The clinical characteristics of COVID-19 omicron variant infection in pregnant women and their neonates.

Objective: The objective of this study was to analyze the clinical characteristics of pregnant women infected with the COVID-19 omicron variant and their neonates during the outbreak in Guangdong province, China. Methods: The clinical data of pregnant women infected with the COVID-19 omicron variant and their neonates were retrospectively collected from two hospitals in Guangdong province. Information recorded included age of mother, date of birth, sex, weight at birth, mode of delivery, gestational age, feeding mode, Apgar score, signs, medical records, underlying comorbidities and laboratory results. The presence of SARS-CoV-2 viral RNA was tested using an real-time PCR assay. Results: Seventy-nine pregnant women infected with COVID-19 omicron variant and their 68 neonates were included in this study. The vast majority (86.1%) of pregnant women was in their third trimester of pregnancy, and only 11 cases (15%) were in the first or second trimester. Of 79 pregnant women, 39 cases were asymptomatic at the time of infection, and 40 mothers presented with mild manifestations of COVID-19. The most common symptoms were fever (92.5%, 37/40) and cough (57.5%, 21/40). All of pregnant women did not receive chest computed tomography (CT) scan or X-ray. No pregnant woman developed severe pneumonia. A total of 68 neonates (3 set of twins) from 65 mothers with COVID-19 were reviewed. Among women who delivered, 34 cases underwent cesarean section, 31 cases underwent vaginal delivery. According to the timing of birth, there were 10 (14.7%) preterm neonates. Two babies were born dead (intrauterine fetal death after 22 weeks of gestation). Of the live babies born (66 cases) from mothers with COVID-19, 9 newborns were lower weight, and one preterm case was born with respiratory distress and intubated, he recovered and developed normally. SARS-CoV-2 nucleic acid testing was conducted on 41 neonates daily after birth, with only one neonate testing positive for SARS-CoV-2 infection on the third day after birth. The infected neonate exhibited typical fever and acute respiratory tract syndrome but ultimately had a good prognosis, recovering after 5 days of treatment. Conclusion: Although preliminary data suggests the risk of severe maternal and fetal complications from Omicron variant infection during pregnancy is lower than previous variants and Delta variant. Our study, which was conducted on a limited population sample, indicates that there is a possibility of severe complications, such as stillbirth, occurring in some fetal cases. These findings emphasize the need for continued attention from obstetricians.

Etiology analysis and G6PD deficiency for term infants with jaundice in Yangjiang of western Guangdong.

Objective: Glucose 6-phosphate dehydrogenase (G6PD) deficiency increases the risk of neonatal hyperbilirubinemia. The aim of this study is to evaluate the risk factors associated with hyperbilirubinemia in infants from the western part of Guangdong Province, and to assess the contribution of G6PD deficiency to neonatal jaundice. Methods: The term infants with neonatal hyperbilirubinemia in People's Hospital of Yangjiang from June 2018 to July 2022 were recruited for the retrospective analysis. All the infants underwent quantitative detection of the G6PD enzyme. The etiology was determined through laboratory tests and clinical manifestations. Results: Out of 1,119 term infants, 435 cases presented with jaundice. For the etiology analysis, infection was responsible for 16.09% (70/435), G6PD deficiency accounted for 9.66% (42/435), of which 3 were complicated with acute bilirubin encephalopathy), bleeding accounted for 8.05% (35/435), hemolytic diseases accounted for 3.45% (15/435), and breast milk jaundice accounted for 2.53% (11/435). One case (0.23%) was attributed to congenital hypothyroidism, multiple etiologies accounted for 22.3% (97/435), and 35.63% (155/435) were of unknown etiology. Of the jaundiced infants, 19.54% (85/435) had G6PD deficiency, while only 10.23% (70/684) of non-jaundiced infants had G6PD deficiency; this difference was found to be statistically significant (P < 0.001). Furthermore, the hemoglobin levels in the jaundiced infants with G6PD deficiency (146.85 ± 24.88 g/L) were lower than those without G6PD deficiency (156.30 ± 22.07 g/L) (P = 0.001). 65 jaundiced infants with G6PD deficiency underwent G6PD mutation testing, and six different genotypes were identified, including c.95A > G, c.392G > T, c.1024C > T, c.1311C > T, c.1376G > T, c.1388G > A, c.871G > A/c.1311C > T, c.392G > T/c.1388G > A, and c.1376G > T/c.1311C > T.65iciency. Conclusion: In newborns in Yangjiang, G6PD deficiency, infection, and neonatal hemolytic disease were identified as the main causes of hyperbilirubinemia and acute bilirubin encephalopathy. Specifically, Hemolytic factors in infants with G6PD deficiency may lead to reduced hemoglobin and increased bilirubin levels in jaundiced infants.

Covid-19 omicron variant infection in neonates of Guangdong province-a report of 52 cases.

Objective: To analyze the clinical characteristics of neonatal infection during the outbreak of COVID-19 omicron variant in Guangdong province of China. Method: The clinical data of neonates infected with COVID-19 omicron variant were collected from three hospitals of Guangdong province, their epidemiological history, clinical manifestation and prognosis were summarized. Results: From December 12, 2022 to January 15, 2023, a total of 52 neonates with COVID-19 infection were identified across three hospitals in Guangdong Province, including 34 males and 18 females. The age of diagnosis was 18.42 ± 6.32 days. 24 cases had clear contact history with adults who were suspected to be infected with COVID-19. The most common clinical manifestation was fever (43/52, 82.7%), the duration of fever was 1-8 days. The other clinical manifestations were cough (27/52, 51.9%), rales (21/52, 40.4%), nasal congestion (10/52, 19.2%), shortness of breath (2/52, 3.8%), and vomiting (4/52, 7.7%). C-reactive protein was only increased in 3 cases. Chest radiological examination was performed in 42 neonates, twenty-three cases showed abnormal chest radiographic findings, including ground-glass opacity and consolidation. Fifty cases were admitted with COVID-19 presentation, two cases were admitted for jaundice. The hospital stay was 6.59 ± 2.77 days. The clinical classification included 3 cases of severe COVID-19 and one critical case. Fifty-one cases were cured and discharged after general treatment, and one critical case with respiratory failure was intubated and transferred to another hospital. Conclusion: The COVID-19 omicron variant infection in neonates is usually mild. The clinical manifestation and laboratory results are not specific, and the short-term prognosis is good.

A New Grey Wolf Optimizer Tuned Extended Generalized Predictive Control for Distillation Process.

The distillation process plays an essential role in the petrochemical industry. However, the high-purity distillation column has complicated dynamic characteristics such as strong coupling and large time delay. To control the distillation column accurately, we proposed an extended generalized predictive control (EGPC) method inspired by the principles of extended state observer and proportional-integral-type generalized predictive control method; the proposed EGPC can adaptively compensate the system for the effects of coupling and model mismatch online and performs well in controlling time-delay systems. The strong coupling of the distillation column needs fast control, and the large time delay requires soft control. To balance the requirement for fast and soft control at the same time, a grey wolf optimizer with reverse learning and adaptive leaders number strategies (RAGWO) was proposed to tune the parameters of EGPC, and these strategies enable RAGWO to have a better initial population and improve its exploitation and exploration ability. The benchmark test results indicate that the RAGWO outperforms the existing optimizers for most of the selected benchmark functions. Extensive simulations show that the proposed method in terms of fluctuation and response time is superior to other methods for controlling the distillation process.

Molecular epidemiological investigation of G6PD deficiency in Yangjiang region, western Guangdong province.

Objectives: The prevalence of G6PD deficiency has not been reported in Yangjiang, a western city in Guangdong province. This study aims to investigate the molecular characteristics of G6PD deficiency in this region. Methods: Blood samples were collected from adults at a local hospital to screen for G6PD deficiency. The deficient samples were subjected to further analysis using PCR and reverse dot blot to determine the specific G6PD variants. Results: Among the 3314 male subjects, 250 cases of G6PD deficiency were found using the G6PD enzyme quantitative assay, resulting in a prevalence of 7.54% (250/3314) in the Yangjiang region. The prevalence of G6PD deficiency in females was 3.42% (176/5145). Out of the 268 cases of G6PD deficiency tested for G6PD mutations, reverse dot blot identified 20 different G6PD variants. The most common G6PD variant was c.1388G>A (81/268), followed by c.1376G>T (48/268), c.95A>G (32/268), c.1024C>T (9/268), c.392G>T (7/268), and c.871G>A/c.1311C>T (6/268). It was observed that c.871G>A was always linked to the polymorphism of c.1311C>T in this population. Conclusion: This investigation into G6PD deficiency in this area is expected to significantly improve our understanding of the prevalence and molecular characterization of this condition.

Nonfinite-modality data augmentation for brain image registration.

Brain image registration is fundamental for brain medical image analysis. However, the lack of paired images with diverse modalities and corresponding ground truth deformations for training hinder its development. We propose a novel nonfinite-modality data augmentation for brain image registration to combat this. Specifically, some available whole-brain segmentation masks, including complete fine brain anatomical structures, are collected from the actual brain dataset, OASIS-3. One whole-brain segmentation mask can generate many nonfinite-modality brain images by randomly merging some fine anatomical structures and subsequently sampling the intensities for each fine anatomical structure using random Gaussian distribution. Furthermore, to get more realistic deformations as the ground truth, an improved 3D Variational Auto-encoder (VAE) is proposed by introducing the intensity-level reconstruction loss and the structure-level reconstruction loss. Based on the generated images and trained improved 3D VAE, a new Synthetic Nonfinite-Modality Brain Image Dataset (SNMBID) is created. Experiments show that pre-training on SNMBID can improve the accuracy of registration. Notably, SNMBID can be a landmark for evaluating other brain registration methods, and the model trained on the SNMBID can be a baseline for the brain image registration task. Our code is available at https://github.com/MangoWAY/SMIBID_BrainRegistration.

Research on an LEO Constellation Multi-Aircraft Collaborative Navigation Algorithm Based on a Dual-Way Asynchronous Precision Communication-Time Service Measurement System (DWAPC-TSM).

In order to solve the collaborative navigation problems in challenging environments such as insufficient visible satellites, obstacle reflections and multipath errors, and in order to improve the accuracy, usability, and stability of collaborative navigation and positioning, we propose a dual-way asynchronous precision communication-timing-measurement system (DWAPC-TSM) LEO constellation multi-aircraft cooperative navigation and positioning algorithm which gives the principle, algorithm structure, and error analysis of the DWAPC-TSM system. In addition, we also analyze the effect of vehicle separation range on satellite observability. The DWAPC-TSM system can achieve high-precision ranging and time synchronization accuracy. With the help of this system, by adding relative ranging and speed measurement observations in an unscented Kalman filter (UKF), the multi-aircraft coordinated navigation and positioning of aircraft is finally realized. The simulation results show that, even without the aid of an altimeter, the multi-aircraft cooperative navigation and positioning algorithm based on the DWAPC-TSM system can achieve good navigation and positioning results, and with the aid of the altimeter, the cooperative navigation and positioning accuracy can be effectively improved. For the formation flight configurations of horizontal collinear and vertical collinear, the algorithm is universal, and in the case of vertical collinear, the navigation performance of the formation members tends to be consistent. Under different relative measurement accuracy, the algorithm can maintain good robustness; compared with some existing classical algorithms, it can significantly improve the navigation and positioning accuracy. A reference scheme for exploring the feasibility of a new cooperative navigation and positioning mode for LEO communication satellites is presented.

Recognizing Missing Electromyography Signal by Data Split Reorganization Strategy and Weight-Based Multiple Neural Network Voting Method.

Surface electromyography (sEMG) signals have been applied widely in prosthetic hand controlling. In the sEMG signal acquisition, wireless devices bring convenience, but also introduce signal missing due to interference or failure during data transmission. The missing signal may only last for tens of milliseconds, but have a great impact on the recognition. Researchers have employed various methods to complete missing sEMG data, but the completed signal may not totally fit the origins, and more extra calculation time will be spent. When recognizing hand gestures by sEMG from few sensors, to recognize the slightly or not serious signal missing, this study proposed a data split reorganization (DSR) strategy and a weight-based multiple neural network voting (WMV) method. To validate the proposed methods, controllable missing sEMG signals are generated artificially. Three time domain features are extracted based on non-overlapping sliding windows. The DSR is employed to make full use of the features, and then the WMV is utilized to recognize them. Nine subjects participated in the experiments, and the results indicate that the accuracy of the proposed methods is higher. For 5%, 10%, and 15% data missing ratios, the accuracy is 93.66%, 92.55%, and 91.19%, respectively. The Wilcoxon signed-rank test also demonstrates that these results are significantly superior to the situations in which the proposed methods are not applied. In the future, we will optimize the proposed methods to recognize the seriously missing sEMG signal.

The Effect of Treadmill Walking on Gait and Upper Trunk through Linear and Nonlinear Analysis Methods.

Treadmills are widely used to recover walking function in the rehabilitation field for those patients with gait disorders. Nevertheless, the ultimate goal of walking function recovery is to walk on the ground rather than on the treadmill. This study aims to determine the effect of treadmill walking on gait and upper trunk movement characteristics using wearable sensors. Eight healthy male subjects are recruited to perform 420-m straight overground walking (OW) and 5 min treadmill walking (TW), wearing 3 inertial measurement units and a pair of insole sensors. In addition to common linear features, nonlinear features, which contains sample entropy, maximal Lyapunov exponent and fractal dynamic of stride intervals (detrended fluctuation analysis), are used to compare the difference between TW and OW condition. Canonical correlation analysis is also used to indicate the correlation between upper trunk movement characteristics and gait features in the aspects of spatiotemporal parameters and gait dynamic features. The experimental results show that the treadmill can cause a shorter stride length, less stride time and worsen long-range correlation of stride intervals. And the treadmill can significantly increase the stability for both gait and upper trunk, while it can significantly reduce gait regularity during swing phase. Canonical correlation analysis results show that treadmill can reduce the correlation between gait and upper trunk features. One possible interpretation of these results is that people tend to walk more cautiously to prevent the risk of falling and neglect the coordination between gait and upper trunk when walking on the treadmill. This study can provide fundamental insightful information about the effect of treadmill walking on gait and upper trunk to support future similar studies.

Analysis of the Effects of Thermal Environment on Optical Systems for Navigation Guidance and Control in Supersonic Aircraft Based on Empirical Equations.

The thermal environment is an important factor in the design of optical systems. This study investigated the thermal analysis technology of optical systems for navigation guidance and control in supersonic aircraft by developing empirical equations for the front temperature gradient and rear thermal diffusion distance, and for basic factors such as flying parameters and the structure of the optical system. Finite element analysis (FEA) was used to study the relationship between flying and front dome parameters and the system temperature field. Systematic deduction was then conducted based on the effects of the temperature field on the physical geometry and ray tracing performance of the front dome and rear optical lenses, by deriving the relational expressions between the system temperature field and the spot size and positioning precision of the rear optical lens. The optical systems used for navigation guidance and control in supersonic aircraft when the flight speed is in the range of 1-5 Ma were analysed using the derived equations. Using this new method it was possible to control the precision within 10% when considering the light spot received by the four-quadrant detector, and computation time was reduced compared with the traditional method of separately analysing the temperature field of the front dome and rear optical lens using FEA. Thus, the method can effectively increase the efficiency of parameter analysis and computation in an airborne optical system, facilitating the systematic, effective and integrated thermal analysis of airborne optical systems for navigation guidance and control.