THE EFFECTS OF EXCHANGE RATE CHANGES ON THE CO-MOVEMENT OF EQUITY MARKETS

This paper analyzes the co-movement of the US equity market and 10 markets in Asia and Oceania (i.e., referred to as domestic markets). We find that the daily returns of the ten emerging markets are significantly correlated with the performance of US market in the previous trading day. Also, we analyze the contemporaneous change in the US/domestic market exchange rate, and how it affects this co-movement. We find that the correlation between the US market and domestic markets is positively related to the net-trade balance that exists between these countries. Countries that tend to net-export to the US are affected more positively by the strengthening of the US dollar compared to the domestic currency

Recovering stellar population parameters via two full-spectrum fitting algorithms in the absence of model uncertainties

Using mock spectra based on Vazdekis/MILES library fitted within the wavelength region 3600-7350\AA, we analyze the bias and scatter on the resulting physical parameters induced by the choice of fitting algorithms and observational uncertainties, but avoid effects of those model uncertainties. We consider two full-spectrum fitting codes: pPXF and STARLIGHT, in fitting for stellar population age, metallicity, mass-to-light ratio, and dust extinction. With pPXF we find that both the bias in the population parameters and the scatter in the recovered logarithmic values follows the expected trend. The bias increases for younger ages and systematically makes recovered ages older, $M_*/L_r$ larger and metallicities lower than the true values. For reference, at S/N=30, and for the worst case ($t=10^8$yr), the bias is 0.06 dex in $M_*/L_r$, 0.03 dex in both age and [M/H]. There is no significant dependence on either E(B-V) or the shape of the error spectrum. Moreover, the results are consistent for both our 1-SSP and 2-SSP tests. With the STARLIGHT algorithm, we find trends similar to pPXF, when the input E(B-V)<0.2 mag. However, with larger input E(B-V), the biases of the output parameter do not converge to zero even at the highest S/N and are strongly affected by the shape of the error spectra. This effect is particularly dramatic for youngest age, for which all population parameters can be strongly different from the input values, with significantly underestimated dust extinction and [M/H], and larger ages and $M_*/L_r$. Results degrade when moving from our 1-SSP to the 2-SSP tests. The STARLIGHT convergence to the true values can be improved by increasing Markov Chains and annealing loops to the "slow mode". For the same input spectrum, pPXF is about two order of magnitudes faster than STARLIGHT's "default mode" and about three order of magnitude faster than STARLIGHT's "slow mode".Comment: Accepted for publication in MNRAS. 17 pages, 17 figure

A multi-layer refined network model for the identification of essential proteins

The identification of essential proteins in protein-protein interaction networks (PINs) can help to discover drug targets and prevent disease. In order to improve the accuracy of the identification of essential proteins, researchers attempted to obtain a refined PIN by combining multiple biological information to filter out some unreliable interactions in the PIN. Unfortunately, such approaches drastically reduce the number of nodes in the PIN after multiple refinements and result in a sparser PIN. It makes a considerable portion of essential proteins unidentifiable. In this paper, we propose a multi-layer refined network (MR-PIN) that addresses this problem. Firstly, four refined networks are constructed by respectively integrating different biological information into the static PIN to form a multi-layer heterogeneous network. Then scores of proteins in each network layer are calculated by the existing node ranking method, and the importance score of a protein in the MR-PIN is evaluated in terms of the geometric mean of its scores in all layers. Finally, all nodes are sorted by their importance scores to determine their essentiality. To evaluate the effectiveness of the multi-layer refined network model, we apply 16 node ranking methods on the MR-PIN, and compare the results with those on the SPIN, DPIN and RDPIN. Then the predictive performances of these ranking methods are validated in terms of the identification number of essential protein at top100 - top600, sensitivity, specificity, positive predictive value, negative predictive value, F-measure, accuracy, Jackknife, ROCAUC and PRAUC. The experimental results show that the MR-PIN is superior to the existing refined PINs in the identification accuracy of essential proteins

Statistical‐based approach for driving style recognition using Bayesian probability with kernel density estimation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166283/1/itr2bf00581.pd

Safety and Effectiveness of Using Disposable Ultrasonic Shears to Coagulate 5–7 mm Blood Vessels: Protocol for a Prospective, Multicenter, Randomized, Parallel Controlled, Non-Inferiority Clinical Trial

BACKGROUND: The ultrasonic scalpel is widely used during surgery. It is safe and effective to close the pulmonary artery branch vessels of 7 mm or below with an ultrasonic energy device as reported. However, there have been no multicenter randomized clinical trial to assess the safety and effectiveness of using ultrasonic scalpel to coagulate 5-7 mm blood vessels in thoracic surgery. METHODS: This is a prospective, multicenter, randomized, parallel controlled, non-inferiority clinical trial. A total of 144 eligible patients planning to undergo lung or esophageal surgery will be randomly allocated to the experimental group and the control group. The investigational product (Disposable Ultrasonic Shears manufactured by Reach Surgical, Inc.) and the control product (Harmonic Ace + 7, 5 mm Diameter Shears with Advanced Hemostasis) will be used in each group. The primary endpoint is the success rate of coagulating target blood vessels during surgery. Secondary endpoints include postoperative rebleeding, intraoperative bleeding volume, drainage volume, surgical duration, etc. Postoperative follow-up before and after discharge will be performed. DISCUSSION: This clinical trial aims to evaluate the safety and effectiveness of using the investigational product (Disposable Ultrasonic Shears manufactured by Reach Surgical, Inc.) and that of the control product (Harmonic Ace + 7, 5 mm Diameter Shears with Advanced Hemostasis) to coagulate 5-7 mm blood vessels in thoracic surgery. TRIAL REGISTRATION: ClinicalTrials.gov: NCT06002737. The trial was prospectively registered on 16 August 2023, https://www. CLINICALTRIALS: gov/study/NCT06002737

EqCo: Equivalent Rules for Self-supervised Contrastive Learning

In this paper, we propose a method, named EqCo (Equivalent Rules for Contrastive Learning), to make self-supervised learning irrelevant to the number of negative samples in InfoNCE-based contrastive learning frameworks. Inspired by the InfoMax principle, we point that the margin term in contrastive loss needs to be adaptively scaled according to the number of negative pairs in order to keep steady mutual information bound and gradient magnitude. EqCo bridges the performance gap among a wide range of negative sample sizes, so that we can use only a few negative pairs (e.g. 16 per query) to perform self-supervised contrastive training on large-scale vision datasets like ImageNet, while with almost no accuracy drop. This is quite a contrast to the widely used large batch training or memory bank mechanism in current practices. Equipped with EqCo, our simplified MoCo (SiMo) achieves comparable accuracy with MoCo v2 on ImageNet (linear evaluation protocol) while only involves 4 negative pairs per query instead of 65536, suggesting that large quantities of negative samples might not be a critical factor in InfoNCE loss

A Survey of Network Protocol Fuzzing: Model, Techniques and Directions

As one of the most successful and effective software testing techniques in recent years, fuzz testing has uncovered numerous bugs and vulnerabilities in modern software, including network protocol software. In contrast to other fuzzing targets, network protocol software exhibits its distinct characteristics and challenges, introducing a plethora of research questions that need to be addressed in the design and implementation of network protocol fuzzers. While some research work has evaluated and systematized the knowledge of general fuzzing techniques at a high level, there is a lack of similar analysis and summarization for fuzzing research specific to network protocols. This paper offers a comprehensive exposition of network protocol software's fuzzing-related features and conducts a systematic review of some representative advancements in network protocol fuzzing since its inception. We summarize state-of-the-art strategies and solutions in various aspects, propose a unified protocol fuzzing process model, and introduce the techniques involved in each stage of the model. At the same time, this paper also summarizes the promising research directions in the landscape of protocol fuzzing to foster exploration within the community for more efficient and intelligent modern network protocol fuzzing techniques

Recovering Stellar Population Parameters via Two Full-Spectrum Fitting Algorithms in the Absence of Model Uncertainties

Using mock spectra based on Vazdekis/MILES library fitted within the wavelength region 3600–7350 Å, we analyse the bias and scatter on the resulting physical parameters induced by the choice of fitting algorithms and observational uncertainties, but avoid effects of those model uncertainties. We consider two full-spectrum fitting codes: PPXF and STARLIGHT, in fitting for stellar population age, metallicity, mass-to-light ratio, and dust extinction. With PPXF, we find that both the bias μ in the population parameters and the scatter σ in the recovered logarithmic values follows the expected trend μ ∝ σ ∝ 1/(S/N)⁠. The bias increases for younger ages and systematically makes recovered ages older, M*/Lr larger and metallicities lower than the true values. For reference, at S/N = 30, and for the worst case (t = 108 yr), the bias is 0.06 dex in M*/Lr, 0.03 dex in both age and [M/H]. There is no significant dependence on either E(B − V) or the shape of the error spectrum. Moreover, the results are consistent for both our 1-SSP (simple stellar population) and 2-SSP tests. With the STARLIGHT algorithm, we find trends similar to PPXF, when the input E(B − V) \u3c 0.2 mag. However, with larger input E(B − V), the biases of the output parameter do not converge to zero even at the highest S/N and are strongly affected by the shape of the error spectra. This effect is particularly dramatic for youngest age (t = 108 yr), for which all population parameters can be strongly different from the input values, with significantly underestimated dust extinction and [M/H], and larger ages and M*/Lr. Results degrade when moving from our 1-SSP to the 2-SSP tests. The STARLIGHT convergence to the true values can be improved by increasing Markov Chains and annealing loops to the ‘slow mode’. For the same input spectrum, PPXF is about two order of magnitudes faster than STARLIGHT’s ‘default mode’ and about three order of magnitude faster than STARLIGHT’s ‘slow mode’

Coordination Control of a Dual-Arm Exoskeleton Robot Using Human Impedance Transfer Skills

This paper has developed a coordination control method for a dual-arm exoskeleton robot based on human impedance transfer skills, where the left (master) robot arm extracts the human limb impedance stiffness and position profiles, and then transfers the information to the right (slave) arm of the exoskeleton. A computationally efficient model of the arm endpoint stiffness behavior is developed and a co-contraction index is defined using muscular activities of a dominant antagonistic muscle pair. A reference command consisting of the stiffness and position profiles of the operator is computed and realized by one robot in real-time. Considering the dynamics uncertainties of the robotic exoskeleton, an adaptive-robust impedance controller in task space is proposed to drive the slave arm tracking the desired trajectories with convergent errors. To verify the robustness of the developed approach, a study of combining adaptive control and human impedance transfer control under the presence of unknown interactive forces is conducted. The experimental results of this paper suggest that the proposed control method enables the subjects to execute a coordination control task on a dual-arm exoskeleton robot by transferring the stiffness from the human arm to the slave robot arm, which turns out to be effective