Search

Background: The purpose of this study was to investigate the prevalence and distribution of different HCV genotypes, as well as to evaluate clinical and laboratory parameters in HCV-infected patients before and after DAA treatment. Material and Methods: An open-label prospective study was conducted on 50 HCV-infected individuals. The HCV-infected patients underwent a baseline evaluation with complete history, examination, and other clinical investigations. These patients received the appropriate DAA according to the genotype for 3 months. At the end of 3 months, these patients were again evaluated clinically. Results: The majority of instances were among younger age groups. Genotype 3 (66%) was the most common. There was a statistically significant difference found in clinical parameters regarding total bilirubin (p=0.008), SGOT (p=0.001), SGPT (p=0.035), ALP (p=

Electric vehicles (EVs) are propelled by electric traction drive systems (ETDSs), which consist of various components including an electric motor, power electronic converter, and gear box. During manufacturing, end-of-line testing is the ultimate step for ensuring the quality and performance of electric motors in electric vehicle (EV) traction drive systems (ETDSs). The outcome of end-of-line testing of electric motors is significantly influenced by the tolerances of their structural parameters, such as stator inner and outer diameters, magnet dimensions, air gaps, and other geometric parameters. The existing literature provides insights into parametric sensitivity, offering guidance for enhancing the reliability of end-of-line testing. In this manuscript, the importance of end-of-line testing and the role of manufacturing tolerances of e-motor structural parameters in the manufacturing process of ETDSs are discussed. The impact of tolerances of e-motor structural parameters on the test results, such as torque, efficiency, back EMF, and e-NV (noise and vibration), is investigated. Finally, key challenges and research gaps in this area are identified, and recommendations for future research to mitigate the drawbacks of end-of-line testing are provided.

Peak overlap hampers quantification in one-dimensional (1D) 1H NMR. 2D 1H -13C HSQC spectrum provides resolution superior to 1D 1H NMR. However, quantifying the components in a complex mixture with HSQC is not straightforward as in 1D 1H NMR. Quantification using HSQC could open up new avenues for studying metabolism. The variations in 1H–13C scalar couplings, T1, T2, and pulse imperfections contribute to this problem. Although T1 and T2 can be suitably chosen to minimize their deleterious effects, the differential polarization transfer for different resonances owing to large variations in 1H -13C couplings does not allow the cross-peak intensities to be directly correlated to the quantity of metabolites. Existing approaches are time-consuming. We show that spatial encoding of the polarization transfer delays in HSQC using sweep frequency pulses in the presence of a magnetic field gradient allows one to have a transfer of polarization from 1H to 13C insensitive to variations in 1H -13C couplings improving the quantitative aspect of HSQC. Comparisons to other QHSQC and perfected HSQC variants are also provided.

The creation of superhydrophobic surfaces (SHS) has received exceptional thought from the entire research community due to its notable application in varied fields such as anti-icing, self-cleaning, drag reduction, anti-bacterial, and oil-water separation. The super­hy­drophobic (SH) conditions for a surface can be attained through the consolidation of a low surface energy surface with appropriate micro/nano-surface roughness through texturing. Motivated by the SH nature of lotus leaf and petal effect, microstructures have been prepared in this work on a metal surface by a fiber laser marking machine at 35 W. The textured surfaces with a different pitch to diameter (p/d) ratio (2.0-0.70) have been turned into hydrophobic and finally SH, after storing in an ambient environment for a few days due to oxide layer deposition on the textured surface. In this study, the maximum contact angle achieved by textured geometry after 30 days of auto-oxidation was 158.6 o. Further, test results showed that the fabricated surfaces have a high potential to maintain their SH nature even after the harsh condition of applications.

Introduction: Newer coexisting conditions should be identified in order to modify newer risk factors. Aim was to identify patients with non-classical or less common coexisting conditions in patients infected of COVID 19. Method: Single centred study from June 2020 to May 2021 at a tertiary centre in North India. A preformed questionnaire was used to record clinical and laboratory parameters and to identify cases which are in addition to CDC list and Indian data. Results: 0.67% (46) cases out of 6832 patients were identified to have non-classical coexisting illness. It was divided into 2 groups-infections A (60.1%) and non-infections B (39.9%). Group A included-tuberculosis- pulmonary (14.3%) & extra pulmonary (32.9%), bacterial (25.0%) viral infections [dengue, hepatitis B & C] (14.3%), HIV disease (10.7%) and malaria (3.6%). Group B included- organ transplant (27.8%), autoimmune [myasthenia gravis, polymyositis, psoriasis] (22.6%), haematologic [Haemophilia, ITP, Aplastic anaemia, APML, CML] (27.8%), uncommon malignancies [disseminated sacral chordoma and GTN] (11.1%) and snakebite (11.1%). Serum Procalcitonin was not helpful for diagnosis of bacterial infection in COVID-19 disease. Group A had significantly longer duration of illness, hepatitis and elevated CRP. The mortality in group A & B were 32.1% and 43.8% respectively. Death in non-severe COVID cases was in tetanus and snakebite. 30.7% death among tuberculosis patients. More than 70% of deaths were attributable to COVID 19 in both the groups. Conclusion: In Indian settings, comorbidities like tuberculosis and bacterial infections can precipitate severe COVID 19 unlike other parts of the world where tuberculosis is relatively uncommon.

Abstract Segmentation of white matter lesions and deep grey matter structures is an important task in the quantification of magnetic resonance imaging in multiple sclerosis. In this paper we explore segmentation solutions based on convolutional neural networks (CNNs) for providing fast, reliable segmentations of lesions and grey-matter structures in multi-modal MR imaging, and the performance of these methods when applied to out-of-centre data. We trained two state-of-the-art fully convolutional CNN architectures on the 2016 MSSEG training dataset, which was annotated by seven independent human raters: a reference implementation of a 3D Unet, and a more recently proposed 3D-to-2D architecture (DeepSCAN). We then retrained those methods on a larger dataset from a single centre, with and without labels for other brain structures. We quantified changes in performance owing to dataset shift, and changes in performance by adding the additional brain-structure labels. We also compared performance with freely available reference methods. Both fully-convolutional CNN methods substantially outperform other approaches in the literature when trained and evaluated in cross-validation on the MSSEG dataset, showing agreement with human raters in the range of human inter-rater variability. Both architectures showed drops in performance when trained on single-centre data and tested on the MSSEG dataset. When trained with the addition of weak anatomical labels derived from Freesurfer, the performance of the 3D Unet degraded, while the performance of the DeepSCAN net improved. Overall, the DeepSCAN network predicting both lesion and anatomical labels was the best-performing network examined.

Background: Homocysteine (HCY) interferes with collagen cross-linking in bones and stimulates osteoclast activity. The activated osteoclasts secrete cathepsin K (CathK), a cysteine protease, in eminent quantity during bone resorption. Hyperhomocysteinemia may effect bone mineral density (BMD) through CathK. We, therefore, examined the relation between HCY and BMD along with CathK, 25-hydroxyvit-D (25[OH]D), intact parathyroid hormone (iPTH), and Vitamin B12. Materials and Methods: We recruited a total of 93 postmenopausal women between the age group of 45–60 years, attending the Endocrinology outpatient department at King George's Medical University, Lucknow. BMD was done by DXA scan using Hologic QDR1000 system. Based on the WHO criteria, patients were segregated into three groups as follows; normal bone mass, osteopenia, and osteoporosis. All women underwent routine biochemical laboratory parameters, HCY, Vitamin B12, and CathK levels. Results: Among 93 postmenopausal women, 56% (52) had osteoporosis. Nineteen percent (18) had normal BMD (mean age, 53.22 ± 8.5 years) and 23 (25%) had osteopenia (mean age 52.86 ± 6.67 years). The mean age in the osteoporetic group was 56.2 ± 6.9 years. The median (interquartile range) levels of HCY in the three groups were 14.5 μmol/L (12.2–24.7), 15.05 μmol/L (12.1–19.9) and 13.2 μmol/L (10.3–17.0), respectively. CathK levels were similar in three groups 7.6 ng/ml (7.0–80.5), 8.3 ng/ml (7.3–8.5), and 8.6 ng/ml (7.2–8.9). Both HCY and CathK were found positively associated with serum phosphorus (r = 0.584, P < 2.01 and r = 0.249, P < 0.05, respectively). Levels of HCY positively correlate with PTH (r = 0.303, P < 0.01) and inversely with Vitamin B12 (r = −0.248, P < 0.05). No significant association was seen between CathK level and 25(OH) D, iPTH, serum calcium. Conclusion: Low bone mass by DXA is a significant problem in postmenopausal females. HCY and CathK do not reliably correlate with bone loss in postmenopausal women although phosphorus metabolism may play a role.

The detection of new or enlarged white-matter lesions is a vital task in the monitoring of patients undergoing disease-modifying treatment for multiple sclerosis. However, the definition of ‘new or enlarged’ is not fixed, and it is known that lesion-counting is highly subjective, with high degree of inter- and intra-rater variability. Automated methods for lesion quantification, if accurate enough, hold the potential to make the detection of new and enlarged lesions consistent and repeatable. However, the majority of lesion segmentation algorithms are not evaluated for their ability to separate radiologically progressive from radiologically stable patients, despite this being a pressing clinical use-case. In this paper, we explore the ability of a deep learning segmentation classifier to separate stable from progressive patients by lesion volume and lesion count, and find that neither measure provides a good separation. Instead, we propose a method for identifying lesion changes of high certainty, and establish on an internal dataset of longitudinal multiple sclerosis cases that this method is able to separate progressive from stable time-points with a very high level of discrimination (AUC = 0.999), while changes in lesion volume are much less able to perform this separation (AUC = 0.71). Validation of the method on two external datasets confirms that the method is able to generalize beyond the setting in which it was trained, achieving an accuracies of 75 % and 85 % in separating stable and progressive time-points. Keywords: Deep Learning, Multiple Sclerosis, MRI, Longitudinal Imaging

The research examines service delivery innovation architecture and its role in achieving sustainable competitive advantage of firms. The study develops and empirically examines an antecedent based model of service delivery innovation. We collected data from 203 service sector professionals working in Mexican financial and information technology firms, and tested the proposed relationship. Further, the study investigates the moderating role of customer orientation on innovation driven performance outcomes. Results show that customer orientation strengthens the service delivery–performance relationship. This paper aims to contribute to the strategic planning of service firms by guiding their resource allocation to ensure sustainable growth.

Comparison of a fully-automated segmentation method that uses compartmental volume information to a semi-automatic user-guided and FDA-approved segmentation technique.Nineteen patients with a recently diagnosed and histologically confirmed glioblastoma (GBM) were included and MR images were acquired with a 1.5 T MR scanner. Manual segmentation for volumetric analyses was performed using the open source software 3D Slicer version 4.2.2.3 (www.slicer.org). Semi-automatic segmentation was done by four independent neurosurgeons and neuroradiologists using the computer-assisted segmentation tool SmartBrush® (referred to as SB), a semi-automatic user-guided and FDA-approved tumor-outlining program that uses contour expansion. Fully automatic segmentations were performed with the Brain Tumor Image Analysis (BraTumIA, referred to as BT) software. We compared manual (ground truth, referred to as GT), computer-assisted (SB) and fully-automated (BT) segmentations with regard to: (1) products of two maximum diameters for 2D measurements, (2) the Dice coefficient, (3) the positive predictive value, (4) the sensitivity and (5) the volume error.Segmentations by the four expert raters resulted in a mean Dice coefficient between 0.72 and 0.77 using SB. BT achieved a mean Dice coefficient of 0.68. Significant differences were found for intermodal (BT vs. SB) and for intramodal (four SB expert raters) performances. The BT and SB segmentations of the contrast-enhancing volumes achieved a high correlation with the GT. Pearson correlation was 0.8 for BT; however, there were a few discrepancies between raters (BT and SB 1 only). Additional non-enhancing tumor tissue extending the SB volumes was found with BT in 16/19 cases. The clinically motivated sum of products of diameters measure (SPD) revealed neither significant intermodal nor intramodal variations. The analysis time for the four expert raters was faster (1 minute and 47 seconds to 3 minutes and 39 seconds) than with BT (5 minutes).BT and SB provide comparable segmentation results in a clinical setting. SB provided similar SPD measures to BT and GT, but differed in the volume analysis in one of the four clinical raters. A major strength of BT may its independence from human interactions, it can thus be employed to handle large datasets and to associate tumor volumes with clinical and/or molecular datasets ("-omics") as well as for clinical analyses of brain tumor compartment volumes as baseline outcome parameters. Due to its multi-compartment segmentation it may provide information about GBM subcompartment compositions that may be subjected to clinical studies to investigate the delineation of the target volumes for adjuvant therapies in the future.

The debate on the relative benefits of conventional and organic farming systems has in recent time gained significant interest. So far, global agricultural development has focused on increased productivity rather than on a holistic natural resource management for food security. Thus, developing more sustainable farming practices on a large scale is of utmost importance. However, information concerning the performance of farming systems under organic and conventional management in tropical and subtropical regions is scarce. This study presents agronomic and economic data from the conversion phase (2007-2010) of a farming systems comparison trial on a Vertisol soil in Madhya Pradesh, central India. A cotton-soybean-wheat crop rotation under biodynamic, organic and conventional (with and without Bt cotton) management was investigated. We observed a significant yield gap between organic and conventional farming systems in the 1(st) crop cycle (cycle 1: 2007-2008) for cotton (-29%) and wheat (-27%), whereas in the 2(nd) crop cycle (cycle 2: 2009-2010) cotton and wheat yields were similar in all farming systems due to lower yields in the conventional systems. In contrast, organic soybean (a nitrogen fixing leguminous plant) yields were marginally lower than conventional yields (-1% in cycle 1, -11% in cycle 2). Averaged across all crops, conventional farming systems achieved significantly higher gross margins in cycle 1 (+29%), whereas in cycle 2 gross margins in organic farming systems were significantly higher (+25%) due to lower variable production costs but similar yields. Soybean gross margin was significantly higher in the organic system (+11%) across the four harvest years compared to the conventional systems. Our results suggest that organic soybean production is a viable option for smallholder farmers under the prevailing semi-arid conditions in India. Future research needs to elucidate the long-term productivity and profitability, particularly of cotton and wheat, and the ecological impact of the different farming systems.

Purpose. To assess results of closed reduction and external fixation for displaced proximal humeral fractures. Methods. 18 men and 2 women aged 18 to 60 (mean, 38) years underwent closed reduction and external fixation using a standard AO fixator for displaced fractures of the proximal humerus. Injury mechanisms were road traffic accident (n=15) and fall from a height (n=5). 15 were 2-part fractures of the surgical neck, 4 were 3-part fractures of the greater tuberosity and surgical neck, and one was a 4-part fracture. One patient also had a grade-1 open fracture. The quality of reduction and shoulder function were assessed. Results. The mean duration of external fixation was 38 (range, 29–46) days. The mean time to radiological union was 11 (range, 9–13) weeks. The mean follow-up period was 11 (range, 6–18) months. Reduction was good (position equivalent to minimal displacement) in 12 patients and fair (good bony contact between the fragments) in 8 patients. Seven patients had pin site infection; all responded to local dressings and oral antibiotics. No patient had avascular necrosis of the humeral head. The mean Neer score was 85 (range, 42–98) out of 100. Shoulder function was excellent in 10 patients, satisfactory in 6, unsatisfactory in 2, and a failure in 2. Conclusion. External fixation preserves the vascularity of the fracture fragments, enables early mobilisation, and achieves safe healing and good function. It is effective for management of displaced proximal humeral fractures.