Electronically Tunable Sinusoidal Oscillator Circuit

This paper presents a novel electronically tunable third-order sinusoidal oscillator synthesized from a simple topology, employing current-mode blocks. The circuit is realized using the active element: Current Controlled Conveyors (CCCIIs) and grounded passive components. The new circuit enjoys the advantages of noninteractive electronically tunable frequency of oscillation, use of grounded passive components, and the simultaneous availability of three sinusoidal voltage outputs. Bias current generation scheme is given for the active elements used. The circuit exhibits good high frequency performance. Nonideal and parasitic study has also been carried out. Wide range frequency tuning is shown with the bias current. The proposed theory is verified through extensive PSPICE simulations using 0.25 μm CMOS process parameters

Improving Accuracy and Computational Efficiency of the Load Flow Computation of an Active/Passive Distribution Network

Over the last couple of decades, there has been a growing trend to make a paradigm shift from the passive distribution network to the active distribution network. With the rapid enlargement of network and installation of distributed generation (DG) units into distribution network, new technical challenges have arisen for load flow computation. The available techniques for the active distribution load flow calculation have limited scope of application and, sometimes, suffer from computational complexity. The complexity level of the distribution system power flow calculation is higher because of the issues of phase imbalance and high R/X ratios of feeder lines. The phase-imbalance increases computational complexity, whereas, the high R/X ratio makes time-consuming derivative based solver such as Newton-Raphson inviable for such large system. The motivation behind this work is to propose distinct mathematical approach for accurate modeling of network components, and loads to reduce computational time with improve accuracy. The applicability of an existing technique remains limited either by DG control modes, or by transformer configurations. The objective of this work is basically to develop an active distribution load flow (ADLF) algorithm with the following features. • Improved computational efficiency. • Applicability to any feeder network. • Accurate modeling of loads. • Applicability to different mode of operations of distributed generators (DGs). Typically, distributed generators are power-electronically interfaced sources that can be operated either in the current-balanced or in the voltage-balanced mode. The integration of DGs to the feeder network enables the distribution system to have bidirectional power exchange with the transmission grid. Which, also improve the voltage profile of the distribution network by providing additional sources of reactive power compensation. The contribution of the first work is to carry out the load flow analysis of a distribution network in the case of the dominant presence of induction motor loads. For a given operating condition, the load representation of an induction motor on the distribution network is made by analyzing its exact equivalent circuit. Thus, the induction motor is precisely represented as a voltage and frequency dependent load. The necessity of representing an induction motor by means of its precise load model is verified through a detailed case study. The convergence of the load flow solution with the precise modeling of induction motor loads is ensured by carrying out the load flow analysis over a complex distribution network containing several loops and distributed generations. The specific contribution of the second work is to improve the accuracy of the results obtained from the load flow analysis of a distribution network via forwardbackward sweeps. Specific attention is paid to the two-port modeling of a transformer with precise consideration for the zero sequence components of its port voltages. The zero sequence voltages at transformer ports are often ignored in the conventional load flow analyses. A new two-port network model is derived, which is generalized enough for the accurate representation of a transformer in the cascaded connection. Based upon the novel two-port representation made, a new set of iteration rules is established to carry out the forward-backward sweeps for solving the load flow results. All possible transformer configurations are taken into account. It is shown that the load flow analysis technique proposed is suitable for both active and passive distribution networks. The accuracy analysis of the load flow results is also carried out. For a given load flow result, by assessing the nodal current imbalances are evaluated based upon the admittance matrix representation of the network. Extensive case studies are performed to demonstrate the utility of the proposed load flow analysis technique. The contribution of the third work is to develop a computationally efficient and generalised algorithm for the load flow calculation in an active distribution network. The available techniques for the active distribution load flow calculation have limited scope of application and, sometimes, suffer from computational complexity. The applicability of an existing technique remains limited either by DG control modes or by transformer configurations. In this chapter, the load flow calculation is carried out by using the concept of Gauss-Zbus iterations, wherein the DG buses are modeled via the technique of power/current compensation. The specific distinctness of the proposed Gauss-Zbus formulation lies in overcoming the limitations imposed by DG control modes for the chosen DG bus modeling as well as in having optimized computational performance. The entire load flow calculation is carried out in the symmetrical component domain by decoupling all the sequence networks. Furthermore, a generalised network modeling is carried out to define decoupled and tap-invariant sequence networks along with maintaining the integrity of the zero sequence network under any transformer configurations.The computational efficiency and accuracy of the methodology proposed are verified through extensive case studies. The contribution of the fourth work is to identify and eliminate unnecessary itvii eration loops in the load flow analysis of an active distribution network so as to improve its overall computational efficiency. The number of iteration loops is minimized through the integrated modeling of a distributed generator (DG) and the associated coupling transformer. The DG bus is not preserved in the load flow calculation and the aforementioned DG-transformer assembly is represented in the form of a voltage dependent negative load at the point of connection to the main distribution network. Thus, the iteration stage that is involved in indirectly preserving the DG in the form of a voltage source or negative constant power load can be got rid of. This, in turn, eliminates the need for multiple rounds of forward-backward sweep iterations to determine the bus voltages. The power characteristics of the DG-transformer assembly are thoroughly investigated through a carefully performed case study so as to assess the potential convergence performance of the proposed

Prevalence of depression, anxiety and Quality of life among North Indian Polycystic ovary syndrome Women: Evidence from a prospective observational study

Background: Polycystic ovary syndrome (PCOS) is a common heterogeneous gynaecological endocrine disorder characterized by clinical features including oligo-amenorrhea/ovulatory dysfunction, hyperandrogenism and polycystic ovarian morphology. PCOS increases the risk of depression and anxiety which leads to poor quality of life. Aim of the study were to determine the prevalence of anxiety and depression among women suffering from PCOS and to determine the quality of life (QOL) in PCOS women.Methods: The study was prospective, observational, non-interventional and questionnaire-based. 192 women with PCOS voluntarily helped in filling the questionnaires consisting of questions using PHQ-9 for depression, GAD-7 for anxiety, SF-12 for general health and PCOSQ-50 for disease-specific domains. All data were recorded in pre-designed case record forms and analysis of data was done using different statistical methods.Results: Majority of PCOS women were either overweight or obese. Based on PHQ-9 20% of women was suffering with major depression and based on GAD-7, 25% with major anxiety. It is found that psychosocial and emotional domain and coping domain of PCOSQ-50 is significant in patients with major depression and major anxiety. Significant effects were seen on their general health as per SF-12 domain. Lack of physical exercise was found in 83% of women.Conclusions: PCOS is a complex disease which decreases the overall quality of life. Therefore, treatment of PCOS women should include psychological counselling along-with with medication, especially in obese PCOS women. Women should be educated with the benefits of lifestyle modification in PCOS

The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

Background: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. Methods: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. Results and Conclusion: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at √s = 13 TeV

Abstract The parton-level top quark (t) forward-backward asymmetry and the anomalous chromoelectric (d̂ t) and chromomagnetic (μ̂ t) moments have been measured using LHC pp collisions at a center-of-mass energy of 13 TeV, collected in the CMS detector in a data sample corresponding to an integrated luminosity of 35.9 fb−1. The linearized variable AFB(1) is used to approximate the asymmetry. Candidate t t ¯ events decaying to a muon or electron and jets in final states with low and high Lorentz boosts are selected and reconstructed using a fit of the kinematic distributions of the decay products to those expected for t t ¯ final states. The values found for the parameters are AFB(1)=0.048−0.087+0.095(stat)−0.029+0.020(syst),μ̂t=−0.024−0.009+0.013(stat)−0.011+0.016(syst), and a limit is placed on the magnitude of | d̂ t| < 0.03 at 95% confidence level. [Figure not available: see fulltext.

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe