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Climate change, a global challenge facing mankind necessitates governments to develop mitigation and adaptation plans. The climate change has multidimensional impacts on environment, fishery, social, economic and development drive...
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Climate change, a global challenge facing mankind necessitates governments to develop mitigation and adaptation plans. The climate change has multidimensional impacts on environment, fishery, social, economic and development drivers.? Climate change hot spots –can be defined as the ‘live labs’?where the manifestation of the climate change impacts is observed “first”. The South west India has been recognised as one among the twenty four hot spot regions identified globally. The present paper assessed the climate change vulnerability of over 800 fisher households in two major fishing villages of Kerala from the south west hotspot regions of India. Exposure (E), Sensitivity (S) and Adaptive Capacity (AC) are the pertinent factors that determine the vulnerability of households which were captured using a structured household questionnaire. One ninety eight? indicators were identified in the construction of vulnerability indices of which 37 related to sensitivity, 36 related to exposure and the other 125 indicators dealt with adaptive capacity. The overall vulnerability of the regions was assessed and the analysis revealed that the Poonthura village of Kerala was more vulnerable when compared to Elamkunnapuzha. The coastal population on their vulnerability scores were categorised into low, moderate, high and very high based on score values and geo-spatial analysis was attempted.? The results revealed that majority of fisher households in both villages were highly vulnerable to climate change, which is a major cause of concern. The study advocates the need for a bottom up approach with the proactive participation of the fishers in developing location specific adaptation and mitigation plans to ensure the livelihood of the fishers and the sustainable development of the fisheries sector in the climate change regime.
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摘要 :
Climate change, a global challenge facing mankind necessitates governments to develop mitigation and adaptation plans. The climate change has multidimensional impacts on environment, fishery, social, economic and development drive...
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Climate change, a global challenge facing mankind necessitates governments to develop mitigation and adaptation plans. The climate change has multidimensional impacts on environment, fishery, social, economic and development drivers.? Climate change hot spots –can be defined as the ‘live labs’ where the manifestation of the climate change impacts is observed “first”. The South west India has been recognised as one among the twenty four hot spot regions identified globally. The present paper assessed the climate change vulnerability of over 800 fisher households in two major fishing villages of Kerala from the south west hotspot regions of India. Exposure (E), Sensitivity (S) and Adaptive Capacity (AC) are the pertinent factors that determine the vulnerability of households which were captured using a structured household questionnaire. One ninety eight? indicators were identified in the construction of vulnerability indices of which 37 related to sensitivity, 36 related to exposure and the other 125 indicators dealt with adaptive capacity. The overall vulnerability of the regions was assessed and the analysis revealed that the Poonthura village of Kerala was more vulnerable when compared to Elamkunnapuzha. The coastal population on their vulnerability scores were categorised into low, moderate, high and very high based on score values and geo-spatial analysis was attempted.? The results revealed that majority of fisher households in both villages were highly vulnerable to climate change, which is a major cause of concern. The study advocates the need for a bottom up approach with the proactive participation of the fishers in developing location specific adaptation and mitigation plans to ensure the livelihood of the fishers and the sustainable development of the fisheries sector in the climate change regime.
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Intraseasonal variations (ISV) of sea surface temperature (SST) in the Bay of Bengal (BoB) is highest in its northwestern part.An Indian Ocean model forced by QuikSCAT winds and climatological river discharge (QR run) reproduces I...
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Intraseasonal variations (ISV) of sea surface temperature (SST) in the Bay of Bengal (BoB) is highest in its northwestern part.An Indian Ocean model forced by QuikSCAT winds and climatological river discharge (QR run) reproduces ISV of SST,albeit with weaker magnitude.Air-sea fluxes,in the presence of a shallow mixed layer,efficiently effect intraseasonal SST fluctuations.Warming during intraseasonal events is smaller (<1℃) for June-July period and larger (1.5°to 2℃) during September,the latter due to a thinner mixed layer.To examine the effect of salinity on ISV,the model was run by artificially increasing the salinity (NORR run) and by decreasing it (MAHA10 run).In NORR,both rainfall and river discharge were switched off and in MAHA 10 the discharge by river Mahanadi was increased tenfold.The spatial pattern of ISV as well as its periodicity was similar in QR,NORR and MAHA 10. The ISV was stronger in NORR and weaker in MAHA10,compared to QR.In NORR,both intraseasonal warming and cooling were higher than in QR,the former due to reduced air-sea heat loss as the mean SST was lower,and the latter due to enhanced subsurface processes resulting from weaker stratification.In MAHA 10,both warming and cooling were lower than in QR,the former due to higher air-sea heat loss owing to higher mean SST, and the latter due to weak subsurface processes resulting from stronger stratification.These model experiments suggest that salinity effects are crucial in determining amplitudes of intraseasonal SST variations in the BoB.
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The paper reports about an in-depth analysis on the dissolution study of η ζ and δ phases of composite zinc coating developed by integrating WO_3 nanoparticles, and assessment of their anti-corrosion characteristics. The compos...
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The paper reports about an in-depth analysis on the dissolution study of η ζ and δ phases of composite zinc coating developed by integrating WO_3 nanoparticles, and assessment of their anti-corrosion characteristics. The composite coating with WO_3 nanoparticles effectively integrated into the η phase than the mixed ζ & δ phases or γ phase offers the best corrosion protection characteristics. The superior anti-corrosion performance of composite zinc coating with distinct amount of nanoparticles integration into the η phase than the other intermetallic phases is due to the formation of compact and crack free Fe-Zn intermetallic layer with strong W-Zn bonds. The work is proposed as a cost-effective and simple method for the evaluation of high-temperature coatings, where the performance is influenced by the formation and stability of interior intermetallics.
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The ByAl_xGa_(1-x–y)N system validates promise as a suitable option for fabricating opto-electronic
devices like light-emitting-diodes (LEDs) and laser diodes. This study conducts a
comparative analysis between two types of LED...
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The ByAl_xGa_(1-x–y)N system validates promise as a suitable option for fabricating opto-electronic
devices like light-emitting-diodes (LEDs) and laser diodes. This study conducts a
comparative analysis between two types of LEDs: one with a single quantum well composed
of AlGaN and another with BAlGaN, containing 1% boron, 22% aluminum, and a
3 nm thickness. These LEDs are designed as AlGaN-based quantum well (LED1) and Bal-
GaN-based quantum well devices (LED2). Technology computer-aided design (TCAD)
Silvaco physical simulator is used to perform simulations and comparisons in terms of both
optical and electrical characteristics. The simulations includes anode current with respect
to anode voltage, luminous power and wall-plug efficiency relative to injection current, and
power spectral density concerning wavelength. Remarkably, even with a mere 1% boron
content within the quantum well, the LED’s performance displays a 5% enhancement in
power spectral density and a 7% boost in wall-plug efficiency.
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At present times, breast cancer becomes a major cause of increased women mortality all over the world. Mammography is an efficient methodology employed for the screening and identification of abnormality. But the earlier identific...
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At present times, breast cancer becomes a major cause of increased women mortality all over the world. Mammography is an efficient methodology employed for the screening and identification of abnormality. But the earlier identification of breast cancer is mainly based on the experience of the radiologist in the interpretation of mammogram and mammogram image quality. The advent of deep learning (DL) and image processing techniques are widely employed to perform breast cancer image classification process. This paper presents an automated breast cancer diagnosis and classification model using DL techniques. In the design of computer aided diagnosis (CAD) model, the Gabor filtering (GF) technique followed by contrast limited adaptive histogram equalization (CLAHE) are employed as a preprocessing step. Then, segmentation of images takes place using the DL model and the feature extraction process in the mammogram region of interest (Rol) images are carried out using the Inception v3 model. Atlast, the classification task of the presented Inception v3 model is implemented using two models namely random forest (RF) and multilayer perceptron (MLP), IV-RF, and IV-MLP models. The breast cancer diagnostic performance of the presented model is examined using benchmark dataset and the simulation outcome is investigated.
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This paper presents Magnetic Resonance Imaging (MRI) brain tumor detection utilizing Fuzzy C Means strategy with an upgraded noise filtering calculation. A novel technique is proposed to enhance the execution of cerebrum tumor dis...
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This paper presents Magnetic Resonance Imaging (MRI) brain tumor detection utilizing Fuzzy C Means strategy with an upgraded noise filtering calculation. A novel technique is proposed to enhance the execution of cerebrum tumor discovery. A new calculation for noise filtering is adapted to extract the correct area of tumor, where execution is enhanced by upgrading the threshold task in wavelet filtering strategy as a preprocessing step. Trial results demonstrate that by utilizing proposed calculation, the filtering procedure gives better execution when contrasted with the current methods. The average value of Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) for Gaussian noise is improved by 40% and 41.06% and for Rician noise, which is 13.73% and 25.39% higher than the state-of-art methods. After filtering, segmentation is done to point out the tumor region. For segmentation, Otsu and FCM methods are adapted here and a comparison is made between these two methods. Experimental results show that Jaccard and Dice coefficient of Fuzzy C Means (FCM) with enhanced filtering is increased by 3.6% and 1.3% compared to the methods available in the literature.
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The goal of this work concentrates on MRI (Magnetic Resonance Imaging) brain tumor findings by utilizing the BRATS dataset images. At first, it undergoes preprocessing criteria using an enhanced DWT (Discrete Wavelet Transform) fi...
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The goal of this work concentrates on MRI (Magnetic Resonance Imaging) brain tumor findings by utilizing the BRATS dataset images. At first, it undergoes preprocessing criteria using an enhanced DWT (Discrete Wavelet Transform) filtering to decrease the noise level in the picture. Following this, segmentation has to extricate the tumor region dependent on improved thresholding activity. At that point, its effectiveness has processed by using the performance measurements, for example, Normalized cross-correlation, PSNR (Peak Signal to Noise Ratio), NAE (Normalized Absolute Error), and AD (Average Difference). The reproduction results show that unrivaled outcomes on the proposed thresholding task contrasted with comparable techniques. Furthermore, this was better than the other strategies for both Rician and Gaussian noise. The proposed approach supports the experts in identifying the exact location of the tumor and broadening their lifetime.
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Electron selective intermediate layers are crucial for both efficiency and stability of the inverted polymer solar cells (IPSCs). In this paper, an established low-temperature (<130°C) recipe to fabricate nano zinc oxide (ZnO) layers (L-ZnO) exhibited typical values of power conversion efficiency (PCE～ 3.3%) with the standard P3HT:PC_(61)BM blend. However, PCEs showed further improvement up to ～24% (～ 4.08%) when these layers were annealed at 300°C (H-ZnO). This annealing step can be bypassed by adopting a slightly different chemistry using Nafion as a modifier (NM-ZnO). I-PSCs fabricated with NM-ZnO showed nearly 40% increase in the PCE (～4.62%) with PEDOT:PSS hole transport layers (HTL) that matches the so far highest recorded value for such a system. For the low-bandgap polymer blend PBDTT-FTTE:PC_(71)BM, a peak efficiency of ～6.77% was obtained compared to ～5.34% with L-ZnO (～28% increase). Our experiments revealed that these enhancements were due to a combination of benefits obtained from Nafion modification such as favourable positioning of work function (WF), high band gap (Eg) and better transport characteristics through the layer interfaces....
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Electron selective intermediate layers are crucial for both efficiency and stability of the inverted polymer solar cells (IPSCs). In this paper, an established low-temperature (<130°C) recipe to fabricate nano zinc oxide (ZnO) layers (L-ZnO) exhibited typical values of power conversion efficiency (PCE～ 3.3%) with the standard P3HT:PC_(61)BM blend. However, PCEs showed further improvement up to ～24% (～ 4.08%) when these layers were annealed at 300°C (H-ZnO). This annealing step can be bypassed by adopting a slightly different chemistry using Nafion as a modifier (NM-ZnO). I-PSCs fabricated with NM-ZnO showed nearly 40% increase in the PCE (～4.62%) with PEDOT:PSS hole transport layers (HTL) that matches the so far highest recorded value for such a system. For the low-bandgap polymer blend PBDTT-FTTE:PC_(71)BM, a peak efficiency of ～6.77% was obtained compared to ～5.34% with L-ZnO (～28% increase). Our experiments revealed that these enhancements were due to a combination of benefits obtained from Nafion modification such as favourable positioning of work function (WF), high band gap (Eg) and better transport characteristics through the layer interfaces.
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In order to examine the variations in inorganic carbon components in the thermal fronts, seven fronts have been sampled in the northeastern Arabian Sea during winter. The sea surface temperature (SST) was cooler by 0.2 to 1.03 ℃ ...
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In order to examine the variations in inorganic carbon components in the thermal fronts, seven fronts have been sampled in the northeastern Arabian Sea during winter. The sea surface temperature (SST) was cooler by 0.2 to 1.03 ℃ within the fronts sampled and three out of seven fronts were relatively saltier (by 0.04 to 0.10) and others were fresher (by 0.03 to 0.13) compared to outside the front. Increase in chlorophyll-a (Chl-a) was observed by 0.05 to 0.6 mg m~(-3) in the four fronts and marginal decrease was noticed in other fronts (0.02-0.23 mg m~(-3)). The increase in Chl-a within the front from that of outside showed linear relation with magnitude of difference in temperature and salinity suggesting that enhanced vertical mixing brought nutrients to surface to support phy-toplankton biomass in the fronts. Dissolved oxygen was relatively under-saturated by -1.6% in the frontal zone compared to outside suggesting that dominant heterotrophy in the former region due to availability of high phy-toplankton biomass. Dissolved inorganic carbon (DIC) was higher in the frontal zone by 3 to 41.5 μM than outside. The salinity normalized DIC displayed linear relation with Chl-a and inverse correlation with dissolved oxygen saturation suggesting that both auto and heterotrophic activities may be responsible for changes in DIC in the frontal zone. The higher levels (by 3 to 50 μatm) were noticed in the frontal zone compared to outside, however, the magnitude of difference was linearly correlated with difference in SST and Chl-a between within and outside fronts. Based on the simple model, it was noticed that biological and mixing effects were dominant controlling factors for pCO_2 followed by thermal and flux effects. The biological effect was dominant at fronts 1 and 3 while mixing effect controls at fronts 2,4 and 6. This study suggests that fronts act as a source or sink depends on the strength of the mixing process associating with biological response and also age of the front.
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