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The data presents 75 chronic myeloid leukemia patients diagnosed over a period 6 years i.e. from 2002 to 2008. The most common presentation was splenomegaly and 97% achieved complete hematological response at median duration of 4.3 weeks. The uniqueness of this study is follow-up with molecular response monitoring. Nearly, 30% patients achieved major molecular response (MMoR) by 12 months. 70% of patients achieved MMoR by median time of 60 months. Only 10% of the patient who achieved MMoR by 18 months had lost their responses subsequently.

Ratcheting studies were carried out on Type 304LN stainless steel straight pipes and elbows subjected to steady internal pressure and cyclic bending load. The internal pressure for all the straight pipes was 35 MPa and in the case of elbows the internal pressure was varied for different elbows, ranging from 27.6 MPa to 39.2 MPa. Cyclic bending load was applied on the specimens by subjecting them to different levels of load-line displacement. The specimens have undergone significant ratchet swelling (ballooning), ovalization and consequent thinning of the cross-section during ratcheting. The straight pipes failed either by occurrence of through-wall crack accompanied by simultaneous ballooning, or bursting with simultaneous ballooning. All the elbows failed by occurrence of through-wall crack accompanied by simultaneous ballooning. Ratcheting behaviour of straight pipes and elbows were compared and it was generally inferred that ratcheting was more pronounced in straight pipes than in elbows.

This paper presents the capability and potential of artificial neural network models for determining the shelf life of processed cheese stored at 30°C. Archaeologists have discovered that as far back as 6000 BC raw cheese had been made from cow's and goat's milk. Since past many decades ripened cheese prepared from cow's milk is converted into processed cheese as a value added product, which has great demand due to its unique body and texture, aroma and flavour, and sensory attributes. Radial basis and multiple linear regression models were developed and compared with each other. Based on the results further regression equations were developed and solved, Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash-Sutcliffo Coefficient performance measures were used for testing prediction potential of the models. MLR model was observed to be superior to radial basis model for predicting the shelf life of processed cheese.

Ratcheting studies were carried out on Type 304LN stainless steel elbows, by applying steady internal pressure and cyclic bending. The elbows were of 168 mm nominal outer diameter and the average thickness varied from 14.7 mm to 15.1 mm. The elbows filled with water were pressurized between 27.6 MPa and 39.2 MPa. Cyclic bending load, under the opening and closing moments, was applied on the elbows at ambient temperature. During the ratcheting experiments, strains were measured at different locations in the curved and straight portions of the elbows using post-yield rosette strain gauges. Ratcheting strain and its rate of change were estimated at different locations of the elbows with increase in number of cycles. In the curved portion of the elbow, ratcheting strain was observed in the hoop direction at the intrados, crown and at a few other locations other than the extrados. No significant ratcheting was observed in both the axial and circumferential directions at the extrados location for all the specimens. The specimens failed by the occurrence of through-wall axial crack in the curved portion, at one of the crown locations, accompanied by simultaneous bulging.

The integrity assessment of the primary piping components needs to be demonstrated under normal operation cyclic loadings as well as under complex cyclic loadings of extreme magnitude as may come during a severe earthquake event. In order to understand material's cyclic plasticity and fatigue-ratcheting behaviour, systematic experimental and analytical investigations have been carried out on specimens of SA333Gr.6 carbon steel and SS304LN stainless steel. The material specification of SA333Gr.6 is same as used in Primary Heat Transport (PHT) piping of Pressurized Heavy Water Reactors (PHWRs) and material specification of SS304LN steel is same as proposed for Indian Advance Heavy Water Reactor's (AHWR's) Main Heat Transport (MHT) piping. The test program included the tensile, axial fatigue and uniaxial ratcheting tests to establish the material's mechanical properties and cyclic plasticity behavior. The results of these tests have been investigated in details using few popular finite element cyclic plasticity models to understand and quantify the material's cyclic plasticity behavior. The studies revealed the need to modify the Chaboche model to simulate the LCF/cyclic plasticity and ratcheting under different strain/stress amplitudes loading conditions. On accounting for modification, the Chaboche model nicely predicted the LCF and ratcheting response for all the tests. The tests, finite element analyses result and their interpretations have been presented in this paper.

An ad-hoc routing protocol is a caucus, or customary, that controls how nodes decide which way to route packets between computing devices in a mobile ad hoc network. Over the years, abundant routing protocols have been developed for ad hoc mobile networks. These can be categorized into table-driven and on-demand routing. The simulations have shown that there certainly is a need for a special ad-hoc routing protocol when mobility increases and security in mobile ad-hoc networks is an extensive area of research. This research paper is a compassing of research on ad-hoc routing protocols. It gives a sufficient amount of literature for the better understanding of the work ahead.

Elman artificial neural network models with single and multilayer for predicting shelf life of processed cheese stored at 7-8ºC were developed. Input parameters were: Body & texture, aroma & flavour, moisture, and free fatty acid, while sensory score was output parameter. Bayesian regularization was training algorithm for the models. The network was trained up to 100 epochs, and neurons in each hidden layers varied from 1 to 20. Transfer function for hidden layer was tangent sigmoid, while for the output layer it was pure linear function. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash - Sutcliffo Coefficient were used for comparing the prediction ability of the developed models. Elman model with combination of 4-17-17-1 performed significantly well for predicting the shelf life of processed cheese stored at 7-8º C.

Soft computing cascade multilayer models were developed for predicting the shelf life of burfi stored at 30 o C. The experimental data of the product relating to moisture, titratable acidity, free fatty acids, tyrosine, and peroxide value were input variables, and the overall acceptability score was the output variable. The modelling results showed excellent agreement between the experimental data and predicted values, with a high determination coefficient (R 2 = 0.993499439) and low RMSE (0.006500561), indicating that the developed model was able to analyze nonlinear multivariate data with very good performance, and can be used for predicting the shelf life of burfi.

This paper highlights the significance of Time-Delay ANN models for predicting shelf life of processed cheese stored at 7-8 o C. Bayesian regularization algorithm was selected as training function. Number of neurons in single and multiple hidden layers varied from 1 to 20. The network was trained with up to 100 epochs. Mean square error, root mean square error, coefficient of determination and nash Sutcliffe coefficient were used for calculating the prediction capability of the developed models. TimeDelay ANN models with multilayer are quite efficient in predicting the shelf life of processed cheese stored at 78 o C.

This paper presents the latency and potential of central nervous system based system intelligent computer engineering system for detecting shelf life of soft mouth melting milk cakes stored at 10 o C. Soft mouth melting milk cakes are exquisite sweetmeat cuisine made out of heat and acid thickened solidified sweetened milk. In today's highly competitive market consumers look for good quality food products. Shelf life is a good and accurate indicator to the food quality and safety. To achieve good quality of food products, detection of shelf life is important. Central nervous system based intelligent computing model was developed which detected 19.82 days shelf life, as against 21 days experimental shelf life.

This paper presents the capability of Time–delay artificial neural network models for predicting shelf life of processed cheese. Datasets were divided into two subsets (30 for training and 6 for validation). Models with single and multi layers were developed and compared with each other. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash -Sutcliffo Coefficient were used as performance evaluators, Time- delay model predicted the shelf life of processed cheese as 28.25 days, which is very close to experimental shelf life of 30 days.

The paper deals with uniaxial ratcheting phenomenon of cyclic plasticity behavior of the materials SA333 carbon Manganese steel. A mechanistic model for the ratcheting phenomenon has been proposed. It is observed that von Mises yield criterion together with Chaboche’s kinematic hardening rules are not sufficient to model ratcheting phenomenon. Other associated phenomena like plastic strain memory surface, back stress memory points and over all the extra hardening behavior have to be incorporated to get a complete material model for ratcheting. The proposed model assembled all these ideas together with von Mises yield criterion and Chabache’s kinematic hardening rule. Low cycle fatigue tests and uniaxial ratcheting tests have been conducted for the materials. The material constants are identified and derived from experimental results. The ratcheting coefficients have been properly calibrated with these material constants. The material model, as mentioned above, for the ratcheting phenomenon has been implemented in an elastic plastic finite element code. The ratcheting results for different stress controlled ratcheting loads have been computed. The good feature of this model is that it reduces to symmetric low cycle fatigue model when loop closes.

Soft mouth melting milk cakes from water buffalo milk were prepared by using milk collected from Experimental Dairy, National Dairy Research Institute, Karnal, India. This milk was standardized to 6% fat. Time-delay and linear layer (design) intelligent computing expert system models were developed for predicting shelf life of soft mouth melting milk cakes stored at 6C. Linear layer (design) model gave best outcomes (MSE: 0.000293366, RMSE: 0.017127919, R: 0.996479613). Regression equations were developed based on these outcomes, shelf life was predicted 49.54 days. The predicted value is close to the experimentally obtained shelf life of 50 days. Therefore, from the study it is concluded that intelligent computing expert system models are effective tool predicting the shelf life of soft mouth melting milk cakes. General Terms Artificial Neural Networks, Neurons, Prediction

The Anderson–Gruneisen parameter ( δ ) is of considerable importance to Earth scientists because it sets limitations on the thermo-elastic properties of the lower mantle and core. However, there are several formulations on the Gruneisen parameter, which are in frequent use and predict varying dependence of δ as a function of temperature. In this paper, the expressions for thermal expansion, thermal expansion coefficients and bulk modulus are obtained considering the anharmonic dependence on temperature and are applied to study these constants to alkaline earth oxides. Using the derived expressions, we have shown that different parameters on which the Anderson–Gruneisen parameter ( δ ) depends are temperature dependent, but above all the Anderson–Gruneisen parameter ( δ ) is independent of temperature. The results obtained have been found to be comparable to experimentaldata.

Background: To study the occurrence of hypocalcaemia in neonates with physiological unconjugated hyperbilirubinemia after 48 hours of phototherapy or at the end of phototherapy, in case duration of phototherapy was less than 48 hours.Methods: This prospective study was conducted on 100 term neonates (61 males and 39 females) admitted to Neonatal intensive care unit of Teerthankar Mahaveer Medical College, Moradabad with unconjugated hyperbilirubinemia and requiring phototherapy. Total Serum bilirubin levels and serum calcium levels were checked before and after phototherapy. Neonates were assessed for clinical features of hypocalcemia i.e. jitteriness, irritability/excitability, lethargy and convulsions.Results: After phototherapy, there was hypocalcemia in 35.0% neonates. The difference between pre and post phototherapy serum calcium levels were found to be statistically significant (p

‘Fatigue Ratcheting’ is a phenomenon which leads to reduction in fatigue life of a structural component by loss of ductility due to cycle-by-cycle accumulation of plastic strain. One real-life example of a situation with fatigue ratcheting possibility is piping of power plants subjected to internal pressure (primary load) and cyclic bending (secondary load). Fatigue ratcheting studies were carried out on TP304 LN stainless steel straight pipes of 168 mm outer diameter subjected to steady internal pressure and four point cyclic bending. The length and average thickness of the pipes were 2800 mm and 15 mm respectively. The thickness was reduced to 12 mm in the gauge length portion of 200 mm at the centre of the pipe. Post-yield two element rosette strain gauges were mounted at various locations within the gauge length to measure the longitudinal and circumferential strains. The pipes were filled with water and pressurized; the pressure was maintained at 35 MPa till the first through-thickness crack was observed. Cyclic bending load was applied on the pipes by subjecting them to different levels of load-line displacements. Number of cycles corresponding to through-thickness crack/s and final failure of the component were recorded. During the tests, load, load-line displacement and deflections at three locations were continuously monitored. Local bulging, ovalization and consequent thinning of the pipe cross-section were observed due to fatigue ratcheting. These ratcheting studies on pressurized piping components of power plants give valuable inputs necessary for designing the components and assuring the integrity of pressure boundary under design basis loads such as loads arising during an earthquake event.

The present study deals with the elastic behaviour of diborides (BeB 2 , MgB 2 and NbB 2 ) under high pressure with the help of equation of state (EOS) using the elastic data reported by Islam et al. It is concluded that EOS, which are based either on quantum statistical model or  pseduopotential model, only are capable of explaining high pressure behaviour of the solids under study.  Moreover the value of first order pressure derivative of bulk modulus at infinite pressure ( K infinity ) is greater than 5/3 and thus the diborides under study do not behave as Thomas-Fermi electron gas under high compression.  Keywords : Equation of state; High Pressure; Diborides.  © 2009 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.  DOI: 10.3329/jsr.v1i2.1189 Â

Thromboembolism during aneurysm coiling is a known complication with almost all thromboembolic phenomenon occurring ipsilateral to the side of vessel catheterization and sometimes bilaterally. A case is reported in which thromboembolism occurred exclusively on the opposite side of vessel catheterization, the first case to be reported, to our knowledge.

s / International Journal of Surgery 12 (2014) S13eS117 S18 postoperative complications was significantly higher in Monklands compared toWishaw (p

In this work, Radial Basis (Exact Fit) and Radial Basis (Fewer Neurons) artificial neural network (ANN) models were developed to evaluate its capability in predicting the solubility index of roller dried goat whole milk powder. The ANN models were trained with a data file composed of variables: loose bulk density, packed bulk density, wettability and dispersibility, while solubility index was the output variable. The modeling results showed that there is an agreement between the experimental data and the predicted values, with coefficient of determination and Nash-Sutcliffe coefficient close to 1. Therefore, this method may be effective for rapid estimation of solubility index of roller dried goat whole milk powder.

Cloud computing is a multi million dollar business. As more and more enterprises are adopting cloud services for their businesses, threat of security has become a big concern for these enterprises and cloud users. This review describes the latest threats and risks associated with cloud computing and suggests techniques for better privacy and security of data in cloud environment. Threats and risks associated with cloud service models (SaaS, PaaS and IaaS) along with cloud deployment models (public and private) are thoroughly discussed with solutions. The security & privacy levels in cloud computing are illustrated and security solutions & standards for cloud computing are proposed. Encryption techniques for securing data in cloud environment are listed and latest security tools for cloud computing are included in this communication.

Artificial Neural Networks (ANNs) have been applied in several areas, viz ., science and technology, engineering, agriculture, life sciences and medicine as they have a remarkable ability to provide accurate results. This communication highlights the systematic information available in the literature concerning the implementation of ANN models for predicting properties of dairy products, fruits, vegetables and meat. The information presented in this review paper shows that over the last decade research related to ANN based predictive modelling in food science has picked up.

The purpose of this study is to develop artificial neural network (ANN) models for predicting shelf life of processed cheese stored at 7-8oC. Body & texture, aroma & flavour, moisture and free fatty acids were taken as input parameters, and sensory score as output parameter for developing the models. The developed Cascade single layer ANN models were compared with each other. Bayesian regularization was used for training ANN models. Network was trained with 100 epochs, and neurons in each hidden layer(s) varied from 3 to 20. Cascade ANN models very well predicted the shelf life of processed cheese.

Feedforward multilayer machine learning artificial neural network (ANN) models were established for predicting shelf life of processed cheese stored at 7-8o C. Soluble nitrogen, pH, standard plate count, yeast & mould count, and spore count were input variables, and sensory score was the output variable. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash–Sutcliffe Coefficient were used for comparing the prediction ability of the developed models. Feedforward ANN model with combination of 5à16à16à1 simulated best with high R2: 0.998717294, suggesting that multilayer machine learning models can predict shelf life of processed cheese.

A 22-year-old man had cerebral venous sinus thrombosis and his angiogram incidentally revealed an absent left common carotid artery with bovine origin of the left external carotid artery. There was also an associated low bifurcation of the right common carotid artery and basilar artery fenestration. The absence of a common carotid artery is a very rare angiographic finding, and an association with a bovine origin of the left external carotid artery has not been reported previously in the literature. Here we provide a description of the case along with a review of the literature and embryology.

A 22-year-old man had cerebral venous sinus thrombosis and his angiogram incidentally revealed an absent left common carotid artery with bovine origin of the left external carotid artery. There was also an associated low bifurcation of the right common carotid artery and basilar artery fenestration. The absence of a common carotid artery is a very rare angiographic finding, and an association with a bovine origin of the left external carotid artery has not been reported previously in the literature. Here we provide a description of the case along with a review of the literature and embryology.

Introduction: Chemo-radiation preceded by induction chemotherapy is reported valuable alternative to laryngectomy in laryngeal cancer for larynx preservation.This study was performed to assess the influence chemo radiation on preservation of larynx. Materials and Methods: Two hundred and fifty sequential patients treated from January 2012 to December 2012 in our institute were reviewed and who were available for follow-up in this retrospective study. Total dose of 66-70 Gray was used at 2 gray per fraction daily for five days week were used. Larynx preservation rate at 3 years of median follow-up were analyzed. Results: Among 250 patients, larynx preservation was possible in 170 patients (68%). With chemo-radiation, excellent preservation of larynx was achieved in stage II (78%) disease, while in advanced stage III and stage IVA, larynx preservation was 67.06% and 64.35%, respectively. Conclusion: Chemo-radiation (either neoadjuvant chemotherapy followed by chemo-radiation or concurrent chemo-radiation) has better larynx preservation rate in early as well was advanced laryngeal cancer patients.

Purpose/Objective(s): In India > 1 million new cases of cancer diagnosed every year. 40-50% of these cases are of head and neck cancer because of tobacco overuse. In our institute we have almost 1000-1300 new cases of Carcinoma Buccal Mucosa reported every year. From which 70-75% are surgically operable. For post-operative Radiotherapy treatment, we treat most of our patients by 2 Dimensional conventional treatments. Purpose of this study is to assess toxicity & long term results of postoperative carcinoma buccal mucosa cases treated by 2 Dimensional conventional treatment planning. Materials/Methods: From January 2009 to January 2012, almost 1980 postoperative cases of Carcinoma Buccal mucosa were referred for radiotherapy treatment. From which 1584 cases were suitable for postoperative 2 Dimensional Conventional planning. In selected cases, 71%, 18%, 11% cases were of Stage IV, III, II (close margin) respectively. Postoperative chemotherapy and radiotherapy was indicated in 475 patients. For all patients Plaster of Paris cast was prepared & X-ray was taken on Simulator machine. Target volume was drawn on x-ray & treatment plan generated on contour drawn with 90-95% isodose line covering the target, with hot spot of +10% on 2D Plato treatment planning system. All patients were treated with unilateral Anterior Posterior Lateral wedge pair technique for buccal mucosa and unilateral lower neck was given in indicated patients. Dose prescribed was 60 Gy/30#, 2Gy/#, 5 days a week, total 6 weeks treatment. Treatment plan verified on day 2 and treatment started. In patients where postoperative chemotherapy and radiotherapy was used, chemotherapy was given Cisplatin 30mg/m[2] every weekly for 6 weeks. In most of the patients, treatment break was not required. All patients completed treatment successfully. Patients were assessed for locoregional control, acute & late toxicity and followed up for 3 years for disease free survival and overall survival. Results: Grade II & III acute mucositis was 82% & 18% respectively in 1109 patients who received only postoperative radiotherapy. For patients who received postoperative radiotherapy and chemotherapy Grade II and Grade III acute mucositis was seen in 75% & 25% respectively and side effects related to Cisplatin were managed conservatively. Almost all patients had Grade II skin reactions. Grade III skin reactions were observed in 8% of patients on post operative radiotherapy alone and 19% of patients on postoperative radiotherapy and chemotherapy but were manageable. All patients tolerated treatment well. For 1584 patients, follow up dropout rate was 20%. None of the patients developed significant late toxicity. As opposite parotid spared, no late complication of xerostomia observed. For 1268 patients, 1-, 2-, 3- year locoregional control rates were 82%, 75%, 68% respectively. Disease free survival rate was 63% (799 patients) & overall survival was almost 55% (697 patients) at median follow up for 40 months. Conclusion: 2D Conventional Radiotherapy Treatment Planning in our set up has shown very good results with almost 50% survival rates. It is less toxic treatment with fewer complications & less time consuming. It is highly cost effective treatment approach & results are very much encouraging.

Introduction: Concurrent chemo-radiation is the main treatment in locally advanced cervical cancer. The change of bladder and rectum volume may lead to change in the positions of these structures and target volume during MUPIT implant which may lead to variation in dose to the organ at risk and target. Materials and Methods: Ten patients of gynecological malignancy were included. MUPIT template was positioned under anesthesia. CT scan was done for the contouring of bladder, rectum, and target and for planning purpose which generates plan (P1). CT scan was repeated before the third fraction of the treatment (CT2). The resultant plan (P2) was analyzed qualitatively and quantitatively. Results: Bladder volume variations of 88.18% to -68.15% were noted. This change in volume lead to differences in the maximum dose in bladder between fractions. The maximum dose variation ranged from 62.53% to -21.49%. The rectal volume variation ranges 11.71% to -46.20% due to the rectal filling. High variation in maximum dose to the rectum were observed which might be due to rectal filling. CTV volume is increased by 19.48% while in other by 19.05% and in all other patients the volume is decreased. CTV volume maximum decreased by 30.54% which might be due to decrease in edema developed during procedure. The volume variation in CTV is in range of 19.48% to -30.54%. Conclusion: It is proposed that re-planning using repeat CT scan is required before third fraction implementation.

This paper describes the potential of machine learning feedforward algorithm for predicting shelf life of processed cheese. Soluble nitrogen, pH, Standard plate count, Yeast & mould count, and Spore count were taken as input parameters, and sensory score as output parameter for developing feedforward single and multilayer models. The dataset was divided into two disjoint sets, one for training and the other for validation. Backpropagation algorithm based on Bayesian Regularization was selected for training the feedforward models. Mean square error, root mean square error, coefficient of determination and nash - sutcliffo coefficient performance measures were used for testing prediction potential of the developed models. The study revealed that feedforward models are good in predicting shelf life of processed cheese.

“Ratcheting” is a phenomenon which leads to reduction in fatigue life of a structural component by loss of ductility due to cycle by cycle accumulation of plastic strain. Ratcheting occurs in a structure subjected to a combination of steady/sustained and cyclic loads such that the material response is in inelastic region. Ratcheting studies were carried out on Type 304LN stainless steel elbows, subjected to steady internal pressure and cyclic bending. The elbows filled with water were pressurized between 27.6 MPa and 39.2 MPa. Cyclic bending load, under opening and closing moments, was applied on the elbows at ambient temperature. Number of cycles corresponding to occurrence of a through-wall crack was recorded. Crack was observed in the bent portion at one of the crown locations in all the four specimens. Maximum strain was observed at the intrados and crown locations of the elbows. The ratcheting strain increased with number of cycles at crown and intrados locations. However, the strain accumulation rate decreased with number of cycles. Strain was observed to be minimum at the extrados location and the same stabilized toward the end of the tests. The specimens have failed by occurrence of through-wall axial crack accompanied by simultaneous ballooning. The ballooning was found to be varying from 3.8% to 5.8% with respect to the original circumference in the bent portion. The reduction in thickness was found to be around 12%–15%.

In 21 st century one of the biggest blessings to hit the world is social networking. Websites like facebook, twitter, Google+ provide a great platform to connect with friends and relatives, forming groups, communities, uploading videos and images, expressing freedom of expression, discussion forums, business, buy and selling opportunities, get togethers and many more things. Connectivity, access, features, and versatility are exceedingly well supported by these social networking sites; even a mobile user with an internet connection can access them. The presence of social networking sites has made life comfortable and enjoyable.

Artificial Neural Networks (ANNs) have been implemented in almost every field, viz., science, technology, medicine and engineering as they have proved useful tools for obtaining the desired output including the analyses and shelf life prediction in case of food products. This review discusses the systematic information available in the literature concerning the implementation of ANN models for shelf life determination of milk, various dairy products, viz., yoghurt, chocolate, butter, cheese, kalakand, dairy confections and milk based coffee drinks, which would be very useful for dairy industry, consumers, wholesalers, retailers, regulatory agencies, food researchers and academicians.

Time-delay single layer artificial neural network models were developed for estimating the shelf life of burfi stored at 30oC. Input variables for the models were moisture, titratable acidity, free fatty acids, tyrosine, and peroxide value, while the overall acceptability score was taken as output variable. Mean square error, root mean square error, coefficient of determination and Nash - sutcliffo coefficient were applied in order to compare the prediction ability of the Time-delay single layer models. The combination of 5-1-1 showed a very high correlation between the training and validation data, establishing that the developed models are effective in predicting the shelf life of burfi.

Feedforward multilayer models were developed for predicting shelf life of processed cheese stored at 30 o C. Input variables were Soluble nitrogen, pH, Standard plate count, Yeast & mould count and Spore count. Sensory score was taken as output parameter for developing feedforward multilayer models. Mean square error, root mean square error, coefficient of determination and nash - sutcliffo coefficient performance measures were implemented for testing prediction potential of the soft computing models. The study revealed that soft computing multilayer models can predict shelf life of processed cheese. DOI: http://dx.doi.org/10.11591/ij-ict.v1i1.506

Time-delay single and multi layer models were developed for predicting shelf life of processed cheese stored at 30 o C. Processed cheese is very nutritious dairy product, rich in milk proteins and milk fat. For developing computational neuroscience models,experimental data relating to body & texture, aroma & flavour, moisture, free fatty acids were taken as input variables, while sensory score as output variable. Mean Square Error, Root Mean Square Error, Coefficient of determination and Nash - Sutcliffo Coefficient were applied in order to compare the prediction performance of the developed computational models. The results of the study established excellent correlation between experimental data and the predicted values, with a high determination coefficient. From the study it was concluded that artificial neural expert time-delay models are good for predicting the shelf life of processed cheese. DOI: http://dx.doi.org/10.11591/ijece.v2i3.353

Artificial neural networks (ANN) have been developed as generalizations of mathematical models of biological nervous systems. Generalized regression (GR) and multiple linear regression (MLR) models for shelf life prediction of dairy product were developed. Results of both the models were evaluated with three types of prediction performance measures viz., mean square error, root mean square error and coefficient of determination R2, and compared with each other. Based on these results, regression equations were developed. From the study, it is concluded that ANN and statistical computerized methods can be employed for predicting shelf life of dairy products. Key words: Artificial neural networks (ANN), shelf life, dairy product, prediction, generalized regression, multiple linear regression.

Cascade multilayer artificial neural network (ANN) models were developed for estimating the shelf life of processed cheese stored at 7-8 o C.Mean square error , root mean square error,coefficient of determination and nash - sutcliffo coefficient were applied in order to compare the prediction ability of the developed models.The developed model with a combination of 5a16a16a1 showed excellent agreement between the actual and the predicted data , thus confirming that multilayer cascade models are good in estimating the shelf life of processed cheese. DOI: http://dx.doi.org/10.11591/ij-ai.v1i1.336

Time–delay artificial neural network (ANN) single layer and multilayer artificial models were developed for predicting the shelf life of processed cheese stored at 7-8o C. Soluble nitrogen, pH; standard plate count, yeast & mould count, and spore count were input variables, and sensory score was output variable. The results showed excellent agreement between training and validation data with high coefficient of determination and nash sutcliffo coefficient, thus suggesting that the developed models are good for predicting the shelf life of processed cheese.

Radial Basis (Fewer Neurons) and Multiple Linear Regression (MLR) models were developed and compared for predicting the shelf life of processed cheese stored at 30o C. Soluble nitrogen, pH, Standard plate count, yeast & mould count, and spore count were taken as input parameters, and sensory score as output parameter. Mean square error, Root mean square error, Coefficient of determination (R2) and Nash - Sutcliffocoefficient (E2) were applied in order to compare the prediction ability of the models. Results showed high correlation between the training and validation data with high R2 and E2 values; thus suggesting that the developed models are efficient for predicting the shelf life of processed cheese. From the study, it was revealed that Radial Basis (Fewer Neurons) model was superior over MLR model for predicting the shelf life of processed cheese.

Surgical site infection (SSI) is the fourth commonest healthcare-associated infection and complicates at least 5% of open operations. In a randomized clinical trial, antimicrobial-coated sutures were compared with their conventional counterparts, polyglactin and poliglecaprone, for skin closure after breast cancer surgery to assess their role in reducing the rate of SSI.Between November 2008 and February 2011, 150 female patients presenting with breast cancer to a single center were randomized to skin closure with antimicrobial-coated or plain sutures. Postoperatively, SSI was defined using the U.S. Centers for Disease Control and Prevention (CDC) definitions and scored using the ASEPSIS or Southampton systems by trained, blinded observers with close post-discharge surveillance and patient diaries. Surgeons and patients were blinded to the type of suture used.Using CDC criteria, the overall rate of SSI was 18.9% at six weeks. Six patients (4.7%) needed intervention or readmission for SSI. Skin closure with antimicrobial sutures showed a non-statistically significant reduction in the SSI rate, to 15.2%, compared with conventional sutures (22.9%). A uniform tendency for fewer SSIs in the antimicrobial-coated suture group was found using ASEPSIS and Southampton scores, but again, the difference was not statistically significant.The previously reported high rate of SSI related to breast surgery was confirmed. Using statistical modeling and earlier reports, the study was powered to show a difference using ASEPSIS scores, but the modification used in this trial failed to find a difference. Finding a statistically significant difference would have needed two to three times the number of patients recruited. Further evaluation of antimicrobial-coated sutures is merited, particularly if used as part of a care bundle to reduce SSI after breast cancer surgery.

In developing countries like ours with a large number of tuberculosis (TB) cases and limited resources, the diagnosis of TB relies primarily on smear microscopy for Acid Fast Bacilli (AFB) but its sensitivity is limited in paucibacillary cases.To evaluate the increase in efficacy of smear microscopy when smears are prepared from clinical samples after concentration by Petroff's method and stained by Auramine O (AO) fluorescent dye as against Ziehl Neelsen (ZN) staining of similar taking culture as the gold standard.Smears were prepared from 393 clinical samples both by direct and after Petroff's concentration and examined by fluorescent microscopy and Ziehl Neelsen method .The concentrated material was also cultured on Lowenstein Jensen media and the results of the two microscopy methods were compared with the culture results taken as the gold standard.Mycobacterial growth was detected in 137 (35.77%) specimens, out of which three were non-tubercular mycobacteria. Using culture as the reference method, the sensitivity of direct staining was 55.55% for ZN and 71.85% for AO. Direct fluorescent microscopy detected 9.29% paucibacillary sputum samples that were missed on ZN staining. On concentration, the sensitivity increased by 6.67% for ZN and 11.11% for AO. The sensitivity of AFB smear microscopy increased by 27.41% and was statistically significant (p =.001) when both methods were combined. The specificity was 99.19% for both ZN and AO.Fluorescent microscopy has higher sensitivity and comparable specificity which is further enhanced by concentration. Now with the advent of newer inexpensive Light Emitting Diode (LED) based fluorescent microscopes (FM), which are easier to use, fluorescent microscopy can be widely used even in peripheral laboratories where culture facilities are not available.

A 40-year-old gentleman was admitted with history of bullet injury to neck with bullet lodged in the ramus of mandible. He sustained fracture mandible with fracture of C2 transverse foramen. He had no neurological deficit at the time of admission and a cerebral digital subtraction angiogram was done to assess the vascular system of head and neck. The left common carotid injection revealed normal internal carotid flow with dissection and complete