The aim of this study is to investigate transient dynamic flow characteristics of the fluid flow through 5-way electric coolant valve (PCCV : Penta-Control Coolant Valve). To achieve this goal, the present paper attempts the three-dimensional dynamic simulation of the fluid flow through the valve using a commercial CFD solver with moving mesh technique to consider flow inertia and dynamic flow in the opening and closing stages of the ball valve rotating motion. Firstly, dynamic flow characteristics and the thermal mixing inside the PCCV ball valve during the opening and closing stage was analyzed. It is found that the discrepancies between dynamic and steady state simulation is remarkable when fluxes with different levels of enthalpy and momentum flow into the PCCV leads to strong flow interference and flow inertia, while the discrepancies are relatively small at low rotation speed and weak flow interference. Then, the effect of dynamic flow characteristics of the valve on dynamic thermal mixing characteristics at two different ball valve rotational speeds and rotational directions were investigated. It was found that the dynamic flow and thermal mixing characteristics inside the PCCV are greatly affected by the rotation speed, rotation direction, and degree of flow interference between fluxes. It is helpful for the design of the better coolant control strategies and the improvement of the FCEV thermal management system.

Coal gasification with carbon dioxide is a process for generating clean gaseous fuels and relieving greenhouse effect. Zhundong coal has high alkali and alkali earth metals (AAEMs) content, medium volatile and low ash in nature. Isothermal CO₂ gasification of char derived from Zhundong coal (R-char) and char from acid washing R-char (AR-char) are performed in thermo-gravimetric analyzer (TGA). The effect of AAEMs is investigated on the gasification behavior in the range of temperatures 1073 K to 1273 K. The carbon conversion increases rapidly with increasing reaction temperature and CO₂ concentration. R-char has high gasification rate and carbon conversion compared with AR-char. The accuracy of the free-model approach for calculating activation energy at different conversions is validated by compared with different kinetic models (volume reaction model, distributed activation energy model). Moreover, R-char gasification with CO₂ shows a compensation effect as the Arrhenius parameters (EA and k0) increase or decrease simultaneously.

Three kinds of inorganic alkali are introduced into tetraethylenepentamine (TPEA) and polyethyleneimine (PEI) modified MCM-41 as the CO2 adsorbents. FT-IR and TGA are used to characterize the surface groups and the thermal stability of adsorbents. Chemical titration method is used to measure the alkali amounts of adsorbents. Thermo-gravimetric analysis with 10%CO2/N2 as the simulated flue gas is used to test the CO2 adsorption performance of adsorbents. The results show that all three kinds of inorganic alkali containing adsorbents exhibit promoted CO2 adsorption capability than traditional TPEA and PEI modified samples. Ca(OH)2 and PEI modified samples exhibit the highest adsorption capacity and stable regeneration property. The introduction of inorganic alkali changes the chemical adsorption mechanism between CO2 and increases the effective alkali amounts due to its hydroxyl groups. The CO2 adsorption capacities have a linear dependence relation with the alkali amounts of adsorbents, indicating that alkali amount is a critical factor for novel adsorbents exploring.

Background: This study aimed to identify the association between occupational stress and depression-well-being by proposing a comprehensive and flexible job burden-capital model with its corresponding hypotheses. Methods: For this research, 1618 valid samples were gathered from the electronic manufacturing service industry in Hunan Province, China; self-rated questionnaires were administered to participants for data collection after obtaining their written consent. The proposed model was fitted and tested through structural equation model analysis. Results: Single-factor correlation analysis results indicated that coefficients between all items and dimensions had statistical significance. The final model demonstrated satisfactory global goodness of fit (CMIN/DF=5.37, AGFI=0.915, NNFI=0.945, IFI=0.952, RMSEA=0.052). Both the measurement and structural models showed acceptable path loadings. Job burden and capital were directly associated with depression and well-being or indirectly related to them through personality. Multi-group structural equation model analyses indicated general applicability of the proposed model to basic features of such a population. Gender, marriage and education led to differences in the relation between occupational stress and health outcomes. Conclusions: The job burden-capital model of occupational stress-depression and well-being was found to be more systematic and comprehensive than previous models.

With the development of higher voltage power grid, the high and low voltage parallel loops are emerging, which lead to energy losses, even threaten the security and stability of power system. The multi-infeed HVDC configurations widely appearing in AC/DC interconnected power system make this situation even worse. Aimed at energy saving and system security, a decision optimization method for power grid operating condition with high and low voltage parallel loops is proposed in this paper. Firstly, considering hub substation distribution and power grid structure, parallel loop opening schemes are generated with GN algorithm. Then, candidate opening schemes are preliminarily selected from all these generated schemes based on a filtering index. Finally, with the influence on power system security, stability and operation economy in consideration, an evaluation model for candidate opening schemes is founded based on analytic hierarchy process (AHP). And a fuzzy evaluation algorithm is used to find the optimal scheme. Simulation results of New England 39-bus system and an actual power system validate the effectiveness and superiority of this proposed method.

In March 2013, a novel avian influenza A H7N9 virus was emerged in China, which cause rapidly progressive pneumonia and with a high fatality rate. Serologic studies to evaluate neutralizing antibodies of infected patients and birds are invaluable tools for immunogenicity research of H7N9 and epidemiological investigation. Conventional neutralization assays are laborious and time-consuming which also hampered by biosafety requirement. In this study, We construct and produce pseudovirus bearing the full-length hemagglutinin (HA) of H7N9 virus in the Env-defective, luciferase-expressing HIV-1 backbone. The production of lentiviral pseudovirus was analysed by HA gene specific real-time reverse-transcription PCR, transmission electron microscopy (TEM), and Western Blot assay to prove the nucleic acid replication, the morphology of virus, and the expression of HA protein in pseudovirus. After that pseudovirus based inhibition assay was established to detect neutralizing antibodies of a panel of serum samples. Our results demonstrated that H7N9 pseudovirus which had single-cycle infection was generated. By comparing the neutralization antibody titers, pseudovirus based neutralization test could be recognized as an alternative of conventional microneutralization (MN). Hence, we conclude that it is possible to use pseudovirus inhibition assay to screen sera samples, as well as evaluate vaccine-induced neutralizing antibodies against H7N9 virus.

In pattern recognition domain, deep architectures are widely used nowadays and they have achieved fine grades. However, these deep architectures need special demands, especially big datasets and GPU. Aiming to gain better grades without deep networks, we propose a simplified algorithm framework using fusion features extracted from the salient areas of faces. Furthermore, the proposed algorithm has achieved a better result than some deep architectures. For extracting more effective features, this paper firstly defines the salient areas on the faces. This paper normalizes the salient areas of the same location in the faces to the same size, therefore it can gain more similar features from different subjects. LBP and HOG features are extracted from the salient areas, fusion features’ dimensions are reduced by Principal Component Analysis( PCA) and we apply softmax to classify the six basic expressions at once. This paper proposes a salient areas definitude method which uses peak expressions frames to compare with their neutral faces. This paper also proposes and applies the idea of normalizing the salient areas to align the specific areas which express the different expressions. This makes the salient areas found from different subjects have the same size. Besides, gamma correction method is firstly applied on LBP features in our algorithm framework which improves our recognition rates significantly. By applying this algorithm framework, our research has gained state-of-the-art performances on CK+ database and JAFFE database.

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s.

Reliability assessment is an important component and tool used for process plants since the facility consists of many loops and instruments attached and operates based on each other availability, thus it requires a statistical method to visualize the reliability. The paper focuses on reliability assessment and prediction based on available statistical models such as normal, log-normal, exponential, and Weibull distribution. This paper also visualizes, which model fits best for assessment and prediction and also considers failure modes caused during a simulation mode process control operation. A simulation model is designed in this paper to observe the failure of the control valve causing stiction to visualize the failure modes and predict the best-fit model for reliability assessment.

Multimodal remote sensing data classification can enhance the model’s ability to distinguish land features through multimodal data fusion. In this context, how to help models understand the relationship between multimodal data and target tasks is the focus of researchers. Inspired by human feedback learning mechanisms, causal reasoning mechanisms, and knowledge induction mechanisms, this paper integrates causal learning, reinforcement learning, and meta learning into a unified remote sensing data classification framework and proposed the causal meta-reinforcement learning (CMRL). First, based on feedback learning mechanisms, we have overcome the limitations of traditional implicit optimization of fusion features and customized a reinforcement learning environment for multimodal remote sensing data classification tasks. Through feedback interactive learning between agents and the environment, we help them understand the complex relationships between multimodal data and labels, thereby achieving full mining of multimodal complementary information. Second, based on the causal inference mechanism we designed causal distribution prediction action, classification reward, and causal intervention reward, capturing pure causal factors in multimodal data and cutting off false statistical associations between non-causal factors and class labels. Finally, based on the knowledge induction mechanism, we designed a bi-layer optimization mechanism based on meta-learning. By constructing a meta training task and meta validation task simulation model in the generalization scenario of unseen data, we helped the model induce cross-task shared knowledge, thereby improving its generalization ability for unseen multimodal data. The experimental results on multiple sets of multimodal datasets show that the proposed method achieved state-of-the-art performance in multimodal remote sensing data classification tasks.

Classifying network flow subsequences in an Industrial IoT gateway is an effective method for identifying Industrial IoT faults. This paper proposes a subsequence classification algorithm SSGBUL-IKNN based on unsupervised learning encoding to address the problem of low classification accuracy. Firstly, we built a network module based on unsupervised learning to encode the flow sequence of the Industrial IoT gateway. In the encoding module, a subsequence calibration algorithm controls the increasing error during the coding process. Then, the specific fault type is obtained through an improved KNN classification algorithm based on the indication distance source from the integrated coding sequences converted by multi-dimensional network flow sequences. The test result on three Industrial IoT datasets of a sewage treatment plant shows that the accuracy of SSGBUL-IKNN in this paper exceeds 92%, significantly higher than the algorithm DTW and TSF. It reaches the classification requirements of Industrial IoT fault diagnosis.

The paper presents an error model of a measurement chain containing link performing discrete wavelet transform algorithm which is most often the last stage of measurement signal processing. The goal is to determine the uncertainty budget of the input quantities of the wavelet transform algorithm. The error model takes into account parts of analog, analog-to-digital and digital processing, describing the properties of subsequent fragments of the chain using their transmittance and processing functions. The proposed model enables the description of both deterministic and non-deterministic properties of signal errors. The proposed model was validated using an example measurement chain created for this purpose.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

This study was conducted to develop a PID control algorithm considering viscosity for the planting depth control system of a rice transplanter using various hydraulic oils at different temperatures and to evaluate the performance of the control algorithm, and compare the performance of the PID control algorithm without considering viscosity and considering viscosity. In this study, the simulation model of the planting depth control system and a PID control algorithm were developed based on the power flow of the rice transplanter (ERP60DS). The primary PID coefficients were determined using the Ziegler–Nichols (Z–N) second method. Routh’s stability criteria were applied to optimize the coefficients. The pole and double zero points of the PID controller were also applied to minimize the sustained oscillations of the responses. The performance of the PID control algorithm was evaluated for three ISO (The International Organization for Standardization) standard viscosity grade (VG) hydraulic oils (VG 32, 46, and 68). The results show that the control algorithm considering viscosity is able to control the pressure of the proportional valve, which is associated with the actuator displacement for various types of hydraulic oils. It was noticed that the maximum pressure was 15.405 bars at 0, 20, 40, 60, 80, and 100 ℃ for all of the hydraulic oils. The settling time and steady-state errors were 0.45 s at 100 ℃ for VG 32, and 0% for all of the conditions. The maximum overshoots were found to be 17.50% at 100 ℃ for VG 32. On the other hand, the PID control algorithm without considering viscosity could not control the planting depth, because the response was slow and did not satisfy the boundary conditions. The PID control algorithm considering viscosity could sufficiently compensate for the nonlinearity of the hydraulic system and was able to perform for any of temperature-dependent viscosity of the hydraulic oils. In addition, the rice transplanter requires a faster response for accurately controlling and maintaining the planting depth. Planting depth is highly associated with actuator displacement. Finally, this control algorithm considering viscosity could be helpful in minimizing the tilting of the seedlings planted using the rice transplanter. Ultimately, it would improve the transplanter performance.

Meningitis is a severe disease associated with death in children under five with highest rates of infections under age of one. Vaccines for Neisseria meningitides and Haemophilus influenza are used to prevent the main causative agents of meningitis. Administration of H. influenzae type b (Hib) vaccine is recommended at 2, 4 and 6 months with a booster dose at 18 months. N. meningitidis has two commercially available vaccines, the pure polysaccharide is recommended at 24 months meanwhile the protein-conjugated vaccines at 12 months. We sought in this study to examine if coadministering the vaccines for the two main meningitis causing bacteria might be synergistic as a preliminary step towards the possibility of shuffling immunization schedule. So, we coadministered Hib vaccine with commercially available vaccines either quadrate (ACWY) polysaccharide meningococcal (Men) or conjugated meningococcal (Nim) vaccines in Balb/C mice (n = 6/group) and compared to each vaccine administered separately and controls. Thirty-five days post immunization, we measured specific antibodies titers. Hib vaccine increased Men antibody titers significantly for serotypes Y and W. When Hib vaccine was coadministrated with Nim, antibody titer for Y, W and A significantly increased. For serotype C, there was no significant difference in antibody titers among immunized groups. As for effect of meningococcal vaccines on Hib, Men significantly increased Hib antibody titers while Nim had no effect. Collectively, our data suggested that coadministration of Hib and Men or Nim vaccines was safe and had synergistic effect on immune responses elicited to both vaccines. Further studies are needed before immunization schedule modifications. Such immunization schedule recommendation should provide better protection against this life-threatening disease in young children.

The numerical implementation of the controllers allows the use of very complex algorithms with ease. However, in practice, due to its proven advantages, the PID controller (and its variants) is widely used in industrial control systems as well as in many other applications that require continuous control. Most of the methods for tuning the parameters of PID controllers are based on time-invariant linear models of the processes, which in practice can lead to poor performance of the control system. The paper presents an application of reinforcement learning algorithms in tuning of PID controllers for the control of some classes of continuous nonlinear systems. Tuning the parameters of PID controllers is done with the help of Twin Delayed Deep Deterministic Policy Gradients (TD3) algorithm which presents a series of advantages compared to other similar methods from Machine Learning dedicated to continuous state and action spaces. TD3 algorithm is an off-policy Actor-Critic based method and was used as it does not require a system model. The presented technique is applied for control of a biotechnological system which has a strongly nonlinear dynamic. The proposed tuning method is compared to the classical tuning methods of PID controllers. The performance of the tuning method based on the TD3 algorithm is demonstrated through simulation illustrating the effectiveness of the proposed methodology.

The increasing availability of longitudinal data (repeated numerical observations of same units at different times) requires the development of flexible techniques to automatically detect common errors in such data. Besides obvious and easily identifiable cases, such as missing or out-of-range data, large longitudinal dataset often present problems not easily traceable by the techniques used for generic datasets. In particular, elusive and baffling problems are i) inversion of one or more values from one unit to another; ii) anomalous jumps in the series of values, iii) errors in the timing of the values due to a recalculation operated by the data providers to compensate previous errors. This work proposes a statistical-mathematical approach based on a system of indicators that is able to capture the complexity of the described problems by working at the formal level, regardless of the specific meaning of the data. The proposed approach identifies suspect erroneous data and is applicable in a variety of contexts. We implement this approach in a relevant database of European Higher Education institutions (ETER) by analyzing Total academic staff, that is one of the most important variables, used in empirical analysis as proxy of size and also considered by policy makers at European level.

The electroencephalogram (EEG) is a record of brain activity. Brain Computer Interface (BCI) technology formed by the EEG signal has become one of the hotspots at present. How to extract the feature signal of EEG is the most basic research of BCI technology. In this paper, A new method of recognizing fatigue, conscious, concentrated state of human brain is proposed by the combination of discrete wavelet transform and the neural network based on EEG signal. First of all, the law signal is preprocessed by the wavelet denoising method because the law EEG signal contains a large number of high frequency noise, which is decomposed into multi-layer high frequency signal and low frequency signal. thus, δ wave, θ wave, α wave, β wave are obtained by the wavelet transform. And then, frequency band energy of the different wave is regards as the feature signal of EEG. In the experiment, the feature signal is classified by radial basic function (RBF) and annealed chaotic competitive learning network (ACCLN). RBF and ACCLN networks are trained with 500 sets of sample data and are tested by 100 sets of samples in different mental states. The experimental results show that the average accuracy of RBF network under three conditions are 88.75%, 88.25%, 88.5%, respectively, and the correct rate of ACCLN network is 97%, 98%, 98%, respectively.

The attitude dynamics and orbit dynamics of large rigid space structures are coupled with each other under gravity gradient, which may affect the stability of the large rigid space structures. In this paper, the gravity gradient stability of a large rigid space structure is studied under both small and large disturbances. Based on the rigid body dynamics and orbit dynamics, an accurate dynamic model without any linearization of the large rigid space structure is established via the natural coordinate formulation (NCF), which is able to describe the large overall motions of the structures. By using the generalized-α algorithm, the gravity gradient stability of the large rigid space structure is simulated and analyzed via various examples, including the influence of large disturbance angles, the positions at the stabilization and unstabilization regions. Finally, the relationship between spinning stability and gravity gradient stability is also investigated via a large spinning space structure.

Recently, SMR (Small Modular Reactor) is expected to be able to operate flexibly in conjunction with a high renewable energy penetration grid as a result of improved safety and easy power control compared to large nuclear power plants. SMRs such as South Korea’s System-integrated Modular Advanced ReacTor (SMART) are designed to use canned motors (CMs) for their reactor coolant pumps (RCPs) to enhance safety. The CMs passively enhance the reactor’s safety by preventing leakage of radioactive reactor coolant. However, with motor sizes designed to be as small as possible, and the increased air gap of CMs between stator and rotor, starting torque may be insufficiently small compared to that of similar sized induction motors (IMs). Thusly, CMs may require variable frequency drives (VFDs) to start. This paper compares the torque characteristics of CMs with those of IMs for SMART’s RCPs. ETAP is then used to perform motor starting analysis for CMs started with and without VFDs. The results are presented and analyzed to find out if the VFDs deal with the CM starting torque issue.

Background: Redo mitral valve surgery is the standard of care for failed mitral bioprostheses or recurrence of mitral regurgitation after repair. Nonetheless, catheterbased valve-in-valve (ViV) or valve-in-ring (ViR)-procedures increasingly become viable alternatives in high risk subpopula-tions. Despite reported good initial results, only little is known about longer-term outcomes. The present series report long-term outcomes of transcatheter mitral ViV- and ViR-procedures. Methods: All consecutive patients (n=54) undergoing transcatheter mitral ViV- or ViR-procedures for failed bioprostheses or recurring regurgitation after mitral repair were retrospectively en-rolled in the time period between 2011 and 2021. The mean age was 76.5 ± 6.5 years, and 30 (55.6%) of the patients were male. The procedures were done using a commercially available balloon-expandable transcatheter heart valve. Clinical and echocardiographic follow-up data were obtained out of the hospital’s database and analyzed. Follow-up reached up to 9.9 years with a total of 164.3 patient-years. Results: A total 25 patients received a ViV- and 29 patients a ViR-procedure. Both groups were at high surgical risk with an STS-PROM of 5.9 ± 3.7 % in ViV- and 8.7 ± 9.0% in ViR-patients, respectively (p<0.01). The procedures itself were mainly unevent-ful with no intraoperative deaths and a low conversion rate (n=2/54; 3.7%). VARC-2 procedural success was low (ViV 20.0% and ViR 10.3%; p=0.45), which was either driven by high rates of transvalvular pressure gradients “>5mmHg” (ViV 92.0% and ViR 27.6%; p<0.01) or residual regurgitation “>trace” (ViV 28.0% and ViR 82.7%; p<0.01). ICU-stay was prolonged in both groups (ViV 3.8 ± 6.8 days and ViR 4.3 ± 6.3 days; p=0.96) with acceptable hospital stay (ViV 9.9 ± 5.9 days and ViR 13.5 ± 8.0 days; p=0.13). Despite 30-days mortality was acceptable (ViV 4.0% and ViR 6.9%; p=1.00), the mean posthospital survival time was disappointingly low (ViV 3.9 ± 2.6 years and ViR 2.3 ± 2.7 years; p<0.01). Overall survival I the entire group was 33.3%.Cardiac reasons for death were frequent in both groups (ViV 38.5% and ViR 52.2%). Cox-regression analysis identified ViR-procedures as a predictor of mortality (HR 2.36, CI 1.19 - 4.67, p=0.01). Conclusions: Despite acceptable immediate outcomes in this high-risk subpopulation, long-terms results are discouraging. Transvalvular pressure gradients as well as residual regurgitations remained drawbacks in this real-world population. The indication for catheterbased mitral ViV- or ViR-procedures thoughtfully must be made in consideration of conventional redo-surgery or conservative treatment.

This paper proposes a novel single-stage buck-boost three-Level neutral-point-clamped (NPC) inverter with two independent dc sources coupled for the grid-tied photovoltaic (PV) application, which can effectively solve the unbalanced operational conditions generally appeared between two coupled independent PV sources induced by the unequal irradiation and temperature distribution. The proposed control scheme can simultaneously guarantee the maximum power point (MPP) operation of both PV sources and maintain the output waveform quality. Compared to the traditional two-stage PV inverter, the proposed NPC inverter could reduce the PV array voltage requirement and dc-link capacitors’ voltage rating, meanwhile show the advantage in operational efficiency. MATLAB simulations and the captured experimental results are presented to show the performance of the proposed three-level inverter.

Heavy rains have created significant threats to human health and life. Floods and other natural disasters, which have a global impact annually, can be attributed to extended durations of intense precipitation. Accurate rainfall predictions are crucial in nations such as Bangladesh, where agriculture is the predominant occupation. The efficiency of machine learning (ML) methods is enhanced by the non-linearity of rainfall, surpassing the effectiveness of other alternative ways. Machine learning techniques show that individual classifiers exhibit worse accuracy than ensemble learning (EL) methodologies. Ensemble Learning techniques are utilized for rainfall prediction and estimating rainfall quantity and daily average temperature to enhance comprehension of the diverse Machine Learning algorithms. This research implements the machine learning techniques and ensemble-based classifier to predict the rainfall occurrence, along with the machine learning regressor models and ensemble-based regressor for the rainfall amount prediction and daily average temperature prediction, using Bangladesh Weather Dataset. The results of the machine learning and ensemble-based models are compared using the Accuracy and F1 score for rainfall occurrence prediction. In contrast, MAE and RMSE evaluation metrics are used for ensemble regressor and regression algorithms for the rainfall amount and daily average temperature prediction. With an accuracy of 83.41% and a recall of 78.17%, the Ensemble Classifier is the best at predicting when it will rain, but its precision of 51.16% stands in for the lowest. The Ensemble Regression model outperforms Linear Regression, Random Forest, and SVR in rainfall amount prediction, with the lowest MAE of 0.36 and RMSE of 0.90. The Ensemble Regression provides the most precise results for daily average temperature prediction with the lowest MAE 0.42 and RMSE 0.54 highlighting its superiority over the other regression models in forecasting temperature with less error. Ensemble approaches consistently lead task performance metrics.

Unsmooth reversing is one of the most common faults in the four-way reversing valve of air conditioning system, and the airflow in the valve chamber and the shape of the slider of the reversing valve are the main factors in unsmooth reversing. In order to study the influence of the airflow in the chamber and the slider shape on the reversing process, the fluid flow in the valve chamber of a four-way reversing valve is obtained using computational fluid dynamics (CFD) simulations, and the influence of slider structure on slider thrust and resistance of the four-way reversing valve is analyzed. Four-way reversing valves with no-cutting, straight-cutting and arc-cutting sliders are employed to evaluate the reversing characteristics. A pressure measuring device for a four-way reversing valve chamber is designed, which is performed to test the chamber pressure of three different types of sliders of four-way reversing valves. The maximum error of experimental tests and simulations is within 5% of engineering tolerance, so as to verify the reliability of numerical simulation. The results indicate that the chamber pressure and resistance-thrust ratio with the cutting slider are reduced, which is beneficial to the reversing of the four-way reversing valve. Compared with the straight cutting structure, the arc cutting slider four-way reversing valve has a more stable reversing process and better comprehensive reversing performance. The results can provide a theoretical basis for engineers to improve the performance of four-way reversing valves.

Sea cucumber peptides are small molecular peptides with biological function obtained from fresh sea cucumber as feedstock, which were hydrolyzed by protease, separated ,and purified. As the main product of sea cucumber refinement, it more accurately expresses the nutritional effect of sea cucumber and has a wide range of potential applications. It has been demonstrated that sea cucumber has a certain value-added effect on bone mineral density regulation, but the differences in bone mineral density regulation of extracts from different parts of sea cucumber and the techniques contributing to the efficient isolation of bone sea cucumber peptides have not been reported. Firstly, the aim of this study was to reveal the differences in osteogenic activities of enzymatic peptides from three major parts of sea cucumber: the body wall, the egg protein, and the intestinal protein. Then, the bone-enhancing sea cucumber peptides were isolated based on the characteristics of the dif-ferences in molecular weight distribution, hydrophilicity, and ionisation degree of sea cucumber, and to explore the possible mechanisms of their action. The findings indicated that sea cucumber peptides extracted from three distinct sites exhibited a dose-dependent enhancement of osteoblast proliferation and differentiation. Upon evaluating the three methods of sea cucumber peptide separation based on molecular weight distribution, hydrophilicity, and ionization, it was observed that the fraction isolated by hydrophobicity and

Only a handful of microbial mosquito larval pathogens have been described to date. Sampling of several natural enzootic infections of mosquito larvae in southwestern Florida indicated the presence of microbial pathogens capable of extensive larval mortality. Microscopic analysis of one sample site revealed extensive apparent growth of a Pythium-like microbe on mosquito lar-vae, with highest infection observed on the siphon and head regions. Structures consistent with sporangia were seen on infected insects after lactophenol blue staining, and higher resolution scanning electron micrographs (SEM) showed sporangia and encysted zoospores targeting the head and siphon regions. The isolate was single colony purified and molecular identification targeting the ITS and COX1 loci coupled to phylogenetic reconstruction indicated that the isolate belonged to the Pythium genus, but was distinct from its closest characterized species, P. angusta-tum. Morphological features were characterized, with the isolate showing rapid growth on all mycological media tested and relatively high thermotolerance, capable of robust growth at 37oC, and hence was designated, P. thermoculicivorax. Sampling from a second series of natural infec-tions of mosquito larvae resulted in the molecular identification of three Trichoderma isolates, one with high similarity to T. strigosum, and the other two clustering with, but distinct from, T. asperellum. These data highlight the occurrence of natural enzootic infections of mosquito larvae, potentially as a resource for the identification of new mosquito pathogens.

As the adoption of renewable energy sources grows, ensuring a stable power balance across various time frames has become a central challenge for modern power systems. In line with the "dual carbon" objectives and the seamless integration of renewable energy sources, harnessing the advantages of various energy storage resources and coordinating the operation of long-term and short-term storage have become pivotal directions for future energy storage deployment. To address the complexities arising from the coupling of different time scales in optimizing energy storage capacity, this paper proposes a method for energy storage planning that accounts for power imbalance risks across multiple time scales. Initially, the Seasonal and Trend decomposition using the Loess (STL) decomposition method is utilized to temporally decouple actual operational data. Subsequently, power balance computations are performed based on the obtained data at various time scales to optimize the allocation of different types of energy storage capacities and assess the associated imbalance risks. Finally, the effectiveness of the proposed approach is validated through hourly applications using real-world data from a province in China over recent years.

The presence of anti SARS-CoV2-RBD antibody (Anti-RBD) prevents severe COVID-19. We aimed to determine the accuracy of a point-of-care Anti-RBD test implemented in person living with HIV (PLWH), systemic lupus erythematosus (SLE), and chronic kidney disease (CKD). We enrolled 182 non-comorbid subjects and 335 persons with comorbid (PLWH, SLE, CKD) to test anti-RBD assay compared to surrogate viral neutralization (SVNT) as the reference test. We performed linear correlation analysis between anti-RBD vs SVNT and a ROC analyses to ascertain anti-RBD cut-off at 30%, 60%, and 90% inhibition of SVNT to calculate accuracy. Correlations of anti-RBD to SVNT among all groups were excellent with R= 0.7903, R=0.7843, R=0.8153 among non-comorbid, SLE and CKD groups, respectively, with significantly higher correlation among the PLWH group (R=0.8877; p-value=0.0072) compared to non-comorbid group. The accuracy of the anti-RBD test among PLWH and CKD group was similar with the non-comorbid but showed lower sensitivity in the SLE group (p=0.000014). The specificity of the test remained high in all groups. In conclusion, the Anti-RBD test had excellent correlation to SVNT. The persistently high specificity in all groups suggests that this test can be reliably utilized to detect presence of low neutralization capacity, prompting additional vaccination.

Water quality assessment in pastoral of Tibetan Plateau, which is water sources for about 40% of world's population and the runoff-yield area of Yellow rivers, is very important. In this paper, Xiahe county which belongs to Tibetan Plateau pastoral was investigated. Six parameters(via, chloride, COD, ammonia nitrogen, nitrate, fluoride, sulfate) were selected to assess the water quality and health degree by using fuzzy comprehensive evaluation methods. The hydrochemical type in surface water was of HCO3--Mg2+-Ca2+ type. The cations and anions in surface water were mainly from weathering and dissolution of carbonate rock. Results showed that the water quality in all 69 sampling sites was all of class Ⅰ. The integrated health degree reached more than 0.85 and the health rate were 100%. Although ammonia nitrogen was regarded as the main contamination factor, but it had a little effect on the entire body of water. Overall, the surface water qualities of most samples in Xiahe County was good condition.

Minimally invasive approaches to the aortic valve have been described since 1993, with great hopes that they would become universal and facilitate day-case cardiac surgery. The literature has shown that these procedures can be undertaken with equivalent mortality, similar operative time, comparative cost and some benefits in hospital length of stay. The competing efforts of the transcatheter aortic valve implantation for these same outcomes have provided an excellent range of treatment options for patients from the Heart Team. We describe the current state of the art, including technical considerations, caveats and complications of minimal access aortic surgery and predict future directions in this space.

The essence of cross-modal generation and retrieval modeling for image-text interactions lies in semantic consistency. Among these, cross-modal representation alignment serves as the foundational requirement for achieving cross-modal semantic consistency. The crux of our proposed method entails the collaborative training of an image captioning model(referred to as the ’captioner’) and a pair of contrastive encoders for image-text matching(referred to as the ’concoder’). This synergistic approach yields concurrent enhancements in concoder’s performance, captioner’s proficiency, and cross-modal semantic coherence. We coin the proposed method as ‘ReCap’. To begin, we initialize the concoder through knowledge distillation from a pre-trained model. During the training process, we use the output of the initialized concoder as input to a residual attention network, jointly training it with the captioner to achieve semantic consistency. Subsequently, we iteratively update the concoder during the image-text momentum encoding phase using the residual attention network, creating a closed-loop for semantic consistency resolution. Upon completion of training, the concoder and captioner modules can be used independently to perform tasks related to cross-modal retrieval and cross-modal generation of text and images. In order to substantiate the efficacy of our proposed method, we initially conducted empirical experiments encompassing image-text retrieval and image captioning tasks, employing a widely recognized benchmark dataset, MSCOCO. Subsequently, we assessed the fine-grained cross-modal alignment performance of the concoder through an image classification task on the iNaturalist 2018 dataset. The achieved performance metrics notably surpassed those achieved by several incumbent state-of-the-art models, thus validating the proficiency of our method. Finally, motivated by the practical requirements of handling the nature conservation image data, we performed caption annotation for the iNaturalist 2018 dataset. Subsequently, we trained the ReCap on this annotated data. Experimental results demonstrate that our proposed method can maintain semantic consistency between cross-modal retrieval and image caption generation for species with similar visual features but distinct semantics. This achievement signifies a meaningful exploration in the field of cross-modal semantic consistency representation, holding significant practical value in the domain of biological research.

The weight coefficients of the diaphragm spring depend on experiences in the traditional optimization. However, this method not only cannot guarantee the optimal solution but it is also not universal. Therefore, a new optimization target function is proposed. The new function takes the minimum of average compress force changing of the spring and the minimum force of the separation as total objectives. Based on the optimization function, the result of the clutch diaphragm spring in a car is analyzed by the non-dominated sorting genetic algorithm (NSGA-II) and the solution set of Pareto is obtained. The results show that the pressing force of the diaphragm spring is improved by 4.09%by the new algorithmand the steering separation force is improved by 6.55%, which has better stability and steering portability. The problem of the weight coefficient in the traditional empirical design is solved. The pressing force of the optimized diaphragm spring varied slightly during the abrasion range of the friction film, and the manipulation became remarkably light.

Ensuring precise electric locomotive stopping is pivotal for achieving intelligent and unmanned auxiliary transportation systems. Currently, human drivers' expertise plays a central role in the stopping process, posing challenges for automation and cargo location accuracy, particularly in coal mining. This paper focuses on achieving accurate electric locomotive stopping under diverse conditions by utilizing permanent magnet synchronous motor-driven locomotives. This technique introduces a novel stopping control method that combines a fuzzy Proportional-Integral-Derivative (F-PID) controller and a vector control model for permanent magnet synchronous motors (PMSM). After this, we design the F-PID using the PMSM technique based on the new fuzzy rules for each sub-system. In the end, extensive simulations and real-world experiments are conducted on an electric locomotive stopping test bed, which demonstrate the effectiveness of the proposed control method. From the simulation results, it confirming that the ability to achieve precise stopping under various working conditions.

The informational synthesis of neural structures, processes, parameters and characteristics that allow a unified description and modeling as neural machines of natural and artificial neural systems is presented. The general informational parameters as the global quantitative measure of the neural systems computing potential as absolute and relative neural power were proposed. Neural information organizing and processing follows the way in which nature manages neural information by developing functions, functionalities and circuits related to different internal or peripheral components and also to the whole system through a non-deterministic memorization, fragmentation and aggregation of afferent and efferent information, deep neural information processing representing multiple alternations of fragmentation and aggregation stages. The relevant neural characteristics were integrated into a neural machine type model that incorporates unitary also peripheral or interface components as the central ones. The proposed approach allows overcoming the technical constraints in artificial computational implementations of neural information processes and also provides a more relevant description of natural ones.

Transcatheter aortic valve implantation (TAVI) has grown exponentially within the cardiology and cardiac surgical spheres. It has now become a routine approach for treating aortic stenosis. Several uncertainties have been raised about TAVI in comparison to conventional surgical aortic valve replacement (SAVR). The primary concerns are with regards to the longevity of the valves. Several factors have been identified that may predict poor outcomes following TAVI. These include the lesser-used finite element analysis (FEA) to quantify the properties of calcifications that affect TAVI valves. This can also be used in conjunction with other integrated software to ascertain the functionality of these valves. Other imaging modalities are now widely available such as Multi-detector row computed tomography(MDCT) which can accurately size the aortic valve annulus.. This may help reduce the incidence of paravalvular leaks and regurgitation which may necessitate further intervention. Structural valve degeneration (SVD) remains a key factor with varying results from current studies. The true incidence of SVD in TAVI compared to SAVR remains unclear with the lack of long term data. It is now widely accepted that both are part of the armamentarium and are not mutually exclusive. Decision-making for the appropriate intervention should be made via shared decision-making involving the heart team.

Anthropogenic development can strongly influence natural river processes, leading to environmental changes that negatively affect important habitats and biodiversity, and consequently reduce economically important natural resources. This study investigated the effects of salinity intrusion on the habitat of the clam Corbicula japonica in the Seomjin River estuarine zone. We employed the Environmental Fluid Dynamics Code (EFDC) model, which incorporates topographic data and hydrological changes, to simulate salinity concentrations. Two salinity measurement facilities were installed in Seomjin River estuarine and operated to optimize the EFDC model. The results show that reduced flow rates due to intake have a negligible impact on the increased salinity. Maintaining optimal salinity (15–20 psu) during neap tides at the Seomjin River Bridge requires constant high flow rates, which poses significant challenges. Saltwater stratification is identified as the primary cause of pronounced salinity stratification, particularly during neap tides. Addressing this issue through river discharge and intake facility operation is challenging. Structural measures, including riverbed restoration and underwater barriers, are recommended to improve resistance to seawater intrusion. Future research should aim to develop scenarios to reduce salinity concentrations, quantify the reduction efficiency, and propose region-specific measures.

Aortic valve stenosis and malignancy frequently coexist and share the same risk factors as atherosclerotic disease. Data reporting the prognosis of patients with severe aortic stenosis and cancer are limited. Tailoring the correct and most optimal care for cancer patients with severe aortic stenosis is complex. Cancer patients may be further disadvantaged by aortic stenosis if it interferes with their treatment by increasing the risk associated with oncologic surgery and compounding the risks associated with cardiotoxicity and heart failure (HF). Nowadays, several therapeutic options are available for aortic valve stenosis (surgical valve replacement , transcatheter valve implantation, balloon valvuloplasty, or medical therapy), but in presence of malignancy, the use of one of these versus the others should be decided on a case-by-case approach, depending on cancer stage and associated treatment, expected outcome, comorbidities and after an accurate physical examination and Doppler-echocardiography which are the key tools for diagnosing and evaluating aortic stenosis. The current review considers the available data on the association between aortic stenosis and cancer, and therapeutic options.

(1) Background: To identify the association between the presence or absence of raphe and aortic valve dysfunction as well as the presence of aortopathy in patients with bicuspid aortic valve (BAV); (2) Methods: This retrospective study enrolled 312 participants (mean [SD] age, 52.7 [14.3] years; 227 men [72.8%]) with BAV. The BAVs were divided into those with presence (raphe+) or absence (raphe-) of raphe. Valvular function was classified as normal, aortic regurgitation (AR), or aortic stenosis (AS) using TTE. The pattern of BAV aortopathy was determined by the presence of dilatation at the sinus of Valsalva and the middle ascending aorta using CCT.; (3) Results: BAVs with raphe+ had a higher prevalence of AR (148 [79.5%] vs. 48 [37.8%], P < .001) but a lower prevalence of AS (90 [48.6%] vs. 99 [78.0%], P < .001) compared with those with raphe-. The types of BAV aortopathy were significantly different (P = 0.021) according to those with BAV-raphe+ and BAV-raphe-.; (4) Conclusions: The presence of a raphe was significantly associated with a higher prevalence of AR but a lower prevalence of AS and combined dilatation of the aortic root and middle ascending aorta. The presence of raphe was an independent determinant of AR.

There is increasing evidence that some adult mitral valve pathologies may have developmental origins involving errors in cell signaling and protein deposition during valvulogenesis. While early and late gestational stages are well-documented in zebrafish and small mammalian models, longitudinal studies in large mammals with a similar gestational period to humans are lacking. Further, the mechanism of chordae tendineae formation and multiplication remains unclear. This current study presents a comprehensive examination of mitral anterior leaflet and chordae tendineae development in a bovine model (with a gestational period of 9 months). Remarkably distinct from small mammals, bovine development displayed early branched chordae, with increasing attachments only until birth, while the anterior leaflet grew both during gestation and postnatally. Chordae also exhibited accelerated collagen deposition, maturation, and crimp development during gestation. These findings suggest that the bovine anterior leaflet and chordae tendineae possess unique compartmentalized processes of development despite being a continuous collagenous structure.

Gut bacteria play an important role in several metabolic processes and human diseases, such as obesity and its co-morbidities, like fatty liver disease, insulin resistance/diabetes and cardiovascular events. Among several factors, dietary patterns, probiotics, prebiotics, synbiotics, antimicrobials and non-dietary factors, such as stress, age, exercise and climatic conditions, can dramatically impact the human gut microbiota diversity and equilibrium. However, the effect of minor food constituents, including food additives and trace contaminants, on human gut microbiota has received less attention. Consequently, the present review aimed to provide an objective perspective of the current knowledge regarding the impacts of minor food constituents on human gut microbiota and consequently, on human health.

Oedaleus decorus asiaticus, Calliptamus abbreviatus, Angaracris rhodopa, and Myrmeleotettix palpalis are the main grasshoppers that harm the natural grassland in the Hexi Corridor. In this study, the MaxEnt model was employed to identify the key environmental factors affecting the distribution of the four grasshoppers habitats and to assess their distribution under current and future climate change conditions. The aim was to provide a basis for grasshopper monitoring, prediction, and precise control. In this study, 61 occurrences of O. decorus asiaticus, 68 occurrences of A. rhodopa, 58 occurrences of C. abbreviatus, and 92 occurrences of M. palpalis were recorded by GPS, and the distribution of suitable habitats for O. decorus asiaticus, C. abbreviatus, A. rhodopa, and M. palpalis were predicted under current and future climatic scenarios using a MaxEnt model. The average AUC and TSS values of the four grasshoppers were greater than 0.9, and the simulation results were excellent and highly reliable. The mean annual precipitation was the main factor limiting the current range of suitable areas for these four species. Under the current climate, O. asiaticus, C. abbreviatus, and A. rhodopa were mainly distributed in the central and eastern parts of the Hexi Corridor, and M. palpalis was distributed throughout the Hexi Corridor, with a potential distribution area of 1.44×104, 1.43×104, 1.29×104, and 2.12×104 km2, accounting for 15.3, 15.2, 13.7, and 22.5% of the total area of the grasslands in the Hexi Corridor, respectively. The highly suitable areas of O. asiaticus, C. abbreviatus, and A. rhodopa were mainly distributed in the east-central part of Zhangye City, the western part of Wuwei City, and the western and southern part of Jinchang City, with areas of 0.35×104, 0.29×104, and 0.20×104 km2, accounting for 3.7, 3, and 2.2% of the grassland area, respectively. The high habitat of M. palpalis was mainly distributed in the southeast of Jiuquan City, the west, middle, and east of Zhangye City, the west of Wuwei City, and the west and south of Jinchang City, with an area of 0.32×104 km2, accounting for 3.4% of the grassland area. In the 2030s, the range of O. asiaticus, C. abbreviatus, A. rhodopa, and M. palpalis was predicted to decrease.

In new Guideline for the Management of Patients with Valvular Heart Disease for tricuspid regurgitation (TR) is focused the importance of measurement of right-sided diastolic pressures and right ventriculography, pulmonary artery pressures, and pulmonary vascular resistance. Assessment of right ventricular (RV) dimensions and function is pivotal to select patients with severe tricuspid regurgitation who may benefit from tricuspid valve intervention. However, with the exception of tricuspid valve annulus diameter, there is no other cut-off value that defines severe RV dysfunction or dilation for this specific group of patients. It may be difficult, if not impossible, to establish a cut-off value of RV dysfunction since the RV may be exposed to pressure and volume overload, myocardial ischemia, intrinsic myocardial disease or pericardial constraint. Furthermore, the response of the RV to tricuspid valve intervention may vary according to each aetiology and the time course of the disease (acute or chronic). Comprehensive assessment of RV function should address in shape remodelling; functional remodelling; tissue remodelling. This assessment should be performed in optimal loading conditions and after euvolemia has been achieved. It’s now that there is no other cut-off value that defines severe RV dysfunction or dilation for patients with severe TR with the exception of tricuspid valve annulus diameter. It may be difficult, if not impossible, to establish a cut-off value of RV dysfunction since the RV may be exposed to pressure and volume overload, myocardial ischemia, intrinsic myocardial disease or pericardial constraint. In this review we analyze the relationship between right ventricular (RV) and TR in term of outcomes and mortality predictor in patients undergoing percutaneous or invasive treatment for severe TR.

In this paper, an adaptive proportional and integral (PI) controller for speed control of electric drives is developed. The adaptive PI controller is designed based on model reference adaptive identification and the Lyapunov function so that the system stability can be proved. To identify the inertia, the viscous friction torque coefficient, and the load torque simultaneously and smoothly, sinusoidal speed reference is usually employed. A modified motion equation considering the low-pass filter for feedback speed and the Coulomb friction torque is introduced and the relationship between the identified parameters and their actual values are clarified. A high-precision digital simulation model is built based on MATLAB/Simulink. The effectiveness of the proposed method is verified by simulations under various conditions.

Background: The association of echocardiographic findings and subsequent risk of left-sided native valve endocarditis (LS-NVE) is undefined. The aim of this study was to determine if transthoracic echocardiographic (TTE) measurements are associated with the subsequent development of LS-NVE in patients without cardiac predisposing conditions. Methods: Institutional databases were evaluated for adults diagnosed with LS-NVE from 2008 to 2020. Patients with prosthetic valves, cardiovascular implantable electronic devices, intracardiac devices, injection drug use, and predisposing cardiac conditions were excluded. Only patients who had a TTE performed 6 months to 3 years before the development of LS-NVE were included as cases. Controls were patients within the same Mayo location with a TTE report and were matched in a 1:3 ratio according to age, gender, Charlson Comorbidity Index, and echocardiography date. Results: There were 148 cases and 431 matched controls. As compared to controls, IE cases had a higher prevalence of diabetes mellitus (46.6% vs. 30.4%) and chronic kidney disease (46.6% vs. 28.1%) (p<0.001). Left ventricular outflow tract velocity (p=0.017), left ventricular ejection fraction (p=0.018), and E: e’ ratio (p=0.050) were associated with LS-NVE. Conclusions: Echocardiographic measurements were associated with subsequent LS-NVE development in this pilot study. A larger cohort of LS-NVE patients, however, is needed to validate these findings.

Recent research efforts in bone tissue engineering have been primarily directed towards manufacture-viable synthesis of biomaterials that can significantly enhance the biocompatibilities and osteogenic capabilities on the new biomaterials. This paper presents a straightforward, cost-effective, optimized, and well-controlled hydrothermal synthesis of Nb-doped potassium titanate nanofibers in high-purity. Characterization data revealed that the Nb-doping potassium titanate maintained the crystal structure, showing great promise for applications in bone tissue engineering.

In recent years, the manufacturing sector has benefited from a variety of technological innovations regarding automation and utilization of artificial intelligence on the shopfloor. During the manufacturing processes of a product, a variety of meta data can be derived from each working step and considered during subsequent stages of its liefycle like shipment, utilization or recycling. With upcoming regulations decided by the European Union, manufacturers must begin to react to the demand of a comprehensive circular economies by introducing technical solutions like Digital Product Passports (DPP). By associating the specific conditions of all stages in the life of a product within a digital identity, e.g., the DPP, transparency and efficiency can be increased. The Gaia-X service landscape aims at realizing federated data infrastructures, enabling robust and transparent services while considering data sovereignty. In this work, a modular and generic multi-tenant framework for utilizing DPPs within cross-company ecosystems is presented with respect to the manufacturing sector. In applying the Secret Network-blockchain for implementing the automation of DPP management processes, premises for Gaia-X compliance and therefore strengthened trust-anchors are realized. By considering details of ecosystems, as well as most interesting security threats to the proposed architecture, a holistic view of applying DPPs in the context of smart production supply chains is shown. In presenting a simple but vivid use case of the production and compilation of car wheels, the fundamental benefits of the work on hand are underlined, once more.

The Tesla valve (TV), a valvular conduit invented by Nicola Tesla over a decade ago, has recently gained significant attention and application in various fields due to the growing interest in microfluidics and nanofluidics. The unique architecture of TV characterized by an asymmetrical design and an arc-shaped channel, has long been an intriguing yet underrated design for building a passive component in a microfluidic system. While previously regarded as a technology without significant use, TV structures have been implemented in wearable devices, thermal manipulation fluidics, micromixers, micropumps, and fuel cell devices. This article presents the first comprehensive review of TV structures in the literature, which has seen significant growth in the last two years. The review discusses typical TV structures, including single-stage TV (STV), multistage TV (MSTV), and TV derivatives (TVD), along with their characteristics and potential applications. The designs of these structures vary based on their intended applications, but all are constructed based on the fundamental principle of the TV structure. Finally, future trends and potential applications of TV structures are summarized and discussed. This review provides a valuable reference for students, early-career scientists, and practitioners in the field of fluidic devices, particularly those interested in using TV structures as passive components.

Nowadays energy saving is a topical issue due to increasing fuel costs and this aspect is amplified by more stringent emissions regulations that impact on vehicle development. A recent study conducted by the U.S. Department of Energy shows that about five percent of the U.S. energy consumption is transmitted by fluid power equipment. Nevertheless, this study also shows that the efficiency of fluid power averages 21 percent. This offers a huge opportunity to improve the current state-of-the-art of fluid power machines, in particular to improve the energy consumption of current applications. These facts dictate a continuous strive toward improvements and more efficient solutions: to accomplish this objective a strong reduction of hydraulic losses and better control strategies of the hydraulic systems are needed. In fluid power, there exist many techniques to reduce/recover energy losses of the conventional layouts, e.g. load sensing, electrohydraulic flow matching, independent metering, etc. One of the most efficient ways to analyze these different layouts and identify the best hydraulic solution is done through virtual simulations instead of prototyping, since the latter involves higher investment costs to deliver the product into the market. However, to build a fluid power machine virtual model, some problems arise relative to different aspects, for instance: loads on actuators (both linear and rotational) are not constant and pumps are driven by a real engine whose speed depends on required torque. Furthermore, it is important to achieve higher level of detail to simulate each component in the circuit: the greater detail, the better the machine behavior is portrayed, but it obviously entails heavy impact on simulation time and computational resources. Therefore, there is a need to create mathematical model of components and systems with sufficient level of detail to easily acquire all those phenomena necessary to correctly evaluate machine performance and make modifications to the fluid power component design. In this context, a hydraulic proportional valve PVG 32 by Danfoss is taken as an object of study, its performance is analyzed with suitable mathematical model and simulation is done to observe closeness of a model to the laboratory experiment.

This paper proposes a position control method for low cost EGR valve system in automotive application. Generally, position control system using in automotive application has many restrictions such as cost and space, the mechanical structure of actuator implies high friction and large difference between static friction and coulomb friction. This large friction difference occurs the vibrated position control result when the controller uses conventional linear controller such as P, PI. In this paper, low cost position control method which can apply under the condition of high difference friction mechanical system. Proposed method is verified by comparing conventional control result of experiments.

This paper Numerically investigates the effectiveness of the turbine rotating blade nozzle position on the vortex and film composite cooling performance. The coolant injecting nozzles arranged near the pressure surface side (PS-side-in) .vs. arranged near the suction surface side (SS-side-in) are compared at the rotating speed range of 0-4000rpm with fluid and thermal conjugate approach. Results show that the nozzle position presents different influences under low and higher rotating speed. In terms of the mainstream flow, rotation makes the stagnation line move from the PS-side pressure surface side to the SS-side suc-tion surface side, which changes the coolant film attachment on the blade leading edge surface. The nozzle position however indicates limited influence on the coolant film flow. In terms of the internal channel vortex flow, the coolant injecting from the nozzles forms a high-velocity region near the target wall which brings about enhancing convective heat transfer. The direction of the near wall vortex flow is opposite and align to the Coriolis force direction in both the PS-side-in and SS-side-in, respectively. Therefore, the Coriolis force augments to the heat transfer of the internal vortex cooling in SS-side-in while weakens the internal heat transfer in PS-side-in. Such effects become more intense with higher rotational speed. The blade surface area-averaged dimensionless temperature that inversely proportional to the actual temperature is 7.8% higher in SS-side-in as compared to that in PS-side-in. The SS-side-in suggests more superior composite cooling perfor-mance under the relatively higher rotating speed.

Digital twins are an emerging technology that could be harnessed for the digitalization of the industry. Steel industry systems contain a large number of electro-hydraulic components, as proportional valves. An input-output model for a novel water proportional cartridge valve is derived from physical modelling based on fluid mechanics, dynamics, and electrical principles. The valve is a two-stage valve with two 2/2-way water proportional valves as the pilot stage and a marginally stable poppet-type cartridge valve as the main valve. The orifice equation, which is based on Bernoulli principles, is approximated by a polynomial which makes parameter estimation easier and makes modelling possible without measuring pressure of the varying control volume situated in the pilot stage part of the valve. Data were collected when the valve was operating as a component in a closed-loop system as part of a press-mill machine in a steel manufacturing plant. Parameter estimation was made by convex optimization with physical constraints to overcome problems caused by poor system excitation. For comparison, a simple linear model was derived and the least squares method used for parameter estimation. A thorough estimation of the parameters relative errors is presented. The model contains 5 parameters related to the design parameters of the valve. The modelled position output is in good agreement with experimental data for training and test data. The model can be used for real time monitoring of the valve’s status by the model parameters. One of the model parameters varies linearly with production cycles. Thus, aging of the valve can be monitored.

To evaluate whether the extent of cardiac damage in severe aortic stenosis (AS) might be associated with the occurrence of conduction system disorders after TAVI. A total of 153 symptomatic patients with severe AS who had a TAVI were categorized before the procedure according to the extent of cardiac damage: stage 1 (13.5%): no or LV damage; stage 2 (58.8%): left atrial/mitral valve damage, atrial fibrillation (AF); stage 3 (27.7%): low-flow state, pulmonary vasculature/tricuspid valve/RV damage. After TAVI, 34% of patients exhibited LBBB and 10% high-degree atrioventricular block (HD-AVB). No patient in group 1 developed HD-AVD whereas new LBBB was frequent in groups 2 and 3. Twenty-one patients presented with resolutive paroxysmal AF with a higher rate for each group increment (group 1: n=0, 0%; group 2: n=11,15.7%; group 3: n=10, 30.3%) (p = 0.012). Patients in group 3 had the higher rate of permanent pacemaker implantation (PPMI) (group 1: n=1, 6.3%; group 2: n=7,10%; group 3: n=9, 27.3%) (p=0.012). No patient in group 1 died during the hospital stay. In conclusion, cardiac damage staging of AS might help identify patients at higher risk of conduction disorders and PPMI requirement after TAVI.

Introduction. Recent studies revealed that differentiation of valvular interstitial cell into myofibroblasts played an important role in pathological valve remodeling in rheumatic valvular disease. Objective. To investigate effects of atorvastatin, olmesartan, and resveratrol on Transforming Growth Factor β1-induced fibrosis. Methods. Valvular interstitial cell was isolated from 12-weeks male New Zealand rabbit (Oryctolagus cuniculus). Culture cells was divided into 4 groups, control group, group I (0.5 mg/mL Atorvastatin), group II (100 nmol/L Olmesartan), group III (50 μM/L Resveratrol) and group IV (combinations). All group were exposed to 100 nM Transforming Growth Factor β1 for 24 hours. Results. Immunochemical staining demonstrated that cells were completely differentiated into myofibroblasts with mean expression of α-smooth muscle actin 24522.64±4566.994. Atorvastatin, olmesartan, resveratrol, and its combination significantly reduced α-smooth muscle actin expression (6823±1735.3, 6942.7±2455.9, 14176.2±3343.3, 5051.8±1612.2 respectively (p<0.001). Conclusion. Our data showed atorvastatin, olmesartan, resveratrol, and its combination significantly reduce Transforming Growth Factor β1-induced valvular fibrosis.

The Stellarator Power Plant Studies Prospective R&amp;D Work Package among the Eurofusion Programme was settled to bring the stellarator engineering to maturity, so that stellarators and particularly the HELIAS (HELical-axis Advanced Stellarator) configuration could be a possible alternative to tokamaks. However, its complex geometry makes designing a Breeding Blanket (BB) that fully satisfies the requirements for such an HELIAS configuration a difficult task. Taking advantage of the acquired experience in BB design for DEMO tokamak, CIEMAT is leading the development of a Dual Coolant Lithium Lead (DCLL) BB for a HELIAS configuration. To answer the specific HELIAS challenges new and advanced solutions have been proposed, as the use of fully detached First Wall (FW) based on liquid metal Capillary Porous Systems (CPS). These proposed solutions have been studied in a simplified 1D model that can help to estimate the relative variations in Tritium Breeding Ratio (TBR) and displacement per atom (dpa) to verify their effectiveness to simplify the BB integration, improve the machine availability while keeping the main BB nuclear functions (i.e. tritium breeding, heat extraction and shielding). This preliminary study demonstrates that the use of FW CPS would reduce the radiation damage received by the blanket without compromising its tritium breeding performance.

The invasion of ship domain stands out as a significant factor contributing to the risk of collisions during vessel navigation. However, there is a lack of research on the mechanisms underlying collision risks specifically related to merchant and fishing vessels in coastal waters. This study proposes an assessment method for collision risks between merchant and fishing vessels in coastal waters and validated through a comparative analysis through visualization. First of all, the operational status of fishing vessels is identified. Collaboratively working fishing vessels are treated as a unified entity, expanding their ship domain during operation to assess collision risks. Secondly, to quantify the collision risk between ships, a collision risk index (CRI) is proposed and visualized based on the severity of collision risk. Finally, taking the high risk area of merchant and fishing vessels collision in the Minjiang River Estuary as an example, this paper conduct the analysis involves classifying ship collision scenarios, extracting risk data under different collision scenarios, and visually analyzing areas prone to danger. The results indicate that this method effectively evaluates the severity of collision risk, and the identified high-risk areas resulting from the analysis is verified by accidents occurred in the recent three years.

Pardosa pseudoannulata is one of the most common wandering spiders in agricultural fields and a potentially good bioindicator for heavy metal contamination. However, little is known about the mechanism by which spiders respond to heavy metals at the molecular level. In this study, high-throughput transcriptome sequencing was employed to characterize the de novo transcriptome of the spiders and to identify differentially expressed genes (DEGs) after cadmium exposure. We obtained 60,489 assembled unigenes, 18,773 of which were annotated in the public databases. Ultimately, 3450 cDNA simple sequence repeats were identified and validated as potential molecular markers in the unigenes. A total of 2939, 2491 and 3759 DEGs were detected among the three libraries of two Cd-treated groups and the control. Functional enrichment analysis revealed that metabolism processes and digestive system function were predominately enriched in response to Cd stress. At the cellular and molecular levels, significantly enriched pathways in lysosomes and phagosomes as well as replication, recombination and repair demonstrated that oxidative damage resulted from Cd exposure. Based on the selected DEGs, certain critical genes involved in defence and detoxification were analysed. These results may elucidate the molecular mechanism underlying spiders' responses to heavy metal stress.

This study describes the development of an automated bag valve mask (BVM) compression system, which, during acute shortages and supply chain disruptions can serve as a temporary emergency ventilator. The resuscitation system is based on the Arduino controller with a real-time operating system installed on a largely RepRap 3-D printable parametric component-based structure. The cost of the system is under $170, which makes it affordable for replication by makers around the world. The device provides a controlled breathing mode with tidal volumes from 100 to 800 milliliters, breathing rates from 5 to 40 breaths/minute, and inspiratory-to-expiratory ratio from 1:1 to 1:4. The system is designed for reliability and scalability of measurement circuits through the use of the serial peripheral interface and has the ability to connect additional hardware due to the object-oriented algorithmic approach. Experimental results demonstrate repeatability and accuracy exceeding human capabilities in BVM-based manual ventilation. Future work is necessary to further develop and test the system to make it acceptable for deployment outside of emergencies in clinical environments, however, the nature of the design is such that desired features are relatively easy to add with the test using protocols and parametric design files provided.

Based on the dynamic strength variation mechanism of concrete under complex loading conditions, two approaches were devised: numerical testing and CT scanning, guided by the principle of minimizing energy dissipation. A methodology for calculating concrete's failure area and measuring its strength was developed. The analysis delves into the mechanisms behind failure patterns and variations in concrete specimen strength, focusing on crack initiation, development, and the resultant failure surface formed by crack propagation, along with the stress distribution in concrete specimens subjected to diverse loading conditions. Through evaluating the strength and computed failure area of concrete specimens, it is evident that the loading method influences both the strength and failure area of concrete specimens. In general, a larger failure area correlates with a higher measured strength.

: Inflammation may mediate the association of mitral valve prolapse (MVP) with ventricular scarring and arrhythmia. The purpose of this study is to investigate the association of neutrophil- and platelet-to-lymphocyte ratios (NLR, PLR) with ventricular arrhythmia in MVP. Clinical and demographic data were extracted from electronic medical records for all patients aged 18-90 years with MVP on echocardiography between 2016-19 at our institution. We studied 65 patients who had a differential blood count within six months prior to ambulatory ECG (A- ECG) (medi-an age [IQR] 70 [61-77] years; 62% female; 12% African American). Patients with surgery or in-fection within six months prior to CBC were excluded. Complex or frequent ventricular ectopy (cfVE) was defined as the presence of two or more premature ventricular contractions (PVCs) on a 10-second ECG tracing or greater than 1% PVC burden or NSVT on ambulatory ECG monitoring. Logistic and bivariate regression was used to analyze clinical, electrocardiographic and echo-cardiographic factors associated with NLR and PLR. Factors associated with higher NLR were congestive heart failure (p=0.005), male sex (p=0.01), age (p=0.003), and bileaflet MVP (p=0.04). NLR was associated with higher absolute PVC burden (rs=0.28, p=0.03) and cfVE (median NLR [IQR] 3.0 [1.6 – 6.3]) with cfVE versus (2.4 [1.4-3.4], p=0.04) without cfVE. An NLR of 5.6 yielded 50% sensitivity and 90% specificity for PVC burden >1% (AUC 0.69). No significant association was found between PLR and PVC burden or cfVE. NLR is associated with PVC burden and com-plex ventricular ectopy in MVP, suggesting that inflammation is a significant factor in the patho-genesis of ventricular arrhythmia in this condition.

Abstract: Toxicity of emerging organic pollutants to photosystems of aquatic plants are still not well clarified. This study aimed to develop a novel ecotoxicological experimental protocol based on nanoscale electrochemical mapping of photosynthetic oxygen evolution of aquatic plants by SECM (scanning electrochemical microscopy). The protocol was also checked by confocal laser scanning microscopy (CLSM), the traditional Clark oxygen electrode method and chlorophyll fluorescence technique. The typical persistent organic pollutant 2,4-dichlorophenol (2,4-DCP) in water environment and the common aquatic Microsorium pteropus (M. pteropus) were chosen as the model organic pollutant and tested plant, respectively. It was found that the SECM method could well discriminated the responses of stoma micromorphology and spatial pattens of photosynthetic oxygen evolution on single stoma. The shape of stoma blurred with increasing 2,4-DCP concentration, which was in good agreement with the CLSM images. The dose-response curves and IC50 values obtained from the SECM data were verified by the data measured by the traditional Clark oxygen electrode method and chlorophyll fluorescence test. The IC50 value of single stoma oxygen emission of 24 h exposed plant leave, which was derived from the SECM current data (32535 μg L-1), was close to those calculated from the maximum photosynthetic efficiency (Fv/Fm) measured by chlorophyll fluorescence test (33963 μg L-1), and the Clark oxygen electrode method photosynthetic oxygen evolution rate (32375 μg L-1). The 72 h and 96 h 2,4-DCP exposure data further confirmed the reliability of the nanoscale stoma oxygen emission mapping methodology for ecotoxicological assessment. In this protocol, the procedures for how to collect effective electrochemical data and how to extract useful information from the single stoma oxygen emission pattern were well established. This study showed that SECM is a feasible and reliable ecotoxicological tool for evaluation of toxicity of organic pollutants to higher plants with unique nanoscale visualization advantage over the conventional methods.

Nowadays brushless DC motors (BLDCMs) are becoming indispensable components as the electrification revolution in the mobility industry is happening. Electric kick scooters, so-called e-scooters, are among these micro-mobility vehicles which are powered by these motors. Due to the uncertain and nonlinear features, the controller performance developed for these motors degrades. For these reasons, a chattering-reduced cascaded Sliding Mode Control (SMC) scheme to effectively track reference motor speed in the outer loop by eliminating torque ripples in the inner loop current control was designed. Field-oriented Control (FOC) methodology was used to implement the SMC in the BLDCM. An exponential reaching law algorithm was proposed for sliding surfaces of the inner and outer loop controllers. The suitability and performance of electric scooter-hub motors were analyzed in terms of traction control. A cascaded speed and torque controller produced significantly favorable results representing minimized torque and current ripples, and operation over a wide speed range.

The valve controlled cylinder drive system is the most common type among hydraulic applications. The nonlinear behaviour in such system is inevitable when the valve spool around its null position [1] , Leaney [2] utilised component linking method to investigate the nonlinearities in a Moog valve controlled asymmetric cylinder drive system by simulation in Fortran, in which a generalised concept is introduced and validated by comparing to the experimental results. An factor is proposed in the generalised concepts to describe the asymmetric cylinder state, which is a constant when the cylinder in extending or retracting, but numerically calculated when the valve spool in the underlap region [2]. This paper utilises the component linking method to simulate the Moog valve controlled asymmetric cylinder drive system in Matlab Simulink, and proposed an analytical solution for factor when the valve spool in the underlap region.

Spin valves with a synthetic antiferromagnet were fabricated by magnetron sputtering. It was shown that the fabricated spin valves had perfect microstructure of layers and smooth interfaces, therefore RKKY interaction dominates in coupling of ferromagnetic layers separated by a copper spacer. Rhombus-shaped microobjects were fabricated from a single spin valve film. The thermomagnetic treatment procedure was found, to form unidirectional anisotropy in the microobject so, that the values of the exchange bias fields in the rhombus’ nonparallel sides were opposite in sign. For the synthetic antiferromagnet CoFeNi/Ru/CoFeNi the difference between ferromagnetic layers thicknesses was found, at which the thermomagnetic treatment forms the same exchange bias all over the rhombus’ side. The sensor element was fabricated in which each side of the rhombus was a shoulder of a Wheatstone bridge. After the thermomagnetic treatment procedure each shoulder worked as an active magnetosensitive element, thus the device operated as the full Wheatstone bridge. The sensor output has the shape of a step, high sensitivity to field change and significant magnetic hysteresis. Such characteristics are suitable for switching devices.

Background. Minimally invasive surgery via right mini-thoracotomy has become the standard of care for the treatment of mitral valve disease worldwide, particularly at high volume centers. In recent years, the spectrum of indications has progressively shifted and extended to fragile and higher risk patients, also addressing more complex mitral valve disease and ultimately including patients with native or prosthetic infective endocarditis. The rationale for the adoption of the minimally invasive approach is to minimize the surgical trauma, promote an earlier postoperative recovery and reduce the incidence of surgical wound infection and other nosocomial infections. The aim of this retrospective observational study is to evaluate the effectiveness and the early and late outcome in patients undergoing minimally invasive surgery for mitral valve infective endocarditis. Methods. Prospectically collected data regarding minimally invasive surgery in patients with mitral valve infective endocarditis were entered into a dedicated database for the period between January 2007 and December 2022 and retrospectively analyzed. All comers during the study period underwent a preoperative evaluation based upon clinical history and anatomy for the allocation to the most appropriate surgical strategy. Selection for the mini-thoracotomy approach was primarily driven by a thorough transthoracic and especially transesophageal echocardiographic evaluation, coupled with total body and vascular imaging. Results. During the study period, 92 patients underwent right mini-thoracotomy to treat native (80/92, 87%) or prosthetic (12/92, 13%) mitral valve endocarditis at our institution, representing 5% of the patients undergoing minimally invasive mitral surgery. Twenty-six (28%) patients had undergone previous cardiac operations, whereas 18 (20%) presented preoperatively with complications related to endocarditis, most commonly systemic embolization. Sixty-nine and 23 patients, respectively, underwent early surgery (75%) or were operated on after the completion of targeted antibiotic treatment (25%). A conservative procedure was feasible in 16/80 (20%) patients with native valve endocarditis. Conversion to standard sternotomy was necessary in a single case (1.1%). No cases of intraoperative iatrogenic aortic dissection were reported. Four patients died perioperatively, accounting for a thirty-day mortality of 4.4%. Causes of death were refractory heart or multiorgan failure and/or septic shock. New onset stroke was observed postoperatively in one case (1.1%). Overall actuarial survival rate at 1 and 5 years after operation was 90.8% and 80.4%, whereas freedom from mitral valve reoperation at 1 and 5 years was 96.3% and 93.2%, respectively. Conclusions. The present study shows good early and long-term results in higher-risk patients undergoing minimally invasive surgery for mitral valve infective endocarditis. Total body, vascular and echocardiographic screening represent the key points to select the optimal approach and allow the extension of indications for minimally invasive surgery to sicker patients, including active endocarditis and sepsis.

The results shown in this paper extend our research group's previous work, which presents the theoretically achievable hydrogen engine-out NOx (H2-NOx) Pareto front of a hydrogen hybrid electric vehicle (H2-HEV). While the Pareto front is calculated offline, which requires significant computing power and time, this work presents an online-capable algorithm to tackle the energy management of a H2-HEV with explicit consideration of the H2-NOx trade-off. Through the inclusion of realistic predictive data on the upcoming driving mission, a model predictive control algorithm (MPC) is utilized to effectively tackle the conflicting goal of achieving low hydrogen consumption while simultaneously minimizing the NOx. In a case study it is shown that the MPC is able to satisfy user-defined NOx limits over the course of various driving missions. Moreover, a comparison to the optimal Pareto front highlights the MPC's ability to achieve close-to-optimal fuel-performance for any desired cumulated NOx target on four realistic routes for passenger cars.

German noise action plans aim to reduce negative health outcomes from noise exposure and identify quiet areas free of noise pollution. Quiet area identification in German noise action plans is based primarily on noise mapping and spatial analysis and not empirical or qualitative data about acoustic environments, thus leaving a gap in the understanding of the quality of formally recognized quiet areas in noise action plans. This work presents a comparative empirical case study in Dortmund, Germany, with the aim to describe the diurnal dB(A) and biophonic properties of quiet areas versus noise 'hot spots'. Sound observations were collected (n=282,764) in five different natural or recreational land use patch types larger than four acres within 33 proposed quiet areas in Dortmund (n=70) and 23 noise hot spots between April 27^th, 2022 and March 2^nd, 2023. We find that quiet areas are on average more than 20 dB(A) quieter than noise hot spots almost every hour of the day. Forests, managed tree stands, cemeteries, and agriculture diel patterns are dominated by dawn dusk chorus in spring and summer, whereas sport and recreation as well as noise hot spots are dominated by traffic and human noise. A novel composite biophony mapping procedure is presented that finds distinct temporal distribution of biophony in forested and agriculture peri-urban locations positively associated with patch size, distance away from LDEN > 55, proximity to water, and the number of vegetation layers in the plant community. Anthrophony distribution dominates urban land uses in all hours of the day, but expands during day and evening and contracts at night and in dusk hours. The procedures presented here illustrate how qualitative information regarding quiet areas can be integrated into German noise action planning.

During the Renaissance, Leonardo Da Vinci was the first person to successfully detail the anatomy of the aortic root and its adjacent structures. Ever since, novel insights into morphology, function and their interplay have accumulated resulting in advanced knowledge on complex functional characteristics of the aortic valve (AV) and root. This shifted the vision from the AV as being a static structure towards that of a dynamic interconnected apparatus within the aortic root as a functional unit, exhibiting a complex interplay with adjacent structures via both humoral and mechanical stimuli. This paradigm shift has stimulated surgical treatment strategies of valvular disease that seek to recapitulate healthy AV function, whereby AV disease can no longer be seen as an isolated morphological pathology which needs to be replaced. As prostheses still cannot reproduce the complexity of human nature, treatment of diseased AVs, whether stenotic or insufficient, has tremendously evolved with a similar shift towards treatments options that are more hemodynamically centered such as the Ross procedure and valve-conserving surgery. Native AV and root components allow for an efficient Venturi effect over the valve to allow for optimal opening during the cardiac cycle, while also alleviating the left ventricle. Next to that, several receptors are present on native AV leaflets, enabling messenger pathways based on their interaction with blood and other shear-stress related stimuli. Many of these physiological and hemodynamical processes are under acknowledged but may hold important clues for innovative treatment strategies, or as potential novel targets for therapeutic agents that halt or reverse the process of valve degeneration. A structured overview of these pathways and their implications for cardiothoracic surgeons and cardiologists is lacking. As such, we provide an overview on embryology, hemodynamics, and messenger pathways of the healthy and diseased AV and its implications for clinical practice, by relating this knowledge to current treatment alternatives and clinical decision-making.

In the current study, a two-dimensional numerical study is carried out to investigate the performance of a novel Double-chamber Parallel Flexible Valves micropump, which utilized the electrowetting-on-dielectrics (EWOD) effect to drive the microfluid flow. By observing the flow fields, the internal circulations are seen on both the left and right side of the pump. The generation of the backflow is discussed by tracking the movement of the vortices. Only slight flow fluctuation is seen in the micropump. Based on the simulation outcomes, the structural parameters including the width of the inlet/outlet, the width of the pumping channel and the diverging angle in the micropump are analyzed, the influence of these parameters on the pumping volume and the maximum pressure have been discussed. Eventually, a group of optimal parameter combinations is given according to the results to extend the operating potential of the micropump.

Urban rail transit hub platform is the most important area for passenger flow distribution. In order to calculate passenger flow volume in platform and evaluate platform service level during rush hours, this paper presents a method for modeling and simulation of passenger flow distribution in platform. Passenger flow distribution model (PFDM) is proposed based on the basic analysis and the superposition principle of passenger flow. Simulation design for PFDM is proposed by Anylogic, which contains simulation process and simulation model. Experiment results show that PFDM and simulation design are effective and accordant with the reality scenario, and the simulation precision is comparatively ideal. This research could provide a beneficial reference for train scheduling and operation management under the viewpoint of traffic safety and service level.

Purpose: To evaluate the efficacy and survival rates of same session ab interno trabeculectomy with the trabectome and Ahmed glaucoma valve implant (AT) in comparison to the Ahmed glaucoma valve alone (A). Method: A total of 107 eyes undergoing primary glaucoma surgery were enrolled in this retrospective comparative case series, including 48 eyes which underwent AT and 59 eyes which received A alone. Participants were identified using the procedural terminology codes, and their medical records were reviewed. The primary outcome measure was surgical success, defined as intraocular pressure (IOP) > 5 mmHg, ≤ 21 mmHg, and IOP reduction ≥ 20% from baseline at two consecutive visits after three months, no reoperation for glaucoma. Secondary outcome measures were IOP, the number of glaucoma medications, incidence of a hypertensive phase, and best corrected visual acuity (BCVA). Results: The cumulative probability of success at one year was 70% in AT, and 65% in A (p=0.85). IOP decreased significantly from 26.6 ± 10.1 mmHg at baseline to 14.7 ± 3.3 mmHg at the final follow-up in AT (p= 0.001). The corresponding numbers for A were 28.8 ± 10.2 and 16.7 ± 4.9, respectively (p= 0.001). The final IOP was significantly lower in AT (p= 0.022). The number of medications at baseline was comparable in both groups (2.6 ± 1.2 in AT and 2.5 ± 1.3 in A, p=0.851). Corresponding number at 1 year visit was 1.2±2 in AT and 2.8±1.8 in A (p=0.001). The incidence of a hypertensive phase was 18.7% in AT and 35.5% in A (p=0.05). HP resolved in only 30% of eyes. The criteria for HP resolution were fulfilled in 9 eyes (30%). There was no difference in the rate of resolution of the hypertensive phase between AT and A (33.3% and 28.5%, respectively, p=0.67). Conclusion: Ahmed glaucoma valve implant with same session trabectome surgery significantly decreased the rate of the hypertensive phase and postoperative IOP as well as the number of glaucoma medications.

This work targets the development of a mobility control system for high-speed series hybrid electric tracked vehicles, which operate with independent traction motors for each track. The scope of the research encompasses the modeling of the series hybrid powertrain specific to military tracked vehicles, as well as an in-depth analysis of their dynamic behavior. Subsequently, the study conducts a critical review of the mobility control approaches sourced from literature, identifying key techniques relevant to high-inertia vehicular applications. Building on the foundational models, the study puts forward a robust closed-loop mobility control system aimed at ensuring precise and stable off-road vehicle operations. The system's resilience and adaptability to a variety of driving conditions are emphasized, with a particular focus on handling maneuvers such as steering and pivoting, which are challenging operations for tracked vehicle agility. The performance of the proposed mobility control system is tested through a series of simulations, covering a spectrum of operational scenarios. These tests are carried out in both offline simulation settings, which permit meticulous fine-tuning of system parameters, and real-time environments that replicate actual field conditions. The simulation results demonstrate the system's capacity to improve vehicular response and highlight its potential impact on the future designs of mobility control systems for the heavy-duty vehicle sector, particularly in defense applications.

Natural gas hydrate, also known as combustible ice and mainly composed of methane, it is identified as the potential clean energy in the 21th century. Due to its large reserves, gas hydrate can ease problems caused by energy resource shortage and has gained attention around the world. In this paper, we focus on the exploration and development of gas hydrate as well as discussing its status and future development trend in China and abroad, then we analyze its opportunities and challenges in China from four aspects: resource, technology, economy and police with five forces model and PEST method. The results show, China has abundance gas hydrate resource; however the backward technologies and inadequate investment has seriously hindered the future development of gas hydrate, so China should establish relevant cooperation framework and intuitional arrangement to attract more investment as well as breaking through technical difficulties to make gas hydrate commercialization as soon as possible.

Although initially conceived for high-risk patients who are ineligible for surgical aortic valve replacement (SAVR), transcatheter aortic valve replacement (TAVR) is now recommended in a wider spectrum of indications including young patients. However, as for SAVR, TAVR is also associated with a risk of infectious complications, namely prosthetic valve endocarditis (PVE). As the number of performed TAVR procedure increases, and despite the low incidence of PVE post TAVR, clinicians should be familiar with the associated risk factors and the clinical presentation. Whereas the diagnosis of native valve endocarditis can be straightforward applying the modified Duke criteria, the diagnosis of PVE is more challenging given its atypical symptoms, lower sensitivity of the criteria, and low diagnostic yield of conventional echocardiography. Delay in proper management can be associated with increased morbidity and mortality. Therefore, clinicians should have a high index of suspicion and initiate proper work-up according to the severity of illness, the underlying host, and the local epidemiology of the causative organisms. The most common causative pathogens are Gram-positive bacteria such as S. aureus, coagulase negative staphylococci, Enterococcus spp. and Streptococcus spp. (particularly the viridans group) and, less likely Gram-negative and fungal pathogens. The high prevalence of antimicrobial resistance complicates the choice of therapy. There remain controversies regarding the optimal management strategies including indications for surgical interventions. Surgical assessment is recommended early in the course of illness and surgical intervention should be considered in selected patients. As in other PVE, duration of therapy depends on the isolated pathogen, the host, and the clinical response. Since TAVR is a relatively new procedure, the outcome of TAVR-PVE is yet to be fully understood.

Enteric infections are a major public health concern. Detecting risk areas requires a strong surveillance system for pathogenic viruses in possible sources such as wastewater. To build an environmental surveillance system, we aimed to identify group A rotavirus (RVA) and human adenovirus (HAdV) in wastewater. We also focused on three different methods of viral concentration to determine suitability for a regular surveillance system. We screened 20 wastewater samples for HAdV and RVA using quantitative polymerase chain reaction (qPCR) and conventional polymerase chain reaction (cPCR). Sixteen posi-tives (18/20) and ten (14/20) positives for HAdV and RVA, respectively, were obtained on qPCR, representing a prevalence of 90% and 70%. Twelve (12) positives were successfully amplified. Bag-mediated filtration system (BMFS) and skimmed milk (SM) flocculation were the most consistent viral concentration methods for HAdV and RVA, respectively. Human adenovirus was identified with nucleotide identity range of 98.48% to 99.53%. Statistical analysis of positives showed that viral burden differed by site (P

Wastewater-based epidemiology (WBE) has emerged as a key method for continuous monitoring of COVID-19 prevalence including circulating SARS-CoV-2 lineages. WBE addresses limitations of traditional clinical COVID-19 surveillance such as clinical test availability, fluctuating testing rates and increased reliance on rapid antigen tests. Our study in Perth, Western Australia, found a significant positive correlation between SARS-CoV-2 concentrations in wastewater and clinical PCR positivity rates (rs = 0.772; p < 0.001) over an 18-month period that included four successive COVID-19 waves. A strong positive correlation was apparent between the proportions of SARS-CoV-2 lineages in wastewater and clinical cases within the same region (rs = 0.728; p < 0.001), including earlier detection of Omicron and recombinant lineages in wastewater before clinical case confirmation. The successful integration of WBE with healthcare data underscores its critical role in enhancing public health decision-making and pandemic management. This approach not only demonstrates the value of WBE in current global health surveillance efforts but also highlights the potential of WBE to address future public health challenges, as a comprehensive disease monitoring and response approach.

Reasonable allocation of production plans and saving the overall electricity cost are crucial for large manufacturing conglomerates, which is an effective way for conglomerates to realize open-source and cost-saving. This paper develops an optimization model of off-site industrial production scheduling for enterprises in response to the problems of high electricity costs due to the irrational allocation of production schedules on the demand side of China's electric power and the difficulty of promoting industrial and commercial distributed photovoltaic (PV) projects in China. The model makes full use of the conditions of different PV resources and different electricity prices in different places to optimize the scheduling of industrial production in different places. The model is embedded with two sub-models of the electricity price prediction model and distributed photovoltaic kWh cost model to complete the model parameters, in which the electricity price prediction model utilizes the LSTM neural network. The integrated model is then solved by the particle swarm algorithm. To verify the effectiveness of the model in solving the problem of off-site production scheduling on the demand side of electricity, the research team researched two off-site pharmaceutical factories belonging to the same large pharmaceutical company. Finally, the research data were substituted into the model for solving, and it was concluded that the optimization model could significantly reduce the cost of electricity consumption of the enterprise by about 7.9 %.

In contemporary construction, the prevalence of vibration serviceability issues in lightweight and slender structures has become increasingly common, owing to advancements in building materials and construction methods. While these structures often meet the criteria for ultimate limit states, they can still elicit complaints due to excessive vibrations induced by human activity. To address this challenge, the Integral Resonant Control (IRC) technique has emerged as a favored approach for actively damping vibrations in various systems. This study introduces a fresh perspective on implementing a multi-input multi-output (MIMO) IRC scheme for active vibration control (AVC) specifically tailored for pedestrian structures utilizing inertial mass actuators. Building upon a common framework and design methodology outlined in previous research, this work presents a novel application of MIMO IRC for AVC. The designed controller is rigorously tested and implemented on a laboratory floor structure to validate its efficacy.

The four-way reversing valve is a key component determining whether a heat pump air conditioning system can work. Studying the four-way reversing valve is of great significance for improving the performance of the heat pump air conditioning system. In this paper, the control equation of the sliding block movement process is constructed to simulate the reversing process of the four-way reversing valve in fluid mechanics, and a detailed study is carried out from the sliding block speed, sliding block acceleration, sliding block force, refrigerant leakage, and other aspects. Research has shown that optimizing the structure of the slider can greatly improve the working performance of the four-way reversing valve. Increasing the height of the slider not only improves the pressure relief ability of the four-way reversing valve and prevents the slider from being damaged by high-pressure gas impact, but also reduces the leakage of refrigerant during the directional process; When reducing the length of the slider, although it will improve the pressure relief capacity of the four-way reversing valve, it also increases the amount of refrigerant leakage. The research results provide a theoretical basis and improvement direction for designers to improve the performance of four-way reversing valves.

Based on the textured controllable interface effect, the dynamic performances of the textured and ordinary pilot valve are analyzed experimentally, and the influence of the textured controllable interface on the response of pilot valve is studied. Results show that when Pin is small, the textured surface shortens the reciprocating time of valve core, increasing the flow rate, and speeds up the piston stroke of oil cylinder. The valve core actions much more stable and sensitivity. Meanwhile, combined with the theoretical calculation, the operation mechanism of texturing the pilot valve is analyzed. It is concluded that the stress of textured valve core sealing surface is greater than that of ordinary one, and the pressure difference gradually decreases with the increase of Pin, and the flow difference is basically the same as the force on the sealing surface. This indicates that the textured surface improves lubrication characteristics, reduces the friction between components. The textured valve makes the velocity changes gently, and enhances the responsiveness and stability of the valve. Those related results provide a new idea for enhancing the response design of the pilot valve.

Rising fuel costs, significant air pollution, and the need to mitigate the negative consequences of oil consumption have diminished the relevance of traditional vehicles. This shift encourages the adoption of safer, more efficient, and eco-friendly transportation alternatives, such as fuel cell, electric, and hybrid vehicles. Brushless direct current motors are gaining popularity due to their high efficiency, power factor, torque, and controllability. By 2030, Brushless Direct Current motors are expected to replace conventional motors as the standard for power transfer, especially in dynamic applications like automobiles, more electric aircraft. This study explores a control technique to improve real-time control of brushless direct current motors in electric vehicles It presents speed control of these system for electric vehicle applications and an overview of electric vehicle technologies. A model for the 120-degree mode was developed using electrical and mechanical equations in MATLAB/Simulink. Three scenarios were examined to assess the potential of controlling brushless direct current motors using constant and dynamic speed and torque. The actual value reached the reference value in the first two scenarios.

The article presents development of the more electric turbofan engine in distributed architecture with a design thrust in the range from 3 to 7.5 and from 7.5 to 30 kN for small and medium-sized unmanned aerial vehicles. The engine subsystems are considered as separate smart modules with a built-in control system, exchanging data via a digital channel with the central engine control and diagnostics unit. The key smart engine units are combined in the following subsystems: starter and turbine generators, oil pumps, actuator of guide vanes, fuel pumps, fuel metering unit, control and diagnostic unit. All pumps and guide vane actuator are electrically driven. Control and monitoring signals are transmitted via a digital bus. Functional and reliability analysis, technical configuration design of each subsystem are presented. Based on analysis of the architecture of distributed control system for gearbox-free more electric engine, different configurations of described subsystems are proposed.

We report the case of a 44-year-old woman who suffered gastric perforation after receiving bag-valve-mask (BVM) ventilation in the setting of alcohol intoxication. She had a markedly distended abdomen and cold, dusky lower extremities upon arrival to the emergency department. Imaging revealed a large volume intraabdominal accumulation of air with compression of the aorta. Needle decompression relieved symptoms of lower extremity arterial insufficiency. However, the patient quickly decompensated and subsequent exploratory laparotomy confirmed gastric rupture. A subtotal gastrectomy was performed but the patient ultimately passed on post-operative day two due to multi-organ dysfunction. Although BVM ventilation is commonplace in both the hospital and field, there is a lack of awareness of the serious complications of abdominal air accumulation due to their rareness in the adult population. Checking for abdominal distention during resuscitation ought to be routine in all patients. Signs of arterial insufficiency accompanying abdominal distention, once confirmed by diagnostic imaging that shows extensive pneumoperitoneum, are indicators of having reached a life-threatening level of air accumulation, calling for immediate needle decompression and exploratory laparotomy.

The utilization of fuel cells (FC) in automotive technology has experienced significant growth in recent years. Fuel cell hybrid electric vehicles (FCHEVs) are powered by a combination of fuel cells, batteries, or/and ultracapacitors (UCs). By integrating power converters with these power sources, the FCHEV system can overcome the limitations of using them separately. The performance of an FCHEV is influenced by the efficiency of the power electronics converter controller, as well as the technical efficiency of the power sources. FCHEVs need intricate energy management systems (EMSs) to function effectively. Poor EMS can lead to low efficiency and accelerated fuel cell and battery degradation. The literature discussed various types of EMSs, such as equivalent consumption minimization strategy, classical PI controller, fuzzy logic controller, and Mutative Fuzzy Logic Controller (MFLC). However, comparing different EMSs can be challenging due to the varying vehicle and system parameters, which might lead to false claims being made regarding system performance. This research aims to categorize and discuss the various topologies of FCHEVs, highlighting their pros and cons, and comparing several EMSs based on performance metrics such as State of Charge (SOC) and FC deterioration.

Abstract: Peptide pools composed of short amino acid sequences have proven to be versatile tools in various research areas and clinical applications. They are powerful tools for epitope mapping, immunotherapy, and vaccine development. Their importance lies in their ability to map complex protein structures, enabling a comprehensive understanding of immune responses and facilitating the identification of potential therapeutic agents. The application of peptide pools also extends to the field of personalized medicine, offering tailored solutions for diseases such as cancer and infectious diseases. Peptide pools are complex mixtures of immunostimulatory antigens primarily intended for T-cell stimulation. They are commercially available in many different compositions and variants. However, unlike other reagents that consist of only one or a few compounds, peptide pools are highly complex products with limited stability. This makes their quality control a major challenge. Quantitative peptide analysis usually requires sophisticated methods, in most cases isotope-labeled standards and reference materials. None of these are routinely available for these products. Synthesis and purification of all labeled peptides might be required. Usually, this approach would be prohibitively laborious and expensive. Therefore, an approach is needed to provide a practical and feasible method for quality control of peptide pools. With insufficient quality control, the use of such products could lead to incorrect experimental results, which would worsen the well-known reproducibility crisis in the biomedical sciences. Here we propose the use of ultra-high performance liquid chromatography (UHPLC) with two detectors, a standard UV detector (at 214 nm) for quantitative analysis and a high-resolution mass spectrometer (HRMS) for identity confirmation. To be cost-efficient and fast, quantification and identification are performed in one chromatographic run. An optimized protocol is shown, and different peak integration methods are compared and discussed. This work was performed using a peptide pool known as CEF, which consists of 32 peptides derived from cytomegalovirus (CMV), Epstein-Barr virus (EBV) and influenza virus, ranging from 8 to 12 amino acids in length.

Accurate forecasting of icing thickness has a great significance for ensuring the security and stability of power grid. In order to improve the forecasting accuracy, this paper proposes an icing forecasting system based on fireworks algorithm and weighted least square support vector machine (W-LSSVM). The method of fireworks algorithm is employed to select the proper input features with the purpose of eliminating the redundant influence. In addition, the aim of W-LSSVM model is to train and test the historical data-set with the selected features. The capability of this proposed icing forecasting model and framework is tested through the simulation experiments using real-world icing data from monitoring center of key laboratory of anti-ice disaster, Hunan, South China. The results show that the proposed W-LSSVM-FA method has a higher prediction accuracy and it may be a promising alternative for icing thickness forecasting.

Degenerative mitral valve disease (DMVD) consists of progressive degeneration of the mitral valve that can occur either in isolation or in association with the tricuspid valve, leading to incomplete coaptation of its leaflets and subsequent valve regurgitation. It's the most common cardiac condition in small animals, accounting for about 75% of cases of heart disease in dogs, mainly affecting elderly small-breed dogs. Breeds with a genetic predisposition such as Cavalier King Charles Spaniels and Bull Terriers tend to develop the disease early. It can be classified into 4 stages: A, B, C, and D, with B having subdivisions (B1 and B2). Animals in stages A, B1, and B2 are asymptomatic, showing clinical signs only from stage C onwards. The report details the case of a 13-year-old Fox Terrier diagnosed at stage B2 of the disease, progressing to stage C within two years. A cardiologist conducted annual monitoring.

Cloud Computing is a promising and emerging technology that is rapidly being adopted by many IT companies due to a number of benefits that it provides, such as large storage space, low investment cost, virtualization, resource sharing, etc. Users are able to store a vast amount of data and information in the cloud and access it from anywhere, anytime on a pay-per-use basis. Since many users are able to share the data and the resources stored in the cloud, there arises a need to provide access to the data to only those users who are authorized to access it. This can be done through access control schemes which allow the authenticated and authorized users to access the data and deny access to unauthorized users. In this paper, a comprehensive review of all the existing access control schemes has been discussed along with analysis. Keywords: role-based access control, attribute-based access control, attribute-based encryption

Wearable technology has been proposed as a potential tool to change the way of human life, such as the smart bracelet and the Google Glass. In the wearable technology, the inertial sensor has great significance in tracking the object movements. The paper focused on detecting the movements of user’s finger based on the inertial sensor to give the control signals. Firstly, the attitude matrix, which represented the transformation relation of carrier coordinate system and the navigation coordinate system, was obtained. Secondly, the attitude matrix was expressed based on the quaternions. Thirdly, the finger gesture was processed by the attitude matrix to get the attitude angle. Finally, the robot was controlled by attitude angle to make the moving action. The experimental results showed the detection of the finger movement is effective.

Background. Recent studies revealed that differentiation of valvular interstitial cell into myofibroblasts played an important role in pathological valve remodeling in rheumatic valvular disease. Objective. To investigate effects of atorvastatin, olmesartan, and resveratrol on Transforming Growth Factor β1-induced fibrosis. Methods. Valvular interstitial cell was isolated from 12-weeks male New Zealand rabbit (Oryctolagus cuniculus). Culture cells was divided into 4 groups, control group, group I (0.5 mg/mL Atorvastatin), group II (100 nmol/L Olmesartan), group III (50 μM/L Resveratrol) and group IV (combinations). All group were exposed to 100 nM Transforming Growth Factor β1 for 24 hours. Results. Immunochemical staining demonstrated that cells were completely differentiated into myofibroblasts with mean expression of α-smooth muscle actin 24522.64±4566.994. Atorvastatin, olmesartan, resveratrol, and its combination significantly reduced α-smooth muscle actin expression (6823±1735.3, 6942.7±2455.9, 14176.2±3343.3, 5051.8±1612.2 respectively (p&lt;0.001). Conclusion. Our data showed atorvastatin, olmesartan, resveratrol, and its combination significantly reduce Transforming Growth Factor β1-induced valvular fibrosis.

Diesel engines, as power equipment, are widely used in the fields of automobile industry, ship and power equipment. Due to wear or faulty adjustment, the valve train clearance abnormal fault is a typical failure of diesel engines, which may result in the performance degradation, even valve fracture and cylinder hit fault. However, the failure mechanism features mainly in time domain and angular domain, on which the current diagnosis methods based, are easily affected by working conditions or hard to extract accurate enough, as the diesel engine keeps running in transient and non-stationary process. This work arms at diagnosing this fault mainly based on frequency band features which would change when the valve clearance fault occurs. For the purpose of extracting a series of frequency band features adaptively，a decomposition technique based on improved variational mode decomposition is investigated in this work. As the connection between the features and the fault is fuzzy, the random forest algorithm is used to analyze the correspondence between features and faults. In addition, the feature dimension is reduced to improve the operation efficiency according to importance score. The experimental results under variable speed condition show that the method based on variational mode decomposition and random forest is capable to detect valve clearance fault effectively.

This work aims to study and analyze a hybrid power system for electric vehicles consisting of a dual low and high-rate lithium battery block and a fuel cell. In this configuration, the high-rate lithium battery powers the electric vehicle in high power demand processes like acceleration mode or on an uphill road; the low-rate battery operates at a low output power range, servicing the auxiliary systems and low power loads and the fuel cell supplies energy at intermediate power demand conditions, normal driving mode, constant velocity, or flat and downhill terrain. The dual power system improves global efficiency since every power unit operates optimally depending on driving conditions. Power sharing optimizes the lithium battery performance and fuel cell capacity, minimizing the size and weight of each energy system and enlarging the driving range. A comparative study between different lithium battery configurations and fuel cell shows an efficiency improvement of 31.4% for the hybrid dual battery block and fuel cell operating in low, high, and intermediate output power ranges, respectively. The study bases on a simulation process recreating current driving conditions for electric cars in urban, peripheral, and intercity routes. An alternative solution consisting of a hybrid system, fuel cell and a high rate lithium battery produces a 29 % power gain.

In this study, a novel two-layer control scheme aimed at enhancing the dynamic performance of a nonlinear vehicle through the utilization of an optimal control approach grounded in predictive control principles is presented. The first layer of our control system focuses on the computation of an optimized rotational torque that ensures lateral dynamic stability. This torque is subsequently translated into differential forces acting on the wheels, employing the inverse tire model to derive the desired longitudinal slips. These slip values are then transmitted to the second layer of our control system. In the second layer, the electric motors associated with the vehicle's wheels dynamically adjust the input torque to accurately track the desired slip, thereby ensuring the overall stability of the electric vehicle. In view of the paramount importance of energy consumption in electric vehicles, we adopt optimal control strategies to substantially minimize battery utilization. To this end, careful selection of appropriate weighting coefficients in the control laws enables us to maintain the electric motors within their permissible operational range while simultaneously minimizing battery energy consumption for desired slip tracking. Extensive simulation results validate the effectiveness of our proposed control system in proficiently managing nonlinear effects and safeguarding the vehicle's stability.

Although many devices have recently been proposed for pressure regulation and energy harvesting in water distribution and transport networks, very few applications are still documented in the scientific literature. A new in-line Banki turbine with positive outflow pressure and a mobile regulating flap, named PRS, was installed and tested in a real water transport network for pressure and discharge regulation. The PRS turbine was directly connected to a 55 kW asynchronous generator with variable rotational velocity, coupled to an inverter. The start-up tests showed how automatic adjustment of the flap position and the impeller velocity variation are able to change the characteristic curve of the PRS according to the flow delivered by the water manager or to the pressure set-point assigned downstream or upstream of the system, still keeping good efficiency values in hydropower production.

This work reports 60 marine alien molluscs, collected by two Belgian citizen scientists, from nine countries across the Mediterranean Sea and the Sea of Marmara. Some of their published observations concerning the collecting dates are compared with the year of first publication for these alien molluscs reported in the literature, which enabled to backdate some of these introductions. This underlines the importance of collaboration between volunteers and institutional scientists in tracing variations and changes in the environment and biodiversity.

This paper presents experimental identification and vibration suppression of a flexible manipulator with non-collocated piezoelectric actuators and strain sensors using optimal multi-poles placement control. To precisely identify the system model, a reduced order transfer function with relocated zeros is proposed, and a first-order inertia element is added to the model to compensate the non-collocation. Comparisons show the identified model match closely with the experimental results both in the time and frequency domains, and a fit of 97.2% is achieved. Based on the identified model, a full-state multi-poles placement controller is designed, and the optimal locations of the closed loop poles are determined. The feasibility of the proposed controller is validated by simulations. Moreover, the controller is tested for different locations of the closed loop poles, and an excellent performance of the optimal locations of the closed loop poles is shown. Finally, the effectiveness of the proposed controller is demonstrated by experiments. Results show that the vibrations of the expected modes are significantly diminished. Besides, vibrations of the higher modes are also slightly suppressed. Accordingly, multi-mode vibrations of the manipulator are well attenuated, and the tip displacement converges quickly with the proposed method.

Background: COVID-19 pneumonia caused by SARS-Cov-2 virus induces alveolar collapse and hypoxia that may become severe. The aim of the study is to analyze the effects of chest physiotherapy using a threshold valve in patients with acute respiratory failure due to COVID-19 pneumonia. Methods; Retrospective observational study, in hospitalized patients from March to May 2020. Breathing exercises were performed with a threshold valve of 10 cmH2O. Fraction of inspired oxygen, oxygen saturation, heart rate, respiratory rate and dyspnea were collected before and after the first session and at the end of the 5th day of chest physiotherapy treatment. Results: The final sample included 125 patients. Significant differences (p&lt;0.01) were found in the pre-post intervention SpO2/FiO2 ratio (250±88.4 vs 275.6±97.5, p&lt;0.001), reaching 354.4±110.2 after 5 days of therapy (p&lt;0.001 with respect to baseline). Mean baseline respiratory, heart rate and level of dyspnea measure by the Borg scale did not change during the technique performance. In patient maneuvers with FiO2&gt;0.4, the SaO2/FiO2 ratio increase was higher than in patients with milder severity (46.85 ± 77.69, p&lt;0.01). Conclusions: Chest physiotherapy with a 10 cmH2O threshold valve is a safe and tolerated intervention with short-term improvement in oxygenation in patients with COVID-19 pneumonia.

Background: This study discerns surgeons’ attitudes and practices in the determination of heart valve replacement for patients with endocarditis due to intravenous drug use (IVDU-IE). We aimed to identify factors contributing to surgeons’ decision-making process for initial and recurrent surgical heart valves, and the availability of institutional guidance. Methods: An IRB approved, anonymous mixed-methods survey instrument was designed and validated with 24 questions. Cardiothoracic surgeons in the U.S. and globally were recruited with a total of 220 enrolling in the study with 176 completing every question on the survey. Results: A cluster analysis revealed that although surgeons can be divided into sub-groups based on their previous experience with valve replacements, these groups are not perfectly homogenous, and the number of identified clusters is dependent on technique used. ANOVA analysis revealed that the variables that most clearly divided the surgeons into subgroups were, in order of importance, years of practice, number of valve replacements, and geography. Conclusions: Our analysis showed heterogeneity among cardiothoracic surgeons regarding how they make clinical decisions regarding re-operative valve replacement related to IVDU-IE Therefore, an opportunity exists for an interprofessional team to develop guidelines to decrease variability in surgical decision-making regarding valve replacement associated with IVDU-IE

Due to the nonlinear stiffness and fractional-order damping characteristics of some real suspension systems, coupled with the presence of viscoelastic materials, fractional-order nonlinear suspension system modeling has become a focus of research in recent years. In this study, an electric oil and gas actuator based on fractional-order PID position feedback control is proposed, through which the damping coefficient of the suspension system is adjusted to realize the active control of the suspension. A fractional order PID algorithm is used to control the motor's rotational angle to realize the damping adjustment of the suspension system. In this process, the road roughness is collected by the sensors as the criterion of damping adjustment, and the particle swarm algorithm is utilized to find the optimal objective function under different road surface slopes, to obtain the optimal cornering value. According to the mathematical and physical model of the suspension system, the simulation model and the corresponding test platform of this type of suspension system are built. The simulation and experimental results show that the simulation results of the fractional-order nonlinear suspension model are closer to the actual experimental values than those of the traditional linear suspension model, and the accuracy of each performance index is improved by more than 18.5%. The designed active suspension system optimizes the body acceleration, suspension dynamic deflection, and tire dynamic load to 89.8%, 56.7%, and 73.4% of the passive suspension, respectively. Notably, the designed fractional order PID control circuit for the motor shows better control results compared to the conventional PID control circuit. This study provides an effective theoretical and empirical basis for the control and optimization of fractional-order nonlinear suspension systems.

Abstract: The article proposes to consider the possibility of connecting the problems of engineering synthesis of frequency control systems for asynchronous electric drives with the basic provisions of the theory of identification of asynchronous electric motors based on the equations of a generalized AC electric machine.The article presents the results of experimental studies of load parrying processes in asynchronous electric drives with vector and scalar controls. These results indicate the absence of fundamental advantages as processes in a drive with vector control. This advantage should have manifested itself in a more efficient formation of the moment and fast transients. It is suggested that the reason for this is in too significant errors, assumptions and simplifications of the equations adopted in the derivation of vector control and which are its theoretical basis. A method is proposed for describing asynchronous electric motors by nonlinear transfer functions, which made it possible to formulate the principle of correction of electric drives and a method for assessing their efficiency.The article shows. that the correction based on the proposed nonlinear transfer functions of the induction motor is much more efficient than the traditional vector control, which was confirmed by detailed experiments and modeling. The results of the most important of which are given in the article. An assumption was made. that the advantage in efficiency is due to a more accurate identification of the dynamics of an asynchronous electric motor with a gear function instead of vector equations.

Transcatheter aortic valve replacement (TAVI) improves event-free survival in patients with severe aortic stenosis, but patients’ exercise capacity remains poor after the procedure. Therefore, we sought to compare the effects of supervised centre-based exercise training program and unsupervised exercise routine on exercise capacity and vascular function in patients after TAVI. Patients were randomised to either centre-based exercise training (12-24 sessions of combined aerobic and low-weight resistance training twice weekly for 8-12 weeks) or unsupervised home-based exercise routine (initial appraisal with detailed recommendations and monthly follow-up). Exercise capacity (cardiopulmonary testing) and vascular function (ultrasonographic measurement of flow-mediated vasodilation [FMD] and arterial stiffness) were assessed at baseline and after the study period. We included 23 patients (mean age 81 years, 61% women), with higher-than-expected drop-out rates (41%) because of the coronavirus-19 pandemic outbreak. Exercise capacity improved over time, irrespective of intervention group: 0.09 ml/min/kg increase in peak oxygen uptake (95%CI [0.01-0.16]; p=0.02), 8.2 Watts increase in workload (95%CI [0.6-15.8]; p=0.034), and 47 seconds increase in cumulative exercise time (95% CI [5.0-89.6]; p=0.029). A between-group difference in change over time (treatment effect) was detected only for FMD (4.49%; 95% CI [2.35; 6.63], p &lt; 0.001), but not for other outcome variables. Both supervised and unsupervised exercise training improve exercise capacity and vascular function in patients after TAVI, with supervised exercise training possibly yielding larger improvements in vascular function, as determined by FMD.