Treatment of hemimasticatory spasm secondary to parry-romberg syndrome via partial resection of the trigeminal nerve motor branch under intraoperative neurophysiological monitoring: A case report and literature review

Parry-Romberg syndrome (PRS) combined with hemimasticatory spasm (HMS) is a rare craniofacial disorder characterized by unilateral facial tissue atrophy with paroxysmal involuntary contractions of the jaw-closing muscles. Although a majority believe that this is a result of demyelination changes from the effect of the facial involvement of PRS on the trigeminal nerve motor branches, the mechanism of PRS is presently unclear. Moreover, the therapeutic effects of existing drugs that target PRS have not been satisfactory. For intolerable spasms of the masticatory muscles, botulinum toxin injection may temporarily relieve the symptoms of spasms. We report a case of HMS secondary to PRS that was treated via a partial resection of the trigeminal nerve motor branch under intraoperative neurophysiological monitoring

The level effect and volatility effect of uncertainty shocks in China

Previous studies have assumed that the volatility of exogenous shocks is constant, which can only measure the level effects of uncertain shocks. This article introduces the time-varying volatility model into a Dynamic Stochastic General Equilibrium (D.S.G.E.) model and uses the third-order perturbation method to identify and decompose the level and volatility effects of uncertainty shocks. Based on the results of empirical research in China, the effect of volatility shocks is different from that of level shocks: the effect of level shocks is direct and positive, and its impact is larger, while the effect of volatility shocks is indirect and negative, and its impact is smaller. This article also finds that the impact of uncertainty shocks will lead to economic stagnation, inflation, and the stagflation effect

Analysis of electrical drive speed control limitations of a power take-off system for wave energy converters

The active control of wave energy converters with oil-hydraulic power take-off systems presents important demands on the electrical drives attached to their pumps, in particular on the required drive accelerations and rotational speeds. This work analyzes these demands on the drives and designs reliable control approaches for such drives by simulating a wave-to-wire model in a hardware in-the-loop simulation test rig. The model is based on a point absorber wave energy converter, being the wave, hydrodynamic and oil-hydraulic part simulated in a computer that sends and receives signals from the real embedded components, such as the drive generator, controller and back-to-back converter. Three different control strategies are developed and tested in this test rig and the results revealed that despite the drive limitations to acceleration levels, well above 1 × 104 rpm/s, these do not significantly affect the power take-off efficiency, because the required acceleration peaks rarely achieve these values. Moreover this drive is much more economical than an oil-hydraulic and equivalent one that is able to operate at those peaks of acceleration.This work was performed within the Strategic Research Plan of the Center for Marine Technology and Ocean Engineering, which is financed by Portuguese Foundation for Science and Technology (Fundacao para a Ciencia e Tecnologia-FCT) and the project "Generic hydraulic power take-off system for wave energy converters" funded by the Portuguese Foundation for Science and Technology (FCT) under contract PTDC/EMS-SIS-1145/2014. The testing has received support from MARINET, a European Community - Research Infrastructure Action under the FP7 "Capacities" Specific Programme, grant agreement nr. 262552. The research leading to these results is also part of the OceaNET project, which has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement nr. 607656

The Mental Health of Healthcare Staff Working During the COVID-19 Crisis: Their Working Hours as a Boundary Condition

Purpose: Healthcare staff operate at the forefront of the fight against COVID-19 and hence face enormous physical and mental pressures. We aim to investigate healthcare staff’s mental health issues and the associated predictors during the COVID-19 pandemic. Specifically, this paper aims to identify some unique predictors of healthcare staff’s mental health issues in Iran, the second country after China to experience a major COVID-19 crisis. Methods: An online survey of 280 healthcare staff in all 31 provinces of Iran assessed staff’s mental distress (K6), depression, and anxiety (PHQ-4) during April 5–20, 2020 during the COVID-19 crisis. Results: Nearly a third of healthcare staff surpassed the cut-off for distress, depression, and anxiety symptoms. Females or more educated healthcare staff were more likely to experience distress. Those who were unsure whether they had COVID-19 were more likely to experience distress and depression symptoms. The number of COVID-19 cases among a healthcare worker’s colleagues or friends positively predicted the worker’s anxiety symptoms. Amongst healthcare staff, doctors were less likely than radiology technologists to experience distress and anxiety symptoms. Technicians and obstetrics staff experienced fewer anxiety symptoms. The age and the weekly working days of healthcare staff interacted such that age is a significant predictor of mental health issues among younger but not older healthcare staff. Conclusion: The identification of the predictors of mental health issues can guide healthcare organizations to screen healthcare workers who are more likely to be mentally vulnerable in the ongoing COVID-19 pandemi

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Uncertainty analysis of the hydrodynamic coefficients estimation of a nonlinear manoeuvring model based on planar motion mechanism tests

Uncertainty analysis of the identified hydrodynamic coefficients of a nonlinear manoeuvring model is presented in this paper. The classical parameter estimation method, Least Square, is briefly introduced, and the uncertainty of the hydrodynamic coefficients due to the noise in the measured data is analysed using singular value decomposition. Then, two methods, truncated singular values decomposition and Tikhonov regularization, are introduced to diminish the uncertainty. A nonlinear manoeuvring mathematical model of a marine surface ship is derived using Lagrange's method. The dimensionless hydrodynamic coefficients are obtained using the Least Squares method, truncated singular values decomposition and Tikhonov regularization with Planar Motion Mechanism test data. The validation process is carried out to test the performance and accuracy of the resulting nonlinear manoeuvring models. The result shows that identification of the uncertain parameters using the truncated singular values decomposition and Tikhonov regularization resulted in good estimating the parameters and significantly diminish the uncertainty.acceptedVersio

Unbalance Suppression for AMB Rotor System Using APF-SRF Algorithm

With the great capability in levitating rotors, active magnetic bearings (AMB) have been increasingly applied in high-speed rotating machinery applications. Typically, for the practical application of AMB rotor systems, synchronous unbalance vibration has long been a critical issue. Thus, exploring a facile yet effective approach to address this issue has attracted tremendous interest from both industrial and academic perspectives. Herein, in this work, we propose a novel strategy to suppress the unbalance vibration through a compensation control algorithm method. The compensation control algorithm which is established based on the combination of first-order all-pass filter (APF) and synchronous rotating frame (SRF) algorithm demonstrates to be efficient in greatly reducing the unbalance vibration and resulting in excellent system stability according to both simulation and experimental results. This work not only confirms the applicability of APF-SRF algorithm for the AMB rotor systems but also opens up a new paradigm to modulate and minimize the unbalance vibration of AMB rotor systems

Parameters Estimation of Nonlinear Manoeuvring Model for Marine Surface Ship Based on PMM Tests

A nonlinear manoeuvring mathematical model of marine surface ship model is briefly introduced. In order to obtain the hydrodynamic coefficients, system identification is used to estimate the parameters using Planar Motion Mechanism (PMM) test data. Usually, the obtained parameters using measured data have a large uncertainty due to the ill-conditioned processes of identification. An optimal Truncated Singular Value Decomposition (TSVD) method is exploited to reduce the uncertainty of the estimated parameters. The optimal number of retaining singular values is calculated by using the L-curve, which is a log-log plot of the norm of a regularized solution versus the norm of the corresponding residual norm. It is a graphical tool for displaying the trade-off between the estimated parameters norm and the corresponding residual error norm. The validation process is performed by comparison of the prediction values with the experimental data in the time domain