Common wave behavior for mergers and acquisitions in OECD countries? a unique analysis using new Markov switching panel model approach

This paper investigates whether or not there is co-waved merger and acquisition (M&A) activity in 26 OECD countries. We apply the Markov Switching model to panel data (MSP hereafter), an approach which has not previously been attempted. Two distinct regimes are recognized in emerge from M&A data: the wave merger regime and normal merger regime. Our MSP captures the co-wave pattern of the sample countries and has a much better fit than either the univariate Markov Switching model or the conventional linear panel model.

The Coordianted Decentralized Paratransit Sysyem: Design, Formulation, and Heuristic

This dissertation investigates the different organizational structures of paratransit services that cover large regions. A paratransit service is demand-responsive, shared-ride transit service using vans or small buses. It is characterized by the use of vehicles that do not operate on a fixed route or a fixed schedule. The paratransit route and schedule are arranged from a user-specified origin to a user-specified destination, and at a user-specified time. To retain productivity by focusing on shorter trips within a denser area, some larger systems have outsourced operations to more than one contractor, with each contractor responsible for the service zone to which their vehicles have been assigned. This service design is called a "zonal structure" or a "zoning approach." The zoning with transfer system coordinates vehicles' schedules at various transfer locations. The schedule coordination of inter-zonal mechanisms of transportation likely reduces trip costs by increasing the ridesharing rate and lowering the number of empty return miles. This study first presents the exact formulation for a coordinated decentralized paratransit system in order to compare its productivity and service quality with independent decentralized and centralized strategies. The formulation is then proven to work correctly, and the results of the computational experiments of small scale instances are shown to demonstrate that the proposed coordinated system is superior to independent decentralized systems in terms of passenger miles per vehicle revenue mile. In the second section, this study develops an insertion-based heuristic method in order to compare the performances of different operational designs when applied to a large-scale system. In an experiment utilizing Houston's demand-responsive service data, we compare the productivity and service levels among three organizational structures: zoning with transfer, zoning without transfer, and no-zoning designs. The results indicate that zoning with transfer can provide significant benefits to paratransit operations that manage zoning structure; however, the no-zoning strategy used by Houston METRO (a relatively low-density region) performs better on average in terms of efficiency. This study concludes that the zoning with transfer method can be proven to be a productive organizational structure

Synthetic Graphene Grown by Chemical Vapor Deposition on Copper Foils

The discovery of graphene, a single layer of covalently bonded carbon atoms, has attracted intense interests. Initial studies using mechanically exfoliated graphene unveiled its remarkable electronic, mechanical and thermal properties. There has been a growing need and rapid development in large-area deposition of graphene film and its applications. Chemical vapour deposition on copper has emerged as one of the most promising methods in obtaining large-scale graphene films with quality comparable to exfoliated graphene. In this chapter, we review the synthesis and characterizations of graphene grown on copper foil substrates by atmospheric pressure chemical vapour deposition. We also discuss potential applications of such large scale synthetic graphene.Comment: 23 pages, 4 figure

Adversarial Deep Network Embedding for Cross-network Node Classification

In this paper, the task of cross-network node classification, which leverages the abundant labeled nodes from a source network to help classify unlabeled nodes in a target network, is studied. The existing domain adaptation algorithms generally fail to model the network structural information, and the current network embedding models mainly focus on single-network applications. Thus, both of them cannot be directly applied to solve the cross-network node classification problem. This motivates us to propose an adversarial cross-network deep network embedding (ACDNE) model to integrate adversarial domain adaptation with deep network embedding so as to learn network-invariant node representations that can also well preserve the network structural information. In ACDNE, the deep network embedding module utilizes two feature extractors to jointly preserve attributed affinity and topological proximities between nodes. In addition, a node classifier is incorporated to make node representations label-discriminative. Moreover, an adversarial domain adaptation technique is employed to make node representations network-invariant. Extensive experimental results demonstrate that the proposed ACDNE model achieves the state-of-the-art performance in cross-network node classification

A Comparative Study of Wireless Protocols: Bluetooth, UWB, ZigBee, and Wi-Fi

(UWB, over IEEE 802.15.3), ZigBee (over IEEE 802.15.4), and Wi-Fi (over IEEE 802.11) are four protocol standards for short-range wireless communications with low power consumption. From an application point of view, Bluetooth is intended for a cordless mouse, keyboard, and hands-free headset, UWB is oriented to high-bandwidth multimedia links, ZigBee is designed for reliable wirelessly networked monitoring and control networks, while Wi-Fi is directed at computer-to-computer connections as an extension or substitution of cabled networks. In this paper, we provide a study of these popular wireless communication standards, evaluating their main features and behaviors in terms of various metrics, including the transmission time, data coding efficiency, complexity, and power consumption. It is believed that the comparison presented in this paper would benefit application engineers in selecting an appropriate protocol

WiRiS: Transformer for RIS-Assisted Device-Free Sensing for Joint People Counting and Localization using Wi-Fi CSI

Channel State Information (CSI) is widely adopted as a feature for indoor localization. Taking advantage of the abundant information from the CSI, people can be accurately sensed even without equipped devices. However, the positioning error increases severely in non-line-of-sight (NLoS) regions. Reconfigurable intelligent surface (RIS) has been introduced to improve signal coverage in NLoS areas, which can re-direct and enhance reflective signals with massive meta-material elements. In this paper, we have proposed a Transformer-based RIS-assisted device-free sensing for joint people counting and localization (WiRiS) system to precisely predict the number of people and their corresponding locations through configuring RIS. A series of predefined RIS beams is employed to create inputs of fingerprinting CSI features as sequence-to-sequence learning database for Transformer. We have evaluated the performance of proposed WiRiS system in both ray-tracing simulators and experiments. Both simulation and real-world experiments demonstrate that people counting accuracy exceeds 90%, and the localization error can achieve the centimeter-level, which outperforms the existing benchmarks without employment of RIS

Subcutaneous nerve activity is more accurate than heart rate variability in estimating cardiac sympathetic tone in ambulatory dogs with myocardial infarction

BACKGROUND: We recently reported that subcutaneous nerve activity (SCNA) can be used to estimate sympathetic tone. OBJECTIVE: The purpose of this study was to test the hypothesis that left thoracic SCNA is more accurate than heart rate variability (HRV) in estimating cardiac sympathetic tone in ambulatory dogs with myocardial infarction (MI). METHODS: We used an implanted radiotransmitter to study left stellate ganglion nerve activity (SGNA), vagal nerve activity (VNA), and thoracic SCNA in 9 dogs at baseline and up to 8 weeks after MI. HRV was determined based on time-domain, frequency-domain, and nonlinear analyses. RESULTS: The correlation coefficients between integrated SGNA and SCNA averaged 0.74 (95% confidence interval [CI] 0.41-1.06) at baseline and 0.82 (95% CI, 0.63-1.01) after MI (P <.05 for both). The absolute values of the correlation coefficients were significantly larger than that between SGNA and HRV analysis based on time-domain, frequency-domain, and nonlinear analyses, respectively, at baseline (P <.05 for all) and after MI (P <.05 for all). There was a clear increment of SGNA and SCNA at 2, 4, 6, and 8 weeks after MI, whereas HRV parameters showed no significant changes. Significant circadian variations were noted in SCNA, SGNA, and all HRV parameters at baseline and after MI, respectively. Atrial tachycardia (AT) episodes were invariably preceded by SCNA and SGNA, which were progressively increased from 120th, 90th, 60th, to 30th seconds before AT onset. No such changes of HRV parameters were observed before AT onset. CONCLUSION: SCNA is more accurate than HRV in estimating cardiac sympathetic tone in ambulatory dogs with MI

Label-free quantitative proteomics of CD133-positive liver cancer stem cells

Abstract Background CD133-positive liver cancer stem cells, which are characterized by their resistance to conventional chemotherapy and their tumor initiation ability at limited dilutions, have been recognized as a critical target in liver cancer therapeutics. In the current work, we developed a label-free quantitative method to investigate the proteome of CD133-positive liver cancer stem cells for the purpose of identifying unique biomarkers that can be utilized for targeting liver cancer stem cells. Label-free quantitation was performed in combination with ID-based Elution time Alignment by Linear regression Quantitation (IDEAL-Q) and MaxQuant. Results Initially, IDEAL-Q analysis revealed that 151 proteins were differentially expressed in the CD133-positive hepatoma cells when compared with CD133-negative cells. We then analyzed these 151 differentially expressed proteins by MaxQuant software and identified 10 significantly up-regulated proteins. The results were further validated by RT-PCR, western blot, flow cytometry or immunofluorescent staining which revealed that prominin-1, annexin A1, annexin A3, transgelin, creatine kinase B, vimentin, and EpCAM were indeed highly expressed in the CD133-positive hepatoma cells. Conclusions These findings confirmed that mass spectrometry-based label-free quantitative proteomics can be used to gain insights into liver cancer stem cells.http://deepblue.lib.umich.edu/bitstream/2027.42/113089/1/12953_2012_Article_407.pd

Measurements of Natural Carbonate Rare Earth Elements in Femtogram Quantities by Inductive Coupled Plasma Sector Field Mass Spectrometry

A rapid and precise standard-bracketing method has been developed for measuring femtogram quantity rare earth element (REE) levels in natural carbonate samples by inductively coupled plasma sector field mass spectrometry that does not require chemical separation steps. A desolvation nebulization system was used to effectively reduce polyatomic interference and enhance sensitivity. REE/Ca ratios are calculated directly from the intensities of the ion beams of 46Ca, 139La, 140Ce, 141Pr, 146Nd, 147Sm, 153Eu, 160Gd, 159Tb, 163Dy, 165Ho, 166Er, 169Tm, 172Yb, and 175Lu using external matrix-matched synthetic standards to correct for instrumental ratio drifting and mass discrimination. A routine measurement time of 3 min is typical for one sample containing 20-40 ppm Ca. Replicate measurements made on natural coral and foraminiferal samples with REE/Ca ratios of 2-242 nmol/mol show that external precisions of 1.9-6.5% (2 RSD) can be achieved with only 10-1000 fg of REEs in 10-20 μg of carbonate. We show that different sources for monthly resolved coral ultratrace REE variability can be distinguished using this method. For natural slow growth-rate carbonate materials, such as sclerosponges, tufa, and speleothems, the high sample throughput, high precision, and high temporal resolution REE records that can be produced with this procedure have the potential to provide valuable time-series records to advance our understanding of paleoclimatic and paleoenvironmental dynamics on different time scales

Effects of Hemodynamic Response Function Selection on Rat fMRI Statistical Analyses

The selection of the appropriate hemodynamic response function (HRF) for signal modeling in functional magnetic resonance imaging (fMRI) is important. Although the use of the boxcar-shaped hemodynamic response function (BHRF) and canonical hemodynamic response (CHRF) has gained increasing popularity in rodent fMRI studies, whether the selected HRF affects the results of rodent fMRI has not been fully elucidated. Here we investigated the signal change and t-statistic sensitivities of BHRF, CHRF, and impulse response function (IRF). The effect of HRF selection on different tasks was analyzed by using data collected from two groups of rats receiving either 3 mA whisker pad or 3 mA forepaw electrical stimulations (n = 10 for each group). Under whisker pad stimulation with large blood-oxygen-level dependent (BOLD) signal change (4.31 ± 0.42%), BHRF significantly underestimated signal changes (P &lt; 0.001) and t-statistics (P &lt; 0.001) compared with CHRF or IRF. CHRF and IRF did not provide significantly different t-statistics (P &gt; 0.05). Under forepaw stimulation with small BOLD signal change (1.71 ± 0.34%), different HRFs provided insignificantly different t-statistics (P &gt; 0.05). Therefore, the selected HRF can influence data analysis in rodent fMRI experiments with large BOLD responses but not in those with small BOLD responses