Avian eggshell coloration predicts shell-matrix protoporphyrin content

Avian eggshell pigmentation may provide information about a female’s physiological condition, in particular her state of oxidative balance. Previously we found that female house wrens (Troglodytes aedon Vieillot, 1809) with lighter, less-maculated, and redder ground-colored shells were older and produced heavier offspring than females laying darker, browner eggs. The strong pro-oxidant protoporphyrin is responsible for this species’ eggshell pigmentation, so differences in pigmentary coloration may be related to eggshell protoporphyrin content and reflect female oxidative balance and condition during egg-formation. Therefore, we tested the assumption that egg-surface coloration is related to the amount of protoporphyrin in the shell matrix. We analyzed digital photographs of eggs to determine maculation coverage as a measure of the overall ground coloration of the egg and its red-, green-, and blue-channel pixel values. Pigments were then extracted from these same eggs and analyzed using high-performance liquid chromatography. There was a strong, positive relationship between eggshell redness and protoporphyrin content of eggshells, but no relationship between percent maculation and protoporphyrin content. Thus, when older, larger females deposit more protoporphyrin in their eggshells, this may reflect a tolerance for high levels of circulating protoporphyrin or an effective mechanism for off-loading protoporphyrin into the eggshell matrix. Keywords: Eggs, Female quality, HPLC, Eggshell pigmentation, Eggshell speckles

A Novel Dual Encryption Algorithm to Enhance the Security in Image Transmission Using LSB 3-2-2 Technique

Nowaday’s providing the security for image is essential for correspondence. Steganography and cryptography are a technical method for the transfer of information to eliminate burglary and stealing of information. Cryptography steganography hides the occurrence of a mystery message. We need more Secured and confidential images to transfer. Steganography procedure on RGB genuine nature utilizing LSB 3-3-2 technique. On the RED & GREEN line, on the LSB Three-Three-two is a procedure, while on the blue channel, it is just 2 LSB. Messages are not exactly RED and GREEN on BLUE platforms. Double encryption techniques are used, such as Caesar cipher & Vigenere cipher, to preserve the nature of the stegno photos and to increase message safety. Use of steganographic strategies are insufficient to give security to informing it is imperative to join the strategy of cryptography. A combination of Caesar Encryption and Vigenere applies to message until they are inserted in LSB Three-Three-Two methods to provide extra protection. At this point we are providing the Caesar code and Vigenere image estimating to enhance security. The target of this is to upgrade the secrecy & security of the image steganography. It will be more efficient because using the two fold layer of security.

Underwater Image Enhancement Method Based On Color Correction and Dark Channel Prior

Concerning to the problem in the distortion of color and the low contrast of underwater image, the image enhancement method in the underwater environment based on color correction and dark channel prior was proposed. When dealing with the color bias problem, the blue channel standard ratio is firstly calculated based on the blue channel, and the red and green channels of the underwater image are compensated to remove the blue and green background colors of the underwater image. In light of the problem in the low contrast of image in underwater environment, the dark channel prior (DCP) method based on the super pixel was used to enhance the corrected underwater image. Finally, the underwater object detection dataset images are tested, and the algorithm proposed in terms of the quality is made the comparison with six advanced image enhancement method in underwater environment. The experimental results show that the proposed algorithm earned the highest score in underwater quality evaluation index (UIQM) compared with the above algorithm.

Express determination of cephalexin

Test means based on immobilized Fehling’s reagent for the determination of cephalexin have been obtained. Methods for visual and colorimetric assessment of antibiotic concentration using a smartphone camera have been developed. The optimal conditions for the indicator reaction have been selected with varying heating time and temperature. For a visual semi-quantitative assessment of the content of cephalexin, a color scale has been obtained. The metrological characteristics of the test method have been determined: the range of the determined contents is 0.5–16 mg/ml, the unreliability interval is 0.1–0.4 mg/ml, and the detection limit is 0.4 mg / ml. For the colorimetric assessment of the concentration of cephalexin, a linear dependence of the intensity of the Blue channel on the logarithm of the concentration of cephalexin (у = –96x + 144, r 2 = 0.99) has been constructed, and linear dependences of the area (у = –36986x + 62458, r 2 = 0.96) and perimeter (у = –270x + 786, r 2 = 0.93) from the logarithm of the concentration of cephalexin have been obtained. The range of the determined contents was 0.1–16 mg/ml, the lower limit was 0.1 mg / ml. The verification of the correctness of the developed test methods was carried out by the «introduced-found» method (Sr  0.13).

Adaptive Matrix Pattern Steganography on RGB Images

Almost all spatial domain image steganography methods rely on modifying the Least Significant Bits (LSB) of each pixel to minimize the visual distortions. However, these methods are susceptible to LSB blind attacks and quantitative steganalyses. This paper presents an adaptive spatial domain image steganography algorithm for hiding digital media based on matrix patterns, named “Adaptive Matrix Pattern” (AMP). The AMP method increases the security of the steganography scheme of largely hidden messages since it adaptively generates a unique codebook matrix pattern for each ASCII character in each image block. Therefore, each ASCII character gets a different codebook matrix pattern even in different regions of the same image. Moreover, it uses a preprocessing algorithm to identify the most suitable image blocks for hiding purposes. The resulting stego-images are robust against LSB blind attacks since the middle bits of green and blue channels generate matrix patterns and hiding secrets, respectively. Experimental results show that AMP is robust against quantitative steganalyses. Additionally, the quality of stego-images, based on the peak signal-to-noise ratio metric, remains high in both stego-RGB-image and in the stego-blue-channel. Finally, the AMP method provides a high hiding capacity, up to 1.33 bits per pixel.

How Can We Record Reliable Information on Animal Colouration in the Wild?

Animal colouration is a phenotypic trait that can provide important information on species ecology and adaptation. Describing animal colours can be very challenging, and digital images may help in this difficult task. Obtaining an image with colours similar to those observed in nature is not trivial, as many factors can alter the final result. Some studies highlighted the importance of a proper post-production and analysis of the images to obtain the best results, but unfortunately very little attention has been paid to how to obtain standardised images suitable to be employed in zoological and ecological studies. This study aims to give evidence about the importance of shooting pictures in standardised condition to obtain reliable data on animal colourations. We provide a method that allows to obtain standardised pictures with colours that are comparable to those observed on wild animals. We used a method that creates an in situ standardised environment to shoot photos of relatively small animals. Our method allows to fully control lights, the factor that affect pictures the most. We also provided a test on the efficiency of this method. Using a colour checker card as reference, we compared the divergence of the Red-Green-Blue channel values obtained from pictures shot in complete darkness with those read by a colorimeter. The average divergence in RGB values between the colorimeter and the RAW images was about 4%. This divergence increased when light disturbance occurred. Our method highlighted the importance of the moment in which pictures are taken, and demonstrated that a fully controlled method is essential for obtaining reliable information on animal colourations, data that can be employed in ecological and evolutionary studies.

Cloud Masks Derived from the Mars Daily Global Maps and an Application to the Tropical Cloud Belt on Mars

An image processing technique is used to derive cloud masks from the color Mars Daily Global Maps (MDGMs) that are composed from the Mars Reconnaissance Orbiter (MRO) Mars Color Imager (MARCI) wide-angle image swaths. The blue channel of each MDGM is used to select cloud candidates and the blue-to-red ratio map is compared with a reference ratio map to filter out false positives. Quality control is performed manually. The derived cloud masks cover 1 Mars year from the summer of Mars year (MY) 28 to the summer of MY 29. The product has a 0.1° longitude by 0.1° latitude resolution and is available each day. This makes it possible to characterize the evolution of the tropical cloud belt from several new perspectives. The tropical cloud belt steadily builds up during northern spring and early summer, peaks near the early- to mid-summer transitional period, and rapidly declines afterward. From the perspective of cloud occurrence frequency and time mean, the cloud belt appears meandrous and zonally discontinuous, with minima in the Amazonis Planitia and Arabia Terra longitudinal sectors. A pronounced cloud branch diverges from the main cloud belt and extends from the Valles Marineris towards the Noachis and Hellas region. The cloud belt exhibits noticeable oscillatory behavior whereby cloud brightening alternates between the western and eastern hemispheres near the equator with a periodicity between 20 and 30 sols. The cloud belt oscillation occurred each Mars year around Ls = 140°, except for the Mars years when intense dust storms made disruptions. The phenomenon appears to be associated with an eastward propagating equatorial Kelvin wave with zonal wavenumber 1. This wave has a much longer wave period than the diurnal and semidiurnal Kelvin waves discussed in most of the previous studies and may be an important factor for the intra-seasonal variability of the tropical cloud belt. The convolution of clouds’ local time variation with MRO’s orbit shift pattern results in a seemingly highly regular 5-day traveling wave in Hovmöller diagrams of cloud masks.

DEEP CONVOLUTIONAL NEURAL STRATEGY FOR DETECTION AND PREDICTION OF MELANOMA SKIN CANCER

The research work has focused on detection and prediction of melanoma which is done by subjecting to features extraction, where the features of an image consisting of melanoma regions are detected by analysis and this analysis is done by considering the features like color and texture-based features learning strategy. These features are extracted by combining color and texture-based features extraction with deep convolutional features representation learning strategy. The colors of images are extracted by representing the colors of different channels into red, green and blue channel information. The combination of texture features extraction with color-based features extraction in addition to Alex net features extraction learning has made the system more robust and efficient toward the segmentation and classification of images. Further, the erected method involves convoluting the features of extracted information with color and texture-based method which has led our system to full convolution neural networks with images features extraction. The melanoma is detected and segmented with watershed segmentation, these segmented features are subjected to the proposed features extraction method, where the features are extracted by combining the methods of texture with color-based information. These colors are made available to the proposed method by analyzing the regions of melanoma images. The erected method does the task of features extraction by Weber law descriptors in combination with red, green, blue channels information extracted from features representation learning. The proposed method has yielded an accuracy of 94.12% of segmentation accuracy and a classification accuracy of 94.32% with respect to various other classification techniques.