Miracle-dz/UniFAR-FTUs huggingface dataset:
Power System Equivalent Inertia Estimation Method Using System Identification

As the proportion of renewable energy sources increase, the inertia of the power system continues to decrease, leading to a serious impact on frequency security and stability. There is an urgent need for an online estimation of the equivalent inertia of power systems. Most of the existing inertia estimation methods are based on the rate of change of frequency under large disturbance scenarios. According to the measurement data under normal operation, this paper estimates the equivalent inertia using system identification. The inertia response of the power system is analysed and an expression for the equivalent inertia is derived. An improved numerical algorithm based on subspace state space system identification and a least squares estimation method is used to calculate the equivalent inertia of the system. The validity of the proposed method is verified in a WSCC 9-bus power system case, showing that the proposed method has a high identification accuracy and can be adapted to different forms of load fluctuations.
Sustainable eating in the “new normal” Italy: ecological food habitus between biospheric values and de-globalizing gastronationalism

ABSTRACT This article presents the results of a survey on sustainable food consumption in Italy during COVID-19 times. The study examines the changes triggered by the pandemic, both in sustainable food practises and in consumers’ value-based priorities. The goal is to identify the structuring of an ecological dietary habitus and even a culinary ethos as attention is paid to the reflexive, axiological dimensions of emerging eating habits. The complexity of the phenomenon has suggested a multi-paradigmatic research approach that accounts for the role of human agency in restructuring eating practises in transitional times. The results highlight an emerging nonlinear axiology in which biospheric universalism ambiguously coexists with the lionizing of locavorism and the glorification of food origins, and the direct provision of local food gains prominence despite the increasing mediatization of food choices. A deglobalizing eating style is emerging, where ecological instantiations seem to indulge culinary nationalism and conservative communitarianism. One of the challenges of the “new normal” will be to endow these dispositions with the axiological coherence of an appropriate ecological culinary ethos, as well as to create the conditions for younger generations to prioritize forward-looking ecological values over conservative gastronationalism to promote the sustainable regeneration of food systems.
Reactive power sharing improvement of droop-controlled DFIG wind turbines in a microgrid

This study presents an innovative control scheme to improve the power sharing among doubly-fed induction generator (DFIG) wind units in a medium-voltage (MV) microgrid. The control objectives of DFIGs in an islanded mode of microgrid operation are to achieve: (i) stabilisation of the microgrid voltage amplitude and frequency, (ii) proper active/reactive power sharing among wind units. To satisfy these requirements, the DFIG control loop based on the traditional droop control is designed. This method, however, cannot satisfactorily operate in a MV microgrid with dominantly resistive line impedances from power sharing point of view. To overcome this problem, a modified control strategy is proposed in this study. The mathematical modelling is developed, and time-domain simulations are presented to verify the novel control scheme in a typical microgrid case study.
Correlation Survey of Workplace Stress, Sleep, and Resilience of Nursing Preceptor in Teaching Hospital

Background: Nursing preceptor are under the pressure of clinical and teaching work. The impact of pressure on physical and mental health includes depression, anxiety, sleep disorders, and even mental exhaustion and exhaustion. If they fail to get relief from work, it will cause negative emotions, and will be physically and mentally exhausted for a long time.Aims: To understand the workplace stress, sleep, and resilience of nursing preceptor.Methods: The study used a cross-sectional study design. The enrollment setting was the Nursing Department of a teaching hospital. A total of 35 nursing preceptors.Results: A total of 54.29% of situational anxiety were moderate, 80.0% of trait anxiety was moderate, 57.1% had difficulty falling asleep, 65.7% were unable to maintain a long sleep, and 71.4% had trouble waking up too early, and 91.4% expressed dissatisfaction with sleep. 80.0% have sleep disturbance, and the resilience is low (below 121 points), accounting for 42.8%. Resilience and situational anxiety (p=.003), trait anxiety (p=.001), sleep disturbance (p<.001), physiological stimulation of sleep physical and mental state (p=.003), and cognitive stimulation of sleep physical and mental state (p< .001) are all negative correlations. Trait anxiety is positively correlated with sleep disorders (p<.001). Conclusion: The score of resilience is low, and the various distress states are higher; the higher the distress states, the higher the sleep disturbance. Therefore, for the stress and sleep problems of clinical nursing instructors, caring services should be provided in the future, or through group activities that provide resilience enhance face stress, and reduce sleep disturbance.Recommendations: Clinics can routinely arrange resilience groups to help nurses increase their ability to face stress and improve their quality of life.
Probabilistic Evaluation of the Multicategory Seasonal Precipitation Re-Forecast

The Meteo-France seasonal forecasting system 7 provides a 7-month forecast range with 25 ensembles. The seasonal precipitation re-forecast (from May to November 1993–2015) was evaluated by the Brier score in terms of accuracy and reliability based on tercile probabilities. Multiple analyses were performed to assess the robustness of the score. These results show that the spatial distribution of the Brier score depends significantly on tercile thresholds, reference data, sampling methods, and ensemble types. Large probabilistic errors over the dry regions on land and the Nino regions in the Pacific can be reduced by adjusting the tercile thresholds. The forecast errors were identified when they were insensitive to different analysis methods. All the analyses detected that the errors increase/decrease with the lead time over the tropical Indian/Pacific Ocean. The intra-seasonal analysis reveals that some of these errors are inherited from monthly forecasts, which may be related to large-scale, short-term variability modes. A new confidence interval calculation was formulated for the “uncertain” case in the reference data. The confidence interval at a 95% level for the mean Brier score over the entire tropical region was quantified. The best estimations are ~6% the mean Brier score for both the above and below-normal terciles.
Epidemiology of myocardial infarction in Korea: hospitalization incidence, prevalence, and mortality

Few studies have comprehensively presented epidemiological indicators of myocardial infarction in Korea. However, multiple published articles and open-source secondary data on the epidemiology of myocardial infarction are now available. This review summarized the hospitalization incidence, prevalence, and mortality rate of myocardial infarction in Korea using articles and open-source data from the Health Insurance Service and the Department of Statistics, surveys of sample populations, registries of patients, and other sources. The epidemiological indicators of myocardial infarction were compared between Korea and other high-income countries. The incidence of hospitalization due to myocardial infarction in Korea was 43.2 cases per 100,000 population in 2016 and has consistently increased since 2011. It was 2.4 times higher among men than among women. The estimated prevalence among adults over 30 years of age ranged from 0.34% to 0.70% in 2020; it was higher among men and increased with age. The mortality in 2020, which was 19.3 per 100,000 population in 2020, remained relatively stable in recent years. Mortality was higher among men than among women. Based on representative inpatient registry data, the proportion of ST-elevated myocardial infarction decreased until recently, and the median time from symptom onset to hospital arrival was approximately 2 hours and 30 minutes. The hospitalization incidence, prevalence, and mortality rate of myocardial infarction were lower in Korea than in other countries, although there was an increasing trend. Comprehensive national-level support and surveillance systems are needed to routinely collect accurate epidemiological indicators.
Hidden Species Diversity was Explored in Two Genera of Catapyrenioid Lichens (Verrucariaceae, Ascomycota) from the Deserts of China

Verrucariaceae is the third-largest lichen family with high species diversity. However, this diversity has not been well-explored in China. We carried out a wide-scale field investigation in the arid and semi-arid regions of Northwest China from 2017 to 2021. A large number of lichen groups, especially those commonly distributed in deserts, were collected. Based on molecular phylogeny using ITS and nuLSU sequences by Bayesian and maximum likelihood analyses, combining morphological characters, seven taxa of catapyrenioid lichens in Verricariaceae were found in this study, including one genus (Clavascidium) and one species (Clavascidium lacinulatum) new to China; one genus (Placidium) new to the mainland of China; and four species (Clavascidium sinense, Placidium nitidulum, Placidium nigrum, and Placidium varium) new to science. It enriched our understanding of the high species diversity in Verrucariaceae and the lichen flora of Chinese arid and semi-arid deserts.
Preamplifier Noise Figure Measurement and Radio Frequency Field Optimization in High Field Magnetic Resonance Imaging

High field magnetic resonance imaging (MRI) is an area of research interest due to the associated improvement in image quality possible. This improvement comes at a cost. Hardware design becomes more complex in order to overcome technical challenges at these higher field strengths. Signal-to-noise ratio is of paramount importance to MR image quality and this comes from carefully designed hardware and pulse sequences. This thesis focuses on the radiofrequency hardware of a high field MRI system. As frequency increases, the difficulties associated with radiofrequency hardware design increase. A noise figure and noise parameter measurement system was developed for measurement of the noise added by measurement electronics in MRI. Noise figure was found to increase for many transistor semiconductors as magnetic
Wireless charging module

A wireless charging module, according to the present embodiment, comprises: a base sheet which has a wireless charging coil formed thereon; a first magnetic sheet which is coupled to the rear surface of the base sheet and has a first permeability; and a second magnetic sheet which is disposed on the front surface side of the base sheet and has a second permeability that is lower than the first permeability. According to the present embodiment, the magnetic field generated from the wireless charging coil many be evenly distributed in all areas by disposing a high-permeability magnetic sheet on the rear surface of the wireless charging coil, and disposing a low-permeability magnetic sheet on the front surface of the wireless charging coil.
Novel lncRNAs with diagnostic or prognostic value screened out from breast cancer via bioinformatics analyses

Background Recent studies have shown that long non-coding RNAs (lncRNAs) may play key regulatory roles in many malignant tumors. This study investigated the use of novel lncRNA biomarkers in the diagnosis and prognosis of breast cancer. Materials and Methods The database subsets of The Cancer Genome Atlas (TCGA) by RNA-seq for comparing analysis of tissue samples between breast cancer and normal control groups were downloaded. Additionally, anticoagulant peripheral blood samples were collected and used in this cohort study. The extracellular vesicles (EVs) from the plasma were extracted and sequenced, then analyzed to determine the expressive profiles of the lncRNAs, and the cancer-related differentially expressed lncRNAs were screened out. The expressive profiles and associated downstream-mRNAs were assessed using bioinformatics (such as weighted correlation network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) enrichments, Receiver-Operating Characteristic (ROC) curve and survival analysis, etc.) to investigate the diagnostic and prognostic values of these EV lncRNAs and their effectors. Results In this study, 41 breast cancer-related lncRNAs were screen out from two datasets of tissue and fresh collected plasma samples of breast cancer via the transcriptomic and bioinformatics techniques. A total of 19 gene modules were identified with WGCNA analysis, of which five modules were significantly correlated with the clinical stage of breast cancer, including 28 lncRNA candidates. The ROC curves of these lncRNAs revealed that the area under the curve (AUC) of all candidates were great than 70%. However, eight lncRNAs had an AUC >70%, indicating that the combined one has a good diagnostic value. In addition, the results of survival analysis suggested that two lncRNAs with low expressive levels may indicate the poor prognosis of breast cancer. By tissue sample verification, C15orf54, AL157935.1, LINC01117, and SNHG3 were determined to have good diagnostic ability in breast cancer lesions, however, there was no significant difference in the plasma EVs of patients. Moreover, survival analysis data also showed that AL355974.2 may serve as an independent prognostic factor and as a protective factor. Conclusion A total of five lncRNAs found in this study could be developed as biomarkers for breast cancer patients, including four diagnostic markers (C15orf54, AL157935.1, LINC01117, and SNHG3) and a potential prognostic marker (AL355974.2).
Deep Learning Automation of Kidney, Liver, and Spleen Segmentation for Organ Volume Measurements in Autosomal Dominant Polycystic Kidney Disease

Organ volume measurements are a key metric for managing ADPKD (the most common inherited renal disease). However, measuring organ volumes is tedious and involves manually contouring organ outlines on multiple cross-sectional MRI or CT images. The automation of kidney contouring using deep learning has been proposed, as it has small errors compared to manual contouring. Here, a deployed open-source deep learning ADPKD kidney segmentation pipeline is extended to also measure liver and spleen volumes, which are also important. This 2D U-net deep learning approach was developed with radiologist labeled T2-weighted images from 215 ADPKD subjects (70% training = 151, 30% validation = 64). Additional ADPKD subjects were utilized for prospective (n = 30) and external (n = 30) validations for a total of 275 subjects. Image cropping previously optimized for kidneys was included in training but removed for the validation and inference to accommodate the liver which is closer to the image border. An effective algorithm was developed to adjudicate overlap voxels that are labeled as more than one organ. Left kidney, right kidney, liver and spleen labels had average errors of 3%, 7%, 3%, and 1%, respectively, on external validation and 5%, 6%, 5%, and 1% on prospective validation. Dice scores also showed that the deep learning model was close to the radiologist contouring, measuring 0.98, 0.96, 0.97 and 0.96 on external validation and 0.96, 0.96, 0.96 and 0.95 on prospective validation for left kidney, right kidney, liver and spleen, respectively. The time required for manual correction of deep learning segmentation errors was only 19:17 min compared to 33:04 min for manual segmentations, a 42% time saving (p = 0.004). Standard deviation of model assisted segmentations was reduced to 7, 5, 11, 5 mL for right kidney, left kidney, liver and spleen respectively from 14, 10, 55 and 14 mL for manual segmentations. Thus, deep learning reduces the radiologist time required to perform multiorgan segmentations in ADPKD and reduces measurement variability.
Flow Feature in Supersonic Non-Isobaric Jet near the Nozzle Edge

Using the example of studying the supersonic underexpanded jet initial section, the issue of interpreting the experimental visualization data and Pitot pressure measurement data using the results of numerical calculations (2d RANS k-ω SST) is discussed. It is shown that the gradient S-shaped feature of the gas-dynamic structure near the nozzle exit, observed in the form of a barrel shock, is a characteristic that separates the expansion and compression regions, and downstream is transformed into a barrel shock. It has been established that the reason for the observed S-shaped curvature of this feature is the axisymmetric nature of the jet flow.
Living Photovoltaics based on Recombinant Expression of MtrA Decaheme in Photosynthetic Bacteria

At the center of microbial bioelectricity applications lies the critical need to express foreign heme proteins that are capable of redirecting the electron flux of the cell’s metabolism. This study presents bioengineered Synechocystis sp. PCC 6803 cells capable of increased electrogenicity through the introduction of a genetic construct for cytochrome expression. We could demonstrate the functional expression of the periplasmic MtrA decaheme c-type cytochrome from Shewanella oneidensis, a dissimilatory metal-reducing exoelectrogen, inside Synechocystis. Protein expression was verified through western-blotting and immunostaining, and oxygen evolution, optical density, and absorption measurements confirm sustained cell activity and viability under the tested expression conditions. Furthermore, the bioengineered cells show enhanced mediated exoelectrogenicity, as confirmed through a colorimetric iron assay and electrochemical measurements. Compared to wildtype cells on graphite electrodes, the bioengineered cells show a 2-fold increase in light-dependent, extracellular electron transfer, achieving photocurrent densities of 4 μA/cm2 under white light illumination of ∼500 μmol m-2s-1. The increased capacitance obtained under illumination and suppressed photocurrents in the presence of the photosynthetic inhibitor, 3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU) suggest increased extraction of photosynthetically derived electrons from the recombinant cells. The improved bioelectricity transport across the outer membranes, as achieved through the heterologous heme expression inside cyanobacteria, presents new opportunities for re-wiring the metabolisms of light-harvesting microbes.
Two-Scale Homogenisation of Partially Degenerating PDEs with Applications to Photonic Crystals and Elasticity

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Design and testing of a novel flexure-based 3-degree-of-freedom elliptical micro/nano-positioning motion stage

In this article, a novel flexure-based 3-degree-of-freedom elliptical micro/nano-positioning motion stage was developed to obtain translation motions along the x, y, and z directions with high working bandwidth. The stage was configurations with a XYZ vertical motion to ensure the crosstalk between each axis is small enough. The motion stage was driven by three piezoelectric actuators. The corresponding working principles and stiffness modeling were detailed in this article. In addition, experimental testing was conducted to investigate the performances of the motion stage. The obtained strokes in x, y, and z directions are 10.39, 15.43, and 15.55 μm, respectively. The response rise time for each axis is within 10 ms, and the maximum crosstalk all within 1.2% ensured the rapid tracking can be achieved.
Overarching Sustainable Energy Management of PV Integrated EV Parking Lots in Reconfigurable Microgrids Using Generative Adversarial Networks

In recent years, environmental issues have motivated the wide usage of electric vehicles (EVs) due to their zero tailpipe emission. However, this trend can pose severe challenges to power systems, such as decreasing equipment lifetime. Moreover, the CO2 emission of EVs is closer to that of internal combustion engine vehicles in some cases due to the carbon footprint of EV charging. Modeling the uncertain nature of EV users’ behavior is another obstacle due to the complex dynamics of these uncertainties. To overcome these problems, an overarching day-ahead smart charging method is proposed in this paper from the perspective of distribution system operators (DSOs), EV users, and governments simultaneously. The aim of the proposed method is to minimize the operating cost of microgrids, the degradation cost of EV batteries, and emission cost by scheduling the active and reactive power of EV parking lots integrated with photovoltaic (PV) systems as well as finding the optimum network configuration. Previous model-based methods cannot appropriately model uncertainties in EV users’ behavior because of some statistical assumptions. Nevertheless, this paper employs data-driven methods based on generative adversarial networks (GAN) to represent these uncertainties. The performance of the proposed method is evaluated by implementing it on a real reconfigurable microgrid. The results show that using the proposed method, the DSO and emission costs can reduce by 11.96% and 3.37% compared to the uncoordinated charging of EVs, respectively. Furthermore, the share of sustainable energy in EV charging increases by 9% using the proposed method.
The fire hazard potential of thermally thin cellulose nonwovens with different overlap configurations

The fire hazard potential of nonwovens with different overlap configurations and various thicknesses between 0.5 and 5 mm were investigated to clarify the possible worsening situation induced by the difference in overlapping configurations. The fire hazard of thermally thin nonwovens is characterized by flame spread, flame height, temperature distribution, and mass loss. The flame spread rate and FDI (fire development index) increase and then decrease as the thickness of the nonwovens increases. The fire hazard potential of samples with OL configuration (overlapping layer by layer configuration) is higher than that with AO configuration (accordion-style overlap configuration), which is reflected in the high FDI, average fire spread rate, and flame height, and low ignition time. The difference between the fire risk of the two overlapping configurations was confirmed by analyzing the heat transfer mechanism. Due to the different packaging methods, the AO and OL configurations of nonwovens show different degrees of shrinkage and curling effects during combustion. The large air gap between the layers and the weight of the sample edge are the reasons for the weak contraction of the sample with an AO configuration. The sample shrinkage with OL configuration strengthens the flame spread to a certain extent by increasing the convective heat transfer in the preheat zone.