3-Chloro-4-methyl­quinolin-2(1H)-one

The title compound, C10H8ClNO, is almost planar (r.m.s. deviation for the 13 non-H atoms = 0.023 Å). In the crystal, inversion dimers linked by pairs of N—H⋯O hydrogen bonds generate R 2 2(8) rings. Weak aromatic π–π stacking inter­actions [centroid–centroid distance = 3.7622 (12) Å] also occur

A validated stability-indicating HPLC method for determination of varenicline in its bulk and tablets

A simple, sensitive and accurate stability-indicating HPLC method has been developed and validated for determination of varenicline (VRC) in its bulk form and pharmaceutical tablets. Chromatographic separation was achieved on a Zorbax Eclipse XDB-C8 column (150 mm × 4.6 mm i.d., particle size 5 μm, maintained at ambient temperature) by a mobile phase consisted of acetonitrile and 50 mM potassium dihydrogen phosphate buffer (10:90, v/v) with apparent pH of 3.5 ± 0.1 and a flow rate of 1.0 ml/min. The detection wavelength was set at 235 nm. VRC was subjected to different accelerated stress conditions. The degradation products, when any, were well resolved from the pure drug with significantly different retention time values. The method was linear (r = 0.9998) at a concentration range of 2 - 14 μg/ml. The limit of detection and limit of quantitation were 0.38 and 1.11 μg/ml, respectively. The intra- and inter-assay precisions were satisfactory; the relative standard deviations did not exceed 2%. The accuracy of the method was proved; the mean recovery of VRC was 100.10 ± 1.08%. The proposed method has high throughput as the analysis involved short run-time (~ 6 min). The method met the ICH/FDA regulatory requirements. The proposed method was successfully applied for the determination of VRC in bulk and tablets with acceptable accuracy and precisions; the label claim percentages were 99.65 ± 0.32%. The results demonstrated that the method would have a great value when applied in quality control and stability studies for VRC

Određivanje donepezil hidroklorida u humanoj plazmi i ljekovitim oblicima pomoću HPLC s detekcijom fluorescencije

A sensitive, isocratic reversed-phase high performance liquid chromatographic method involving fluorescence detection was developed for the determination of donepezil hydrochloride in tablets and in human plasma. Pindolol was successfully used as an internal standard. Good chromatographic separation was achieved by using analytical column C18. The system operated at room temperature using a mobile phase consisting of methanol, phosphate buffer (0.02 mol L1) and triethyl amine (pH 3.5) (55: 45: 0.5 V/V/V) at a flow rate 0.9 mL min1. The analyte and internal standard were extracted from human plasma via liquid-liquid extraction. The proposed method was validated for selectivity, linearity, accuracy and precision. The calibration curve was linear over the range of 5-2000 ng mL1 of donepezil with detection limit of 1.5 ng mL1. Intra- and inter-day relative standard deviations were less than 2.5 %. The method was found to be suitable for the quality control of donepezil hydrochloride in bulk drug as well as in human plasma.Ovaj rad opisuje HPLC metodu određivanja donepezil hidroklorida (DP) u tabletama i u ljudskoj plazmi u nano području. Postavljena je osjetljiva metoda izokratične HPLC s fluorescencijskom detekcijom. Kao unutarnji standard upotrebljen je pindolol. Dobro kromatografsko odjeljivanje postignuto je primjenom analitičke kolone C18. Radna temperatura bila je sobna, a kao mobilna faza upotrebljena je smjesa metanola, fosfatnog pufera (0,02 mol L1) i trietilamina (pH 3,5) (55:45:0.5 V/V/V). Analit i unutarnji standard su ekstrahirani iz ljudske plazme ekstrakcijom tekuće-tekuće. Predložena metoda je validirana s obzirom na selektivnost, područje linearnosti, ispravnost i preciznost. Kalibracijska funkcija bila je linearna u području od 5-2000 ng mL1 donepezila, a granica detekcije iznosila je 2 ng mL1. Relativna standardna devijacija za repetabilnost i intermedijarnu preciznost bila je manja od 2,5 %. Metoda je primjenljliva u kontroli kvalitete ljekovitih formulacija s DP-om i u praćenju DP-a u ljudskoj plazmi

UR-CarA-Net: A Cascaded Framework with Uncertainty Regularization for Automated Segmentation of Carotid Arteries on Black Blood MR Images

We present a fully automated method for carotid artery (CA) outer wall segmentation in black blood MRI using partially annotated data and compare it to the state-of-the-art reference model. Our model was trained and tested on multicentric data of patients (106 and 23 patients, respectively) with a carotid plaque and was validated on different MR sequences (24 patients) as well as data that were acquired with MRI systems of a different vendor (34 patients). A 3D nnU-Net was trained on pre-contrast T1w turbo spin echo (TSE) MR images. A CA centerline sliding window approach was chosen to refine the nnU-Net segmentation using an additionally trained 2D U-Net to increase agreement with manual annotations. To improve segmentation performance in areas with semantically and visually challenging voxels, Monte-Carlo dropout was used. To increase generalizability, data were augmented with intensity transformations. Our method achieves state-of-the-art results yielding a Dice similarity coefficient (DSC) of 91.7% (interquartile range (IQR) 3.3%) and volumetric intraclass correlation (ICC) with ground truth of 0.90 on the development domain data and a DSC of 91.1% (IQR 7.2%) and volumetric ICC with ground truth of 0.83 on the external domain data outperforming top-ranked methods for open-source CA segmentation. The uncertainty-based approach increases the interpretability of the proposed method by providing an uncertainty map together with the segmentation

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

Enhancing field service operations via fuzzy automation of tactical supply plan

Tactical supply planning (TSP) is an integral part of the end-to-end field resource planning process. It takes as input, constrained demand from the strategic plan at monthly (or quarterly) level, decomposes it to daily or weekly level and plans the capacity accordingly to meet the expected demand. The plan is then executed and sent to a work allocation system for on-the-day scheduling of individuals tasks to resources. A tactical supply plan ensures that there are enough resources available in the field on any given day. It highlights underutilised resources and offers recommendations on how best to deploy surplus resources. As such, TSP focuses on improving customer satisfaction by minimising operational cost and maximising right-first-time (RFT) objectives. In this chapter, we describe opportunities and challenges in automating tactical supply planning and present a fuzzy approach to address the challenges. The motivation is to minimise the effort required for producing a resource plan. More importantly, our objective is to leverage computation intelligence to produce optimised supply plan in order to increase RFT and the customer satisfaction

Solving stochastic optimal reactive power dispatch using an Adaptive Beluga Whale optimization considering uncertainties of renewable energy resources and the load growth

The electrical system performance can be improved considerably by controlling the reactive power flow in the system. The reactive power control can be achieved by optimal reactive power dispatch (ORPD) problem solution and optimal integration of the FACTS devices. With high penetration of renewable energy sources (RESs) and the load growth, the ORPD solution became a challenging and a complex task due to the stochastic nature of the RERs and the load growth. In this regard, the aim of this paper is to solve the stochastic optimal reactive power dispatch (SORPD) with optimal inclusion of PV units, wind turbines and the unified power flow controller (UPFC) under uncertainties of the load growth and the generated powers. An Adaptive Beluga Whale Optimization (ABWO) is proposed for solving the SORPD which is based on the Fitness-Distance Balance Selection (FDBS) strategy and the territorial solitary males’ strategy of the Mountain Gazelle Optimizer. The proposed ABWO is tested on IEEE 30-bus system and a comparison with other optimization techniques for solving the ordinary ORPD is presented for validating the proposed ABWO. The obtained results reveal that the TEPL is reduced from 5.3168 MW to 3.97985 MW with optimal integration of the RERs and UPFC. Likewise, the TEVD is reduced from 0.1794p.u. to 0.10689p.u. and the TVSI is decreased from 0.1289p.u. to 0.0476p.u

Comparative Study of Larvicidal Activity of Spinel Co3O4 Nanorods and Entomopathogenic Metarhizium brunneum Conidia against Culex pipiens

Herein, we report the synthesis of spinel cobalt oxide nanorods (Co3O4 NRs) by a modified co-precipitation approach and examine their larvicidal activity against Culex pipiens. The structure and morphology of the as-prepared Co3O4 NRs were emphasized using X-ray diffraction (XRD), Raman spectroscopy, energy dispersive X-ray spectroscopy (EDAX), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). It was found that Co3O4 nanostructures have a face-centered spinel cubic crystal structure with a mean crystallite size of 38 nm. These nanostructures have a rod like shape with a mean diameter of 30 nm and an average length of 60 nm. The TGA measurements revealed the high stability of the formed spinel cubic structure at 400 °C. The optical behavior indicates the direct transition of electrons through an optical band gap in the range of 2.92–3.08 eV. These unique chemical and physical properties of Co3O4 NRs enabled them to be employed as a strong agent for killing the C. pipiens. A comparison study was employed between the as-prepared Co3O4 and the entomopathogenic fungus Metarhizium brunneum as a control agent of C. pipiens larvae. The results revealed that the as-prepared nanorods have higher mortality against C. pipiens larvae compared with the well-known M. brunneum

UR-CarA-Net: A Cascaded Framework with Uncertainty Regularization for Automated Segmentation of Carotid Arteries on Black Blood MR Images

We present a fully automated method for carotid artery (CA) outer wall segmentation in black blood MRI using partially annotated data and compare it to the state-of-the-art reference model. Our model was trained and tested on multicentric data of patients (106 and 23 patients, respectively) with a carotid plaque and was validated on different MR sequences (24 patients) as well as data that were acquired with MRI systems of a different vendor (34 patients). A 3D nnU-Net was trained on pre-contrast T1w turbo spin echo (TSE) MR images. A CA centerline sliding window approach was chosen to refine the nnU-Net segmentation using an additionally trained 2D U-Net to increase agreement with manual annotations. To improve segmentation performance in areas with semantically and visually challenging voxels, Monte-Carlo dropout was used. To increase generalizability, data were augmented with intensity transformations. Our method achieves state-of-the-art results yielding a Dice similarity coefficient (DSC) of 91.7% (interquartile range (IQR) 3.3%) and volumetric intraclass correlation (ICC) with ground truth of 0.90 on the development domain data and a DSC of 91.1% (IQR 7.2%) and volumetric ICC with ground truth of 0.83 on the external domain data outperforming top-ranked methods for open-source CA segmentation. The uncertainty-based approach increases the interpretability of the proposed method by providing an uncertainty map together with the segmentation