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This work describes the dissipative constraint-based load frequency control problem for multi-area power system under load disturbances. Particularly, a new model incorporating time-varying delays and cyber-attacks are widespread in communication networks, significantly impacting control and stability. Consequently, the state-space equations of the addressed model are formulated and analyzed under the impact of false data injection attacks, and time-varying delays. The analysis is simplified by representing cyber-attacks using nonlinear functions adhering to Lipschitz continuity, while possible cyber-attacks are characterized by stochastic parameters conforming to Bernoulli distributions. Followed by the above information, stochastic analysis and Lyapunov-Krasovskii stability theory, the convex optimization problem is formulated. As a consequence, the load frequency control gains were effectively constructed, confirming that the established power model is stochastically stable and strictly (Q,S,R)-γ-dissipative. Finally, the case studies are employed to examine the usefulness of the suggested scheme., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors also confirmed that the work reported in this paper has not been published elsewhere., (Copyright © 2025 International Society of Automation. Published by Elsevier Ltd. All rights reserved.)

Recently, multi-resolution pyramid-based techniques have emerged as the prevailing research approach for image super-resolution. However, these methods typically rely on a single mode of information transmission between levels. In our approach, a wavelet pyramid recursive neural network (WPRNN) based on wavelet energy entropy (WEE) constraint is proposed. This network transmits previous-level wavelet coefficients and additional shallow coefficient features to capture local details. Besides, the parameter of low- and high-frequency wavelet coefficients within each pyramid level and across pyramid levels is shared. A multi-resolution wavelet pyramid fusion (WPF) module is devised to facilitate information transfer across network pyramid levels. Additionally, a wavelet energy entropy loss is proposed to constrain the reconstruction of wavelet coefficients from the perspective of signal energy distribution. Finally, our method achieves the competitive reconstruction performance with the minimal parameters through an extensive series of experiments conducted on publicly available datasets, which demonstrates its practical utility., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This work investigates the less conservative stability conditions for linear systems with a time-varying delay. At first, augmented Lyapunov-Krasovskii functionals(LKFs) are constructed with state vectors that have not been utilized in the existing works, and an augmented zero equality that can be derived according to the augmented vector is proposed. By utilizing them, a stability condition is proposed in the form of a linear matrix inequality. And, by using novel delay-dependent LKFs and the introduced ones, improved results are obtained than the previous result. The addition of the delay-dependent LKFs increases the number of decision variables in the results. Therefore, any vectors of integral inequalities utilized in the proposed criterion are appropriately adjusted to reduce computational complexity. To check the excellence and validity of the proposed results, several numerical examples are applied., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 ISA. Published by Elsevier Ltd. All rights reserved.)

This article investigates the asymptotic stabilization of periodic piecewise time-varying systems with time-varying delay under various cyber attacks, particularly deception and acrlong DoS attacks. The addressed system is reformed into a number of time-varying subsystems based on the time interval for each period. Following that, a state-feedback controller with periodic time-varying gain parameters is developed to solve the stabilization problem. The control design depicts the possibility of the aforementioned cyber attacks with two mutually exclusive stochastic Bernoulli distributed parameters. Then, an augmented Lyapunov-Krasovskii functional with periodically varying matrices is used to determine the conditions for designing the proposed controller that ensures the mean-square asymptotic stability of the addressed system. The results of numerical examples support the conclusion that the proposed method is effective and superior, regardless of the cyber attacks involved.

Background: Even amid the coronavirus disease-19 (COVID-19) pandemic, the spread of multidrug-resistant bacteria and infection control are still important tasks. After recognizing the carbapenem-resistant Acinetobacter baumannii (CRAB) outbreak that occurred in the isolation room for COVID-19, we would like to introduce what infection control measures were implemented to eradicate it., Materials and Methods: All COVID-19 patients with CRAB in any specimen admitted to the COVID-19 isolation ward of the tertiary hospital in Korea from October to November 2021 were analyzed., Results: During the outbreak, 23 patients with COVID-19 and CRAB infections were identified. The index case was an 85-year-old female referred from a long-term care facility. CRAB was identified in sputum culture in most patients (91.3%). The CRAB outbreak occurred mainly in the rooms around the index case. Environmental cultures on the floor, air inlet, air outlet, and window frame of the rooms were performed. The antimicrobial resistance patterns of CRAB from patients and the environment were identical; whole-genome sequencing analyses revealed isolated clonality. Infection control measures with enhanced environmental cleaning using 1,000 ppm sodium hypochlorite and phenolic compounds, enhanced hand hygiene, additional education, and mandatory additional gowning and gloving of COVID-19 personal protective equipment (PPE) were applied on 29 October. No CRAB infection cases occurred from 2 November for two weeks., Conclusion: In addition to applying PPE and COVID-19 precautions in COVID-19 isolation wards, adhering to strict contact precautions along with environmental control can help prevent the spread of multidrug-resistant bacteria., Competing Interests: JYC is editorial board of Infect Chemother; however, he did not involve in the peer reviewer selection, evaluation, and decision process of this article. Otherwise, no potential conflicts of interest relevant to this article was reported., (© 2024 by The Korean Society of Infectious Diseases, Korean Society for Antimicrobial Therapy, The Korean Society for AIDS, and Korean Society of Pediatric Infectious Diseases.)

This article is concerned with the fixed-time stability (FTS) problem of nonlinear impulsive systems (NISs). By means of the impulsive control mechanism and Lyapunov functions theory, several sufficient conditions are established to ensure the FTS of general NISs. Meanwhile, some novel impulse-dependent settling-time estimation schemes are developed, which fully considers the influence of stabilizing impulses and destabilizing impulses on the convergence rate of the system states. The proposed schemes establish a quantitative relationship between the upper bound of the settling time and impulse effects. It shows that stabilizing impulses can accelerate the convergence rate of the system states and leads to the upper bound of the settling time being smaller. Conversely, destabilizing impulses can reduce it and make the upper bound of the settling time larger. Then, the theoretical results are applied to delayed inertial neural networks (DINNs), where two kinds of controllers are designed to realize fixed-time synchronization of the considered systems in the impulse sense. Finally, some numerical examples are provided to illustrate the validity of the proposed theoretical results.

This work is devoted the problem of a security-guaranteed filter design for a class of discrete-time Markov jump systems that are vulnerable to stochastic deception attacks and have random sensor saturation. Deception attacks, in particular, are taken into account in the filter when the attacker attempts to modify the broadcast signal in communication networks by inserting some misleading information data into the assessment output. The Bernoulli distribution is satisfied by two sets of introduced stochastic variables. It shows the likelihood that the broadcaster's data transmissions will be the focus of deception attacks and sensor saturation. The Lyapunov functional technique is established, and criteria are derived to ensure that the system is mean-square stable. Furthermore, explicit expression of the filter gains is obtained by solving a set of linear matrix inequalities. Lastly, two simulation examples including a synthetic genetic regulatory network are provided to further demonstrate the validity and efficiency of the suggested theoretical results., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 ISA. Published by Elsevier Ltd. All rights reserved.)

In this paper, we focus on the real power sharing and frequency regulation of distributed generators in islanded microgrids with abnormal asynchronous stochastic cyber attacks, which is of great significance to the information security and stable operation of microgrids. Firstly, considering the possible cyber attacks in the communication network, a distributed non-fragile controller with coupled memory delay is proposed according to the nonperiodic sampled-data control. Then, the construction of delay-dependent two-sided looped-functional makes the Lyapunov-Krasovskii functional contain more delay and sampling information and relaxes constraints on free matrices. In addition, based on the enhanced integral inequality technique and the linear convex combination method, a sampling-based consensus protocol is presented to solve the issues of real power sharing and frequency regulation in the islanded microgrids. Finally, to verify the effectiveness and feasibility of the designed control strategy, a modified IEEE 34-bus test system is used for the experiment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 ISA. Published by Elsevier Ltd. All rights reserved.)

This article scrutinizes the stabilization and fault reconstruction issues for interval type-2 fuzzy-based cyber-physical systems with actuator faults, deception attacks and external disturbances. The primary objective of this research is to formulate the learning observer system with the interval type-2 fuzzy technique that reconstructs the actuator faults as well as the immeasurable states of the addressed fuzzy based model. Further, the information of reconstructed actuator faults is incorporated in the developed controller with the imperfect premise variables for ensuring the stabilization of the system under consideration. At the same time, the H ∞ technique is employed to reduce the impact of external disturbances in the considered model. In addition to that, the deception attacks are represented as a stochastic variable that satisfies the Bernoulli distributions. On the ground of this, a set of sufficient criteria is deduced in the context of linear matrix inequalities to affirm the stability of the addressed systems. Furthermore, the requisite gain matrices are computed by resolving the obtained linear matrix inequality based stability criteria. At last, two simulation examples, including the mass-spring-damper system are exhibited to demonstrate the usefulness of analytical findings of the developed strategy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 ISA. Published by Elsevier Ltd. All rights reserved.)

In recent years, deep learning super-resolution models for progressive reconstruction have achieved great success. However, these models which refer to multi-resolution analysis basically ignore the information contained in the lower subspaces and do not explore the correlation between features in the wavelet and spatial domain, resulting in not fully utilizing the auxiliary information brought by multi-resolution analysis with multiple domains. Therefore, we propose a super-resolution network based on the wavelet multi-resolution framework (WMRSR) to capture the auxiliary information contained in multiple subspaces and to be aware of the interdependencies between spatial domain and wavelet domain features. Initially, the wavelet multi-resolution input (WMRI) is generated by combining wavelet sub-bands obtained from each subspace through wavelet multi-resolution analysis and the corresponding spatial domain image content, which serves as input to the network. Then, the WMRSR captures the corresponding features from the WMRI in the wavelet domain and spatial domain, respectively, and fuses them adaptively, thus learning fully explored features in multi-resolution and multi-domain. Finally, the high-resolution images are gradually reconstructed in the wavelet multi-resolution framework by our convolution-based wavelet transform module which is suitable for deep neural networks. Extensive experiments conducted on two public datasets demonstrate that our method outperforms other state-of-the-art methods in terms of objective and visual qualities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

This paper investigates an observer-based state estimation issue for discrete-time semi-Markovian jump neural networks with Round-Robin protocol and cyber attacks. In order to avoid the network congestion and save the communication resources, the Round-Robin protocol is used to schedule the data transmissions over the networks. Specifically, the cyber attacks are modeled as a set of random variables satisfying the Bernoulli distribution. On the basis of the Lyapunov functional and the discrete Wirtinger-based inequality technique, some sufficient conditions are established to guarantee the dissipativity performance and mean square exponential stability of the argument system. In order to compute the estimator gain parameters, a linear matrix inequality approach is utilized. Finally, two illustrative examples are provided to demonstrate the effectiveness of the proposed state estimation algorithm., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors also confirmed that the work reported in this paper has not been published elsewhere., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In this work, we address hybrid-driven-based robust synchronization problem for multi-weighted complex dynamical networks with actuator saturation and deception attacks. The hybrid-triggered mechanism, which combines a switch between the event-triggered scheme and the time-triggered scheme, is often used to reduce the data transmission and the alleviate network burden. Further, the equivalent-input-disturbance technique is applied to eliminate the unknown disturbance effect of the addressed system. Moreover, a memory controller is designed under actuator saturation to ensure that the resultant augmented system is asymptotically synchronized even in the presence of deception attacks. Finally, three numerical examples are given to show the validity of the obtained theoretical results., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

This article proposes three new methods to enlarge the feasible region for guaranteeing stability for generalized neural networks having time-varying delays based on the Lyapunov method. First, two new zero equalities in which three states are augmented are proposed and inserted into the results of the time derivative of the constructed Lyapunov-Krasovskii functionals for the first time. Second, inspired by the Wirtinger-based integral inequality, new Lyapunov-Krasovskii functionals are introduced. Finally, by utilizing the relationship among the augmented vectors and from the original equation, newly augmented zero equalities are established and Finsler's lemma are applied. Through three numerical examples, it is verified that the proposed methods can contribute to enhance the allowable region of maximum delay bounds.

This work investigates the stability and dissipativity problems for neural networks with time-varying delay. By the construction of new augmented Lyapunov-Krasovskii functionals based on integral inequality and the use of zero equality approach, three improved results are proposed in the forms of linear matrix inequalities. And, based on the stability results, the dissipativity analysis for NNs with time-varying delays was investigated. Through some numerical examples, the superiority and effectiveness of the proposed results are shown by comparing the existing works., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Most deep neural networks (DNNs) are trained with large amounts of noisy labels when they are applied. As DNNs have the high capacity to fit any noisy labels, it is known to be difficult to train DNNs robustly with noisy labels. These noisy labels cause the performance degradation of DNNs due to the memorization effect by over-fitting. Earlier state-of-the-art methods used small loss tricks to efficiently resolve the robust training problem with noisy labels. In this paper, relationship between the uncertainties and the clean labels is analyzed. We present novel training method to use not only small loss trick but also labels that are likely to be clean labels selected from uncertainty called "Uncertain Aware Co-Training (UACT)". Our robust learning techniques (UACT) avoid over-fitting the DNNs by extremely noisy labels. By making better use of the uncertainty acquired from the network itself, we achieve good generalization performance. We compare the proposed method to the current state-of-the-art algorithms for noisy versions of MNIST, CIFAR-10, CIFAR-100, T-ImageNet and News to demonstrate its excellence., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

This paper investigates the robust synchronization problem for a class of master-slave neural networks (MSNNs) subject to network-induced delays, unknown time-varying uncertainty, and exogenous disturbances. An equivalent-input-disturbance (EID) estimation technique is applied to compensate for the effects of unknown uncertainty and disturbances in the system output. In addition, to reduce the burden of the communication channel in the addressed MSNNs and improve the utilization of bandwidth an event-triggered control protocol is developed to obtain the synchronization of MSNNs. In particular, event-triggering conditions are verified periodically at every sampling instant in both sensors and actuators to avoid the Zeno behavior in the networks. By designing an appropriate low-pass filter in the EID estimator block, the accuracy of disturbance estimation performance is improved. Moreover, by concatenating the synchronization error, observer, and filter states as a single state vector, an augmented system is formulated. Then the tangible delay-dependent stability condition for that augmented system is established by employing the Lyapunov stability theory and reciprocally convex approach. Based on the feasible solutions of the derived stability conditions, the event-triggering parameters, controller, and observer gains are co-designed. Finally, two toy examples are given to illustrate the established theoretical findings., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

HY-80 and HY-100 steels, widely used in constructing large ocean vessels and submarine hulls, contain mixed microstructures of tempered bainite and martensite and provide high tensile strength and toughness. Weld integrity in HY steels has been studied to verify and optimize welding conditions. In this study, the T-joint weld coupons, HY80 and HY100, were fabricated from HY-80 and HY-100 steel plates with a thickness of 30 mm as base metals by submerged-arc welding. Flux-cored arc welding was performed on an additional welding coupon consisting of HY-100 to evaluate the effect of repair welds (HY100RP). Microstructures in the heat-affected zones (HAZ) were thoroughly analyzed by optical observation. Instrumented indentation testing, taking advantage of local characterization, was applied to assess the yield strength and the residual stress of the HAZ and base regions. The maximum hardness over 400 HV was found in the HAZ due to the high volume fraction of untempered martensite microstructure. The yield strength of the weld coupons was evaluated by indentation testing, and the results showed good agreement with the uniaxial tensile test (within 10% range). The three coupons showed similar indentation residual stress profiles on the top and bottom surfaces. The stress distribution of the HY100 coupon was comparable to the results from X-ray diffraction. HY100RP demonstrated increased tensile residual stress compared to the as-welded coupon due to the effect of the repair weld (323 and 103 MPa on the top and bottom surfaces). This study verifies the wide applicability of indentation testing in evaluating yield strength and residual stress.

This paper concerns with the issues of designing an improved-equivalent-input-disturbance (IEID) based robust two dimensional modified repetitive control (2D MRC) for a class of fuzzy systems in the presence of aperiodic disturbances. Specifically, IEID-estimator is implemented to the 2D MRC systems that estimates all types of disturbances and compensates them for assuring robust stability. In particular, the proposed 2D MRC system has two different type of behaviours such as continuous control and discrete learning independently. To obtain gains of the observer and the controller, an adequate set of robust stability conditions is derived in the form of a linear-matrix-inequalities. Finally, simulation results for three numerical examples are provided to depict the efficacy of the proposed control technique., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 ISA. Published by Elsevier Ltd. All rights reserved.)

This paper gives attention to the issues of output tracking and disturbance rejection performance for a class of fractional order Takagi-Sugeno fuzzy systems in the presence of time-varying delay and unknown external disturbances. More specifically, a new configuration of a fractional order modified repetitive controller that incorporates an improved equivalent-input-disturbance estimator and gain fluctuations in its design is proposed to perform disturbance rejection for the addressed system. By introducing a continuous frequency distributed equivalent model and using the Lyapunov-Krasovskii stability theory, a new set of sufficient conditions ensuring robust asymptotic stability of the resulting closed-loop system is obtained in the framework of linear matrix inequalities. Finally, a numerical example is presented to validate the developed theoretical results, where it is shown that the obtained conditions could force the considered system output to exactly track the given any kind of reference signal by compensating the unknown external disturbance., (Copyright © 2019 ISA. Published by Elsevier Ltd. All rights reserved.)

This paper investigates the synchronization issue for a family of time-delayed fractional-order complex dynamical networks (FCDNs) with time delay, unknown bounded uncertainty and disturbance. A novel fractional uncertainty and disturbance estimator (FUDE) based feedback control strategy is proposed to not only synchronize the considered FCDNs but also guaranteeing the precise rejection of unmodelled system uncertainty and external disturbance. Especially, in FUDE-based approach, model uncertainties and external disturbance are integrated as a lumped disturbance and it does not require a completely known system model or a disturbance model. On the other hand, the design algorithm for the proposed control strategy is based on the state-space framework, rather than frequency-based design methodologies in the literature, which helps for predominant comprehension of the inner system behaviour. Also, by the temperance of Lyapunov stability theory and fractional calculus, a set of adequate conditions in the linear matrix inequality framework is obtained, which guarantees the robust synchronization of the closed-loop system. Furthermore, an iterative optimization algorithm is proposed to improve control robustness against the external disturbance and model uncertainties. Finally, two numerical illustrations including financial network model, where the influence of adjustment of macro-economic policies in the entire financial system are given to exhibit the rightness and important features of the acquired theoretical results., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

This paper is concerned with the problem of passivity for uncertain neural networks with time-varying delays. First, the recently developed integral inequality called generalized free-matrix-based integral inequality is extended to estimate further tight lower bound of integral terms. By constructing a suitable augmented LKF, an enhanced passivity condition for the concerned network is derived in terms of linear matrix inequalities (LMIs). Here, the integral terms having three states in its quadratic form is estimated by the proposed Lemma. As special cases of main results, for neural networks without uncertainties, passivity and stability conditions are derived. Through three numerical examples, it will be shown that the developed conditions can promote the level of passivity and stability criteria., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

This paper addresses the problem of finite-time synchronization of stochastic coupled neural networks (SCNNs) subject to Markovian switching, mixed time delay, and actuator saturation. In addition, coupling strengths of the SCNNs are characterized by mutually independent random variables. By utilizing a simple linear transformation, the problem of stochastic finite-time synchronization of SCNNs is converted into a mean-square finite-time stabilization problem of an error system. By choosing a suitable mode dependent switched Lyapunov-Krasovskii functional, a new set of sufficient conditions is derived to guarantee the finite-time stability of the error system. Subsequently, with the help of anti-windup control scheme, the actuator saturation risks could be mitigated. Moreover, the derived conditions help to optimize estimation of the domain of attraction by enlarging the contractively invariant set. Furthermore, simulations are conducted to exhibit the efficiency of proposed control scheme., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

This paper investigates synchronization in complex dynamical networks (CDNs) with interval time-varying delays. The CDNs are representative of systems composed of a large number of interconnected dynamical units, and for the purpose of the mathematical analysis, the leading work is to model them as graphs whose nodes represent the dynamical units. At this time, we take note of the importance of each node in networks. One way, in this paper, is that the closeness-centrality mentioned in the field of social science is grafted onto the CDNs. By constructing a suitable Lyapunov-Krasovskii functional, and utilizing some mathematical techniques, the sufficient and closeness-centrality-based conditions for synchronization stability of the networks are established in terms of linear matrix inequalities. Ultimately, the use of the closeness-centrality can be weighted with regard to not only the interconnection relation among the nodes, which was utilized in the existing works but also more information about nodes. Here, the centrality will be added as the concerned information. Moreover, to avoid the computational burden causing the nonconvex term including the square of the time-varying delay, how to deal with it is applied by estimating it to the convex term including time-varying delay. Finally, two illustrative examples are given to show the advantage of the closeness-centrality in point of the robustness on time-delay.

Manipulation of the chemical vapor deposition graphene synthesis conditions, such as operating P, T, heating/cooling time intervals, and precursor gas concentration ratios (CH 4 /H 2 ), allowed for synthesis of polycrystalline single-layered graphene with controlled grain sizes. The graphene samples were then suspended on 8 μm diameter patterned holes on a silicon-nitride (Si 3 N 4 ) substrate, and the in-plane thermal conductivities k(T) for 320 K < T < 510 K were measured to be 2660-1230, 1890-1020, and 680-340 W/m·K for average grain sizes of 4.1, 2.2, and 0.5 μm, respectively, using an opto-thermal Raman technique. Fitting of these data by a simple linear chain model of polycrystalline thermal transport determined k = 5500-1980 W/m·K for single-crystal graphene for the same temperature range above; thus, significant reduction of k was achieved when the grain size was decreased from infinite down to 0.5 μm. Furthermore, detailed elaborations were performed to assess the measurement reliability of k by addressing the hole-edge boundary condition, and the air-convection/radiation losses from the graphene surface.

This study combined phosphoric acid-catalyzed pretreatment and enzymatic hydrolysis to produce biosugars from Gracilaria verrucosa as a potential renewable resource for bioenergy applications. We optimized phosphoric acid-catalyzed pretreatment conditions to 1:10 solid-to-liquid ratio, 1.5 % phosphoric acid, 140 °C, and 60 min reaction time, producing a 32.52 ± 0.06 % total reducing sugar (TRS) yield. By subsequent enzymatic hydrolysis, a 68.61 ± 0.90 % TRS yield was achieved. These results demonstrate the potential of phosphoric acid to produce biosugars for biofuel and biochemical production applications.

Background: Impaired nitric oxide-mediated pulmonary vascular tone is commonly found in heart failure with reduced ejection fraction (HFrEF), and is associated with derangement of left ventricular (LV) hemodynamics and decreased exercise capacity, which may be reversed by PDE5 inhibitor. This study investigated the effects of a new, long-acting PDE5 inhibitor on LV hemodynamics and exercise capacity in HFrEF., Methods: Patients with chronic HFrEF on optimal medical therapy for >30 days before enrollment were randomly assigned to placebo or udenafil at a dose of 50mg 2x/day for the first 4 weeks followed by 100mg 2x/day for the next 8 weeks. All patients underwent cardiopulmonary exercise echocardiography before and after the 12-week treatment., Results: Improvement of subjective functional capacity was more frequently reported in the udenafil group (P = 0.002). Also, a higher increase in peak VO2 (Δpeak VO2, 21.6% (6.9 ~ 106.4%) vs 1.9% (-15.7 ~ 21.0%) in the placebo group, P = 0.04) and a larger decrease in ventilatory efficiency were observed in the udenafil group (Δ-6.4 ± 9.7 vs Δ1.9 ± 12.1 in the placebo group, P = 0.03). Regarding LV systolic function, the extent of increment in LV ejection fraction was significantly greater in the udenafil group (6.6 ± 6.4% vs 2.3 ± 4.8% in the placebo group, P = 0.02). In the udenafil group, an echocardiographic surrogate of LV filling pressure was more prominently decreased (P = 0.006) along with a significant reverse remodeling of left atrial volume index (57 ± 25mL at baseline to 44 ± 23 at 12th week, P = 0.04) and a progressive fall in B-type natriuretic peptide level (589 ± 679pg/mL at baseline to 220 ± 225pg/mL at 12th week, P < 0.001), indicating LV diastolic function improvement. Udenafil was well tolerated without excess of adverse events compared to placebo., Conclusions: Udenafil improves LV systolic/diastolic functions and exercise capacity in conjunction with established conventional pharmacotherapy, without significant adverse events in HFrEF., (Copyright © 2015 Elsevier Inc. All rights reserved.)

This paper proposes a new consensus criterion for nonlinear complex systems with edge betweenness centrality measure. By construction of a suitable Lyapunov-Krasovskii functional, the consensus criterion for such systems is established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. One numerical example is given to illustrate the effectiveness of the proposed methods.

In this brief, an extended dissipativity analysis was conducted for a neural network with time-varying delays. The concept of the extended dissipativity can be used to solve for the H∞, L2-L∞, passive, and dissipative performance by adjusting the weighting matrices in a new performance index. In addition, the activation function dividing method is modified by introducing a tuning parameter. Examples are provided to show the effectiveness and less conservatism of the proposed method.

This study examines the state estimation problem for neural networks with a time-varying delay. Unlike other studies, the sampled-data with stochastic sampling is used to design the state estimator using a novel approach that divides the bounding of the activation function into two subintervals. To fully use the sawtooth structure characteristics of the sampling input delay, a discontinuous Lyapunov functional is proposed based on the extended Wirtinger inequality. The desired estimator gain can be characterized in terms of the solution to linear matrix inequalities (LMIs). Finally, the proposed method is applied to two numerical examples to show the effectiveness of our result., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Background: Left ventricular (LV) mass is an important prognostic indicator in hypertrophic cardiomyopathy. Although LV mass can be easily calculated using conventional echocardiography, it is based on geometric assumptions and has inherent limitations in asymmetric left ventricles. Real-time three-dimensional echocardiographic (RT3DE) imaging with single-beat capture provides an opportunity for the accurate estimation of LV mass. The aim of this study was to validate this new technique for LV mass measurement in patients with hypertrophic cardiomyopathy., Methods: Sixty-nine patients with adequate two-dimensional (2D) and three-dimensional echocardiographic image quality underwent cardiac magnetic resonance (CMR) imaging and echocardiography on the same day. Real-time three-dimensional echocardiographic images were acquired using an Acuson SC2000 system, and CMR-determined LV mass was considered the reference standard. Left ventricular mass was derived using the formula of the American Society of Echocardiography (M-mode mass), the 2D-based truncated ellipsoid method (2D mass), and the RT3DE technique (RT3DE mass)., Results: The mean time for RT3DE analysis was 5.85 ± 1.81 min. Intraclass correlation analysis showed a close relationship between RT3DE and CMR LV mass (r = 0.86, P < .0001). However, LV mass by the M-mode or 2D technique showed a smaller intraclass correlation coefficient compared with CMR-determined mass (r = 0.48, P = .01, and r = 0.71, P < .001, respectively). Bland-Altman analysis showed reasonable limits of agreement between LV mass by RT3DE imaging and by CMR, with a smaller positive bias (19.5 g [9.1%]) compared with that by the M-mode and 2D methods (-35.1 g [-20.2%] and 30.6 g [17.6%], respectively)., Conclusions: RT3DE measurement of LV mass using the single-beat capture technique is practical and more accurate than 2D or M-mode LV mass in patients with hypertrophic cardiomyopathy., (Copyright © 2013 American Society of Echocardiography. Published by Mosby, Inc. All rights reserved.)

This paper considers the problem of delay-dependent stability criteria for neural networks with time-varying delays. First, by constructing a newly augmented Lyapunov-Krasovskii functional, a less conservative stability criterion is established in terms of linear matrix inequalities. Second, by proposing novel activation function conditions which have not been proposed so far, further improved stability criteria are proposed. Finally, three numerical examples used in the literature are given to show the improvements over the existing criteria and the effectiveness of the proposed idea.

Surface roughness-controlled nanocrystalline diamond film was fabricated as an undulated line and space pattern on a silicon oxide surface. To simulate a MEMS (Micro-/Electro-Mechanical System) and NEMS (Nano-/Electro-Mechanical System) patterned surface, 800 nm and 1 microm wide lines with a 200 nm wide space pattern were prepared on the substrate using E-beam lithography and an ESAND (Electrostatic Self-assembly of NanoDiamond) seeding layer lift-off process. Through this process, an undulated pattern of a nanocrystalline CVD diamond successfully formed by a conventional micro crystalline diamond growth system. The roughness of the deposited surface was controlled by regulating the size of the seeding nanodiamond particles. Crushing of the nanodiamond aggregates and dispersion of the nanodiamond solution was performed in an attrition milling system. An AFM (Atomic Force Microscopy) probe was used for the wear test and surface profiling of nanocrystalline diamond coatings. 2-D friction coefficient mapping by LFM (Lateral Force Microscopy) scanning showed a low friction coefficient (< 0.1) on the line-patterned diamond surface, and a higher friction coefficient (< 0.3) on a narrow area adjacent to the undulated pattern edges. With prolonged LFM scanning, the high coefficient of friction was reduced to less than 0.1. The bonding status of the nanocrystalline diamond was analyzed with Raman spectroscopy.

Ultra thin and smooth nano crystalline diamond films were fabricated with electrostatic self-assembly seeding of explosively synthesized nano-diamond particles. Hard aggregates of nano-diamond particles were crushed by high revolution attrition milling at 1000 RPM to regulate the particle size. Through this process, cationic nano-diamond particles were coated with anionic PSS (poly sodium 4-styrene sulfonate) electrolytes. Anionic Si(100) substrate was coated with cationic PDDA (poly diallyldimethyl ammonium chloride) solution. Si(100)/PDDA/PSS/ND (nano-diamond) layer-by-layer structure was formed as a seeding layer by the simple dipping and rinsing of positively charged substrate into anionic PSS/nano-diamond solution. Throughout the seeding process, neither mechanical damage nor chemical attack was observed on the substrate. Every stage of this preparation was carried out at room temperature and pressure. The effect of attrition milling was determined by changing the milling time from 1 hr to 5 hrs. Through the attritional milling and monolayer formation of the nano-diamond, nucleation density was increased up to 3 x 10(11)/cm2. Typical hot filament chemical vapor deposition system was used to coat the diamond film on the ESA (electrostatic self-assembly) seeded Si(100) substrate. Although typical diamond deposition conditions (90 torr/1% CH4 in H2/800 degrees C) were maintained, ultra thin (< 100 nm) and continuous nano crystalline diamond films were deposited. Regardless of metallic or ceramic substrate, ESND (ESA Seeding of nano-diamond) process is applicable if the substrate has any charge. This simple nano technology based process ensures high thickness uniformity of diamond coating without visible edge effect.