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Calciphylaxis or calcific uremic arteriolopathy (CUA) is an infrequent complication in patients with renal failure. Its manifestations range from ischemia to gangrene especially in areas of adiposity. Penile calciphylaxis is very rarely seen. Treatment can be medical or surgical. Sodium thiosulphate has shown to be an efficient treatment. Here were present a case of 74-year-old male who presented with penile calciphylaxis and was treated successfully with oral sodium thiosulphate. [ABSTRACT FROM AUTHOR]

Eucalyptus oil consumption is well known to cause adverse effects on central nervous system like seizures, ataxia and unconsciousness. No antidote is available and treatment is largely supportive. We report a case of rhabdomyolysis with pigment cast nephropathy and acute kidney injury in a young female following eucalyptus oil consumption and its successful management. [ABSTRACT FROM AUTHOR]

Introduction: The two formulations of antihuman thymocyte immunoglobulin that are used as T‑cell depleting induction agents in renal transplantation are anti‑thymocyte globulins(ATG) thymoglobulin and (antiT‑lymphocyte globulin [ATLG]‑Grafalon‑formerly ATG‑Fresenius). Very few trials have compared these two formulations. In this retrospective study, we compared the incidence of infections, rejections, graft survival, mortality, and lymphocyte profile of ATG and ATLG. Materials and Methods: This was a single‑center retrospective study of 127 consecutive kidney‑alone transplant recipients from January 2014 to June 2019. Patients received 3 mg/kg of ATG or 4 mg/kg single dose of ATLG. CD 3 counts were done on day 3 of the transplant. Most of the recipients received standard triple immunosuppression of tacrolimus, mycophenolate mofetil, and prednisolone. Results: Fifty‑eight patients received ATG and 69 patients received ATLG. Baseline demographics were similar between the two groups. Death‑censored graft survival(99%) (P = 0.258) and biopsy‑proven acute rejection (BPAR) (32% vs. 29%, P = 0.128) were similar in both groups. Graft survival was better in ATLG group (92.7% vs. 87.5% P = 0.020). Bacterial infections (41.1% vs. 27.6%, P = 0.03) and sepsis‑related mortality (11.54% vs. 4.34% P = 0.02) were significantly higher in the ATG group. Conclusion: ATLG, when used as an induction agent, was associated with a lesser rate of bacterial infections and sepsis‑related mortality, but better graft survival as compared to ATG but has comparable BPAR, death‑censored graft survival, and viral/fungal infections. [ABSTRACT FROM AUTHOR]

Diabetes Mellitus is one of the most important serious challenges in both developed and developing countries. It leads to significant medical complications including ischemic heart disease, stroke, nephropathy, retinopathy, neuropathy and peripheral vascular disease. Early identification of patients at risk of developing diabetes is a major healthcare need. Thus cloud based healthcare is the one and only solution. In this paper, we use cloud computing for the creation and organization of cloud based health care services and also use classification technique. The diagnosis of diabetes is used to classifies the individual users as "Diabetic" or "Non-Diabetic" through Naïve Bayes classifier. [ABSTRACT FROM AUTHOR]

Automatic document classification process is the important area of research in the field of Text Mining(TM). Text mining is the process of discovering the interesting pattern or knowledge from huge amount of data. The document classification process used in many domains. Here, to take the classification process is apply SMS spam classification. The benchmarked dataset is used and the same data set is processed in various ML algorithms of Naïve Bayes, Support Vector Machine, Decision Tree and Logistic Regression model. In this paper evaluates the results of various machine learning algorithms for automatic document classification in SMS spam classification. [ABSTRACT FROM AUTHOR]

Tuberous sclerosis complex (TSC) represents a genetic disorder of hamartoma formation in many organs; particularly the skin, brain, eye, kidney, and heart. We are reporting a case of TSC in a patient and his daughter. The interesting feature is the appearance of the facial angiofibromas in this patient. In this patient, there was a sudden spurt in growth of these lesions in the last 7 months at the age of 50 years giving an appearance of nodular growth, misleading the diagnosis. The lesion was biopsied to know any secondary changes had occurred. There is no mention in the literature regarding such a rapid growth or any secondary changes occurring in angiofibromas. Neither the biopsy revealed any secondary changes. Hence, this interesting phenomenon has been reported. Is it apt to call it as "ANGIOFIBROMA PROLIFERANZA" or "ANGIOFIBROMA VIPULA"? (The word VIPULA in local South Indian Kannada language is prolific growth). [ABSTRACT FROM AUTHOR]

The chief aim of this paper is to develop an effective approach to the issue of load profile clustering by applying Improved Replacement In Bee Optimization algorithm (IRIBO). While, intelligent metering solutions like Automated Meter Reading (AMR), Automated Meter Infrastructure (AMI) are in place to address the current issues prevailing in the domain of electricity markets, algorithm using Improved Replacement In Bee Optimization has been proved beneficial and uncomplicated to apply within a selective database. In this study Load Profile (LP) clustering distribution networks based on the shape of the load profile was studied for fitness function in the selected LP clustering. The results clearly indicate that LP clustering has advantages in providing metering solutions to consumers who do not possess digital metering which can be easily operated with trivial changes in the calibrations. [ABSTRACT FROM AUTHOR]

Ensuring security biometrically is essential in most of the authentication and identification scenario. Recognition based on iris patterns is a thrust area of research cause to provide reliable, simple and rapid identification system. Machine learning classification algorithm of support vector machine [SVM] is applied in this work for personal identification. The profuse as well as unique patterns of iris are acquired and stored in the form of matrix template which contains 4800 elements for each iris. The row vectors of 2400 elements are passed as inputs to SVM classifier. The SVM generates separate classes for each user and performs matching based on the template's unique spectral features of iris. The experimental results of this proposed work illustrate a better performance of 98.5% compared to the existing methods such as hamming distance, local binary pattern and various kernels of SVM. The popular CASIA (Chinese Academy of Sciences - Institute of Automation) iris database with fifty users' eye image samples are experimented to prove, that the least Square method of Quadratic kernel based SVM is comparatively better with minimal true rejection rate. [ABSTRACT FROM AUTHOR]

We report an experimental proof of concept for speckle-based one-to-three non-line-of-sight (NLOS) free space optical (FSO) communication channels employing structured light shift-keying. A 3-bit gray image of resolution 100×100 pixels is encoded in Laguerre-Gaussian or Hermite-Gaussian beams and decoded using their respective intensity speckle patterns via trained 1D convolutional neural network. We have achieved an average classification accuracy of 96% and 93% using L G ml and H G pq beams, respectively, among all three channels. It demonstrates the directional independence and broadcasting capability of speckle-based decoding (SBD) in FSO communication using structured light. Further, we have extended the study from 2D to 1D SBD in one-to-three NLOS FSO communication channels to decrease the computational cost and to emphasize the importance of the 1D SBD approach.