34 research outputs found
Energy efficient parallel configuration based six degree of freedom machining bed
The process of material removal from a workpiece to obtain the desired shape is termed machining. Present-day material removal technologies have high spindle speeds and thus allow quick material removal. These high-speed spindles are highly exposed to vibrations and, as a result, the accuracy of the final workpiece’s dimensions is compromised. To overcome this problem, the motion of the tool is restricted, and multiple degrees of freedom are given through the motion of the workpiece in different axes. A machining bed configured as a parallel manipulator capable of giving six degrees of freedom (DOF) to the workpiece is proposed in this regard. However, the proposed six DOF machining bed should be energy efficient to avoid an increase in machining cost. The benefit of using the proposed configuration is a reduction in dimensional error and computational time which, as a result, reduces the energy utilization, vibrations, and machining time in practice. This paper presents kinematics, dynamics and energy efficiency models, and the development of the proposed configuration of the machining bed. The energy efficiency model is derived from the dynamics model. The models are verified in simulation and experimentally. To minimize error and computation time, a PID controller is also designed and tested in simulation as well as experimentally. The resulting energy efficiency is also analyzed. The results verify the efficacy of the proposed configuration of the machining bed, minimizing position error to 2% and reducing computation time by 27%, hence reducing the energy consumption and enhancing the energy efficiency by 60%
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Potential of waste cooking oil biodiesel as renewable fuel in combustion engines:A review
LC-MS/MS and GC-MS Analysis for the Identification of Bioactive Metabolites Responsible for the Antioxidant and Antibacterial Activities of Lygodium microphyllum (Cav.) R. Br
Natural products serve as a valuable source of antioxidants with potential health benefits for various conditions. Lygodium microphyllum (Cav.) R. Br., also known as Old World climbing fern, is an invasive climbing fern native to Southeast Asia, Africa, South America, Australia, and Melanesia. It has been reported to possess interesting pharmacological properties including hepatoprotective and anti-inflammatory mechanisms. This study analyzed the potential bioactive metabolites that contribute to the antioxidant and antimicrobial effects of L. microphyllum (LM) by profiling the crude extract using high-resolution LC-MS/MS and GC-MS systems. Several classes of compounds such as phenolics, flavonoids, terpenoids, steroids, macrolides, vitamins, lipids, and other hydrocarbons were found in the crude extract of LM through non-targeted analysis. A total of 74 compounds were detected in LC-MS/MS, whereas a total of nine compounds were identified in GC-MS. Out of the 74 compounds detected in LC-MS/MS, 34 compounds, primarily quercetin, kaempferol, trifolin, pyroglutamic acid, arachidonic acid, and rutin were reported with antioxidant, antimicrobial, antiinflammatory, and hepatoprotective activities. The presence of phenolic and flavonoid compounds with reported bioactivities in the crude extract of LM evidence its pharmacological properties
The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study
Objective
To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation.
Patients and Methods
This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries.
Results
Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3–34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1–30.2), UTUC (n = 128) 1.14% (95% CI 0.77–1.52), renal cancer (n = 107) 1.05% (95% CI 0.80–1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32–2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03–1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90–4.15; P < 0.001), male sex 1.30 (95% CI 1.14–1.50; P < 0.001), and smoking 2.70 (95% CI 2.30–3.18; P < 0.001).
Conclusions
A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
Development and Demonstration of a Cost-Effective In-Vehicle Lane Departure and Advanced Curve Speed Warning System
A Lane-Departure Warning System (LDWS) and Advance Curve -Warning System (ACWS) are critical among several Advanced Driver- Assistance Systems (ADAS) functions, having significant potential to reduce crashes. Generally, LDWS us e different image processing or optical s canning techniques to detect a lane departure. Such LDWS have some limitations such as harsh weather or irregular la ne markings can influence their performance. Other LDWS use a GPS receiver with access to digital maps with lane-level resolution to improve the system's efficiency but make the overall system more complex and expensive. In this report, a lane-departure detection method is proposed, which uses a standard GPS receiver to determine the lateral shift of a vehicle by comparing a vehicle’s trajectory to a reference road direction without the need of any digital maps with lane-level resolution. This method only needs road-level information from a standard digital mapping database. Furthermore, the system estimates the road curvature and provides advisory speed for a given curve simultaneously. The field test results show that the proposed system can detect a true lane departure with an accuracy of almost 100%. Although no true lane departure was left undetected, occasional false lane departures were detected about 10% of the time when the vehicle did not actually depart its lane. Furthermore, system always issues the curve warning with an advisory speed at a safe distance well ahead of time
Phytochemical and biological evaluation of defatted seeds of Jatropha curcas
In this study, the antimicrobial, antioxidant, phytotoxic and phytochemical properties of defatted seeds of Jatropha curcas were evaluated. A crude methanolic extract of defatted seeds was tested against three fungal strains - Aspergillus niger, Aspergillus flavus and Aspergillus fumigatus - and five bacteria: Escherichia coli and Klebsiella pneumoniae (Gram-negative) and Micrococcus luteus, Bacillus subtilis and Staphylococcus aureus (Gram positive). The methanolic extract was diluted in dimethylsulfoxide to final concentrations of 1, 2, 3, 4 and 5 mg/10 mL. The largest zones of inhibition against K. pneumoniae, M. luteus and B. subtilis were achieved using the concentration of 5 mg/10 mL. The concentration of 1 mg/10 mL was most effective against S. aureus and E. coli. In a 1, 1-diphenyl-2-picrylahydrazyl (DPPH) radical scavenging assay, the 5 mg/10 mL concentration of the Jatropha seed extract showed the strongest activity. Higher concentrations of the Jatropha seed extract (10 mg/50 mL and 5 mg/50 mL) significantly inhibited the germination of radish seeds and had negative effects on radish seedling relative water content, shoot length, root length, seedling fresh weight and seedling dry weight (p<0.05). Phytochemical analyses of the defatted seeds detected alkaloids (7.3%), flavonoids (0.39%) and soluble phenolics (mg gallic acid equivalents/g extract). Based on these results, it was inferred that J. curcas seeds contain active ingredients that are effective against pathogenic microbes and therefore could be used to formulate drugs to treat various diseases
Primary cardiac sarcomas: Risk of brain metastases and management
Primary cardiac neoplasms are very rarely encountered, and the most common type of malignant tumours occurring primarily in the heart are sarcomas. These carry a lethal prognosis on account of their late presentation and aggressive spread. They have a high propensity for cerebral metastases. Such cases are exceptionally uncommon, and till date only a few examples are available. Currently, there is no standard protocol for the management of primary cardiac sarcoma with brain metastase
Linear Active Disturbance Rejection Control for a Laser Powder Bed Fusion Additive Manufacturing Process
Functional metal parts with complicated geometry and internal features for the aerospace and automotive industries can be created using the laser powder bed fusion additive manufacturing (AM) technique. However, the lack of uniform quality of the produced parts in terms of strength limits its enormous potential for general adoption in industries. Most of the defects in selective laser melting (SLM) parts are associated with a nonuniform melt pool size. The melt pool area may fluctuate in spite of constant SLM processing parameters, like laser power, laser speed, hatching distance, and layer thickness. This is due to heat accumulation in the current track from previously scanned tracks in the current layer. The feedback control strategy is a promising tool for maintaining the melt pool dimensions. In this study, a dynamic model of the melt pool cross-sectional area is considered. The model is based on the energy balance of lumped melt pool parameters. Energy coming from previously scanned tracks is considered a source of disturbance for the current melt pool cross-section area in the control algorithm. To track the reference melt pool area and manage the disturbances and uncertainties, a linear active disturbance rejection control (LADRC) strategy is considered. The LADRC control technique is more successful in terms of rapid reference tracking and disturbance rejection when compared to the conventional PID controller. The simulation study shows that an LADRC control strategy presents a 65% faster time response than the PID, a 97% reduction in the steady state error, and a 98% reduction in overshoot. The integral time absolute error (ITAE) performance index shows 95% improvement for reference tracking of the melt pool area in SLM. In terms of reference tracking and robustness, LADRC outperforms the PID controller and ensures that the melt pool size remains constant