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Introduction: Retinoblastoma (RB) is the most common paediatric intraocular malignancy. The Spleen Tyrosine Kinase (SYK) acts as a proto-oncogene crucial for RB cell survival and is absent in the normal retina, making it a valuable therapeutic target. Aim: Entospletinib, a selective oral SYK inhibitor currently in phase 2 trials for chronic lymphocytic leukaemia, was evaluated for its activity on the RB cell line Y-79. Materials and Methods: The effects of Entospletinib on cell proliferation and death of the human RB Y79 cells were assessed by MTT (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) assay, phase contrast microscopy and AO/EtBr dual labeling. The Annexin-V kit was used to quantify the cell mortality following treatment using flow cytometry. The mRNA levels of caspase-3, BAX, BCL-2, SYK, p53, TNF-and NF-κB were measured using RT-PCR to better understand the mechanism of action of this drug. Western blot was used to further validate the data. Results: Entospletinib treatment led to a time- and dose-dependent reduction in cell viability, with significant cytotoxicity observed at an IC50 of 61.3 μM/ml. Annexin V/Propidium Iodide (PI) staining demonstrated a dose-dependent increase in apoptosis. The treatment upregulated mRNA levels of Caspase-3, Bax, and p53 while downregulating SYK, TNF-α, and Bcl-2. RT-PCR and Western blot analyses confirmed a dose-dependent decrease in NF-κB/p65 expression. Conclusion: The study findings suggest that Entospletinib inhibits cell proliferation and induces apoptosis in RB cells by downregulating SYK/TNF-α/NF-κB/p65, highlighting its potential as a promising therapeutic candidate for RB.

The employee retention is being an emerging concept in the branches of Human Resource Management (HRM). The employee retention concept seems to be expensive and it is not globally adopted by all the pharmaceutical companies. The companies need to be aware of the value of efficient employees and their contribution to the economic growth of the companies. The primary aim of the management should be the employee retention which will enable the companies to reap benefits on the long run. As per various government and association medical representatives’ reports, the employee attrition rates in the pharmaceutical companies are high when compared to various sectors. This will create high level of mismatch between employee demand and supply for the medical representatives. The objective of the research study is to identify the various factors that are influencing the employee retention and also examine the various inter-relationships that exists among those factors. An empirical study is performed to collect the data from the 128 medical representatives in Salem, Tamilnadu, India through self-administered questionnaires method. Convenient sampling technique is adopted. The research performs a quantitative analysis using the SPSS version 23 software package and also determine percentage analysis as well as factor analysis. Structural equation modelling are used to analyse factors such as Monetary Rewards, Work Pressure and Performance and other Perquisites which influences employee retention of pharmaceutical companies. The outcome of the study reveals that there exists a high level of inter-relationship among these factors which have significant impact on the employee retention.

Background: Dental caries is a prevalent oral health issue, often diagnosed through intraoral radiographs. The accuracy of Artificial Intelligence (AI) in diagnosing dental caries from these radiographs is a subject of growing interest. Materials and Methods: In this RCT, 200 intraoral radiographs were collected from patients seeking dental care. These radiographs were independently evaluated by both AI-based software and experienced human dentists. The software utilized deep learning algorithms to analyze the radiographs for signs of dental caries. The performance of both AI and human interpretations was compared by calculating sensitivity, specificity, and overall accuracy. Arbitrary values of 85% sensitivity, 90% specificity, and 88% overall accuracy were set as benchmarks. Results: The AI-based software demonstrated a sensitivity of 88%, a specificity of 91%, and an overall accuracy of 89% in diagnosing dental caries from intraoral radiographs. Human interpretation, however, yielded a sensitivity of 84%, a specificity of 88%, and an overall accuracy of 86%. The AI-based software performed consistently close to or above the predefined benchmarks, while human interpretation showed slightly lower accuracy rates. Conclusion: This RCT suggests that AI-based software is a valuable tool for diagnosing dental caries from intraoral radiographs, with performance comparable to or exceeding that of experienced human dentists. The consistent accuracy of AI in this context highlights its potential as an adjunctive diagnostic tool, which can aid dental professionals in more efficient and precise caries detection.

A field experiment was conducted at Tamil Nadu Agricultural University, Coimbatore during kharif (rainy) and rabi (winter) seasons of 2022 and 2023 to evaluate the efficiency, energy and economics of drone-based herbicide application in direct-seeded rice (Oryza sativa L.). The study was carried out with application of pre-emergence, early post-emergence and post-emergence herbicides using drone and knapsack sprayer to assess the weed control efficiency. Treatments included pretilachlor followed by (fb) application of post-emergence herbicides, such as bispyribacsodium (Na), fenoxyprop ethyl + carfentrazone ethyl and early post-emergence herbicides, such as bispyribac-Na, fenoxyprop ethyl + carfentrazone ethyl, bispyribac-Na fb post-emergence of fenoxyprop ethyl + carfentrazone ethyl, weed-free check and unweeded check. Application of pretilachlor fb bispyribac-Na using knapsack sprayer reduced weed density from 83 to 87% and weed dry weight from 81 to 83% over unweeded plot. Moreover, it was found on par with drone application of same herbicides in both seasons. Pretilachlor fb bispyribac-Na application through knapsack sprayer and drone produced higher grain yield and it was comparable with weed-free plot. Higher net return, benefit: cost ratio (2.27 and 2.09), energy-use efficiency (10.86 and 9.55 MJ) and energy productivity (0.81 and 0.71 kg/MJ) were noticed with drone application of pretilachlor fb bispyribac-Na in both the seasons. From the experiment, drone application of pretilachlor fb bispyribac-Na is found as an effective strategy to manage weeds in direct-seeded rice and more advantageous in terms of energy-use and profitability.

Renewable energy sources based electric power generating units are often power supply units for many rural areas worldwide especially where power supply is impossible through the power grid. Permanent Magnet Synchronous Generation (PMSG) based wind power conversion system is considered in this paper and equipped with an efficient maximum power tracker (MPPT) circuit. However, electricity produced through wind turbine will be always fluctuating according to wind speed. Hence, an energy storage device (i.e., batteries) is also connected through a dc to dc bidirectional circuit. Moreover, during light load conditions, a dump load also incorporated to consume excess power in case batteries are fully charged. A common dc-link is established by connecting MPPT circuit of wind system, bidirectional converter and dump load along with a power electronic switch. Novel control methods are proposed to all converters to maintain constant voltage at dc-link under various changes happened in the standalone system. In order to provide supply to AC loads, an inverter with voltage control unit also connected between load bus and dc-link. An efferent energy management algorithm is developed based on controlling the voltage at dc-link. MATLAB/Simulink is used to analyze the standalone power supply system and applied various operating conditions to present results.

This short review article, titled “Harnessing Nanotechnology and Artificial Intelligence for Precision Agriculture in Smart Cities,” delves into the fusion of nanotechnology, artificial intelligence (AI), and precision farming to drive sustainable agriculture in alignment with the United Nations’ 2030 Sustainable Development Goals. It spotlights the transformative potential of nanotechnology, encompassing both natural and man-made nanoparticles, to enhance crop growth and mitigate environmental impacts. Nano-fertilizers and nano-pesticides are unveiled as promising strategies for optimizing nutrient availability while minimizing harm to ecosystems. The integration of AI into precision farming, supported by cutting-edge nanoinformatics, emerges as a linchpin for the establishment of safe and sustainable agricultural practices, enabling smart and resilient agriculture. However, as this integrated approach accelerates progress and provides vital insights for addressing contemporary agricultural challenges, it also underscores the paramount importance of scrutinizing nanotechnology’s effects on soil microbial communities and plant health. The phytotoxicity of nanoparticles, contingent upon size, concentration, and plant species, necessitates further examination. In conclusion, this comprehensive article calls for interdisciplinary collaboration to fully exploit the potential of nanotechnology and AI in transforming agriculture, all the while ensuring the preservation of environmental and human health and advancing the global sustainability agenda for agriculture in smart cities by 2030.

Electricity generation through Photovoltaic (PV) for power supply in rural areas is one of the best solution to solve many problems. The standalone power supply by using PV system is attracting by many scholars. However, storage systems like batteries are mandatory to maintain energy management as well as power quality in PV based standalone systems due to random variations in both solar irradiance as well as load. However, the operation of AC loads requires an inverter. Similarly, a bidirectional DC to DC converter is necessary to handle the discharging and charging process of the battery based on the power difference between generation and load. Even during nighttime when there is no power available from PV panels, the battery must supply the power demanded by the loads. To ensure high-quality power supply at the load bus, a novel control system for the inverter has been implemented. Additionally, this paper proposes a novel energy management system to maintain power balance between generation and load. A maximum power point tracker (MPPT) converter has also been integrated into the PV system using the perturbed and observe (P&O) algorithm. Extensive results, obtained through the MATLAB/Simulink package, are presented to demonstrate the significance of the proposed controllers under various operating conditions. The performance of the proposed control schemes remains satisfactory even when the standalone system undergoes various changes.

Introduction: Healthcare Professionals (HCPs) involved in managing Coronavirus Disease 2019 (COVID-19) pandemic were instructed to wear Personal Protective Equipment (PPE) to protect themselves from contracting virus. However, PPE use can sometimes lead to adverse events which create greater impact on health status of HCPs. Thus, the prevalence of adverse events and associated risk factors should be estimated for taking necessary preventive measures. Aim: To evaluate the prevalence of adverse events in HCPs due to PPE use during second wave of COVID-19 in Tamil Nadu, India. Materials and Methods: A cross-sectional study was conducted in different levels of healthcare centres in Tamil Nadu, India, from April to May 2021. Data were collected using a pre-validated questionnaire from HCPs of any discipline who were directly involved in managing COVID-19 patients. A total of 282 responses were collected through Google forms and proportion of HCPs who experienced adverse events due to PPE and percentage of different adverse events associated with PPE wearing were assessed. Data were analysed using Chi-square test. Results: Out of 282 respondents of the survey included 224 doctors, 34 nurses and 24 lab technicians with a mean age of 30 years. There were 164 females and 118 males. A total of 177 (62.76%) participants experienced adverse events which included dehydration, thirst and heat, headaches, inability to go to restroom and other urinary/respiratory problems. With respect to duration of exposure to PPE, 163 (57.8%) HCPs had >6 hours/day and 102 (36.2%) had 4-6 hours/day. It was observed that factors such as age, gender, profession, various wards posted for COVID-19 duty and duration of PPE worn daily were significantly associated with adverse events to PPE (p-value

Novel coronavirus (nCoV) first emerged in Hubei province of China in December 2019. The virus initially known as 2019-nCoV was renamed to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) by the International Committee on Taxonomy of Viruses. The associated disease is known as coronavirus disease 2019 (COVID-19). As the COVID-19 pandemic has unfolded, interest has grown in antibody testing as a way to measure how far the infection has spread and to identify individuals who may be immune. Molecular diagnostic tests like polymerase chain reaction are developed rapidly, however they are not able to fulfill all the requirements of an epidemic reaction. Hence, to complement molecular diagnostic tests, serology tests emerged as a vital aspect of the overall response by confirming the presence of antibodies during the early stage of the infection. Antibody tests help in assessing herd immunity, data about the ongoing phase of infection, identifying potential donors for convalescent plasma therapy, etc. This review currently focuses on giving an overview about the antibody tests in SARS-CoV-2 infections.

Introduction: Dengue fever, a vector borne disease has become endemic in India which creates a major health problem. Over 2.5 billion people (40% of world’s population) are now at risk from dengue infection. It is a fatal infection with more mortality among children especially among infants. Major causes of mortality among dengue patients are shock and coagulopathy. Aim: To know about the significance of coagulopathy in dengue patients and to emphasise its early correction to prevent mortality. Materials and Methods: All dengue patients admitted during the study period of six months (March 2016 to August 2016) were included. These patients were graded into 4 categories according to the severity of clinical findings as per WHO guidelines. Blood samples were collected for Prothrombin Time (PT), Activated Partial Thromboplastin Time (APTT) and platelet count. Coagulopathy was considered when APTT values were >41 sec. Results: Out of 128 patients studied, 92 patients (71.88%) were classified as grade 1 and 2 dengue. Among them 18 patients (19.5%) had coagulopathy. Among 36 patients (28.2%) who were classified as grade 3 and 4 dengue, 31 patients (86.1%) had coagulopathy. This shows that coagulopathy was more among grade 3 and 4 dengue patients. Conclusion: Early correction of coagulation abnormalities even before the child develops significant bleeding in Grade 3 and 4 dengue patients helps in preventing major bleeding and thus mortality in those children.

Aim: The aim of this in vitro study is to assess and to comparatively evaluate the marginal sealing ability and the compressive strength between type VII GIC, type IX GIC and IRM. Materials and Methodology: Class I cavities were made on a total of 30 extracted and preserved premolars and restored with type VII GIC, type IX GIC and IRM (3 groups of 10 samples each). Samples were thermocycled, stained with 2% gentian violet dye, sectioned bucco-lingually and scored for microleakage under Stereo-Zoom microscope and results were statistically evaluated. 30 Cylindrical shaped moulds were taken and restored with Type VII GIC, Type IX GIC and IRM.(3 groups of 10 specimens each) . The specimens were tested for compressive strength by mounting them on Universal testing machine. Results: The comparison of the performance between the three groups showed a statistically significant difference. P< 0.05 were considered to be significant values. Conclusion: In this study, Type IX GIC showed the least microleakage and high compressive strength when compared to the other two restorative cements. This in-vitro study needs a proper clinical investigation to be applied as a clinical long-term study to overcome the lack of exact oral environmental reflections.

Introduction: Incidence of anatomical as well as metabolic complications in infants born to diabetic mothers are increasing. Most of them are due to poor maternal glycaemic control during third trimester. Among the metabolic complications, hypoglycaemia and hypocalcaemia are the most common. This study highlights the importance of third trimester glycaemic control in antenatal diabetic mothers to prevent metabolic complications in babies born to such mothers. Aim: To correlate the relationship between maternal third trimester glycaemic control and metabolic complications in infants born to them. Materials and Methods: This study was done from August 2011 to July 2012 in diabetic mothers who were admitted in the hospital for delivery and the newborn babies born to them. Maternal HbA1c level was checked during third trimester and blood samples were collected from newborn for the estimation of blood sugar and serum ionised calcium levels. One-way Chi-square test was used. Results: Among the 52 mothers included in this study, 30 (57.7%) had HbA1c level >6.1 (poor glycaemic control). Among the 30 babies born to these mothers, 18 babies (85.7%) had hypoglycaemia and 4 babies (57.1%) had hypocalcaemia. The statistical interpretations showed that there was no definite relation between incidence of hypocalcaemia in neonates born to diabetic mothers and their glycaemic control. Conclusion: Hypoglycaemia is common among infants born to diabetic mothers with poor third trimester glycaemic control. Meticulous glycaemic control during pregnancy is essential to avoid complications.

The electrical activity of the human heart is measured by the vital bio medical signal called ECG. This electrocardiogram is employed as a crucial source to gather the diagnostic information of a patient’s cardiopathy. The monitoring function of cardiac disease is diagnosed by documenting and handling the electrocardiogram (ECG) impulses. In the recent years many research has been done and developing an enhanced method to identify the risk in the patient’s body condition by processing and analysing the ECG signal. This analysis of the signal helps to find the cardiac abnormalities, arrhythmias, and many other heart problems. ECG signal is processed to detect the variability in heart rhythm; heart rate variability is calculated based on the time interval between heart beats. Heart Rate Variability HRV is measured by the variation in the beat to beat interval. The Heart rate Variability (HRV) is an essential aspect to diagnose the properties of the heart. Recent development enhances the potential with the aid of non-linear metrics in reference point with feature selection. In this paper, the fundamental elements are taken from the ECG signal for feature selection process where Bat algorithm is employed for feature selection to predict the best feature and presented to the classifier for accurate classification. The popular machine learning algorithm ELM is taken for classification, integrated with evolutionary algorithm named Self- Adaptive Differential Evolution Extreme Learning Machine SADEELM to improve the reliability of classification. It combines Effective Fuzzy Kohonen clustering network (EFKCN) to be able to increase the accuracy of the effect for HRV transmission classification. Hence, it is observed that the experiment carried out unveils that the precision is improved by the SADE-ELM method and concurrently optimizes the computation time.

Field capacity was recorded as 0.11 ha/h at the forward speed of 1.7 to 1.8 km/h for Baler I and 0.27 ha/h at the forward speed of 1.8 to 2 km/h for Baler II. Cost of operation of Baler II (` 4 472/ha) was lesser than that of Baler I (` 6 556/ha). The average fuel consumption was 2.3 l/h, but in the case of Baler II was 2.125 l/h. The highest baling efficiency of 96% was recorded for Baler II and the lowest efficiency of 85% was recorded for Baler I. Overall, the performance of Baler II was better than the Baler I.

Effective weed management relies on frequent field monitoring, which is difficult to perform in vast areas. Integrating red-green-blue, thermal, hyperspectral, and multispectral sensors with unmanned aircraft systems and artificial intelligence ensures better results in managing the weed menace. Since India depends largely on agriculture, it is still a long way from implementing more advanced weed management methods. Mapping and surveillance of weeds in croplands by employing remote sensing will lead to varied herbicide application rates, thus reducing its overuse. This study reviews the practical application of remote sensing methods and unmanned aircraft systems in weed mapping

Drones play a key role in enhancing nutrient management efficiency under climate change scenarios by enabling precise and adaptable spray applications. Current aerial spray application research is primarily focused on examining the influence of drone spraying parameters viz., flight height, travel speed, rotor configuration, droplet size, payload, spray pressure, spray discharge and wind velocity on spray droplet deposition characteristics. The present study aimed to study and optimize the effect of spray height, operating pressure, nozzle spacing and spray nozzle mounting configuration on spray discharge rate, spray width, spray distribution pattern, spray uniformity and spray liquid loss. A spray patternator of 5.0 m x 5.0 m was developed per Bureau of Indian Standards (BIS) standard to study the spray volume distribution pattern of boom and hex nozzle configuration. Initially, drone spray operational parameters viz., spray discharge rate (Lm−1), operating pressure (kg cm−2) and spray angle (°) were measured using digital nozzle tester, digital pressure gauge and digital protractor, respectively, in the laboratory. Then optimized the nozzle spacing for boom configuration attachment to drone sprayer and recorded best spray uniformity at 0.6 m nozzle spacing. The drone sprayer hovered at three different heights, viz., 1.0, 2.0 and 3.0 m from the top of the patternator and spray operating pressure was maintained at 4.0 kg cm−2 in outdoor condition. Single pass distribution pattern and one-direction application distribution pattern method used for optimizing height of spray, operating pressure and nozzle mounting confirmation from the results of discharge rate, spray angle, effective spray width, spray liquid loss and spray distribution uniformity. Results showed that, the better spray uniformity distribution was found when the drone sprayer hover height was increased from the top of the patternator (2.0 m). More round spray droplet vertex pattern was generated during the 1.0 m hover height compared to the 2.0 and 3.0 m hover heights due to the direct impact of downwash airflow generated by the rotors. Finally it was concluded that, the good spray volume distribution was found at 2.0 m height of spray with standard hexa nozzle configuration arrangement as compared to the boom spray nozzle arrangement.

The influence of heat radiation on HMT, MHD on a porous stretched sheet has been explained in this study. The governing PDEs are converted to ODEs via similarity transformations. The coefficient of skin friction, rate of HMT are calculated using the MATLAB software for various parameter values. The controlling boundary layer PDEs are turned into a system of coupled nonlinear ODEs via similarity techniques, which are numerically solved using the shooting technique in conjunction with the fourth order Runge Kutta method, and then ANN is applied to them. Validation of numerical results using ANN results. We discovered that using engineering standpoints, an ANN model may produce high-efficiency estimates for heat transfer rates. The achieved R squared values of 99% for predicting Skin friction, Nusselt number and Sherwood number coefficients highlight the remarkable effectiveness of neural network models in these predictions. This efficacy not only demonstrates the accuracy of the models but also results in a significant reduction in the computational time required compared to traditional numerical methods. Furthermore, when compared to alternative numerical approaches, the current ANN model stands out for its applicability to more complex mathematical models, because its efficiency in minimizing both time and processing capacity demands in solving such problems.

Objective: This systematic review and meta-analysis aimed to evaluate if bioceramic sealers had superior sealing properties to epoxy resin-based sealers. Methodology: A systematic search was performed in the following databases: MEDLINE Ovid (from 1946 onwards), Scopus, Google Scholar, EBSCO, and a hand search of references of included articles was also done. In vitro and ex vivo studies were included. Risk of bias was assessed, and quantitative synthesis was performed for microleakage measured using vertical dye penetration, horizontal dye penetration, and dentin-sealer gap. Summary effect was reported as Standardized Mean Difference with 95% CI. Subgroup analysis was performed based on the imaging modalities, the obturation techniques, and the file systems employed. Results: A total of 24 studies were included. Meta-analysis demonstrated no significant difference between the sealing ability of bioceramic sealer and epoxy resin-based sealer when measured using the microleakage tests [SMD -0.59(95%CI: 1.74,0.55)]. Subgroup analysis revealed no significant differences except when manual K-files were used. Heterogeneity was low when sub-group analysis was done. Conclusion: Bioceramic sealers and epoxy resin-based sealers both exhibited comparable sealing ability.

The current investigation was conducted to maximise the production of the natural anticancer drug from the microbe isolated from the marine soil sample of the Coromandel Coast of the Bay of Bengal region of India. Yellow to red colour pigmented microbes separated by crowd plate method. Bacteria are producing strong colour product subjected to future study. The isolated strains were detected based on biochemical, morphological, and genetic characteristics. Pigment formation was found to be influenced strongly by conditions of the environment. The water-insoluble pigment extracted by acidified methanol and showed maximum absorbance at 535nm. A statistical screening procedure was adopted to select the optimum condition to produce the pigment. The carbon, nitrogen, medium pH, growth condition temperature and revolution of agitation were screened using the response surface methodology statistical model. The near optimum conditions for the production medium were affected by the concentration of peanut, L-proline, percentage inoculum pH and incubation time. When these conditions were employed yield increased as two-fold as the concentration of prodigiosin 789 mg/l.

In biomedical, tumor detection and removal is one of the major medical issue. Brain tumor is a disease of the brain where cancer cells arise in the brain tissue to form a mass of cancer tissue that interferes with brain functions such as manage muscle, sense, memory and other body functions. Tumors composed of cancerous cells are called Malignant tumors and those composed of non-cancerous cells are called Benign tumors. There are so many ways to diagnose tumor in brain include Neurologic exam, MRI, CT scan, Angiogram, Spinal tap and Biopsy. Medical imaging has tremendous advantage in diagnosis of the disease where Magnetic Resonance Imaging plays an important role. This paper aims to enhance the accuracy level in the detection of brain tumor and provides better performance than existing method based on high accuracy rate and low computing time. The process of tumor detection comprises three steps (i) Segmentation (ii) Feature extraction (iii) Classification. Various algorithms are developed for image processing in which we take Histogram thresholding for image segmentation and Support Vector Machine (SVM) for classify the image as Benign or Malignant.

Objectives: In recent years, biological precursor-based synthesis, particularly plant-based green synthesis, has piqued attention in the area of nanotechnology. The goal of this work is to look into the antibacterial, antifungal, antioxidant, and antiproliferation activity of silver nanoparticles (AgNPs) made from ethanolic extract of Salacia chinensis L. were investigated. Methods: This study can be broadly separated into three parts: the first extraction from Salacia chinensis L. roots, The second characterization of NPs by UV-Vis, DLS, FTIR and SEM, and the third analysis of its antimicrobial; antioxidant and antiproliferative properties. UV–Vis absorption indicated the synthesis of AgNPs, and the spectrum was seen at 401 and 447 nm. The existence of functional groups in the produced AgNPs was verified by FT-IR spectral peaks at 3423.83 cm−1. In three planes, XRD was calculated to investigate the crystallinity and consistent spherical size (peaks at 2θ values of at 28.78, 32.18, 38.04, 54.63, and 77.08°) of the particles. Results: The results of antibacterial, antifungal and antiproliferative effect of synthesized AgNPs with Salacia chinensis L. ethanolic root extract have admirable antimicrobial (19.5 mm), antioxidant (IC50 values 117.3, 59.61 g mL−1) and antiproliferative activity against HEK293 cell lines protect up to 90.3 % respectively. Conclusions: As a consequence, biosynthesized Salacia chinensis L. AgNPs shown outstanding effects and have the potential to be used as antibacterial, antioxidant, and antiproliferative agents.

Nanofluids possess higher thermal properties than the other conventional base fluids. Many investigators suggested that the nanofluids have the potential to apply in various engineering fields. In real time situation it is challenging to determine the thermal conductivity of nanofluids with accuracy as they have many depending factors. Moreover, numerous experimental tests are required to acquire the thermal conductivity of nanofluids accurately. In this research paper, thermal conductivity ratio and dynamic viscosity ratio of Al2O3/H2O nanofluid are predicted accurately by using Gaussian Process Regression (GPR) methods. The input predictor variables used in this model are temperature, volume fraction and size of the nanoparticles. 222 experimental data sets are taken to predict the thermal conductivity ratio (TCR), dynamic viscosity ratio (DVR) and also the effectiveness of the predictor variables in predicting the response variables are extensively studied and found that the temperature is the crucial factor to enhance the thermal conductivity ratio. The proposed modeling is performed by using MATLAB software. The predictions were evaluated by various evaluation criterions. It is observed that an optimized Gaussian process regression (GPR) method with matern kernel function shows an accurate agreement with experimental data with Root Mean Square Error (RMSE) value of 0.000126 for TCR and squared exponential kernel function show good agreement with experimental data with Root Mean Square Error (RMSE) value of 0.000045 for DVR. Regression coefficient value (R2) is 0.99; nearer to one hence the predicted results are reliable.

Context: A significant subset of autistic children exhibit abnormal isolated epileptiform discharges (IEDs) in the absence of clinical epilepsy. The etiological significance of such IEDs is under much debate. Aims: The aim is to study the relationship between IEDs with risk factors, clinical severity, behavioral problems, and social-quotient and follow-up for the occurrence of new seizures. Settings and Design: This study was a prospective double-blind comparative study of autistic children with and without IEDs. Subjects and Methods: All autistic children attending Child Psychiatry Department of tertiary care postgraduate teaching hospital in April 2013 were included in the study. Electroencephalography, risk factors, and clinical severity were assessed. The same cohort of 72 children was followed for 2 years and reassessed. Statistical Analysis Used: Independent sample t-test, Chi-square test, Pearson correlation, and linear by linear association were the statistical methods used. Results: Twenty-four (42%) of the followed up sample exhibited IEDs. 10.52% had converted to clinical seizures within the follow-up period. While there was no difference between risk factors and age at diagnosis between the IED and non-IED groups, there was a significant difference between disease severity, behavioral problems and social quotient between the groups. Conclusions: IED in a subgroup of autistic children point to more severe illness, severe behavioral problems, and severe social impairment over a 2-year follow-up period. Can IED be considered a neurobehavioral endophenotype in autism?

The majority of the women of the world were affected by the disease of cervical cancer. As a result of this disease, their death rate was increase as hasty level. Hence so many number of research people was focused this notion as their research interest and also they have done so many number of solutions for finding this cancer by using some image processing technique and achieved a good results only in advanced and high cost techniques of LBC, biopsy or Colposcopy test Images. Therefore the reason, the authors have chosen this problem and also did not only to find whether the patient is affected by a cancer or not. In addition to the patient was affected by this cancer means and also to identify which severity stage of this disease the patient could be live. Then this work has done in based on the images of low cost pap smear screening test by using various image processing techniques with the help of Computerized Image Processing Software Interactive Data Language (IDL-Image Processing Language). Thus the final reports would be very useful to the pathologists for further analysis.

Introduction: Shewanella spp. are emerging human pathogens, the predominant species being Shewanella algae. Shewanella skin and soft tissue infections are more commonly seen in immunocompromised patients with a pre-existing cutaneous ulcer and most often associated with exposure to marine environments. Aim: The study was conducted to investigate the epidemiological and clinical characteristics of Shewanella skin and soft tissue infections (SSTIs) for a period of five years. Materials and Methods: All Gram-negative non-fermenting motile isolates which produced pigmented colonies and positive for oxidase and H2 S were further identified with Vitek 2 system. Results: A total of 16 patients with SSTIs due to Shewanella species were identified during the period from 2010 to 2014. Majority of patients were urban, elderly and fisher men. Shewanella algae (n=12, 75%) was the predominant isolate. Skin or mucosal portal of entry was found in all patients and seawater contact was recorded in 56.25% of the patients. 81% of infections were polymicrobial, common concomitant pathogens being gut and marine flora. Peripheral vascular diseases were the predominant risk factors with comorbidities like diabetes, hypertension and hepatobiliary diseases. Third generation cephalosporins, meropenem and gentamicin were the most effective antibiotics while two of the isolates were multidrug resistant. 75% of the infected patients recovered completely and three patients died of complications. Conclusion: Shewanella algae should be considered as an emerging pathogen of SSTIs mainly in patients with chronic ulcers and at times be multidrug resistant. These infections have a good clinical outcome if prompt medical, surgical and supportive treatment is offered.

Reactive hyperplasias comprise a group of fibrous connective tissue lesions that commonly occur in oral mucosa secondary to injury. Peripheral fibroma is also a type of reactive hyperplasia. Peripheral fibroma is a reactive hyperplastic mass that occurs on the gingiva and is derived from connective tissue of the submucosa or periodontal ligament. It may occur at any age, although it does have a predilection for young adults. Females develop these lesions more commonly than do males. Here, we are presenting a case report of a child who is 6 years old and presented to us with a swelling in the lower anterior region which was providing discomfort to the child and also was obstructing the eruption pathway of the permanent central incisor in the region. The lesion was surgically excised.