Cor triatriatum sinister with situs inversus totalis in an infant.

Cor triatriatum sinister is a rare congenital cardiac malformation characterized by a membrane in the left atrium which separates the left atrium into the proximal and distal chambers.Association of cor triatriatum is extremely rare with situs inversus totalis. This article reports a rare case of cor triatriatum sinister with situs inversus totalis in a 5 month old female infantpeer-reviewe

Segmentation and Classification of Brain Tumor Extraction using K Means and Genetic Algorithm

A Brain Cancer is very serious disease causing deaths of many individuals. The detection and classification system must be available so that it can be diagnosed at early stages. Cancer classification has been one of the most challenging tasks in clinical diagnosis. At present cancer classification is done mainly by looking through the cells’ morphological differences, which do not always give a clear distinction of cancer subtypes. Unfortunately, this may have a significant impact on the final outcome of whether a patient could be cured effectively or not. We have proposed a methodology to segment and classify the brain MRI image using k-means clustering algorithm and Genetic algorithm

Green twist to an old theme. An eco-friendly approach

Owing to present environmental awareness, attempts are being made toward the evolution of environmentally benign processes using solid-supported reagents and microwave-assisted reactions. A newly developed, nonmetallic oxidative reagent, "clayan", has been exploited for various reactions such as deprotection, oxidation, oxidative coupling, and nitration and bromination of activated and deactivated arenes. In another green chemistry endeavor, reactions such as reduction and cyclization have been successfully carried out in dry media under microwave irradiation. The nonsolvent reaction, experimental simplicity, and enhanced selectivity are the main attractive features of the approach

Brain Tumor Extraction using Genetic Algorithm

A Brain Cancer is very serious disease causing deaths of many individuals. The detection and classification system must be available so that it can be diagnosed at early stages. Cancer classification has been one of the most challenging tasks in clinical diagnosis. At present cancer classification is done mainly by looking through the cells� morphological differences, which do not always give a clear distinction of cancer subtypes. Unfortunately, this may have a significant impact on the final outcome of whether a patient could be cured effectively or not. We have proposed a methodology to segment and classify the brain MRI image using k-means clustering algorithm and Genetic algorithm

Revista ew on Brain Tumour Detection using Image Processing

The Automatic Support Intelligent System is used to detect Brain Tumor through the combination of neural network and fuzzy logic system. It helps in the diagnostic and aid in the treatment of the brain tumor. The detection of the Brain Tumor is a challenging problem, due to the structure of the Tumor cells in the brain. This project presents an analytical method that enhances the detection of brain tumor cells in its early stages and to analyze anatomical structures by training and classification of the samples in neural network system and tumor cell segmentation of the sample using fuzzy clustering algorithm. The artificial neural network will be used to train and classify the stage of Brain Tumor that would be benign, malignant or normal. The Fast discrete curvelet transformation is used to analysis texture of an image. In brain structure analysis, the tissues which are WM and GM are extracted. Probabilistic Neural Network with radial basis function is employed to implement an automated Brain Tumor classification. Decision making is performed in two stages: feature extraction using GLCM and the classification using PNN-RBF network. The segmentation is performed by fuzzy logic system and its result would be used as a base for early detection of Brain Tumor which would improves the chances of survival for the patient. The performance of this automated intelligent system evaluates in terms of training performance and classification accuracies to provide the precise and accurate results. The simulated result enhances and shows that classifier and segmentation algorithm provides better accuracy than previous methodologies

Multisystem Langerhans cell histiocytosis in an infant: A case report and review of literature

Langerhans cell histiocytosis (LCH) is a rare disease of childhood which originates from marrow-derived immature myeloid dendritic cells of skin and visceral organs with incompletely understood etiopathogenesis. An 11-month-old infant presented with fever, pallor, multiple erythematous, crusted, scaly hypopigmented macules, and shiny colored papules over scalp, forehead, and trunk along with hepatosplenomegaly. Persistent pancytopenia, punched out lesion on a brain scan, and multinucleated giant cells with eosinophilic cytoplasm admixture with eosinophils and lymphocytes on skin biopsy were seen. Immunohistochemistry was positive for CD1a and S100. The patient was treated with vinblastine and steroid, but unfortunately parents did not complete the therapy. A high index of suspicion is necessary to make timely diagnosis and therapy to minimize the frustration felt by parents/patients

Image Encoding & Decoding Using Base64 Technique and It�s Wireless Transmission Using Li-Fi

Li-Fi is one of the advanced and fastest technology among other available data transmission technologies in the world of data communication. The high bandwidth and immunity to interference ability of Li-Fi makes it unique from other available wireless technologies. It could be used in areas where high data transfer is much required and other wireless technologies are restricted due to their hazardous signal radiations. It could be useful in variety of application including audio transmission, video transmission, text transmission and image transmission. Li-Fi communication is also called as the Visible Light Communication (VLC) since we make the use visible light for transmitting the data from transmitter to receiver. In this article a prototype is designed to transfer a 2D image using UART serial communication from one PC to another PC using VLC

Data Communication Using Li-Fi

Wireless data transmission demand is increased over the years. But due to lack of radio frequency spectrum and hazardous electromagnetic waves comes out from it Li-Fi appears as a new cheaper, greener, and healthier alternative to traditional Wi-Fi. Presently there are two trends being seen in the world of Wireless communication: First, the enrichment or extension of wireless services & second being increased in demand by users for these services. The need is fulfilled by RF spectrum but the usage is very limited. So the emerging technology-Li-Fi came into picture, which uses visible light as a source of communication. The recent advancement in the wireless communication world has made VLC as one of the high-speed, efficient, secured and cheaper optical wireless communication technology. [12] This research paper focuses on required hardware for transmission of text Li-Fi system. The PCB of Transmitter and Receiver are designed by using PCB Artist 4.0 tool. The Microcontroller ATMega16 has been used for the purpose of performing operation at transceiver section. Its programming is done by using AVR studio. Successful transmission and reception of text is carried out on the transceiver. Hence this research paper shows an innovative way of designing a transceiver with low cost electronic hardware components and using already available white LED light bulb. This Li-Fi technology envisions a future where data for smart phones, laptops and tablets will be transmitted in an economic and ecofriendly medium of light in room

Serial Data Transmission using Visible Light Communication

Li-Fi is a label for wireless-communication system using light as a carrier instead of radio frequencies as in Wi-Fi [1]. The light waves cannot penetrate walls hence Li-Fi (Light-Fidelity) can be used in sensitive areas such as in Aircraft [13, 15]. It can be implemented using white-LED light bulbs at the downlink transmitter. In these types of devices a constant current is applied for the purpose of illumination. However, by fast and subtle variations of the current, the optical output can be made to vary at extremely high speeds. Due to this characteristic of optical current it is used in Li-Fi setup. The operational procedure is very simple- if the LED is on, then transmit a 1, if it�s off then transmit a 0. The LEDs can be switched on and off very quickly, and hence it gives nice opportunities for transmitting data. All that is required is some LEDs and a controller that code data into those LEDs. All one has to do is to increase the rate at which the LED�s flicker [2] depending upon the data needs to be encode. Further enhancements can be made in this method, like we can use an array of LEDs for parallel data transmission, or using mixtures of red, green and blue LEDs. It can alter the light�s frequency with this approach each frequency encodes a different data Channel [5]. Such advancements promise a theoretical speed of 10 Gbps � meaning you can download a full high-definition film in just 30 seconds

Study of blood indices and high performance liquid chromatography (HPLC) in differentiation of β-thalassemia trait and iron deficiency anaemia

Background: Iron deficiency anemia (IDA) and beta thalassaemia trait (BTT) are two of the most common causes of microcytic anemia.It is essential to differentiate between the two, so as to avoid unnecessary iron therapy which is contraindicated in beta thalassaemia .We retrospectively evaluated the reliability of various indices for differential diagnosis of microcytosis and -TT in the same patient groups .Methods: A total of 200 patients were evaluated. We calculated 6 discrimination indices in all patients with anemia or suspected beta thalassemia. None of the subjects had  combined  IDA and -TT. The patient groups were evaluated according to  the Mentzer, Shine and Lal, England and Fraser,Srivastava, Green and King, Ricerca.Results: According to percentage correctly diagnosed criteria, Ricerca  and Mentzer  index are considered as the two best discrimination indices in differentiation between β thalassemia trait  and iron deficiency anaemia .Youden’s index showed the following ranking with respect to the indices’ ability to distinguish between -TT and IDA, Ricerca index >  Mentzer index > Green and King index >  Srivastava index >  Shine and Lal index > England and Fraser index.Conclusions: Ricerca  and Mentzer  index are considered as the two best discrimination indices in differentiation between β thalassemia trait  and iron deficiency anaemia.Keywords: Iron deficiency anemia (IDA) and beta thalassaemia trait (-TT)