Miracle-dz/UniFAR-FTUs huggingface dataset:
DC corrective optimal power flow based on generator and branch outages modelled as fictitious nodal injections

This study deals with a new formulation for the direct current corrective optimal power flow. The formulation is based on the outage of generators and/or branches modelled as fictitious injections of active power. By including that fictitious injections in the optimisation problem, the injections are adjusted to the post-contingency state as a consequence of the corrective actions carried out to bring the system back to its normal state. So, when the analysis of contingencies is performed, the classical topological analysis and the subsequent analyses are avoided with this approach. This new formulation uses the sensitivity matrix between branch power flows and powers injected in a power system. An important feature of this matrix is to remain constant during the contingency analysis performed for the generation-load scenario (base case) of each period of time to be analysed. The approach proposed is illustrated in the IEEE-RTS of 24 buses. The results obtained in this distribution network demonstrate that the proposed methodology can assess the impact of contingencies with an acceptable accuracy and a short computation time.
Improving Acetabular Component Positioning in Total Hip Arthroplasty: A Cadaveric Study of an Inertial Navigation Tool and a Novel Registration Method

Background: Incorrect acetabular component positioning in total hip arthroplasty (THA) has been associated with poor outcomes. Computer-assisted hip arthroplasty increases accuracy and consistency of cup positioning compared to conventional methods. Traditional navigation units have been associated with problems such as bulkiness of equipment and reproducibility of anatomical landmarks, particularly in obese patients or the lateral position. Purpose: We sought to evaluate the accuracy of a novel miniature inertial measurement system, the Navbit Sprint navigation device (Navbit, Sydney, Australia), to navigate acetabular component positioning in both the supine and lateral decubitus positions. We also aimed to validate a new method of patient registration that does not require acquisition of anatomical landmarks for navigation. Methods: We performed THA in a cadaveric study in supine and lateral positions using Navbit navigation to record cup position and compared mean scores from 3 Navbit devices for each cup position on post-implantation CT scans. Results: A total of 11 cups (5 supine and 6 lateral) were available for comparison. A difference of 2.34° in the supine direct anterior approach when assessing acetabular version was deemed to be statistically but not clinically significant. There was no statistically significant difference between CT and navigation measurements of cup position in the lateral position. Conclusion: This cadaveric study suggests that a novel inertial-based navigation tool is accurate for cup positioning in THA in the supine and lateral positions. Furthermore, it validates a novel registration method that does not require the identification of anatomical landmarks.
Radiomics-based convolutional neural network for brain tumor segmentation on multiparametric magnetic resonance imaging

Abstract. Accurate segmentation of gliomas on routine magnetic resonance image (MRI) scans plays an important role in disease diagnosis, prognosis, and patient treatment planning. We present a fully automated approach, radiomics-based convolutional neural network (RadCNN), for segmenting both high- and low-grade gliomas using multimodal MRI volumes (T1c, T2w, and FLAIR). RadCNN incorporates radiomic texture features (i.e., Haralick, Gabor, and Laws) within DeepMedic [a deep 3-D convolutional neural network (CNN) segmentation framework that uses image intensities; a top performing method in the BraTS 2016 challenge] to further augment the performance of brain tumor subcompartment segmentation. We first identify textural radiomic representations that best separate the different subcompartments [enhancing tumor (ET), whole tumor (WT), and tumor core (TC)] on the training set, and then feed these representations as inputs to the CNN classifier for prediction of different subcompartments. We hypothesize that textural radiomic representations of lesion subcompartments will enhance the separation of subcompartment boundaries, and hence providing these features as inputs to the deep CNN, over and above raw intensity values alone, will improve the subcompartment segmentation. Using a training set of N = 241 patients, validation set of N = 44, and test set of N = 46 patients, RadCNN method achieved Dice similarity coefficient (DSC) scores of 0.71, 0.89, and 0.73 for ET, WT, and TC, respectively. Compared to the DeepMedic model, RadCNN showed improvement in DSC scores for both ET and WT and demonstrated comparable results in segmenting the TC. Similarly, smaller Hausdorff distance measures were obtained with RadCNN as compared to the DeepMedic model across all the subcompartments. Following the segmentation of the different subcompartments, we extracted a set of subcompartment specific radiomic descriptors that capture lesion disorder and assessed their ability in separating patients into different survival cohorts (short-, mid- and long-term survival) based on their overall survival from the date of baseline diagnosis. Using a multilinear regression approach, we achieved accuracies of 0.57, 0.63, and 0.45 for the training, validation, and test cases, respectively.
A Method for Detecting Noise, Single Pass, Cross Pass and Echo of Mobile Phone

Quality of Experience is referred to as an important index for measuring how well the user's requirements are satisfied, and many methods have been presented to evaluate speech quality. But they cannot identify the kind of disturbances when the quality of speech is not good. This paper aims at proposing a method which can identify the kind of disturbances lowering the Quality of Experience. The approach proposed is based on PESQ and P563 algorithms. It adopted asymmetrical factor of PESQ and cosine distance in frequency domain to compare original signal with degraded signal. And a new time realignment method and temporal masking method were used to improve detection precision in wireless environments. This new algorithm is tested in real world including GSM and UMTS environments. The results indicate that this algorithm is helpful for detecting noise, single pass, cross pass and echoing automatically.
Photovoltaics in India-Thrust on Research and Education

Photovoltaics has registered an impressive growth despite the vicissitudes of the sixty years since the first solar cell was developed at the BELL LABS in 1954. It is a defining moment for the PV Industry today as costs are coming down with economies of scale and the need for clean and green energy is gathering momentum. This paper reviews some of the recent trends in photovoltaic technology, the research initiatives in India and also how the academia in our country is gearing up to meet the objectives enunciated in the Jawaharlal Nehru Solar Mission document in terms of training, curriculum development and research in collaboration with the Industry. The ultimate aim is to ensure energy sufficiency, energy security and reliability.
Dielectric rod antenna based on image NRD guide coupled to rectangular waveguide

A dielectric rod antenna based on an image NRD guide fed by a slot in the broad wall of a rectangular waveguide is proposed. This configuration is developed for the use in the design of an array of this antenna. The antenna characteristics are investigated using the finite difference time domain (FDTD) technique. Measured results at 30 GHz band are presented to validate the numerical analysis.
Strong Seasonal Variations of Seismic Velocity in Eastern Margin of Tibetan Plateau and Sichuan Basin From Ambient Noise Interferometry

Ambient noise interferometry between seismic stations makes it possible to monitor temporal changes of the Earth's media continuously. Here, we examined seasonal changes of Rayleigh‐wave empirical Greens functions at 2–10‐s period from 8 years of continuous data of 200 seismic station pairs in Sichuan, China. We used a wavelet decomposition to extract the seasonal signals. We found that most station pairs show seasonal variations with velocity perturbations of up to 0.8%. The seasonality varies in strength, amplitude, phase, periods, and location, but the phase is remarkably consistent, with the largest changes mostly in summer or winter months. We believe that the cause of the seasonality is likely the elastic loading due to regional precipitation. The effect is greater in the tectonically active Tibetan Plateau margin than in the stable Sichuan basin and in the deeper crust than in the uppermost crust. The effect is also strongly influenced by local crustal structure. Our results indicate that studies of tectonic crustal changes need to consider non‐tectonic effects.
Cavity‐perturbation method improvement by a numerical calibration process

The cavity‐perturbation method is a very simple and useful technique to extract dielectric properties of materials at microwave frequencies. However, the classical calibration process drastically limits its range of validity. In this article, we propose a new numerical approach which enables to broaden the validity range of the cavity‐perturbation technique. © 2014 Wiley Periodicals, Inc. Microwave Opt Technol Lett 56:904–906, 2014
Multiple output zero-current switching switched-capacitor bidirectional dc–dc converter

The proposed circuit is a multiple output quasi-resonant (QR) zero-current switching (ZCS) switched-capacitor (SC) converter with a bidirectional power flow control conversion scheme. The principles of the proposed multiple output QR ZCS SC bidirectional dc–dc converter are described using a detailed circuit model for analysis. Simulation and experimental results are carried out to verify the validity and the soft switching performance of the proposed converter. The maximum efficiency achievable is about 94 and 92% for the forward and reverse power flow control schemes, respectively. The output voltage can be regulated by changing the switching frequency for the designed compensated closed-loop controller.
The Effects of Exergames on Muscle Architecture: A systematic review and meta-analysis protocol

Muscle architectural parameters play a crucial role in the rate of force development, strength, and sports performance. On the other hand, deteriorated muscle architectural parameters are associated with injuries, sarcopenia, mortality, falls, and fragility. With the development of technology, exergames have emerged as a complementary tool for physical therapy programs. The PRISMA 2020 statement was followed during the systematic review and meta-analysis. CENTRAL, CINAHL, PROQUEST, PubMed, and OpenGrey databases were searched last time on 22 September 2021. In total, five controlled trials were included in the systematic review. Twelve weeks of virtual dance exercise (Dance Central game for Xbox 360®) showed a medium effect on the improvement of hamstrings (g = 0.55, 95% CI (−0.03, 1.14), I2 = 0%) and the quadriceps femoris muscle cross-sectional area (g = 0.58, 95% CI (0.1, 1.00), I2 = 0%) in community-dwelling older women. Additionally, a four-week virtual balance-training program (the ProKin System) led to significant increments in the cross-sectional areas of individual paraspinal muscles (14.55–46.81%). However, previously investigated exergame programs did not show any medium or large effects on the architectural parameters of the medial gastrocnemius muscle in community-dwelling older women. Distinct exergame programs can be used as a complementary therapy for different prevention and rehabilitation programs.
Py-GC-MS Study on Catalytic Pyrolysis of Biocrude Obtained via HTL of Fruit Pomace

Herein, we proposed new two-stage processing of blackcurrant pomace toward a value-added, hydrocarbon-rich biocrude fraction. The approach consisted of thermochemical liquefaction of a wet-type organic matter into liquid biocrude followed by its upgrade by thermal and catalytic pyrolysis. Particularly, we put effort into investigating the effect of selected catalysts (ZSM-5 and HY zeolite) on the composition of the volatiles released during the pyrolysis of the biocrude. The latter was obtained through liquefaction of the raw material in the binary solvent system of water and isopropanol. The biocrude yield accounted for ca. 45 wt. % of the initial dry biomass. It was a complex mixture of various component groups with an abundant share of oxygenates, especially carboxylic acids and esters. Thereafter, the biocrude was subjected to a pyrolysis study performed by means of the microscale coupled pyrolysis-gas chromatography-mass spectrometry technique (Py-GC-MS). The dominant components identified in the catalytic pyrolytic volatiles were unsaturated hydrocarbons (both cyclic and aliphatic ones) and, to a lesser extent, oxygen and nitrogen compounds. The addition of the ZSM-5 and HY zeolite allowed us to attain the relative total share of hydrocarbons in the volatile fraction equal to 66% and 73%, respectively (in relation to identified compounds). Thus, catalytic pyrolysis over zeolites seems to be particularly prospective due to the promotion of the deoxygenation reactions, which manifested in the noticeable decrease in the share of oxygen compounds in the evolved volatiles. The developed innovative two-stage processing of blackcurrant pomaces allows for obtaining value-added products that could serve as chemicals, biocomponents, and self-contained biofuels as well as bioplastic precursors. The presented contribution brings some new insights into the field of valorization of residuals generated by the food industry sector.
Comparison of SARS-CoV-2 Receptors Expression in Primary Endothelial Cells and Retinoic Acid-Differentiated Human Neuronal Cells

SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) is primarily responsible for coronavirus disease (COVID-19) and it is characterized by respiratory illness with fever and dyspnea. Severe vascular problems and several other manifestations, including neurological ones, have also been frequently reported, particularly in the great majority of “long hauler” patients. SARS-CoV-2 infects and replicates in lung epithelial cells, while dysfunction of endothelial and neuronal brain cells has been observed in the absence of productive infection. It has been shown that the Spike protein can interact with specific cellular receptors, supporting both viral entry and cellular dysfunction. It is thus clear that understanding how and when these receptors are regulated, as well as how much they are expressed would help in unveiling the multifaceted aspects of this disease. Here, we show that SH-SY5Y neuroblastoma cells express three important cellular surface molecules that interact with the Spike protein, namely ACE2, TMPRSS2, and NRP1. Their levels increase when cells are treated with retinoic acid (RA), a commonly used agent known to promote differentiation. This increase matched the higher levels of receptors observed on HUVEC (primary human umbilical vein endothelial cells). We also show by confocal imaging that replication-defective pseudoviruses carrying the SARS-CoV-2 Spike protein can infect differentiated and undifferentiated SH-SY5Y, and HUVEC cells, although with different efficiencies. Neuronal cells and endothelial cells are potential targets for SARS-CoV-2 infection and the interaction of the Spike viral protein with these cells may cause their dysregulation. Characterizing RNA and protein expression tempo, mode, and levels of different SARS-CoV-2 receptors on both cell subpopulations may have clinical relevance for the diagnosis and treatment of COVID-19-infected subjects, including long hauler patients with neurological manifestations.
Weighted Sobolev-Morrey Estimates for Nondivergence Degenerate Operators with Drift on Homogeneous Groups

Let X0,X1,…,Xq(q<N) be real vector fields, which are left invariant on homogeneous group G, provided that X0 is homogeneous of degree two and X1,…,Xq are homogeneous of degree one. We consider the following nondivergence degenerate operator with drift L=∑i,j=1qaij(x)XiXj+a0(x)X0, where the coefficients aij(x), a0(x) belonging to vanishing mean oscillation space are bounded measurable functions. Furthermore, aij(x) satisfies the uniform ellipticity condition on Rq and a0(x)≠0. We obtain the local weighted Sobolev–Morrey estimates by applying the boundedness of commutators and interpolation inequalities on weighted Morrey spaces.
Distributed temperature sensing (DTS) to characterize the performance of producing oil wells

This paper describes how distributed temperature sensing (DTS) based on Raman Scattering is being used as an in-situ logging technique in oil and gas wells. Traditional methods of gathering production data to characterize oil and gas well performance have relied on the introduction of electric logging tools into the well. This can be an expensive process in highly deviated or horizontal wells and usually results in the well being shut-in with the loss or deferment of hydrocarbon production. More recently permanently placed pressure sensors based on CMOS technology have been used, but these systems do not easily deliver distributed measurements and reliability has been found to be poor.
MEMS inertial sensors for load monitoring of wind turbine blades

Structural load monitoring of wind turbines is becoming increasingly important due increasing turbine size and offshore deployment. Rotor blades are key components that can be monitored by continuously measuring their deflection and thereby determining strain and loads on the blades. In this paper, a method is investigated for monitoring blade deformation that utilizes micro-electromechanical systems (MEMS) comprising triaxial accelerometers, magnetometers and gyroscopes. This approach is demonstrated using a cantilever beam instrumented with 5 MEMS and 4 strain gauges. The measured changes in angles obtained from the MEMS are used to determine a deformation surface which is used as an input to a finite element model in order to estimate the strain throughout the beam. The results are then verified by comparison with strain gauge measurements.
Design evaluation of digital consumer products using virtual reality-based functional behaviour simulation

Abstract To realize the virtual design and prototyping of every digital consumer product faithfully, it is important to allow all the people involved in the design process to experience its realistic appearance and functional behaviour. Proposed in this paper is a novel approach to design evaluation of a digital consumer product, which can satisfy such requirements using virtual reality-based functional behaviour simulation. In the approach, a product model, multimedia contents data, a functional behaviour model and a finite state machine are combined to constitute the virtual product model of a product of interest. A state transition methodology is adopted to capture the functional behaviour of the product, which is simulated by the finite state machine in a virtual reality environment. Based on the approach, a product design evaluation system has been developed and applied for the design evaluation of various products. A preliminary user study has been conducted to show the usefulness of the proposed approach by comparing it with other approaches using real products and two-dimensional screen prototypes.
Design and fabrication of a polymer-based micron-scale semispherical vertical interconnecting structure for 3D photonic integrated circuit application

A vertically interconnected structure is a key feature of a photonic integrated circuit application, like an optical printed circuit board. Conventional vertical interconnecting structures have a 45 degree mirror, with or without metal coating to enhance its reflectance. We have designed a curved-shape semi-spherical type vertical interconnecting structure to enhance vertical interconnecting efficiency, and also developed simple fabrication procedure to realize it.
A New Miniaturized Gas Sensor Based on Zener Diode Network Covered by Metal Oxide

The development of “portable, low cost and low consumption” gas microsensors is one of the strong needs for embedded portable devices in many fields such as public domain. In this paper, a new approach is presented on making, on the same chip, a network of head-to-tail facing PN junctions in order to miniaturize the sensor network and considerably reduce the required power for heating each cell independently. This paper is about recognizing a device that integrates both sensing and self-heating. This first study aims to evaluate the possibilities of this type of diode network for use as a gas sensor. The first part concerns the description of the technological process that is based on a doped polysilicon wafer in which a thin layer of metal oxide (a gallium-doped zinc oxide in our case) is deposited by RF sputtering. An electrical model will be proposed to explain the operation and advantage of this approach. We will show the two types of tests that have been carried out (static and dynamic) as well as the first encouraging results of these electrical characterizations under variable atmospheres.
System efficiency of a DC/DC converter‐based wind farm

In this paper, three DC/DC converter topologies are evaluated from an energy efficiency point of view regarding their suitability for the application in a DC wind farm grid. The three investigated topologies are the fullbridge (FB) converter, the single active bridge (SAB) converter and the series parallel resonant (LCC) converter. The energy efficiency of the three converter topologies is evaluated for different control strategies. It is found that the LCC and FB converters have the lowest losses of the three topologies. It is also shown that the wide range of operation creates problems for all three converters. The SAB converter has the largest increase in losses caused by the wide range of operation. The FB converter also has an increase in losses for this variable operating range, whereas the LCC converter has large stresses for the input and output filters. By considering some further factors, such as the contribution to the energy production cost, the design and the control of the converters, the FB converter is found to be a suitable choice for wind farm application. Copyright © 2007 John Wiley & Sons, Ltd.
Coherent array of 900 semiconductor laser amplifiers

The design, fabrication, and testing of a two-dimensional array of 900 laser diode power amplifiers injected by a single semiconductor master oscillator is discussed. This array extends the results of the 200-emitter array reported on last year. The array consists of a stack of ten 100-emitter linear arrays. Nine of the 100-emitter arrays were successfully stacked and injected by a semiconductor master oscillator laser by way of a 1 to 10 semiconductor ridge- waveguide splitter and amplifier array. The tenth 100-emitter array was included in the stack but the fiber optic used to connect it to the 1 to 10 splitter broke before final strain-relief was added. The 900 amplifiers produced approximately 36 W of coherent power in the near field. Poor fill optics allowed only 15.6 W to be delivered to the far field of which 5.5 W were phase aligned into a narrow beam in one axis and into 5 major spots in the other axis. Improved optics and higher power emitters are the next steps in moving this array architecture to high power and brightness.