Terms Of Leakage Research Articles

Conception of nanosized hybrid liposome/poloxamer particles to thicken the interior core of liposomes and delay hydrophilic drug delivery.

Liposomes are nanocarriers composed of phospholipids, especially designed to potentially carry drugs. However, liposomes suffer in terms of leakage of small hydrophilic drugs. To control the release, a system with lipid shell and polymeric viscous core, namely Hybrid liposome/polymer inside (HLPin), has been designed. For this purpose, we setup a syringe pump apparatus equipped with homemade tubing system. HLPin formulation consisting of poloxamer (5% w/v) was found to be optimal when produced at injection rates of 5 mL.min-1. Then, we tend to characterize the HLPin with DLS, TEM, TRPS, thermal analysis and densitometry in comparison with a polymer added after formation of the liposomes. The optimal formulation was evaluated for its stability and cytotoxicity. The selected conditions and composition resulted in nanocarriers which are highly reproducible with mono-disperse size distribution with an average size of 206 ± 4.8 nm and a polydispersity index of 0.15 ± 0.015. Densitometry and thermal analysis results confirmed the formation of HLPin. Interestingly, HLPin were stable over 2 months, produced no cytotoxicity and exhibited slow release of rhodamine and Doxorubicin in comparison to liposome formulation. Our homemade tubing system coupled with syringe pump apparatus achieved reproducible, precisely controlled production for the HLPin formulation which can be scale up.

Realizing a Planar 4H-SiC Junctionless FET for Sub-10-nm Regime Using P+ Pocket

In this paper, using calibrated device simulations, we propose the use of a P± pocket at channel-drain and channel-source interfaces in 4H-SiC junctionless FET (4H-SiC p-JLFET) to achieve efficient volume depletion in the sub-10-nm regime; thus relaxing the need of channel thickness scaling or the use of complex device architectures. The P± pocket improves the OFF-state current (IOFF) by ~ 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">9</sup> , while slightly degrading the ON-state current (ION) and subthreshold slope (SS) for a 7-nm channel length device. This large gain in IOFF presents the possibility of realizing multiple threshold voltage (VTH) devices by tuning the metal-gate work function, which helps in creating optimized designs in terms of area, power, leakage, and performance, which is not possible in Si JLFETs, due to their need of high metal-gate work functions to achieve volume depletion even at larger channel lengths. The 4H-SiC p-JLFET gives ~1pA/μm IOFF even at an elevated temperature of 600 K. We also discuss the scaling of the SiC p-JLFETs for 7-and 5-nm channel length.

Analysis of discharge process of oil pipeline with complex topography

During the commissioning process of ”first injection of crude oil after water injection”, due to the density difference between crude oil and water, the oil pressure on the left side of the ”U” section is less than the right hydraulic pressure, and the running process of the oil head is stagnated in a hilly oil pipeline with high elevation difference. Concerning this problem, solution of discharging pressure by using relief valve in valve station nearby oil–water interfacial point is proposed in this paper. According to the actual data, gas–liquid flow in a gas-cap empty process of a big drop and hilly oil pipeline was numerically investigated by dynamic multiphase simulation software OLGA. Simulation data in terms of flow rate, pressure and leakage were compared under different leaking apertures. The simulation results show that the general pressure variation tendencies at the vent, bottom point or top and low elbows show no connection with vent diameters but its final fluctuation that the smaller the diameter is, the more intensive the fluctuation gets.. And as for the emptying of a big drop and hilly pipeline, appropriate increase of leaking aperture can improve the drainage ratio (leakage/general capacity of the pipeline) and drainage rate, but excessive aperture will cause severe negative pressure and breakage cavity which foster the likelihood of close water-surge and damage to the pipe safety.

A new approach for solution of time dependent neutron transport equation based on nodal discretization using MCNPX code with feedback

This paper proposes a new method for solving the time-dependent neutron transport equation based on nodal discretization using the MCNPX code. Most valid nodal codes are based on the diffusion theory with differences in approximating the leakage term until now. However, the Monte Carlo (MC) method is able to estimate transport parameters without approximations usual in diffusion method. Therefore, improving the nodal approach via the MC techniques can substantially reduce the errors caused by diffusion approximations. In the proposed method, the reactor core is divided into nodes of arbitrary dimensions, and all terms of the transport equation e.g. interaction rates and leakage ratio are estimated using MCNPX. They are then employed within the time-dependent neutron transport equation for each node independently to compute the neutron population. Based on this approach, a time-dependent code namely MCNP-NOD (MCNPX code based on a NODal discretization) was developed for solving time-dependent transport equation in an arbitrary geometry considering feed backs. The MCNP-NOD is able to simulate multi-group processes using appropriate libraries. Several test problems are examined to evaluate the method.

Just the tonic! Legume biorefining for alcohol has the potential to reduce Europe's protein deficit and mitigate climate change

Industrialised agriculture is heavily reliant upon synthetic nitrogen fertilisers and imported protein feeds, posing environmental and food security challenges. Increasing the cultivation of leguminous crops that biologically fix nitrogen and provide high protein feed and food could help to address these challenges. We report on the innovative use of an important leguminous crop, pea (Pisum sativum L.), as a source of starch for alcohol (gin) production, yielding protein-rich animal feed as a co-product. We undertook life cycle assessment (LCA) to compare the environmental footprint of 1 L of packaged gin produced from either 1.43 kg of wheat grain or 2.42 kg of peas via fermentation and distillation into neutral spirit. Allocated environmental footprints for pea-gin were smaller than for wheat-gin across 12 of 14 environmental impact categories considered. Global warming, resource depletion, human toxicity, acidification and terrestrial eutrophication footprints were, respectively, 12%, 15%, 15%, 48% and 68% smaller, but direct land occupation was 112% greater, for pea-gin versus wheat-gin. Expansion of LCA boundaries indicated that co-products arising from the production of 1 L of wheat- or pea-gin could substitute up to 0.33 or 0.66 kg soybean animal feed, respectively, mitigating considerable greenhouse gas emissions associated with land clearing, cultivation, processing and transport of such feed. For pea-gin, this mitigation effect exceeds emissions from gin production and packaging, so that each L of bottled pea gin avoids 2.2 kg CO2 eq. There is great potential to scale the use of legume starches in production of alcoholic beverages and biofuels, reducing dependence on Latin American soybean associated with deforestation and offering considerable global mitigation potential in terms of climate change and nutrient leakage — estimated at circa 439 Tg CO2 eq. and 8.45 Tg N eq. annually.

Passivity and passification of memristive neural networks with leakage term and time-varying delays

This paper investigates passivity and passification for memristive neural networks (MNNs) with both leakage and time-varying delays. MNNs are converted into traditional neural networks (NNs) by nonsmooth analysis, then sufficient conditions are derived to guarantee the passivity based on Lyapunov method. A novel Lyapunov–Krasovskii functional (LKF) is constructed without requiring all the symmetric matrices to be positive definite. The relaxed passivity criteria with less conservativeness or complexity are obtained in the form of linear matrix inequalities (LMIs), which can be verified easily by the LMI toolbox. Then, the passification controller is designed with the relaxed criteria to ensure that MNNs with both leakage and time-varying delays are passive. Finally, two pertinent examples are presented to show the effectiveness of the theoretical results.

Laparoscopic liver resection in elderly patients: systematic review and meta-analysis.

Laparoscopic liver resection (LLR) is becoming standard practice, replacing the open approach in terms of safety and feasibility. However, few data are available for the elderly. The objective of this study is to assess the feasibility of LLR in elderly patients, by making a comparison with open liver resection (OLR) and with non-elderly patients. Relevant studies found in the Cochrane Library, Embase, PubMed, and Web of Science were used in order to perform a systematic review and meta-analysis. Nine fully extracted comparative studies were included and two groups were identified: Group 1 with a comparison between OLR and LLR in the elderly and Group 2 with a focus on differences after LLR between elderly and non-elderly patients. A total number of 497 elderly patients who underwent LLR were analyzed. A random effect model was used for the meta-analysis. In Group 1, 1025 elderly patients were included: 640 underwent OLR and 385 underwent LLR. LLR was associated with minor blood loss (MD - 240mL, 95% CI - 416.61, - 63.55; p 0.008; I2 = 96%), less transfusion (8% vs. 13.1%; RR 0.61, 95% CI 0.41, 0.91; p = 0.02; I2 = 0%), fewer postoperative Clavien-Dindo III/IV complications (RR 0.48 in favor of LLR; 95% CI 0.29, 0.77; p = 0.003; I2 = 0%). On the other hand, no significant difference was observed in terms of bile leakage, ascites, mortality, liver failure, or R0 resection. Group 2 included 112 elderly and 276 non-elderly patients who underwent LLR. The meta-analysis showed no significant difference in terms of blood loss, transfusions, liver failure, Clavien-Dindo III/IV complications, postoperative mortality, ascites, bile leak, hospital stay, R0 resection, and operative time. Laparoscopic liver resection is a safe and feasible procedure for elderly patients. However, further randomized studies are required to confirm this.

Negative CO2 emissions - An analysis of the retention times required with respect to possible carbon leakage

With present emissions the global CO2 budget associated with a maximum temperature increase of about 1.5–2 °C will likely be spent within a few decades, Thus, it will be very difficult or perhaps even impossible to meet the climate targets agreed upon in Paris only by decreasing emissions of greenhouse gases. Scenarios presented in the IPCC reports accommodate for this by introducing so-called negative CO2 emissions. The idea is that the cumulative CO2 emission budget will be exceeded, but that massive negative emissions, especially during the latter part of the century, will remove the surplus of CO2 in the atmosphere.A number of different Negative Emissions Technologies (NETs) have been proposed, including Biomass Energy with Carbon Capture and Storage (BECCS), afforestation/reforestation, altered agricultural practices, biochar production, enhanced weathering and direct air captured. However, many of the options proposed could be associated with carbon leakage which could compromise the purpose of negative emissions, e.g. storage in of carbon in growing/dead biomass that leaks to the atmosphere. Furthermore, it may be difficult to safely assess the long-term leakage rates. To reach the large negative emissions needed it is expected to require a mix of approaches having different expected retention times, and different safety in terms of leakage rates.Could the risk of leakage mean that we are just delaying the problem and transferring the problem to coming generations? The short answer to this is that it all depends on the leakage rates. Different leakage rates and mixes of leakage rates are investigated in the paper. For the case of a mixture of leakage time scales of 300, 1000 and 10,000 years and assuming that 80% or more was permanently stored, the contribution to the atmospheric stock was small, peaking at about 3 ppm CO2. It was concluded that leakage would not significantly compromise the benefits of negative emissions unless leakage is substantial and rapid. To quantify what could be meant by substantial and rapid, an example would be if 100% of the CO2 stored would leak out at a rate of the order of 1%/year.

Reduction of Electron Leakage in a Deep Ultraviolet Nitride Laser Diode with a Double-Tapered Electron Blocking Layer**Supported by the National Key Research and Development Program under Grant No 2016YFE0118400, the Key Project of Science and Technology of Henan Province under Grant No 172102410062, the National Natural Science Foundation of China under Grant No 61176008, and the National Natural Science Foundation

A double-tapered AlGaN electron blocking layer (EBL) is proposed to apply in a deep ultraviolet semiconductor laser diode. Compared with the inverse double-tapered EBL, the laser with the double-tapered EBL shows a higher slope efficiency, which indicates that effective enhancement in the transportation of electrons and holes is achieved. Particularly, comparisons among the double-tapered EBL, the inverse double-tapered EBL, the single-tapered EBL and the inverse single-tapered EBL show that the double-tapered EBL has the best performance in terms of current leakage.

Robust Adaptive Path Following Control of an Unmanned Surface Vessel Subject to Input Saturation and Uncertainties

This paper investigates the path following control problem of an unmanned surface vessel (USV) subject to input saturation and uncertainties including model parameters uncertainties and unknown time-varying external disturbances. A nonlinear robust adaptive control scheme is proposed to address the issue, more specifically, steering a USV to follow the desired path at a certain velocity assignment despite the involved disturbances, by utilizing the finite-time currents observer based line-of-sight (LOS) guidance and radial basis function neural networks (RBFNN). Backstepping and Lyapunov’s direct method are the main design frameworks. Based on the finite-time currents observer and adaptive control technique, an improved LOS guidance law is proposed to obtain the desired approaching angle to the desired path, making compensations for the effects of unknown time-varying ocean currents. Then, a kinetic controller with the capability of uncertainties estimation and disturbances rejection is proposed based on the RBFNNs, where the adaptive laws including leakage terms estimate the approximation error and the unknown time-varying disturbances. Subsequently, sophisticated auxiliary control systems are employed to handle input saturation constraints of actuators. All error signals of the closed-loop system are proved to be locally uniformly ultimately bounded (UUB). Numerical simulations demonstrated the effectiveness and robustness of the proposed path following control method.

Finite-time stabilization of uncertain delayed-hopfield neural networks with a time-varying leakage delay via non-chattering control

This article is concerned with the finite-time stabilization (FTSB) of a class of delayed-Hopfield neural networks with a time-varying delay in the leakage term in the presence of parameter uncertainties. To accomplish the target of FTSB, two new finite-time controllers are designed for uncertain delayed-Hopfield neural networks with a time-varying delay in the leakage term. By utilizing the finite-time stability theory and the Lyapunov-Krasovskii functional (LKF) approach, some sufficient conditions for the FTSB of these neural networks are established. These conditions, which can be used for the selection of control parameters, are in the form of linear matrix inequalities (LMIs) and can be numerically checked. Additionally, an upper bound of the settling time was estimated. Finally, our theoretical results are further substantiated by two numerical examples with graphical illustrations to demonstrate the effectiveness of the results.

Robust adaptive control for unmatched systems with guaranteed parameter estimation convergence

SummaryThis paper provides a modified model reference adaptive control (MRAC) scheme to achieve better transient control performance for systems with unknown unmatched dynamics, where an adaptive law with guaranteed convergence is introduced. We first revisit the standard MRAC system and analyze the tracking error bound by using L2‐norm and Cauchy‐Schwartz inequality. Based on this analysis, we suggest a feasible way to compensate the undesired transient dynamics induced by the gradient descent–based adaptive laws subject to sluggish convergence or even parameter drift. Then, a modified adaptive law with an alternative leakage term containing the parameter estimation error is developed. With this adaptive law, the convergence of both the estimation error and tracking error can be proved simultaneously. This enhanced convergence property can contribute to deriving smoother control signal and improved control response. Moreover, this paper provides a simple and numerically feasible approach to online verify the well‐known persistent excitation condition by testing the positive definiteness of an introduced auxiliary matrix. Comparative simulations based on a benchmark 3‐DOF helicopter model are given to validate the effectiveness of the proposed MRAC approach and show the improved performance over several other MRAC schemes.

Effect of leakage delay on finite time boundedness of impulsive high-order neutral delay generalized neural networks

This paper investigates the impulsive effects on the finite time boundedness (FTB) and the FTB-stabilization for a high-order neutral-type neural networks (HONNNs) with leakage delay and mixed time-varying delay including both discrete and infinite distributed delays. The average impulsive interval technique and Lyapunov–Krasovskii functional (LKF) method are employed to derive sufficient conditions for the effect of the time delay in the leakage term on FTB in presence of destabilizing impulses. These conditions are in the form of linear matrix inequalities (LMIs) which can be numerically checked. Moreover, a state delay-free feedback control is designed to ensure the FTB-stabilization for impulsive HONNNs. Our theoretical results are further substantiated by numerical examples with graphical illustrations to confirm them and show their effectiveness.

Negative capacitance independent multi-gate FinFETs and their optimisations

ABSTRACTIn order to reduce the operating voltage of FinFET and increase the flexibility of integrated circuit design, we have proposed a Negative Capacitance Independent Multi-Gate FinFET (NC-IMG-FinFET) with Ferroelectric-Metal-Insulator-Semiconductor-Insulator (FMISI) structure. Both the device and circuit analysis model of NC-IMG-FinFET are addressed, which are used to analyse the performance parameters of the device (the surface potential, internal gate voltage amplification, Sub-threshold Swing (SS), on-current and leakage) and the performance of a circuit (delay, power consumption, power delay product (PDP)). The simulation model of the NC-IMG-FinFET has been constructed by combining BSIM-IMG model with ferroelectric Landau-Khalatnikov model. The optimisations for ferroelectric film thickness of the NC-IMG-FinFETs are carried out in terms of device characteristics and circuit performances. The simulation results are consistent with the analysis results, indicating that the NC-IMG-FinFET has superior performance compared with the baseline device, in terms of smaller leakage, larger on/off current ratio and smaller SS (38.3 mV/dec at room temperature). Compared with the baseline IMG-FinFET circuits, there is large performance improvement for the NC-IMG-FinFET circuits, in terms of the power consumption and PDP.

Finite-Time Convergence Adaptive Neural Network Control for Nonlinear Servo Systems

Although adaptive control design with function approximators, for example, neural networks (NNs) and fuzzy logic systems, has been studied for various nonlinear systems, the classical adaptive laws derived based on the gradient descent algorithm with σ -modification or e -modification cannot guarantee the parameter estimation convergence. These nonconvergent learning methods may lead to sluggish response in the control system and make the parameter tuning complex. The aim of this paper is to propose a new learning strategy driven by the estimation error to design the alternative adaptive laws for adaptive control of nonlinear servo systems. The parameter estimation error is extracted and used as a new leakage term in the adaptive laws. By using this new learning method, the convergence of both the estimated parameters and the tracking error can be achieved simultaneously. The proposed learning algorithm is further tailored to retain finite-time convergence. To handle unknown nonlinearities in the servomechanisms, an augmented NN with a new friction model is used, where both the NN weights and some friction model coefficients are estimated online via the proposed algorithms. Comparisons with the σ -modification algorithm are addressed in terms of convergence property and robustness. Simulations and practical experiments are given to show the superior performance of the suggested adaptive algorithms.

Predictable Privacy-Preserving Mobile Crowd Sensing: A Tale of Two Roles

The rise of mobile crowd sensing has brought privacy issues into a sharp view. In this paper, our goal is to achieve the predictable privacy-preserving mobile crowd sensing, which we envision to have the capability to quantify the privacy protections, and simultaneously allowing application users to predict the utility loss at the same time. The Salus algorithm is first proposed to protect the private data against the data reconstruction attacks. To understand privacy protection, we quantify the privacy risks in terms of private data leakage under reconstruction attacks. To predict the utility, we provide accurate utility predictions for various crowd sensing applications using Salus. The risk assessments can be generally applied to different type of sensors on the mobile platform, and the utility prediction can also be used to support various applications that use data aggregators such as average, histogram, and classifiers. Finally, we propose and implement the $P^{3}$ application framework. Both measurement results using online datasets and real-world case studies show that the $P^{3}$ provides accurate risk assessments and utility estimations, which makes it a promising framework to support future privacy-preserving mobilecrowd sensing applications.

Adaptive neural network control for robotic manipulators with guaranteed finite-time convergence

Although adaptive control with neural networks has been widely studied for robotic systems, the classical adaptive laws have been derived by using the gradient algorithm to minimize the tracking error, and thus their sluggish convergence may lead to performance degradation or even affect the operation safety. In this paper, we propose an adaptive neural control strategy for nonlinear robot manipulators with new adaptive laws. We first reformulate the robotic model by defining a set of auxiliary variables to avoid using the joint acceleration signals. Then an adaptive law with the extracted estimation error being new leakage terms is developed to update the unknown weight of the radial basis function neural network (RBFNN) used to address the unknown dynamics. With this new learning algorithm, both the tracking error and estimation error will exponentially converge to a small set around zero, whose size solely depends on the RBFNN approximation error. Moreover, we incorporate the sliding mode technique into the design of adaptive law and feedback control, such that finite-time convergence can be proved. The robustness of the proposed estimation and control methods is also investigated. Finally, simulation results based on a SCARA robot model are provided to demonstrate the effectiveness of the proposed approaches, and illustrate their superior response over classical adaptive control schemes with σ-modification method.

Role of cell wall and cell membrane integrity in imparting defense response against Phytophthora capsici in black pepper (Piper nigrum L.)

The structural defense response of a black pepper line (04-P24) showing root resistance to Phytophthora capsici was studied in comparison with a highly susceptible line (Sreekara). Role of cell wall reinforcement and cell membrane integrity was analyzed. Cell membrane integrity was studied under hydroponic system in terms of leakage of electrolytes caused by the cell membrane damage due to pathogen entry. Root cell membrane rupture and resultant phenolic leakage were clearly visible in the form of color change of the liquid phase during the course of infection. Root leachates of Sreekara turned highly dark due to the increased level of phenol leakage which was proportional to the cell membrane damage. The root leachate was analyzed for change in conductivity, total phenols and ortho-dihydroxy (OD) phenols. Cell wall reinforcement of the vascular tissues of black pepper root upon pathogen inoculation was analyzed histochemically. Toluidine blue O and Maule staining differentiated the intensity of lignin deposition in the root cells of both lines and it was comparatively stronger in the resistant line. Scanning electron microscopy revealed that hyphae of P. capsici are not penetrating the root of 04-P24 supporting the finding that roots of this line don’t support Phytophthora infection.

Dynamics of impulsive neutral-type BAM neural networks

In this letter, the existence and the global exponential stability of piecewise pseudo almost periodic solutions (PAPT) for bidirectional associative memory neural networks (BAMNNs) with time-varying delay in leakage (or forgetting) terms and impulsive are investigated by applying contraction mapping fixed point theorem, the exponential dichotomy of linear differential equations and differential inequality techniques. Furthermore, we give an explanatory example to illustrate the efficiency of the theoretical predictions.

The material-region-based 2D/1D transport method

The 2D/1D transport method is the dominant method for high-fidelity direct whole-core transport calculations, which attracts a lot of attention in recent decades. In the 2D/1D method, some sources of deviation are introduced, including spatial and angular approximation of leakage term and cross-section homogenization for 1D axial calculation. These approximations are analyzed and a material-region-based 2D/1D transport method with anisotropic leakage term, which avoids cross-section homogenization, as well as reduces spatially flat leakage approximation, are developed to improve accuracy at the expense of acceptable memory and efficiency loss. Finally, a BWR assembly case, the C5G7 benchmark and a rod-cluster assembly case are tested to verify the accuracy and performance of the material-region-based 2D/1D method.