Capacity sharing, product differentiation and welfare

This article constructs a duopoly market with product differentiation and analyses profits, consumer surplus and social welfare under three conditions: (a) two enterprises have sufficient capacity; (b) one enterprise has insufficient capacity, and another enterprise has excess capacity that is not shared; and (c) one enterprise has insufficient capacity, and another enterprise has excess capacity and engages in capacity sharing. Through comparison, the implementation conditions for and effects of capacity sharing and the role of product differentiation are revealed. The results show that capacity sharing helps increase producer surplus and social welfare. Capacity constraints reduce social welfare but can be solved by capacity sharing. Capacity sharing can only be realised when both enterprises are profitable, and the charge for capacity sharing should not be too high or too low. Product differentiation has impacts on output, profit, consumer surplus and social welfare, and these impacts are restricted by the existence of capacity constraints and capacity sharing

P3OP^{3}O: Transferring Visual Representations for Reinforcement Learning via Prompting

It is important for deep reinforcement learning (DRL) algorithms to transfer their learned policies to new environments that have different visual inputs. In this paper, we introduce Prompt based Proximal Policy Optimization ($P^{3}O$), a three-stage DRL algorithm that transfers visual representations from a target to a source environment by applying prompting. The process of $P^{3}O$ consists of three stages: pre-training, prompting, and predicting. In particular, we specify a prompt-transformer for representation conversion and propose a two-step training process to train the prompt-transformer for the target environment, while the rest of the DRL pipeline remains unchanged. We implement $P^{3}O$ and evaluate it on the OpenAI CarRacing video game. The experimental results show that $P^{3}O$ outperforms the state-of-the-art visual transferring schemes. In particular, $P^{3}O$ allows the learned policies to perform well in environments with different visual inputs, which is much more effective than retraining the policies in these environments.Comment: This paper has been accepted to be presented at the upcoming IEEE International Conference on Multimedia & Expo (ICME) in 202

Research on leakage characteristics of working clearances of hydrogen circulation pump

The volumetric efficiency of the hydrogen circulation pump (HCP) is mainly affected by the amount of leakage in working clearances. Studying the leakage characteristics of working clearances is of great significance for optimizing the performance of the HCP. Therefore, this paper developed a three-blade elliptical conjugate rotor HCP, and compared the results of experiments and simulations for different working conditions. On this basis, the flow rate, pressure, and internal flow field changes of radial clearance models and axial clearance models with four different scales of 0.1mm, 0.14mm, 0.18mm, and 0.22 mm were studied. The results indicate that: under four different pressure ratios and rotational speeds, the simulation results using the overlapping grid method showed a maximum difference of 4.17% compared to the experimental results, verifying the reliability of the simulation calculation method; the average flow rate of the HCP is linearly inversely proportional to both the radial clearance and the axial clearance, with a decrease rate of 11.6 Nm3/h and 5.8 Nm3/h as the clearance size increases by 0.04 mm; the radial clearance leakage of the same size is higher than the axial clearance, the leakage value in the radial clearance between the rotors is higher than that between the rotor and the pump casing, and the internal leakage of axial clearance is not evenly distributed, with higher leakage value in the middle area than that in the left and right areas

Rotation Initialization and Stepwise Refinement for Universal LiDAR Calibration

Autonomous systems often employ multiple LiDARs to leverage the integrated advantages, enhancing perception and robustness. The most critical prerequisite under this setting is the estimating the extrinsic between each LiDAR, i.e., calibration. Despite the exciting progress in multi-LiDAR calibration efforts, a universal, sensor-agnostic calibration method remains elusive. According to the coarse-to-fine framework, we first design a spherical descriptor TERRA for 3-DoF rotation initialization with no prior knowledge. To further optimize, we present JEEP for the joint estimation of extrinsic and pose, integrating geometric and motion information to overcome factors affecting the point cloud registration. Finally, the LiDAR poses optimized by the hierarchical optimization module are input to time synchronization module to produce the ultimate calibration results, including the time offset. To verify the effectiveness, we conduct extensive experiments on eight datasets, where 16 diverse types of LiDARs in total and dozens of calibration tasks are tested. In the challenging tasks, the calibration errors can still be controlled within 5cm and 1{\deg} with a high success rate.Comment: 19 pages, 19 figure

Hybrid optimization algorithm for handwritten document enhancement

The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance; however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of the CEC2013 benchmark, the AIWGOA demonstrates notable advantages across various metrics. Subsequently, an evaluation index was employed to assess the enhanced handwritten documents and images, affirming the superior practical application of the AIWGOA compared with other algorithms.Web of Science7833786376

Serology assays used in SARS-CoV-2 seroprevalence surveys worldwide: a systematic review and meta-analysis of assay features, testing algorithms, and performance

Many serological assays to detect SARS-CoV-2 antibodies were developed during the COVID-19 pandemic. Differences in the detection mechanism of SARS-CoV-2 serological assays limited the comparability of seroprevalence estimates for populations being tested. We conducted a systematic review and meta-analysis of serological assays used in SARS-CoV-2 population seroprevalence surveys, searching for published articles, preprints, institutional sources, and grey literature between 1 January 2020, and 19 November 2021. We described features of all identified assays and mapped performance metrics by the manufacturers, third-party head-to-head, and independent group evaluations. We compared the reported assay performance by evaluation source with a mixed-effect beta regression model. A simulation was run to quantify how biased assay performance affects population seroprevalence estimates with test adjustment. Among 1807 included serosurveys, 192 distinctive commercial assays and 380 self-developed assays were identified. According to manufacturers, 28.6% of all commercial assays met WHO criteria for emergency use (sensitivity [Sn.] >= 90.0%, specificity [Sp.] >= 97.0%). However, manufacturers overstated the absolute values of Sn. of commercial assays by 1.0% [0.1, 1.4%] and 3.3% [2.7, 3.4%], and Sp. by 0.9% [0.9, 0.9%] and 0.2% [-0.1, 0.4%] compared to third-party and independent evaluations, respectively. Reported performance data was not sufficient to support a similar analysis for self-developed assays. Simulations indicate that inaccurate Sn. and Sp. can bias seroprevalence estimates adjusted for assay performance; the error level changes with the background seroprevalence. The Sn. and Sp. of the serological assay are not fixed properties, but varying features depending on the testing population. To achieve precise population estimates and to ensure the comparability of seroprevalence, serosurveys should select assays with high performance validated not only by their manufacturers and adjust seroprevalence estimates based on assured performance data. More investigation should be directed to consolidating the performance of self-developed assays

Interfacial energetics reversal strategy for efficient perovskite solar cells

Reducing heterointerface nonradiative recombination is a key challenge for realizing highly efficient perovskite solar cells (PSCs). Motivated by this, a facile strategy is developed via interfacial energetics reversal to functionalize perovskite heterointerface. A surfactant molecule, trichloro[3-(pentafluorophenyl)propyl]silane (TPFS) reverses perovskite surface energetics from intrinsic n-type to p-type, evidently demonstrated by ultraviolet and inverse photoelectron spectroscopies. The reconstructed perovskite surface energetics match well with the upper deposited hole transport layer, realizing an exquisite energy level alignment for accelerating hole extraction across the heterointerface. Meanwhile, TPFS further diminishes surface defect density. As a result, this cooperative strategy leads to greatly minimized nonradiative recombination. PSCs achieve an impressive power conversion efficiency of 25.9% with excellent reproducibility, and a nonradiative recombination-induced qVoc loss of only 57 meV, which is the smallest reported to date in n-i-p structured PSCs

Denervation as a Common Mechanism Underlying Different Pulmonary Vein Isolation Strategies for Paroxysmal Atrial Fibrillation: Evidenced by Heart Rate Variability after Ablation

Backgrounds. Segmental and circumferential pulmonary vein isolations (SPVI and CPVI) have been demonstrated to be effective therapies for paroxysmal atrial fibrillation (PAF). PVI is well established as the endpoint of different ablation techniques, whereas it may not completely account for the long-term success. Methods. 181 drug-refractory symptomatic PAF patients were referred for segmental or circumferential PVI (SPVI = 67; CPVI = 114). Heart rate variability (HRV) was assessed before and after the final ablation. Results. After following up for 62.23±12.75 months, patients underwent 1.41±0.68 procedures in average, and the success rates in SPVI and CPVI groups were comparable. 119 patients were free from AF recurrence (SPVI-S, n=43; CPVI-S, n=76). 56 patients had recurrent episodes (SPVI-R, n=21; CPVI-R, n=35). Either ablation technique decreased HRV significantly. Postablation SDNN and rMSSD were significantly lower in SPVI-S and CPVI-S subgroups than in SPVI-R and CPVI-R subgroups (SPVI-S versus SPVI-R: SDNN 91.8±32.6 versus 111.5±36.2 ms, rMSSD 47.4±32.3 versus 55.2±35.2 ms; CPVI-S versus CPVI-R: SDNN 83.0±35.6 versus 101.0±40.7 ms, rMSSD 41.1±22.9 versus 59.2±44.8 ms; all P<0.05). Attenuation of SDNN and rMSSD remained for 12 months in SPVI-S and CPVI-S subgroups, whereas it recovered earlier in SPVI-R and CPVI-R subgroups. Multivariate logistic regression analysis identified SDNN as the only predictor of long-term success. Conclusions. Beyond PVI, denervation may be a common mechanism underlying different ablation strategies for PAF

Single-cell analysis of chromatin accessibility in the adult mouse brain.

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs-specifically, those identified from a subset of cortical excitatory neurons-are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and human brains