were specific to canine parvovirus (CPV), and one of them was used in an indirect enzyme-linked immunosorbent assay (ELISA) for the detection of CPV antibodies. The minimum detection limit of this method was 1:1280. There was good agreement between tVP2-based indirect ELISA and the commercially available diagnostic kit. The results suggest that the recombinant tVP2 protein-based ELISA could be used to detect CPV antibodies.Key words: Canine parvovirus, recombinant truncated VP2 (tVP2), enzyme-linked immunosorbent assay (ELISA), antibody detection

Tuning the nonlinear optical absorption of reduced graphene oxide by chemical reduction

Reduced graphene oxides with varying degrees of reduction have been produced by hydrazine reduction of graphene oxide. The linear and nonlinear optical properties of both graphene oxide as well as the reduced graphene oxides have been measured by single beam Z-scan measurement in the picosecond region. The results reveal both saturable absorption and two-photon absorption, strongly dependent on the intensity of the pump pulse: saturable absorption occurs at lower pump pulse intensity (~1.5 GW/cm2 saturation intensity) whereas two-photon absorption dominates at higher intensities (≥5.7 GW/cm2). Intriguingly, we find that the two-photon absorption coefficient (from 1.5 cm/GW to 4.5cm/GW) and the saturation intensity (from 1 GW/cm2 to 2 GW/cm2) vary with chemical reduction, which is ascribed to the varying concentrations of sp2 domains and sp2 clusters in the reduced graphene oxides. Our results not only provide an insight into the evolution of the nonlinear optical coefficient in reduced graphene oxide, but also suggest that chemical engineering techniques may usefully be applied to tune the nonlinear optical properties of various nano-materials, including atomically thick graphene sheets

Phase-Specific Augmented Reality Guidance for Microscopic Cataract Surgery Using Long-Short Spatiotemporal Aggregation Transformer

Phacoemulsification cataract surgery (PCS) is a routine procedure conducted using a surgical microscope, heavily reliant on the skill of the ophthalmologist. While existing PCS guidance systems extract valuable information from surgical microscopic videos to enhance intraoperative proficiency, they suffer from non-phasespecific guidance, leading to redundant visual information. In this study, our major contribution is the development of a novel phase-specific augmented reality (AR) guidance system, which offers tailored AR information corresponding to the recognized surgical phase. Leveraging the inherent quasi-standardized nature of PCS procedures, we propose a two-stage surgical microscopic video recognition network. In the first stage, we implement a multi-task learning structure to segment the surgical limbus region and extract limbus region-focused spatial feature for each frame. In the second stage, we propose the long-short spatiotemporal aggregation transformer (LS-SAT) network to model local fine-grained and global temporal relationships, and combine the extracted spatial features to recognize the current surgical phase. Additionally, we collaborate closely with ophthalmologists to design AR visual cues by utilizing techniques such as limbus ellipse fitting and regional restricted normal cross-correlation rotation computation. We evaluated the network on publicly available and in-house datasets, with comparison results demonstrating its superior performance compared to related works. Ablation results further validated the effectiveness of the limbus region-focused spatial feature extractor and the combination of temporal features. Furthermore, the developed system was evaluated in a clinical setup, with results indicating remarkable accuracy and real-time performance. underscoring its potential for clinical applications

A novel type 2 diabetes risk allele increases the promoter activity of the muscle-specific small ankyrin 1 gene

Genome-wide association studies have identified Ankyrin-1 (ANK1) as a common type 2 diabetes (T2D) susceptibility locus. However, the underlying causal variants and functional mechanisms remain unknown. We screened for 8 tag single nucleotide polymorphisms (SNPs) in ANK1 between 2 case-control studies. Genotype analysis revealed significant associations of 3 SNPs, rs508419 (first identified here), rs515071, and rs516946 with T2D (P 0.80); subsequent analysis indicated that the CCC haplotype associated with increased T2D susceptibility (OR 1.447, P < 0.001). Further mapping showed that rs508419 resides in the muscle-specific ANK1 gene promoter. Allele-specific mRNA and protein level measurements confirmed association of the C allele with increased small ANK1 (sAnk1) expression in human skeletal muscle (P = 0.018 and P < 0.001, respectively). Luciferase assays showed increased rs508419-C allele transcriptional activity in murine skeletal muscle C2C12 myoblasts, and electrophoretic mobility-shift assays demonstrated altered rs508419 DNA-protein complex formation. Glucose uptake was decreased with excess sAnk1 expression upon insulin stimulation. Thus, the ANK1 rs508419-C T2D-risk allele alters DNA-protein complex binding leading to increased promoter activity and sAnk1 expression; thus, increased sAnk1 expression in skeletal muscle might contribute to T2D susceptibility