| 1. |
-
- 2019
-
Tidskriftsartikel (refereegranskat)
|
|
| 2. |
- Kumar, Atul, et al.
(författare)
-
The structure of Rv3717 reveals a novel amidase from Mycobacterium tuberculosis.
- 2013
-
Ingår i: Acta Crystallographica Section D. - : Wiley-Blackwell. - 0907-4449 .- 1399-0047. ; 69:Pt 12, s. 2543-54
-
Tidskriftsartikel (refereegranskat)abstract
- Bacterial N-acetylmuramoyl-L-alanine amidases are cell-wall hydrolases that hydrolyze the bond between N-acetylmuramic acid and L-alanine in cell-wall glycopeptides. Rv3717 of Mycobacterium tuberculosis has been identified as a unique autolysin that lacks a cell-wall-binding domain (CBD) and its structure has been determined to 1.7 Å resolution by the Pt-SAD phasing method. Rv3717 possesses an α/β-fold and is a zinc-dependent hydrolase. The structure reveals a short flexible hairpin turn that partially occludes the active site and may be involved in autoregulation. This type of autoregulation of activity of PG hydrolases has been observed in Bartonella henselae amidase (AmiB) and may be a general mechanism used by some of the redundant amidases to regulate cell-wall hydrolase activity in bacteria. Rv3717 utilizes its net positive charge for substrate binding and exhibits activity towards a broad spectrum of substrate cell walls. The enzymatic activity of Rv3717 was confirmed by isolation and identification of its enzymatic products by LC/MS. These studies indicate that Rv3717, an N-acetylmuramoyl-L-alanine amidase from M. tuberculosis, represents a new family of lytic amidases that do not have a separate CBD and are regulated conformationally.
|
|
| 3. |
- Karn, Arodh Lal, et al.
(författare)
-
An integrated approach for sustainable development of wastewater treatment and management system using IoT in smart cities
- 2023
-
Ingår i: Soft Computing - A Fusion of Foundations, Methodologies and Applications. - : Springer. - 1432-7643 .- 1433-7479. ; 27, s. 5159-5175
-
Tidskriftsartikel (refereegranskat)abstract
- The present world is intimidated by the problem of water scarcity that is to be addressed immediately. So, it is wise to treat wastewater to meet the massive need for drinking water for the fast-growing population. The magnificent application of Internet of Things (IoT) technology in many smart cities has derived fruitful results. This research study has proposed a real-time system using IoT that regularly monitors specific crucial parameters of a wastewater treatment plant and informs any plant's dysfunction to the operator. Furthermore, the large stream of data sets generated by IoT sensors in real-time can be analyzed and processed by complex event processing (CEP). This study was experimented with Smart Treatment (SMARTreat) architecture and its application in a simple water system of an industrial estate in South India. The proposed architecture showed outstanding results and has received positive comments from the water treatment plant managers.
|
|
| 4. |
- Arroyo-Urena, M. A., et al.
(författare)
-
Flavon signatures at the HL-LHC
- 2023
-
Ingår i: Physical Review D. - : American Physical Society. - 2470-0010 .- 2470-0029. ; 108:9
-
Tidskriftsartikel (refereegranskat)abstract
- The detection of a single Higgs boson at the Large Hadron Collider (LHC) has allowed one to probe some properties of it, including the Yukawa and gauge couplings. However, in order to probe the Higgs potential, one has to rely on new production mechanisms, such as Higgs pair production. In this paper, we show that such a channel is also sensitive to the production and decay of a so-called 'flavon' field (HF), a new scalar state that arises in models that attempt to explain the hierarchy of the Standard Model (SM) fermion masses. Our analysis also focuses on the other decay channels involving the flavon particle, specifically the decay of the flavon to a pair of Z bosons (HF -> ZZ) and the concurrent production of a top quark and charm quark via the 0 -> tc decays (0 = HF; AF), having one or more leptons in the final states. In particular, we show that, with 3000 fb-1 of accumulated data at 14 TeV (the Run 3 stage) of the LHC an heavy flavon HF with mass MHF similar or equal to 2mt can be explored with 3a-5a significance through these channels.
|
|
| 5. |
- Haslett, Sophie, 1988-, et al.
(författare)
-
Nighttime NO emissions strongly suppress chlorine and nitrate radical formation during the winter in Delhi
- 2023
-
Ingår i: Atmospheric Chemistry And Physics. - 1680-7316 .- 1680-7324. ; 23:16, s. 9023-9036
-
Tidskriftsartikel (refereegranskat)abstract
- Atmospheric pollution in urban regions is highly influenced by oxidants due to their important role in the formation of secondary organic aerosol (SOA) and smog. These include the nitrate radical (NO3), which is typically considered a nighttime oxidant, and the chlorine radical (Cl), an extremely potent oxidant that can be released in the morning in chloride-rich environments as a result of nocturnal build-up of nitryl chloride (ClNO2). Chloride makes up a higher percentage of particulate matter in Delhi than has been observed anywhere else in the world, which results in Cl having an unusually strong influence in this city. Here, we present observations and model results revealing that atmospheric chemistry in Delhi exhibits an unusual diel cycle that is controlled by high concentrations of NO during the night. As a result of this, the formation of both NO3 and dinitrogen pentoxide (N2O5), a precursor of ClNO2 and thus Cl, are suppressed at night and increase to unusually high levels during the day. Our results indicate that a substantial reduction in nighttime NO has the potential to increase both nocturnal oxidation via NO(3 )and the production of Cl during the day.
|
|
| 6. |
- Kumar, Varun, et al.
(författare)
-
Highly time-resolved chemical speciation and source apportionment of organic aerosol components in Delhi, India, using extractive electrospray ionization mass spectrometry
- 2022
-
Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 22:11, s. 7739-7761
-
Tidskriftsartikel (refereegranskat)abstract
- In recent years, the Indian capital city of Delhi has been impacted by very high levels of air pollution, especially during winter. Comprehensive knowledge of the composition and sources of the organic aerosol (OA), which constitutes a substantial fraction of total particulate mass (PM) in Delhi, is central to formulating effective public health policies. Previous source apportionment studies in Delhi identified key sources of primary OA (POA) and showed that secondary OA (SOA) played a major role but were unable to resolve specific SOA sources. We address the latter through the first field deployment of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) in Delhi, together with a high-resolution aerosol mass spectrometer (AMS). Measurements were conducted during the winter of 2018/19, and positive matrix factorization (PMF) was used separately on AMS and EESI-TOF datasets to apportion the sources of OA. AMS PMF analysis yielded three primary and two secondary factors which were attributed to hydrocarbon-like OA (HOA), biomass burning OA (BBOA-1 and BBOA-2), more oxidized oxygenated OA (MO-OOA), and less oxidized oxygenated OA (LO-OOA). On average, 40 % of the total OA mass was apportioned to the secondary factors. The SOA contribution to total OA mass varied greatly between the daytime (76.8 %, 10:00–16:00 local time (LT)) and nighttime (31.0 %, 21:00–04:00 LT). The higher chemical resolution of EESI-TOF data allowed identification of individual SOA sources. The EESI-TOF PMF analysis in total yielded six factors, two of which were primary factors (primary biomass burning and cooking-related OA). The remaining four factors were predominantly of secondary origin: aromatic SOA, biogenic SOA, aged biomass burning SOA, and mixed urban SOA. Due to the uncertainties in the EESI-TOF ion sensitivities, mass concentrations of EESI-TOF SOA-dominated factors were related to the total AMS SOA (i.e. MO-OOA + LO-OOA) by multiple linear regression (MLR). Aromatic SOA was the major SOA component during the daytime, with a 55.2 % contribution to total SOA mass (42.4 % contribution to total OA). Its contribution to total SOA, however, decreased to 25.4 % (7.9 % of total OA) during the nighttime. This factor was attributed to the oxidation of light aromatic compounds emitted mostly from traffic. Biogenic SOA accounted for 18.4 % of total SOA mass (14.2 % of total OA) during the daytime and 36.1 % of total SOA mass (11.2 % of total OA) during the nighttime. Aged biomass burning and mixed urban SOA accounted for 15.2 % and 11.0 % of total SOA mass (11.7 % and 8.5 % of total OA mass), respectively, during the daytime and 15.4 % and 22.9 % of total SOA mass (4.8 % and 7.1 % of total OA mass), respectively, during the nighttime. A simple dilution–partitioning model was applied on all EESI-TOF factors to estimate the fraction of observed daytime concentrations resulting from local photochemical production (SOA) or emissions (POA). Aromatic SOA, aged biomass burning, and mixed urban SOA were all found to be dominated by local photochemical production, likely from the oxidation of locally emitted volatile organic compounds (VOCs). In contrast, biogenic SOA was related to the oxidation of diffuse regional emissions of isoprene and monoterpenes. The findings of this study show that in Delhi, the nighttime high concentrations are caused by POA emissions led by traffic and biomass burning and the daytime OA is dominated by SOA, with aromatic SOA accounting for the largest fraction. Because aromatic SOA is possibly more toxic than biogenic SOA and primary OA, its dominance during the daytime suggests an increased OA toxicity and health-related consequences for the general public.
|
|
| 7. |
- Mehbodniya, Abolfazl, et al.
(författare)
-
Fetal health classification from cardiotocographic data using machine learning
- 2021
-
Ingår i: Expert systems (Print). - : John Wiley & Sons. - 0266-4720 .- 1468-0394. ; 39:6
-
Tidskriftsartikel (refereegranskat)abstract
- Health complications during the gestation period have evolved as a global issue. These complications sometimes result in the mortality of the fetus, which is more prevalent in developing and underdeveloped countries. The genesis of machine learning (ML) algorithms in the healthcare domain have brought remarkable progress in disease diagnosis, treatment, and prognosis. This research deploys various ML algorithms to predict fetal health from the cardiotocographic (CTG) data by labelling the health state into normal, needs guarantee, and pathology. This work assesses the influence of various factors measured through CTG to predict the health state of the fetus through algorithms like support vector machine, random forest (RF), multi-layer perceptron, and K-nearest neighbours. In addition to this, the regression analysis and correlation analysis revealed the influence of the attributes on fetal health. The results of the algorithms show that RF performs better than its peers in terms of accuracy, precision, recall, F1-score, and support. This work can further enhance more promising results by performing suitable feature engineering in the CTG data.
|
|
| 8. |
- Mishra, Suneeti, et al.
(författare)
-
Rapid night-time nanoparticle growth in Delhi driven by biomass-burning emissions
- 2023
-
Ingår i: Nature Geoscience. - : Springer Science and Business Media LLC. - 1752-0894 .- 1752-0908. ; 16:3, s. 224-230
-
Tidskriftsartikel (refereegranskat)abstract
- Natural and anthropogenic biomass burning are among the major sources of particulate pollution worldwide that affects air quality, climate and human health. Delhi, one of the world’s most populated cities, experiences severe haze events caused by particulate pollution during winter, but the underlying pathways remain poorly understood. Here we observe intense and frequent nocturnal particle growth events during haze development in Delhi from measurements of aerosols and gases during January–February at the Indian Institute of Technology in Delhi. The particle growth events occur systematically despite the unfavourable condition for new-particle formation, including the lack of photochemical production of low-volatility vapours and considerable loss of vapours under extremely polluted conditions. We estimate that this process is responsible for 70% of the total particle-number concentration during haze. We identify that the condensation of primary organic vapours from biomass burning is the leading cause of the observed growth. The sharp decrease in night-time temperatures and rapid increase in biomass-burning emissions drive these primary organic vapours out of equilibrium, resulting in their condensation and the growth of nanoparticles into sizes relevant for haze formation. This high impact of primary biomass-burning emissions on night-time nanoparticle growth is unique compared with most urban locations globally, where low-volatility vapours formed through oxidation during the day drive particle growth and haze formation. As uncontrolled biomass burning for residential heating and cooking is rife in the Indo–Gangetic plain, we expect this growth mechanism to be a source of ultrafine particles, affecting the health of 5% of the world’s population and impacting the regional climate. Our work implies that regulating uncontrolled biomass-combustion emissions may help inhibit nocturnal haze formation and improve human health in India.
|
|
| 9. |
- Orellana, Pilar, et al.
(författare)
-
Relationship between acute pyelonephritis, renal scarring, and vesicoureteral reflux. Results of a coordinated research project.
- 2004
-
Ingår i: Pediatric nephrology (Berlin, Germany). - : Springer Science and Business Media LLC. - 0931-041X .- 1432-198X. ; 19:10, s. 1122-6
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Acute pyelonephritis (APN) may produce permanent renal damage (PRD), which can subsequently lead to diverse complications. We prospectively evaluated 147 females and 122 males (mean age 3.5 years) with APN in order to analyze the relationship between the presence of PRD, at the time of cortical renal scintigraphy, and age, gender, episodes of urinary tract infection (UTI), and presence of vesicoureteral reflux (VUR). There were 152 children studied after the first proven UTI. VUR was present in 150 children. PRD was observed in 170 children. There were no significant differences between boys and girls. PRD was found in 36.4% of children younger than 1 year and in 70.1% of those older than 1 year ( P<0.0001). Of children with VUR, 72% had PRD compared with 52% of children without VUR ( P<0.0001). Of children with a first episode of UTI, 55.9% developed PRD as did 72.6% of those with recurrent UTI ( P=0.004). Our results showed that PRD in children with APN is important, especially in the presence of VUR, recurrent UTI, and older age.
|
|
| 10. |
- Roy, Dilip Kumar, et al.
(författare)
-
Improving Forecasting Accuracy of Multi-Scale Groundwater Level Fluctuations Using a Heterogeneous Ensemble of Machine Learning Algorithms
- 2023
-
Ingår i: Water. - : MDPI. - 2073-4441. ; 15:20
-
Tidskriftsartikel (refereegranskat)abstract
- Accurate groundwater level (GWL) forecasts are crucial for the efficient utilization, strategic long-term planning, and sustainable management of finite groundwater resources. These resources have a substantial impact on decisions related to irrigation planning, crop selection, and water supply. This study evaluates data-driven models using different machine learning algorithms to forecast GWL fluctuations for one, two, and three weeks ahead in Bangladesh’s Godagari upazila. To address the accuracy limitations inherent in individual forecasting models, a Bayesian model averaging (BMA)-based heterogeneous ensemble of forecasting models was proposed. The dataset encompasses 1807 weekly GWL readings (February 1984 to September 2018) from four wells, divided into training (70%), validation (15%), and testing (15%) subsets. Both standalone models and ensembles employed a Minimum Redundancy Maximum Relevance (MRMR) algorithm to select the most influential lag times among candidate GWL lags up to 15 weeks. Statistical metrics and visual aids were used to evaluate the standalone and ensemble GWL forecasts. The results consistently favor the heterogeneous BMA ensemble, excelling over standalone models for multi-step ahead forecasts across time horizons. For instance, at GT8134017, the BMA approach yielded values like R (0.93), NRMSE (0.09), MAE (0.50 m), IOA (0.96), NS (0.87), and a-20 index (0.94) for one-week-ahead forecasts. Despite a slight decline in performance with an increasing forecast horizon, evaluation indices confirmed the superior BMA ensemble performance. This ensemble also outperformed standalone models for other observation wells. Thus, the BMA-based heterogeneous ensemble emerges as a promising strategy to bolster multi-step ahead GWL forecasts within this area and beyond.
|
|
