Search Results (19)

Background and Objective: Temperature management is key for reliable operation of permanent magnet synchronous motors (PMSMs). The lumped-parameter thermal network (LPTN) is fast and interpretable but struggles with nonlinear behavior under high power density. We propose OLTEM, a physics-informed deep model that combines LPTN with a thermal neural network (TNN) to improve prediction accuracy while keeping physical meaning. Methods: OLTEM embeds LPTN into a recurrent state-space formulation and learns three parameter sets: thermal conductance, inverse thermal capacitance, and power loss. Two additions are introduced: (i) a state-conditioned squeeze-and-excitation (SC-SE) attention that adapts feature weights using the current temperature state, and (ii) an enhanced power-loss sub-network that uses a deep MLP with SC-SE and non-negativity constraints. The model is trained and evaluated on the public Electric Motor Temperature dataset (Paderborn University/Kaggle). Performance is measured by mean squared error (MSE) and maximum absolute error across permanent-magnet, stator-yoke, stator-tooth, and stator-winding temperatures. Results: OLTEM tracks fast thermal transients and yields lower MSE than both the baseline TNN and a CNN–RNN model for all four components. On a held-out generalization set, MSE remains below 4.0 °C² and the maximum absolute error is about 4.3–8.2 °C. Ablation shows that removing either SC-SE or the enhanced power-loss module degrades accuracy, confirming their complementary roles. Conclusions: By combining physics with learned attention and loss modeling, OLTEM improves PMSM temperature prediction while preserving interpretability. This approach can support motor thermal design and control; future work will study transfer to other machines and further reduce short-term errors during abrupt operating changes. Full article

In an optomechanical system (OMS), the dynamics of quantum correlations, e.g., quantum discord, can witness synchronized squeezing between the cavity and mechanical modes. We investigate an OMS driven by two coherent fields, and demonstrate that optimal quantum correlations and squeezing synchronization can be achieved by carefully tuning key parameters: the cavity-laser detunings, loss rates, and the effective coupling ratio between the optomechanical interaction and the amplitude drive. By employing the steady-state solution of the covariance matrix within the Lyapunov framework, we identify the conditions under which squeezing becomes stabilized. Furthermore, we demonstrate that synchronized squeezing of the cavity and mechanical modes can be effectively controlled by tuning the loss ratio between the cavity and mechanical subsystems. Alternatively, in the case where the cavity is driven by a single field, we demonstrate that synchronized squeezing in the conjugate quadratures of the cavity and mechanical modes can still be achieved, provided that the cavity is coupled to a squeezed reservoir. The presence of this engineered reservoir compensates the absent driving field, by injecting directional quantum noise, thereby enabling the emergence of steady-state squeezing correlations between the two modes. A critical aspect of our study reveals how the interplay between dissipative and driven-dispersive squeezing mechanisms governs the system’s bandwidth and robustness against decoherence. Our findings provide a versatile framework for manipulating quantum correlations and squeezing in OMS, with applications in quantum metrology, sensing, and the engineering of nonclassical states. This work advances the understanding of squeezing synchronization and offers new strategies for enhancing quantum-coherent phenomena in dissipative environments. Full article

Sleep apnea, characterized by its high prevalence and serious health consequences, faces a critical bottleneck in diagnosis. Polysomnography (PSG), the gold standard, is costly and cumbersome, while wearable devices struggle with quality control and patient compliance, rendering them as unsuitable for both large-scale screening and continuous monitoring. To address these challenges, this research introduces a contactless, low-cost, and accurate event-level sleep apnea detection method leveraging frequency-modulated continuous-wave (FMCW) radar technology. The core of our approach is a novel deep-learning model, built upon the U-Net architecture and augmented with self-attention mechanisms and squeeze-and-excitation (SE) modules, meticulously designed for the precise event-level segmentation of sleep apnea from FMCW radar signals. Crucially, we integrate blood oxygen saturation (SpO₂) prediction as an auxiliary task within a multitask-learning framework to enhance the model’s feature extraction capabilities and clinical utility by capturing physiological correlations between apnea events and oxygen levels. Rigorous evaluation in a clinical dataset, comprising data from 35 participants, with synchronized PSG and radar data demonstrated a performance exceeding that of the baseline methods (Base U-Net and CNN–MHA), achieving a high level of accuracy in event-level segmentation (with an F1-score of 0.8019) and OSA severity grading (91.43%). These findings underscore the significant potential of our radar-based event-level detection system as a non-contact, low-cost, and accurate solution for OSA assessment. This technology offers a promising avenue for transforming sleep apnea diagnosis, making large-scale screening and continuous home monitoring a practical reality and ultimately leading to improved patient outcomes and public health impacts. Full article

In ship propulsion, accurately diagnosing faults in permanent magnet synchronous motor is essential but challenging due to limitations in the intuitive characterization and feature extraction of fault signals. This study presents an innovative approach to motor fault detection by integrating phase-contrastive current dot patterns with an enhanced residual network, enhancing the diagnostic effect. Initially, the research involves creating a dataset that simulates stator currents. It is achieved through mathematical modeling of two common faults in permanent magnet synchronous motors: inter-turn short circuits and demagnetization. Subsequently, the parameters of the phase-contrastive current dot pattern are optimized using the Hunter-Prey Optimization technique to convert the three-phase stator currents of the motor into grayscale images. Lastly, a residual network, which includes a Squeeze-and-Excitation module, is engineered to boost the identification of crucial fault characteristics. The experimental results show that the proposed method achieves a high accuracy rate of 98.5% in the fault diagnosis task of motors, which can accurately identify the fault information and is significant in enhancing the reliability and safety of ship propulsion systems. Full article

Speech-driven lip synchronization is a crucial technology for generating realistic facial animations, with broad application prospects in virtual reality, education, training, and other fields. However, existing methods still face challenges in generating high-fidelity facial animations, particularly in addressing lip jitter and facial motion instability issues in continuous frame sequences. This study presents VividWav2Lip, an improved speech-driven lip synchronization model. Our model incorporates three key innovations: a cross-attention mechanism for enhanced audio-visual feature fusion, an optimized network structure with Squeeze-and-Excitation (SE) residual blocks, and the integration of the CodeFormer facial restoration network for post-processing. Extensive experiments were conducted on a diverse dataset comprising multiple languages and facial types. Quantitative evaluations demonstrate that VividWav2Lip outperforms the baseline Wav2Lip model by 5% in lip sync accuracy and image generation quality, with even more significant improvements over other mainstream methods. In subjective assessments, 85% of participants perceived VividWav2Lip-generated animations as more realistic compared to those produced by existing techniques. Additional experiments reveal our model’s robust cross-lingual performance, maintaining consistent quality even for languages not included in the training set. This study not only advances the theoretical foundations of audio-driven lip synchronization but also offers a practical solution for high-fidelity, multilingual dynamic face generation, with potential applications spanning virtual assistants, video dubbing, and personalized content creation. Full article

Background: Esophageal self-expandable metal stents (SEMS) are an important endoscopic tool. These stents have now been adapted successfully to manage post-bariatric surgery complications such as anastomotic leaks and strictures. In centers of expertise, this has become the primary standard-of-care treatment given its minimally invasive nature, and that it results in early oral feeding, decreased hospitalization, and overall favorable outcomes. Self-expandable metal stents (SEMS) fractures are a rare complication of unknown etiology. We aimed to investigate possible causes of SEMS fractures and highlight a unique endoscopic approach utilized to manage a fractured and impaled SEMS. Methods: This is a retrospective study of consecutive patients who underwent esophageal SEMS placement between 2015–2021 at a tertiary referral center to identify fractured SEMS. Patient demographics, stent characteristics, and possible etiologies of fractured SEMS were identified. A comprehensive literature review was also conducted to evaluate all prior cases of fractured SEMS and to hypothesize fracture theories. Results: There were seven fractured esophageal SEMS, of which six were used to manage post-bariatric surgery complications. Five SEMS were deployed with their distal ends in the gastric antrum and proximal ends in the distal esophagus. All stents fractured within 9 weeks of deployment. Most stents (5/7) were at least 10 cm in length with fractures commonly occurring in the distal third of the stents (6/7). The wires of a fractured SEMS were embedded within the esophagogastric junction in one case, prompting the use of an overtube that was synchronously advanced while steadily extracting the stent. Discussion: We suggest the following four etiologies of SEMS fractures: anatomical, physiological, mechanical, and chemical. Stent curvature at the stomach incisura can lead to strain- and stress-related fatigue due to mechanical bending with exacerbation from respiratory movements. Physiologic factors (gastric body contractions) can result in repetitive squeezing of the stent, adding to metal fatigue. Intrinsic properties (long length and low axial force) may be contributing factors. Lastly, the stomach acidic environment may cause nitinol-induced chemical weakness. Despite the aforementioned theories, SEMS fracture etiology remains unclear. Until more data become available, it may be advisable to remove these stents within 6 weeks. Full article

We present a systematic study on the effects of dynamical transfer and steady-state synchronization of quantum states in a hybrid optomechanical network consisting of two cavities, which carry atoms inside and interact via a common moving mirror such as the mechanical oscillator. It is found that a high fidelity transfer of Schrödinger’s cat and squeezed states between two cavities modes is possible. On the other hand, we demonstrate the synchronization effect of the cavity modes in a steady squeezed state with its high fidelity realized by the mechanical oscillator that intermediates the generation, transfer and stabilization of the squeezing. In this framework, we also study the generation and evolution of bipartite and tripartite entanglement and find its connection to the effects of quantum state transfer and synchronization. Particularly, when the transfer occurs at the maximal fidelity, any entanglement is almost zero, so the different cavity modes are disentangled. However, these modes become entangled when the two bosonic modes are synchronized in a stationary squeezed state. The results provided by the current study may find applications in quantum information technologies, in addition to the setups for metrology, where squeezed states are essential. Full article

The large number of photovoltaics connected to the distribution network via power electronic converters squeezes the functional space of traditional synchronous generators in the power system and reduces the inertia of the network itself. However, due to the random and fluctuating nature of PV power generation, different types of meteorological conditions can also affect the inertia support capability of PV output power. Therefore, this paper proposes a frequency regulation control strategy based on the dynamic characteristics of the grid-side DC capacitor. Firstly, the control strategy of the grid-side inverter is improved and the mechanism of the frequency dynamic response model under PV penetration is analysed. Secondly, data from different weather types are correlated and analysed to predict PV power, and wireless sensor technology is used to introduce the data signals into the control link. Finally, a simulation model of a two-stage PV power generation system is developed and the fast-response capability of the system under different control parameters when the load is increased or decreased is analysed. The results show that under the proposed frequency regulation strategy, the larger the regulation coefficient and virtual inertia time constant, the greater the virtual inertia provided by the PV power generation, which improves the stability of the distribution network. Full article

The article deals with the computational study of the rigid rotor coupled with squeeze film dampers. Various techniques such as the method of computation of the synchronous response with a circular centred orbit, the harmonic balance method, and the direct time integration method are used to analyse the nonlinear behaviour of the rotor system. The results indicate that the rotor system can exhibit both a synchronous circular response with a large orbit radius and a nonsynchronous response with a quasiperiodic character. However, both responses are undesirable in rotating machinery and should be avoided. The new results are presented to provide insight into the impact of initial conditions on the vibration response via basins of attraction. The simulations show that: (i) the basins of attraction are more sensitive to the choice of the initial velocities than displacements, (ii) the basins of attraction are noticeably dependent on the rotor speed in the region of a nonsynchronous response, and (iii) the border between the basins of attraction can be smooth or without a clear structure. The research brings clear conditions defined by parameters such as the dimensionless SFD constant, unbalance, and rotational speed for the suppression of undesirable nonlinear phenomena. The results suggest that the damper can effectively improve the vibration response of high-speed rotating machinery, but its design must be chosen appropriately. Full article

Aim: Healthcare administrative databases represent a valuable source for real-life data analysis. The primary aim of this study is to compare effectiveness and cost profile in non-small-cell lung cancer (NSCLC) patients harboring synchronous brain metastases (BMs) who received non-chemo first-line systemic therapy with or without advanced radiotherapy (aRT). Methods: Diagnostic ICD-9-CM codes were used for identifying all patients with a new diagnosis of lung cancer between 2012 and 2019. Among these, patients who had started a first-line systemic treatment with either TKIs or pembrolizumab, alone or in combination with intensity-modulated or stereotactic RT, were selected. Clinical outcomes investigated included overall survival (OS), progression-free survival (PFS), and time-to-treatment failure (TTF). The cost outcome was defined as the average per capita cumulative healthcare direct costs of the treatment, including all inpatient and outpatient costs. Results: The final cohort included 177 patients, of whom 58 were treated with systemic treatment plus aRT (STRT) and 119 with systemic treatment alone. The addition of aRT to systemic treatment was associated with a significantly better OS (p = 0.020) and PFS (p = 0.041) than systemic therapy alone. The ICER (incremental cost-effectiveness ratio) value indicated an average cost of €3792 for each month of survival after STRT treatment and confirmed clinical effectiveness but higher healthcare costs. Conclusions: This real-world study suggests that upfront aRT for NCLSC patients with synchronous BMs represents a valid treatment strategy, boosting the efficacy of novel and emerging drug classes with sustainable costs for the health service. Translational relevance: The present real-world study reports that the use of upfront advanced radiotherapyaRT and new-generation systemic agents, such as TKIs and pembrolizumab, may have higher oncological control and an improved cost-effectiveness profile than the use of new-generation systemic agents alone in NCLSC patients with synchronous brain metastases. Acquired evidence can also be used to inform policymakers that adding advanced radiotherapy results is a sustainable cost for the health service. Since approximately 50% of patients do not meet RCT inclusion criteria, a significant proportion of them is receiving treatment that is not evidence-informed; therefore, these results warrant further studies to identify the best radiotherapy timing and possible dose escalation approaches to improving treatment efficacy in patient subgroups not typically represented in randomized controlled trials. Full article

This study addresses any sensor based on measuring a physical quantity through the phase of a probing beam. This includes sensing of rotation, acceleration, index change, displacement, fields… While most phase measurements are made by detecting an amplitude change in interfering beams, we detect instead a phase change through a relative frequency shift of two correlated frequency combs. This paper explores the limit sensitivity that this method can achieve, when the combs are generated in an Optical Parametric Oscillator (OPO), pumped synchronously by a train of femtosecond pulses separated by half the OPO cavity round-trip time. It is shown that a phase difference as small as 0.4 nanoradians can be resolved between the two pulses circulating in the cavity. This phase difference is one order of magnitude better than the previous record. The root-mean-square deviation of the measured phase over measuring time is close to the standard quantum limit (phase-photon number uncertainty product of 0.66). Innovations that made such improved performances possible include a more stable OPO cavity design; a stabilization system with a novel purely electronic locking of the OPO cavity length relative to that of the pump laser; a shorter pump laser cavity; and a square pulse generator for driving a 0.5 mm pathlength lithium niobate phase modulator. Future data acquisition improvements are suggested that will bring the phase sensitivity exactly to the standard quantum limit, and beyond the quantum limit by squeezing. Full article

Wireless sensor networks usually suffer from the issue of time synchronization discrepancy due to environmental effects or clock management collapse. This will result in time delays between the dynamic responses collected by wireless sensors. If non-synchronized dynamic response data are directly used for structural modal identification, it leads to the misestimation of modal parameters. To overcome the non-synchronization issue, this study proposes a time synchronization approach to detect and correct asynchronous dynamic responses based on frequency domain decomposition (FDD) with frequency-squeezing processing (FSP). By imposing the expected relationship between modal phase angles extracted from the first-order singular value spectrum, the time lags between different sensors can be estimated, and synchronization can be achieved. The effectiveness of the proposed approach is fully demonstrated by numerical and experimental studies, as well as field measurement of a large-span spatial structure. The results verify that the proposed approach is effective for the time synchronization of wireless accelerometer sensors. Full article

Global warming and environmental changes have resulted in more frequent and extreme weather events, as well as larger-scale disasters around the world. This study presents a disaster risk analysis in Taiwan coastal area using the Climate Disaster Resilience Index (CDRI) and examines the strategies adopted by the coastal residents of Taiwan, through a new concept of “copability” analysis. Based on the results, the majority of the coastal regions fall under the medium-to-low resilient category with the south-western and northern coast of Taiwan as the most high-risk regions posing a high risk to millions of people facing climatic disasters in the future. The coping mechanisms used by local residents are also influenced by the socioeconomic status of the decision-makers as well as the synchronization of disasters. Based on the findings, a 4R management package is developed in which the copability and resilience management strategy are squeezed into four main sectors of resource, reason, roadmap, and respond to work towards a more coordinated management and use of natural resources across sectors and scales. It is advised that all governmental, private, and community actors implement coherent climate risk management measures, accompanied by mitigation initiatives, in order to establish a sustainable level of climate resilience in cities. Full article

The polyphase structural evolution of a sector of the internal Central Apennines, where the significance of pelagic deposits atop neritic carbonate platform and active margin sediments has been long debated, is here documented. The results of a new geological survey in the Volsci Range, supported by new stratigraphic constraints from the syn-orogenic deposits, are integrated with the analysis of 2D seismic reflection lines and available wells in the adjacent Latin Valley. Late Cretaceous syn-sedimentary faults are documented and interpreted as steps linking a carbonate platform to the adjacent pelagic basin, located to the west. During Tortonian time, the pelagic deposits were squeezed off and juxtaposed as mélange units on top of the carbonate platform. Subsurface data highlighted stacked thrust sheets that were first involved into an initial in-sequence propagation with top-to-the-ENE, synchronous to late Tortonian foredeep to wedge-top sedimentation. We distinguish up to four groups of thrust faults that occurred during in-sequence shortening (thrusts 1–3; about 55–60 km) and backthrusting (thrust 4). During Pliocene to recent times, the area has been uplifted and subsequently extended by normal faults cross-cutting the accretionary wedge. Beside regional interest, our findings bear implications on the kinematic evolution of an orogenic wedge affected by far-traveled units. Full article

Background: advanced paraclinical approaches using functional neuroimaging and electroencephalography (EEG) allow identifying patients who are covertly aware despite being diagnosed as unresponsive wakefulness syndrome (UWS). Bedside detection of covert awareness employing motor imagery tasks (MI), which is a universally accepted clinical indicator of awareness in the absence of overt behavior, may miss some of these patients, as they could still have a certain level of awareness. We aimed at assessing covert awareness in patients with UWS using a visuomotor-guided motor imagery task (VMI) during EEG recording. Methods: nine patients in a minimally conscious state (MCS), 11 patients in a UWS, and 15 healthy individuals (control group—CG) were provided with an VMI (imagine dancing while watching a group dance video to command), a simple-MI (imagine squeezing their right hand to command), and an advanced-MI (imagine dancing without watching a group dance video to command) to detect command-following. We analyzed the command-specific EEG responses (event-related synchronization/desynchronization—ERS/ERD) of each patient, assessing whether these responses were appropriate, consistent, and statistically similar to those elicited in the CG, as reliable markers of motor imagery. Results: All patients in MCS, all healthy individuals and one patient in UWS repeatedly and reliably generated appropriate EEG responses to distinct commands of motor imagery with a classification accuracy of 60–80%. Conclusions: VMI outperformed significantly MI tasks. Therefore, patients in UWS may be still misdiagnosed despite a rigorous clinical assessment and an appropriate MI assessment. It is thus possible to suggest that motor imagery tasks should be delivered to patients with chronic disorders of consciousness in visuomotor-aided modality (also in the rehabilitation setting) to greatly entrain patient’s participation. In this regard, the EEG approach we described has the clear advantage of being cheap, portable, widely available, and objective. It may be thus considered as, at least, a screening tool to identify the patients who deserve further, advanced paraclinical approaches. Full article