Stemming the tide: Does climate risk affect M&A performance?

We examine the effect of climate change risks (CCR) on firms' decision of engaging in mergers and acquisitions (M&A) and M&A performance. In this study we use the responses by firms on ‘climate change-related risks and opportunities’ of the CDP survey and 1,372 deals of listed US firms during 2010-2020. Consistent with risk vulnerability theory, our evidence indicates that firms with higher CCR have a lower probability of engaging in M&As. After controlling for possible endogeneity, our results also indicate that if acquirers with higher climate change risks choose to engage in M&A, it significantly reduces the announcement returns. These findings suggest that extant measures of climate change risks should be rethought when evaluating M&A efficiency. More broadly, our paper provides causal evidence that managers need to integrate CCR into their formal risk management systems to avoid unsuccessful M&As

An Adaptive Color Image Segmentation

A novel Adaptive Color Image Segmentation (ACIS) System for color image segmentation is presented. The proposed ACIS system uses a neural network with architecture similar to the multilayer perceptron (MLP) network. The main difference is that neurons here uses a multisigmoid activation function. The multisigmoid function is the key for segmentation. The number of steps i.e. thresholds in the multisigmoid function are dependant on the number of clusters in the image. The threshold values for detecting the clusters and their labels are found automatically from the first order derivative of histograms of saturation and intensity in the HSV color space. Here, the main use of neural network is to detect the number of objects automatically from an image. The advantage of this method is that no a priori knowledge is required to segment the color image. ACIS label the objects with their mean colors. The algorithm is found to be reliable and works satisfactorily on different kinds of color images. Experimental results show that the performance of ACIS is robust on noisy images also

Quality Enhancement of Low-Resolution Biomedical Images Using Multiwavelet Transform

The recent increase in the wide use of digital imaging technologies in consumer and other areas (e.g., security and military) has brought with it a simultaneous demand for higher-resolution images. The demand for such high-resolution (HR) images can be met by algorithmic advances in resolution enhancement technology intended with hardware development. Such HR images not only give the viewer a more pleasing picture but also offer additional details that are important for subsequent analysis in many applications. Therefore, a resolution enhancement (high resolution) approach using computational, mathematical, and statistical techniques has received a great deal of attention recently. One promising approach is to use Image-processing techniques to obtain an HR image (or sequence) from low- resolution (LR) image. The High resolution images are frequently required in biomedical applications, because the HR images provide the accurate spatial and intensity information for correct diagnosis. In this paper multi-wavelet transform and interpolation method are use for image resolution enhancement

A Survey on Feature Recommendation Techniques

Recommendation systems are a very common now days and it is used in a variety of applications. A recommender system that is designed to reduce the human effort of performing domain analysis. Domain analysis is the task in which we can find the commonality and difference between the different software’s of same domain ‘feature recommendation is very useful now a days. This approach relies on data mining techniques to discover common features across products as well as the relationship among these common features. In this paper we used different techniques which are used for domain analysis and feature recommendation. This approach mines descriptions of product from publicly available online product descriptions, uses a text mining and a novel incremental diffusive clustering algorithm to discover features in specific domain , uses association rule mining to know latent relationships between the features within the products of same domain and uses KNN algorithm which generates a probabilistic feature model that represents commonalities, variant. DOI: 10.17762/ijritcc2321-8169.150316

Review on Green computing to save environment and power management

Computers are used everywhere in human life hence computer consumes more electricity.Toxic, carbon dioxide produce by computer material. But use of computer is necessary in human life. Existence of Green Computing to overcome negative effect of computer to environment.Green computer solves  the problem of power consumption of computer system. It also provides technique to minimize pollution by computer material. Moreover, thousands of computing devices are manufactured every day and the same amount of old computers is being thrown away loading up the e-wastes. So it is highly important to manage these computing devices in such a way that they last longer and even if they are disposed of, they shouldn’t cause much harm to the nature. Green computing can take many forms in itself. Green technology focuses on reducing the environmental impact of industrial processes and innovative technologies caused by Earths growing population It has taken upon itself the goal to provide society’s needs in ways that do not damage or reduce natural resources. It is mainly used to protect environment, optimize energy consumption and keeps Green environment. The main goal of green computing is that increasing energy efficiency and reducing the use of harmful materials. Green computing ultimately focuses on ways in reducing overall environmental impacts. It require the integration of Green computing Practices such as recycling, electronic waste removal power consumption, virtualization, improving cooling technology, and optimization of the requirements. The major power consumption components are processors and the main memory in the servers.This paper gives idea of saving energy & environment which helps to save money

UTERINE ARTERIOVENOUS MALFORMATION TRANSVAGINAL DOPPLER ULTRASONOGRAPHY: CASE REPORT

Uterine arteriovenous malformation (AVM) is a rare condition, with fewer than 100 cases reported in the literature. Despite it being rare, it is a potentially life-threatening condition. This case report describes a healthy 29-year-old patient, nulligravida, with an unremarkable medical history, came from gynaecologist for ultrasaound due to complain of irregular heavy PV bleeding. Transvaginal Doppler ultrasonography is a widely available, noninvasive and excellent diagnostic method. Transvaginal ultrasound (TVS) of the pelvis showed increased vascularity with multidirectional flow of the uterus and a prominent vessel, located on the posterior wall.KEYWORDS: Arteriovenous malformation; Primary infertility; Transvaginal ultrasound

UTERINE ARTERIOVENOUS MALFORMATION TRANSVAGINAL DOPPLER ULTRASONOGRAPHY: CASE REPORT

Uterine arteriovenous malformation (AVM) is a rare condition, with fewer than 100 cases reported in the literature. Despite it being rare, it is a potentially life-threatening condition. This case report describes a healthy 29-year-old patient, nulligravida, with an unremarkable medical history, came from gynaecologist for ultrasaound due to complain of irregular heavy PV bleeding. Transvaginal Doppler ultrasonography is a widely available, noninvasive and excellent diagnostic method. Transvaginal ultrasound (TVS) of the pelvis showed increased vascularity with multidirectional flow of the uterus and a prominent vessel, located on the posterior wall.KEYWORDS: Arteriovenous malformation; Primary infertility; Transvaginal ultrasound

Single muscle fiber proteomics reveals unexpected mitochondrial specialization

Mammalian skeletal muscles are composed of multinucleated cells termed slow or fast fibers according to their contractile and metabolic properties. Here, we developed a high-sensitivity workflow to characterize the proteome of single fibers. Analysis of segments of the same fiber by traditional and unbiased proteomics methods yielded the same subtype assignment. We discovered novel subtype-specific features, most prominently mitochondrial specialization of fiber types in substrate utilization. The fiber type-resolved proteomes can be applied to a variety of physiological and pathological conditions and illustrate the utility of single cell type analysis for dissecting proteomic heterogeneity

Solar energy harvesting in magnetoelectric coupled manganese ferrite nanoparticles incorporated nanocomposite polymer films

Poly(vinylidenefluoride-co-trifluoroethylene) (P(VDF-TrFE)) based pyroelectric as well as magnetoelectric materials offer great promises for energy harvesting for flexible and wearable applications. Hence, this work focus on solar energy harvesting as well as magnetoelectric phenomenon in two phase nanocomposite film where the constituting phases are manganese ferrite (MnFe2O4) nanoparticles and P(VDF-TrFE) polymer. Composite films have been prepared using solution casting technique. X-ray diffraction result shows higher crystallinity of these films. The ferroelectric, magnetic and magnetoelectric properties in variation with applied field and volume percentage of ferrite nanoparticles have been investigated. The preparation condition was optimized in such a way that it results improved ferroelectric polarization of nanocomposite film after incorporation of small amount of ferrite nanoparticles. The maximum magnetoelectric-coupling coefficient of about 156 mV/Oe-Cm was obtained for optimum nanocomposite film when DC bias field was applied perpendicular to electric polarization direction. From a pyroelectric device perspective, solar energy harvesting is also reported. An open circuit voltage of 5V and short circuit current of order of ~1 nA is demonstrated without any pre amplification. Hence, the combination of magnetoelectric and pyroelectric properties of nanocomposite film presented here indicate as a perfect candidate for smart materials, spintronics devices and specified magnetoelectric-based applications