Citizen Relationship Management (CRM) based on information and communication technology offers immediate and efficient response to citizens' needs, and when citizens use the CRM services and in turn ...have positive service experience via the use of the CRM services, their perceived assessment to public service quality and performance can be improved. This study draws on data from the citizen survey of the City and County of San Francisco to test the relationship between citizens use 311 system to contact with the City Hall and citizen satisfaction with the quality of public service encounter. The finding indicates that citizens who use 311 system are more satisfied with the courtesy and professionalism of public officials than citizens who do not. However, the question-response capacity of public officials has opposite result. Citizens who use 311 system are problem-solved orientated and have high expectation of how well their questions are responded and be resolved by public officials.
DNAM-1 (CD226) is an activating receptor expressed on natural killer (NK) cells, CD8(+) T cells, and other immune cells. Upon recognition of its ligands, CD155 and CD112, DNAM-1 promotes NK ...cell-mediated elimination of transformed and virus-infected cells. It also has a key role in expansion and maintenance of virus-specific memory NK cells. Herein, the mechanism by which DNAM-1 controls NK cell-mediated cytotoxicity and cytokine production was elucidated. Cytotoxicity and cytokine production triggered by DNAM-1 were mediated via a conserved tyrosine- and asparagine-based motif in the cytoplasmic domain of DNAM-1. Upon phosphorylation by Src kinases, this motif enabled binding of DNAM-1 to adaptor Grb2, leading to activation of enzymes Vav-1, phosphatidylinositol 3' kinase, and phospholipase C-γ1. It also promoted activation of kinases Erk and Akt, and calcium fluxes. Although, as reported, DNAM-1 promoted adhesion, this function was signal-independent and insufficient to promote cytotoxicity. DNAM-1 signaling was also required to enhance cytotoxicity, by increasing actin polymerization and granule polarization. We propose that DNAM-1 promotes NK cell activation via an immunoreceptor tyrosine tail (ITT)-like motif coupling DNAM-1 to Grb2 and other downstream effectors.
The development of intrinsically stretchable n-type polymer semiconductors is highly desirable for various wearable and implantable electronics. However, very few studies have reported ...high-performance stretchable n-type conjugated polymers by molecular engineering. Herein, high electron mobility preservation under high stretch-strains is achieved by changing the type of grafted side chains as well as increasing the density of grafted side chains. A series of bis(2-oxoindolin-3-ylidene)-benzodifuran-dione (BIBDF)-based conjugated polymers with different side chains including alkyl chains and hybrid siloxane-based chains was synthesized to investigate the structure–property relationship. The experimental results demonstrated that replacing branched alkyl side chains with linear hybrid siloxane-based side chains and increasing the density of side chains greatly reduced the crystallinity of films and improved the flexibility of polymer chains. The resulting polymer CSi-PBIBDF showed significantly enhanced mechanical properties while maintaining high electron transport properties. Surprisingly, the electron mobility parallel to the stretching direction for the CSi-PBIBDF thin film reached 0.21 cm2 V–1 s–1 at 100% strain, which is higher than that of the unstretched state, attributed to the stretch-induced alignment of the polymer chain. The current study demonstrated that systematic side chain engineering is extremely important to achieve high-performance stretchable n-type polymer semiconductors.
This paper investigates the role of quadrature exactness in the approximation scheme of hyperinterpolation. Constructing a hyperinterpolant of degree
n
requires a positive-weight quadrature rule with ...exactness degree 2
n
. We examine the behavior of such approximation when the required exactness degree 2
n
is relaxed to
n
+
k
with
0
<
k
≤
n
. Aided by the Marcinkiewicz–Zygmund inequality, we affirm that the
L
2
norm of the exactness-relaxing hyperinterpolation operator is bounded by a constant independent of
n
, and this approximation scheme is convergent as
n
→
∞
if
k
is positively correlated to
n
. Thus, the family of candidate quadrature rules for constructing hyperinterpolants can be significantly enriched, and the number of quadrature points can be considerably reduced. As a potential cost, this relaxation may slow the convergence rate of hyperinterpolation in terms of the reduced degrees of quadrature exactness. Our theoretical results are asserted by numerical experiments on three of the best-known quadrature rules: the Gauss quadrature, the Clenshaw–Curtis quadrature, and the spherical
t
-designs.
A
bstract
The chase of universal bounds on diffusivities in strongly coupled systems and holographic models has a long track record. The identification of a universal velocity scale, independent of ...the presence of well-defined quasiparticle excitations, is one of the major challenges of this program. A recent analysis, valid for emergent IR fixed points exhibiting local quantum criticality, and dual to IR AdS
2
geometries, suggests to identify such a velocity using the time and length scales at which hydrodynamics breaks down — the equilibration velocity. The latter relates to the radius of convergence of the hydrodynamic expansion and it is extracted from a collision between a hydrodynamic diffusive mode and a non-hydrodynamic mode associated to the IR AdS
2
region. In this short note, we confirm this picture for holographic systems displaying the spontaneous breaking of translational invariance. Moreover, we find that, at zero temperature, the lower bound set by quantum chaos and the upper one defined by causality and hydrodynamics exactly coincide, determining uniquely the diffusion constant. Finally, we comment on the meaning and universality of this newly proposed prescription.
With a pace of about twice the observed rate of global warming, the temperature on the Qinghai‐Tibetan Plateau (Earth's ‘third pole’) has increased by 0.2 °C per decade over the past 50 years, which ...results in significant permafrost thawing and glacier retreat. Our review suggested that warming enhanced net primary production and soil respiration, decreased methane (CH4) emissions from wetlands and increased CH4 consumption of meadows, but might increase CH4 emissions from lakes. Warming‐induced permafrost thawing and glaciers melting would also result in substantial emission of old carbon dioxide (CO2) and CH4. Nitrous oxide (N2O) emission was not stimulated by warming itself, but might be slightly enhanced by wetting. However, there are many uncertainties in such biogeochemical cycles under climate change. Human activities (e.g. grazing, land cover changes) further modified the biogeochemical cycles and amplified such uncertainties on the plateau. If the projected warming and wetting continues, the future biogeochemical cycles will be more complicated. So facing research in this field is an ongoing challenge of integrating field observations with process‐based ecosystem models to predict the impacts of future climate change and human activities at various temporal and spatial scales. To reduce the uncertainties and to improve the precision of the predictions of the impacts of climate change and human activities on biogeochemical cycles, efforts should focus on conducting more field observation studies, integrating data within improved models, and developing new knowledge about coupling among carbon, nitrogen, and phosphorus biogeochemical cycles as well as about the role of microbes in these cycles.
In this paper, we test the weak cosmic censorship conjecture (WCCC) for n≥4 dimensional nearly extremal RN-AdS black holes with non-trivial topologies, namely plane and hyperbola, using the new ...version of gedanken experiment proposed by Sorce and Wald. Provided that the non-electromagnetic part of the stress tensor of matter fields satisfies the null energy condition and the linear stability condition holds, we find that the black holes cannot be overcharged under the second-order perturbation approximation, which includes the self-force and finite-size effects. As a result, we conclude that the violation of Hubeny type never occurs and the WCCC holds for the topological RN-AdS black hole.
Artificial intelligence is widely applied to automate Diabetic retinopathy diagnosis. Diabetes-related retinal vascular disease is one of the world’s most common leading causes of blindness and ...vision impairment. Therefore, automated DR detection systems would greatly benefit the early screening and treatment of DR and prevent vision loss caused by it. Researchers have proposed several systems to detect abnormalities in retinal images in the past few years. However, Diabetic Retinopathy automatic detection methods have traditionally been based on hand-crafted feature extraction from the retinal images and using a classifier to obtain the final classification. DNN (Deep neural networks) have made several changes in the previous few years to assist overcome the problem mentioned above. We suggested a two-stage novel approach for automated DR classification in this research. Due to the low fraction of positive instances in the asymmetric Optic Disk (OD) and blood vessels (BV) detection system, preprocessing and data augmentation techniques are used to enhance the image quality and quantity. The first step uses two independent U-Net models for OD (optic disc) and BV (blood vessel) segmentation. In the second stage, the symmetric hybrid CNN-SVD model was created after preprocessing to extract and choose the most discriminant features following OD and BV extraction using Inception-V3 based on transfer learning, and detects DR by recognizing retinal biomarkers such as MA (microaneurysms), HM (hemorrhages), and exudates (EX). On EyePACS-1, Messidor-2, and DIARETDB0, the proposed methodology demonstrated state-of-the-art performance, with an average accuracy of 97.92%, 94.59%, and 93.52%, respectively. Extensive testing and comparisons with baseline approaches indicate the efficacy of the suggested methodology.
Seismic data denoising is an important mean to extract useful information from seismic data, remove interference, and improve the SNR(signal-to-noise ratio) of seismic data. Therefore, the research ...on denoising methods of seismic data has always been a hot topic. At present, most convolutional neural networks for desert seismic data denoising use single scale convolutional kernels to extract feature information, which is prone to cause missing details. Therefore, we propose the Multi-scale Dilated Convolution Network (MDCN) to remove desert seismic noise. Dilational convolution operators of different sizes are used to autocratically extract features of different scales from seismic data. The extracted features are then connected in series and fused into multi-scale information used for denoising. Moreover, using dilated convolutions can increase the receptive field, so that the output of each convolution would contain a larger range of information than single scale convolutional neural networks, which means they have access to a larger window and as a result can use temporal information. In order to increase the receiving range of the network and obtain more context information, we cascade multiple modules to form a deep network. In this way, we can extract as much detailed information as possible from the desert seismic data. The results of the experiment show that our method effectively suppresses the desert noise and also better retains the effective signal.
•The model can effectively remove noise in desert seismic records, recover the seismic events and enhance their continuity.•Combine multi-scale ideas with neural networks to extract and learn more abundant information.•The use of dilated convolutions is conducive to capture as much feature information from the noisy records.
A design method of low-dimensional disturbance rejection fuzzy control (DRFC) via multiple observers is proposed for a class of nonlinear parabolic partial differential equation (PDE) systems, where ...the disturbance is modeled by an exosystem of ordinary differential equations (ODEs) and enters into the PDE system through the control channel. In the proposed scheme, the modal decomposition technique is initially applied to the PDE system to derive a slow subsystem of low-dimensional nonlinear ODEs, which accurately captures the dominant dynamics of the PDE system. The resulting nonlinear slow subsystem is subsequently represented by a Takagi-Sugeno (T-S) fuzzy model. From the T-S fuzzy model and the exosystem, a fuzzy slow mode observer and a fuzzy disturbance observer are constructed to estimate the slow mode and the disturbance, respectively. Furthermore, a nonlinear observation spillover observer is proposed to compensate the effect of observation spillover. Then, based on these observers, a low-dimensional DRFC design is developed in terms of linear matrix inequalities to guarantee the exponential stability of the closed-loop PDE system in the presence of the disturbance. Finally, the effectiveness of the proposed design method is demonstrated on the control of one-dimensional Burgers-KPP-Fisher diffusion-reaction system and the temperature profile of a catalytic rod.
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