Order flow, information and trading behaviour in foreign exchange and equity markets.

It has been shown in the literature that under asymmetric information, trading process itself is a part of pricing mechanism and order flow is the vehicle of information transmission and has a profound impact on prices. This thesis is composed of three major closely connected parts on order flow economics: (1) exchange rate determination and inter-market order flow effect, (2) market conditions and order flow impact and (3) limit order execution and microstructure factors. The first part of this thesis empirically investigates the price impact of order flow in four major currency markets and the results show that order flow has strong impact on exchange rates in all four markets and over various sampling frequencies. In a new result, inter-market effect is discovered where exchange rate movements in one market can be explained by the order flow in other relevant markets. In terms of forecasting ability, the order flow model out-performs random walk model that has so far beaten all macro-based exchange rate models. The second part addresses the dependence structure between flow and price change in the FX markets and finds that flow-return relationship is not linear as assumed in the previous literature. Order flow tends to be more informative and has larger impact on prices when market spreads are large, volume is low or volatility is high. These results cannot be fully explained by existing micro structure models. The last part of thesis studies how limit order execution probability is affected by microstructure factors. Using the tick data from the London Stock Exchange, it is demonstrated that price aggressiveness, spread and potential market pressure have significant impacts on the limit order execution

Augmented Tikhonov Regularization Method for Dynamic Load Identification

We introduce the augmented Tikhonov regularization method motivated by Bayesian principle to improve the load identification accuracy in seriously ill-posed problems. Firstly, the Green kernel function of a structural dynamic response is established; then, the unknown external loads are identified. In order to reduce the identification error, the augmented Tikhonov regularization method is combined with the Green kernel function. It should be also noted that we propose a novel algorithm to determine the initial values of the regularization parameters. The initial value is selected by finding a local minimum value of the slope of the residual norm. To verify the effectiveness and the accuracy of the proposed method, three experiments are performed, and then the proposed algorithm is used to reproduce the experimental results numerically. Numerical comparisons with the standard Tikhonov regularization method show the advantages of the proposed method. Furthermore, the presented results show clear advantages when dealing with ill-posedness of the problem

Long-lived Searches of Vector-like Lepton and Its Accompanying Scalar at Colliders

Recently, the vector-like leptons (VLLs) as a simple extension to the standard model (SM) have attracted widespread attention both in theory and experiments. The present collider searches mainly focus on the studies of their prompt decays, which prefer a relatively large coupling. In this paper, we concentrate on searches for long-lived signatures of the singlet VLLs $F$ or their accompanying scalar particles $\phi$ both in the hadronic and electronic colliders. The long-lived signatures are naturally induced from small chiral mass mixing between VLLs and SM leptons. Two specific models distinguished by whether the VLLs couple to scalar particles are introduced to realize the aforementioned features. For long-lived VLLs case, we find that with the kink track method the sensitivities at future HL-LHC with $\sqrt{s}=13~\text{TeV}$ can reach the regions for VLL mass $m_F \in [200,950]~\text{GeV}$ and the mass mixing parameter $\theta_L \in [10^{-10},10^{-7}]$. For the long-lived accompanying scalar particle case, by fixing VLLs or scalar mass, or the mass ratio between VLL and the accompanying scalar, we explore the projected sensitivities through the time delay and displaced vertex strategies, which can probe the regions for $m_F \in [200,1200]~\text{GeV}$ and coupling $y\theta_L\in [10^{-11},10^{-6}]$. Furthermore, we also explore the long-lived accompanying scalars at the future CEPC provided that the VLLs can couple to the SM first-generation leptons. We find that CEPC has good performances for $m_\phi < 70~\text{GeV}$ and $m_F<1000~\text{GeV}$. These long-lived searches are complementary to previous studies, which opens the door towards the smaller coupling regions.Comment: 29 pages, 7 figure

Aligning Linguistic Words and Visual Semantic Units for Image Captioning

Image captioning attempts to generate a sentence composed of several linguistic words, which are used to describe objects, attributes, and interactions in an image, denoted as visual semantic units in this paper. Based on this view, we propose to explicitly model the object interactions in semantics and geometry based on Graph Convolutional Networks (GCNs), and fully exploit the alignment between linguistic words and visual semantic units for image captioning. Particularly, we construct a semantic graph and a geometry graph, where each node corresponds to a visual semantic unit, i.e., an object, an attribute, or a semantic (geometrical) interaction between two objects. Accordingly, the semantic (geometrical) context-aware embeddings for each unit are obtained through the corresponding GCN learning processers. At each time step, a context gated attention module takes as inputs the embeddings of the visual semantic units and hierarchically align the current word with these units by first deciding which type of visual semantic unit (object, attribute, or interaction) the current word is about, and then finding the most correlated visual semantic units under this type. Extensive experiments are conducted on the challenging MS-COCO image captioning dataset, and superior results are reported when comparing to state-of-the-art approaches.Comment: 8 pages, 5 figures. Accepted by ACM MM 201

Numerical Modeling of Mineralizing Processes During the Formation of the Yangzhuang Kiruna-Type Iron Deposit, Middle and Lower Yangtze River Metallogenic Belt, China: Implications for the Genesis and Longevity of Kiruna-Type Iron Oxide-Apatite Systems

The Yangzhuang iron deposit is a Kiruna-type iron oxide-apatite (IOA) deposit within the Ningwu mining district of the Middle and Lower Yangtze River Metallogenic Belt (MLYRMB), China. This study applies a numerical modeling approach to identify the key processes associated with the formation of the deposit that cannot be easily identified using traditional analytical approaches, including the duration of the mineralizing process and the genesis of iron orebodies within intrusions associated with the deposit. This approach highlights the practical value of numerical modeling in quantitatively analyzing mineralizing processes during the formation of mineral deposits and assesses how these methods can be used in future geological research. Our numerical model links heat transfer, pressure, fluid flow, chemical reactions, and the movement of ore-forming material. Results show that temperature anomaly and structure (occurrence of the contact of intrusion and the Triassic Xujiashan group) are two key factors controlling the formation of the Yangzhuang deposit. This modeling also indicates that the formation of the Yangzhuang deposit only took some 8000 years, a reaction that is likely to be controlled by temperature and diffusion rates within the system. The dynamic changes of temperature and the distribution of mineralization also indicate that the orebodies located inside the intrusions most likely formed after magma ascent rather than representing blocks of existing mineralization that descended into the magma as a result of stoping or other similar processes. All these data form the basis for future research into the forming processes of Kiruna-type IOA systems as well as magmatic–hydrothermal systems more broadly, including providing useful insights for future exploration for these systems. The simulation approach used in this study has several limitations, such as oversimplified chemical reactions, uncertainty of pre-metallogenic conditions and limitation of 2D model. Future development into both theories and methods will definitely improve the practical significance of numerical simulation of ore-forming processes and provide quantitative results for more geological issues

Esketamine opioid-free intravenous anesthesia versus opioid intravenous anesthesia in spontaneous ventilation video-assisted thoracic surgery: a randomized controlled trial

BackgroundOpioid-free anesthesia (OFA) provides adequate analgesia and can reduce postoperative opioid consumption, but its efficacy in spontaneous ventilation video-assisted thoracic surgery (SV-VATS) has not been demonstrated. We aimed to investigate the hypothesis that OFA could provide the same perioperative pain control as opioid anesthesia (OA), maintain safe and stable respiration and hemodynamics during surgery, and improve postoperative recovery.MethodsSixty eligible patients (OFA group: n=30; OA group: n=30) treated between September 15, 2022, and December 15, 2022, at The First Hospital of Guangzhou Medical University were included. They were randomized to receive standard balanced OFA with esketamine or OA with remifentanil combined with sufentanil. The primary outcome was the pain numeric rating score (NRS) at postoperative 24 h, and the secondary outcomes were intraoperative respiratory and hemodynamic data, opioid consumption, vasoactive drug dosage, and recovery in the post-anesthesia care unit and ward.ResultsThere was no significant difference in the postoperative pain scores and recovery quality between the two groups. The OFA group had a significantly lower dose of phenylephrine (P=0.001) and a lower incidence of hypotension (P=0.004) during surgery. The OFA group resumed spontaneous respiration faster (P&lt;0.001) and had a higher quality of lung collapse (P=0.02). However, the total doses of propofol and dexmetomidine were higher (P=0.03 and P=0.02), and the time to consciousness was longer (P=0.039) in the OFA group.ConclusionsOFA provides the same level of postoperative pain control as OA, but it is more advantageous in maintaining circulatory and respiratory stability and improving the quality of pulmonary collapse in SV-VATS

DNN-Based ADNMPC of an Industrial Pickling Cold-Rolled Titanium Process via Field Enhancement Heat Exchange

The dynamic neural network based adaptive direct nonlinear model predictive control is designed to control an industrial microwave heating pickling cold-rolled titanium process. The identifier of the direct adaptive nonlinear model identification and the controller of the adaptive nonlinear model predictive control are designed based on series-parallel dynamic neural network training by RLS algorithm with variable incremental factor, gain, and forgetting factor. These identifier and controller are used to constitute intelligent controller for adjusting the temperature of microwave heating acid. The correctness of the controller structure, the convergence, and feasibility of the control algorithms is tested by system simulation. For a given point tracking, model mismatch simulation results show that the controller can be implemented on the system to track and overcome the mismatch system model. The control model can be achieved to track on pickling solution concentration and temperature of a given reference and overcome the disturbance

High-power mid-infrared femtosecond master oscillator power amplifier Er:ZBLAN fiber laser system

High-power femtosecond mid-infrared (MIR) lasers are of vast importance to both fundamental research and applications. We report a high-power femtosecond master oscillator power amplifier laser system consisting of a single-mode Er:ZBLAN fiber mode-locked oscillator and pre-amplifier followed by a large-mode-area Er:ZBLAN fiber main amplifier. The main amplifier is actively cooled and bidirectionally pumped at 976 nm, generating a slope efficiency of 26.9%. Pulses of 8.12 W, 148 fs at 2.8 μm with a repetition rate of 69.65 MHz are achieved. To the best of our knowledge, this is the highest average power ever achieved from a femtosecond MIR laser source. Such a compact ultrafast laser system is promising for a wide range of applications, such as medical surgery and material processing

Tapered side-polished microfibre sensor for high sensitivity hCG detection

A high sensitivity human chorionic gonadotropin (hCG) detection was conducted by a tapered side-polished (TSP) optical fiber sensor. Experimentally, the TSP fiber sensor was made by side polishing a short section of single mode fiber to a D shape structure and tapering the D shape section to a small diameter (<10 μm in the experiments). By functionalizing the primary antibody of hCG onto the TSP fiber surface, the sensor was used for detecting hCG concentration. Experimental results show that when the hCG concentration is 0.1 mIU/mL, the sensor has an average wavelength shift of 0.82 nm. The limit of detection (LoD) of the hCG is estimated 0.058 mIU/mL, assuming three times of maximum wavelength variation (3×0.15=0.45 nm) in Phosphate buffer saline (PBS) to the measurement limit. The specificity has also been tested by immersing the sensor into a mixed biomaterial solution (hCG -1 mIU/mL, pig-IgG -1 /mL, Staphylococcus aureus -6×105 CFU/mL and Escherichia coli -2.5×105 CFU/mL). The result showed that the TSP optical fiber sensor has excellent specificity. The biosensor has potential application in clinical/medical diagnostics, human health, environmental quality and food safety monitoring