Plasticized poly(lactic acid) with low molecular weight poly(ethylene glycol) : mechanical, thermal, and morphology properties

Poly(lactic acid) PLA was plasticized with low molecular weight poly(ethylene glycol) PEG-200 to improve the ductility of PLA, while maintaining the plasticizer content at maximum 10 wt%. Low molecular weight of PEG enables increased miscibility with PLA and more efficient reduction of glass transition temperature (Tg). This effect is enhanced not only by the low molecular weight but also by its higher content. The tensile properties demonstrated that the addition of PEG-200 to PLA led to an increase of elongation at break (>7000%), but a decrease of both tensile strength and tensile modulus. The plasticization of the PLA with PEG-200 effectively lowers Tg as well as cold-crystallization temperature, increasing with plasticizer content. SEM micrographs reveal plastic deformation and few long threads of a deformed material are discernible on the fracture surface. The use of low molecular weight PEG-200 reduces the intermolecular force and increases the mobility of the polymeric chains, thereby improving the flexibility and plastic deformation of PLA

Motor controlled system development with force-assistance using force/torque sensor for four-axis ceiling suspension system

Multi-axis force and torque sensors are type of transducers. They can measure force and torque in three dimensions. These sensors have multiple applications in robotic systems. The majority of these type of sensors use the strain measurement in any elastic structure. There are multiple approaches for strain measurement which include resistive strain gauge, piezo-electric and capacitive technologies. The evaluation of such a system can be done on various parameters, maximizing the acceptable sensing range while minimizing measurement errors/crosstalk is the main design challenge. In future, because force and torque sensors are necessary for service machines to interact with people in different situations, they will be widely deployed. However, it is challenging to find an appropriate force/torque sensor, and the cost is very high, because of certain design concerns and needs. This paper discusses an application based on the multi-axis force/torque sensor. A force-assisted control system has been proposed with simultaneous motorized action using force as feedback. The sensor needs and machine performance are reviewed after a thorough analysis of relevant data. This thorough investigation will benefit in the interfacing of specialized force/torque sensors to reduce crosstalk and aid in broadening the scope of service machines in which they can be used

Microbiological profile of COVID-19 patients admitted in a tertiary care hospital Mathura, Uttar Pradesh, India

Background: The pandemic due to severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) has drawn worldwide worst effect with diagnostic challenge. Every investigation has its own importance for diagnosis, care, treatment and for management of corona virus disease-2019 (COVID-19) patients. Here this prospective study aimed to investigate the microbiological profile, prevalence of co-infection, and antibiotic susceptibility pattern of patients with confirmed SARS-CoV-2.Methods: A total of 336 samples were processed in COVID laboratory, Department of Microbiology. An array of serological investigations was done by rapid card screening test. C-Reactive protein (CRP) was analyzed by nephelometer. Blood culture was done by automated system and urine culture on Cystine-Lactose-Electrolyte-Deficient (CLED) Agar. Antibiotic susceptibility tests were done by Kirby Bauer disc diffusion method.Results: Out of 336 samples tested 76%were male and 24%were female. All samples tested were negative for HIV, HBsAg, HCV, syphilis, malarial parasite. CRP and Typhi -dot with IgM and IgG antibody were positive in 89.28% and 11.42% respectively. About 27% of COVID-19 patients showed bacterial and fungal co-infections. The most prevalent organisms were MR-CoNS (26%), K. pneumoniae (19%) and less prevalent were P. aeruginosa (6%) and A. baumannii (4%).  C. albicans (11%) was the only isolated fungi. All gram positive isolates were 100% sensitive to Linezolid and vancomycin, among gram negative isolates, 100% were sensitive to colistin and polymyxin B.Conclusions: Microbiological investigation for presence of other co-infecting agents among patients with COVID-19 infection should be considered, and prompt treatment should be carried out accordingly

Comparative analysis of features of online numerical methods used for parameter estimation of PMSM

As permanent magnet synchronous motors (PMSM) have high power density, efficiency, good dynamic performance, and small size they are becoming popular in electric vehicle (EV) applications. Control performance and the efficiency of the system get affected due to electrical, mechanical parameters. Parameters value gets affected by voltage source inverter (VSI) non-linearities, temperature and magnetic saturation effects. If exact parameters for particular torque speed requirement are found, the efficiency of system increases. There are various offline and online methods for finding parameters. Offline methods are easy to implement but requires extra setup and estimate parameters in steady state. Because the effects of transient conditions are taken into account during identification, online methods for obtaining real-time data under running conditions are becoming more popular. An overview about online numerical methods to estimate electrical parameters of PMSM is given. It discusses difference between various methods in terms of computational cost, convergence speed, noise and identification error. Choosing of method will be easy using this work. For inductance estimation, the extended Kalman filter (EKF) algorithm has an identification error of 0.24% under temperature effect and -0.3% under VSI non-linearities effect. The identification error for Rs and ψf using the recursive least square (RLS) method is 0.5% and 0.02%, respectively, when temperature is considered. EKF and RLS algorithms are proposed

Dynamic programming-based control system development for advanced electric power drive

An efficient method for raising the effectiveness and performance of fuel cell electric vehicles (FCEVs) is the dynamic programming controller (DPC). By using real-time data to optimize the control inputs, FCEVs can achieve higher levels of efficiency and reduce their environmental impact. The DPC algorithm works by solving an optimization problem at each time step, based on the current state of the vehicle and its environment. The optimal control inputs are then applied to the vehicle to achieve the desired performance criteria. This paper presents the study that utilized MATLAB/Simulink to design, model, and simulate DPC for a FCEV. Controlling various components of the fuel cell (FC) with the optimum power requirement is needed for increasing the performance and mileage of the FCEV. It's important to use FC energy as effectively as possible. Having supervisory control over the FCEV's energy consumption and battery charging is necessary for it to produce this output at its best. To use the hydrogen efficiently, a control strategy is designed for energy management in FCEV. The designed control strategies are implemented through simulation using Simulink in MATLAB. The results show prominent performance of dynamic programming (DP) over rule-based controllers

REVIEW ON CYANIDE POISONING

Cyanide is one of the most lethal poison. It leads to death within a few minutes to a few hours sometimes. Depending upon the dose and route of administration or exposure the symptoms develop. The area of exposure is manufacturing and industrial sources such as insecticides, photographic solution, fumigation and electroplating work, plastic manufacturing and jewelry cleaners etc. History shows the common use of cyanide poisoning in suicidal and homicidal cases and also use as chemical warfare agent for terrorist attack. Incidence of cyanide poisoning is rare but the occurrence of death is seen instant in some cases. It causes histotoxic anoxia and inhibits oxidative phosphorylation, a process where oxygen is utilized for the production of essential cellular energy sources in the form of ATP. It does so by binds to the enzyme cytochrome C oxidase and blocks mitochondrial transport chain. This results in cellular hypoxia and the depletion of ATP occur, leading to metabolic acidosis. Symptoms such as headache, dizziness, vertigo, spasmodic closure of jaw and clawing of hands, tonic type of convulsions of the limb and trunk, muscular weakness and flaccidity, muscular paralysis, intense cyanosis, hypertension followed by hypotension, coma etc leads to death. Death is mainly due to cardiovascular failure and respiratory failure. Thus, rapid treatment to be started in such patients. The 100 % oxygen support and rapid therapy of antidotal treatment is necessary for life saving. Very efficient antidote is Hydroxocobalamin and other antidotes are also important in cyanide poisoning in the treatment as life saver. Survivors of cyanide poisoning may develop neuropathies.</jats:p

Structural dynamic testing for seismic response simulation and time variant reliability estimation

The research work reported in this thesis addresses a few problems which arise in the context of experimental dynamic testing of engineering structures under earthquake loads. Firstly, we consider the problem of characterizing and controlling errors that occur during hybrid simulation based pseudo-dynamic testing with substructuring. The study notes the complex interaction between the errors, that originate due to the approximations involved in the numerical modelling, and the experimental errors associated with actuation and measurements. This interaction involves a nonlinear dynamic response simulation of the test structure, and the error of simulation is noted to be system state dependent. The study proposes an adaptive time stepping strategy which is based on the solution of an associated linearized variational equation of motion of the test structure. The proposed method is illustrated on systems displaying geometric nonlinearity and contact nonlinearity due to pounding. The test protocol is implemented on a reaction wall based multiple servo-hydraulic actuation-based test system. The study is followed by an investigation into experimental estimation of time variant reliability of engineering structures subjected to earthquake loads modelled as a set of random processes. Specifically, the study has developed an experimental protocol which employs a combination of Markov Chain splitting methods and surrogate modelling tools, to arrive at a sampling variance reduced estimator for the probability of failure. It is shown that the implementation of the experimental protocol does not require explicit knowledge of a valid mathematical model of the test structure. The procedure developed has been shown to be applicable to tackle the problems of time variant component and system reliability estimation, and the procedure can handle both linear and nonlinear vibrating systems. The proposed test protocol has been implemented not only on the reaction wall based multiple servo-hydraulic actuation-based test system, but also on a multi-actuator earthquake shaking tabl

Mechanical Characterization Study of Additive as Nanofiller in Poly (ε-Caprolactone) Nanocomposite

In order to keep with ever evolving technology in biomedical field, the demand for Poly (ε-caprolactone) (PCL) is gaining importance due to its biodegradability and biocompatibility. However, the low mechanical, barrier and thermal strength of PCL restricts its widespread use. These drawbacks of virgin PCL can be rectified by incorporating nanofiller into the PCL matrix. Till date, research has been carried out incorporating nano-fiber into PCL but to the best of our knowledge there is hardly any literature regarding organoclay modified nanofiller-PCL composites. The present study represents PCL nanocomposites preparation and characterization. The FTIR and XRD spectra observe uniform distribution of nanofiller in the PCL matrix. The characterization of mechanical properties shows enhancement in strength till 3.5 wt% loading and declining trend afterwards indicating agglomeration of nanofiller at higher wt% ratio. The increase in tensile strength without sacrificing elongation at break provides these composites with very attractive mechanical properties.</jats:p

Assessment of Auto-rickshaw Drivers Knowledge Regarding the Effects of Air Pollution on Health and Its Prevention

Background: Air pollution is the major environmental pollution that contains different types of gases, dust particles, small molecules, etc. Air pollution is mainly caused by smoke or other harmful gases, such as oxides of carbon, sulfur, and nitrogen. Auto-rickshaw drivers are not only affected by air pollution, they are exposed to climatic changes, and. poor road conditions. They are exposed to air pollution, dust, infected droplets, job insecurity, noise pollution and vibration, business demands, damage to their vehicles, and, schedule-related pressure. Drivers also have the responsibility of their passengers and pedestrians- ‘lives and other vehicles. The objective of the study is to analyze knowledge among auto-rickshaw drivers regarding the health effects of air pollution and its prevention.&#x0D; Methods: An observational research methodology, a cross-sectional research design was used to perform this analysis. Probability purposive sampling technique was used to collect data from auto-rickshaw drivers based on the health effects of air pollution and its prevention utilizing structured questionnaires. The sample attributes have been defined by frequency, percentage, after data collection. The Chi-square test was also used to figure out the correlation between knowledge and specified demographic variables.&#x0D; Results: The findings show that 1.67% of auto-rickshaw drivers had an average level of knowledge score, 38.33% of them were having good and 60 % of them were having an excellent level of knowledge score and none of them were found to have a very poor level of knowledge. The minimum knowledge score was 7 and the maximum knowledge score was 14. Hence it indicates that auto-rickshaw drivers have good knowledge about the effect of air pollution and their prevention.&#x0D; Conclusions: The study shows that the auto-rickshaw drivers having good knowledge about air pollution to the management of respiratory diseases and along with their complications as well as to take the required measures to avoid respiratory complications. </jats:p

Cyber intrusion detection using ensemble of deep learning with prediction scoring based optimized feature sets for IOT networks

Detecting intrusions in Internet of Things (IoT) networks is critical for maintaining cybersecurity. Traditional Intrusion Detection Systems (IDS) often face challenges in identifying unknown attacks and tend to have high false positive rates. To address these issues, we propose the Ensemble of Deep Learning Models with Prediction Scoring-based Optimized Feature Sets (EDLM-PSOFS). Our approach begins with data preprocessing utilizing MissForest imputation and label one-hot encoding, effectively managing incomplete and categorical data.For feature selection, we employ the Median-based Shapiro-Wilk test alongside Correlation-Adaptive LASSO Regression (CALR) to ensure robust feature extraction. To capture temporal patterns effectively, our ensemble integrates Global Attention Long Short-Term Memory networks (GA-LSTMs), utilizing layered structures, residual connections, and attention mechanisms. Additionally, to enhance interpretability and support decision-making, we incorporate the Exploit Prediction Scoring System (EPSS), which evaluates prediction scores and provides detailed insights, thereby improving overall model performance. This comprehensive methodology aims to strengthen the detection capabilities of IDS in IoT environments, reducing false positives while effectively identifying unknown threats