The Influence of Leverage Capacity and Cash Reserves on Long-term Operating Performance of Mergers and Acquisitions in US

This paper basically investigates the influence of leverage capacity and cash reserves on long-term operating performance of acquirer firms in the US public firms after M&As. I use accounting-data based measure, create an OSL model to examine whether and how the different firms, deals, industry relativity characteristics and economic environment condition could improve post-M&As operating performance of acquirer firms in the long run. Using a sample of 760 US firms M&As deals that completed from 2000 to 2012, I find that the better historical operating performance is, the higher the firm profitability would be achieved, while leverage capacity and industry relatedness between targets and acquirers has no significant effect on improving long-term performance. Moreover, my results also suggest that prepare more cash before mergers would deteriorate post-merger operating performance of acquirers, while during financial crisis period and for cash payment deal, the influence of cash reserves could be altered, and it would have a positive significant influence on enhancing operating performance. Keywords: Long-term operating performance, leverage capacity, cash reserves, industry relativity, financial crisis, method of payment

Suppression of stimulated Raman scattering by angularly incoherent light, towards a laser system of incoherence in all dimensions of time, space, and angle

Laser-plasma instability (LPI) is one of the main obstacles in laser-driven inertial confinement fusion (ICF) for achieving predictable and reproducible fusion at high gain. For the first time we have proved analytically and confirmed with three-dimensional particle-in-cell simulations that angular incoherence has additional and much stronger suppression of the instability growth rate than the well-known temporal incoherence and spatial incoherence usually used in ICF studies. For the model used in our calculations, the maximum field ratio between the stimulated Raman scattering and the driving pulses drops from 0.2 for the Laguerre-Gaussian pulse with a single non-zero topological charge to 0.05 for the super light spring with an angular momentum spread and random relative phases. In particular, angular incoherence does not introduce extra undesirable hot electrons. This opens a novel way to suppress LPI with the light of an angular momentum spread and paves the way towards a low LPI laser system with a super light spring of incoherence in all dimensions of time, space, and angle

Geometric Prior Based Deep Human Point Cloud Geometry Compression

The emergence of digital avatars has raised an exponential increase in the demand for human point clouds with realistic and intricate details. The compression of such data becomes challenging with overwhelming data amounts comprising millions of points. Herein, we leverage the human geometric prior in geometry redundancy removal of point clouds, greatly promoting the compression performance. More specifically, the prior provides topological constraints as geometry initialization, allowing adaptive adjustments with a compact parameter set that could be represented with only a few bits. Therefore, we can envisage high-resolution human point clouds as a combination of geometric priors and structural deviations. The priors could first be derived with an aligned point cloud, and subsequently the difference of features is compressed into a compact latent code. The proposed framework can operate in a play-and-plug fashion with existing learning based point cloud compression methods. Extensive experimental results show that our approach significantly improves the compression performance without deteriorating the quality, demonstrating its promise in a variety of applications

Development and Inter-Laboratory Validation of Unlabeled Probe Melting Curve Analysis for Detection of JAK2 V617F Mutation in Polycythemia Vera

Background: JAK2 V617F, a somatic point mutation that leads to constitutive JAK2 phosphorylation and kinase activation, has been incorporated into the WHO classification and diagnostic criteria of myeloid neoplasms. Although various approaches such as restriction fragment length polymorphism, amplification refractory mutation system and real-time PCR have been developed for its detection, a generic rapid closed-tube method, which can be utilized on routine genetic testing instruments with stability and cost-efficiency, has not been described. Methodology/Principal Findings: Asymmetric PCR for detection of JAK2 V617F with a 3'-blocked unlabeled probe, saturate dye and subsequent melting curve analysis was performed on a Rotor-Gene (R) Q real-time cycler to establish the methodology. We compared this method to the existing amplification refractory mutation systems and direct sequencing. Hereafter, the broad applicability of this unlabeled probe melting method was also validated on three diverse real-time systems (Roche LightCycler (R) 480, Applied Biosystems ABI (R) 7500 and Eppendorf Mastercycler (R) ep realplex) in two different laboratories. The unlabeled probe melting analysis could genotype JAK2 V617F mutation explicitly with a 3% mutation load detecting sensitivity. At level of 5% mutation load, the intra-and inter-assay CVs of probe-DNA heteroduplex (mutation/wild type) covered 3.14%/3.55% and 1.72%/1.29% respectively. The method could equally discriminate mutant from wild type samples on the other three real-time instruments. Conclusions: With a high detecting sensitivity, unlabeled probe melting curve analysis is more applicable to disclose JAK2 V617F mutation than conventional methodologies. Verified with the favorable inter- and intra-assay reproducibility, unlabeled probe melting analysis provided a generic mutation detecting alternative for real-time instruments

Mortality Prediction with Adaptive Feature Importance Recalibration for Peritoneal Dialysis Patients

The study aims to develop AICare, an interpretable mortality prediction model, using Electronic Medical Records (EMR) from follow-up visits for End-Stage Renal Disease (ESRD) patients. AICare includes a multi-channel feature extraction module and an adaptive feature importance recalibration module. It integrates dynamic records and static features to perform a personalized health context representation learning. The dataset encompasses 13,091 visits and demographic data of 656 peritoneal dialysis (PD) patients spanning 12 years. An additional public dataset of 4,789 visits from 1,363 hemodialysis (HD) patients is also considered. AI Care outperforms traditional deep learning models in mortality prediction while retaining interpretability. It uncovers mortality-feature relationships, variations in feature importance, and provides reference values. An AI-Doctor interaction system is developed for visualizing patients’ health trajectories and risk indicators

The Influence of Leverage Capacity and Cash Reserves on Long-term Operating Performance of Mergers and Acquisitions in US

This paper basically investigates the influence of leverage capacity and cash reserves on long-term operating performance of acquirer firms in the US public firms after M&As. I use accounting-data based measure, create an OSL model to examine whether and how the different firms, deals, industry relativity characteristics and economic environment condition could improve post-M&As operating performance of acquirer firms in the long run. Using a sample of 760 US firms M&As deals that completed from 2000 to 2012, I find that the better historical operating performance is, the higher the firm profitability would be achieved, while leverage capacity and industry relatedness between targets and acquirers has no significant effect on improving long-term performance. Moreover, my results also suggest that prepare more cash before mergers would deteriorate post-merger operating performance of acquirers, while during financial crisis period and for cash payment deal, the influence of cash reserves could be altered, and it would have a positive significant influence on enhancing operating performance. Keywords: Long-term operating performance, leverage capacity, cash reserves, industry relativity, financial crisis, method of payment

An intelligent recommendation method for coal mine accident case via ontology knowledge service

Abstract Coal mine accidents, for example, water leakage and collapse, can damage the circuit system, and they in turn can affect the stable operation of the coal mine. Therefore, it is necessary to identify the causes of coal mine accidents and reduce the number of accidents in coal mines. Government and enterprises have already accumulated numerous coal mine accident cases. To summarize the characteristics and rules of accidents, survey the deep cause of the accident, avoid the recurrence of similar accidents, and early pre‐control of risk source, there is a need to analyze the correlation in the accident characteristics. Then, with the help of ontology knowledge service model, we address this issue in this article. For guaranteeing the inference efficiency of ontology knowledge, we propose a semiautomatic construction method for coal mine accident cases to construct ontology. Here, the reliability of ontology construction and the professionalism of domain knowledge provide a feasible approach to ontology learning using structured and semi‐structured data sources. Furthermore, the weighted Word2vec and spectral clustering method are combined, an intelligent recommendation algorithm with accident ontology is accordingly presented, while presenting a local optimal distance calculation similarity strategy. This method can serve as an assistant to help users mine similar coal mine accident cases. Finally, the experimental results show that after comparing with some other popular methods, the proposed approach can achieve a satisfactory performance on the coal mine dataset with an accuracy of 99.47%, the precision of 98.92%, and the F1‐score of 99.35

A Study on the Dynamics of Landscape Patterns in the Yellow River Delta Region

The Yellow River Delta region is one of the estuarine deltas with the fastest land building speed, and it is an important region for the study of landscape pattern change due to its diverse variety of landscape types. By analyzing the dynamic degree, landscape type transfer matrix, and landscape indices of landscape types in the Yellow River Delta region in 2005, 2012, and 2018, this paper found that the area of construction land, salt fields, and breeding ponds in the Yellow River Delta region has increased to a large extent, with an increase in the aggregation degree and the utilization rate of this landscape type, and the landscape has developed toward the direction of aggregation and unification. The increase in construction land area mainly comes from the transfer of cropland area, part of which is occupied in order to adapt to urban expansion, and the salt fields and breeding ponds mainly come from the transfer of waters and mudflats, which can be seen as the main utilization direction of the water landscape. Moreover, unused land has increased with the degree of dispersion and fragmentation of development and utilization, so the exploitation and utilization of unused land still needs to be optimized. Through the analysis of the dynamic change in landscape pattern, we can explore the direction and extent of the evolution of landscape types, which has certain guiding significance for the sustainable use of land resources and the sustainable development of economy in the Yellow River Delta region

Characterization of the Undrained Shear Strength of Expansive Soils of High Water Content

In recent years, engineering constructions increase rapidly in western and central areas of China, where expansive soil widely distributes. Since expansive soil is sensitive to water content, the characterization of its shear strength should be carefully conducted. For simplicity and ease of use, the Mohr-Coulomb criterion is often adopted to describe the shear strength of expansive soil. In this paper, the physical meaning of the cohesion and frictional strength of expansive soil are explained, and the variations of the strength parameters with water content are investigated. By fitting to the experimental results from direct shear test and triaxial tests, the changing characteristics of cohesion and friction angle with water content are obtained