Search Results (7)

Background/Objectives: The co-morbidity between neurodevelopmental tics and functional tic-like behaviors (FTBs) in patients with Tourette syndrome (TS) is relatively under-investigated. The demographic and clinical characteristics of a large sample of patients with TS who presented with co-morbid FTBs (functional overlay) were assessed to raise awareness of this complex clinical presentation and to shed light on the differential diagnosis between the two conditions. Methods: We analyzed the clinical data of 63 patients (44 females, mean age 24 years, range 13–40) with pre-existing TS who (sub)acutely developed co-morbid FTBs (TS + FTBs) after the onset of the COVID-19 pandemic and compared them with 63 age- and gender-matched controls with TS (neurodevelopmental tics only). The diagnosis of co-morbid FTBs was validated by the European Society for the Study of Tourette Syndrome (ESSTS) criteria. Results: Complex vocal tics (p < 0.001), including coprolalia (p = 0.002), and self-injurious behaviors (p < 0.001), often as part of tic attacks (p < 0.001), were confirmed to be more commonly reported by the group of patients with TS + FTBs, who were also more likely to present with anxiety (p < 0.001) and other functional neurological symptoms (p < 0.001) compared to patients with TS. Conclusions: Patients with TS and co-morbid FTBs can pose significant diagnostic and treatment challenges. By systematically applying ESSTS criteria, we confirmed specific red flags for the diagnosis of functional overlay in patients with TS. The correct identification of this composite clinical phenotype plays a key role in preventing the misdiagnosis of treatment-resistant TS and implementing tailored treatment interventions. Full article

Due to nonlinear aerodynamics, “non-traditional” flight modes may appear in longitudinal and lateral/directional dynamics once an aircraft experiences a high angle of attack and rapid maneuvers. Signal decomposition techniques are required to uncover these modes since they are hidden in flight characteristics. This study represents the Enhanced SynchroSqueezing Transform (ESST) for the extraction of “non-traditional” flight modes from flight data. Developed in the framework of the SynchroSqueezing Transform (SST), the ESST decomposes an Amplitude- and Frequency-Modulated (AMFM) signal into Intrinsic Mode Functions (IMFs). This process is optimized using the Genetic Algorithm (GA). Numerical investigations are performed to confirm the validity of the ESST. Both quantitative criteria for the fitness of the IMFs and qualitative study of the Time–Frequency Representations (TFRs) suggest that the ESST may perform better than the SST in decomposing nonlinear and non-stationary signals. Then, a method is proposed to find the instantaneous characteristics of the flight modes obtained by the ESST. The ESST analyzes an aircraft’s longitudinal and lateral flight data in post-stall maneuvers. The TFRs of flight parameters verify the existence of identical flight modes at different flight conditions. The IMFs are separated, and their instantaneous characteristics are computed. In addition, the ESST modes are compared to conventional modes. The results indicate that the ESST is capable of obtaining both classical oscillatory modes, such as Short Period (SP) and Dutch Roll (DR), and “non-traditional” modes. In the end, coupled modes are identified by comparing longitudinal and lateral IMFs. Full article

Due to the influence of the complex underwater environment, the sound speed constantly changes, resulting in the acoustic signal propagation trajectory being curved, which greatly affects the positioning accuracy of the underwater long baseline (LBL) system. In this paper, an improved LBL positioning method based on a B-spline surface for fitting the effective sound speed table (ESST) is proposed. Firstly, according to the underwater sound speed profile, the discrete ESST of each measurement station is constructed before the positioning test, and then, the node position of the B-spline surface is optimized by particle swarm optimization (PSO) to accurately fit the discrete ESST. Based on this, the improved LBL positioning method is constructed. In the underwater positioning test, the effective sound speed can be quickly found by measuring the time of arrival (TOA) of the acoustic signal and the target depth, and moreover, the target position parameters can be quickly and accurately estimated. The numerical simulation results show that the improved positioning method proposed in this paper can effectively improve the LBL positioning accuracy and provide the theoretical basis and the technical support for the underwater navigation and positioning. Full article

In recent years, the frequency of forced oscillation events due to control system malfunctions or improper parameter settings has increased. Tuning the parameters of exciters and governor models is crucial for maintaining power system stability. Traditional simulation studies typically involve small transient disturbances or step changes to find optimal parameter sets, but existing optimization algorithms often fall short in fine-tuning for forced oscillations. Identifying the sensitive parameters within these control models is essential for ensuring stability during large, sustained disturbances. This study focuses on identifying these critical exciter and governor model parameters by analyzing their influence on sustained forced oscillations. Using Kundur’s two-area system, we analyze common exciter models such as SCRX, ESST1A, and AC7B, along with governor models like GAST, HYGOV, and GGOV1, utilizing PSS^®E software version 34. Sustained forced oscillations are injected at generator-1 of area-1, with individual parameter changes dynamically simulated. By considering a local oscillation frequency of 1.4 Hz and an inter-area oscillation mode of 0.25 Hz, we analyze the impact of each parameter change on the magnitude and frequency of forced oscillations as well as on active and reactive power outputs. This novel approach highlights the most influential parameters of each tested model—such as exciter, governor, and turbine gains, as well as time constant parameters—on the impact of forced oscillations. Based on our findings, the sensitive parameters of each tested model are ranked. These would provide valuable insights for industry operators to fine-tune control settings during oscillation events, ultimately enhancing system stability. Full article

Healing after tooth extraction involves a series of reparative processes affecting both alveolar bone and soft tissues. The aim of the present study was to investigate whether activation of molecular signals during the healing process confers a regenerative advantage to the extraction socket soft tissue (ESsT) at 8 weeks of healing. Compared to subepithelial connective tissue graft (CTG), qRT-PCR analyses revealed a dramatic enrichment of the ESsT in osteogenic differentiation markers. However, ESsT and CTG shared characteristics of nonspecialized soft connective tissue by expressing comparable levels of genes encoding abundant extracellular matrix (ECM) proteins. Genes encoding the transforming growth factor-β1 (TGF-β1) and its receptors were strongly enriched in the CTG, whereas the transcript for the insulin-like growth factor-1 (IGF-1) showed significantly high and comparable expression in both tissues. Mechanical stimulation, by the means of cyclic strain or matrix stiffness applied to primary ESsT cells (ESsT-C) and CTG fibroblasts (CTG-F) extracted from the tissue samples, revealed that stress-induced TGF-β1 not exceeding 2.3 ng/mL, as measured by ELISA, in combination with IGF-1 up to 2.5 ng/mL was able to induce the osteogenic potential of ESsT-Cs. However, stiff matrices (50 kPa), upregulating the TGF-β1 expression up to 6.6 ng/mL, caused downregulation of osteogenic gene expression in the ESsT-Cs. In CTG-Fs, endogenous or stress-induced TGF-β1 ≥ 4.6 ng/mL was likely responsible for the complete lack of osteogenesis. Treatment of ESsT-Cs with TGF-β1 and IGF-1 proved that, at specific concentrations, the two growth factors exhibited either an inductive-synergistic or a suppressive activity, thus determining the osteogenic and mineralization potential of ESsT-Cs. Taken together, our data strongly warrant the clinical exploration of ESsT as a graft in augmentative procedures during dental implant placement surgeries. Full article

Ecosystem services (ESs) are a multiple whole composed of multiple services and their multiple relations, which can be expressed as tensors (multiple functions of multiple vectors). This study attempts to introduce the concept and method of tensors into ES research to solve problems caused by the multiplicity of ESs, such as multiple descriptions and perceptions of ESs, repeated calculation of ES values, and cascading relationships with the social economy. Taking the Manas River Basin composite ecosystem as an example, we constructed five different types of ES tensors based on different understandings and applications: (1) As multiple vectors, three eigenvectors were extracted from the ES state tensor (ESST), including farmland service (FS), vegetation service (VS) and water service (WS). According to the ES response tensor (ESRT), an increase in FS may lead to a decline in overall services. (2) As multiple functions, the ES value (ESV) of the basin was measured by the ESV metric tensor (ESVMT), with a gross value of 14.8 billion USD and a net value of 10.17 billion USD. From different stakeholders perceptions constructed by the ecosystem services to human well-beings (ES-HW) tensor, the human well-being values (HWV) were ranked as citizens > farmers ≈ herdsmen > public. (3) The HWV output efficiency of different LULC per unit of water use was calculated by a fourth-order mixed tensor constructed by water–LULC–ES–HW multiple cascading relations. Among them, the HWV efficiency of water areas and wetlands was the highest, but the area was the smallest. Cultivated land and unused land had the lowest HWV efficiency and largest area. In general, the ES tensor is the extension and integration of the ES scalars/indicators to the ES vectors/bundles, which can provide tools for the integral expression, objective measurement and multiple perceptions of ESs. Full article

Real-time, continuous and accurate blast furnace burden level information is of great significance for controlling the charging process, ensuring a smooth operation of a blast furnace, reducing energy consumption and emissions and improving blast furnace output. However, the burden level information measured by conventional mechanical stock rods and radar probes exhibit problems of weak anti-interference ability, large fluctuations in accuracy, poor stability and discontinuity. Therefore, a space-time fusion prediction and detection method of burden level based on a long-term focus memory network (LFMN) and an efficient structure self-tuning RBF neural network (ESST-RBFNN) is proposed. First, the space dimensional features are extracted by the space regression model based on radar data. Then, the LFMN is designed to predict the burden level and extract the time dimensional features. Finally, the ESST-RBFNN based on a proposed fast eigenvector space clustering algorithm (ESC) is constructed to obtain reliable and continuous burden level information with high accuracy. Both the simulation results and industrial verification indicate that the proposed method can provide real-time and continuous burden level information in real-time, which has great practical value for industrial production. Full article