Traditional high pressure mechanical compressors account for over half of the car station’s cost, have insufficient reliability and are not feasible for a large-scale fuel cell market. An alternative technology, employing a two-stage, hybrid system based on electrochemical and metal hydride compression technologies, represents an excellent alternative to conventional compressors. The high-pressure stage, operating at 100-875 bar, is based on a metal hydride thermal system. A techno-economic analysis of the metal hydride system is presented and discussed. A model of the metal hydride system was developed, integrating a lumped parameter mass and energy balance model with an economic model. A novel metal hydride heat exchanger configuration is also presented, based on mini-channel heat transfer systems, allowing for effective high-pressure compression. Several metal hydrides were analyzed and screened, demonstrating that one selected material, namely (Ti_0.97Zr_0.03)_1.1Cr_1.6Mn_0.4, is likely the best candidate material to be employed for high-pressure compressors under the specific conditions. System efficiency and costs were assessed based on the properties of currently available materials at industrial levels. Results show that the system can reach pressures on the order of 875 bar with thermal power provided at approximately 150 °C. The system cost is comparable with the current mechanical compressors and can be reduced in several ways as discussed in the paper.

Starting from the model of a slow-rolling missile with six degrees of freedom (6 DOF) in the body frame, a 6 DOF model in the Resal frame is obtained, which is used to linearize the coupled commanded motion. Based on the linearized model, we obtain the structural scheme of the commanded object and define the quality parameters. The obtained parameters have a complex representation (with real and imaginary parts) due to the coupling between longitudinal channels. Then, the kinematic guidance equations, the seeker equations and the actuator specific to the slow-rolling single-channel missile are defined using a switching function. The guidance kinematic equations, the seeker equations and the actuator model are linearized in the Resal frame, and the structural diagram of the homing missile is constructed. Starting from this, the characteristic polynomial having complex coefficients is determined and then analyzed with the Frank-Wall stability criterion. Based on the analysis, a stability range is determined for the navigation constant and a minimum and possibly a maximum limit for the time to hit the target is obtained. The stability range defined for the navigation constant on the linear model is finally validated on the nonlinear model in the body frame.

Dietary intake of omega-3 polyunsaturated fatty acids (eicosapentaenoic acid, EPA) exerts antiarrhythmic effects, although the mechanisms are poorly understood. Here we investigated the possible beneficial actions of EPA on saturated fatty acid-induced changes of the L-type Ca2+ channel in cardiomyocytes. Cardiomyocytes were cultured with oleic acid/palmitic acid mixture (OAPA) in the presence or absence of EPA. Beating rate reduction of cardiomyocytes caused by OAPA were reversed by EPA. EPA also retrieved a reduction of Cav1.2-L-type Ca2+ current, mRNA and protein caused by OAPA. Immunocytochemical analysis revealed a distinct downregulation of the Cav1.2 channel caused by OAPA with a concomitant decrease in the phosphorylated component of a transcription factor adenosine-3’, 5’-cyclic monophosphate (cAMP) response element binding protein (CREB) in the nucleus, which were rescued by EPA. A free fatty acid receptor 4 (FFAR4) agonist TUG-891 reversed expression of Cav1.2- and CREB-mRNA caused by OAPA, whereas an FFAR4 antagonist AH-7614 abolished the effects of EPA. Excessive reactive oxygen species (ROS) accumulation caused by OAPA decreased Cav1.2- and CREB-mRNA expressions, which were reversed by an ROS scavenger. Our data suggest that EPA rescues cellular remodeling caused by OAPA lipotoxicity and oxidative stresses via both free fatty acid receptor 4-dependent and -independent pathways.

Loss of photoreceptors in retinal degenerative diseases also impacts the inner retina: bipolar cell dendrites retract, neurons rewire and protein expression changes. ON-bipolar cells represent an attractive target for optogenetic vision restoration. However, above-described maladaptations may negatively impact the quality of restored vision. To investigate this question, we employed human post-mortem retinas and transgenic rd1_Opto-mGluR6 mice expressing the optogenetic construct Opto-mGluR6 in ON-bipolar cells and carrying the retinal degeneration rd1 mutation. We found significant changes in delayed rectifier potassium channel expression in ON-bipolar cells of degenerative retinas. In particular, we found an increase in Kv1.3 expression already in early stages of degeneration. Immunohistochemistry localized Kv1.3 channels specifically to OBC axons. In whole-cell patch-clamp experiments, ON-bipolar cells in the degenerated murine retina were less responsive, which could be reversed by application of the specific Kv1.3 antagonist Psora-4. Notably, Kv1.3 block significantly increased the amplitude and kinetics of Opto-mGluR6-mediated light responses in ON-bipolar cells of the blind retina and increased the signal-to-noise ratio of light-triggered responses in retinal ganglion cells. We propose that reduction of Kv1.3 activity in the degenerated retina, either by pharmacological block or by KCNA3 gene silencing, could improve the quality of restored vision.

Due to the special characteristics of the shooting distance and angle of remote sensing satellites, the pixel area ratio of ship targets is small and the feature expression is insufficient, which leads to unsatisfactory ship detection performance and even situations such as missed detection and false detection. In this study, we propose an improved-YOLOv5 algorithm. The improvement strategies mainly include: (1) Add the Convolutional Block Attention Module (CBAM) into the Backbone to enhance the extraction of target-adaptive optimal features; (2) Introduce cross-layer connection channel and lightweight GSConv structure into the Neck to achieve higher-level multi-scale feature fusion and reduce the number of model parameters; (3) The Wise-IoU loss function is used to cal-culate the localization loss in the Output, and assign reasonable gradient gains to cope with dif-ferences in image quality. In addition, during the preprocessing stage of experimental data, a me-dian and bilateral filter method is used for noise reduction to reduce interference from ripples and waves and highlight the information of ship features. The experimental results show that Im-proved-YOLOv5 has a significant improvement in recognition accuracy compared to various mainstream target detection algorithms; Compared to the original YOLOv5s, the mean Average Precision (mAP) has improved by 3.2% and the Frames Per Second (FPN) has accelerated by 8.7%.

Human Face and facial parts are the most significant parts as it reveals a person’s true identity. It plays an important role in various biometric applications like crowd analysis, human tracking, photography, cosmetic surgery, etc. There are many techniques are available to detect a facial image. Among them, skin detection is the most popular one. The aim of this paper is to detect first the person's identity from facial image and finally check any spot present the the detected person. The first step is to detect the maximum skin region based on a combination method of RGB and HSV color space model. Next it is to verify the skin areas of human through machine learning approach. The Aggregated Channel Features (ACF) detector is used to identify the different facial parts like eye pairs, nose, and mouth. Bootstrap aggregation decision tree classifier is applied to classify the person’s identity based on Histogram Oriented Gradient (HOG) features value. The experimental results show that the proposed method gives the average 97% accuracy.

: E-commerce sales surge represents a huge challenge for urban freight transport. Parcel lockers constitute a valid solution for addressing the challenges home deliveries imply. In fact, eliminating courier-consumer contact (also relevant for health-related issues, as made evident by COVID19 pandemic) and delivering in few predefined places might help coping with missed deliveries substantially. Furthermore, this option enables consolidated shipping and reducing delivery trip costs. This paper analyses and compares consumers’ preferences for alternative collection strategies. It investigates home delivery vs parcel locker use and forecasts their future market shares. This is performed based on both customers’ socio-economic variables and attributes characterising these alternative logistic fulfilment strategies. The case study considered rests upon a stated preference survey deployed in the city of Rome. The investigation specifically targets young people (i.e., population under 30 years) since they represent early adopters. Discrete choice models allow both quantifying the monetary value of parcel lockers attributes (i.e., willingness to pay measures) and estimating the potential demand for this innovative delivery scheme. Results show that distance and accessibility are the main choice determinants. Furthermore, there is an overall high propensity to adopt parcel lockers. This research can support policymakers when implementing such solutions.

Psychiatric disorders are mental, behavioral or emotional disorders. These conditions are prevalent, one in four adults suffer from any type of psychiatric disorders world-wide. It has always been observed that psychiatric disorders have a genetic component, however new methods to sequence full genomes of large cohorts have identified with high precision genetic risk loci for these conditions. Psychiatric disorders include, but are not limited to, bipolar disorder, schizophrenia, autism spectrum disorder, anxiety disorders, major depressive disorder, and attention-deficit and hyperactivity disorder. Several risk loci for psychiatric disorders fall within genes that encode for voltage-gated calcium channels (Ca_Vs). Calcium entering through Ca_Vs is key for multiple neuronal processes. In this review, we will summarize recent findings that link Ca_Vs and their auxiliary subunits to psychiatric disorders. First, we will provide a general overview of Ca_Vs structure, classification, function, expression and pharmacology. Next, we will summarize tools and databases to study risk loci associated with psychiatric disorders. We will examine functional studies of risk variations in Ca_V genes when available. We will review pharmacological evidence of the use of Ca_V modulators to treat psychiatric disorders. Our review will be of interest for those studying pathophysiological aspects of Ca_Vs.

Nowadays, brain signal processing is performed rapidly in various brain-computer interface (BCI) applications. Most researchers focus on developing new methods for the future or improving the basic implemented models to identify the optimum standalone feature set. Our research focuses on four ideas. One of them introduces future communication models, and the others are for improving old models or methods. These are: 1) new communication imagery model instead of speech imager using the mental task: Due to speech imagery is very difficult, and it is impossible to imagine sound for all of the characters in all of the languages. Our research introduces a new mental task model for all languages that call Lip-sync imagery. This model can use for all characters in all languages. This paper implemented two lip-sync for two sounds, characters or letters. 2) New combination Signals: Selecting an inopportune frequency domain can lead to inefficient feature extraction. Therefore, domain selection is so important for processing. This combination of limited frequency ranges proposes a preliminary for creating Fragmentary Continuous frequency. For the first model, two s intervals of 4 Hz as filter banks were examined and tested. The primary purpose is to identify the combination of filter banks with 4Hz (scale of each filter bank) from the 4Hz to 40Hz frequency domain as new combination signals (8Hz) to obtain well and efficient features using increasing distinctive patterns and decreasing similar patterns of brain activities.3) new supplement bond graph classifier for SVM classifier: When SVM linear uses in very noisy, the performance is decreased. But we introduce a new bond graph linear classifier to supplement SVM linear in noisy data. 4) a deep formula recognition model: it converts the data of the first layer into a formula model (formula extraction model). The main goal is to reduce the noise in the subsequent layers for the coefficients of the formulas. The output of the last layer is the coefficients selected by different functions in different layers. Finally, the classifier extracts the root interval of the formulas, and the diagnosis does based on the root interval. For all of the ideas achieved the results of implementing methods. The results are between 55% to 98%. Less result is 55% for the deep detection formula, and the highest result is 98% for new combination signals.

In this paper, we proposed a novel saddle type FinFET (S-FinFET) to effectively solve problems occurring under the capacitor node of dynamic random-access memory (DRAM) cell and showed how its structure was superior to conventional S-FinFETs in terms of short channel effect (SCE), subthreshold slope (SS), and gate-induced drain leakage (GIDL). The proposed FinFET exhibited 4 times lower Ioff than modified S-FinFET called RFinFET with more improved DIBL characteristics while minimizing Ion reduction compared to RFinFET. Our results also confirmed that the proposed device showed improved DIBL and Ioff characteristics as gate channel length decreased.