Critical review on arsenic: Its occurrence, contamination and remediation from water and soil

With the increasing pollution in today’s world, importance is being given to solve a problem and do it in a sustainable, eco-friendly manner. Arsenic is a class-1 carcinogen and also causes many other side effects to humans, plants and animals. The utilization of arsenic as wood preservatives, pesticides, or its historical overuse by some military units for rice killing operations has led to the increase in the toxic effects of arsenic like its carcinogenicity, decreased immune response etc. Although conventional methods like coagulation, lime softening, adsorption, membrane technology are effective, they have their disadvantages like additional waste generation, causing increased pollution and are expensive. The better alternative is phytoremediation. Appropriate plants like Brassica juncea, Hydrilla verticilata, Pteris vittata L., Vallisneria natans,  can be chosen based on the method of the remediation like phytoextraction, phytostabilization and phytofiltration or phytovoltalization. This review provides the list of a few plants which can be likely chosen for the purpose of both water and soil remediation. Advancements are occurring in bioremediation studies with the development of transgenic plants like transgenic tobacco, transgenic Arabidopsis thaliana for better phytoremediation.  Understanding the mechanism employed by the plant for its uptake/detoxification can aid in the enhancement of the process of remediation with the external supply of phosphorus. Along with this, the proper and safe disposal of plants is crucial for the remediation process. In addition, awareness of this solution to the general public is to be made for its effectiveness

IOT Based Intelligent Bin for Smart Cities

The method of connecting the objects or things through wireless connectivity, Internet called Internet Of Things. Nowadays a variety of tasks are based on IOT. Cities in the world are becoming smarter by implementing the things around using IOT. This is a new trend in technology. Smart cities include obstacle tracking, object sensing, traffic control, tracking of our activities, examining the baby, monitoring home lights and so on. One of the objective of smart cities is keeping the environment clean and neat. This aim is not fulfilled without the garbage bin management system. Hence the paper “IOT Based Intelligent Bin for Smart Cities” has been developed. Bin management is one of the major applications of IOT. Here sensors are connected to the all the bins at different areas. It senses the level of garbage in bin. When it reaches threshold a message is sent via GSM to the concerned person to clean it as soon as possible. The completed task is done in LabVIEW environment

Comparative study of the efficacy and safety of olopatadine eyedrops and sodium cromoglycate in clinical practice: a prospective study

Background: Allergic eye diseases are the commonest causes of ocular morbidity worldwide. To choose the best therapy in allergic conjunctivitis, understanding of underlying mechanisms implicated in triggering the allergy is very important. Olopatadine with a wide spectrum has proven to be very effective in allergic conjunctivitis. The objective of the study was to compare the efficacy and safety of ophthalmic solutions of olopatadine 0.2% once daily, olopatadine 0.1% twice daily and sodium cromoglycate 2% four times daily in allergic conjunctivitis for 3 weeks.Methods: This was a prospective, single centre study enrolling 304 patients with allergic conjunctivitis attending ophthalmology clinics. Subjects were assessed for ocular signs and symptoms at 3 visits-baseline, week 2, week 3. The change from baseline in the mean scores of itching and redness at 3 weeks was primary outcome variable.Results: The reduction in signs and symptoms were statistically significant in all the three groups (p <0.001). Both the olopatadine receiving groups were better than sodium cromoglycate receiving group in reducing ocular signs and symptoms by pairwise comparison by wilcoxon signed rank test.Conclusions: Olopatadine ophthalmic solution is better than sodium cromoglycate ophthalmic solution in reducing the ocular signs and symptoms in allergic conjunctivitis

In-Depth Performance Evaluation of PFP and ESG Sequence-Based Function Prediction Methods in CAFA 2011 Experiment

Background Many Automatic Function Prediction (AFP) methods were developed to cope with an increasing growth of the number of gene sequences that are available from high throughput sequencing experiments. To support the development of AFP methods, it is essential to have community wide experiments for evaluating performance of existing AFP methods. Critical Assessment of Function Annotation (CAFA) is one such community experiment. The meeting of CAFA was held as a Special Interest Group (SIG) meeting at the Intelligent Systems in Molecular Biology (ISMB) conference in 2011. Here, we perform a detailed analysis of two sequence-based function prediction methods, PFP and ESG, which were developed in our lab, using the predictions submitted to CAFA. Results We evaluate PFP and ESG using four different measures in comparison with BLAST, Prior, and GOtcha. In addition to the predictions submitted to CAFA, we further investigate performance of a different scoring function to rank order predictions by PFP as well as PFP/ESG predictions enriched with Priors that simply adds frequently occurring Gene Ontology terms as a part of predictions. Prediction accuracies of each method were also evaluated separately for different functional categories. Successful and unsuccessful predictions by PFP and ESG are also discussed in comparison with BLAST. Conclusion The in-depth analysis discussed here will complement the overall assessment by the CAFA organizers. Since PFP and ESG are based on sequence database search results, our analyses are not only useful for PFP and ESG users but will also shed light on the relationship of the sequence similarity space and functions that can be inferred from the sequences

A Review of Ensemble Machine Learning Approach in Prediction of Diabetes Diseases

Data mining techniques improve efficiency and reliability in diabetes classification. Machine learning techniques are applied to predict medical dataset to safe human life. The large set of medical dataset is accessible in data warehousing which used in the real time application. Currently Diabetes Diseases (DD) is among the leading cause of death in the world. Data mining techniques are used to group and predict symptoms in medical dataset by different examiners. Data set from Pima Indian Diabetes Dataset (PIMA) were utilized to compare results with the results from other examiners. In this system, the most well known algorithms; K-Nearest Neighbor (KNN), Na�ve Bayes (NBs), Random Forest (RF) and J48 are used to construct an ensemble model. The experiment�s result reveals that an ensemble hybrid model increases the accuracy by combining individual techniques in to one. As a result, the model serves to be useful by doctors and Pathologist for the realistic health management of diabetes

Ceftaroline fosamil in the treatment of methicillin-resistant Staphylococcus aureus

Ceftaroline fosamil, a cephalosporin approved by the FDA for treating infections caused by methicillin-resistant Staphylococcus aureus (MRSA). Staphylococcus aureus, particularly MRSA strains, poses a significant health risk due to antibiotic resistance. Ceftaroline fosamil is unique in its ability to bind to penicillin-binding protein 2a (PBP2a) found in MRSA, inhibiting bacterial cell wall synthesis and causing bacterial death. The pharmacokinetics of ceftaroline involve rapid conversion to its active form, primarily excretion through the kidneys, and a plasma protein binding rate of approximately 20%. Ceftaroline is effective against complex skin and soft tissue infections (cSSTIs) and community-acquired pneumonia (CAP), especially when MRSA is suspected. However, its efficacy against gram-negative bacteria is limited. The safety profile of ceftaroline fosamil is generally good, with reported adverse events comparable to other comparator agents in clinical trials. It is contraindicated in individuals with hypersensitivity to cephalosporins. Comparative efficacy with other antibiotics like vancomycin and daptomycin is discussed, emphasizing the importance of considering individual patient characteristics and local prevalence of resistant bacteria. The use of ceftaroline fosamil in special populations, such as pediatric and adult patients. While its efficacy in pediatric MRSA infections is explored, the lack of large-scale clinical trials for certain conditions like MRSA bacteremia is acknowledged. Clinical outcomes, including successful treatment of MRSA bacteremia, infective endocarditis, central nervous system infections, and nosocomial pneumonia, are discussed, suggesting ceftaroline fosamil's potential as a valuable therapeutic option. The conclusion underscores its breakthrough status, offering hope in addressing MRSA infections and improving patient outcomes

AN HYPERBOLIC IMAGINARY OPERATIONS WHICH SAVES COMPLEXITY

The Three-D structures for example hyperboloids, paraboloids, and ellipsoids require CORDIC to become operated both in circular and hyperbolic trajectories. The hardware implementation of those applications requires several CORDIC processor operating in various modes and various trajectories. A reconfigurable CORDIC may be used for various applications in communication systems, signal processing, 3-D graphics, robotics aside from general scientific calculations, and waveform generations. The reconfigurable CORDIC architectures are created in Verilog and synthesized while using Xilinx ISE and Synopsis Design Compiler using UMC 180-nm CMOS library, for that FPGA and ASIC implementations, correspondingly. Much like reconfigurable rotation-mode CORDIC, for growing shift-indices, the implementation of RCCUs is simplified for reconfigurable vectoring-mode CORDIC too. These codes, oftentimes, don't require additional parity check bits as well as in the remainder require just one or two additional bits. The decoding complexity increases but is likely to be implemented with limited effect on the memory speed. These codes are helpful for applications where the error rates are low, however, once the error rates are large, codes that may correct errors on multiple independent bits are essential. The input coordinates [x_ in, y_ in ] are first preprocessed to acquire coordinates [xin, yin] and octant mapping signals. Because of the insufficient symmetry in hyperbolic functions, the RoC can't be extended towards the entire coordinate space

Dynamic and Static Gesture Recognition System Using Moments

Gesture recognition is the novel idea to enhance the signs recognition of those who have speech and hearing disability .Our project discusses an improved method for gesture recognition .The algorithm extracts the gestures from the video given to it and it detects the hand using HSV skin color segmentation in the intent to eliminate the other parts of the body and detect only hands .It distinguishes between static and dynamic gestures and extracts the appropriate feature vector .We used SPHINX parser to form word from set of letters. We strive to enhance the reliability and efficiency by using faster static gesture recognition algorithm