Pregnancy outcome in women treated for subclinical hypothyroidism detected in early gestation

Background: Thyroid disorders are among the most common endocrine disorders in pregnancy. Objective of present study were to investigate the outcome of pregnancy in those women detected to have subclinical hypothyroidism in early gestation and to evaluate whether treatment of subclinical hypothyroidism reduces the adverse pregnancy outcome.Methods: Pregnant women detected to have Subclinical hypothyroidism (TSH >2.5- 6 mU/L and N Free T4) in the 1st trimester were selected and randomly divided into 2 groups. One group received treatment with Thyroxine. They were followed up till delivery and outcome noted.Results: The mean maternal age of both the group was 26 yrs. The gestational age at delivery and the newborn birth weight did not show any statistically significant difference. Antenatal complications like Gestational Diabetes, hypertension, small for gestation, and preterm were almost the same in both groups. There was significant increase in the primary caesarean rate in the treated group. No significant difference in the number of term vaginal delivery in both groups.Conclusions: Treatment of women with SCH (TSH <6 mU/L) does not reduce the risk of adverse pregnancy outcome. Benefits of treatment need to be weighed against any potential risks

Diagnostics of gear faults using ensemble empirical mode decomposition, hybrid binary bat algorithm and machine learning algorithms

Early fault detection is a challenge in gear fault diagnosis. In particular, efficient feature extraction and feature selection is a key issue to automatic condition monitoring and fault diagnosis processes. In order to focus on those issues, this paper presents a study that uses ensemble empirical mode decomposition (EEMD) to extract features and hybrid binary bat algorithm (HBBA) hybridized with machine learning algorithm to reduce the dimensionality as well to select the predominant features which contains the necessary discriminative information. Efficiency of the approaches are evaluated using standard classification metrics such as Nearest neighbours, C4.5, DTNB, K star and JRip. The gear fault experiments were conducted, acquired the vibration signals for different gear states such as normal, frosting, pitting and crack, under constant motor speed and constant load. The proposed method is applied to identify the different gear faults at early stage and the results demonstrate its effectiveness

Dynamic Time Warping Approach for User Authentication of Smartphones Using Single-handed Shakes

An immense amount of private information is stored in smartphones. In order to secure information from being tapped a new form of authentication mechanism is needed. Previous unlock mechanism like pattern authentication or code based authentication are vulnerable as they are not using a person's unique attribute. In this paper, we propose a method for unlocking phones based on user?s handshakes. The gesture sensors and the proximity sensors help us capture the unique handshake of the person. This unlock mechanism makes it harder for the attacker to reproduce the same type of handshake even if he observes the shaking pattern

Regulatory Challenges in Clinical Trials: Strategies to Overcome Commonly Observed Deficiencies

140-148Apart from the regular clinical trials, bioavailability/bioequivalence studies are conducted to assess the safety and efficacy of generic drugs, comparing it with a reference listed drug. Clinical trial data is mandatory for further approval of the drug, for it to enter the market. These investigations are strictly regulated by various global and national regulatory authorities. The global clinical trials market is expected to register a Compound Annual Growth Rate (CAGR) of nearly 4.5% during the forecast period, 2018 to 2023. A major challenge for them to achieve the forecasted growth is meeting the increased level of compliance to the regulations. In recent times the research Organizations have been issued an increased number of warning letters with stringent procedures and even subsequent closure of the organizations. This case study conducted by the review of warning letters and other observations pointed out by two major global regulatory authorities, the FDA and EMA and the critical areas were identified. Recommendations were made for the major areas which were critical and repetitive. It was concluded that consistent methods are required to improve the quality of studies to effectively eliminate the challenges in mere future and contribute for the betterment of the drugs’ market

BIOACTIVE POTENTIAL OF ENDOPHYTIC FUNGI ASPERGILLUS FLAVUS (SS03) AGAINST CLINICAL ISOLATES

Objective: This study was to evaluate the antimicrobial potential of endophytic fungi isolated from the medicinal plant Moringa oleifera Lam. collected from the Omalur region, Salem district.Methods: The endophytic fungi were isolated from stem, leaves, flowers and calyx of Moringa oleifera by surface sterilization method. The samples were surface sterilized by immersing it in 70% ethanol for 5 seconds followed by 4% sodium hypochlorite for 90 seconds and then a final rinsing in sterile distilled water. Then fungal biomass was extracted for intracellular metabolites by using ethyl acetate as solvent. The crude extract was filtered, and the filtrate was dried under vacuum at 40 °C. The filtrate was analyzed for antimicrobial activity. The fungi which showed the maximum activity was identified and the metabolite present in the ethyl acetate extract was characterized and identified by GC-MS and NMR analysis.Results: The predominant endophytic fungi isolated belongs to the genera of Aspergillus spp, Aspergillus flavus, Aspergillus versicolor, Aspergillus niger, Aspergillus ochraceus, Aspergillus terreus and dematiaceous fungi namely Bipolaris spp. From this Aspergillus flavus showed the highest zone of inhibition was observed against Staphylococcus aureus and Bacillus 22 mm and strain of Candida tropicalis 19 mm. The efficiency of the bioactive compound was identified by GC-MS and NMR analysis and found to be Fenaclon, (R)(-) 14 methyl-8-hexadecyn-1-ol, Trans-β-farnesene (E)-β-farnesene, 9-Octcadecene,1,1, DimethoxyConclusion: This study results indicate that the bioactive metabolites produce the endophytic fungi Aspergillus flavus could be promising source as antimicrobial agents

A Self-learning Nonlinear Variable Gain Proportional Derivative (PD) Controller in Robot Manipulators

This paper proposes a nonlinear variable gain Proportional-Derivative (PD) controller that exhibits self-constructing and self-learning capabilities. In this method, the conventional linear PD controller is augmented with a nonlinear variable PD gain control signal using a dynamic structural network. The dynamic structural network known as Growing Multi-Experts etwork grows in time by placing hidden nodes in regions of the state space visited by the system during operation. This results in a network that is "economic" in terms of network sileo The proposed approach enhances the adaptability of conventional PD controller while preserving its' linear structure. Based on the simulation study on variable load and friction compensation, the fast adaptation is shown to be able to compensate the non-linearity and the uncertainty in the robotic system

Phytochemical Screening and Antimicrobial Activity of the Plant Extracts of Mimosa pudica L. Against Selected Microbes

Mimosa pudica L. is a creeping annual or perennial herb. It has been identified as Lajjalu in Ayurveda and has been found to have antiasthmatic, aphrodisiac, analgesic and antidepressant. In the present study the active phytocomponents of Mimosa pudica were revealed using phytochemical analysis. The antimicrobial activity of Mimosa was studied using well diffusion method. The activity was tested against Aspergillus fumigatus, Citrobacter divergens and Klebsiella pneumonia at different concentrations of 50, 100 and 200μg/disc and the results have been illustrated