Dynamic Stress Analysis with Different boundry Conditions by ISO-Surface behaviour

Any CAE (Computer Aided Engineering) software the first result will be in contour manner which comes with the colour scale (Legend).But that will only give rough scenario about what is happening inside the layers in object when force is applied. That result is in iso-surface mode. Different members like Slabs, Beams and beam column joints behavior can be decided by the plane stress. An iso-surface is a three-dimensional analog of an iso-line. It is a surface that represents points of a constant value within a volume of space. Computer aided investigations on a solid object are carried out using the ANSYS 15.0 software to verify maximum stress and its location. To predict detailed stress values with 3D model created itself by Ansys 15.0 15. Solid object is made with the two imprinted faces on it for the application of dynamic analysis. Dynamic analysis is done by dividing time in to fractions & after that iso-surface is studied. Material used during the research is structural steel due to its importance and availability. The behavior of iso-surface changes with respect to the boundary condition viz. contact area of force. Visual representations of iso-surfaces are ubiquitous in the scientific and engineering literature. In this paper, we present techniques to assess the behavior of iso-surface extraction codes. More concretely, we derive formulas for the expected order of accuracy (or convergence rate) of several iso-surface features, and compare them to experimentally observed results in the selected codes. This technique is practical: in two cases, it exposed actual problems in implementations. We provide the reader with the range of responses they can expect to encounter with iso-surface techniques, both under "normal operating conditions" and also under adverse conditions. Armed with this information the results of the verification process--practitioners can judiciously select the iso-surface extraction technique appropriate for their problem of interest, and have confidence in its behavior. The material taken is structural steel in which the linear behavior is taken consideration in this case

FINE SCALE MAPPING OF LAURENTIAN MIXED FOREST NATURAL HABITAT COMMUNITIES USING MULTISPECTRAL NAIP AND UAV DATASETS COMBINED WITH MACHINE LEARNING METHODS

Natural habitat communities are an important element of any forest ecosystem. Mapping and monitoring Laurentian Mixed Forest natural communities using high spatial resolution imagery is vital for management and conservation purposes. This study developed integrated spatial, spectral and Machine Learning (ML) approaches for mapping complex vegetation communities. The study utilized ultra-high and high spatial resolution National Agriculture Imagery Program (NAIP) and Unmanned Aerial Vehicle (UAV) datasets, and Digital Elevation Model (DEM). Complex natural vegetation community habitats in the Laurentian Mixed Forest of the Upper Midwest. A detailed workflow is presented to effectively process UAV imageries in a dense forest environment where the acquisition of ground control points (GCPs) is extremely difficult. Statistical feature selection methods such as Joint Mutual Information Maximization (JMIM) which is not that widely used in the natural resource field and variable importance (varImp) were used to discriminate spectrally similar habitat communities. A comprehensive approach to training set delineation was implemented including the use of Principal Components Analysis (PCA), Independent Components Analysis (ICA), soils data, and expert image interpretation. The developed approach resulted in robust training sets to delineate and accurately map natural community habitats. Three ML algorithms were implemented Random Forest (RF), Support Vector Machine (SVM), and Averaged Neural Network (avNNet). RF outperformed SVM and avNNet. Overall RF accuracies across the three study sites ranged from 79.45-87.74% for NAIP and 87.31-93.74% for the UAV datasets. Different ancillary datasets including spectral enhancement and image transformation techniques (PCA and ICA), GLCM-Texture, spectral indices, and topography features (elevation, slope, and aspect) were evaluated using the JMIM and varImp feature selection methods, overall accuracy assessment, and kappa calculations. The robustness of the workflow was evaluated with three study sites which are geomorphologically unique and contain different natural habitat communities. This integrated approach is recommended for accurate natural habitat community classification in ecologically complex landscapes

Thioredoxin-interacting protein regulates protein disulfide isomerases and endoplasmic reticulum stress

The endoplasmic reticulum (ER) is responsible for protein folding, modification, and trafficking. Accumulation of unfolded or misfolded proteins represents the condition of ER stress and triggers the unfolded protein response (UPR), a key mechanism linking supply of excess nutrients to insulin resistance and type 2 diabetes in obesity. The ER harbors proteins that participate in protein folding including protein disulfide isomerases (PDIs). Changes in PDI activity are associated with protein misfolding and ER stress. Here, we show that thioredoxin-interacting protein (Txnip), a member of the arrestin protein superfamily and one of the most strongly induced proteins in diabetic patients, regulates PDI activity and UPR signaling. We found that Txnip binds to PDIs and increases their enzymatic activity. Genetic deletion of Txnip in cells and mice led to increased protein ubiquitination and splicing of the UPR regulated transcription factor X-box-binding protein 1 (Xbp1s) at baseline as well as under ER stress. Our results reveal Txnip as a novel direct regulator of PDI activity and a feedback mechanism of UPR signaling to decrease ER stress

Drug price control order: the impact on pharmacoeconomics

Background: The objective of the present study was to analyze the prices of metformin, losartan, atorvastatin, paracetamol and aspirin for the doses which are included in the list of Drug Price Control Order (DPCO) 2013.Methods: Current index medical specialties India, 37th year, April-July 2015 issue was used for analysis. The retail prices of the drugs in INR were tabulated in Microsoft Office Excel 2013. The prices of the above listed drugs were compared with prices of DPCO 2013 for the same doses of drugs. The analysis of drugs costing more than the prices listed in the DPCO with the margin of the difference in percentage was carried out.Results: Out of 25 brands of metformin 500 mg tablet, 11 (44%) brands had price higher than listed in DPCO 2013. Similarly, prices for losartan 25 mg and 50 mg tablets, 8 (25%) out of 32 and 11 (31.42%) out of 35 were higher respectively. For atorvastatin 5 mg and 10 mg tablets, 2 (9.52%) out of 21 and 8 (13.55%) out of 59 brands had higher prices. For paracetamol 500 mg tablet, 12 (63.15%) out of 19 brands were priced higher than DPCO list. For aspirin 100 mg tablet and 325 mg tablet, 3 (100%) out of 3 brands and 1 (100%) out of 1 brand had higher prices.Conclusions: Many of the brand formulations have higher prices than the DPCO 2013 issued by government of India. The clinicians prescribing these drugs should be aware of these brand formulations to reduce the cost of the drug therapy

COVID-19 in Spain and India: Comparing Policy Implications by Analyzing Epidemiological and Social Media Data

The COVID-19 pandemic has forced public health experts to develop contingent policies to stem the spread of infection, including measures such as partial/complete lockdowns. The effectiveness of these policies has varied with geography, population distribution, and effectiveness in implementation. Consequently, some nations (e.g., Taiwan, Haiti) have been more successful than others (e.g., United States) in curbing the outbreak. A data-driven investigation into effective public health policies of a country would allow public health experts in other nations to decide future courses of action to control the outbreaks of disease and epidemics. We chose Spain and India to present our analysis on regions that were similar in terms of certain factors: (1) population density, (2) unemployment rate, (3) tourism, and (4) quality of living. We posit that citizen ideology obtainable from twitter conversations can provide insights into conformity to policy and suitably reflect on future case predictions. A milestone when the curves show the number of new cases diverging from each other is used to define a time period to extract policy-related tweets while the concepts from a causality network of policy-dependent sub-events are used to generate concept clouds. The number of new cases is predicted using sentiment scores in a regression model. We see that the new case predictions reflects twitter sentiment, meaningfully tied to a trigger sub-event that enables policy-related findings for Spain and India to be effectively compared

Triple mesh technique in repair of recurrent lumbar incisional hernia

Lumbar hernias occur infrequently and can be congenital, primary (inferior or Petit type, and superior or Grynfeltt type), post-traumatic, or incisional. They are bounded by the 12th rib, the iliac crest, the erector spinae, and the external oblique muscle. Most postoperative incisional hernias occur in nephrectomy or aortic aneurysm repair incisions for which various surgical method in context of meshplasty are available. In this case 60 yr. male hypertensive patient presented to the outpatient clinic of institute with recurrent left side lumbar incisional hernia, patient was previously operated for left side nephrolithiasis 15 years back and onlay meshplasty 2 years back for incisional hernia. The patient was operated under high risk for recurrent incisional hernia repair by triple layered meshplasties in the same sitting. Lumbar incisional hernias are often diffuse with fascial defects that are usually hard to appreciate. Computed tomography scan is the diagnostic modality of choice with adjuvant clinical findings, which allows differentiating them from abdominal wall musculature denervation atrophy complicating flank incisions. Repairing these hernias is difficult due to the surrounding structures for which our surgical approach included a triple mesh repair consisting of underlay, inlay and onlay meshplasty thereby anticipating further such incidences of incisional hernia

Colloidal Structure Dictates Antimicrobial Efficacy in LL-37 Self-Assemblies With Glycerol Monooleate

The antimicrobial peptide LL-37 is a promising alternative to conventional antibiotics to combat bacteria in suspension and biofilms. Its self-assembly with polar lipids is suggested to improve its potential for therapeutic applications with higher stability against degradation and bioavailability. This study investigates the self-assembly of LL-37 with glyceryl monooleate (GMO), establishing the link between colloidal structure and antimicrobial activity. Small-angle X-ray scattering, dynamic light scattering and cryogenic transmission electron microscopy show structural transformation from dispersions of inverse bicontinuous structure (cubosomes) to multilamellar vesicles and direct rod-like mixed-micelles upon increasing the content of LL-37 in GMO. In vitro assays against planktonic and biofilm cells demonstrate that 128 µg mL -1 of GMO cubosomes have no impact on Pseudomonas aeruginosa. Still, the cubosomes reduce the Staphylococcus aureus planktonic population by ≈ 1-log after 24 h. Cylindrical micelles formed at LL-37/GMO 9/1 and 8/2 with 128 µg mL -1 LL-37 decrease the Pseudomonas aeruginosa population by 6-log. This activity is gradually abolished when LL-37 is encapsulated in vesicles or cubosomes. They also demonstrate low antibiofilm efficacy and promote the biomass of Staphylococcus aureus biofilms. These results highlight the importance of colloidal structure for therapeutic outcomes, providing insights for advanced lipid nanocarrier designs. </p