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The future distribution systems expose to an unprecedented level of uncertainties due to renewable resources, nontraditional loads, aging infrastructure, etc., posing potential risks to secure operation of the system.This article proposes a new technique to estimate the voltage stability margin of the distribution systems with high penetration of renewables.Its convergence and robustness under complex and stressed working conditions are guaranteed in theory. This technique is handy for the operation as it features self-adaptive step size and is applicable to general system topology. It leverages a newly derived analytical solvability certificate based on the Kantorovich fixed-point theorem. A fast version of the proposed technique is duly proposed to speed up the computation up to 8 times while maintaining high accuracy, which lends itself to online and time-sensitive emergency tasks. Numerical simulations with various IEEE test feeders verify the performance of the techniques. Ministry of Education (MOE) Nanyang Technological University National Research Foundation (NRF) This work was supported in part by NTU SUG, MOE AcRF TIER 1- 2019-T1-001-119 (RG 79/19), and in part by EMA & NRFEMA-EP004-EKJGC-0003.

The significant penetration of renewable energy resources into power systems introduces intermittent disturbances that drive the system away from its stable operating point (i.e., equilibrium). Nevertheless, as long as the system states are still contained inside a region of attraction (ROA), the system will finally return to the normal operating equilibrium. Thus, the ROA plays a crucial role in the stability assessment of dynamical power systems under uncertainties. This brief introduces a novel framework to construct the ROA of a power system centered around a stable equilibrium by using stable state trajectories of system dynamics. Most existing works on estimating ROA rely on analytic Lyapunov functions, which are subject to two limitations: the analytic Lyapunov functions may not be always readily available and the resulting ROA may be overly conservative. This work overcomes these two limitations by leveraging the converse Lyapunov theorem in control theory to eliminate the need for an analytic Lyapunov function and learning unknown Lyapunov functions with the Gaussian process (GP) approach. In addition, a GP upper confidence bound (GP-UCB)-based sampling algorithm is designed to reconcile the tradeoff between the exploitation for enlarging the ROA and the exploration for enhancing the confidence level of the sample region. Within the constructed ROA, it is guaranteed in the probability that the system state will converge to the stable equilibrium with a confidence level. Extensive simulations and experimental validations are conducted to substantiate the assessment approach for the ROA of IEEE test systems and a real smartgrid using phasor measurement unit (PMU) data. It is demonstrated that the proposed approach can significantly enlarge the estimated ROA compared to that of the analytic Lyapunov counterpart.

Supplemental Figure S5. Related to Figure 4C-E: Primary breast tumors in Early SNAIL1 KO exhibit loss of EMT phenotype and metastatic potential

Supplemental Figure S1. Related to Figure 1: Generation and characterization of the SNAIL1-CBR mouse

Supplemental Material and Methods. Additional description of materials and methods used

Supplemental Figure S4. Related to Figure 3: SNAIL1 expression in primary breast tumors precedes detection of DTCs, but SNAIL1 is not expressed by DTCs and lung metastases in MMTV-PyMT mice

Supplemental Figure S2. Related to Figure 2A-E: SNAIL1 expression in primary breast tumors strongly correlates with increased metastasis in MMTV-neuNT mice

Supplemental Figure S6. Related to Figure 5D: SNAIL1 is not expressed by lung metastases in mice overexpressing SNAIL1 in primary breast tumors

Supplemental Table S1. Spatiotemporal expression of SNAIL1 in MMTV-PyMT mice

Supplemental Figure S3. Related to Figure 2F-J: SNAIL1 expression in primary breast tumors correlates with increased invasion

Supplemental Table and Figure Legends. Legends to the supplemental table and figures

Introduction: Early ICH expansion is associated with a higher rate of poor outcomes and death in aSAH patients, especially in limited-resource settings. This study aimed to investigate the impact of ICH expansion on the outcomes and the factors related to an ICH expansion in aSAH patients in an LMIC. Hypothesis: Understanding factors related to ICH after an aneurysmal rupture in different countries, particularly in limited-resource regions, is crucial for reducing poor outcomes and mortality. Methods: We performed a multicenter prospective cohort study of patients (≥18 years) presenting with aSAH at three central hospitals in Hanoi, Vietnam, from August 2019 to June 2021. We collected data on the demographics, baseline characteristics, management, and outcomes and compared these data between patients who had an ICH expansion (defined as ICH detected on an admission CT scan) and patients who did not. We assessed factors associated with ICH expansion on admission using logistic regression. Results: Of 415 patients, 198 (47.7%) were men, and the median age was 57.0 years (IQR: 48.0-67.0). ICH expansion accounted for 20.5% (85/415) of aSAH patients. There was a significant difference in the 90-day poor outcomes (43.5%; 37/85 and 29.1%; 96/330; p=0.011) and 90-day mortality (36.5%; 31/85 and 20.0%; 66/330; p=0.001) between patients who had ICH and patients who did not have ICH expansion. The multivariate analysis showed that systolic BP of 140 mmHg or more (OR: 2.674; 95% CI: 1.372-5.214), WFNS grades II (OR: 3.683; 95% CI: 1.250-10.858) to V (OR: 6.912; 95% CI: 2.553-18.709), and a ruptured MCA aneurysm (OR: 3.717; 95% CI: 1.848-7.477) were independent predictors of ICH expansion. Conclusions: In our study, ICH accounted for a substantial proportion of aSAH patients and contributed significantly to a high rate of poor outcomes and death. On admission, a higher systolic BP, a worse neurological status, and a ruptured MCA aneurysm were independent predictors of ICH expansion. This study indicates independent predictors of an early ICH expansion, such as a higher admission systolic BP and a worse initial neurological status, after aneurysmal ruptures that require only a clinical examination and, therefore, may be particularly valuable in resource-limited settings.

We study the long time statistics of a two-dimensional Hamiltonian system in the presence of Gaussian white noise. While the original dynamics is known to exhibit finite time explosion, we demonstrate that under the impact of the stochastic forcing as well as a deterministic perturbation, the solutions are exponentially attractive toward the unique invariant probability measure. This extends previously established results in which the system is shown to be noise-induced stable in the sense that the solutions are bounded in probability.

In this paper, a novel convexification approach for Small-Signal Stability Constraint Optimal Power Flow (SSSC-OPF) has been presented that does not rely on eigenvalue analysis. The proposed methodology is based on the sufficient condition for the small-signal stability, developed as a Bilinear Matrix Inequality (BMI), and uses network structure-preserving Differential Algebraic Equation (DAE) modeling of the power system. The proposed formulation is based on Semi-definite Programming (SDP) and objective penalization that has been proposed for feasible solution recovery, making the method computationally efficient for large-scale systems. A vector-norm based objective penalty function has also been proposed for feasible solution recovery while working over large and dense BMIs with matrix variables. An effectiveness study carried out on WECC 9-bus, New England 39-bus, and IEEE 118-bus test systems show that the proposed method is capable of achieving a stable equilibrium point without inflicting a high stability-induced additional cost. Energy Market Authority (EMA) Ministry of Education (MOE) Nanyang Technological University National Research Foundation (NRF) Accepted version The authors are supported by NTU SUG, MOE AcRF TIER 1- 2019-T1-001-119 (RG 79/19), EMA & NRF EMA-EP004- EKJGC-0003, and NRF DERMS for Energy Grid 2.0.

In this paper, an optimal steady-state voltage control framework is developed based on a novel linear Voltage-Power dependence deducted from Gaussian Process (GP) learning. Different from other point-based linearization techniques, this GP-based linear relationship is valid over a subspace of operating points and thus suitable for a system with uncertainties such as those in power injections due to renewables. The proposed optimal voltage control algorithms, therefore, perform well over a wide range of operating conditions. Both centralized and distributed optimal control schemes are introduced in this framework. The least-squares estimation is employed to provide analytical forms of the optimal control which offer great computational benefits. Moreover, unlike many existing voltage control approaches deploying fixed voltage references, the proposed control schemes not only minimize the control efforts but also optimize the voltage reference setpoints that lead to the least voltage deviation errors with respect to such setpoints. The control algorithms are also extended to handle uncertain power injections with robust optimal solutions which guarantee compliance with the voltage regulation standards. As for the distributed control scheme, a new network partition problem is cast, based on the concept of Effective Voltage Control Source (EVCS), as an optimization problem which is further solved using convex relaxation. Various simulations on the IEEE 33-bus and 69-bus test feeders are presented to illustrate the performance of the proposed voltage control algorithms and EVCS-based network partition. Energy Market Authority (EMA) Nanyang Technological University National Research Foundation (NRF) Accepted version This work was supported in part by the Nanyang Technological University SUG, in part by the Academic Research Fund TIER 1 2019-T1-001-119 (RG 79/19), and in part by the Energy Market Authority (EMA) and National Research Foundation (NRF) Singapore under Grant EMA-EP004-EKJGC-0003.

Two new polyisoprenylated benzophenones, planchoniones A (1) and B (2), together with two known benzophenones (3, 4) and six known xanthones (5-10), were isolated from an ethyl acetate extract of t...

Oral squamous cell carcinoma (OSCC) is one of the most painful cancers, which interferes with orofacial function including talking and eating. We report that legumain (Lgmn) cleaves protease-activated receptor-2 (PAR2) in the acidic OSCC microenvironment to cause pain. Lgmn is a cysteine protease of late endosomes and lysosomes that can be secreted; it exhibits maximal activity in acidic environments. The role of Lgmn in PAR2-dependent cancer pain is unknown. We studied Lgmn activation in human oral cancers and oral cancer mouse models. Lgmn was activated in OSCC patient tumors, compared with matched normal oral tissue. After intraplantar, facial or lingual injection, Lgmn evoked nociception in wild-type (WT) female mice but not in female mice lacking PAR2in NaV1.8-positive neurons (Par2Nav1.8), nor in female mice treated with a Lgmn inhibitor, LI-1. Inoculation of an OSCC cell line caused mechanical and thermal hyperalgesia that was reversed by LI-1.Par2Nav1.8andLgmndeletion attenuated mechanical allodynia in female mice with carcinogen-induced OSCC. Lgmn caused PAR2-dependent hyperexcitability of trigeminal neurons from WT female mice.Par2deletion, LI-1, and inhibitors of adenylyl cyclase or protein kinase A (PKA) prevented the effects of Lgmn. Under acidified conditions, Lgmn cleaved within the extracellular N terminus of PAR2at Asn30↓Arg31, proximal to the canonical trypsin activation site. Lgmn activated PAR2by biased mechanisms in HEK293 cells to induce Ca2+mobilization, cAMP formation, and PKA/protein kinase D (PKD) activation, but not β-arrestin recruitment or PAR2endocytosis. Thus, in the acidified OSCC microenvironment, Lgmn activates PAR2by biased mechanisms that evoke cancer pain.SIGNIFICANCE STATEMENTOral squamous cell carcinoma (OSCC) is one of the most painful cancers. We report that legumain (Lgmn), which exhibits maximal activity in acidic environments, cleaves protease-activated receptor-2 (PAR2) on neurons to produce OSCC pain. Active Lgmn was elevated in OSCC patient tumors, compared with matched normal oral tissue. Lgmn evokes pain-like behavior through PAR2. Exposure of pain-sensing neurons to Lgmn decreased the current required to generate an action potential through PAR2. Inhibitors of adenylyl cyclase and protein kinase A (PKA) prevented the effects of Lgmn. Lgmn activated PAR2to induce calcium mobilization, cAMP formation, and activation of protein kinase D (PKD) and PKA, but not β-arrestin recruitment or PAR2endocytosis. Thus, Lgmn is a biased agonist of PAR2that evokes cancer pain.

The generalized Langevin equation (GLE) is a stochastic integro-differential equation that has been used to describe the velocity of microparticles in viscoelastic fluids. In this work, we consider the large-time asymptotic properties of a Markovian approximation to the GLE in the presence of a wide class of external potential wells. The qualitative behavior of the GLE is largely determined by its memory kernel K, which summarizes the delayed response of the fluid medium on the particles past movement. When K can be expressed as a finite sum of exponentials, it has been shown that long-term time-averaged properties of the position and velocity do not depend on K at all. In certain applications, however, it is important to consider the GLE with a power law memory kernel. Using the fact that infinite sums of exponentials can have power law tails, we study the infinite-dimensional version of the Markovian GLE in a potential well. In the case where the memory kernel K is integrable (i.e. in the asymptotically diffusive regime), we are able to extend previous results and show that there is a unique stationary distribution for the GLE system and that the long-term statistics of the position and velocity do not depend on K. However, when K is not integrable (i.e. in the asymptotically subdiffusive regime), we are able to show the existence of an invariant probability measure but uniqueness remains an open question. In particular, the method of asymptotic coupling used in the integrable case to show uniqueness does not apply when K fails to be integrable.

In light of recent work on particles fluctuating in linear viscoelastic fluids, we study a linear stochastic partial-integro-differential equation with memory that is driven by a stationary noise on a bounded, smooth domain. Using the framework of generalized stationary solutions introduced in McKinley and Nguyen (SIAM J Math Anal 50(5):5119–5160, 2018), we provide conditions on the differential operator and the noise to obtain the existence as well as Hölder regularity of the stationary solutions for the concerned equation. As an application of the regularity results, we compare to analogous classical results for the stochastic heat equation. When the 1d stochastic heat equation is driven by white noise, solutions are continuous with space and time regularity that is Hölder$$(1/2-\epsilon )$$(1/2-ϵ)and$$(1/4-\epsilon )$$(1/4-ϵ)respectively. When driven by colored-in-space noise, solutions can have a range of regularity properties depending on the structure of the noise. Here, we show that the particular form of colored-in-time memory that arises in viscoelastic diffusion applications, satisfying what is called the Fluctuation–Dissipation relationship, yields sample paths that are Hölder$$(1/2-\epsilon )$$(1/2-ϵ)and$$(1/2-\epsilon )$$(1/2-ϵ)in space and time.

We consider a class of semi-linear differential Volterra equations with memory terms, polynomial nonlinearities and random perturbation. For a broad class of nonlinearities, we study statistically steady states of the system and find that they possess regularities compatible with those of the weak solutions. Moreover, if sufficiently many directions in the phase space are stochastically forced, we employ the \emph{generalized coupling} approach to establish the existence and uniqueness of the invariant probability measure to which the system is exponentially attractive. This extends ergodicity results previously established in [Bonaccorsi et al., SIAM J. Math. Anal., 44 (2012)].

We study the long time statistics of a class of semi--linear wave equations modeling the motions of a particle suspended in continuous media while being subjected to random perturbations via an additive Gaussian noise. By comparison with the nonlinear reaction settings, of which the solutions are known to possess geometric ergodicity, we find that, under the impact of nonlinear dissipative damping, the mixing rate is at least polynomial of any order. This relies on a combination of Lyapunov conditions, the contracting property of the Markov transition semigroup as well as the notion of $d$--small sets.

This paper discusses the physical dynamics of the use of the Active Flow Control (AFC) actuators embedded in a Vertical Take-Off and Landing (VTOL) aircraft. Results of High-Fidelity numerical simulations are examined at near stall conditions. Different approaches of AFC are proposed to suppress the flow separation at these conditions. First the flow around the VTOL aircraft at high angle of attack in the take-off and landing configurations in real flight conditions at high Reynolds number are examined, then different flow control strategies are investigated. It was found that at these flow condition a flow separation travels along the spanwise direction in the near trailing-edge region of the wing with additional corner vortices between the wing-nacelle and the wing-fuselage junctions. Zero Net Mass Flux (ZNMF) actuators, also called synthetic jets, were then used for Active Flow Control. It was found that these ZNMF devices, when operating at the optimal blowing velocity and activation frequency, and when placed at the correct location enable the flow to re-attach and to delay the flow separation, resulting in an increase in aerodynamic efficiency of the aircraft. This work presented in this paper has been carried out in the context of the European project CleanSky2 Active Flow Control for TiltRotor aircraft (AFC4TR), Grant Agreement 886718.

This paper attempts to model both static and dynamic dependence structures and measure impacts of energy consumptions (both renewable (EC) and non-renewable (REN) energies), economic globalization (GLO), and economic growth (GDP) on carbon dioxide (CO

π-stacked organic electronic materials are tunable light absorbers with many potential applications in optoelectronics. The optical properties of such molecules are highly dependent on the nature and energy of electron-hole pairs or excitons formed upon light absorption, which in turn are determined by intra- and intermolecular electronic and vibrational excitations. Here, we present a first-principles approach for describing the optical spectrum of stacked organic molecules with strong vibronic coupling. For stacked perylene tetracarboxylic acid diimides, we describe optical excitations by using the time-dependent density functional theory with a Franck-Condon Herzberg-Teller approximation of vibronic effects and validate our approach with comparison to experimental ultraviolet-visible (UV-vis) absorption measurements of solvated model systems. We determine that for larger macromolecules, unlike for single molecules, the sampling of the ground-state potential energy surface significantly influences the optical absorption spectrum. We account for this effect by applying our analysis to ∼100 structures extracted from equilibrated molecular dynamics simulations and averaging the optical spectrum over the entire ensemble. Additionally, we demonstrate that intermolecular electronic coupling within the stacks results in multiple low-energy electronically excited states that all contribute to the optical spectrum. This study provides a computationally feasible recipe for describing the spectroscopic properties of stacked organic chromophores via first-principles density functional theory.

The generalized Langevin equation (GLE) is a universal model for particle velocity in a viscoelastic medium. In this paper, we consider the GLE family with fractional memory kernels. We show that, in the critical regime where the memory kernel decays like $1/t$ for large $t$, the mean squared displacement (MSD) of particle motion grows linearly in time up to a slowly varying (logarithm) term. Moreover, we establish the well-posedness of the GLE in this regime. This solves an open question from [Mckinley 2018 Anomalous] and completes the answer to the conjecture put forward in [Morgado 2002 Relation] on the relationship between memory kernel decay and anomalously diffusive behavior. Under slightly stronger assumptions on the memory kernel, we construct an Abelian-Tauberian framework that leads to robust bounds on the deviation of the MSD around its asymptotic trend. This bridges the gap between the GLE memory kernel and the spectral density of anomalously diffusive particle motion characterized in [Didier 2017 Asymptotic].

Power injection uncertainties in distribution power grids, which are mostly induced by aggressive introduction of intermittent renewable sources, may drive the system away from normal operating regimes and potentially lead to the loss of long-term voltage stability (LTVS). Naturally, there is an ever increasing need for a tool for assessing the LTVS of a distribution system. This paper presents a fast and reliable tool for constructing inner approximations of LTVS regions in multidimensional injection space such that every point in our constructed region is guaranteed to be solvable. Numerical simulations demonstrate that our approach outperforms all existing inner approximation methods in most cases. Furthermore, the constructed regions are shown to cover substantial fractions of the true voltage stability region. This paper will later discuss a number of important applications of the proposed technique, including fast screening for viable injection changes, constructing an effective solvability index and rigorously certified loadability limits.

Perylene-3,4,9,10-tetracarboxylic diimides (PTCDIs) have been extensively studied for organic electronics applications. Additionally, PTCDI-based supramolecular architectures have been used as platforms for the investigation of various charge transfer/transport phenomena. For these systems, the study of their structural characteristics and self-assembly behavior with molecular dynamics simulations has remained relatively limited. Herein, we describe a detailed molecular dynamics investigation of the intramolecular self-assembly of DNA-inspired columnar macromolecules, which consist of multiple hexaethyleneglycol-substituted PTCDIs that are covalently appended to a phosphoalkane backbone. By evaluating relevant geometric and energetic parameters obtained from our simulations, we determine the factors underpinning the dynamics of PTCDI stacking for our constructs. Our findings may shed insight into the structure of biomimetic one-dimensional molecular wires from PTCDIs and other related materials.

Carbon nanotube (CNT) is prepared by chemical vapor deposition method and their electrochemical behaviors for instance oxygen evolution (OER) and hydrogen evolution (HER) reaction have been successfully studied. In recent times, Pt-free electrocatalysts have been greatly attractive in electrochemical hydrogen evolution reactions for the replacement of fossil fuels and development of sustainable energy carriers. Chemical vapor deposition method was used as an efficient way to synthesize CNTs directly. The as prepared free-standing and multifunctional CNT electrodes are used for overall water splitting applications. In this work, we have designed CNT as electrode material as well as current collector using Ni-foil and Ni-foam substrate and their fundamental characterizations confirm the structural, morphological behaviors of CNTs. Moreover, the well-ordered growth of CNT was obtained in Ni-foam CNTs 1 and 2, whereas in the Ni foil CNTs 1 and 2 less growth of CNT and amorphous carbon sponge was exceeded, which was further confirmed by the SEM images. The achieved electrochemical HER results displayed that the Ni-foam-CNT-2 exhibited lower overpotential, smallest Tafel slope and lower resistance value of 110 mV, 240 mV/dec and 0.24 Ω respectively. Moreover, Ni-foam-CNT-2 revealed excellent stability with 86.6 % retention over 20 h. Hence, it is one of the cost-effective and reliable materials for electrochemical hydrogen evolution reaction. This work was supported by UGC-SAP, DST-FIST, DST-PURSE, MHRD-RUSA grants.

Two new polyisoprenylated benzophenones, planchoniones A (

This paper presents a novel optimal energy storage siting and sizing approach that enables a networked microgrid community in active distribution systems. The siting and sizing problem is formulated using probabilistic self-sufficiency constraint (PSSC) based on voltage controllability concepts. The location and number of energy storage needed are derived via voltage control capacity, leveraging a subspace-wise linear voltage-power relationship developed using the Gaussian Process Regression. We propose a sitting-sizing feedback mechanism by combining different voltage control ideas and PSSC to enhance the optimal storage placement over iterations. The simulation results on an NMG community show the effectiveness of PSSC against robust sizing and the importance of the proposed feedback mechanism, which incorporates the changes in flow pattern due to storage placement.

Simple Summary Oral cancer is often deadly and severely painful. Because this form of cancer pain cannot be adequately treated with current medications including opiates, new treatment approaches are needed. Cathepsin S, a lysosomal cysteine protease may play a role in oral cancer pain through a protease-activated receptor-2 (PAR2)-dependent mechanism. We undertook a series of experiments to define the role of cathepsin S in oral cancer pain. We compared cathepsin S activity in human oral cancer tumors versus patient-matched normal tissue; a human oral cancer cell line versus a benign dysplastic oral keratinocyte cell line; and in an orthotopic xenograft tongue cancer mouse model versus normal controls in mice. We localized cathepsin S in macrophages and carcinoma cells in human oral cancers. The injection of cathepsin S caused nociception in a mouse model while the injection of oral cancer cells in which the gene for cathepsin S is deleted generated less nociception. Our findings will lay the foundations for clinical trials of cathepsin S inhibitors for treating oral cancer pain. Abstract Oral squamous cell carcinoma (SCC) pain is more prevalent and severe than pain generated by any other form of cancer. We previously showed that protease-activated receptor-2 (PAR2) contributes to oral SCC pain. Cathepsin S is a lysosomal cysteine protease released during injury and disease that can activate PAR2. We report here a role for cathepsin S in PAR2-dependent cancer pain. We report that cathepsin S was more active in human oral SCC than matched normal tissue, and in an orthotopic xenograft tongue cancer model than normal tongue. The multiplex immunolocalization of cathepsin S in human oral cancers suggests that carcinoma and macrophages generate cathepsin S in the oral cancer microenvironment. After cheek or paw injection, cathepsin S evoked nociception in wild-type mice but not in mice lacking PAR2 in Nav1.8-positive neurons (Par2Nav1.8), nor in mice treated with LY3000328 or an endogenous cathepsin S inhibitor (cystatin C). The human oral SCC cell line (HSC-3) with homozygous deletion of the gene for cathepsin S (CTSS) with CRISPR/Cas9 provoked significantly less mechanical allodynia and thermal hyperalgesia, as did those treated with LY3000328, compared to the control cancer mice. Our results indicate that cathepsin S is activated in oral SCC, and that cathepsin S contributes to cancer pain through PAR2 on neurons.