Coronary artery disease(CAD) occurring in less than 45 years of age is termed as young CAD.Recent studies show a prevalence of 1.2% of CAD cases in this age group.Ethnic wise south Asians especially Indians are more v...Coronary artery disease(CAD) occurring in less than 45 years of age is termed as young CAD.Recent studies show a prevalence of 1.2% of CAD cases in this age group.Ethnic wise south Asians especially Indians are more vulnerable to have CAD in young age group with a prevalence of 5% to 10%.Conventional risk factors such as smoking,diabetes,hypertension,obesity and family history seems to be as important as in older CAD subjects.But the prevalence of these risk factors seems to vary in younger subjects.By far the most commonly associated risk factor is smoking in young CAD.Several genes associated with lipoprotein metabolism are now found to be associated with young CAD like cholesterol ester transfer protein(CETP) gene,hepatic lipase gene,lipoprotein lipase gene,apo A1 gene,apo E gene and apo B.Biomarkers such as lipoprotein(a),fibrinogen,D-dimer,serum Wnt,gamma glutamyl transferase,vitamin D2 and osteocalcin are seems to be associated with premature CAD in some newer studies.In general CAD in young has better prognosis than older subjects.In terms of prognosis two risk factors obesity and current smoking are associated with poorer outcomes.Angiographic studies shows predominance of single vessel disease in young CAD patients.Like CAD in older person primary and secondary prevention plays an important role in prevention of new and further coronary events.展开更多
A heavy metal contaminated soil sample collected from a mine in Chonnam Province of South Korea was found to be a source of heavy metal adsorbing biosorbents. Chemical analyses showed high contents of lead （Pb） at 3...A heavy metal contaminated soil sample collected from a mine in Chonnam Province of South Korea was found to be a source of heavy metal adsorbing biosorbents. Chemical analyses showed high contents of lead （Pb） at 357 mg/kg and cyanide （CN） at 14.6 mg/kg in the soil. The experimental results showed that Penicillium sp. MRF-1 was the best lead resistant fungus among the four individual metal tolerant fungal species isolated from the soil. Molecular characterization of Penicillium sp. MRF-1 was determined using ITS regions sequences. Effects of pH, temperature and contact time on adsorption of Pb（Ⅱ） by Penicillium sp. MRF-1 were studied. Favorable conditions for maximum biosportion were found at pH 4 with 3 hr contact time. Biosorption of Pb（Ⅱ） gradually increased with increasing temperature. Efficient performance of the biosorbent was described using Langmuir and Freundlich isotherms. Adsorption kinetics was studied using pseudo first-order and pseudo second-order models. Biosorbent Penicillium sp. MRF-1 showed the maximum desorption in alkali conditions. Consistent adsorption/desorption potential of the biosorbent in repetitive cycles validated the efficacy of it in large scale. SEM studies given notes on surface modification of fungal biomass under metal stress and FT-IR results showed the presence of amino groups in the surface structure of the biosorbent. In conclusion, the new biosorbent Penicillium sp. MRF- 1 may potentially be used as an inexpensive, easily cultivatable material for the removal of lead from aqueous solution.展开更多
Amplified chirality and Förster resonance energy transfer(FRET)-assisted chirality transfer frommolecular to nanoscale level have been shown to play a vital role in co-assembled nanohelix for potential energy tra...Amplified chirality and Förster resonance energy transfer(FRET)-assisted chirality transfer frommolecular to nanoscale level have been shown to play a vital role in co-assembled nanohelix for potential energy transfer in biological systems.Herein,we have constructed a chiral host–guest complex donor system for chiral amplification via induced chirality of pillar[5]arene host and loaded it with an achiral dye acceptor to demonstrate how chirality-assisted excitation energy transfer occurred in the supramolecular nanohelix system in an aqueous medium.展开更多
Objective:To characterize the pharmacological importance of biosurfactants isolated from halophilic Bacillus sp BS3.Methods:Halophilic Bacillus sp.BS3 was isolated from solar salt works,identified by 16S rRNA sequenci...Objective:To characterize the pharmacological importance of biosurfactants isolated from halophilic Bacillus sp BS3.Methods:Halophilic Bacillus sp.BS3 was isolated from solar salt works,identified by 16S rRNA sequencing and was used for screening their biosurfactant production.Characters of the biosurfactant and their anticancer activity were analyzed and performed in mammary epithelial carcinoma cell at different concentrations.Results:The biosurfactant were characterized by TLC,FTIR and GC-MS analysis and identified as lipopeptide type.GC-MS analysis revealed that,the biosurfactant had various compounds including 13Docosenamide.(Z);Mannosamine,9- and N,N,N',N'-tetramethyl.Surprisingly the antiviral activity was found against shrimp white spot syndrome virus(WSSV) by suppressing the viral replication and significantly raised shrimp survival(P<0.01).Anticancer activity performed in the mammary epithelial carcinoma cell at different concentrations of biosurfactants,among the various concentrations of biosurfactants such as 0.000 25,0.002 5,0.025,0.25 and 2.5 μ g,the 0.25 μ g concentration suppressed the cells significantly(P<0.05) to 24.8%.Conclusions:Based on the findings,the present study concluded that,there is a possibility to develop eco-friendly antimicrobial and anticancer drugs from the extremophilic origin.展开更多
Li-Fraumeni syndrome(LFS)is a well-defined autosomal dominant predisposition syndrome due to TP53 germline mutation that causes many cancer malig-nancies.This early-onset syndrome poses a state of widespread malignanc...Li-Fraumeni syndrome(LFS)is a well-defined autosomal dominant predisposition syndrome due to TP53 germline mutation that causes many cancer malig-nancies.This early-onset syndrome poses a state of widespread malignancy.Such an inherited condition possessing defective p53,guardian of the genome,in the germline has the potential to cause multiple cancers by predominantly affecting mesenchyme(connective tissues,blood cells),breast,brain,and adrenal cortex organs.The tumors initially identified in LFS can eventually propagate to cause secondary malignancies.LFS contributes to multiple cancers in individuals with defective p53 inheritance.When suspected to possess any mass,patients with other co-morbidities,in particular those with certain cardiovascular conditions,undergo screening using high-throughput techniques like transthoracic and transesophageal echocardiography or cardiothoracic magnetic resonance imaging to locate and interpret the size of the mass.In LFS cases,it is certain to presume these masses as cancers and plan their management employing invasive surgeries after performing all efficient diagnostic tools.There are only poor predictions to rule out the chances of any other pathology.This criterion emphasizes the necessity to speculate alternative precision diagnostic methods to affirm such new growth or masses encountered in LFS cases.Moreover,it has all the possibilities to ultimately influence surgical procedures that may be invasive or complicate operative prognosis.Hence,it is essential to strategize an ideal protocol to diagnose any new unexplored mass in the LFS community.In this editorial,we discuss the importance of diagnostic approaches on naïve pristine masses in LFS.展开更多
Different types of neuroendocrine cancer,including medullary thyroid cancer(MTC)and thyroid C-cell hyperplasia,are part of multiple endocrine neoplasia type 2(MEN2).A proto-oncogene mutation of the rearranged during t...Different types of neuroendocrine cancer,including medullary thyroid cancer(MTC)and thyroid C-cell hyperplasia,are part of multiple endocrine neoplasia type 2(MEN2).A proto-oncogene mutation of the rearranged during transfection(RET)gene changes the way that receptor tyrosine kinases work.Multiple endocrine neoplasia,a pathological condition,involves these kinases.When the RET protooncogene changes,it can cause endocrine adenomas and hyperplasia to happen at the same time or one after the other.Pheochromocytoma,medullary thyroid carcinoma,and hyperparathyroidism,alone or in combination,are present in MEN2A patients.Some patients may also have skin lichen amyloidosis or Hirschsprung's disease.Patients with MEN2A often present with MTC.MTC is aggressive and has the worst prognosis,as most patients exhibit lymph node metastasis.MTC is one of the important causes of death in patients with MEN2A.RET mutation analysis aids in identifying MEN2A symptoms and monitoring levels of calcium,thyroid hormones,calcitonin,normetanephrine,fractionated metanephrines,and parathyroid hormone.The earlier diagnosis of MTC significantly improves survival and prompts better management of MEN2A.In this editorial,we will discuss the significance of molecular diagnostic approaches in detecting RET oncogene mutations in MEN2A.展开更多
Analyzing human facial expressions using machine vision systems is indeed a challenging yet fascinating problem in the field of computer vision and artificial intelligence. Facial expressions are a primary means throu...Analyzing human facial expressions using machine vision systems is indeed a challenging yet fascinating problem in the field of computer vision and artificial intelligence. Facial expressions are a primary means through which humans convey emotions, making their automated recognition valuable for various applications including man-computer interaction, affective computing, and psychological research. Pre-processing techniques are applied to every image with the aim of standardizing the images. Frequently used techniques include scaling, blurring, rotating, altering the contour of the image, changing the color to grayscale and normalization. Followed by feature extraction and then the traditional classifiers are applied to infer facial expressions. Increasing the performance of the system is difficult in the typical machine learning approach because feature extraction and classification phases are separate. But in Deep Neural Networks (DNN), the two phases are combined into a single phase. Therefore, the Convolutional Neural Network (CNN) models give better accuracy in Facial Expression Recognition than the traditional classifiers. But still the performance of CNN is hampered by noisy and deviated images in the dataset. This work utilized the preprocessing methods such as resizing, gray-scale conversion and normalization. Also, this research work is motivated by these drawbacks to study the use of image pre-processing techniques to enhance the performance of deep learning methods to implement facial expression recognition. Also, this research aims to recognize emotions using deep learning and show the influences of data pre-processing for further processing of images. The accuracy of each pre-processing methods is compared, then combination between them is analysed and the appropriate preprocessing techniques are identified and implemented to see the variability of accuracies in predicting facial expressions. .展开更多
Clavicle fractures are among the most prevalent types of fractures with numerous treatment strategies that have evolved over time.In the realm of lateral-third clavicle fracture management,several surgical methods are...Clavicle fractures are among the most prevalent types of fractures with numerous treatment strategies that have evolved over time.In the realm of lateral-third clavicle fracture management,several surgical methods are available,with plate and screw constructs being one of the most frequently employed options.Within this construct,numerous choices exist for fixing the fracture.This editorial provides an overview of the common plate options utilized in the management of distal third clavicle fractures underscoring the critical considerations and approaches that guide clinicians in selecting the most appropriate fixation techniques,considering the complex landscape of clavicle fractures and their challenging management.展开更多
Tenosynovitis represents a common clinical condition characterized by inflam-mation of the synovium that encases the tendon sheath.Although tenosynovities may be noted in any tendon in the body,extremities such as han...Tenosynovitis represents a common clinical condition characterized by inflam-mation of the synovium that encases the tendon sheath.Although tenosynovities may be noted in any tendon in the body,extremities such as hand,and foot remain the sites of high predilection to acquire this condition.The predominant cause of this predilection rests in the intricate tendon arrangements in these extremities that permit fine motor actions.This editorial explores the common causes and the complications associated with this condition to improve the understanding of the readers of this common condition encountered in our everyday clinical practice.展开更多
Emotion represents the feeling of an individual in a given situation. There are various ways to express the emotions of an individual. It can be categorized into verbal expressions, written expressions, facial express...Emotion represents the feeling of an individual in a given situation. There are various ways to express the emotions of an individual. It can be categorized into verbal expressions, written expressions, facial expressions and gestures. Among these various ways of expressing the emotion, the written method is a challenging task to extract the emotions, as the data is in the form of textual dat. Finding the different kinds of emotions is also a tedious task as it requires a lot of pre preparations of the textual data taken for the research. This research work is carried out to analyse and extract the emotions hidden in text data. The text data taken for the analysis is from the social media dataset. Using the raw text data directly from the social media will not serve the purpose. Therefore, the text data has to be pre-processed and then utilised for further processing. Pre-processing makes the text data more efficient and would infer valuable insights of the emotions hidden in it. The preprocessing steps also help to manage the text data for identifying the emotions conveyed in the text. This work proposes to deduct the emotions taken from the social media text data by applying the machine learning algorithm. Finally, the usefulness of the emotions is suggested for various stake holders, to find the attitude of individuals at that moment, the data is produced. .展开更多
This paper concentrates on enhancing the productivity of the multilevel inverter and nature of yield voltage waveform. Seven level lessened switches topology has been actualized with just seven switches. Essential Swi...This paper concentrates on enhancing the productivity of the multilevel inverter and nature of yield voltage waveform. Seven level lessened switches topology has been actualized with just seven switches. Essential Switching plan and Selective Harmonics Elimination were executed to diminish the Total Harmonics Distortion (THD) esteem. Selective Harmonics Elimination Stepped Waveform (SHESW) strategy is executed to dispense with the lower order harmonics. Fundamental switching plan is utilized to control the switches in the inverter. The proposed topology is reasonable for any number of levels. The harmonic lessening is accomplished by selecting fitting switching angles. It indicates would like to decrease starting expense and unpredictability consequently it is able for modern applications. In this paper, third and fifth level harmonics have been disposed of. Simulation work is done utilizing the MATLAB/Simulink programming results have been displayed to accept the hypothesis.展开更多
Under mixed traffic conditions prevailing on Indian roads,drivers show complex response when faced with yellow signal because lane assignment gets dynamic in nature.The present study analyzes the effect of surrounding...Under mixed traffic conditions prevailing on Indian roads,drivers show complex response when faced with yellow signal because lane assignment gets dynamic in nature.The present study analyzes the effect of surrounding vehicles on response of the drivers while facing dilemma at intersections.Although dilemma zone definitions hold true in case of homogeneous traffic mix,a statistical analysis is performed to check the consistency across the definitions under mixed traffic condition.Present study shows a significant difference in percentage of red light running in comparison to homogeneous traffic as reported by various studies.For carrying out the research,study locations are chosen in such a way to reflect diversity in road geometry,traffic composition and signal characteristics.The results deduced in this study indicate a strong correlation between the driver's decision making choice and the effect of presence of surrounding vehicle at the onset of yellow signal.The effect of critical time analysis has been found out to be one of the parameters other than critical distance in categorizing driver's aggressiveness while facing the yellow signal.In the process of identifying the statistical significance of dilemma zone definitions,it has been found that under heterogeneous traffic condition,drivers behave differently as compared to homogenous traffic when it comes to dilemma zone.It is observed that the percentage of vehicles crossing the intersection when faced with dilemma by violating the red light is 11.6%according to dilemma zone definition I whereas the definition II has yielded about 10.8%violation covering different vehicle types.The above violation figures derived based on the above definition is somewhat higher as compared to homogeneous traffic condition which is observed to be of the order of 5%-6%.展开更多
In this paper, we study a fractional-order model with time-delay to describe the dynamics of Ebola virus infection with cytotoxic T-lymphocyte （CTL） response in vivo. The time- delay is introduced in the CTL respons...In this paper, we study a fractional-order model with time-delay to describe the dynamics of Ebola virus infection with cytotoxic T-lymphocyte （CTL） response in vivo. The time- delay is introduced in the CTL response term to represent time required to stimulate the immune system. Based on fractional Laplace transform, some conditions on stability and Hopf bifurcation are derived for the model. The analysis shows that the fractional- order with time-delay can effectively enrich the dynamics and strengthen the stability condition of fractional-order infection model. Finally, the derived theoretical results are justified by some numerical simulations.展开更多
Inverters are power electronic devices that change over DC to sinusoidal AC quantity. Be that as it may, in down to earth, these devices produce non-sinusoidal yield which contains harmonics, so as to blend a close si...Inverters are power electronic devices that change over DC to sinusoidal AC quantity. Be that as it may, in down to earth, these devices produce non-sinusoidal yield which contains harmonics, so as to blend a close sinusoidal component and to lessen the harmonic distortion multilevel inverters developed. Mathematical methods, which were developed, are derivative based and need initial considerations. To overcome this, evolutionary algorithms, which are derivative free and accurate, were developed for obtaining multi levels of output voltage. The proposed work uses two evolutionary algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. These algorithms are used to generate the switching angles by satisfying the non linear transcendental equations that govern the low order harmonic components. A seven level cascaded full bridge inverter is designed using MATLAB/Simulink and the results validate the results for switching angles. The Total Harmonic Distortion (THD) value obtained for GA and PSO is 11.81% and 10.84% respectively. The solution obtained from GA algorithm was implemented in hardware using dsPIC controller to validate the simulation results. The THD value obtained for cascaded seven-level multilevel inverter in the hardware prototype is 25.9%.展开更多
<div style="text-align:justify;"> Recent days, heart ailments assume a fundamental role in the world. The physician gives different name for heart disease, for example, cardiovascular failure, heart fa...<div style="text-align:justify;"> Recent days, heart ailments assume a fundamental role in the world. The physician gives different name for heart disease, for example, cardiovascular failure, heart failure and so on. Among the automated techniques to discover the coronary illness, this research work uses Named Entity Recognition (NER) algorithm to discover the equivalent words for the coronary illness content to mine the significance in clinical reports and different applications. The Heart sickness text information given by the physician is taken for the preprocessing and changes the text information to the ideal meaning, at that point the resultant text data taken as input for the prediction of heart disease. This experimental work utilizes the NER to discover the equivalent words of the coronary illness text data and currently uses the two strategies namely Optimal Deep Learning and Whale Optimization which are consolidated and proposed another strategy Optimal Deep Neural Network (ODNN) for predicting the illness. For the prediction, weights and ranges of the patient affected information by means of chosen attributes are picked for the experiment. The outcome is then characterized with the Deep Neural Network and Artificial Neural Network to discover the accuracy of the algorithms. The performance of the ODNN is assessed by means for classification methods, for example, precision, recall and f-measure values. </div>展开更多
Beach pea or beach cowpea(Vigna marina(Burm.)Merr.)belongs to the family Fabaceae.It is a close relative of cultivated Vigna species such as adzuki bean(V.angularis),cowpea(V.unguiculata),mung bean(V.radiata),and blac...Beach pea or beach cowpea(Vigna marina(Burm.)Merr.)belongs to the family Fabaceae.It is a close relative of cultivated Vigna species such as adzuki bean(V.angularis),cowpea(V.unguiculata),mung bean(V.radiata),and blackgram(V.mungo),and is distributed throughout the tropics.With its ability to tolerate salt stress,beach pea has great potential to contribute salt-tolerance genes for developing salt-tolerant cultivars in cultivated Vigna species.However,it is still underutilized in Vigna breeding programs.A draft genome sequence of beach pea was generated using a high-throughput next-generation sequencing platform,yielding 23.7 Gb of sequence from 79,929,868 filtered reads.A de novo genome assembly containing 68,731 scaffolds gave an N50 length of 10,272 bp and the assembled sequences totaled 365.6 Mb.A total of 35,448 SSRs,including 3574 compound SSRs,were identified and primer pairs for most of these SSRs were designed.Genome analysis identified 50,670 genes with mean coding sequence length 1042 bp.Phylogenetic analysis revealed highest sequence similarity with V.angularis,followed by V.radiata.Comparison with the V.angularis genome revealed 16,699 SNPs and 2253 InDels and comparison with the V.radiata genome revealed 17,538 SNPs and 2300 InDels.To our knowledge this is the first draft genome sequence of beach pea derived from an accession(ANBp-14-03)adapted locally in the Andaman and Nicobar Islands of India.The draft genome sequence may facilitate the genetic enhancement in cultivated Vigna species.展开更多
There is a paradigm shift happening in automotive industry towards electric vehicles as environment and sustainability issues gainedmomentum in the recent years among potential users.Connected and Autonomous Electric ...There is a paradigm shift happening in automotive industry towards electric vehicles as environment and sustainability issues gainedmomentum in the recent years among potential users.Connected and Autonomous Electric Vehicle(CAEV)technologies are fascinating the automakers and inducing them to manufacture connected autonomous vehicles with self-driving features such as autopilot and self-parking.Therefore,Traffic Flow Prediction(TFP)is identified as a major issue in CAEV technologies which needs to be addressed with the help of Deep Learning(DL)techniques.In this view,the current research paper presents an artificial intelligence-based parallel autoencoder for TFP,abbreviated as AIPAE-TFP model in CAEV.The presented model involves two major processes namely,feature engineering and TFP.In feature engineering process,there are multiple stages involved such as feature construction,feature selection,and feature extraction.In addition to the above,a Support Vector Data Description(SVDD)model is also used in the filtration of anomaly points and smoothen the raw data.Finally,AIPAE model is applied to determine the predictive values of traffic flow.In order to illustrate the proficiency of the model’s predictive outcomes,a set of simulations was performed and the results were investigated under distinct aspects.The experimentation outcomes verified the effectual performance of the proposed AIPAE-TFP model over other methods.展开更多
The rapid depletion of fossil fuel and growing demand necessitates researchers to find alternative fuels which are clean and sustainable. The need for finding renewable, low cost and environmentally friendly fuel reso...The rapid depletion of fossil fuel and growing demand necessitates researchers to find alternative fuels which are clean and sustainable. The need for finding renewable, low cost and environmentally friendly fuel resources can never be understated. An efficient method of generation and storage of hydrogen will enable automotive manufacturers to introduce hydrogen fuelled engine in the market. In this paper, a conventional DI diesel engine was modified to operate as gas engine. The intake manifold of the engine was supplied with hydrogen along with recirculated exhaust gas and air. The injection rates of hydrogen were maintained at three levels with 2 L/min, 4 L/min, 6 L/min and 8 L/min and 10 L/min with an injection pressure of 2 bar. Many of the combustion parameters like heat release rate （HRR）, ignition delay, combustion duration, rate of pressure rise （ROPR）, cumulative heat release rate （CHR）, and cyclic pressure fluctuations were measured. The HRR peak pressure decreased with the increase in EGR rate, while combustion duration increased with the EGR rate. The cyclic pressure variation also increased with the increase in EGR rate.展开更多
This study aims to investigate the effects of variable thread pitch on stress distribution in bones of different bone qualities under two different loading conditions(Vertical,and Horizontal)for a Zirconia dental impl...This study aims to investigate the effects of variable thread pitch on stress distribution in bones of different bone qualities under two different loading conditions(Vertical,and Horizontal)for a Zirconia dental implant.For this purpose,a three dimensional finite element model of the mandibular premolar section and three single threaded implants of 0.8 mm,1.6 mm,2.4 mm pitch was designed.Finite element analysis software was used to develop the model and three different bone qualities(Type II,Type III,and Type IV)were prepared.A vertical load of 200 N,and a horizontal load of 100 N was applied at the abutment surface.The von-Mises stress criterion was used to analyze the results.The crestal bony-region of the mandibular section was subjected to maximum von-Mises stresses for all bone qualities.The outcome of this study indicates that,horizontal loading had more influence on stress distribution than vertical loading,regardless of the bone qualities and pitch values.Varying the dental implant pitch does not cause any decrease in stress distribution in bone,when the bone density decreased.The study concluded that implants with minimum pitch values induced lesser stress values at the implant-bone interface.展开更多
In recent times,financial globalization has drastically increased in different ways to improve the quality of services with advanced resources.The successful applications of bitcoin Blockchain(BC)techniques enable the...In recent times,financial globalization has drastically increased in different ways to improve the quality of services with advanced resources.The successful applications of bitcoin Blockchain(BC)techniques enable the stockholders to worry about the return and risk of financial products.The stockholders focused on the prediction of return rate and risk rate of financial products.Therefore,an automatic return rate bitcoin prediction model becomes essential for BC financial products.The newly designed machine learning(ML)and deep learning(DL)approaches pave the way for return rate predictive method.This study introduces a novel Jellyfish search optimization based extreme learning machine with autoencoder(JSO-ELMAE)for return rate prediction of BC financial products.The presented JSO-ELMAE model designs a new ELMAE model for predicting the return rate of financial products.Besides,the JSO algorithm is exploited to tune the parameters related to the ELMAE model which in turn boosts the classification results.The application of JSO technique assists in optimal parameter adjustment of the ELMAE model to predict the bitcoin return rates.The experimental validation of the JSO-ELMAE model was executed and the outcomes are inspected in many aspects.The experimental values demonstrated the enhanced performance of the JSO-ELMAE model over recent state of art approaches with minimal RMSE of 0.1562.展开更多
文摘Coronary artery disease(CAD) occurring in less than 45 years of age is termed as young CAD.Recent studies show a prevalence of 1.2% of CAD cases in this age group.Ethnic wise south Asians especially Indians are more vulnerable to have CAD in young age group with a prevalence of 5% to 10%.Conventional risk factors such as smoking,diabetes,hypertension,obesity and family history seems to be as important as in older CAD subjects.But the prevalence of these risk factors seems to vary in younger subjects.By far the most commonly associated risk factor is smoking in young CAD.Several genes associated with lipoprotein metabolism are now found to be associated with young CAD like cholesterol ester transfer protein(CETP) gene,hepatic lipase gene,lipoprotein lipase gene,apo A1 gene,apo E gene and apo B.Biomarkers such as lipoprotein(a),fibrinogen,D-dimer,serum Wnt,gamma glutamyl transferase,vitamin D2 and osteocalcin are seems to be associated with premature CAD in some newer studies.In general CAD in young has better prognosis than older subjects.In terms of prognosis two risk factors obesity and current smoking are associated with poorer outcomes.Angiographic studies shows predominance of single vessel disease in young CAD patients.Like CAD in older person primary and secondary prevention plays an important role in prevention of new and further coronary events.
基金supported by Agricultural R&D Promotion Center,South Korea (No. 060101001)
文摘A heavy metal contaminated soil sample collected from a mine in Chonnam Province of South Korea was found to be a source of heavy metal adsorbing biosorbents. Chemical analyses showed high contents of lead （Pb） at 357 mg/kg and cyanide （CN） at 14.6 mg/kg in the soil. The experimental results showed that Penicillium sp. MRF-1 was the best lead resistant fungus among the four individual metal tolerant fungal species isolated from the soil. Molecular characterization of Penicillium sp. MRF-1 was determined using ITS regions sequences. Effects of pH, temperature and contact time on adsorption of Pb（Ⅱ） by Penicillium sp. MRF-1 were studied. Favorable conditions for maximum biosportion were found at pH 4 with 3 hr contact time. Biosorption of Pb（Ⅱ） gradually increased with increasing temperature. Efficient performance of the biosorbent was described using Langmuir and Freundlich isotherms. Adsorption kinetics was studied using pseudo first-order and pseudo second-order models. Biosorbent Penicillium sp. MRF-1 showed the maximum desorption in alkali conditions. Consistent adsorption/desorption potential of the biosorbent in repetitive cycles validated the efficacy of it in large scale. SEM studies given notes on surface modification of fungal biomass under metal stress and FT-IR results showed the presence of amino groups in the surface structure of the biosorbent. In conclusion, the new biosorbent Penicillium sp. MRF- 1 may potentially be used as an inexpensive, easily cultivatable material for the removal of lead from aqueous solution.
基金supported by the National Natural Science Foundation of China for the Sino-German Mobility Program(grant no.M-0411)the Natural Science Foundation of Jiangsu Province(grant nos.BK20211179 and BK20200432)the Fundamental Research Funds for the Central Universities(grant no.NS2021040).
文摘Amplified chirality and Förster resonance energy transfer(FRET)-assisted chirality transfer frommolecular to nanoscale level have been shown to play a vital role in co-assembled nanohelix for potential energy transfer in biological systems.Herein,we have constructed a chiral host–guest complex donor system for chiral amplification via induced chirality of pillar[5]arene host and loaded it with an achiral dye acceptor to demonstrate how chirality-assisted excitation energy transfer occurred in the supramolecular nanohelix system in an aqueous medium.
基金The work was supported by Tamil Nadu State Council for Science and Technology(TNSCST),Chennai,India(MS-004/TNSCST/SPS/AR/2010-2011)
文摘Objective:To characterize the pharmacological importance of biosurfactants isolated from halophilic Bacillus sp BS3.Methods:Halophilic Bacillus sp.BS3 was isolated from solar salt works,identified by 16S rRNA sequencing and was used for screening their biosurfactant production.Characters of the biosurfactant and their anticancer activity were analyzed and performed in mammary epithelial carcinoma cell at different concentrations.Results:The biosurfactant were characterized by TLC,FTIR and GC-MS analysis and identified as lipopeptide type.GC-MS analysis revealed that,the biosurfactant had various compounds including 13Docosenamide.(Z);Mannosamine,9- and N,N,N',N'-tetramethyl.Surprisingly the antiviral activity was found against shrimp white spot syndrome virus(WSSV) by suppressing the viral replication and significantly raised shrimp survival(P<0.01).Anticancer activity performed in the mammary epithelial carcinoma cell at different concentrations of biosurfactants,among the various concentrations of biosurfactants such as 0.000 25,0.002 5,0.025,0.25 and 2.5 μ g,the 0.25 μ g concentration suppressed the cells significantly(P<0.05) to 24.8%.Conclusions:Based on the findings,the present study concluded that,there is a possibility to develop eco-friendly antimicrobial and anticancer drugs from the extremophilic origin.
文摘Li-Fraumeni syndrome(LFS)is a well-defined autosomal dominant predisposition syndrome due to TP53 germline mutation that causes many cancer malig-nancies.This early-onset syndrome poses a state of widespread malignancy.Such an inherited condition possessing defective p53,guardian of the genome,in the germline has the potential to cause multiple cancers by predominantly affecting mesenchyme(connective tissues,blood cells),breast,brain,and adrenal cortex organs.The tumors initially identified in LFS can eventually propagate to cause secondary malignancies.LFS contributes to multiple cancers in individuals with defective p53 inheritance.When suspected to possess any mass,patients with other co-morbidities,in particular those with certain cardiovascular conditions,undergo screening using high-throughput techniques like transthoracic and transesophageal echocardiography or cardiothoracic magnetic resonance imaging to locate and interpret the size of the mass.In LFS cases,it is certain to presume these masses as cancers and plan their management employing invasive surgeries after performing all efficient diagnostic tools.There are only poor predictions to rule out the chances of any other pathology.This criterion emphasizes the necessity to speculate alternative precision diagnostic methods to affirm such new growth or masses encountered in LFS cases.Moreover,it has all the possibilities to ultimately influence surgical procedures that may be invasive or complicate operative prognosis.Hence,it is essential to strategize an ideal protocol to diagnose any new unexplored mass in the LFS community.In this editorial,we discuss the importance of diagnostic approaches on naïve pristine masses in LFS.
文摘Different types of neuroendocrine cancer,including medullary thyroid cancer(MTC)and thyroid C-cell hyperplasia,are part of multiple endocrine neoplasia type 2(MEN2).A proto-oncogene mutation of the rearranged during transfection(RET)gene changes the way that receptor tyrosine kinases work.Multiple endocrine neoplasia,a pathological condition,involves these kinases.When the RET protooncogene changes,it can cause endocrine adenomas and hyperplasia to happen at the same time or one after the other.Pheochromocytoma,medullary thyroid carcinoma,and hyperparathyroidism,alone or in combination,are present in MEN2A patients.Some patients may also have skin lichen amyloidosis or Hirschsprung's disease.Patients with MEN2A often present with MTC.MTC is aggressive and has the worst prognosis,as most patients exhibit lymph node metastasis.MTC is one of the important causes of death in patients with MEN2A.RET mutation analysis aids in identifying MEN2A symptoms and monitoring levels of calcium,thyroid hormones,calcitonin,normetanephrine,fractionated metanephrines,and parathyroid hormone.The earlier diagnosis of MTC significantly improves survival and prompts better management of MEN2A.In this editorial,we will discuss the significance of molecular diagnostic approaches in detecting RET oncogene mutations in MEN2A.
文摘Analyzing human facial expressions using machine vision systems is indeed a challenging yet fascinating problem in the field of computer vision and artificial intelligence. Facial expressions are a primary means through which humans convey emotions, making their automated recognition valuable for various applications including man-computer interaction, affective computing, and psychological research. Pre-processing techniques are applied to every image with the aim of standardizing the images. Frequently used techniques include scaling, blurring, rotating, altering the contour of the image, changing the color to grayscale and normalization. Followed by feature extraction and then the traditional classifiers are applied to infer facial expressions. Increasing the performance of the system is difficult in the typical machine learning approach because feature extraction and classification phases are separate. But in Deep Neural Networks (DNN), the two phases are combined into a single phase. Therefore, the Convolutional Neural Network (CNN) models give better accuracy in Facial Expression Recognition than the traditional classifiers. But still the performance of CNN is hampered by noisy and deviated images in the dataset. This work utilized the preprocessing methods such as resizing, gray-scale conversion and normalization. Also, this research work is motivated by these drawbacks to study the use of image pre-processing techniques to enhance the performance of deep learning methods to implement facial expression recognition. Also, this research aims to recognize emotions using deep learning and show the influences of data pre-processing for further processing of images. The accuracy of each pre-processing methods is compared, then combination between them is analysed and the appropriate preprocessing techniques are identified and implemented to see the variability of accuracies in predicting facial expressions. .
文摘Clavicle fractures are among the most prevalent types of fractures with numerous treatment strategies that have evolved over time.In the realm of lateral-third clavicle fracture management,several surgical methods are available,with plate and screw constructs being one of the most frequently employed options.Within this construct,numerous choices exist for fixing the fracture.This editorial provides an overview of the common plate options utilized in the management of distal third clavicle fractures underscoring the critical considerations and approaches that guide clinicians in selecting the most appropriate fixation techniques,considering the complex landscape of clavicle fractures and their challenging management.
文摘Tenosynovitis represents a common clinical condition characterized by inflam-mation of the synovium that encases the tendon sheath.Although tenosynovities may be noted in any tendon in the body,extremities such as hand,and foot remain the sites of high predilection to acquire this condition.The predominant cause of this predilection rests in the intricate tendon arrangements in these extremities that permit fine motor actions.This editorial explores the common causes and the complications associated with this condition to improve the understanding of the readers of this common condition encountered in our everyday clinical practice.
文摘Emotion represents the feeling of an individual in a given situation. There are various ways to express the emotions of an individual. It can be categorized into verbal expressions, written expressions, facial expressions and gestures. Among these various ways of expressing the emotion, the written method is a challenging task to extract the emotions, as the data is in the form of textual dat. Finding the different kinds of emotions is also a tedious task as it requires a lot of pre preparations of the textual data taken for the research. This research work is carried out to analyse and extract the emotions hidden in text data. The text data taken for the analysis is from the social media dataset. Using the raw text data directly from the social media will not serve the purpose. Therefore, the text data has to be pre-processed and then utilised for further processing. Pre-processing makes the text data more efficient and would infer valuable insights of the emotions hidden in it. The preprocessing steps also help to manage the text data for identifying the emotions conveyed in the text. This work proposes to deduct the emotions taken from the social media text data by applying the machine learning algorithm. Finally, the usefulness of the emotions is suggested for various stake holders, to find the attitude of individuals at that moment, the data is produced. .
文摘This paper concentrates on enhancing the productivity of the multilevel inverter and nature of yield voltage waveform. Seven level lessened switches topology has been actualized with just seven switches. Essential Switching plan and Selective Harmonics Elimination were executed to diminish the Total Harmonics Distortion (THD) esteem. Selective Harmonics Elimination Stepped Waveform (SHESW) strategy is executed to dispense with the lower order harmonics. Fundamental switching plan is utilized to control the switches in the inverter. The proposed topology is reasonable for any number of levels. The harmonic lessening is accomplished by selecting fitting switching angles. It indicates would like to decrease starting expense and unpredictability consequently it is able for modern applications. In this paper, third and fifth level harmonics have been disposed of. Simulation work is done utilizing the MATLAB/Simulink programming results have been displayed to accept the hypothesis.
基金The authors would like to thank senior colleagues and technical staff for their continuous support for carrying out this project as well as director,Central Road Research Institute,New Delhi,for allowing us to take up this work as an in-house R&D project(OLP-0597).
文摘Under mixed traffic conditions prevailing on Indian roads,drivers show complex response when faced with yellow signal because lane assignment gets dynamic in nature.The present study analyzes the effect of surrounding vehicles on response of the drivers while facing dilemma at intersections.Although dilemma zone definitions hold true in case of homogeneous traffic mix,a statistical analysis is performed to check the consistency across the definitions under mixed traffic condition.Present study shows a significant difference in percentage of red light running in comparison to homogeneous traffic as reported by various studies.For carrying out the research,study locations are chosen in such a way to reflect diversity in road geometry,traffic composition and signal characteristics.The results deduced in this study indicate a strong correlation between the driver's decision making choice and the effect of presence of surrounding vehicle at the onset of yellow signal.The effect of critical time analysis has been found out to be one of the parameters other than critical distance in categorizing driver's aggressiveness while facing the yellow signal.In the process of identifying the statistical significance of dilemma zone definitions,it has been found that under heterogeneous traffic condition,drivers behave differently as compared to homogenous traffic when it comes to dilemma zone.It is observed that the percentage of vehicles crossing the intersection when faced with dilemma by violating the red light is 11.6%according to dilemma zone definition I whereas the definition II has yielded about 10.8%violation covering different vehicle types.The above violation figures derived based on the above definition is somewhat higher as compared to homogeneous traffic condition which is observed to be of the order of 5%-6%.
文摘In this paper, we study a fractional-order model with time-delay to describe the dynamics of Ebola virus infection with cytotoxic T-lymphocyte （CTL） response in vivo. The time- delay is introduced in the CTL response term to represent time required to stimulate the immune system. Based on fractional Laplace transform, some conditions on stability and Hopf bifurcation are derived for the model. The analysis shows that the fractional- order with time-delay can effectively enrich the dynamics and strengthen the stability condition of fractional-order infection model. Finally, the derived theoretical results are justified by some numerical simulations.
文摘Inverters are power electronic devices that change over DC to sinusoidal AC quantity. Be that as it may, in down to earth, these devices produce non-sinusoidal yield which contains harmonics, so as to blend a close sinusoidal component and to lessen the harmonic distortion multilevel inverters developed. Mathematical methods, which were developed, are derivative based and need initial considerations. To overcome this, evolutionary algorithms, which are derivative free and accurate, were developed for obtaining multi levels of output voltage. The proposed work uses two evolutionary algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. These algorithms are used to generate the switching angles by satisfying the non linear transcendental equations that govern the low order harmonic components. A seven level cascaded full bridge inverter is designed using MATLAB/Simulink and the results validate the results for switching angles. The Total Harmonic Distortion (THD) value obtained for GA and PSO is 11.81% and 10.84% respectively. The solution obtained from GA algorithm was implemented in hardware using dsPIC controller to validate the simulation results. The THD value obtained for cascaded seven-level multilevel inverter in the hardware prototype is 25.9%.
文摘<div style="text-align:justify;"> Recent days, heart ailments assume a fundamental role in the world. The physician gives different name for heart disease, for example, cardiovascular failure, heart failure and so on. Among the automated techniques to discover the coronary illness, this research work uses Named Entity Recognition (NER) algorithm to discover the equivalent words for the coronary illness content to mine the significance in clinical reports and different applications. The Heart sickness text information given by the physician is taken for the preprocessing and changes the text information to the ideal meaning, at that point the resultant text data taken as input for the prediction of heart disease. This experimental work utilizes the NER to discover the equivalent words of the coronary illness text data and currently uses the two strategies namely Optimal Deep Learning and Whale Optimization which are consolidated and proposed another strategy Optimal Deep Neural Network (ODNN) for predicting the illness. For the prediction, weights and ranges of the patient affected information by means of chosen attributes are picked for the experiment. The outcome is then characterized with the Deep Neural Network and Artificial Neural Network to discover the accuracy of the algorithms. The performance of the ODNN is assessed by means for classification methods, for example, precision, recall and f-measure values. </div>
文摘Beach pea or beach cowpea(Vigna marina(Burm.)Merr.)belongs to the family Fabaceae.It is a close relative of cultivated Vigna species such as adzuki bean(V.angularis),cowpea(V.unguiculata),mung bean(V.radiata),and blackgram(V.mungo),and is distributed throughout the tropics.With its ability to tolerate salt stress,beach pea has great potential to contribute salt-tolerance genes for developing salt-tolerant cultivars in cultivated Vigna species.However,it is still underutilized in Vigna breeding programs.A draft genome sequence of beach pea was generated using a high-throughput next-generation sequencing platform,yielding 23.7 Gb of sequence from 79,929,868 filtered reads.A de novo genome assembly containing 68,731 scaffolds gave an N50 length of 10,272 bp and the assembled sequences totaled 365.6 Mb.A total of 35,448 SSRs,including 3574 compound SSRs,were identified and primer pairs for most of these SSRs were designed.Genome analysis identified 50,670 genes with mean coding sequence length 1042 bp.Phylogenetic analysis revealed highest sequence similarity with V.angularis,followed by V.radiata.Comparison with the V.angularis genome revealed 16,699 SNPs and 2253 InDels and comparison with the V.radiata genome revealed 17,538 SNPs and 2300 InDels.To our knowledge this is the first draft genome sequence of beach pea derived from an accession(ANBp-14-03)adapted locally in the Andaman and Nicobar Islands of India.The draft genome sequence may facilitate the genetic enhancement in cultivated Vigna species.
文摘There is a paradigm shift happening in automotive industry towards electric vehicles as environment and sustainability issues gainedmomentum in the recent years among potential users.Connected and Autonomous Electric Vehicle(CAEV)technologies are fascinating the automakers and inducing them to manufacture connected autonomous vehicles with self-driving features such as autopilot and self-parking.Therefore,Traffic Flow Prediction(TFP)is identified as a major issue in CAEV technologies which needs to be addressed with the help of Deep Learning(DL)techniques.In this view,the current research paper presents an artificial intelligence-based parallel autoencoder for TFP,abbreviated as AIPAE-TFP model in CAEV.The presented model involves two major processes namely,feature engineering and TFP.In feature engineering process,there are multiple stages involved such as feature construction,feature selection,and feature extraction.In addition to the above,a Support Vector Data Description(SVDD)model is also used in the filtration of anomaly points and smoothen the raw data.Finally,AIPAE model is applied to determine the predictive values of traffic flow.In order to illustrate the proficiency of the model’s predictive outcomes,a set of simulations was performed and the results were investigated under distinct aspects.The experimentation outcomes verified the effectual performance of the proposed AIPAE-TFP model over other methods.
文摘The rapid depletion of fossil fuel and growing demand necessitates researchers to find alternative fuels which are clean and sustainable. The need for finding renewable, low cost and environmentally friendly fuel resources can never be understated. An efficient method of generation and storage of hydrogen will enable automotive manufacturers to introduce hydrogen fuelled engine in the market. In this paper, a conventional DI diesel engine was modified to operate as gas engine. The intake manifold of the engine was supplied with hydrogen along with recirculated exhaust gas and air. The injection rates of hydrogen were maintained at three levels with 2 L/min, 4 L/min, 6 L/min and 8 L/min and 10 L/min with an injection pressure of 2 bar. Many of the combustion parameters like heat release rate （HRR）, ignition delay, combustion duration, rate of pressure rise （ROPR）, cumulative heat release rate （CHR）, and cyclic pressure fluctuations were measured. The HRR peak pressure decreased with the increase in EGR rate, while combustion duration increased with the EGR rate. The cyclic pressure variation also increased with the increase in EGR rate.
文摘This study aims to investigate the effects of variable thread pitch on stress distribution in bones of different bone qualities under two different loading conditions(Vertical,and Horizontal)for a Zirconia dental implant.For this purpose,a three dimensional finite element model of the mandibular premolar section and three single threaded implants of 0.8 mm,1.6 mm,2.4 mm pitch was designed.Finite element analysis software was used to develop the model and three different bone qualities(Type II,Type III,and Type IV)were prepared.A vertical load of 200 N,and a horizontal load of 100 N was applied at the abutment surface.The von-Mises stress criterion was used to analyze the results.The crestal bony-region of the mandibular section was subjected to maximum von-Mises stresses for all bone qualities.The outcome of this study indicates that,horizontal loading had more influence on stress distribution than vertical loading,regardless of the bone qualities and pitch values.Varying the dental implant pitch does not cause any decrease in stress distribution in bone,when the bone density decreased.The study concluded that implants with minimum pitch values induced lesser stress values at the implant-bone interface.
基金supported in part by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2021R1A6A1A03039493)by the NRF grant funded by the Korea government(MSIT)(NRF-2022R1A2C1004401).
文摘In recent times,financial globalization has drastically increased in different ways to improve the quality of services with advanced resources.The successful applications of bitcoin Blockchain(BC)techniques enable the stockholders to worry about the return and risk of financial products.The stockholders focused on the prediction of return rate and risk rate of financial products.Therefore,an automatic return rate bitcoin prediction model becomes essential for BC financial products.The newly designed machine learning(ML)and deep learning(DL)approaches pave the way for return rate predictive method.This study introduces a novel Jellyfish search optimization based extreme learning machine with autoencoder(JSO-ELMAE)for return rate prediction of BC financial products.The presented JSO-ELMAE model designs a new ELMAE model for predicting the return rate of financial products.Besides,the JSO algorithm is exploited to tune the parameters related to the ELMAE model which in turn boosts the classification results.The application of JSO technique assists in optimal parameter adjustment of the ELMAE model to predict the bitcoin return rates.The experimental validation of the JSO-ELMAE model was executed and the outcomes are inspected in many aspects.The experimental values demonstrated the enhanced performance of the JSO-ELMAE model over recent state of art approaches with minimal RMSE of 0.1562.
