366 research outputs found

    What Explains Credit Default Swaps Bid-Ask Spread?

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    The pace at which the Credit default swaps (CDS) has been growing since its inception topped all projections. Despite the rapid growth, there is still room for enhancement of liquidity in the CDS market. Asymmetric information is another concern of investors in CDS market, however, some literature addressed that it may not be as serious as regarded. Bid-ask spreads is commonly used as a proxy of both liquidity and asymmetric information. Our empirical study confirms that CDS bid-ask spread has explanatory power to CDS premium. We then investigate the liquidity component in CDS bid-ask spreads. We use the bond age, bond amount, and bond time-to-maturity as the liquidity measure. We confirm that the bond market and CDS market are closely correlated. However, the composition of CDS bid-ask spread need to be further studied. Key Words: Credit Default Swaps; Bid-Ask Spread; Liquidit

    Making sense of employees' sensemaking : evidence from a multi-skilling project

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    This study aims to expand Weick and his colleagues' (2005) sensemaking framework by exploring prospection, work role identity, and emotion in the sensemaking process. It adopts a qualitative case study approach and examines the sensemaking of employees (both professional and non-professional) during a multi-skilling project. The study reveals three forms of sensemaking, namely 'wide sensemaking', 'narrow sensemaking' and 'ambivalent sensemaking', depending on the dynamics among prospection, work role identity, emotion in sensemaking. The study finds that people's sensemaking is affected by the disparity between the core attributes in their initial work role identity and those in the newly designed role of a multi-skilling project. Moreover, this study extends theories of prospection in sensemaking, arguing that people experiencing different disparity between their original work role identity and the work role identity associated with the Project display different patterns of prospective sensemaking. In addition, the thesis considers emotion in sensemaking, which was induced from the data. Emotions elicited in sensemaking affect the selection of anomalies as sensemaking cues, and indicate the need for identity work. Furthermore, in making sense of a multi-skilling project the valence and intensity of emotions elicited are determined by the level of difficulty to restore to one’s acceptable work role identity

    Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine

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    Preterm birth (PTB) is the leading cause of perinatal mortality and long-term morbidity, which results in significant health and economic problems. The early detection of PTB has great significance for its prevention. The electrohysterogram (EHG) related to uterine contraction is a noninvasive, real-time, and automatic novel technology which can be used to detect, diagnose, or predict PTB. This paper presents a method for feature extraction and classification of EHG between pregnancy and labour group, based on Hilbert-Huang transform (HHT) and extreme learning machine (ELM). For each sample, each channel was decomposed into a set of intrinsic mode functions (IMFs) using empirical mode decomposition (EMD). Then, the Hilbert transform was applied to IMF to obtain analytic function. The maximum amplitude of analytic function was extracted as feature. The identification model was constructed based on ELM. Experimental results reveal that the best classification performance of the proposed method can reach an accuracy of 88.00%, a sensitivity of 91.30%, and a specificity of 85.19%. The area under receiver operating characteristic (ROC) curve is 0.88. Finally, experimental results indicate that the method developed in this work could be effective in the classification of EHG between pregnancy and labour group

    Investigation of the topography-dependent current in conductive AFM and the calibration method

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    The topography and the electrical properties of materials are two crucial characteristics in determining their functionalities. Conductive atomic force microscopy (CAFM) is widely recognized for its ability to independently measure the topology and conductivity of the sample surface. The increasing trend towards miniaturization in electrical devices and sensors has led to an urgent demand for enhancing the accuracy of CAFM characterization. However, the sample's topography may affect the current measured by CAFM, leading to an inaccurate estimation of the sample's conductivity. Herein, we investigated the existence of topography-dependent current that originates from changes in capacitance between the probe and sample in CAFM testing. A linear correlation between the current and topography has been established using both experimental and theoretical methods. A calibration method based on this linear correlation has been proposed to eliminate the current error induced by the uneven surface of both insulators and conductors. This work will yield substantial advantages for research requiring high-precision CAFM testing.Comment: Corrected typo

    The capacity of health service commissioners to use evidence: a case study

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    Clinical Commissioning Groups (CCGs) lead a network of organisations that plan and make decisions about what services to provide through the NHS. By examining decision-making about service interventions designed to reduce potentially avoidable elderly care admissions into acute hospitals, our study explores the capacity of CCG-led commissioning networks to make decisions that are based on evidence. Empirically, we study 13 cases of representative (region, size, urban/rural) commissioning networks in England, drawing on interviews with commissioning managers, general practitioners (GPs), patient and public involvement (PPI) representatives and other relevant stakeholders. CCGs can not only draw on evidence about what is most clinically effective or cost-effective, but can also consider patient experience and local knowledge held by doctors. However, the inclusion of GPs and PPI representatives is limited, so the local knowledge of doctors and the patient experience are not considered as fully as they might be in commissioning decisions. CCGs can use government agencies, such as commissioning support units, that provide external information about local population and existing service provision, but they fail to do so adequately. The voluntary sector can play a key role in providing local knowledge about individual patients and their needs. Finally, given the need for health and social care organisations to collaborate to support older people so that they do not experience potentially avoidable admissions to acute hospitals, there is a need for organisations to develop joint evidence-based strategies and work together in real time to exchange information. From our research, in collaboration with a PPI reference group, a self-assessment questionnaire for CCG-led commissioning networks was developed, which allows CCGs to assess and develop their capacity to acquire and use different types of evidence in their decision-making.questionnaire for CCG-led commissioning networks was developed, which allows CCGs to assess and develop their capacity to acquire and use different types of evidence in their decision-making

    Audio-Visual Instance Segmentation

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    In this paper, we propose a new multi-modal task, namely audio-visual instance segmentation (AVIS), in which the goal is to identify, segment, and track individual sounding object instances in audible videos, simultaneously. To our knowledge, it is the first time that instance segmentation has been extended into the audio-visual domain. To better facilitate this research, we construct the first audio-visual instance segmentation benchmark (AVISeg). Specifically, AVISeg consists of 1,258 videos with an average duration of 62.6 seconds from YouTube and public audio-visual datasets, where 117 videos have been annotated by using an interactive semi-automatic labeling tool based on the Segment Anything Model (SAM). In addition, we present a simple baseline model for the AVIS task. Our new model introduces an audio branch and a cross-modal fusion module to Mask2Former to locate all sounding objects. Finally, we evaluate the proposed method using two backbones on AVISeg. We believe that AVIS will inspire the community towards a more comprehensive multi-modal understanding

    The Central Domain of MCPH1 Controls Development of the Cerebral Cortex and Gonads in Mice

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    MCPH1 is the first gene identified to be responsible for the human autosomal recessive disorder primary microcephaly (MCPH). Mutations in the N-terminal and central domains of MCPH1 are strongly associated with microcephaly in human patients. A recent study showed that the central domain of MCPH1, which is mainly encoded by exon 8, interacts with E3 ligase βTrCP2 and regulates the G2/M transition of the cell cycle. In order to investigate the biological functions of MCPH1’s central domain, we constructed a mouse model that lacked the central domain of MCPH1 by deleting its exon 8 (designated as Mcph1 -Δe8). Mcph1 -Δe8 mice exhibited a reduced brain size and thinner cortex, likely caused by a compromised self-renewal capacity and premature differentiation of Mcph1 -Δe8 neuroprogenitors during corticogenesis. Furthermore, Mcph1 -Δe8 mice were sterile because of a loss of germ cells in the testis and ovary. The embryonic fibroblasts of Mcph1 -Δe8 mice exhibited premature chromosome condensation (PCC). All of these findings indicate that Mcph1 -Δe8 mice are reminiscent of MCPH1 complete knockout mice and Mcph1 -ΔBR1 mice. Our study demonstrates that the central domain of MCPH1 represses microcephaly, and is essential for gonad development in mammals
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